Error reports

[justinchuby]

Include step status

✅ Obtain model graph with `torch.export.export`
✅ Translate the graph into ONNX
❌ Run `onnx.checker` on the ONNX model
⚪ Execute the model with ONNX Runtime
⚪ Validate model output accuracy

[justinchuby]

PyTorch ONNX Conversion Report

✅ Obtain model graph with `torch.export.export`
✅ Translate the graph into ONNX
✅ Run `onnx.checker` on the ONNX model
✅ Execute the model with ONNX Runtime
✅ Validate model output accuracy

Profile result

  _     ._   __/__   _ _  _  _ _/_   Recorded: 10:17:49  Samples:  949
 /_//_/// /_\ / //_// / //_'/ //     Duration: 2.263     CPU time: 0.864
/   _/                      v4.6.2

Program: -c

2.262 _torch_onnx_export_adapter_with_error_report  torch_onnx/_patch.py:210
└─ 2.262 _torch_onnx_export_adaptor  torch_onnx/_patch.py:139
   ├─ 1.637 export  torch/export/__init__.py:73
   │     [126 frames hidden]  torch, contextlib, importlib, jinja2,...
   └─ 0.625 exported_program_to_ir  torch_onnx/_core.py:574
      ├─ 0.527 OnnxRegistry.from_torchlib  torch_onnx/_registration.py:114
      │  ├─ 0.325 TracedOnnxFunction.function_ir  ../onnxscript/onnxscript/values.py:587
      │  │  ├─ 0.242 get_src_and_ast  ../onnxscript/onnxscript/_internal/ast_utils.py:16
      │  │  │  ├─ 0.200 getsource  inspect.py:1256
      │  │  │  │     [6 frames hidden]  inspect, tokenize, <built-in>
      │  │  │  └─ 0.039 parse  ast.py:33
      │  │  │        [2 frames hidden]  ast, <built-in>
      │  │  └─ 0.067 Converter.translate_function_signature  ../onnxscript/onnxscript/converter.py:1463
      │  │     └─ 0.067 Converter._translate_function_signature_common  ../onnxscript/onnxscript/converter.py:1378
      │  │        └─ 0.029 is_valid_type  ../onnxscript/onnxscript/type_annotation.py:172
      │  │           └─ 0.029 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
      │  ├─ 0.128 OpSignature.from_function  torch_onnx/_schemas.py:398
      │  │  ├─ 0.066 get_type_hints  typing.py:2300
      │  │  │     [6 frames hidden]  typing, <built-in>
      │  │  └─ 0.035 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
      │  │     └─ 0.025 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
      │  └─ 0.051 _get_overload  torch_onnx/_registration.py:57
      │     └─ 0.041 _OpNamespace.__getattr__  torch/_ops.py:905
      ├─ 0.037 create_onnx_friendly_decomposition_table  torch_onnx/_decomp.py:39
      │  └─ 0.027 _get_registered_ops  torch_onnx/_decomp.py:12
      └─ 0.035 wrapper  torch/export/exported_program.py:80
            [6 frames hidden]  torch

[justinchuby]

PyTorch ONNX Conversion Error Report

✅ Obtain model graph with `torch.export.export`
❌ Translate the graph into ONNX
⚪ Run `onnx.checker` on the ONNX model
⚪ Execute the model with ONNX Runtime
⚪ Validate model output accuracy

Error message:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 490, in _add_nodes
    _handle_call_function_node_with_lowering(
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 372, in _handle_call_function_node_with_lowering
    raise RuntimeError(
RuntimeError: No ONNX function found for <OpOverload(op='aten.index_put', overload='default')>. Failure message: All overloads did not match the node `%index_put : [num_users=1] = call_function[target=torch.ops.aten.index_put.default](args = (%arg0_1, [%arg1_1], %lift_fresh_copy), kwargs = {})`.
- Failed to match overload `OnnxFunction(<function aten_index_put at 0x1784c82c0>)`: Parameter type not compatible with argument: param=`Parameter(name='self', type_constraint=TypeConstraintParam(name='TReal', allowed_types={Tensor(INT32), Tensor(FLOAT), Tensor(INT16), Tensor(FLOAT16), Tensor(BFLOAT16), Tensor(INT8), Tensor(DOUBLE), Tensor(INT64)}, description=''), required=True, variadic=False, default=_EMPTY_DEFAULT)`, assigned_types=`{}`, arg=`BOOL`
- Failed to match overload `OnnxFunction(<function aten_index_put_bool at 0x1784c8360>)`: Parameter type not compatible with argument: param=`Parameter(name='self', type_constraint=TypeConstraintParam(name='TReal', allowed_types={Tensor(INT32), Tensor(FLOAT), Tensor(INT16), Tensor(FLOAT16), Tensor(BFLOAT16), Tensor(INT8), Tensor(DOUBLE), Tensor(INT64)}, description=''), required=True, variadic=False, default=_EMPTY_DEFAULT)`, assigned_types=`{}`, arg=`BOOL`

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 174, in _torch_onnx_export_adaptor
    ir_model = torch_onnx.exported_program_to_ir(program)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 626, in exported_program_to_ir
    values = _add_nodes(exported_program, model, lower=lower, registry=registry)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 501, in _add_nodes
    raise RuntimeError(
RuntimeError: Error when translating node %index_put : [num_users=1] = call_function[target=torch.ops.aten.index_put.default](args = (%arg0_1, [%arg1_1], %lift_fresh_copy), kwargs = {}). See the stack trace for more information.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 230, in _torch_onnx_export_adapter_with_error_report
    ir_model, program = _torch_onnx_export_adaptor(*args, **kwargs, check=True)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 197, in _torch_onnx_export_adaptor
    raise OnnxConversionError(
torch_onnx._patch.OnnxConversionError: Failed to convert the exported program to an ONNX model. This is step 2/2 of exporting the model to ONNX. Please create an issue in the PyTorch GitHub repository against the *onnx* component and attach the full error stack as well as reproduction scripts. You can run `torch_onnx.analyze()` to produce an error report after obtaining an ExportedProgram with `torch.export.export()`.

Exported program:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, _lifted_tensor_constant0: "b8[]", arg0_1: "b8[100]", arg1_1: "i64[25]"):
            # File: /Users/justinc/Documents/GitHub/torch-onnx/tests/pytorch_test.py:2361 in forward, code: mask[indices] = True
            lift_fresh_copy: "b8[]" = torch.ops.aten.lift_fresh_copy.default(_lifted_tensor_constant0);  _lifted_tensor_constant0 = None
            index_put: "b8[100]" = torch.ops.aten.index_put.default(arg0_1, [arg1_1], lift_fresh_copy);  arg0_1 = arg1_1 = lift_fresh_copy = None
            return (index_put, index_put)

Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=<InputKind.CONSTANT_TENSOR: 4>, arg=TensorArgument(name='_lifted_tensor_constant0'), target='_lifted_tensor_constant0', persistent=None), InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg0_1'), target=None, persistent=None), InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg1_1'), target=None, persistent=None)], output_specs=[OutputSpec(kind=<OutputKind.USER_INPUT_MUTATION: 6>, arg=TensorArgument(name='index_put'), target='arg0_1'), OutputSpec(kind=<OutputKind.USER_OUTPUT: 1>, arg=TensorArgument(name='index_put'), target=None)])
Range constraints: {}

