onnxruntime/docs/OperatorKernels.md at 4ffd022b0b1a62880d2498679f360878fdbbd796

mirror of https://github.com/saymrwulf/onnxruntime.git synced 2026-05-27 22:45:57 +00:00

kunal-vaishnavi 2a17d5cf32

### Description
This PR contains fusion-level and kernel-level optimizations for [Meta's
LLaMA-2](https://blogs.microsoft.com/blog/2023/07/18/microsoft-and-meta-expand-their-ai-partnership-with-llama-2-on-azure-and-windows/).

Some of the added optimizations include:

- SimplifiedLayerNorm changes
  - Fusions for multiple variants
- SkipSimplifiedLayerNorm changes
  - Kernel support for CPU
- Rotary embeddings (previously did not exist)
  - Fusions for multiple variants
  - CPU and CUDA kernels
  - Supports interleaving and non-interleaving in the same kernels
  - Optimized cache that requires half of its originally exported sizes
- Reduced from `(max_sequence_length, head_size)` to
`(max_sequence_length, head_size / 2)`
- Multi-head attention
  - Support for 2D and 3D attention masks
- Group query attention (for FP16 CUDA and INT4 CUDA)
  - Integration with flash attention v2 and past-present buffer sharing
- Removes need for `attention_mask` input as it is supported in the
kernel
- 4 bit quantization
  - `block_size` parameter is available for customizing
- Support the new changes for [Microsoft
version](https://github.com/microsoft/Llama-2-Onnx)
- Support combinations of the below variants (ex: export ORT version and
run with Optimum)

Supported variants of LLaMA-2 include:
- [ORT
version](https://github.com/microsoft/onnxruntime/tree/main/onnxruntime/python/tools/transformers/models/llama)
- Produces one ONNX file that is already optimized (and quantized if
requested)
  - Integrates with Optimum
- [Another Microsoft version](https://github.com/microsoft/Llama-2-Onnx)
  - Already exported and available off-the-shelf
  - Faster versions of those models will be uploaded there soon
- [Hugging Face version](https://huggingface.co/meta-llama)
  - Models that end with `-hf`
- Some older and current versions of
[`transformers`](https://github.com/huggingface/transformers) and
[`optimum`](https://github.com/huggingface/optimum) that export the
model to ONNX differently
- Note that while some older versions are supported, it is recommended
to use the latest package versions.

### Usage

To use the optimizations, please see `README.md` for details. Please
note the various `requirements.txt` files for the package versions
recommended in order to use these changes.

To run the ORT transformer optimizer separately, run the script as
follows:
```
$ cd onnxruntime/onnxruntime/python/tools/transformers/
$ python3 optimizer.py --input <filename>.onnx --output <filename>.onnx --model_type gpt2 --num_heads <number of attention heads> --hidden_size <attention hidden size> --use_external_data_format --opt_level 0
```

### Motivation and Context
This PR helps the following issues:
- https://github.com/microsoft/onnxruntime/issues/14997
- https://github.com/microsoft/onnxruntime/issues/16254
- https://github.com/microsoft/onnxruntime/issues/17681
- https://github.com/microsoft/onnxruntime/issues/17925
- https://github.com/microsoft/onnxruntime-inference-examples/issues/320

This PR uses changes from the following PRs:
- https://github.com/pytorch/pytorch/pull/104468
- https://github.com/pytorch/pytorch/pull/109759
- https://github.com/microsoft/onnxruntime/pull/17020
- https://github.com/microsoft/onnxruntime/pull/17674
- https://github.com/microsoft/onnxruntime/pull/17890
- https://github.com/microsoft/onnxruntime/pull/17920
- https://github.com/huggingface/transformers/pull/26162
- https://github.com/huggingface/optimum/pull/1257
- https://github.com/huggingface/optimum/pull/1289
- https://github.com/huggingface/optimum/pull/1462

### New TorchDynamo Exporter (experimental stage)

This PR uses changes from the following issues and PRs to begin
supporting the [new TorchDynamo
exporter](https://pytorch.org/docs/stable/onnx.html#torchdynamo-based-onnx-exporter):
- https://github.com/huggingface/transformers/pull/26307
- https://github.com/pytorch/pytorch/issues/104903
- https://github.com/pytorch/pytorch/pull/105040
- https://github.com/microsoft/onnxscript/pull/847
- https://github.com/microsoft/onnxscript/pull/862
- https://github.com/microsoft/onnxscript/issues/493

2023-10-23 13:00:56 -07:00

232 KiB

Raw Blame History

Supported Operators and Data Types

This file is automatically generated from the registered kernels by this script. Do not modify directly.

