onnxruntime/docs/OperatorKernels.md

Supported Operators and Data Types

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

Execution Providers

• CPUExecutionProvider
• CUDAExecutionProvider

---

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)
		[11, 12]	T = tensor(double), tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
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	11+	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	14+	T = 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)
Cast	in input:T1 out output:T2	13+	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(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)
		[6, 12]	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(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)
Ceil	in X:T out Y:T	13+	T = tensor(float)
		[6, 12]	T = 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(int64), tensor(int8), tensor(uint64), tensor(uint8)
		12	T = tensor(double), tensor(float), 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(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	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)
		[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)
DepthToSpace	in input:T out output:T	13+	T = tensor(float)
		[11, 12]	T = tensor(float)
		[1, 10]	T = tensor(float)
DequantizeLinear	in x:T in x_scale:tensor(float) in x_zero_point:T out y:tensor(float)	13+	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) T1 = tensor(bool)
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	13+	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(float)
		[6, 12]	T = 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) Tind = 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) Tind = 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) Tind = 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	12+	T = tensor(double), tensor(float), tensor(int32), tensor(int64) T1 = tensor(bool)
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	14+	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	13+	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(float), tensor(float16) T2 = tensor(bool)
		[9, 12]	T1 = 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	1+	T = tensor(double), tensor(float)
LeakyRelu	in X:T out Y:T	6+	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	12+	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	13+	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	11+	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(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)
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) T1 = 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)
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	9+	T = tensor(float)
		[7, 8]	T = tensor(float)
Pad	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(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	13+	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(uint8) T2 = tensor(int8), tensor(uint8) T3 = 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(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(uint8)
QuantizeLinear	in x:T1 in y_scale:tensor(float) in y_zero_point:T2 out y:T2	13+	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 out reduced:T	13+	T = tensor(float), tensor(int32)
		[11, 12]	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
ReduceL2	in data:T out reduced:T	13+	T = tensor(float), tensor(int32)
		[11, 12]	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
ReduceLogSum	in data:T out reduced:T	13+	T = tensor(float), tensor(int32)
		[11, 12]	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
ReduceLogSumExp	in data:T out reduced:T	13+	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)
ReduceMax	in data:T out reduced:T	13+	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 out reduced:T	13+	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 out reduced:T	13+	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 out reduced:T	13+	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 out reduced:T	13+	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)
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	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) 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	13+	T1 = tensor(float), tensor(int32), tensor(uint8)
		[11, 12]	T1 = tensor(float), tensor(int32), tensor(uint8)
		10	T = tensor(float), 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(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
RoiAlign	in X:T1 in rois:T1 in batch_indices:T2 out Y:T1	10+	T = tensor(double), tensor(float) T2 = tensor(int64)
Round	in X:T out Y:T	11+	T = tensor(double), tensor(float), tensor(float16)
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	11+	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)
		[9, 10]	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)
		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	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)
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(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	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)
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:T out Y:T out inv_std_var:U	1+	T = 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	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)
		[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(float)
		[1, 12]	T = 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	13+	T = tensor(float), tensor(int32), tensor(int64), tensor(string), tensor(uint8)
		[11, 12]	T = tensor(float), tensor(int32), tensor(int64), tensor(string), tensor(uint8)
		[2, 10]	T = tensor(float), tensor(int32), tensor(int64), tensor(string), 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+	T = 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(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(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(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(uint8)
		[7, 8]	T = tensor(float), tensor(int32), tensor(uint8)
Where	in condition:B in X:T in Y:T out output:T	9+	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)	1+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64) T2 = tensor(int64), tensor(string)
TreeEnsembleRegressor	in X:T out Y:tensor(float)	1+	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 weight:T in bias:T in mask_index:M in past:T 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)
BiasGelu	in A:T in B:T out C:T	1+	T = tensor(float)
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+	T = tensor(float) T2 = tensor(int32)
DequantizeLinear	in x:T1 in x_scale:T2 in x_zero_point:T1 out y:T2	1+	T1 = tensor(int8), 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 out output:T out mask_index:T1	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)
Inverse	in X:T out Y:T	1+	T = tensor(double), tensor(float), tensor(float16)
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(uint8) T2 = tensor(int8), tensor(uint8) T3 = tensor(float)
MaxpoolWithMask	in X:T in M:tensor(int32) out Y:T	1+	X = 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)
NhwcMaxPool	in x:T out y:T	1+	T = 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)
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(uint8) T2 = tensor(int8), tensor(uint8) T3 = 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)
QuantizeLinear	in x:T1 in y_scale:T1 in y_zero_point:T2 out y:T2	1+	T1 = tensor(float) T2 = tensor(int8), tensor(uint8)
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)
SampleOp	in X:T out Y: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	1+	T = tensor(double), tensor(float)
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)
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	I = tensor(int64) T = tensor(double), tensor(float), tensor(float16)
		[7, 9]	I = tensor(int64) 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	14+	T = 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	13+	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(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(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(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)
DequantizeLinear	in x:T in x_scale:tensor(float) in x_zero_point:T out y:tensor(float)	10+	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(double), tensor(float), tensor(float16), tensor(int64) Tind = tensor(int64)
		12	T = tensor(double), tensor(float), tensor(float16), tensor(int64) Tind = 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	12+	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	14+	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	13+	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)
		[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	1+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16) U = tensor(double), tensor(float)
LeakyRelu	in X:T out Y:T	6+	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	12+	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	13+	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)
		[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+	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]	I = tensor(int64) 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(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)
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(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)
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)
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(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) T1 = 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	9+	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 out output:T or in data:T out output:T	13+	T = 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	13+	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:tensor(float) in y_zero_point:T2 out y:T2	10+	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)
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 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 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 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 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 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 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 out reduced:T	13+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int8), tensor(uint8)
		12	T = tensor(double), tensor(float), tensor(float16), tensor(int32), 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 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 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	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) 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+	T = 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	11+	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)
		[9, 10]	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)
		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	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) 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)
SimplifiedLayerNormalization	in X:T in scale:T out Y:T out inv_std_var:U	1+	T = tensor(double), tensor(float), tensor(float16) U = tensor(double), tensor(float)
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(float), 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(float), 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(float), 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) Tind = tensor(float), tensor(int32), tensor(int64)
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)
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	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)
		[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(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)
		10	I = tensor(int64) 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, 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)
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)
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	9+	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 weight:T in bias:T in mask_index:M in past:T out output:T out present: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(double), tensor(float), tensor(float16)
BiasSoftmax	in data:T in bias:T out output:T	1+	T = tensor(double), tensor(float), tensor(float16)
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)
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)
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 out output:T out mask_index:T1	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)
Gelu	in X:T out Y:T	1+	T = tensor(double), tensor(float), 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)
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)
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)
Rfft	in X:T out Y:T	1+	T = tensor(double), 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	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)