Analysis

PyTorch ONNX Conversion Analysis

Model Information

The model has 0 parameters and 0 buffers (non-trainable parameters). Number of parameters per dtype: defaultdict(<class 'int'>, {}) Number of buffers per dtype: defaultdict(<class 'int'>, {})

Inputs:

• arg0_1: TensorMetadata(shape=torch.Size([100]), dtype=torch.bool, requires_grad=False, stride=(1,), memory_format=torch.contiguous_format, is_quantized=False, qparams={})
• arg1_1: TensorMetadata(shape=torch.Size([25]), dtype=torch.int64, requires_grad=False, stride=(1,), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

Outputs:

• index_put: TensorMetadata(shape=torch.Size([100]), dtype=torch.bool, requires_grad=False, stride=(1,), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

The FX graph has 6 nodes in total. Number of FX nodes per op:

• placeholder: 3
• call_function: 2
• output: 1

Of the call_function nodes, the counts of operators used are:

• aten.lift_fresh_copy.default: 1
• aten.index_put.default: 1

ONNX Conversion Information

The model contains operators the dispatcher could not find registered ONNX decompositions for. This may be due to missing implementations, decompositions not registered correctly, or a bug in the dispatcher.

Errors grouped by operator:

• aten.index_put.default: All overloads did not match the node %index_put : [num_users=1] = call_function[target=torch.ops.aten.index_put.default](args = (%arg0_1, [%arg1_1], %lift_fresh_copy), kwargs = {}).
  • Failed to match overload OnnxFunction(<function aten_index_put at 0x1784c82c0>): Parameter type not compatible with argument: param=Parameter(name='self', type_constraint=TypeConstraintParam(name='TReal', allowed_types={Tensor(INT32), Tensor(FLOAT), Tensor(INT16), Tensor(FLOAT16), Tensor(BFLOAT16), Tensor(INT8), Tensor(DOUBLE), Tensor(INT64)}, description=''), required=True, variadic=False, default=_EMPTY_DEFAULT), assigned_types={}, arg=BOOL
  • Failed to match overload OnnxFunction(<function aten_index_put_bool at 0x1784c8360>): Parameter type not compatible with argument: param=Parameter(name='self', type_constraint=TypeConstraintParam(name='TReal', allowed_types={Tensor(INT32), Tensor(FLOAT), Tensor(INT16), Tensor(FLOAT16), Tensor(BFLOAT16), Tensor(INT8), Tensor(DOUBLE), Tensor(INT64)}, description=''), required=True, variadic=False, default=_EMPTY_DEFAULT), assigned_types={}, arg=BOOL. Example node: %index_put : [num_users=1] = call_function[target=torch.ops.aten.index_put.default](args = (%arg0_1, [%arg1_1], %lift_fresh_copy), kwargs = {}). All nodes: [index_put]

    Profile result

  _     ._   __/__   _ _  _  _ _/_   Recorded: 10:26:29  Samples:  319
 /_//_/// /_\ / //_// / //_'/ //     Duration: 0.587     CPU time: 0.261
/   _/                      v4.6.2

Program: -c

0.587 _torch_onnx_export_adapter_with_error_report  torch_onnx/_patch.py:210
└─ 0.587 _torch_onnx_export_adaptor  torch_onnx/_patch.py:139
   ├─ 0.510 exported_program_to_ir  torch_onnx/_core.py:574
   │  ├─ 0.421 OnnxRegistry.from_torchlib  torch_onnx/_registration.py:114
   │  │  ├─ 0.228 TracedOnnxFunction.function_ir  ../onnxscript/onnxscript/values.py:587
   │  │  │  ├─ 0.175 get_src_and_ast  ../onnxscript/onnxscript/_internal/ast_utils.py:16
   │  │  │  │  ├─ 0.146 getsource  inspect.py:1256
   │  │  │  │  │     [14 frames hidden]  inspect, tokenize, <built-in>, <string>
   │  │  │  │  └─ 0.029 parse  ast.py:33
   │  │  │  │        [2 frames hidden]  ast, <built-in>
   │  │  │  └─ 0.050 Converter.translate_function_signature  ../onnxscript/onnxscript/converter.py:1463
   │  │  │     └─ 0.050 Converter._translate_function_signature_common  ../onnxscript/onnxscript/converter.py:1378
   │  │  │        ├─ 0.025 is_valid_type  ../onnxscript/onnxscript/type_annotation.py:172
   │  │  │        │  └─ 0.025 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        │     ├─ 0.015 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        │     │  └─ 0.007 <listcomp>  ../onnxscript/onnxscript/type_annotation.py:150
   │  │  │        │     │     └─ 0.007 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        │     │        └─ 0.007 _is_tensor_type  ../onnxscript/onnxscript/type_annotation.py:123
   │  │  │        │     └─ 0.006 <listcomp>  ../onnxscript/onnxscript/type_annotation.py:150
   │  │  │        │        └─ 0.006 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        ├─ 0.011 is_attr_type  ../onnxscript/onnxscript/type_annotation.py:168
   │  │  │        │  └─ 0.011 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        └─ 0.007 pytype_to_attrtype  ../onnxscript/onnxscript/type_annotation.py:83
   │  │  │           └─ 0.007 _remove_annotation  ../onnxscript/onnxscript/type_annotation.py:70
   │  │  │              └─ 0.007 get_origin  typing.py:2424
   │  │  └─ 0.181 OpSignature.from_function  torch_onnx/_schemas.py:398
   │  │     ├─ 0.071 get_type_hints  typing.py:2300
   │  │     │     [8 frames hidden]  typing, <built-in>
   │  │     ├─ 0.067 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │  └─ 0.060 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │     ├─ 0.037 _is_optional  torch_onnx/_schemas.py:185
   │  │     │     │  └─ 0.037 get_args  typing.py:2454
   │  │     │     │        [2 frames hidden]  typing
   │  │     │     └─ 0.018 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │        └─ 0.012 [self]  torch_onnx/_schemas.py
   │  │     ├─ 0.028 [self]  torch_onnx/_schemas.py
   │  │     └─ 0.010 signature  inspect.py:3278
   │  │           [4 frames hidden]  inspect
   │  ├─ 0.049 create_onnx_friendly_decomposition_table  torch_onnx/_decomp.py:39
   │  │  ├─ 0.037 core_aten_decompositions  torch/_decomp/__init__.py:253
   │  │  │     [5 frames hidden]  torch
   │  │  └─ 0.008 OpOverload.__hash__  torch/_ops.py:596
   │  └─ 0.036 wrapper  torch/export/exported_program.py:80
   │        [22 frames hidden]  torch
   └─ 0.076 export  torch/export/__init__.py:73
         [56 frames hidden]  torch, contextlib, traceback

[justinchuby]

PyTorch ONNX Conversion Error Report

✅ Obtain model graph with `torch.export.export`
✅ Translate the graph into ONNX
❌ Run `onnx.checker` on the ONNX model
⚪ Execute the model with ONNX Runtime
⚪ Validate model output accuracy

Error message:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 292, in _torch_onnx_export_adapter_with_error_report
    onnx.checker.check_model(proto, full_check=True)
  File "/Users/justinc/Documents/GitHub/torch-onnx/venv/lib/python3.11/site-packages/onnx/checker.py", line 179, in check_model
    C.check_model(
onnx.onnx_cpp2py_export.shape_inference.InferenceError: [ShapeInferenceError] Inference error(s): (op_type:Cast, node name: node_Cast_0): [ShapeInferenceError] Inferred shape and existing shape differ in rank: (2) vs (0)

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 296, in _torch_onnx_export_adapter_with_error_report
    raise OnnxCheckerError(
torch_onnx._patch.OnnxCheckerError: Conversion successful but the ONNX model fails ONNX checker. Please create an issue in the PyTorch GitHub repository against the *onnx* component and attach the full error stack as well as reproduction scripts. 