Operators implemented by CPUExecutionProvider

Op Name	Parameters	OpSet Version	Types Supported
Operator Domain: ai.onnx
Abs	in X:T out Y:T	13+	T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[6, 12]	T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Acos	in input:T out output:T	7+	T = tensor(float)
Acosh	in input:T out output:T	9+	T = tensor(float)
Add	in A:T in B:T out C:T	14+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		13	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[7, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Affine	in X:T out Y:T	1+	T = tensor(float)
And	in A:T in B:T out C:T1	7+	T = tensor(bool) T1 = tensor(bool)
ArgMax	in data:T out reduced:tensor(int64)	13+	T = tensor(double), tensor(float), tensor(int32), tensor(int8), tensor(uint8)
		[11, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int8), tensor(uint8)
		[1, 10]	T = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
ArgMin	in data:T out reduced:tensor(int64)	13+	T = tensor(double), tensor(float), tensor(int32)
		[11, 12]	T = tensor(double), tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
Asin	in input:T out output:T	7+	T = tensor(float)
Asinh	in input:T out output:T	9+	T = tensor(float)
Atan	in input:T out output:T	7+	T = tensor(float)
Atanh	in input:T out output:T	9+	T = tensor(float)
AveragePool	in X:T out Y:T	19+	T = tensor(float)
		[11, 18]	T = tensor(float)
		10	T = tensor(float)
		[7, 9]	T = tensor(float)
BatchNormalization	in X:T in scale:T in B:T in input_mean:U in input_var:U out Y:T out running_mean:U out running_var:U or in X:T in scale:T in B:T in mean:T in var:T out Y:T out mean:T out var:T out saved_mean:T out saved_var:T or in X:T in scale:T1 in B:T1 in input_mean:T2 in input_var:T2 out Y:T out running_mean:T2 out running_var:T2	15+	T = tensor(double), tensor(float) T1 = tensor(double), tensor(float) T2 = tensor(double), tensor(float)
		14	T = tensor(double), tensor(float) U = tensor(double), tensor(float)
		[9, 13]	T = tensor(double), tensor(float)
		[7, 8]	T = tensor(double), tensor(float)
BitShift	in X:T in Y:T out Z:T	11+	T = tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseAnd	in A:T in B:T out C:T	18+	T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseNot	in X:T out Y:T	18+	T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseOr	in A:T in B:T out C:T	18+	T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseXor	in A:T in B:T out C:T	18+	T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BlackmanWindow	in size:T1 out output:T2	17+	T1 = tensor(int32), tensor(int64) T2 = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Cast	in input:T1 out output:T2	19+	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 18]	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[6, 12]	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Ceil	in X:T out Y:T	13+	T = tensor(double), tensor(float)
		[6, 12]	T = tensor(double), tensor(float)
Celu	in X:T out Y:T	12+	T = tensor(float)
Clip	in input:T in min:T in max:T out output:T or in input:T out output:T	13+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
		12	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
		11	T = tensor(float)
		[6, 10]	T = tensor(float)
Col2Im	in input:T in image_shape:tensor(int64) in block_shape:tensor(int64) out output:T	18+	T = tensor(float)
Compress	in input:T in condition:T1 out output:T	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
Concat	in inputs:T out concat_result:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[4, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ConcatFromSequence	in input_sequence:S out concat_result:T	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
ConstantOfShape	in input:T1 out output:T2	20+	T1 = tensor(int64) T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 19]	T1 = tensor(int64) T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Conv	in X:T in W:T in B:T out Y:T	11+	T = tensor(float)
		[1, 10]	T = tensor(float)
ConvInteger	in x:T1 in w:T2 in x_zero_point:T1 in w_zero_point:T2 out y:T3	10+	T1 = tensor(uint8) T2 = tensor(uint8) T3 = tensor(int32)
ConvTranspose	in X:T in W:T in B:T out Y:T	11+	T = tensor(float)
		[1, 10]	T = tensor(float)
Cos	in input:T out output:T	7+	T = tensor(float)
Cosh	in input:T out output:T	9+	T = tensor(float)
Crop	in input:T out output:T	1+	T = tensor(float)
CumSum	in x:T in axis:T2 out y:T	14+	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T2 = tensor(int32), tensor(int64)
		[11, 13]	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T2 = tensor(int32), tensor(int64)
DFT	in input:T1 in dft_length:T2 in axis:tensor(int64) out output:T1 or in input:T1 in dft_length:T2 out output:T1	17+	T1 = tensor(double), tensor(float) T2 = tensor(int32), tensor(int64)
DepthToSpace	in input:T out output:T	13+	T = tensor(double), tensor(float)
		[11, 12]	T = tensor(double), tensor(float)
		[1, 10]	T = tensor(double), tensor(float)
DequantizeLinear	in x:T in x_scale:tensor(float) in x_zero_point:T out y:tensor(float) or in x:T1 in x_scale:T2 in x_zero_point:T1 out y:T2	19+	T1 = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int32), tensor(int8), tensor(uint8) T2 = tensor(float), tensor(float16)
		[13, 18]	T = tensor(int32), tensor(int8), tensor(uint8)
		[10, 12]	T = tensor(int32), tensor(int8), tensor(uint8)
Det	in X:T out Y:T	11+	T = tensor(float)
Div	in A:T in B:T out C:T	14+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		13	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[7, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Dropout	in data:T in ratio:T1 in training_mode:T2 out output:T out mask:T2 or in data:T out output:T out mask:T or in data:T out output:T out mask:T1	13+	T = tensor(double), tensor(float) T1 = tensor(double), tensor(float) T2 = tensor(bool)
		12	T = tensor(double), tensor(float) T1 = tensor(double), tensor(float) T2 = tensor(bool)
		[10, 11]	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(bool)
		[7, 9]	T = tensor(double), tensor(float), tensor(float16)
DynamicQuantizeLinear	in x:T1 out y:T2 out y_scale:tensor(float) out y_zero_point:T2	11+	T2 = tensor(uint8)
DynamicSlice	in data:T in starts:Tind in ends:Tind in axes:Tind out output:T	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
Einsum	in Inputs:T out Output:T	12+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Elu	in X:T out Y:T	6+	T = tensor(float)
Equal	in A:T in B:T out C:T1	19+	T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string) T1 = tensor(bool)
		[13, 18]	T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
		[11, 12]	T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
		[7, 10]	T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
Erf	in input:T out output:T	13+	T = tensor(float)
		[9, 12]	T = tensor(float)
Exp	in input:T out output:T	13+	T = tensor(double), tensor(float)
		[6, 12]	T = tensor(double), tensor(float)
Expand	in input:T in shape:tensor(int64) out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[8, 12]	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
EyeLike	in input:T1 out output:T2	9+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64) T2 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)
Flatten	in input:T out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 8]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Floor	in X:T out Y:T	13+	T = tensor(double), tensor(float)
		[6, 12]	T = tensor(double), tensor(float)
GRU	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T out Y:T out Y_h:T	14+	T = tensor(double), tensor(float) T1 = tensor(int32)
		[7, 13]	T = tensor(double), tensor(float) T1 = tensor(int32)
Gather	in data:T in indices:Tind out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
GatherElements	in data:T in indices:Tind out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
GatherND	in data:T in indices:tensor(int64) out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) indices = tensor(int64)
		12	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) indices = tensor(int64)
		11	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) indices = tensor(int64)
Gemm	in A:T in B:T in C:T out Y:T	13+	T = tensor(double), tensor(float)
		[11, 12]	T = tensor(double), tensor(float)
		[9, 10]	T = tensor(double), tensor(float)
		[7, 8]	T = tensor(double), tensor(float)
GlobalAveragePool	in X:T out Y:T	1+	T = tensor(float)
GlobalLpPool	in X:T out Y:T	2+	T = tensor(float)
GlobalMaxPool	in X:T out Y:T	1+	T = tensor(float)
Greater	in A:T in B:T out C:T1	13+	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
		[9, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
		[7, 8]	T = tensor(double), tensor(float) T1 = tensor(bool)
GreaterOrEqual	in A:T in B:T out C:T1	16+	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
		[12, 15]	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
GridSample	in X:T1 in grid:T2 out Y:T1	16+	T1 = tensor(float) T2 = tensor(float)
HammingWindow	in size:T1 out output:T2	17+	T1 = tensor(int32), tensor(int64) T2 = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
HannWindow	in size:T1 out output:T2	17+	T1 = tensor(int32), tensor(int64) T2 = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
HardSigmoid	in X:T out Y:T	6+	T = tensor(float)
Hardmax	in input:T out output:T	13+	T = tensor(float)
		[11, 12]	T = tensor(float)
		[1, 10]	T = tensor(float)
Identity	in input:T out output:T or in input:V out output:V	19+	V = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[16, 18]	V = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[14, 15]	V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
If	in cond:B out outputs:V	19+	B = tensor(bool) V = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[16, 18]	B = tensor(bool) V = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 15]	B = tensor(bool) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	B = tensor(bool) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	B = tensor(bool) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ImageScaler	in input:T out output:T	1+	T = tensor(float)
InstanceNormalization	in input:T in scale:T in B:T out output:T	6+	T = tensor(float)
IsInf	in X:T1 out Y:T2	10+	T1 = tensor(double), tensor(float) T2 = tensor(bool)
IsNaN	in X:T1 out Y:T2	13+	T1 = tensor(double), tensor(float), tensor(float16) T2 = tensor(bool)
		[9, 12]	T1 = tensor(double), tensor(float), tensor(float16) T2 = tensor(bool)
LRN	in X:T out Y:T	13+	T = tensor(float)
		[1, 12]	T = tensor(float)
LSTM	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T in initial_c:T in P:T out Y:T out Y_h:T out Y_c:T	14+	T = tensor(double), tensor(float) T1 = tensor(int32)
		[7, 13]	T = tensor(double), tensor(float) T1 = tensor(int32)
LayerNormalization	in X:T in Scale:T in B:T out Y:T out Mean:U out InvStdDev:U or in X:T in Scale:V in B:V out Y:V out Mean:U out InvStdDev:U	17+	T = tensor(double), tensor(float) U = tensor(float)
		[1, 16]	T = tensor(double), tensor(float) U = tensor(double), tensor(float) V = tensor(double), tensor(float)
LeakyRelu	in X:T out Y:T	16+	T = tensor(float)
		[6, 15]	T = tensor(float)
Less	in A:T in B:T out C:T1	13+	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
		[9, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
		[7, 8]	T = tensor(double), tensor(float) T1 = tensor(bool)
LessOrEqual	in A:T in B:T out C:T1	16+	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
		[12, 15]	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
Log	in input:T out output:T	13+	T = tensor(double), tensor(float)
		[6, 12]	T = tensor(double), tensor(float)
LogSoftmax	in input:T out output:T	13+	T = tensor(double), tensor(float)
		[11, 12]	T = tensor(double), tensor(float)
		[1, 10]	T = tensor(double), tensor(float)
Loop	in M:I in cond:B in v_initial:V out v_final_and_scan_outputs:V	19+	B = tensor(bool) I = tensor(int64) V = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[16, 18]	B = tensor(bool) I = tensor(int64) V = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 15]	B = tensor(bool) I = tensor(int64) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	B = tensor(bool) I = tensor(int64) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	B = tensor(bool) I = tensor(int64) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
LpNormalization	in input:T out output:T	1+	T = tensor(double), tensor(float)
LpPool	in X:T out Y:T	18+	T = tensor(float)
		[11, 17]	T = tensor(float)
		[2, 10]	T = tensor(float)
MatMul	in A:T in B:T out Y:T	13+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[9, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[1, 8]	T = tensor(double), tensor(float)
MatMulInteger	in A:T1 in B:T2 in a_zero_point:T1 in b_zero_point:T2 out Y:T3	10+	T1 = tensor(int8), tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(int32)
Max	in data_0:T out max:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		12	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[8, 11]	T = tensor(double), tensor(float)
		[6, 7]	T = tensor(float)
MaxPool	in X:T out Y:T or in X:T out Y:T out Indices:I	12+	I = tensor(int64) T = tensor(double), tensor(float), tensor(int8), tensor(uint8)
		[8, 11]	I = tensor(int64) T = tensor(double), tensor(float)
		[1, 7]	T = tensor(float)
MaxRoiPool	in X:T in rois:T out Y:T	1+	T = tensor(float)
MaxUnpool	in X:T1 in I:T2 in output_shape:T2 out output:T1	11+	T1 = tensor(float) T2 = tensor(int64)
		[9, 10]	T1 = tensor(float) T2 = tensor(int64)
Mean	in data_0:T out mean:T	13+	T = tensor(float)
		[8, 12]	T = tensor(float)
		[6, 7]	T = tensor(float)
MeanVarianceNormalization	in X:T out Y:T or in input:T out output:T	13+	T = tensor(float)
		[9, 12]	T = tensor(float)
		[1, 8]	T = tensor(float)
MelWeightMatrix	in num_mel_bins:T1 in dft_length:T1 in sample_rate:T1 in lower_edge_hertz:T2 in upper_edge_hertz:T2 out output:T3	17+	T1 = tensor(int32), tensor(int64) T2 = tensor(float) T3 = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Min	in data_0:T out min:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		12	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[8, 11]	T = tensor(double), tensor(float)
		[6, 7]	T = tensor(float)
Mod	in A:T in B:T out C:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[10, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Mul	in A:T in B:T out C:T	14+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		13	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[7, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Multinomial	in input:T1 out output:T2	7+	T1 = tensor(float) T2 = tensor(int32), tensor(int64)
Neg	in X:T out Y:T	13+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8)
		[6, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8)
NonZero	in X:T out Y:tensor(int64)	13+	T = tensor(bool), tensor(float), tensor(int32), tensor(int64), tensor(uint8)
		[9, 12]	T = tensor(bool), tensor(float), tensor(int32), tensor(int64), tensor(uint8)
Not	in X:T out Y:T	1+	T = tensor(bool)
OneHot	in indices:T1 in depth:T2 in values:T3 out output:T3	11+	T1 = tensor(float), tensor(int32), tensor(int64) T2 = tensor(float), tensor(int32), tensor(int64) T3 = tensor(float), tensor(int32), tensor(int64), tensor(string)
		[9, 10]	T1 = tensor(float), tensor(int32), tensor(int64) T2 = tensor(float), tensor(int32), tensor(int64) T3 = tensor(float), tensor(int32), tensor(int64), tensor(string)
Optional	in input:V out output:O	15+	O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
OptionalGetElement	in input:O out output:V	18+	O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[15, 17]	O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
OptionalHasElement	in input:O out output:B	18+	B = tensor(bool) O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[15, 17]	B = tensor(bool) O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8))
Or	in A:T in B:T out C:T1	7+	T = tensor(bool) T1 = tensor(bool)
PRelu	in X:T in slope:T out Y:T	16+	T = tensor(float)
		[9, 15]	T = tensor(float)
		[7, 8]	T = tensor(float)
Pad	in data:T in pads:tensor(int64) in constant_value:T in axes:Tind out output:T or in data:T in pads:tensor(int64) in constant_value:T out output:T or in data:T out output:T	19+	T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
		18	T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 17]	T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
		[2, 10]	T = tensor(double), tensor(float)
ParametricSoftplus	in X:T out Y:T	1+	T = tensor(float)
Pow	in X:T in Y:T out Z:T or in X:T in Y:T1 out Z:T	15+	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[13, 14]	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
		12	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[7, 11]	T = tensor(double), tensor(float)
QLinearConv	in x:T1 in x_scale:tensor(float) in x_zero_point:T1 in w:T2 in w_scale:tensor(float) in w_zero_point:T2 in y_scale:tensor(float) in y_zero_point:T3 in B:T4 out y:T3	10+	T1 = tensor(int8), tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(int8), tensor(uint8) T4 = tensor(int32)
QLinearMatMul	in a:T1 in a_scale:tensor(float) in a_zero_point:T1 in b:T2 in b_scale:tensor(float) in b_zero_point:T2 in y_scale:tensor(float) in y_zero_point:T3 out y:T3	10+	T1 = tensor(int8), tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(int8), tensor(uint8)
QuantizeLinear	in x:T1 in y_scale:T1 in y_zero_point:T2 out y:T2 or in x:T1 in y_scale:tensor(float) in y_zero_point:T2 out y:T2	19+	T1 = tensor(float), tensor(float16) T2 = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int8), tensor(uint8)
		[13, 18]	T1 = tensor(float) T2 = tensor(int8), tensor(uint8)
		[10, 12]	T1 = tensor(float) T2 = tensor(int8), tensor(uint8)
RNN	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T out Y:T out Y_h:T	14+	T = tensor(float) T1 = tensor(int32)
		[7, 13]	T = tensor(float) T1 = tensor(int32)
RandomNormal	out output:T	1+	T = tensor(double), tensor(float)
RandomNormalLike	in input:T1 out output:T2	1+	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(double), tensor(float)
RandomUniform	out output:T	1+	T = tensor(double), tensor(float)
RandomUniformLike	in input:T1 out output:T2	1+	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(double), tensor(float)
Range	in start:T in limit:T in delta:T out output:T	11+	T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64)
Reciprocal	in X:T out Y:T	13+	T = tensor(double), tensor(float)
		[6, 12]	T = tensor(double), tensor(float)
ReduceL1	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(int32), tensor(int64)
		[13, 17]	T = tensor(float), tensor(int32), tensor(int64)
		[11, 12]	T = tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(float), tensor(int32), tensor(int64)
ReduceL2	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(int32), tensor(int64)
		[13, 17]	T = tensor(float), tensor(int32), tensor(int64)
		[11, 12]	T = tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(float), tensor(int32), tensor(int64)
ReduceLogSum	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(int32), tensor(int64)
		[13, 17]	T = tensor(float), tensor(int32), tensor(int64)
		[11, 12]	T = tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(float), tensor(int32), tensor(int64)
ReduceLogSumExp	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[13, 17]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[11, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
ReduceMax	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		[13, 17]	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		12	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		11	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
ReduceMean	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(double), tensor(float), tensor(int32)
		[13, 17]	T = tensor(double), tensor(float), tensor(int32)
		[11, 12]	T = tensor(double), tensor(float), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(int32)
ReduceMin	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		[13, 17]	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		12	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		11	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
ReduceProd	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(int32), tensor(int64)
		[13, 17]	T = tensor(float), tensor(int32), tensor(int64)
		[11, 12]	T = tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(float), tensor(int32), tensor(int64)
ReduceSum	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[11, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
ReduceSumSquare	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[13, 17]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[11, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Relu	in X:T out Y:T	14+	T = tensor(double), tensor(float), tensor(int32), tensor(int8)
		13	T = tensor(double), tensor(float)
		[6, 12]	T = tensor(double), tensor(float)
Reshape	in data:T in shape:tensor(int64) out reshaped:T or in data:T out reshaped:T	19+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) shape = tensor(int64)
		[14, 18]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) shape = tensor(int64)
		13	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) shape = tensor(int64)
		[5, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) shape = tensor(int64)
		[1, 4]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Resize	in X:T in scales:tensor(float) out Y:T or in X:T1 in roi:T2 in scales:tensor(float) in sizes:tensor(int64) out Y:T1	19+	T1 = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
		18	T1 = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
		[13, 17]	T1 = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
		[11, 12]	T1 = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
		10	T = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
ReverseSequence	in input:T in sequence_lens:tensor(int64) out Y:T	10+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
RoiAlign	in X:T1 in rois:T1 in batch_indices:T2 out Y:T1	16+	T1 = tensor(double), tensor(float) T2 = tensor(int64)
		[10, 15]	T1 = tensor(double), tensor(float) T2 = tensor(int64)
Round	in X:T out Y:T	11+	T = tensor(double), tensor(float), tensor(float16)
STFT	in signal:T1 in frame_step:T2 in window:T1 in frame_length:T2 out output:T1	17+	T1 = tensor(double), tensor(float) T2 = tensor(int32), tensor(int64)
Scale	in input:T out output:T	1+	T = tensor(float)
ScaledTanh	in input:T out output:T	1+	T = tensor(float)
Scan	in initial_state_and_scan_inputs:V out final_state_and_scan_outputs:V or in sequence_lens:I in initial_state_and_scan_inputs:V out final_state_and_scan_outputs:V	19+	V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[16, 18]	V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 15]	V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 10]	V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		8	I = tensor(int64) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Scatter	in data:T in indices:Tind in updates:T out output:T	[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
ScatterElements	in data:T in indices:Tind in updates:T out output:T	18+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[16, 17]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[13, 15]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
ScatterND	in data:T in indices:tensor(int64) in updates:T out output:T	18+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[16, 17]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 15]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Selu	in X:T out Y:T	6+	T = tensor(float)
SequenceAt	in input_sequence:S in position:I out tensor:T	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)) T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SequenceConstruct	in inputs:T out output_sequence:S	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)) T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SequenceEmpty	out output:S	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceErase	in input_sequence:S in position:I out output_sequence:S	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceInsert	in input_sequence:S in tensor:T in position:I out output_sequence:S	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceLength	in input_sequence:S out length:I	11+	I = tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
Shape	in data:T out shape:T1	19+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[15, 18]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[13, 14]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[1, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
Shrink	in input:T out output:T	9+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sigmoid	in X:T out Y:T	13+	T = tensor(double), tensor(float)
		[6, 12]	T = tensor(double), tensor(float)
Sign	in input:T out output:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 12]	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SimplifiedLayerNormalization	in X:T in scale:V out Y:V out inv_std_var:U	1+	T = tensor(double), tensor(float) U = tensor(double), tensor(float) V = tensor(double), tensor(float)
Sin	in input:T out output:T	7+	T = tensor(double), tensor(float)
Sinh	in input:T out output:T	9+	T = tensor(float)
Size	in data:T out size:T1	19+	T = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[13, 18]	T = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[1, 12]	T = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
Slice	in data:T in starts:Tind in ends:Tind in axes:Tind in steps:Tind out output:T or in data:T out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		10	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[1, 9]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Softmax	in input:T out output:T	13+	T = tensor(double), tensor(float)
		[11, 12]	T = tensor(double), tensor(float)
		[1, 10]	T = tensor(double), tensor(float)
Softplus	in X:T out Y:T	1+	T = tensor(float)
Softsign	in input:T out output:T	1+	T = tensor(float)
SpaceToDepth	in input:T out output:T	13+	T = tensor(double), tensor(float)
		[1, 12]	T = tensor(double), tensor(float)
Split	in input:T in split:T out outputs...:T or in input:T in split:tensor(int64) out outputs:T or in input:T out outputs:T	18+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 17]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[2, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SplitToSequence	in input:T in split:I out output_sequence:S	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)) T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string)
Sqrt	in X:T out Y:T	13+	T = tensor(double), tensor(float)
		[6, 12]	T = tensor(double), tensor(float)
Squeeze	in data:T in axes:tensor(int64) out squeezed:T or in data:T out squeezed:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
StringNormalizer	in X:tensor(string) out Y:tensor(string)	10+	X = tensor(string)
Sub	in A:T in B:T out C:T	14+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		13	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[7, 12]	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Sum	in data_0:T out sum:T	13+	T = tensor(double), tensor(float)
		[8, 12]	T = tensor(double), tensor(float)
		[6, 7]	T = tensor(double), tensor(float)
Tan	in input:T out output:T	7+	T = tensor(float)
Tanh	in input:T out output:T	13+	T = tensor(double), tensor(float)
		[6, 12]	T = tensor(double), tensor(float)
TfIdfVectorizer	in X:T out Y:T1	9+	T = tensor(int32), tensor(int64), tensor(string) T1 = tensor(float)
ThresholdedRelu	in X:T out Y:T	10+	T = tensor(float)
		[1, 9]	T = tensor(float)
Tile	in input:T in repeats:T1 out output:T or in input:T in tiles:T in axis:T out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[6, 12]	T = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
TopK	in X:T in K:tensor(int64) out Values:T out Indices:I or in X:T out Values:T out Indices:I	11+	I = tensor(int64) T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		10	I = tensor(int64) T = tensor(double), tensor(float)
		[1, 9]	I = tensor(int64) T = tensor(double), tensor(float)
Transpose	in data:T out transposed:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Trilu	in input:T in k:tensor(int64) out output:T	14+	T = tensor(double), tensor(float), tensor(int64)
Unique	in X:T out Y:T out indices:tensor(int64) out inverse_indices:tensor(int64) out counts:tensor(int64)	11+	T = tensor(double), tensor(float), tensor(int64), tensor(int8), tensor(string)
Unsqueeze	in data:T in axes:tensor(int64) out expanded:T or in data:T out expanded:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Upsample	in X:T in scales:tensor(float) out Y:T or in X:T out Y:T	9	T = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
		[7, 8]	T = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
Where	in condition:B in X:T in Y:T out output:T	16+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string), tensor(uint8)
		[9, 15]	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string), tensor(uint8)
Xor	in A:T in B:T out C:T1	7+	T = tensor(bool) T1 = tensor(bool)


