ir_version: 8 producer_name: "pytorch" producer_version: "2.2.1" model_version: 0 graph { name: "main_graph" node { input: "input" input: "ortshared_1_1_1_1_token_110" input: "ortshared_1_1_1_0_token_107" output: "/sincnet/wav_norm1d/InstanceNormalization_output_0" name: "/sincnet/wav_norm1d/InstanceNormalization" op_type: "InstanceNormalization" attribute { name: "epsilon" f: 9.999999747378752e-06 type: FLOAT } } node { input: "/sincnet/wav_norm1d/InstanceNormalization_output_0" output: "onnx::Gather_115" name: "Shape_111" op_type: "Shape" attribute { name: "start" i: 0 type: INT } } node { input: "onnx::Gather_115" input: "ortshared_7_0_1_1_token_113" output: "onnx::Equal_117" name: "Gather_113" op_type: "Gather" attribute { name: "axis" i: 0 type: INT } } node { input: "onnx::Equal_117" input: "ortshared_7_0_1_1_token_113" output: "onnx::Cast_119" name: "Equal_115" op_type: "Equal" } node { input: "onnx::Cast_119" output: "onnx::Abs_121" name: "If_117" op_type: "If" attribute { name: "then_branch" g { node { input: "/sincnet/wav_norm1d/InstanceNormalization_output_0" input: "/sincnet/conv1d.0/Concat_2_output_0" output: "122" name: "Conv_118" op_type: "Conv" attribute { name: "strides" ints: 10 type: INTS } attribute { name: "kernel_shape" ints: 251 type: INTS } attribute { name: "auto_pad" s: "NOTSET" type: STRING } attribute { name: "dilations" ints: 1 type: INTS } attribute { name: "pads" ints: 0 ints: 0 type: INTS } attribute { name: "group" i: 1 type: INT } } name: "sub_graph" doc_string: "" output { name: "122" type { tensor_type { elem_type: 1 shape { dim { dim_param: "Conv122_dim_0" } dim { dim_value: 80 } dim { dim_param: "Conv122_dim_2" } } } } } } type: GRAPH } attribute { name: "else_branch" g { node { input: "onnx::Gather_115" input: "126" input: "127" input: "125" output: "128" name: "Slice_124" op_type: "Slice" } node { input: "128" input: "129" output: "130" name: "Squeeze_126" op_type: "Squeeze" } node { input: "130" input: "135" output: "136" name: "Unsqueeze_132" op_type: "Unsqueeze" } node { input: "132" input: "134" input: "136" output: "137" name: "Concat_133" op_type: "Concat" attribute { name: "axis" i: 0 type: INT } } node { input: "/sincnet/wav_norm1d/InstanceNormalization_output_0" input: "137" output: "138" name: "Reshape_134" op_type: "Reshape" attribute { name: "allowzero" i: 0 type: INT } } node { input: "138" input: "/sincnet/conv1d.0/Concat_2_output_0" output: "batched_conv" name: "Conv_135" op_type: "Conv" attribute { name: "strides" ints: 10 type: INTS } attribute { name: "kernel_shape" ints: 251 type: INTS } attribute { name: "auto_pad" s: "NOTSET" type: STRING } attribute { name: "dilations" ints: 1 type: INTS } attribute { name: "pads" ints: 0 ints: 0 type: INTS } attribute { name: "group" i: 1 type: INT } } node { input: "batched_conv" output: "147" name: "Shape_143" op_type: "Shape" attribute { name: "start" i: 0 type: INT } } node { input: "147" input: "150" input: "151" input: "148" input: "153" output: "154" name: "Slice_150" op_type: "Slice" } node { input: "onnx::Gather_115" input: "141" input: "143" input: "140" input: "145" output: "146" name: "Slice_142" op_type: "Slice" } node { input: "146" input: "154" output: "155" name: "Concat_151" op_type: "Concat" attribute { name: "axis" i: 0 type: INT } } node { input: "batched_conv" input: "155" output: "156" name: "Reshape_152" op_type: "Reshape" attribute { name: "allowzero" i: 0 type: INT } } name: "sub_graph1" initializer { dims: 1 data_type: 7 name: "151" raw_data: "\377\377\377\377\377\377\377\177" } initializer { dims: 1 data_type: 7 name: "134" raw_data: "\001\000\000\000\000\000\000\000" } initializer { dims: 1 data_type: 7 name: "125" raw_data: "\000\000\000\000\000\000\000\000" } initializer { dims: 1 data_type: 7 name: "126" raw_data: "\377\377\377\377\377\377\377\377" } initializer { dims: 1 data_type: 7 name: "127" raw_data: "\377\377\377\377\377\377\377\177" } initializer { dims: 1 data_type: 7 name: "129" raw_data: "\000\000\000\000\000\000\000\000" } initializer { dims: 1 data_type: 7 name: "150" raw_data: "\376\377\377\377\377\377\377\377" } initializer { dims: 1 data_type: 7 name: "153" raw_data: "\001\000\000\000\000\000\000\000" } initializer { dims: 1 data_type: 7 name: "135" raw_data: "\000\000\000\000\000\000\000\000" } initializer { dims: 1 data_type: 7 name: "140" raw_data: "\000\000\000\000\000\000\000\000" } initializer { dims: 1 data_type: 7 name: "141" raw_data: "\000\000\000\000\000\000\000\000" } initializer { dims: 1 data_type: 7 name: "132" raw_data: "\377\377\377\377\377\377\377\377" } initializer { dims: 1 data_type: 7 name: "145" raw_data: "\001\000\000\000\000\000\000\000" } initializer { dims: 1 data_type: 7 name: "148" raw_data: "\000\000\000\000\000\000\000\000" } initializer { dims: 1 data_type: 7 name: "143" raw_data: "\377\377\377\377\377\377\377\377" } doc_string: "" output { name: "156" type { tensor_type { elem_type: 1 shape { dim { dim_param: "Reshape156_dim_0" } dim { dim_param: "Reshape156_dim_1" } dim { dim_param: "Reshape156_dim_2" } dim { dim_param: "Reshape156_dim_3" } } } } } } type: GRAPH } } node { input: "onnx::Abs_121" output: "/sincnet/Abs_output_0" name: "/sincnet/Abs" op_type: "Abs" } node { input: "/sincnet/Abs_output_0" output: "/sincnet/pool1d.0/MaxPool_output_0" name: "/sincnet/pool1d.0/MaxPool" op_type: "MaxPool" attribute { name: "storage_order" i: 0 type: INT } attribute { name: "pads" ints: 0 ints: 0 type: INTS } attribute { name: "ceil_mode" i: 0 type: INT } attribute { name: "strides" ints: 3 type: INTS } attribute { name: "kernel_shape" ints: 3 type: INTS } attribute { name: "auto_pad" s: "NOTSET" type: STRING } attribute { name: "dilations" ints: 1 type: INTS } } node { input: "/sincnet/pool1d.0/MaxPool_output_0" input: "sincnet.norm1d.0.weight" input: "sincnet.norm1d.0.bias" output: "/sincnet/norm1d.0/InstanceNormalization_output_0" name: "/sincnet/norm1d.0/InstanceNormalization" op_type: "InstanceNormalization" attribute { name: "epsilon" f: 9.999999747378752e-06 type: FLOAT } } node { input: "/sincnet/norm1d.0/InstanceNormalization_output_0" output: "/sincnet/LeakyRelu_output_0" name: "/sincnet/LeakyRelu" op_type: "LeakyRelu" attribute { name: "alpha" f: 0.009999999776482582 type: FLOAT } } node { input: "/sincnet/LeakyRelu_output_0" input: "sincnet.conv1d.1.weight" input: "sincnet.conv1d.1.bias" output: "/sincnet/conv1d.1/Conv_output_0" name: "/sincnet/conv1d.1/Conv" op_type: "Conv" attribute { name: "strides" ints: 1 type: INTS } attribute { name: "kernel_shape" ints: 5 type: INTS } attribute { name: "auto_pad" s: "NOTSET" type: STRING } attribute { name: "dilations" ints: 1 type: INTS } attribute { name: "pads" ints: 0 ints: 0 type: INTS } attribute { name: "group" i: 1 type: INT } } node { input: "/sincnet/conv1d.1/Conv_output_0" output: "/sincnet/pool1d.1/MaxPool_output_0" name: "/sincnet/pool1d.1/MaxPool" op_type: "MaxPool" attribute { name: "storage_order" i: 0 type: INT } attribute { name: "pads" ints: 0 ints: 0 type: INTS } attribute { name: "ceil_mode" i: 0 type: INT } attribute { name: "strides" ints: 3 type: INTS } attribute { name: "kernel_shape" ints: 3 type: INTS } attribute { name: "auto_pad" s: "NOTSET" type: STRING } attribute { name: "dilations" ints: 1 type: INTS } } node { input: "/sincnet/pool1d.1/MaxPool_output_0" input: "sincnet.norm1d.1.weight" input: "sincnet.norm1d.1.bias" output: "/sincnet/norm1d.1/InstanceNormalization_output_0" name: "/sincnet/norm1d.1/InstanceNormalization" op_type: "InstanceNormalization" attribute { name: "epsilon" f: 9.999999747378752e-06 type: FLOAT } } node { input: "/sincnet/norm1d.1/InstanceNormalization_output_0" output: "/sincnet/LeakyRelu_1_output_0" name: "/sincnet/LeakyRelu_1" op_type: "LeakyRelu" attribute { name: "alpha" f: 0.009999999776482582 type: FLOAT } } node { input: "/sincnet/LeakyRelu_1_output_0" input: "sincnet.conv1d.2.weight" input: "sincnet.conv1d.2.bias" output: "/sincnet/conv1d.2/Conv_output_0" name: "/sincnet/conv1d.2/Conv" op_type: "Conv" attribute { name: "strides" ints: 1 type: INTS } attribute { name: "kernel_shape" ints: 5 type: INTS } attribute { name: "auto_pad" s: "NOTSET" type: STRING } attribute { name: "dilations" ints: 1 type: INTS } attribute { name: "pads" ints: 0 ints: 0 type: INTS } attribute { name: "group" i: 1 type: INT } } node { input: "/sincnet/conv1d.2/Conv_output_0" output: "/sincnet/pool1d.2/MaxPool_output_0" name: "/sincnet/pool1d.2/MaxPool" op_type: "MaxPool" attribute { name: "storage_order" i: 0 type: INT } attribute { name: "pads" ints: 0 ints: 0 type: INTS } attribute { name: "ceil_mode" i: 0 type: INT } attribute { name: "strides" ints: 3 type: INTS } attribute { name: "kernel_shape" ints: 3 type: INTS } attribute { name: "auto_pad" s: "NOTSET" type: STRING } attribute { name: "dilations" ints: 1 type: INTS } } node { input: "/sincnet/pool1d.2/MaxPool_output_0" input: "sincnet.norm1d.2.weight" input: "sincnet.norm1d.2.bias" output: "/sincnet/norm1d.2/InstanceNormalization_output_0" name: "/sincnet/norm1d.2/InstanceNormalization" op_type: "InstanceNormalization" attribute { name: "epsilon" f: 9.999999747378752e-06 type: FLOAT } } node { input: "/sincnet/norm1d.2/InstanceNormalization_output_0" output: "/sincnet/LeakyRelu_2_output_0" name: "/sincnet/LeakyRelu_2" op_type: "LeakyRelu" attribute { name: "alpha" f: 0.009999999776482582 type: FLOAT } } node { input: "/sincnet/LeakyRelu_2_output_0" output: "/lstm/Shape" name: "/lstm/Shape" op_type: "Shape" attribute { name: "start" i: 0 type: INT } } node { input: "/lstm/Shape" input: "ortshared_7_1_3_0_token_104" output: "/lstm/Shape_output_0" name: "Gather" op_type: "Gather" attribute { name: "axis" i: 0 type: INT } doc_string: "Added in transpose optimizer" } node { input: "/lstm/Shape_output_0" input: "ortshared_7_0_1_0_token_105" output: "/lstm/Gather_output_0" name: "/lstm/Gather" op_type: "Gather" attribute { name: "axis" i: 0 type: INT } } node { input: "/lstm/Gather_output_0" input: "ortshared_7_1_1_2_token_111" output: "/lstm/Unsqueeze_output_0" name: "/lstm/Unsqueeze" op_type: "Unsqueeze" } node { input: "ortshared_7_1_1_0_token_106" input: "/lstm/Unsqueeze_output_0" input: "ortshared_7_1_1_3_token_114" output: "/lstm/Concat_output_0" name: "/lstm/Concat" op_type: "Concat" attribute { name: "axis" i: 0 type: INT } } node { input: "/lstm/Concat_output_0" output: "/lstm/ConstantOfShape_output_0" name: "/lstm/ConstantOfShape" op_type: "ConstantOfShape" attribute { name: "value" t { dims: 1 data_type: 1 raw_data: "\000\000\000\000" } type: TENSOR } } node { input: "/lstm/ConstantOfShape_output_0" input: "ortshared_7_1_1_5_token_116" input: "ortshared_7_1_1_0_token_106" input: "ortshared_7_1_1_2_token_111" output: "/lstm/Slice_7_output_0" name: "/lstm/Slice_7" op_type: "Slice" } node { input: "/lstm/ConstantOfShape_output_0" input: "ortshared_7_1_1_1_token_108" input: "ortshared_7_1_1_5_token_116" input: "ortshared_7_1_1_2_token_111" output: "/lstm/Slice_5_output_0" name: "/lstm/Slice_5" op_type: "Slice" } node { input: "/lstm/ConstantOfShape_output_0" input: "ortshared_7_1_1_4_token_115" input: "ortshared_7_1_1_1_token_108" input: "ortshared_7_1_1_2_token_111" output: "/lstm/Slice_3_output_0" name: "/lstm/Slice_3" op_type: "Slice" } node { input: "/lstm/ConstantOfShape_output_0" input: "ortshared_7_1_1_2_token_111" input: "ortshared_7_1_1_4_token_115" input: "ortshared_7_1_1_2_token_111" output: "/lstm/Slice_1_output_0" name: "/lstm/Slice_1" op_type: "Slice" } node { input: "/sincnet/LeakyRelu_2_output_0" output: "/lstm/Transpose_output_0" name: "/lstm/Transpose" op_type: "Transpose" attribute { name: "perm" ints: 2 ints: 0 ints: 1 type: INTS } } node { input: "/lstm/Transpose_output_0" input: "onnx::LSTM_784" input: "onnx::LSTM_785" input: "onnx::LSTM_783" input: "" input: "/lstm/Slice_1_output_0" input: "/lstm/Slice_1_output_0" output: "/lstm/LSTM_output_0" output: "/lstm/LSTM_output_1" output: "/lstm/LSTM_output_2" name: "/lstm/LSTM" op_type: "LSTM" attribute { name: "layout" i: 0 type: INT } attribute { name: "input_forget" i: 0 type: INT } attribute { name: "direction" s: "bidirectional" type: STRING } attribute { name: "hidden_size" i: 128 type: INT } } node { input: "/lstm/LSTM_output_0" output: "/lstm/Transpose_1_output_0" name: "/lstm/Transpose_1" op_type: "Transpose" attribute { name: "perm" ints: 0 ints: 2 ints: 1 ints: 3 type: INTS } } node { input: "/lstm/Transpose_1_output_0" input: "ortshared_7_1_3_1_token_112" output: "/lstm/Reshape_output_0" name: "/lstm/Reshape" op_type: "Reshape" attribute { name: "allowzero" i: 0 type: INT } } node { input: "/lstm/Reshape_output_0" input: "onnx::LSTM_827" input: "onnx::LSTM_828" input: "onnx::LSTM_826" input: "" input: "/lstm/Slice_3_output_0" input: "/lstm/Slice_3_output_0" output: "/lstm/LSTM_1_output_0" output: "/lstm/LSTM_1_output_1" output: "/lstm/LSTM_1_output_2" name: "/lstm/LSTM_1" op_type: "LSTM" attribute { name: "layout" i: 0 type: INT } attribute { name: "input_forget" i: 0 type: INT } attribute { name: "direction" s: "bidirectional" type: STRING } attribute { name: "hidden_size" i: 128 type: INT } } node { input: "/lstm/LSTM_1_output_0" output: "/lstm/Transpose_2_output_0" name: "/lstm/Transpose_2" op_type: "Transpose" attribute { name: "perm" ints: 0 ints: 2 ints: 1 ints: 3 type: INTS } } node { input: "/lstm/Transpose_2_output_0" input: "ortshared_7_1_3_1_token_112" output: "/lstm/Reshape_1_output_0" name: "/lstm/Reshape_1" op_type: "Reshape" attribute { name: "allowzero" i: 0 type: INT } } node { input: "/lstm/Reshape_1_output_0" input: "onnx::LSTM_870" input: "onnx::LSTM_871" input: "onnx::LSTM_869" input: "" input: "/lstm/Slice_5_output_0" input: "/lstm/Slice_5_output_0" output: "/lstm/LSTM_2_output_0" output: "/lstm/LSTM_2_output_1" output: "/lstm/LSTM_2_output_2" name: "/lstm/LSTM_2" op_type: "LSTM" attribute { name: "layout" i: 0 type: INT } attribute { name: "input_forget" i: 0 type: INT } attribute { name: "direction" s: "bidirectional" type: STRING } attribute { name: "hidden_size" i: 128 type: INT } } node { input: "/lstm/LSTM_2_output_0" output: "/lstm/Transpose_3_output_0" name: "/lstm/Transpose_3" op_type: "Transpose" attribute { name: "perm" ints: 0 ints: 2 ints: 1 ints: 3 type: INTS } } node { input: "/lstm/Transpose_3_output_0" input: "ortshared_7_1_3_1_token_112" output: "/lstm/Reshape_2_output_0" name: "/lstm/Reshape_2" op_type: "Reshape" attribute { name: "allowzero" i: 0 type: INT } } node { input: "/lstm/Reshape_2_output_0" input: "onnx::LSTM_913" input: "onnx::LSTM_914" input: "onnx::LSTM_912" input: "" input: "/lstm/Slice_7_output_0" input: "/lstm/Slice_7_output_0" output: "/lstm/LSTM_3_output_0" output: "/lstm/LSTM_3_output_1" output: "/lstm/LSTM_3_output_2" name: "/lstm/LSTM_3" op_type: "LSTM" attribute { name: "layout" i: 0 type: INT } attribute { name: "input_forget" i: 0 type: INT } attribute { name: "direction" s: "bidirectional" type: STRING } attribute { name: "hidden_size" i: 128 type: INT } } node { input: "/lstm/LSTM_3_output_0" output: "/lstm/Transpose_4_output_0" name: "/lstm/Transpose_4" op_type: "Transpose" attribute { name: "perm" ints: 0 ints: 2 ints: 1 ints: 3 type: INTS } } node { input: "/lstm/Transpose_4_output_0" input: "ortshared_7_1_3_1_token_112" output: "/lstm/Reshape_3_output_0" name: "/lstm/Reshape_3" op_type: "Reshape" attribute { name: "allowzero" i: 0 type: INT } } node { input: "/lstm/Reshape_3_output_0" output: "/lstm/Transpose_5_output_0" name: "/lstm/Transpose_5" op_type: "Transpose" attribute { name: "perm" ints: 1 ints: 0 ints: 2 type: INTS } } node { input: "/lstm/Transpose_5_output_0" input: "onnx::MatMul_915" output: "/linear.0/MatMul_output_0" name: "/linear.0/MatMul" op_type: "MatMul" } node { input: "linear.0.bias" input: "/linear.0/MatMul_output_0" output: "/linear.0/Add_output_0" name: "/linear.0/Add" op_type: "Add" } node { input: "/linear.0/Add_output_0" output: "/LeakyRelu_output_0" name: "/LeakyRelu" op_type: "LeakyRelu" attribute { name: "alpha" f: 0.009999999776482582 type: FLOAT } } node { input: "/LeakyRelu_output_0" input: "onnx::MatMul_916" output: "/linear.1/MatMul_output_0" name: "/linear.1/MatMul" op_type: "MatMul" } node { input: "linear.1.bias" input: "/linear.1/MatMul_output_0" output: "/linear.1/Add_output_0" name: "/linear.1/Add" op_type: "Add" } node { input: "/linear.1/Add_output_0" output: "/LeakyRelu_1_output_0" name: "/LeakyRelu_1" op_type: "LeakyRelu" attribute { name: "alpha" f: 0.009999999776482582 type: FLOAT } } node { input: "/LeakyRelu_1_output_0" input: "onnx::MatMul_917" output: "/classifier/MatMul_output_0" name: "/classifier/MatMul" op_type: "MatMul" } node { input: "ortshared_1_1_7_0_token_109" input: "/classifier/MatMul_output_0" output: "/classifier/Add_output_0" name: "/classifier/Add" op_type: "Add" } node { input: "/classifier/Add_output_0" output: "output" name: "/activation/LogSoftmax" op_type: "LogSoftmax" attribute { name: "axis" i: -1 type: INT } } initializer { dims: 1 data_type: 1 name: "ortshared_1_1_1_1_token_110" } initializer { dims: 1 data_type: 1 name: "ortshared_1_1_1_0_token_107" } initializer { dims: 80 dims: 1 dims: 251 data_type: 1 name: "/sincnet/conv1d.0/Concat_2_output_0" } initializer { data_type: 7 name: "ortshared_7_0_1_0_token_105" } initializer { dims: 1 data_type: 7 name: "ortshared_7_1_1_2_token_111" } initializer { data_type: 7 name: "ortshared_7_0_1_1_token_113" } initializer { dims: 60 dims: 80 dims: 5 data_type: 1 name: "sincnet.conv1d.1.weight" } initializer { dims: 60 data_type: 1 name: "sincnet.conv1d.1.bias" } initializer { dims: 60 dims: 60 dims: 5 data_type: 1 name: "sincnet.conv1d.2.weight" } initializer { dims: 60 data_type: 1 name: "sincnet.conv1d.2.bias" } initializer { dims: 80 data_type: 1 name: "sincnet.norm1d.0.weight" } initializer { dims: 80 data_type: 1 name: "sincnet.norm1d.0.bias" } initializer { dims: 60 data_type: 1 name: "sincnet.norm1d.1.weight" } initializer { dims: 60 data_type: 1 name: "sincnet.norm1d.1.bias" } initializer { dims: 60 data_type: 1 name: "sincnet.norm1d.2.weight" } initializer { dims: 60 data_type: 1 name: "sincnet.norm1d.2.bias" } initializer { dims: 128 data_type: 1 name: "linear.0.bias" } initializer { dims: 128 data_type: 1 name: "linear.1.bias" } initializer { dims: 7 data_type: 1 name: "ortshared_1_1_7_0_token_109" } initializer { dims: 1 data_type: 7 name: "ortshared_7_1_1_4_token_115" } initializer { dims: 2 dims: 1024 data_type: 1 name: "onnx::LSTM_783" } initializer { dims: 2 dims: 512 dims: 60 data_type: 1 name: "onnx::LSTM_784" } initializer { dims: 2 dims: 512 dims: 128 data_type: 1 name: "onnx::LSTM_785" } initializer { dims: 2 dims: 1024 data_type: 1 name: "onnx::LSTM_826" } initializer { dims: 2 dims: 512 dims: 256 data_type: 1 name: "onnx::LSTM_827" } initializer { dims: 2 dims: 512 dims: 128 data_type: 1 name: "onnx::LSTM_828" } initializer { dims: 2 dims: 1024 data_type: 1 name: "onnx::LSTM_869" } initializer { dims: 2 dims: 512 dims: 256 data_type: 1 name: "onnx::LSTM_870" } initializer { dims: 2 dims: 512 dims: 128 data_type: 1 name: "onnx::LSTM_871" } initializer { dims: 2 dims: 1024 data_type: 1 name: "onnx::LSTM_912" } initializer { dims: 2 dims: 512 dims: 256 data_type: 1 name: "onnx::LSTM_913" } initializer { dims: 2 dims: 512 dims: 128 data_type: 1 name: "onnx::LSTM_914" } initializer { dims: 256 dims: 128 data_type: 1 name: "onnx::MatMul_915" } initializer { dims: 128 dims: 128 data_type: 1 name: "onnx::MatMul_916" } initializer { dims: 128 dims: 7 data_type: 1 name: "onnx::MatMul_917" } initializer { dims: 1 data_type: 7 name: "ortshared_7_1_1_1_token_108" } initializer { dims: 1 data_type: 7 name: "ortshared_7_1_1_5_token_116" } initializer { dims: 3 data_type: 7 name: "ortshared_7_1_3_1_token_112" } initializer { dims: 1 data_type: 7 name: "ortshared_7_1_1_3_token_114" } initializer { dims: 1 data_type: 7 name: "ortshared_7_1_1_0_token_106" } initializer { dims: 3 data_type: 7 name: "ortshared_7_1_3_0_token_104" } input { name: "input" type { tensor_type { elem_type: 1 shape { dim { dim_param: "B" } dim { dim_param: "C" } dim { dim_param: "T" } } } } } output { name: "output" type { tensor_type { elem_type: 1 shape { dim { dim_param: "LogSoftmaxoutput_dim_0" } dim { dim_param: "LogSoftmaxoutput_dim_1" } dim { dim_value: 7 } } } } } } opset_import { domain: "" version: 17 } opset_import { domain: "com.microsoft.experimental" version: 1 } opset_import { domain: "ai.onnx.ml" version: 4 } opset_import { domain: "ai.onnx.training" version: 1 } opset_import { domain: "com.microsoft" version: 1 } opset_import { domain: "ai.onnx.preview.training" version: 1 } opset_import { domain: "com.microsoft.nchwc" version: 1 } opset_import { domain: "org.pytorch.aten" version: 1 }