Exported program:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, arg0_1: "b8[2, 2]"):
            # File: /Users/justinc/Documents/GitHub/torch-onnx/tests/pytorch_test.py:9451 in forward, code: return x.all()
            all_1: "b8[]" = torch.ops.aten.all.default(arg0_1);  arg0_1 = None
            return (all_1,)

Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg0_1'), target=None, persistent=None)], output_specs=[OutputSpec(kind=<OutputKind.USER_OUTPUT: 1>, arg=TensorArgument(name='all_1'), target=None)])
Range constraints: {}

Analysis

PyTorch ONNX Conversion Analysis

Model Information

The model has 0 parameters and 0 buffers (non-trainable parameters). Number of parameters per dtype: defaultdict(<class 'int'>, {}) Number of buffers per dtype: defaultdict(<class 'int'>, {})

Inputs:

• arg0_1: TensorMetadata(shape=torch.Size([2, 2]), dtype=torch.bool, requires_grad=False, stride=(2, 1), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

Outputs:

• all_1: TensorMetadata(shape=torch.Size([]), dtype=torch.bool, requires_grad=False, stride=(), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

The FX graph has 3 nodes in total. Number of FX nodes per op:

• placeholder: 1
• call_function: 1
• output: 1

Of the call_function nodes, the counts of operators used are:

• aten.all.default: 1

ONNX Conversion Information

All operators in the model have registered ONNX decompositions.

Profile result

  _     ._   __/__   _ _  _  _ _/_   Recorded: 10:30:52  Samples:  1171
 /_//_/// /_\ / //_// / //_'/ //     Duration: 2.612     CPU time: 1.174
/   _/                      v4.6.2

Program: -c

2.611 _torch_onnx_export_adapter_with_error_report  torch_onnx/_patch.py:210
└─ 2.611 _torch_onnx_export_adaptor  torch_onnx/_patch.py:139
   ├─ 1.940 export  torch/export/__init__.py:73
   │     [92 frames hidden]  torch, contextlib, tokenize, <string>...
   └─ 0.670 exported_program_to_ir  torch_onnx/_core.py:574
      ├─ 0.577 OnnxRegistry.from_torchlib  torch_onnx/_registration.py:114
      │  ├─ 0.269 OpSignature.from_function  torch_onnx/_schemas.py:398
      │  │  ├─ 0.120 get_type_hints  typing.py:2300
      │  │  │     [4 frames hidden]  typing, <built-in>
      │  │  ├─ 0.089 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
      │  │  │  └─ 0.077 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
      │  │  │     └─ 0.068 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
      │  │  │        └─ 0.064 TensorType.__hash__  ../onnxscript/onnxscript/ir/_core.py:1291
      │  │  │           └─ 0.064 TensorType.__repr__  ../onnxscript/onnxscript/ir/_core.py:1299
      │  │  │              └─ 0.062 DataType.__repr__  ../onnxscript/onnxscript/ir/_enums.py:94
      │  │  │                 └─ 0.050 [self]  ../onnxscript/onnxscript/ir/_enums.py
      │  │  └─ 0.039 _get_attr_type  torch_onnx/_schemas.py:204
      │  └─ 0.267 TracedOnnxFunction.function_ir  ../onnxscript/onnxscript/values.py:587
      │     ├─ 0.214 get_src_and_ast  ../onnxscript/onnxscript/_internal/ast_utils.py:16
      │     │  ├─ 0.168 getsource  inspect.py:1256
      │     │  │     [5 frames hidden]  inspect, tokenize
      │     │  └─ 0.043 parse  ast.py:33
      │     │        [2 frames hidden]  ast, <built-in>
      │     └─ 0.044 Converter.translate_function_signature  ../onnxscript/onnxscript/converter.py:1463
      │        └─ 0.044 Converter._translate_function_signature_common  ../onnxscript/onnxscript/converter.py:1378
      ├─ 0.039 wrapper  torch/export/exported_program.py:80
      │     [2 frames hidden]  torch
      └─ 0.036 create_onnx_friendly_decomposition_table  torch_onnx/_decomp.py:39
         └─ 0.033 _get_registered_ops  torch_onnx/_decomp.py:12

[justinchuby]

PyTorch ONNX Conversion Report

✅ Obtain model graph with `torch.export.export`
✅ Translate the graph into ONNX
✅ Run `onnx.checker` on the ONNX model
✅ Execute the model with ONNX Runtime
✅ Validate model output accuracy

Exported program:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, arg0_1: "f32[10, 10, 10]", arg1_1: "f32[10, 10, 10]", arg2_1: "f32[20, 5, 10, 10, 10]"):
            # File: /Users/justinc/Documents/GitHub/torch-onnx/venv/lib/python3.11/site-packages/torch/_dynamo/external_utils.py:36 in inner, code: return fn(*args, **kwargs)
            native_layer_norm = torch.ops.aten.native_layer_norm.default(arg2_1, [10, 10, 10], arg0_1, arg1_1, 1e-05);  arg2_1 = arg0_1 = arg1_1 = None
            getitem: "f32[20, 5, 10, 10, 10]" = native_layer_norm[0];  native_layer_norm = None
            return (getitem,)

Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=<InputKind.PARAMETER: 2>, arg=TensorArgument(name='arg0_1'), target='weight', persistent=None), InputSpec(kind=<InputKind.PARAMETER: 2>, arg=TensorArgument(name='arg1_1'), target='bias', persistent=None), InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg2_1'), target=None, persistent=None)], output_specs=[OutputSpec(kind=<OutputKind.USER_OUTPUT: 1>, arg=TensorArgument(name='getitem'), target=None)])
Range constraints: {}

Profile result

  _     ._   __/__   _ _  _  _ _/_   Recorded: 10:31:18  Samples:  285
 /_//_/// /_\ / //_// / //_'/ //     Duration: 0.682     CPU time: 0.310
/   _/                      v4.6.2