Operator Domain: ai.onnx.ml
ArrayFeatureExtractor	in X:T in Y:tensor(int64) out Z:T	1+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string)
Binarizer	in X:T out Y:T	1+	T = tensor(float)
CastMap	in X:T1 out Y:T2	1+	T1 = map(int64,tensor(float)), map(int64,tensor(string)) T2 = tensor(float), tensor(int64), tensor(string)
CategoryMapper	in X:T1 out Y:T2	1+	T1 = tensor(int64), tensor(string) T2 = tensor(int64), tensor(string)
DictVectorizer	in X:T1 out Y:T2	1+	T1 = map(int64,tensor(double)), map(int64,tensor(float)), map(int64,tensor(string)), map(string,tensor(double)), map(string,tensor(float)), map(string,tensor(int64)) T2 = tensor(double), tensor(float), tensor(int64), tensor(string)
FeatureVectorizer	in X:T1 out Y:tensor(float)	1+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
Imputer	in X:T out Y:T	1+	T = tensor(float), tensor(int64)
LabelEncoder	in X:T1 out Y:T2	2+	T1 = tensor(float), tensor(int64), tensor(string) T2 = tensor(float), tensor(int64), tensor(string)
		1	T1 = tensor(int64), tensor(string) T2 = tensor(int64), tensor(string)
LinearClassifier	in X:T1 out Y:T2 out Z:tensor(float)	1+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64) T2 = tensor(int64), tensor(string)
LinearRegressor	in X:T out Y:tensor(float)	1+	T = tensor(float)
Normalizer	in X:T out Y:tensor(float)	1+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
OneHotEncoder	in X:T out Y:tensor(float)	1+	T = tensor(double), tensor(float), tensor(int64), tensor(string)
SVMClassifier	in X:T1 out Y:T2 out Z:tensor(float)	1+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64) T2 = tensor(int64), tensor(string)
SVMRegressor	in X:T out Y:tensor(float)	1+	T = tensor(float)
Scaler	in X:T out Y:tensor(float)	1+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
TreeEnsembleClassifier	in X:T1 out Y:T2 out Z:tensor(float)	3+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64) T2 = tensor(int64), tensor(string)
		[1, 2]	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64) T2 = tensor(int64), tensor(string)
TreeEnsembleRegressor	in X:T out Y:tensor(float)	3+	T = tensor(double), tensor(float)
		[1, 2]	T = tensor(double), tensor(float)
ZipMap	in X:tensor(float) out Z:T	1+	T = seq(map(int64,tensor(float))), seq(map(string,tensor(float)))


