mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-21 05:34:18 +08:00
5f2f343e1e
Example:
```python
File "/home/xmfan/core/a/pytorch/torch/autograd/graph.py", line 829, in _engine_run_backward
return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
NotImplementedError: TorchDispatchMode not yet implemented for compiled autograd.
You can disable compiled autograd for this operation by:
1. Relocating the unsupported autograd call outside the compiled region.
2. Wrapping the unsupported autograd call within a scope that disables compiled autograd.
3. Configuring the specific compilation unit to disable compiled autograd.
4. Globally disabling compiled autograd at the application's initialization.
```
No duplicate error messages for python side trace-time errors
```python
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/xmfan/core/a/pytorch/torch/_dynamo/compiled_autograd.py", line 344, in begin_capture
raise NotImplementedError(
NotImplementedError: Found tensor of type <class 'torch.nn.utils._expanded_weights.expanded_weights_impl.ExpandedWeight'>, which is not supported by FakeTensorMode. You can turn off compiled autograd by either:
1. Moving the unsupported autograd call outside of the torch.compile'd region.
2. Wrapping the unsupported autograd call in the torch._dynamo.compiled_autograd._disable() context manager.
3. Setting torch._dynamo.config.compiled_autograd=False for the torch.compile call containing the unsupported autograd call.
4. Setting torch._dynamo.config.compiled_autograd=False at the start of the program.
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/156509
Approved by: https://github.com/jansel
ghstack dependencies: #156374
73 lines
2.2 KiB
C++
73 lines
2.2 KiB
C++
#pragma once
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#include <ATen/Tensor.h>
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#include <torch/csrc/Export.h>
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#include <string>
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#include <vector>
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namespace torch::dynamo::autograd {
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class CompiledNodeArgs;
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class SwapSavedVariables;
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struct PackedArgs;
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} // namespace torch::dynamo::autograd
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// A hook that's called on gradients
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namespace torch::autograd {
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using Variable = at::Tensor;
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using variable_list = std::vector<Variable>;
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struct TORCH_API FunctionPreHook {
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virtual ~FunctionPreHook() = default;
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virtual variable_list operator()(const variable_list& grads) = 0;
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// only implemented for python hooks, registers hook with compiled autograd
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virtual void compiled_args(
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torch::dynamo::autograd::CompiledNodeArgs& args) const {
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TORCH_CHECK_NOT_IMPLEMENTED(
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false,
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std::string("compiled_args nyi, see [Note: Compiled Autograd] ") +
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typeid(*this).name());
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}
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};
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struct TORCH_API FunctionPostHook {
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virtual ~FunctionPostHook() = default;
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virtual variable_list operator()(
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const variable_list& outputs /* grad_inputs */,
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const variable_list& inputs /* grad_outputs */) = 0;
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// only implemented for python hooks, registers hook with compiled autograd
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virtual void compiled_args(
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torch::dynamo::autograd::CompiledNodeArgs& args) const {
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TORCH_CHECK_NOT_IMPLEMENTED(
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false,
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std::string("compiled_args nyi, see [Note: Compiled Autograd] ") +
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typeid(*this).name());
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}
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};
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struct TORCH_API PostAccumulateGradHook {
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virtual ~PostAccumulateGradHook() = default;
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virtual void operator()(const Variable& tensor) = 0;
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// only implemented for python hooks on nodes, registers hook with compiled
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// autograd
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virtual void compiled_args(
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torch::dynamo::autograd::CompiledNodeArgs& args) const {
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TORCH_CHECK_NOT_IMPLEMENTED(
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false,
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std::string("compiled_args nyi, see [Note: Compiled Autograd] ") +
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typeid(*this).name());
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}
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virtual void apply_with_saved(
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Variable&,
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torch::dynamo::autograd::SwapSavedVariables&) {
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TORCH_CHECK_NOT_IMPLEMENTED(
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false,
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std::string("compiled_args nyi, see [Note: Compiled Autograd] ") +
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typeid(*this).name());
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}
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};
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} // namespace torch::autograd
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