Program: -c

0.681 _torch_onnx_export_adapter_with_error_report  torch_onnx/_patch.py:210
└─ 0.681 _torch_onnx_export_adaptor  torch_onnx/_patch.py:139
   ├─ 0.496 exported_program_to_ir  torch_onnx/_core.py:574
   │  ├─ 0.403 OnnxRegistry.from_torchlib  torch_onnx/_registration.py:114
   │  │  ├─ 0.257 TracedOnnxFunction.function_ir  ../onnxscript/onnxscript/values.py:587
   │  │  │  ├─ 0.188 get_src_and_ast  ../onnxscript/onnxscript/_internal/ast_utils.py:16
   │  │  │  │  ├─ 0.174 getsource  inspect.py:1256
   │  │  │  │  │     [8 frames hidden]  inspect, tokenize, <built-in>, <string>
   │  │  │  │  └─ 0.009 parse  ast.py:33
   │  │  │  │        [2 frames hidden]  ast, <built-in>
   │  │  │  └─ 0.068 Converter.translate_function_signature  ../onnxscript/onnxscript/converter.py:1463
   │  │  │     └─ 0.068 Converter._translate_function_signature_common  ../onnxscript/onnxscript/converter.py:1378
   │  │  │        └─ 0.057 is_valid_type  ../onnxscript/onnxscript/type_annotation.py:172
   │  │  │           └─ 0.057 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │              └─ 0.054 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │                 └─ 0.051 <listcomp>  ../onnxscript/onnxscript/type_annotation.py:150
   │  │  │                    └─ 0.051 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │                       └─ 0.049 _is_tensor_type  ../onnxscript/onnxscript/type_annotation.py:123
   │  │  │                          └─ 0.048 [self]  ../onnxscript/onnxscript/type_annotation.py
   │  │  └─ 0.137 OpSignature.from_function  torch_onnx/_schemas.py:398
   │  │     ├─ 0.088 get_type_hints  typing.py:2300
   │  │     │     [11 frames hidden]  typing, <built-in>
   │  │     ├─ 0.033 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │  └─ 0.030 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │     └─ 0.027 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │        ├─ 0.013 TensorType.__hash__  ../onnxscript/onnxscript/ir/_core.py:1291
   │  │     │        │  └─ 0.010 TensorType.__repr__  ../onnxscript/onnxscript/ir/_core.py:1299
   │  │     │        │     └─ 0.008 [self]  ../onnxscript/onnxscript/ir/_core.py
   │  │     │        └─ 0.009 [self]  torch_onnx/_schemas.py
   │  │     └─ 0.009 signature  inspect.py:3278
   │  │           [4 frames hidden]  inspect
   │  ├─ 0.073 wrapper  torch/export/exported_program.py:80
   │  │     [62 frames hidden]  torch, <built-in>
   │  └─ 0.018 create_onnx_friendly_decomposition_table  torch_onnx/_decomp.py:39
   │     └─ 0.007 core_aten_decompositions  torch/_decomp/__init__.py:253
   │           [2 frames hidden]  torch
   └─ 0.185 export  torch/export/__init__.py:73
         [69 frames hidden]  torch, contextlib, traceback, <built-in>

[justinchuby]

PyTorch ONNX Conversion Error Report

✅ Obtain model graph with `torch.export.export`
✅ Translate the graph into ONNX
❌ Run `onnx.checker` on the ONNX model
⚪ Execute the model with ONNX Runtime
⚪ Validate model output accuracy

Error message:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 292, in _torch_onnx_export_adapter_with_error_report
    onnx.checker.check_model(proto, full_check=True)
  File "/Users/justinc/Documents/GitHub/torch-onnx/venv/lib/python3.11/site-packages/onnx/checker.py", line 179, in check_model
    C.check_model(
onnx.onnx_cpp2py_export.shape_inference.InferenceError: [ShapeInferenceError] Inference error(s): (op_type:Cast, node name: node_Cast_0): [ShapeInferenceError] Inferred shape and existing shape differ in rank: (2) vs (0)

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 296, in _torch_onnx_export_adapter_with_error_report
    raise OnnxCheckerError(
torch_onnx._patch.OnnxCheckerError: Conversion successful but the ONNX model fails ONNX checker. Please create an issue in the PyTorch GitHub repository against the *onnx* component and attach the full error stack as well as reproduction scripts. 

Exported program:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, arg0_1: "b8[2, 2]"):
            # File: /Users/justinc/Documents/GitHub/torch-onnx/tests/pytorch_test.py:9451 in forward, code: return x.all()
            all_1: "b8[]" = torch.ops.aten.all.default(arg0_1);  arg0_1 = None
            return (all_1,)

Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg0_1'), target=None, persistent=None)], output_specs=[OutputSpec(kind=<OutputKind.USER_OUTPUT: 1>, arg=TensorArgument(name='all_1'), target=None)])
Range constraints: {}

ONNX model:

<
    ir_version=9,
    opset_imports={'': 18},
    producer_name='torch',
    producer_version='2.3.1',
    domain=None,
    model_version=None,
>
graph(
    name=main_graph,
    inputs=(
        %"arg0_1"<BOOL,[2,2]>
    ),
    outputs=(
        %"val_all_1"<BOOL,[]>
    ),
) {
    0 |  # node_Cast_0
         %"val_all_1"<BOOL,[]> ⬅️ ::Cast(%"arg0_1") {to=9}
    return %"val_all_1"<BOOL,[]>
}

Analysis

PyTorch ONNX Conversion Analysis

Model Information

The model has 0 parameters and 0 buffers (non-trainable parameters). Number of parameters per dtype: defaultdict(<class 'int'>, {}) Number of buffers per dtype: defaultdict(<class 'int'>, {})

Inputs:

• arg0_1: TensorMetadata(shape=torch.Size([2, 2]), dtype=torch.bool, requires_grad=False, stride=(2, 1), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

Outputs:

• all_1: TensorMetadata(shape=torch.Size([]), dtype=torch.bool, requires_grad=False, stride=(), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

The FX graph has 3 nodes in total. Number of FX nodes per op:

• placeholder: 1
• call_function: 1
• output: 1

Of the call_function nodes, the counts of operators used are:

• aten.all.default: 1

ONNX Conversion Information

All operators in the model have registered ONNX decompositions.

Profile result

  _     ._   __/__   _ _  _  _ _/_   Recorded: 10:34:51  Samples:  1165
 /_//_/// /_\ / //_// / //_'/ //     Duration: 3.177     CPU time: 1.208
/   _/                      v4.6.2

Program: -c

3.176 _torch_onnx_export_adapter_with_error_report  torch_onnx/_patch.py:210
└─ 3.176 _torch_onnx_export_adaptor  torch_onnx/_patch.py:139
   ├─ 2.397 export  torch/export/__init__.py:73
   │     [97 frames hidden]  torch, contextlib, importlib, functoo...
   └─ 0.779 exported_program_to_ir  torch_onnx/_core.py:574
      ├─ 0.650 OnnxRegistry.from_torchlib  torch_onnx/_registration.py:114
      │  ├─ 0.305 TracedOnnxFunction.function_ir  ../onnxscript/onnxscript/values.py:587
      │  │  ├─ 0.218 get_src_and_ast  ../onnxscript/onnxscript/_internal/ast_utils.py:16
      │  │  │  ├─ 0.186 getsource  inspect.py:1256
      │  │  │  │     [7 frames hidden]  inspect, tokenize
      │  │  │  └─ 0.032 parse  ast.py:33
      │  │  │        [2 frames hidden]  ast, <built-in>
      │  │  └─ 0.074 Converter.translate_function_signature  ../onnxscript/onnxscript/converter.py:1463
      │  │     └─ 0.074 Converter._translate_function_signature_common  ../onnxscript/onnxscript/converter.py:1378
      │  │        └─ 0.048 is_valid_type  ../onnxscript/onnxscript/type_annotation.py:172
      │  │           └─ 0.047 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
      │  │              └─ 0.035 get_origin  typing.py:2424
      │  ├─ 0.298 OpSignature.from_function  torch_onnx/_schemas.py:398
      │  │  ├─ 0.115 _get_attr_type  torch_onnx/_schemas.py:204
      │  │  │  └─ 0.115 get_origin  typing.py:2424
      │  │  │        [2 frames hidden]  typing, <built-in>
      │  │  ├─ 0.091 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
      │  │  │  ├─ 0.044 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
      │  │  │  │  └─ 0.038 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
      │  │  │  └─ 0.036 isinstance  <built-in>
      │  │  └─ 0.054 get_type_hints  typing.py:2300
      │  └─ 0.041 _get_overload  torch_onnx/_registration.py:57
      │     └─ 0.037 OpOverloadPacket.__getattr__  torch/_ops.py:800
      ├─ 0.058 create_onnx_friendly_decomposition_table  torch_onnx/_decomp.py:39
      │  └─ 0.056 _get_registered_ops  torch_onnx/_decomp.py:12
      │     └─ 0.047 OpOverloadPacket.__getattr__  torch/_ops.py:800
      └─ 0.049 wrapper  torch/export/exported_program.py:80
            [9 frames hidden]  torch