Operator Domain: com.microsoft
Attention	in input:T in weights:T in bias:T in mask_index:M in past:T in relative_position_bias:T in past_sequence_length:M out output:T out present:T	1+	T = tensor(float)
AttnLSTM	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T in initial_c:T in P:T in QW:T in MW:T in V:T in M:T in memory_seq_lens:T1 in AW:T out Y:T out Y_h:T out Y_c:T	1+	T = tensor(double), tensor(float) T1 = tensor(int32)
BeamSearch	in input_ids:F in max_length:I in min_length:I in num_beams:I in num_return_sequences:I in length_penalty:T in repetition_penalty:T in vocab_mask:M in prefix_vocab_mask:M in attention_mask:I in decoder_input_ids:I in logits_processor:I out sequences:I out sequences_scores:T out scores:T	1+	T = tensor(float)
BiasGelu	in A:T in B:T out C:T	1+	T = tensor(float)
BifurcationDetector	in src_tokens:T in cur_tokens:T in prev_suffix_match_idx:T in pred_tokens:T out tokens:T out suffix_match_idx:T	1+	T = tensor(int64)
CDist	in A:T in B:T out C:T	1+	T = tensor(double), tensor(float)
ConvTransposeWithDynamicPads	in X:T in W:T in Pads:tensor(int64) in B:T out Y:T	1+	T = tensor(float)
CropAndResize	in X:T1 in rois:T1 in batch_indices:T2 in crop_size:T2 out Y:T1	1+	T1 = tensor(float) T2 = tensor(int32)
DequantizeLinear	in x:T1 in x_scale:T2 in x_zero_point:T1 out y:T2	1+	T1 = tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint8) T2 = tensor(float)
DynamicQuantizeLSTM	in X:T in W:T2 in R:T2 in B:T in sequence_lens:T1 in initial_h:T in initial_c:T in P:T in W_scale:T in W_zero_point:T2 in R_scale:T in R_zero_point:T2 out Y:T out Y_h:T out Y_c:T	1+	T = tensor(float) T1 = tensor(int32) T2 = tensor(int8), tensor(uint8)
DynamicQuantizeMatMul	in A:T1 in B:T2 in b_scale:T1 in b_zero_point:T2 in bias:T1 out Y:T1	1+	T1 = tensor(float) T2 = tensor(int8), tensor(uint8)
EmbedLayerNormalization	in input_ids:T1 in segment_ids:T1 in word_embedding:T in position_embedding:T in segment_embedding:T in gamma:T in beta:T in mask:T1 in position_ids:T1 out output:T out mask_index:T1 out embedding_sum:T	1+	T = tensor(float)
ExpandDims	in X:T in axis:tensor(int32) out Y:T	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) axis = tensor(int32)
FastGelu	in X:T in bias:T out Y:T	1+	T = tensor(float)
FusedConv	in X:T in W:T in B:T in Z:T out Y:T	1+	T = tensor(float)
FusedGemm	in A:T in B:T in C:T out Y:T	1+	T = tensor(float)
FusedMatMul	in A:T in B:T out Y:T	1+	T = tensor(float)
GatherND	in data:T in indices:Tind out output:T	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
Gelu	in X:T out Y:T	1+	T = tensor(float)
GreedySearch	in input_ids:I in max_length:I in min_length:I in repetition_penalty:T in vocab_mask:I in prefix_vocab_mask:I in attention_mask:I out sequences:I	1+	T = tensor(float)
GridSample	in X:T1 in Grid:T1 out Y:T2	1+	T1 = tensor(float) T2 = tensor(float)
Inverse	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
MatMulFpQ4	in A:T1 in B:T2 in B_shape:T3 out Y:T1	1+	T1 = tensor(float) T2 = tensor(uint8) T3 = tensor(int64)
MatMulInteger16	in A:T1 in B:T2 out Y:T3	1+	T1 = tensor(int16) T2 = tensor(int16) T3 = tensor(int32)
MatMulIntegerToFloat	in A:T1 in B:T2 in a_scale:T3 in b_scale:T3 in a_zero_point:T1 in b_zero_point:T2 in bias:T3 out Y:T3	1+	T1 = tensor(int8), tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(float)
MatMulNBits	in A:T1 in B:T2 in scales:T1 in zero_points:T2 out Y:T1	1+	T1 = tensor(float) T2 = tensor(uint8)
MaxpoolWithMask	in X:T in M:tensor(int32) out Y:T	1+	T = tensor(float)
MultiHeadAttention	in query:T in key:T in value:T in bias:T in key_padding_mask:M in relative_position_bias:T in past_key:T in past_value:T out output:T out present_key:T out present_value:T	1+	T = tensor(float)
MurmurHash3	in X:T1 out Y:T2	1+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string), tensor(uint32), tensor(uint64) T2 = tensor(int32), tensor(uint32)
NGramRepeatBlock	in input_ids:Tid in scores:T out scores_out:T	1+	T = tensor(float) Tid = tensor(int64)
NhwcMaxPool	in x:T out y:T	1+	T = tensor(int8), tensor(uint8)
Pad	in data:T in pads:tensor(int64) in value:T out output:T	1+	T = tensor(float)
QAttention	in input:T1 in weight:T2 in bias:T3 in input_scale:T3 in weight_scale:T3 in mask_index:T4 in input_zero_point:T1 in weight_zero_point:T2 in past:T3 out output:T3 out present:T3	1+	T1 = tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(float) T4 = tensor(int32)
QEmbedLayerNormalization	in input_ids:T1 in segment_ids:T1 in word_embedding_quant:T2 in position_embedding_quant:T2 in segment_embedding:T2 in gamma_quant:T2 in beta_quant:T2 in mask:T1 in word_embedding_scale:T in position_embedding_scale:T in segment_embedding_scale:T in gamma_scale:T in beta_scale:T in word_embedding_zero_point:T2 in position_embedding_zero_point:T2 in segment_embedding_zero_point:T2 in gamma_zero_point:T2 in beta_zero_point:T2 out layernorm_out:T out mask_index_out:T1	1+	T = tensor(float)
QGemm	in A:TA in a_scale:T in a_zero_point:TA in B:TB in b_scale:T in b_zero_point:TB in C:TC in y_scale:T in y_zero_point:TYZ out Y:TY	1+	T = tensor(float) TA = tensor(int8), tensor(uint8) TB = tensor(int8), tensor(uint8) TC = tensor(int32) TY = tensor(float), tensor(int8), tensor(uint8) TYZ = tensor(int8), tensor(uint8)
QLinearAdd	in A:T in A_scale:tensor(float) in A_zero_point:T in B:T in B_scale:tensor(float) in B_zero_point:T in C_scale:tensor(float) in C_zero_point:T out C:T	1+	T = tensor(int8), tensor(uint8)
QLinearConv	in x:T1 in x_scale:tensor(float) in x_zero_point:T1 in w:T2 in w_scale:tensor(float) in w_zero_point:T2 in y_scale:tensor(float) in y_zero_point:T3 in B:T4 out y:T3	1+	T1 = tensor(int8), tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(int8), tensor(uint8) T4 = tensor(int32)
QLinearLeakyRelu	in X:T in X_scale:tensor(float) in X_zero_point:T in Y_scale:tensor(float) in Y_zero_point:T out Y:T	1+	T = tensor(int8), tensor(uint8)
QLinearMul	in A:T in A_scale:tensor(float) in A_zero_point:T in B:T in B_scale:tensor(float) in B_zero_point:T in C_scale:tensor(float) in C_zero_point:T out C:T	1+	T = tensor(int8), tensor(uint8)
QLinearSigmoid	in X:T in X_scale:tensor(float) in X_zero_point:T in Y_scale:tensor(float) in Y_zero_point:T out Y:T	1+	T = tensor(int8), tensor(uint8)
QLinearSoftmax	in X:T in X_scale:tensor(float) in x_zero_point:T in y_scale:tensor(float) in y_zero_point:T out Y:T	1+	T = tensor(int8), tensor(uint8)
QLinearWhere	in condition:B in X:T in x_scale:TF in x_zero_point:T in Y:T in y_scale:TF in y_zero_point:T in z_scale:TF in z_zero_point:T out Z:T	1+	T = tensor(int8), tensor(uint8)
QuantizeLinear	in x:T1 in y_scale:T1 in y_zero_point:T2 out y:T2	1+	T1 = tensor(float) T2 = tensor(int16), tensor(int8), tensor(uint16), tensor(uint8)
QuickGelu	in X:T out Y:T	1+	T = tensor(float)
Range	in start:T in limit:T in delta:T out Y:T	1+	T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64)
RotaryEmbedding	in input:T in position_ids:M in cos_cache:T in sin_cache:T out output:T	1+	M = tensor(int64) T = tensor(float)
SampleOp	in X:T out Y:T	1+	T = tensor(float)
Sampling	in input_ids:I in max_length:I in min_length:I in repetition_penalty:T in vocab_mask:I in prefix_vocab_mask:I in attention_mask:I in presence_mask:I in seed:I out sequences:I out filtered_logits:T	1+	T = tensor(float)
SkipLayerNormalization	in input:T in skip:T in gamma:T in beta:T in bias:T out output:T out mean:U out inv_std_var:U out input_skip_bias_sum:T	1+	T = tensor(double), tensor(float)
SkipSimplifiedLayerNormalization	in input:T in skip:T in gamma:T in bias:T out output:T out mean:U out inv_std_var:U out input_skip_bias_sum:T	1+	T = tensor(double), tensor(float)
SparseToDenseMatMul	in A:T in B:T1 out Y:T1	1+	T = sparse_tensor(double), sparse_tensor(float), sparse_tensor(int32), sparse_tensor(int64), sparse_tensor(uint32), sparse_tensor(uint64) T1 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Tokenizer	in X:T out Y:T	1+	T = tensor(string)
TransposeMatMul	in A:T in B:T out Y:T	1+	T = tensor(float)
Trilu	in X:T in k:tensor(int64) out Y:T	1+	T = tensor(double), tensor(float), tensor(int64)
Unique	in x:T out y:T out idx:tensor(int64) out counts:tensor(int64)	1+	T = tensor(float)
WhisperBeamSearch	in input_ids:F in max_length:I in min_length:I in num_beams:I in num_return_sequences:I in length_penalty:T in repetition_penalty:T in vocab_mask:M in prefix_vocab_mask:M in attention_mask:I in decoder_input_ids:I in logits_processor:I in cross_qk_layer_head:I in extra_decoding_ids:I out sequences:I out sequences_scores:T out scores:T out cross_qk:V out non_speech_probs:T	1+	T = tensor(float)
WordConvEmbedding	in Sequence:T in W:T1 in B:T1 in C:T1 out Y:T1	1+	T = tensor(int32) T1 = tensor(float)


Operator Domain: com.microsoft.nchwc
AveragePool	in X:T out Y:T	1+	T = tensor(float)
Conv	in X:T in W:T in B:T in Sum:T out Y:T	1+	T = tensor(float)
GlobalAveragePool	in X:T out Y:T	1+	T = tensor(float)
GlobalMaxPool	in X:T out Y:T	1+	T = tensor(float)
MaxPool	in X:T out Y:T	1+	T = tensor(float)
ReorderInput	in X:T out Y:T	1+	T = tensor(float)
ReorderOutput	in X:T out Y:T	1+	T = tensor(float)
Upsample	in X:T out Y:T	1+	T = tensor(float)

