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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72741
as titled.
Context:
This is useful in fast mitigating feature induced overfitting in the sense that we can do omni-transfer on a trained model and apply dropout with ratio = 1 on features resulting in overfitting. Directly removing the features would not be feasible on omni-transfer scenarios since the downstream FC sizes would change.
Experimental records:
https://fb.quip.com/npIkAgRc8jl9#temp:C:DWC050ceaba14424d23a78462c01
Doing dropout = 1 on selected features improves the eval NE over the next few hours (compared to v0 baseline) as is shown in the figures.
Test Plan:
```
buck test caffe2/caffe2/python/operator_test:dropout_op_test
```
Reviewed By: ustctf
Differential Revision: D34178732
fbshipit-source-id: 533feebe21bc582eefd756de397d5c7807c7438d
(cherry picked from commit 5dabf9c484)
56 lines
1.4 KiB
C++
56 lines
1.4 KiB
C++
#ifndef CAFFE2_OPERATORS_DROPOUT_OP_H_
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#define CAFFE2_OPERATORS_DROPOUT_OP_H_
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#include "caffe2/core/context.h"
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#include "caffe2/core/logging.h"
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#include "caffe2/core/operator.h"
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#include "caffe2/utils/math.h"
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namespace caffe2 {
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template <typename T, class Context>
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class DropoutOp final : public Operator<Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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template <class... Args>
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explicit DropoutOp(Args&&... args)
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: Operator<Context>(std::forward<Args>(args)...),
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ratio_(this->template GetSingleArgument<float>("ratio", 0.5)),
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is_test_(
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this->template GetSingleArgument<int>(OpSchema::Arg_IsTest, 0)) {
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CAFFE_ENFORCE_GE(ratio_, 0);
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}
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bool RunOnDevice() override;
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protected:
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float ratio_;
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bool is_test_;
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// Input: X; Output: Y, mask.
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};
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template <typename T, class Context>
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class DropoutGradientOp final : public Operator<Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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template <class... Args>
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explicit DropoutGradientOp(Args&&... args)
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: Operator<Context>(std::forward<Args>(args)...),
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ratio_(this->template GetSingleArgument<float>("ratio", 0.5)),
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is_test_(
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this->template GetSingleArgument<int>(OpSchema::Arg_IsTest, 0)) {
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CAFFE_ENFORCE_GE(ratio_, 0);
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}
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bool RunOnDevice() override;
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protected:
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float ratio_;
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bool is_test_;
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// Input: dY, mask; Output: dX
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};
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} // namespace caffe2
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#endif // CAFFE2_OPERATORS_DROPOUT_OP_H_
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