[justinchuby]

PyTorch ONNX Conversion Error Report

✅ Obtain model graph with `torch.export.export`
❌ Translate the graph into ONNX
⚪ Run `onnx.checker` on the ONNX model
⚪ Execute the model with ONNX Runtime
⚪ Validate model output accuracy

Error message:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 490, in _add_nodes
    _handle_call_function_node_with_lowering(
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 372, in _handle_call_function_node_with_lowering
    raise RuntimeError(
RuntimeError: No ONNX function found for <OpOverload(op='aten.grid_sampler_3d', overload='default')>. Failure message: No decompositions registered for the real-valued input

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 174, in _torch_onnx_export_adaptor
    ir_model = torch_onnx.exported_program_to_ir(program)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 626, in exported_program_to_ir
    values = _add_nodes(exported_program, model, lower=lower, registry=registry)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 501, in _add_nodes
    raise RuntimeError(
RuntimeError: Error when translating node %grid_sampler_3d : [num_users=1] = call_function[target=torch.ops.aten.grid_sampler_3d.default](args = (%arg0_1, %arg1_1, 0, 0, True), kwargs = {}). See the stack trace for more information.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 230, in _torch_onnx_export_adapter_with_error_report
    ir_model, program = _torch_onnx_export_adaptor(*args, **kwargs, check=True)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 197, in _torch_onnx_export_adaptor
    raise OnnxConversionError(
torch_onnx._patch.OnnxConversionError: Failed to convert the exported program to an ONNX model. This is step 2/2 of exporting the model to ONNX. Please create an issue in the PyTorch GitHub repository against the *onnx* component and attach the full error stack as well as reproduction scripts. You can run `torch_onnx.analyze()` to produce an error report after obtaining an ExportedProgram with `torch.export.export()`.

Exported program:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, arg0_1: "f32[1, 1, 2, 3, 2]", arg1_1: "f32[1, 3, 2, 4, 3]"):
            # File: /Users/justinc/Documents/GitHub/torch-onnx/tests/pytorch_test.py:13040 in forward, code: return torch.nn.functional.grid_sample(
            grid_sampler_3d: "f32[1, 1, 3, 2, 4]" = torch.ops.aten.grid_sampler_3d.default(arg0_1, arg1_1, 0, 0, True);  arg0_1 = arg1_1 = None
            return (grid_sampler_3d,)

Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg0_1'), target=None, persistent=None), InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg1_1'), target=None, persistent=None)], output_specs=[OutputSpec(kind=<OutputKind.USER_OUTPUT: 1>, arg=TensorArgument(name='grid_sampler_3d'), target=None)])
Range constraints: {}

Analysis

PyTorch ONNX Conversion Analysis

Model Information

The model has 0 parameters and 0 buffers (non-trainable parameters). Number of parameters per dtype: defaultdict(<class 'int'>, {}) Number of buffers per dtype: defaultdict(<class 'int'>, {})

Inputs:

• arg0_1: TensorMetadata(shape=torch.Size([1, 1, 2, 3, 2]), dtype=torch.float32, requires_grad=False, stride=(12, 12, 6, 2, 1), memory_format=torch.channels_last_3d, is_quantized=False, qparams={})
• arg1_1: TensorMetadata(shape=torch.Size([1, 3, 2, 4, 3]), dtype=torch.float32, requires_grad=False, stride=(72, 24, 12, 3, 1), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

Outputs:

• grid_sampler_3d: TensorMetadata(shape=torch.Size([1, 1, 3, 2, 4]), dtype=torch.float32, requires_grad=False, stride=(24, 24, 8, 4, 1), memory_format=torch.channels_last_3d, is_quantized=False, qparams={})

The FX graph has 4 nodes in total. Number of FX nodes per op:

• placeholder: 2
• call_function: 1
• output: 1

Of the call_function nodes, the counts of operators used are:

• aten.grid_sampler_3d.default: 1

ONNX Conversion Information

The model contains operators the dispatcher could not find registered ONNX decompositions for. This may be due to missing implementations, decompositions not registered correctly, or a bug in the dispatcher.

Errors grouped by operator:

• aten.grid_sampler_3d.default: No decompositions registered for the real-valued input. Example node: %grid_sampler_3d : [num_users=1] = call_function[target=torch.ops.aten.grid_sampler_3d.default](args = (%arg0_1, %arg1_1, 0, 0, True), kwargs = {}). All nodes: [grid_sampler_3d]

Profile result

  _     ._   __/__   _ _  _  _ _/_   Recorded: 10:35:03  Samples:  303
 /_//_/// /_\ / //_// / //_'/ //     Duration: 0.652     CPU time: 0.256
/   _/                      v4.6.2