Operators implemented by CUDAExecutionProvider

Op Name	Parameters	OpSet Version	Types Supported
Operator Domain: ai.onnx
Abs	in X:T out Y:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Add	in A:T in B:T out C:T	14+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[7, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Affine	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
And	in A:T in B:T out C:T1	7+	T = tensor(bool) T1 = tensor(bool)
ArgMax	in data:T out reduced:tensor(int64)	11	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
ArgMin	in data:T out reduced:tensor(int64)	11	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
AveragePool	in X:T out Y:T	11+	T = tensor(double), tensor(float), tensor(float16)
		10	T = tensor(double), tensor(float), tensor(float16)
		[7, 9]	T = tensor(double), tensor(float), tensor(float16)
BatchNormalization	in X:T in scale:T in B:T in input_mean:U in input_var:U out Y:T out running_mean:U out running_var:U or in X:T in scale:T in B:T in mean:T in var:T out Y:T out mean:T out var:T out saved_mean:T out saved_var:T or in X:T in scale:T1 in B:T1 in input_mean:T2 in input_var:T2 out Y:T out running_mean:T2 out running_var:T2	15+	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(double), tensor(float), tensor(float16) T2 = tensor(double), tensor(float), tensor(float16)
		14	T = tensor(double), tensor(float), tensor(float16) U = tensor(double), tensor(float), tensor(float16)
		[9, 13]	T = tensor(double), tensor(float), tensor(float16)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16)
Cast	in input:T1 out output:T2	19+	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e5m2), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e5m2), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 18]	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e5m2), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 12]	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e5m2), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[6, 8]	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e5m2), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Ceil	in X:T out Y:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16)
Clip	in input:T in min:T in max:T out output:T or in input:T out output:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int64), tensor(int8), tensor(uint64), tensor(uint8)
		12	T = tensor(double), tensor(float), tensor(float16), tensor(int64), tensor(int8), tensor(uint64), tensor(uint8)
		11	T = tensor(float)
		[6, 10]	T = tensor(float)
Compress	in input:T in condition:T1 out output:T	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
Concat	in inputs:T out concat_result:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[4, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ConcatFromSequence	in input_sequence:S out concat_result:T	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
ConstantOfShape	in input:T1 out output:T2	9+	T1 = tensor(int64) T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Conv	in X:T in W:T in B:T out Y:T	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
ConvTranspose	in X:T in W:T in B:T out Y:T	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
Cos	in input:T out output:T	7+	T = tensor(double), tensor(float), tensor(float16)
Crop	in input:T out output:T	1+	T = tensor(double), tensor(float), tensor(float16)
CumSum	in x:T in axis:T2 out y:T	14+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T2 = tensor(int32), tensor(int64)
		[11, 13]	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T2 = tensor(int32), tensor(int64)
DepthToSpace	in input:T out output:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
DequantizeLinear	in x:T in x_scale:tensor(float) in x_zero_point:T out y:tensor(float) or in x:T1 in x_scale:T2 in x_zero_point:T1 out y:T2	19+	T1 = tensor(float8e4m3fn), tensor(float8e5m2), tensor(int8), tensor(uint8) T2 = tensor(float), tensor(float16)
		[13, 18]	T = tensor(int8), tensor(uint8)
		[10, 12]	T = tensor(int8), tensor(uint8)
Div	in A:T in B:T out C:T	14+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[7, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Dropout	in data:T in ratio:T1 in training_mode:T2 out output:T out mask:T2 or in data:T out output:T out mask:T or in data:T out output:T out mask:T1	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) T1 = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) T2 = tensor(bool)
		12	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(double), tensor(float), tensor(float16) T2 = tensor(bool)
		[10, 11]	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(bool)
		[7, 9]	T = tensor(double), tensor(float), tensor(float16)
DynamicSlice	in data:T in starts:Tind in ends:Tind in axes:Tind out output:T	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
Einsum	in Inputs:T out Output:T	12+	T = tensor(double), tensor(float), tensor(float16)
Elu	in X:T out Y:T	6+	T = tensor(double), tensor(float), tensor(float16)
Equal	in A:T in B:T out C:T1	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T1 = tensor(bool)
		[11, 12]	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[7, 10]	T = tensor(bool), tensor(int32), tensor(int64)
Erf	in input:T out output:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[9, 12]	T = tensor(double), tensor(float), tensor(float16)
Exp	in input:T out output:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16)
Expand	in input:T in shape:tensor(int64) out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[8, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
EyeLike	in input:T1 out output:T2	9+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64) T2 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)
Flatten	in input:T out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 8]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Floor	in X:T out Y:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16)
GRU	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T out Y:T out Y_h:T	14+	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(int32)
		[7, 13]	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(int32)
Gather	in data:T in indices:Tind out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
GatherElements	in data:T in indices:Tind out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
GatherND	in data:T in indices:tensor(int64) out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int64) indices = tensor(int64)
		12	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int64) indices = tensor(int64)
		11	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int64) indices = tensor(int64)
Gemm	in A:T in B:T in C:T out Y:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16)
		[9, 10]	T = tensor(double), tensor(float), tensor(float16)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16)
GlobalAveragePool	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
GlobalMaxPool	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
Greater	in A:T in B:T out C:T1	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T1 = tensor(bool)
		[9, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16)
GreaterOrEqual	in A:T in B:T out C:T1	16+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T1 = tensor(bool)
		[12, 15]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T1 = tensor(bool)
HardSigmoid	in X:T out Y:T	6+	T = tensor(double), tensor(float), tensor(float16)
Identity	in input:T out output:T or in input:V out output:V	19+	V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[14, 18]	V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
If	in cond:B out outputs:V	19+	B = tensor(bool) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 18]	B = tensor(bool) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	B = tensor(bool) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	B = tensor(bool) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ImageScaler	in input:T out output:T	1+	T = tensor(double), tensor(float), tensor(float16)
InstanceNormalization	in input:T in scale:T in B:T out output:T	6+	T = tensor(double), tensor(float), tensor(float16)
LRN	in X:T out Y:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[1, 12]	T = tensor(double), tensor(float), tensor(float16)
LSTM	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T in initial_c:T in P:T out Y:T out Y_h:T out Y_c:T	14+	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(int32)
		[7, 13]	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(int32)
LayerNormalization	in X:T in Scale:T in B:T out Y:T out Mean:U out InvStdDev:U or in X:T in Scale:V in B:V out Y:V out Mean:U out InvStdDev:U	17+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) U = tensor(float)
		[1, 16]	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) U = tensor(double), tensor(float) V = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
LeakyRelu	in X:T out Y:T	16+	T = tensor(double), tensor(float), tensor(float16)
		[6, 15]	T = tensor(double), tensor(float), tensor(float16)
Less	in A:T in B:T out C:T1	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T1 = tensor(bool)
		[9, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16)
LessOrEqual	in A:T in B:T out C:T1	16+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T1 = tensor(bool)
		[12, 15]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T1 = tensor(bool)
Log	in input:T out output:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16)
LogSoftmax	in input:T out output:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
Loop	in M:I in cond:B in v_initial:V out v_final_and_scan_outputs:V	19+	B = tensor(bool) I = tensor(int64) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 18]	B = tensor(bool) I = tensor(int64) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	B = tensor(bool) I = tensor(int64) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	B = tensor(bool) I = tensor(int64) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
MatMul	in A:T in B:T out Y:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
		[9, 12]	T = tensor(double), tensor(float), tensor(float16)
		[1, 8]	T = tensor(double), tensor(float), tensor(float16)
MatMulInteger	in A:T1 in B:T2 in a_zero_point:T1 in b_zero_point:T2 out Y:T3	10+	T1 = tensor(int8) T2 = tensor(int8) T3 = tensor(int32)
Max	in data_0:T out max:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		12	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[6, 11]	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
MaxPool	in X:T out Y:T or in X:T out Y:T out Indices:I	12+	I = tensor(int64) T = tensor(double), tensor(float), tensor(float16), tensor(int8), tensor(uint8)
		11	I = tensor(int64) T = tensor(double), tensor(float), tensor(float16)
		10	I = tensor(int64) T = tensor(double), tensor(float), tensor(float16)
		[8, 9]	I = tensor(int64) T = tensor(double), tensor(float), tensor(float16)
		[1, 7]	T = tensor(double), tensor(float), tensor(float16)
MemcpyFromHost	in X:T out Y:T	1+	T = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
MemcpyToHost	in X:T out Y:T	1+	T = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Min	in data_0:T out min:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		12	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[6, 11]	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
Mod	in A:T in B:T out C:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[10, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Mul	in A:T in B:T out C:T	14+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[7, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Neg	in X:T out Y:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
NonZero	in X:T out Y:tensor(int64)	13+	T = tensor(bool), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint8)
		[9, 12]	T = tensor(bool), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint8)
Not	in X:T out Y:T	1+	T = tensor(bool)
OneHot	in indices:T1 in depth:T2 in values:T3 out output:T3	11+	T1 = tensor(int32), tensor(int64) T2 = tensor(int32), tensor(int64) T3 = tensor(float), tensor(float16), tensor(int64)
Or	in A:T in B:T out C:T1	7+	T = tensor(bool) T1 = tensor(bool)
PRelu	in X:T in slope:T out Y:T	16+	T = tensor(double), tensor(float), tensor(float16)
		[9, 15]	T = tensor(double), tensor(float), tensor(float16)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16)
Pad	in data:T in pads:tensor(int64) in constant_value:T in axes:Tind out output:T or in data:T in pads:tensor(int64) in constant_value:T out output:T or in data:T out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16)
		[2, 10]	T = tensor(double), tensor(float), tensor(float16)
ParametricSoftplus	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
Pow	in X:T in Y:T out Z:T or in X:T in Y:T1 out Z:T	15+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64) T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
		[13, 14]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64) T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
		12	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64) T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
		[7, 11]	T = tensor(double), tensor(float), tensor(float16)
QuantizeLinear	in x:T1 in y_scale:T1 in y_zero_point:T2 out y:T2 or in x:T1 in y_scale:tensor(float) in y_zero_point:T2 out y:T2	19+	T1 = tensor(float), tensor(float16) T2 = tensor(float8e4m3fn), tensor(float8e5m2), tensor(int8), tensor(uint8)
		[13, 18]	T1 = tensor(float) T2 = tensor(int8), tensor(uint8)
		[10, 12]	T1 = tensor(float) T2 = tensor(int8), tensor(uint8)
RNN	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T out Y:T out Y_h:T	14+	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(int32)
		[7, 13]	T = tensor(double), tensor(float), tensor(float16) T1 = tensor(int32)
RandomNormal	out output:T	1+	T = tensor(double), tensor(float), tensor(float16)
RandomNormalLike	in input:T1 out output:T2	1+	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(double), tensor(float), tensor(float16)
RandomUniform	out output:T	1+	T = tensor(double), tensor(float), tensor(float16)
RandomUniformLike	in input:T1 out output:T2	1+	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(double), tensor(float), tensor(float16)
Range	in start:T in limit:T in delta:T out output:T	11+	T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64)
Reciprocal	in X:T out Y:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16)
ReduceL1	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceL2	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceLogSum	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
ReduceLogSumExp	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
ReduceMax	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		12	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		11	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
ReduceMean	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceMin	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	14+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		13	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		12	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		11	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceProd	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceSum	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
ReduceSumSquare	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
Relu	in X:T out Y:T	14+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
		13	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16)
Reshape	in data:T in shape:tensor(int64) out reshaped:T or in data:T out reshaped:T	19+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) shape = tensor(int64)
		[14, 18]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) shape = tensor(int64)
		13	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) shape = tensor(int64)
		[5, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) shape = tensor(int64)
		[1, 4]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Resize	in X:T in scales:tensor(float) out Y:T or in X:T1 in roi:T2 in scales:tensor(float) in sizes:tensor(int64) out Y:T1	13+	T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
		[11, 12]	T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
		10	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
ReverseSequence	in input:T in sequence_lens:tensor(int64) out Y:T	10+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
RoiAlign	in X:T1 in rois:T1 in batch_indices:T2 out Y:T1	10+	T1 = tensor(double), tensor(float) T2 = tensor(int64)
Round	in X:T out Y:T	11+	T = tensor(double), tensor(float), tensor(float16)
ScaledTanh	in input:T out output:T	1+	T = tensor(double), tensor(float), tensor(float16)
Scan	in initial_state_and_scan_inputs:V out final_state_and_scan_outputs:V or in sequence_lens:I in initial_state_and_scan_inputs:V out final_state_and_scan_outputs:V	19+	V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[16, 18]	V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 15]	V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 10]	V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		8	I = tensor(int64) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Scatter	in data:T in indices:Tind in updates:T out output:T	[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
ScatterElements	in data:T in indices:Tind in updates:T out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
ScatterND	in data:T in indices:tensor(int64) in updates:T out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Selu	in X:T out Y:T	6+	T = tensor(double), tensor(float), tensor(float16)
SequenceAt	in input_sequence:S in position:I out tensor:T	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)) T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SequenceConstruct	in inputs:T out output_sequence:S	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)) T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SequenceEmpty	out output:S	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceErase	in input_sequence:S in position:I out output_sequence:S	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceInsert	in input_sequence:S in tensor:T in position:I out output_sequence:S	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceLength	in input_sequence:S out length:I	11+	I = tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
Shape	in data:T out shape:T1	19+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[15, 18]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[13, 14]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[1, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
Shrink	in input:T out output:T	9+	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sigmoid	in X:T out Y:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16)
Sign	in input:T out output:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SimplifiedLayerNormalization	in X:T in scale:V out Y:V out inv_std_var:U	1+	T = tensor(double), tensor(float), tensor(float16) U = tensor(double), tensor(float) V = tensor(double), tensor(float), tensor(float16)
Sin	in input:T out output:T	7+	T = tensor(double), tensor(float), tensor(float16)
Size	in data:T out size:T1	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		[1, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
Slice	in data:T in starts:Tind in ends:Tind in axes:Tind in steps:Tind out output:T or in data:T out output:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		10	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		[1, 9]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Softmax	in input:T out output:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
		[11, 12]	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
Softplus	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
Softsign	in input:T out output:T	1+	T = tensor(double), tensor(float), tensor(float16)
SpaceToDepth	in input:T out output:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[1, 12]	T = tensor(double), tensor(float), tensor(float16)
Split	in input:T in split:T out outputs...:T or in input:T in split:tensor(int64) out outputs:T or in input:T out outputs:T	18+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[13, 17]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[2, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sqrt	in X:T out Y:T	13+	T = tensor(double), tensor(float), tensor(float16)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16)
Squeeze	in data:T in axes:tensor(int64) out squeezed:T or in data:T out squeezed:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sub	in A:T in B:T out C:T	14+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[7, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Sum	in data_0:T out sum:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
		[8, 12]	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
		[6, 7]	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
Tanh	in input:T out output:T	13+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16)
ThresholdedRelu	in X:T out Y:T	10+	T = tensor(double), tensor(float), tensor(float16)
		1+	T = tensor(double), tensor(float), tensor(float16)
Tile	in input:T in repeats:T1 out output:T or in input:T in tiles:T in axis:T out output:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64) T1 = tensor(int64)
		[6, 12]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64) T1 = tensor(int64)
TopK	in X:T in K:tensor(int64) out Values:T out Indices:I or in X:T out Values:T out Indices:I	11+	I = tensor(int64) T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
		10	I = tensor(int64) T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
		[1, 9]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
Transpose	in data:T out transposed:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Trilu	in input:T in k:tensor(int64) out output:T	14+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Unsqueeze	in data:T in axes:tensor(int64) out expanded:T or in data:T out expanded:T	13+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[11, 12]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Upsample	in X:T in scales:tensor(float) out Y:T or in X:T out Y:T	9	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
Where	in condition:B in X:T in Y:T out output:T	16+	B = tensor(bool) T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint8)
		[9, 15]	B = tensor(bool) T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint8)
Xor	in A:T in B:T out C:T1	7+	T = tensor(bool) T1 = tensor(bool)


