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### Description update with ONNX 1.16.0 branch according to https://github.com/microsoft/onnxruntime/blob/main/docs/How_To_Update_ONNX_Dev_Notes.md ONNX 1.16.0 release notes: https://github.com/onnx/onnx/releases/tag/v1.16.0 #### Updated ops for CPU EP: - DequantizeLinear(21) - Added int16 and uint16 support + various optimizer tests - Missing int4 and uint4 support - Missing block dequantization support - QuantizeLinear(21) - Added int16 and uint16 support + various optimizer tests - Missing int4 and uint4 support - Missing block quantization support - Cast(21) - Missing int4 and uint4 support - CastLike(21) - Missing int4 and uint4 support - ConstantOfShape(21) - Missing int4 and uint4 support - Identity(21) - Missing int4 and uint4 support - If(21) - Missing int4 and uint4 support - Loop(21) - Missing int4 and uint4 support - Reshape(21) - Missing int4 and uint4 support - Scan(21) - Missing int4 and uint4 support - Shape(21) - Missing int4 and uint4 support - Size(21) - Missing int4 and uint4 support - Flatten(21) - Missing float8e4m3fnuz, float8e5m2, float8e5m2fnuz, int4, and uint4 support - Pad(21) - Missing float8e4m3fnuz, float8e5m2, float8e5m2fnuz, int4, and uint4 support - Squeeze(21) - Missing float8e4m3fnuz, float8e5m2, float8e5m2fnuz, int4, and uint4 support - Transpose(21) - Missing float8e4m3fnuz, float8e5m2, float8e5m2fnuz, int4, and uint4 support - Unsqueeze(21) - Missing float8e4m3fnuz, float8e5m2, float8e5m2fnuz, int4, and uint4 support #### Unimplemented opset 21 features/ops - int4 and uint4 data type - QLinearMatMul(21) - GroupNormalization(21) - ai.onnx.ml.TreeEnsemble(5) ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. --> ### Disabled tests #### ORT Training orttraining/orttraining/test/python/orttraining_test_ort_apis_py_bindings.py - test_ort_custom_ops: Potential shape inference bug for custom ops #### Python quantization unit tests test/onnx/python/quantization (shape inference bug) - test_op_conv_transpose.py: test_quantize_conv_transpose_u8u8_fp16 - test_op_conv_transpose.py: test_quantize_conv_transpose_s8s8_fp16 - test_op_gemm.py: test_quantize_qop_gemm_s8s8 - test_op_gemm.py: test_quantize_qop_gemm_e4m3fn_same - test_op_gemm.py: test_quantize_qop_gemm_e4m3fn_p3 - test_op_matmul.py: test_quantize_matmul_u8u8_f16 - test_op_matmul.py: test_quantize_matmul_s8s8_f16 - test_op_matmul.py: test_quantize_matmul_s8s8_f16_entropy - test_op_matmul.py: test_quantize_matmul_s8s8_f16_percentile - test_op_matmul.py: test_quantize_matmul_s8s8_f16_distribution - test_op_relu.py: test_quantize_qop_relu_s8s8 #### ONNX tests - test_maxpool_2d_ceil_output_size_reduce_by_one: ONNX 1.16.0 fixed a maxpool output size bug and added this test. Enable this test when [ORT PR](https://github.com/microsoft/onnxruntime/pull/18377) is merged. Refer to original [ONNX PR](https://github.com/onnx/onnx/pull/5741). - test_ai_onnx_ml_tree_ensemble_set_membership_cpu: new unimplemented op ai.onnx.ml.TreeEnsemble - test_ai_onnx_ml_tree_ensemble_single_tree_cpu: same - test_ai_onnx_ml_tree_ensemble_set_membership_cuda: same - test_ai_onnx_ml_tree_ensemble_single_tree_cuda: same - test_cast_INT4_to_FLOAT_cpu: ORT Cast(21) impl doesn't support int4 yet - test_cast_INT4_to_INT8_cpu: same - test_cast_UINT4_to_FLOAT_cpu: same - test_cast_UINT4_to_UINT8_cpu: same - test_cast_INT4_to_FLOAT_cuda - test_cast_INT4_to_INT8_cuda - test_cast_UINT4_to_FLOAT_cuda - test_cast_UINT4_to_UINT8_cuda - test_constantofshape_float_ones_cuda: ConstantOfShape(21) not implemented for cuda - test_constantofshape_int_shape_zero_cuda: same - test_constantofshape_int_zeros_cuda: same - test_flatten_axis0_cuda: Flatten(21) not implemented for cuda - test_flatten_axis1_cuda: same - test_flatten_axis2_cuda: same - test_flatten_axis3_cuda: same - test_flatten_default_axis_cuda: same - test_flatten_negative_axis1_cuda: same - test_flatten_negative_axis2_cuda: same - test_flatten_negative_axis3_cuda: same - test_flatten_negative_axis4_cuda: same - test_qlinearmatmul_2D_int8_float16_cpu: QLinearMatMul(21) for onnx not implemented in ORT yet - test_qlinearmatmul_2D_int8_float32_cpu: same - test_qlinearmatmul_2D_uint8_float16_cpu: same - test_qlinearmatmul_2D_uint8_float32_cpu: same - test_qlinearmatmul_3D_int8_float16_cpu: same - test_qlinearmatmul_3D_int8_float32_cpu: same - test_qlinearmatmul_3D_uint8_float16_cpu: same - test_qlinearmatmul_3D_uint8_float32_cpu: same - test_qlinearmatmul_2D_int8_float16_cuda: same - test_qlinearmatmul_2D_int8_float32_cuda: same - test_qlinearmatmul_2D_uint8_float16_cuda: same - test_qlinearmatmul_2D_uint8_float32_cuda: same - test_qlinearmatmul_3D_int8_float16_cuda: same - test_qlinearmatmul_3D_int8_float32_cuda: same - test_qlinearmatmul_3D_uint8_float16_cuda: same - test_qlinearmatmul_3D_uint8_float32_cuda: same - test_size_cuda: Size(21) not implemented for cuda - test_size_example_cuda: same - test_dequantizelinear_blocked: Missing implementation for block dequant for DequantizeLinear(21) - test_quantizelinear_blocked_asymmetric: Missing implementation for block quant for QuantizeLinear(21) - test_quantizelinear_blocked_symmetric: Missing implementation for block quant for QuantizeLinear(21) --------- Signed-off-by: liqunfu <liqun.fu@microsoft.com> Signed-off-by: Ganesan Ramalingam <grama@microsoft.com> Co-authored-by: Ganesan Ramalingam <grama@microsoft.com> Co-authored-by: George Wu <jywu@microsoft.com> Co-authored-by: adrianlizarraga <adlizarraga@microsoft.com>
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Operators Support Table
The following table shows ai.onnx operators from which onnx opset version are currently supported by ONNX Runtime Web. For example, 4-6, 8+ means ONNX Runtime Web currently support opset version 4 to 6, 8 and above.
See Compatibility for a list of the supported platforms.
This file is automatically generated from the def files via this script. Do not modify directly.