Program: -c

0.652 _torch_onnx_export_adapter_with_error_report  torch_onnx/_patch.py:210
└─ 0.652 _torch_onnx_export_adaptor  torch_onnx/_patch.py:139
   ├─ 0.459 exported_program_to_ir  torch_onnx/_core.py:574
   │  ├─ 0.440 OnnxRegistry.from_torchlib  torch_onnx/_registration.py:114
   │  │  ├─ 0.277 TracedOnnxFunction.function_ir  ../onnxscript/onnxscript/values.py:587
   │  │  │  ├─ 0.164 get_src_and_ast  ../onnxscript/onnxscript/_internal/ast_utils.py:16
   │  │  │  │  ├─ 0.115 getsource  inspect.py:1256
   │  │  │  │  │     [11 frames hidden]  inspect, tokenize, <built-in>, linecache
   │  │  │  │  └─ 0.045 parse  ast.py:33
   │  │  │  │        [2 frames hidden]  ast, <built-in>
   │  │  │  └─ 0.108 Converter.translate_function_signature  ../onnxscript/onnxscript/converter.py:1463
   │  │  │     ├─ 0.096 Converter._translate_function_signature_common  ../onnxscript/onnxscript/converter.py:1378
   │  │  │     │  ├─ 0.026 is_attr_type  ../onnxscript/onnxscript/type_annotation.py:168
   │  │  │     │  │  └─ 0.026 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │     │  │     ├─ 0.014 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │     │  │     └─ 0.010 _is_primitive_attr_type  ../onnxscript/onnxscript/type_annotation.py:79
   │  │  │     │  │        └─ 0.010 _GenericAlias.__hash__  typing.py:1378
   │  │  │     │  ├─ 0.021 Converter._bind  ../onnxscript/onnxscript/converter.py:278
   │  │  │     │  │  └─ 0.019 [self]  ../onnxscript/onnxscript/converter.py
   │  │  │     │  ├─ 0.018 is_valid_type  ../onnxscript/onnxscript/type_annotation.py:172
   │  │  │     │  │  └─ 0.018 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │     │  │     └─ 0.013 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │     │  │        └─ 0.012 <listcomp>  ../onnxscript/onnxscript/type_annotation.py:150
   │  │  │     │  │           └─ 0.012 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │     │  │              └─ 0.009 _is_tensor_type  ../onnxscript/onnxscript/type_annotation.py:123
   │  │  │     │  │                 └─ 0.007 [self]  ../onnxscript/onnxscript/type_annotation.py
   │  │  │     │  ├─ 0.010 Converter._source_of  ../onnxscript/onnxscript/converter.py:238
   │  │  │     │  │  └─ 0.009 [self]  ../onnxscript/onnxscript/converter.py
   │  │  │     │  ├─ 0.010 Converter._eval_constant_expr  ../onnxscript/onnxscript/converter.py:451
   │  │  │     │  └─ 0.010 [self]  ../onnxscript/onnxscript/converter.py
   │  │  │     └─ 0.011 [self]  ../onnxscript/onnxscript/converter.py
   │  │  └─ 0.154 OpSignature.from_function  torch_onnx/_schemas.py:398
   │  │     ├─ 0.067 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │  └─ 0.056 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │     └─ 0.053 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │        ├─ 0.034 TensorType.__hash__  ../onnxscript/onnxscript/ir/_core.py:1291
   │  │     │        │  └─ 0.025 TensorType.__repr__  ../onnxscript/onnxscript/ir/_core.py:1299
   │  │     │        │     ├─ 0.016 [self]  ../onnxscript/onnxscript/ir/_core.py
   │  │     │        │     └─ 0.009 DataType.__repr__  ../onnxscript/onnxscript/ir/_enums.py:94
   │  │     │        └─ 0.017 [self]  torch_onnx/_schemas.py
   │  │     ├─ 0.062 get_type_hints  typing.py:2300
   │  │     │     [10 frames hidden]  typing, <built-in>
   │  │     └─ 0.012 signature  inspect.py:3278
   │  │           [4 frames hidden]  inspect
   │  ├─ 0.010 wrapper  torch/export/exported_program.py:80
   │  │     [6 frames hidden]  torch
   │  └─ 0.007 create_onnx_friendly_decomposition_table  torch_onnx/_decomp.py:39
   └─ 0.193 export  torch/export/__init__.py:73
         [78 frames hidden]  torch, contextlib, ast, <built-in>, <...

[justinchuby]

PyTorch ONNX Conversion Error Report

✅ Obtain model graph with `torch.export.export`
❌ Translate the graph into ONNX
⚪ Run `onnx.checker` on the ONNX model
⚪ Execute the model with ONNX Runtime
⚪ Validate model output accuracy

Error message:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 490, in _add_nodes
    _handle_call_function_node_with_lowering(
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 372, in _handle_call_function_node_with_lowering
    raise RuntimeError(
RuntimeError: No ONNX function found for <OpOverload(op='aten.index_put', overload='default')>. Failure message: All overloads did not match the node `%index_put : [num_users=1] = call_function[target=torch.ops.aten.index_put.default](args = (%arg0_1, [%arg1_1], %lift_fresh_copy), kwargs = {})`.
- Failed to match overload `OnnxFunction(<function aten_index_put at 0x1436c82c0>)`: Parameter type not compatible with argument: param=`Parameter(name='self', type_constraint=TypeConstraintParam(name='TReal', allowed_types={Tensor(BFLOAT16), Tensor(INT8), Tensor(INT32), Tensor(INT64), Tensor(FLOAT), Tensor(DOUBLE), Tensor(FLOAT16), Tensor(INT16)}, description=''), required=True, variadic=False, default=_EMPTY_DEFAULT)`, assigned_types=`{}`, arg=`BOOL`
- Failed to match overload `OnnxFunction(<function aten_index_put_bool at 0x1436c8360>)`: Parameter type not compatible with argument: param=`Parameter(name='self', type_constraint=TypeConstraintParam(name='TReal', allowed_types={Tensor(BFLOAT16), Tensor(INT8), Tensor(INT32), Tensor(INT64), Tensor(FLOAT), Tensor(DOUBLE), Tensor(FLOAT16), Tensor(INT16)}, description=''), required=True, variadic=False, default=_EMPTY_DEFAULT)`, assigned_types=`{}`, arg=`BOOL`

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 174, in _torch_onnx_export_adaptor
    ir_model = torch_onnx.exported_program_to_ir(program)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 626, in exported_program_to_ir
    values = _add_nodes(exported_program, model, lower=lower, registry=registry)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 501, in _add_nodes
    raise RuntimeError(
RuntimeError: Error when translating node %index_put : [num_users=1] = call_function[target=torch.ops.aten.index_put.default](args = (%arg0_1, [%arg1_1], %lift_fresh_copy), kwargs = {}). See the stack trace for more information.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 230, in _torch_onnx_export_adapter_with_error_report
    ir_model, program = _torch_onnx_export_adaptor(*args, **kwargs, check=True)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 197, in _torch_onnx_export_adaptor
    raise OnnxConversionError(
torch_onnx._patch.OnnxConversionError: Failed to convert the exported program to an ONNX model. This is step 2/2 of exporting the model to ONNX. Please create an issue in the PyTorch GitHub repository against the *onnx* component and attach the full error stack as well as reproduction scripts. You can run `torch_onnx.analyze()` to produce an error report after obtaining an ExportedProgram with `torch.export.export()`.

Exported program:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, _lifted_tensor_constant0: "b8[]", arg0_1: "b8[100]", arg1_1: "i64[25]"):
            # File: /Users/justinc/Documents/GitHub/torch-onnx/tests/pytorch_test.py:2361 in forward, code: mask[indices] = True
            lift_fresh_copy: "b8[]" = torch.ops.aten.lift_fresh_copy.default(_lifted_tensor_constant0);  _lifted_tensor_constant0 = None
            index_put: "b8[100]" = torch.ops.aten.index_put.default(arg0_1, [arg1_1], lift_fresh_copy);  arg0_1 = arg1_1 = lift_fresh_copy = None
            return (index_put, index_put)

Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=<InputKind.CONSTANT_TENSOR: 4>, arg=TensorArgument(name='_lifted_tensor_constant0'), target='_lifted_tensor_constant0', persistent=None), InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg0_1'), target=None, persistent=None), InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg1_1'), target=None, persistent=None)], output_specs=[OutputSpec(kind=<OutputKind.USER_INPUT_MUTATION: 6>, arg=TensorArgument(name='index_put'), target='arg0_1'), OutputSpec(kind=<OutputKind.USER_OUTPUT: 1>, arg=TensorArgument(name='index_put'), target=None)])
Range constraints: {}

Analysis

PyTorch ONNX Conversion Analysis

Model Information

The model has 0 parameters and 0 buffers (non-trainable parameters). Number of parameters per dtype: defaultdict(<class 'int'>, {}) Number of buffers per dtype: defaultdict(<class 'int'>, {})

Inputs:

• arg0_1: TensorMetadata(shape=torch.Size([100]), dtype=torch.bool, requires_grad=False, stride=(1,), memory_format=torch.contiguous_format, is_quantized=False, qparams={})
• arg1_1: TensorMetadata(shape=torch.Size([25]), dtype=torch.int64, requires_grad=False, stride=(1,), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

Outputs:

• index_put: TensorMetadata(shape=torch.Size([100]), dtype=torch.bool, requires_grad=False, stride=(1,), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

The FX graph has 6 nodes in total. Number of FX nodes per op:

• placeholder: 3
• call_function: 2
• output: 1

Of the call_function nodes, the counts of operators used are:

• aten.lift_fresh_copy.default: 1
• aten.index_put.default: 1

ONNX Conversion Information

The model contains operators the dispatcher could not find registered ONNX decompositions for. This may be due to missing implementations, decompositions not registered correctly, or a bug in the dispatcher.