Operator Domain: com.microsoft
Attention	in input:T in weights:T in bias:T in mask_index:M in past:T in relative_position_bias:T in past_sequence_length:M out output:T out present:T	1+	T = tensor(float), tensor(float16)
BeamSearch	in input_ids:F in max_length:I in min_length:I in num_beams:I in num_return_sequences:I in length_penalty:T in repetition_penalty:T in vocab_mask:M in prefix_vocab_mask:M in attention_mask:I in decoder_input_ids:I in logits_processor:I out sequences:I out sequences_scores:T out scores:T	1+	T = tensor(float), tensor(float16)
BiasAdd	in X:T in bias:T in skip:T out Y:T	1+	T = tensor(float), tensor(float16)
BiasDropout	in data:T in bias:T in residual:T in ratio:T1 in training_mode:T2 out output:T out mask:T2	1+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) T1 = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) T2 = tensor(bool)
BiasGelu	in A:T in B:T out C:T	1+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
BiasSoftmax	in data:T in bias:T out output:T	1+	T = tensor(double), tensor(float), tensor(float16)
BiasSplitGelu	in X:T in bias:T out Y:T	1+	T = tensor(float), tensor(float16)
BitmaskBiasDropout	in data:T in bias:T in residual:T in ratio:T1 in training_mode:T2 out output:T out mask:T3	1+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) T1 = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) T2 = tensor(bool) T3 = tensor(uint32)
BitmaskDropout	in data:T in ratio:T1 in training_mode:T2 out output:T out mask:T3	1+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) T1 = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) T2 = tensor(bool) T3 = tensor(uint32)
ComplexMul	in A:T in B:T out C:T	1+	T = tensor(float), tensor(float16)
ComplexMulConj	in A:T in B:T out C:T	1+	T = tensor(float), tensor(float16)
ConvTransposeWithDynamicPads	in X:T in W:T in Pads:tensor(int64) in B:T out Y:T	1+	T = tensor(float)
DecoderAttention	in query:T in key:T in q_weight:T in kv_weight:T in bias:T in key_padding_mask:B in key_cache:T in value_cache:T in static_kv:B in use_past:B in has_layer_state:B in has_key_padding_mask:B out output:T out new_key_cache:T out new_value_cache:T	1+	T = tensor(float), tensor(float16)
DecoderMaskedMultiHeadAttention	in query:T in key:T in value:T in mask_index:M in relative_position_bias:T in past_key:T in past_value:T in past_sequence_length:M in beam_width:M in cache_indirection:M in bias:T out output:T out present_key:T out present_value:T out qk:V	1+	T = tensor(float), tensor(float16)
DecoderMaskedSelfAttention	in input:T in weights:T in bias:T in mask_index:M in past:T in relative_position_bias:T in past_sequence_length:M in beam_width:M in cache_indirection:M out output:T out present:T	1+	T = tensor(float), tensor(float16)
DequantizeLinear	in x:T1 in x_scale:T2 in x_zero_point:T1 out y:T2	1+	T1 = tensor(int8), tensor(uint8) T2 = tensor(float16)
DequantizeWithOrder	in input:Q in scale_input:S out output:F	1+	F = tensor(float), tensor(float16) Q = tensor(int8) S = tensor(float)
DynamicTimeWarping	in input:F out output:I	1+	F = tensor(float) I = tensor(int32)
EmbedLayerNormalization	in input_ids:T1 in segment_ids:T1 in word_embedding:T in position_embedding:T in segment_embedding:T in gamma:T in beta:T in mask:T1 in position_ids:T1 out output:T out mask_index:T1 out embedding_sum:T	1+	T = tensor(float), tensor(float16)
FastGelu	in X:T in bias:T out Y:T	1+	T = tensor(bfloat16), tensor(float), tensor(float16)
FusedConv	in X:T in W:T in B:T in Z:T out Y:T	1+	T = tensor(float)
FusedMatMul	in A:T in B:T out Y:T	1+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
GatedRelativePositionBias	in query_layer:T in query_bias:T in rel_pos:T in weight:T in bias:T in eco_a:T in token_offset:M out output:T	1+	T = tensor(float), tensor(float16)
Gelu	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
GreedySearch	in input_ids:I in max_length:I in min_length:I in repetition_penalty:T in vocab_mask:I in prefix_vocab_mask:I in attention_mask:I out sequences:I	1+	T = tensor(float), tensor(float16)
GridSample	in X:T1 in Grid:T1 out Y:T2	1+	T1 = tensor(float) T2 = tensor(float)
GroupNorm	in X:T in gamma:M in beta:M out Y:T	1+	T = tensor(float), tensor(float16)
GroupQueryAttention	in query:T in key:T in value:T in past_key:T in past_value:T in past_sequence_length:M out output:T out present_key:T out present_value:T	1+	M = tensor(int32), tensor(int64) T = tensor(float16)
Inverse	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
Irfft	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
LongformerAttention	in input:T in weight:T in bias:T in mask:T in global_weight:T in global_bias:T in global:G out output:T	1+	T = tensor(float), tensor(float16)
MatMulNBits	in A:T1 in B:T2 in scales:T1 in zero_points:T2 out Y:T1	1+	T1 = tensor(float), tensor(float16) T2 = tensor(uint8)
MultiHeadAttention	in query:T in key:T in value:T in bias:T in key_padding_mask:M in relative_position_bias:T in past_key:T in past_value:T out output:T out present_key:T out present_value:T	1+	T = tensor(float), tensor(float16)
NGramRepeatBlock	in input_ids:Tid in scores:T out scores_out:T	1+	T = tensor(float) Tid = tensor(int64)
NhwcConv	in X:T in W:T in B:T out Y:T	1+	T = tensor(float), tensor(float16)
PackedAttention	in input:T in weights:T in bias:T in token_offset:M in cumulative_sequence_length:M in relative_position_bias:T out output:T	1+	T = tensor(float), tensor(float16)
PackedMultiHeadAttention	in query:T in key:T in value:T in bias:T in token_offset:M in cumulative_sequence_length:M in relative_position_bias:T out output:T	1+	T = tensor(float), tensor(float16)
QAttention	in input:T1 in weight:T2 in bias:T3 in input_scale:T3 in weight_scale:T3 in mask_index:T4 in input_zero_point:T1 in weight_zero_point:T2 in past:T3 out output:T3 out present:T3	1+	T1 = tensor(int8) T2 = tensor(int8) T3 = tensor(float), tensor(float16) T4 = tensor(int32)
QOrderedAttention	in input:Q in scale_input:S in scale_Q_gemm:S in scale_K_gemm:S in scale_V_gemm:S in Q_weight:Q in K_weight:Q in V_weight:Q in scale_Q_weight:S in scale_K_weight:S in scale_V_weight:S in Q_bias:S in K_bias:S in V_bias:S in scale_QKT_gemm:S in scale_QKT_softmax:S in scale_values_gemm:S in mask_index:G in past:Q in relative_position_bias:S out output:Q	1+	G = tensor(int32) Q = tensor(int8) S = tensor(float)
QOrderedGelu	in X:Q in scale_X:S in scale_Y:S out Y:Q	1+	Q = tensor(int8) S = tensor(float)
QOrderedLayerNormalization	in X:Q in scale_X:S in scale:F in B:F in scale_Y:S out Y:Q	1+	F = tensor(float), tensor(float16) Q = tensor(int8) S = tensor(float)
QOrderedLongformerAttention	in input:Q in scale_input:S in weight:Q in scale_weight:S in bias:S in scale_bias:S in scale_qkv_gemm:S in mask:F in global_weight:Q in scale_global_weight:S in global_bias:S in scale_global_gemm:S in global:G in scale_output:S out output:Q	1+	F = tensor(float16) G = tensor(int32) Q = tensor(int8) S = tensor(float)
QOrderedMatMul	in A:Q in scale_A:S in B:Q in scale_B:S in scale_Y:S in bias:S in C:Q in scale_C:S out Y:Q	1+	Q = tensor(int8) S = tensor(float)
QuantizeLinear	in x:T1 in y_scale:T1 in y_zero_point:T2 out y:T2	1+	T1 = tensor(float16) T2 = tensor(int8), tensor(uint8)
QuantizeWithOrder	in input:F in scale_input:S out output:Q	1+	F = tensor(float), tensor(float16) Q = tensor(int8) S = tensor(float)
QuickGelu	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
RelativePositionBias	in bias_table:T in query_length:U in key_length:U out output:T	1+	T = tensor(float), tensor(float16)
RemovePadding	in input:T in sequence_token_count:M out output:T out token_offset:M out cumulated_seq_len:M out max_seq_len:M	1+	T = tensor(float), tensor(float16)
RestorePadding	in input:T in token_offset:M out output:T	1+	T = tensor(float), tensor(float16)
Rfft	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
RotaryEmbedding	in input:T in position_ids:M in cos_cache:T in sin_cache:T out output:T	1+	M = tensor(int64) T = tensor(float), tensor(float16)
Sampling	in input_ids:I in max_length:I in min_length:I in repetition_penalty:T in vocab_mask:I in prefix_vocab_mask:I in attention_mask:I in presence_mask:I in seed:I out sequences:I out filtered_logits:T	1+	T = tensor(float), tensor(float16)
SkipLayerNormalization	in input:T in skip:T in gamma:T in beta:T in bias:T out output:T out mean:U out inv_std_var:U out input_skip_bias_sum:T	1+	T = tensor(float), tensor(float16)
SkipSimplifiedLayerNormalization	in input:T in skip:T in gamma:T in bias:T out output:T out mean:U out inv_std_var:U out input_skip_bias_sum:T	1+	T = tensor(float), tensor(float16)
TransposeMatMul	in A:T in B:T out Y:T	1+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
Trilu	in X:T in k:tensor(int64) out Y:T	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
UnfoldTensor	in input:T out output:T	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
WhisperBeamSearch	in input_ids:F in max_length:I in min_length:I in num_beams:I in num_return_sequences:I in length_penalty:T in repetition_penalty:T in vocab_mask:M in prefix_vocab_mask:M in attention_mask:I in decoder_input_ids:I in logits_processor:I in cross_qk_layer_head:I in extra_decoding_ids:I out sequences:I out sequences_scores:T out scores:T out cross_qk:V out non_speech_probs:T	1+	T = tensor(float), tensor(float16)

Operators implemented by DmlExecutionProvider

Op Name	Parameters	OpSet Version	Types Supported
Operator Domain: ai.onnx
Abs	in X:T out Y:T	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
		6+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
Acos	in input:T out output:T	7+	T = tensor(float), tensor(float16)
Acosh	in input:T out output:T	9+	T = tensor(float), tensor(float16)
Add	in A:T in B:T out C:T	14+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		7+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Affine	in X:T out Y:T	1+	T = tensor(float), tensor(float16)
And	in A:T in B:T out C:T1	7+	T = tensor(bool)
ArgMax	in data:T out reduced:tensor(int64)	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		12+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ArgMin	in data:T out reduced:tensor(int64)	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		12+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Asin	in input:T out output:T	7+	T = tensor(float), tensor(float16)
Asinh	in input:T out output:T	9+	T = tensor(float), tensor(float16)
Atan	in input:T out output:T	7+	T = tensor(float), tensor(float16)
Atanh	in input:T out output:T	9+	T = tensor(float), tensor(float16)
AveragePool	in X:T out Y:T	11+	T = tensor(float), tensor(float16)
		10+	T = tensor(float), tensor(float16)
		7+	T = tensor(float), tensor(float16)
BatchNormalization	in X:T in scale:T in B:T in input_mean:U in input_var:U out Y:T out running_mean:U out running_var:U or in X:T in scale:T in B:T in mean:T in var:T out Y:T out mean:T out var:T out saved_mean:T out saved_var:T or in X:T in scale:T1 in B:T1 in input_mean:T2 in input_var:T2 out Y:T out running_mean:T2 out running_var:T2	15+	T = tensor(float), tensor(float16)
		14+	T = tensor(float), tensor(float16)
		9+	T = tensor(float), tensor(float16)
		7+	T = tensor(float), tensor(float16)
BitShift	in X:T in Y:T out Z:T	11+	T = tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseAnd	in A:T in B:T out C:T	18+	T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseNot	in X:T out Y:T	18+	T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseOr	in A:T in B:T out C:T	18+	T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseXor	in A:T in B:T out C:T	18+	T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Cast	in input:T1 out output:T2	13+	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		9+	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		6+	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
CastLike	in input:T1 in target_type:T2 out output:T2	15+	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Ceil	in X:T out Y:T	13+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
Celu	in X:T out Y:T	12+	T = tensor(float), tensor(float16)
Clip	in input:T in min:T in max:T out output:T or in input:T out output:T	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		12+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
Concat	in inputs:T out concat_result:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		4+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ConcatFromSequence	in input_sequence:S out concat_result:T	11+	T = seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ConstantOfShape	in input:T1 out output:T2	9+	T1 = tensor(int64) T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Conv	in X:T in W:T in B:T out Y:T	11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
ConvInteger	in x:T1 in w:T2 in x_zero_point:T1 in w_zero_point:T2 out y:T3	10+	T1 = tensor(int8), tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(int32)
ConvTranspose	in X:T in W:T in B:T out Y:T	11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
Cos	in input:T out output:T	7+	T = tensor(float), tensor(float16)
Cosh	in input:T out output:T	9+	T = tensor(float), tensor(float16)
Crop	in input:T out output:T	1+	T = tensor(float), tensor(float16)
CumSum	in x:T in axis:T2 out y:T	14+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		11+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
DFT	in input:T1 in dft_length:T2 in axis:tensor(int64) out output:T1 or in input:T1 in dft_length:T2 out output:T1	17+	T1 = tensor(float), tensor(float16) T2 = tensor(int64)
DepthToSpace	in input:T out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
DequantizeLinear	in x:T in x_scale:tensor(float) in x_zero_point:T out y:tensor(float) or in x:T1 in x_scale:T2 in x_zero_point:T1 out y:T2	13+	T = tensor(int32), tensor(int8), tensor(uint8)
		10+	T = tensor(int32), tensor(int8), tensor(uint8)
Div	in A:T in B:T out C:T	14+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		7+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Dropout	in data:T in ratio:T1 in training_mode:T2 out output:T out mask:T2 or in data:T out output:T out mask:T or in data:T out output:T out mask:T1	7+	T = tensor(float), tensor(float16)
DynamicQuantizeLinear	in x:T1 out y:T2 out y_scale:tensor(float) out y_zero_point:T2	11+	T1 = tensor(float) T2 = tensor(uint8)
Einsum	in Inputs:T out Output:T	12+	T = tensor(float), tensor(float16)
Elu	in X:T out Y:T	6+	T = tensor(float), tensor(float16)
Equal	in A:T in B:T out C:T1	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		11+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		7+	T = tensor(float), tensor(float16) T1 = tensor(bool)
Erf	in input:T out output:T	13+	T = tensor(float), tensor(float16)
		9+	T = tensor(float), tensor(float16)
Exp	in input:T out output:T	13+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
Expand	in input:T in shape:tensor(int64) out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		8+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
EyeLike	in input:T1 out output:T2	9+	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Flatten	in input:T out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		9+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Floor	in X:T out Y:T	13+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
GRU	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T out Y:T out Y_h:T	14+	T = tensor(float), tensor(float16)
		7+	T = tensor(float), tensor(float16)
Gather	in data:T in indices:Tind out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		1+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
GatherElements	in data:T in indices:Tind out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
GatherND	in data:T in indices:tensor(int64) out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		12+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Gemm	in A:T in B:T in C:T out Y:T	13+	T = tensor(float), tensor(float16)
		11+	T = tensor(float), tensor(float16)
		9+	T = tensor(float), tensor(float16)
		7+	T = tensor(float), tensor(float16)
GlobalAveragePool	in X:T out Y:T	1+	T = tensor(float), tensor(float16)
GlobalLpPool	in X:T out Y:T	2+	T = tensor(float), tensor(float16)
GlobalMaxPool	in X:T out Y:T	1+	T = tensor(float), tensor(float16)
Greater	in A:T in B:T out C:T1	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		9+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		7+	T = tensor(float), tensor(float16) T1 = tensor(bool)
GreaterOrEqual	in A:T in B:T out C:T1	16+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		12+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
GridSample	in X:T1 in grid:T2 out Y:T1	16+	T1 = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T2 = tensor(float), tensor(float16)
HardSigmoid	in X:T out Y:T	6+	T = tensor(float), tensor(float16)
Hardmax	in input:T out output:T	13+	T = tensor(float), tensor(float16)
		11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
Identity	in input:T out output:T or in input:V out output:V	16+	V = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		14+	V = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
If	in cond:B out outputs:V	19+	B = tensor(bool) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		16+	B = tensor(bool) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	B = tensor(bool) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	B = tensor(bool) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		7+	B = tensor(bool) V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ImageScaler	in input:T out output:T	1+	T = tensor(float), tensor(float16)
InstanceNormalization	in input:T in scale:T in B:T out output:T	6+	T = tensor(float), tensor(float16)
IsInf	in X:T1 out Y:T2	10+	T1 = tensor(float) T2 = tensor(bool)
IsNaN	in X:T1 out Y:T2	13+	T1 = tensor(float), tensor(float16) T2 = tensor(bool)
		9+	T1 = tensor(float), tensor(float16) T2 = tensor(bool)
LRN	in X:T out Y:T	13+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
LSTM	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T in initial_c:T in P:T out Y:T out Y_h:T out Y_c:T	14+	T = tensor(float), tensor(float16)
		7+	T = tensor(float), tensor(float16)
LayerNormalization	in X:T in Scale:T in B:T out Y:T out Mean:U out InvStdDev:U or in X:T in Scale:V in B:V out Y:V out Mean:U out InvStdDev:U	17+	T = tensor(float), tensor(float16) U = tensor(float)
		1+	T = tensor(float), tensor(float16) V = tensor(float), tensor(float16)
LeakyRelu	in X:T out Y:T	16+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
Less	in A:T in B:T out C:T1	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		9+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		7+	T = tensor(float), tensor(float16) T1 = tensor(bool)
LessOrEqual	in A:T in B:T out C:T1	16+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
		12+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(bool)
Log	in input:T out output:T	13+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
LogSoftmax	in input:T out output:T	13+	T = tensor(float), tensor(float16)
		11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
LpNormalization	in input:T out output:T	1+	T = tensor(float), tensor(float16)
LpPool	in X:T out Y:T	11+	T = tensor(float), tensor(float16)
		2+	T = tensor(float), tensor(float16)
MatMul	in A:T in B:T out Y:T	13+	T = tensor(float), tensor(float16)
		9+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
MatMulInteger	in A:T1 in B:T2 in a_zero_point:T1 in b_zero_point:T2 out Y:T3	10+	T1 = tensor(int8), tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(int32)
Max	in data_0:T out max:T	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		12+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		8+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
MaxPool	in X:T out Y:T or in X:T out Y:T out Indices:I	12+	I = tensor(int64) T = tensor(float), tensor(float16), tensor(int8), tensor(uint8)
		11+	I = tensor(int64) T = tensor(float), tensor(float16), tensor(int8), tensor(uint8)
		10+	I = tensor(int64) T = tensor(float), tensor(float16), tensor(int8), tensor(uint8)
		8+	I = tensor(int64) T = tensor(float), tensor(float16), tensor(int8), tensor(uint8)
		1+	T = tensor(float), tensor(float16)
MaxRoiPool	in X:T in rois:T out Y:T	1+	T = tensor(float), tensor(float16)
MaxUnpool	in X:T1 in I:T2 in output_shape:T2 out output:T1	11+	T1 = tensor(float), tensor(float16) T2 = tensor(int64)
		9+	T1 = tensor(float), tensor(float16) T2 = tensor(int64)
Mean	in data_0:T out mean:T	13+	T = tensor(float), tensor(float16)
		8+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
MeanVarianceNormalization	in X:T out Y:T or in input:T out output:T	13+	T = tensor(float), tensor(float16)
		9+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
MemcpyFromHost	in X:T out Y:T	1+	T = seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
MemcpyToHost	in X:T out Y:T	1+	T = seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Min	in data_0:T out min:T	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		12+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		8+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
Mod	in A:T in B:T out C:T	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
		10+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
Mul	in A:T in B:T out C:T	14+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		7+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Neg	in X:T out Y:T	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
		6+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
NonZero	in X:T out Y:tensor(int64)	13+	T = tensor(bool), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
		9+	T = tensor(bool), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
Not	in X:T out Y:T	1+	T = tensor(bool)
OneHot	in indices:T1 in depth:T2 in values:T3 out output:T3	11+	T1 = tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T3 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		9+	T1 = tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T3 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
OptionalGetElement	in input:O out output:V	18+	O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		15+	O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)) V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
OptionalHasElement	in input:O out output:B	18+	B = tensor(bool) O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		15+	B = tensor(bool) O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8))
Or	in A:T in B:T out C:T1	7+	T = tensor(bool)
PRelu	in X:T in slope:T out Y:T	16+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8)
		9+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8)
		7+	T = tensor(float), tensor(float16)
Pad	in data:T in pads:tensor(int64) in constant_value:T in axes:Tind out output:T or in data:T in pads:tensor(int64) in constant_value:T out output:T or in data:T out output:T	18+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		2+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ParametricSoftplus	in X:T out Y:T	1+	T = tensor(float), tensor(float16)
Pow	in X:T in Y:T out Z:T or in X:T in Y:T1 out Z:T	15+	T = tensor(float), tensor(float16), tensor(int32) T1 = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
		13+	T = tensor(float), tensor(float16), tensor(int32) T1 = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
		12+	T = tensor(float), tensor(float16), tensor(int32) T1 = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
		7+	T = tensor(float), tensor(float16)
QLinearConv	in x:T1 in x_scale:tensor(float) in x_zero_point:T1 in w:T2 in w_scale:tensor(float) in w_zero_point:T2 in y_scale:tensor(float) in y_zero_point:T3 in B:T4 out y:T3	10+	T1 = tensor(int8), tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(int8), tensor(uint8) T4 = tensor(int32)
QLinearMatMul	in a:T1 in a_scale:tensor(float) in a_zero_point:T1 in b:T2 in b_scale:tensor(float) in b_zero_point:T2 in y_scale:tensor(float) in y_zero_point:T3 out y:T3	10+	T1 = tensor(int8), tensor(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(int8), tensor(uint8)
QuantizeLinear	in x:T1 in y_scale:T1 in y_zero_point:T2 out y:T2 or in x:T1 in y_scale:tensor(float) in y_zero_point:T2 out y:T2	13+	T1 = tensor(float), tensor(int32) T2 = tensor(int8), tensor(uint8)
		10+	T1 = tensor(float), tensor(int32) T2 = tensor(int8), tensor(uint8)
RNN	in X:T in W:T in R:T in B:T in sequence_lens:T1 in initial_h:T out Y:T out Y_h:T	14+	T = tensor(float), tensor(float16)
		7+	T = tensor(float), tensor(float16)
Range	in start:T in limit:T in delta:T out output:T	11+	T = tensor(float), tensor(int16), tensor(int32), tensor(int64)
Reciprocal	in X:T out Y:T	13+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
ReduceL1	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		11+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		1+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
ReduceL2	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13+	T = tensor(float), tensor(float16)
		11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
ReduceLogSum	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13+	T = tensor(float), tensor(float16)
		11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
ReduceLogSumExp	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13+	T = tensor(float), tensor(float16)
		11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
ReduceMax	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		12+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
ReduceMean	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13+	T = tensor(float), tensor(float16)
		11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
ReduceMin	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		12+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
ReduceProd	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		11+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		1+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
ReduceSum	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	13+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		11+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		1+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
ReduceSumSquare	in data:T in axes:tensor(int64) out reduced:T or in data:T out reduced:T	18+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		13+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		11+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		1+	T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Relu	in X:T out Y:T	14+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8)
		13+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
Reshape	in data:T in shape:tensor(int64) out reshaped:T or in data:T out reshaped:T	14+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		5+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Resize	in X:T in scales:tensor(float) out Y:T or in X:T1 in roi:T2 in scales:tensor(float) in sizes:tensor(int64) out Y:T1	13+	T1 = tensor(float), tensor(float16) T2 = tensor(float), tensor(float16)
		11+	T1 = tensor(float), tensor(float16) T2 = tensor(float), tensor(float16)
		10+	T = tensor(float), tensor(float16)
ReverseSequence	in input:T in sequence_lens:tensor(int64) out Y:T	10+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
RoiAlign	in X:T1 in rois:T1 in batch_indices:T2 out Y:T1	16+	T1 = tensor(float), tensor(float16) T2 = tensor(int32), tensor(int64)
		10+	T1 = tensor(float), tensor(float16) T2 = tensor(int32), tensor(int64)
Round	in X:T out Y:T	11+	T = tensor(float), tensor(float16)
STFT	in signal:T1 in frame_step:T2 in window:T1 in frame_length:T2 out output:T1	17+	T1 = tensor(float), tensor(float16) T2 = tensor(int32), tensor(int64)
ScaledTanh	in input:T out output:T	1+	T = tensor(float), tensor(float16)
Scatter	in data:T in indices:Tind in updates:T out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		9+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
ScatterElements	in data:T in indices:Tind in updates:T out output:T	16+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
ScatterND	in data:T in indices:tensor(int64) in updates:T out output:T	16+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Selu	in X:T out Y:T	6+	T = tensor(float), tensor(float16)
SequenceAt	in input_sequence:S in position:I out tensor:T	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)) T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SequenceConstruct	in inputs:T out output_sequence:S	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)) T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SequenceEmpty	out output:S	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceErase	in input_sequence:S in position:I out output_sequence:S	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceInsert	in input_sequence:S in tensor:T in position:I out output_sequence:S	11+	I = tensor(int32), tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceLength	in input_sequence:S out length:I	11+	I = tensor(int64) S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
Shape	in data:T out shape:T1	15+	T = seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		13+	T = seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		1+	T = seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
Shrink	in input:T out output:T	9+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
Sigmoid	in X:T out Y:T	13+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
Sign	in input:T out output:T	13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		9+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sin	in input:T out output:T	7+	T = tensor(float), tensor(float16)
Sinh	in input:T out output:T	9+	T = tensor(float), tensor(float16)
Size	in data:T out size:T1	13+	T = seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
		1+	T = seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) T1 = tensor(int64)
Slice	in data:T in starts:Tind in ends:Tind in axes:Tind in steps:Tind out output:T or in data:T out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		10+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) Tind = tensor(int32), tensor(int64)
		1+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Softmax	in input:T out output:T	13+	T = tensor(float), tensor(float16)
		11+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
Softplus	in X:T out Y:T	1+	T = tensor(float), tensor(float16)
Softsign	in input:T out output:T	1+	T = tensor(float), tensor(float16)
SpaceToDepth	in input:T out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Split	in input:T in split:T out outputs...:T or in input:T in split:tensor(int64) out outputs:T or in input:T out outputs:T	18+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		2+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sqrt	in X:T out Y:T	13+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
Squeeze	in data:T in axes:tensor(int64) out squeezed:T or in data:T out squeezed:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sub	in A:T in B:T out C:T	14+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		13+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		7+	T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sum	in data_0:T out sum:T	13+	T = tensor(float), tensor(float16)
		8+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
Tan	in input:T out output:T	7+	T = tensor(float), tensor(float16)
Tanh	in input:T out output:T	13+	T = tensor(float), tensor(float16)
		6+	T = tensor(float), tensor(float16)
ThresholdedRelu	in X:T out Y:T	10+	T = tensor(float), tensor(float16)
		1+	T = tensor(float), tensor(float16)
Tile	in input:T in repeats:T1 out output:T or in input:T in tiles:T in axis:T out output:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		6+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
TopK	in X:T in K:tensor(int64) out Values:T out Indices:I or in X:T out Values:T out Indices:I	11+	I = tensor(int64) T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		10+	I = tensor(int64) T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	I = tensor(int64) T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Transpose	in data:T out transposed:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Trilu	in input:T in k:tensor(int64) out output:T	14+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Unsqueeze	in data:T in axes:tensor(int64) out expanded:T or in data:T out expanded:T	13+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		11+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		1+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Upsample	in X:T in scales:tensor(float) out Y:T or in X:T out Y:T	10+	T = tensor(float), tensor(float16)
		9+	T = tensor(float), tensor(float16)
		7+	T = tensor(float), tensor(float16)
Where	in condition:B in X:T in Y:T out output:T	16+	B = tensor(bool) T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		9+	B = tensor(bool) T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Xor	in A:T in B:T out C:T1	7+	T = tensor(bool)