Errors grouped by operator:

• aten.index_put.default: All overloads did not match the node %index_put : [num_users=1] = call_function[target=torch.ops.aten.index_put.default](args = (%arg0_1, [%arg1_1], %lift_fresh_copy), kwargs = {}).
  • Failed to match overload OnnxFunction(<function aten_index_put at 0x1436c82c0>): Parameter type not compatible with argument: param=Parameter(name='self', type_constraint=TypeConstraintParam(name='TReal', allowed_types={Tensor(BFLOAT16), Tensor(INT8), Tensor(INT32), Tensor(INT64), Tensor(FLOAT), Tensor(DOUBLE), Tensor(FLOAT16), Tensor(INT16)}, description=''), required=True, variadic=False, default=_EMPTY_DEFAULT), assigned_types={}, arg=BOOL
  • Failed to match overload OnnxFunction(<function aten_index_put_bool at 0x1436c8360>): Parameter type not compatible with argument: param=Parameter(name='self', type_constraint=TypeConstraintParam(name='TReal', allowed_types={Tensor(BFLOAT16), Tensor(INT8), Tensor(INT32), Tensor(INT64), Tensor(FLOAT), Tensor(DOUBLE), Tensor(FLOAT16), Tensor(INT16)}, description=''), required=True, variadic=False, default=_EMPTY_DEFAULT), assigned_types={}, arg=BOOL. Example node: %index_put : [num_users=1] = call_function[target=torch.ops.aten.index_put.default](args = (%arg0_1, [%arg1_1], %lift_fresh_copy), kwargs = {}). All nodes: [index_put]

Profile result

  _     ._   __/__   _ _  _  _ _/_   Recorded: 10:35:13  Samples:  305
 /_//_/// /_\ / //_// / //_'/ //     Duration: 0.678     CPU time: 0.241
/   _/                      v4.6.2

Program: -c

0.678 _torch_onnx_export_adapter_with_error_report  torch_onnx/_patch.py:210
└─ 0.678 _torch_onnx_export_adaptor  torch_onnx/_patch.py:139
   ├─ 0.548 exported_program_to_ir  torch_onnx/_core.py:574
   │  ├─ 0.480 OnnxRegistry.from_torchlib  torch_onnx/_registration.py:114
   │  │  ├─ 0.268 TracedOnnxFunction.function_ir  ../onnxscript/onnxscript/values.py:587
   │  │  │  ├─ 0.171 get_src_and_ast  ../onnxscript/onnxscript/_internal/ast_utils.py:16
   │  │  │  │  ├─ 0.144 getsource  inspect.py:1256
   │  │  │  │  │     [10 frames hidden]  inspect, tokenize, <built-in>, <string>
   │  │  │  │  └─ 0.027 parse  ast.py:33
   │  │  │  │        [2 frames hidden]  ast, <built-in>
   │  │  │  └─ 0.086 Converter.translate_function_signature  ../onnxscript/onnxscript/converter.py:1463
   │  │  │     └─ 0.085 Converter._translate_function_signature_common  ../onnxscript/onnxscript/converter.py:1378
   │  │  │        ├─ 0.059 is_valid_type  ../onnxscript/onnxscript/type_annotation.py:172
   │  │  │        │  └─ 0.059 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        │     └─ 0.056 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        │        └─ 0.054 <listcomp>  ../onnxscript/onnxscript/type_annotation.py:150
   │  │  │        │           └─ 0.054 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        │              └─ 0.049 _is_tensor_type  ../onnxscript/onnxscript/type_annotation.py:123
   │  │  │        │                 ├─ 0.041 TensorType.__subclasscheck__  <frozen abc>:121
   │  │  │        │                 │     [2 frames hidden]  <frozen abc>
   │  │  │        │                 └─ 0.008 [self]  ../onnxscript/onnxscript/type_annotation.py
   │  │  │        └─ 0.018 is_attr_type  ../onnxscript/onnxscript/type_annotation.py:168
   │  │  │           └─ 0.018 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │              └─ 0.010 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │                 └─ 0.009 <listcomp>  ../onnxscript/onnxscript/type_annotation.py:150
   │  │  │                    └─ 0.007 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  ├─ 0.196 OpSignature.from_function  torch_onnx/_schemas.py:398
   │  │  │  ├─ 0.118 get_type_hints  typing.py:2300
   │  │  │  │     [13 frames hidden]  typing, <built-in>
   │  │  │  ├─ 0.049 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │  │  │  └─ 0.044 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │  │  │     ├─ 0.026 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │  │  │     │  ├─ 0.014 [self]  torch_onnx/_schemas.py
   │  │  │  │     │  └─ 0.008 DataType.__call__  enum.py:686
   │  │  │  │     └─ 0.007 [self]  torch_onnx/_schemas.py
   │  │  │  └─ 0.020 signature  inspect.py:3278
   │  │  │        [4 frames hidden]  inspect
   │  │  └─ 0.009 [self]  torch_onnx/_registration.py
   │  └─ 0.060 wrapper  torch/export/exported_program.py:80
   │        [32 frames hidden]  torch
   └─ 0.130 export  torch/export/__init__.py:73
         [55 frames hidden]  torch, contextlib, <built-in>

[justinchuby]

PyTorch ONNX Conversion Error Report

✅ Obtain model graph with `torch.export.export`
❌ Translate the graph into ONNX
⚪ Run `onnx.checker` on the ONNX model
⚪ Execute the model with ONNX Runtime
⚪ Validate model output accuracy

Error message:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 490, in _add_nodes
    _handle_call_function_node_with_lowering(
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 372, in _handle_call_function_node_with_lowering
    raise RuntimeError(
RuntimeError: No ONNX function found for <OpOverload(op='aten.grid_sampler_3d', overload='default')>. Failure message: No decompositions registered for the real-valued input

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 174, in _torch_onnx_export_adaptor
    ir_model = torch_onnx.exported_program_to_ir(program)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 626, in exported_program_to_ir
    values = _add_nodes(exported_program, model, lower=lower, registry=registry)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_core.py", line 501, in _add_nodes
    raise RuntimeError(
RuntimeError: Error when translating node %grid_sampler_3d : [num_users=1] = call_function[target=torch.ops.aten.grid_sampler_3d.default](args = (%arg0_1, %arg1_1, 0, 0, True), kwargs = {}). See the stack trace for more information.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 230, in _torch_onnx_export_adapter_with_error_report
    ir_model, program = _torch_onnx_export_adaptor(*args, **kwargs, check=True)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/justinc/Documents/GitHub/torch-onnx/src/torch_onnx/_patch.py", line 197, in _torch_onnx_export_adaptor
    raise OnnxConversionError(
torch_onnx._patch.OnnxConversionError: Failed to convert the exported program to an ONNX model. This is step 2/2 of exporting the model to ONNX. Please create an issue in the PyTorch GitHub repository against the *onnx* component and attach the full error stack as well as reproduction scripts. You can run `torch_onnx.analyze()` to produce an error report after obtaining an ExportedProgram with `torch.export.export()`.