Operator Domain: com.microsoft
Attention	in input:T in weights:T in bias:T in mask_index:M in past:T in relative_position_bias:T in past_sequence_length:M out output:T out present:T	1+	M = tensor(int32) T = tensor(float), tensor(float16)
BiasAdd	in X:T in bias:T in skip:T out Y:T	1+	T = tensor(float), tensor(float16)
BiasGelu	in A:T in B:T out C:T	1+	T = tensor(float), tensor(float16)
BiasSplitGelu	in X:T in bias:T out Y:T	1+	T = tensor(float), tensor(float16)
ConvTransposeWithDynamicPads	in X:T in W:T in Pads:tensor(int64) in B:T out Y:T	1+	T = tensor(float), tensor(float16)
DequantizeLinear	in x:T1 in x_scale:T2 in x_zero_point:T1 out y:T2	1+	T1 = tensor(int32), tensor(int8), tensor(uint8) T2 = tensor(float), tensor(float16)
EmbedLayerNormalization	in input_ids:T1 in segment_ids:T1 in word_embedding:T in position_embedding:T in segment_embedding:T in gamma:T in beta:T in mask:T1 in position_ids:T1 out output:T out mask_index:T1 out embedding_sum:T	1+	T = tensor(float), tensor(float16)
FusedMatMul	in A:T in B:T out Y:T	1+	T = tensor(float), tensor(float16)
FusedMatMulActivation	in A:T in B:T out Y:T	1+	T = tensor(float), tensor(float16)
Gelu	in X:T out Y:T	1+	T = tensor(float), tensor(float16)
GroupNorm	in X:T in gamma:M in beta:M out Y:T	1+	M = tensor(float), tensor(float16) T = tensor(float), tensor(float16)
MultiHeadAttention	in query:T in key:T in value:T in bias:T in key_padding_mask:M in relative_position_bias:T in past_key:T in past_value:T out output:T out present_key:T out present_value:T	1+	M = tensor(int32) T = tensor(float), tensor(float16)
NhwcConv	in X:T in W:T in B:T out Y:T	1+	T = tensor(float), tensor(float16)
QLinearAdd	in A:T in A_scale:tensor(float) in A_zero_point:T in B:T in B_scale:tensor(float) in B_zero_point:T in C_scale:tensor(float) in C_zero_point:T out C:T	1+	T = tensor(int8), tensor(uint8)
QLinearSigmoid	in X:T in X_scale:tensor(float) in X_zero_point:T in Y_scale:tensor(float) in Y_zero_point:T out Y:T	1+	T = tensor(int8), tensor(uint8)
QuantizeLinear	in x:T1 in y_scale:T1 in y_zero_point:T2 out y:T2	1+	T1 = tensor(float), tensor(float16), tensor(int32) T2 = tensor(int8), tensor(uint8)
QuickGelu	in X:T out Y:T	1+	T = tensor(float), tensor(float16)
SkipLayerNormalization	in input:T in skip:T in gamma:T in beta:T in bias:T out output:T out mean:U out inv_std_var:U out input_skip_bias_sum:T	1+	T = tensor(float), tensor(float16)


Operator Domain: com.microsoft.dml
DmlFusedAdd	in A:T in B:T out C:T	1+	T = tensor(float), tensor(float16)
DmlFusedBatchNormalization	in X:T in scale:T in B:T in mean:T in var:T out Y:T out mean:T out var:T out saved_mean:T out saved_var:T	1+	T = tensor(float), tensor(float16)
DmlFusedConv	in X:T in W:T in B:T out Y:T	1+	T = tensor(float), tensor(float16)
DmlFusedConvTranspose	in X:T in W:T in B:T out Y:T	1+	T = tensor(float), tensor(float16)
DmlFusedGemm	in A:T in B:T in C:T out Y:T	1+	T = tensor(float), tensor(float16)
DmlFusedInstanceNormalization	in input:T in scale:T in B:T out output:T	1+	T = tensor(float), tensor(float16)
DmlFusedMatMul	in A:T in B:T out Y:T	1+	T = tensor(float), tensor(float16)
DmlFusedMeanVarianceNormalization	in input:T out output:T	1+	T = tensor(float), tensor(float16)
DmlFusedSum	in data_0:T out sum:T	1+	T = tensor(float), tensor(float16)

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