Exported program:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, arg0_1: "f32[1, 1, 2, 3, 2]", arg1_1: "f32[1, 3, 2, 4, 3]"):
            # File: /Users/justinc/Documents/GitHub/torch-onnx/tests/pytorch_test.py:13040 in forward, code: return torch.nn.functional.grid_sample(
            grid_sampler_3d: "f32[1, 1, 3, 2, 4]" = torch.ops.aten.grid_sampler_3d.default(arg0_1, arg1_1, 0, 0, True);  arg0_1 = arg1_1 = None
            return (grid_sampler_3d,)

Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg0_1'), target=None, persistent=None), InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='arg1_1'), target=None, persistent=None)], output_specs=[OutputSpec(kind=<OutputKind.USER_OUTPUT: 1>, arg=TensorArgument(name='grid_sampler_3d'), target=None)])
Range constraints: {}

Analysis

PyTorch ONNX Conversion Analysis

Model Information

The model has 0 parameters and 0 buffers (non-trainable parameters). Number of parameters per dtype: defaultdict(<class 'int'>, {}) Number of buffers per dtype: defaultdict(<class 'int'>, {})

Inputs:

• arg0_1: TensorMetadata(shape=torch.Size([1, 1, 2, 3, 2]), dtype=torch.float32, requires_grad=False, stride=(12, 12, 6, 2, 1), memory_format=torch.contiguous_format, is_quantized=False, qparams={})
• arg1_1: TensorMetadata(shape=torch.Size([1, 3, 2, 4, 3]), dtype=torch.float32, requires_grad=False, stride=(72, 24, 12, 3, 1), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

Outputs:

• grid_sampler_3d: TensorMetadata(shape=torch.Size([1, 1, 3, 2, 4]), dtype=torch.float32, requires_grad=False, stride=(24, 24, 8, 4, 1), memory_format=torch.contiguous_format, is_quantized=False, qparams={})

The FX graph has 4 nodes in total. Number of FX nodes per op:

• placeholder: 2
• call_function: 1
• output: 1

Of the call_function nodes, the counts of operators used are:

• aten.grid_sampler_3d.default: 1

ONNX Conversion Information

The model contains operators the dispatcher could not find registered ONNX decompositions for. This may be due to missing implementations, decompositions not registered correctly, or a bug in the dispatcher.

Errors grouped by operator:

• aten.grid_sampler_3d.default: No decompositions registered for the real-valued input. Example node: %grid_sampler_3d : [num_users=1] = call_function[target=torch.ops.aten.grid_sampler_3d.default](args = (%arg0_1, %arg1_1, 0, 0, True), kwargs = {}). All nodes: [grid_sampler_3d]

Profile result

  _     ._   __/__   _ _  _  _ _/_   Recorded: 10:35:23  Samples:  286
 /_//_/// /_\ / //_// / //_'/ //     Duration: 0.600     CPU time: 0.245
/   _/                      v4.6.2

Program: -c

0.600 _torch_onnx_export_adapter_with_error_report  torch_onnx/_patch.py:210
└─ 0.600 _torch_onnx_export_adaptor  torch_onnx/_patch.py:139
   ├─ 0.512 exported_program_to_ir  torch_onnx/_core.py:574
   │  ├─ 0.436 OnnxRegistry.from_torchlib  torch_onnx/_registration.py:114
   │  │  ├─ 0.283 TracedOnnxFunction.function_ir  ../onnxscript/onnxscript/values.py:587
   │  │  │  ├─ 0.193 get_src_and_ast  ../onnxscript/onnxscript/_internal/ast_utils.py:16
   │  │  │  │  ├─ 0.167 getsource  inspect.py:1256
   │  │  │  │  │     [13 frames hidden]  inspect, tokenize, <string>, <built-in>
   │  │  │  │  └─ 0.024 parse  ast.py:33
   │  │  │  │        [2 frames hidden]  ast, <built-in>
   │  │  │  └─ 0.088 Converter.translate_function_signature  ../onnxscript/onnxscript/converter.py:1463
   │  │  │     └─ 0.087 Converter._translate_function_signature_common  ../onnxscript/onnxscript/converter.py:1378
   │  │  │        ├─ 0.075 is_valid_type  ../onnxscript/onnxscript/type_annotation.py:172
   │  │  │        │  └─ 0.075 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        │     ├─ 0.061 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        │     │  └─ 0.060 <listcomp>  ../onnxscript/onnxscript/type_annotation.py:150
   │  │  │        │     │     └─ 0.060 is_value_type  ../onnxscript/onnxscript/type_annotation.py:131
   │  │  │        │     │        └─ 0.060 _is_tensor_type  ../onnxscript/onnxscript/type_annotation.py:123
   │  │  │        │     │           └─ 0.059 TensorType.__instancecheck__  <frozen abc>:117
   │  │  │        │     │                 [3 frames hidden]  <frozen abc>, <built-in>
   │  │  │        │     └─ 0.010 _remove_annotation  ../onnxscript/onnxscript/type_annotation.py:70
   │  │  │        │        └─ 0.006 get_origin  typing.py:2424
   │  │  │        └─ 0.006 Converter._eval_constant_expr  ../onnxscript/onnxscript/converter.py:451
   │  │  └─ 0.145 OpSignature.from_function  torch_onnx/_schemas.py:398
   │  │     ├─ 0.053 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │  ├─ 0.037 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │  │  ├─ 0.018 _get_allowed_types_from_type_annotation  torch_onnx/_schemas.py:255
   │  │     │  │  │  └─ 0.006 [self]  torch_onnx/_schemas.py
   │  │     │  │  └─ 0.014 _is_optional  torch_onnx/_schemas.py:185
   │  │     │  │     └─ 0.011 [self]  torch_onnx/_schemas.py
   │  │     │  └─ 0.015 DataType.__call__  enum.py:686
   │  │     │        [2 frames hidden]  enum
   │  │     ├─ 0.042 signature  inspect.py:3278
   │  │     │     [5 frames hidden]  inspect
   │  │     └─ 0.039 get_type_hints  typing.py:2300
   │  │           [9 frames hidden]  typing, <built-in>
   │  ├─ 0.040 wrapper  torch/export/exported_program.py:80
   │  │     [20 frames hidden]  torch
   │  └─ 0.033 create_onnx_friendly_decomposition_table  torch_onnx/_decomp.py:39
   │     └─ 0.028 _get_registered_ops  torch_onnx/_decomp.py:12
   │        └─ 0.025 OnnxRegistry.is_registered  torch_onnx/_registration.py:232
   │           └─ 0.025 OnnxRegistry.get_decomps  torch_onnx/_registration.py:209
   │              └─ 0.024 [self]  torch_onnx/_registration.py
   └─ 0.088 export  torch/export/__init__.py:73
         [76 frames hidden]  torch, contextlib, ast, traceback