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add assign composite backward op #51430

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merged 7 commits into from
Mar 15, 2023
Merged

add assign composite backward op #51430

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a99eb40
add assign composite backward op
SylarTiaNII Mar 9, 2023
20bb6c5
fix log msg
SylarTiaNII Mar 9, 2023
3b2539a
code style
SylarTiaNII Mar 9, 2023
9f76b64
Merge branch 'develop' of https://github.com/SylarTiaNII/Paddle into …
SylarTiaNII Mar 10, 2023
e4e7f6b
fix comp rule
SylarTiaNII Mar 13, 2023
8ff8ad6
replace assign with by_pass
SylarTiaNII Mar 14, 2023
163ad33
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
SylarTiaNII Mar 14, 2023
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22 changes: 22 additions & 0 deletions paddle/fluid/operators/assign_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,10 @@ limitations under the License. */
#include <string>

#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/prim/api/composite_backward/composite_backward_api.h"
#include "paddle/fluid/prim/utils/static/composite_grad_desc_maker.h"
#include "paddle/fluid/prim/utils/static/desc_tensor.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/unary.h"
namespace paddle {
Expand Down Expand Up @@ -109,6 +113,23 @@ class AssignGradMaker : public framework::SingleGradOpMaker<T> {
}
};

class AssignCompositeGradOpMaker : public prim::CompositeGradOpMakerBase {
using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;

public:
void Apply() override {
paddle::Tensor out_grad = this->GetSingleOutputGrad("Out");
paddle::Tensor input_grad = this->GetSingleInputGrad("X");

auto dx_ptr = this->GetOutputPtr(&input_grad);
std::string dx_name = this->GetOutputName(input_grad);

VLOG(6) << "Running assign_grad composite func";
prim::assign_grad<prim::DescTensor>(out_grad, dx_ptr);
this->RecoverOutputName(input_grad, dx_name);
}
};

DECLARE_INPLACE_OP_INFERER(AssignOpInplaceInferer, {"X", "Out"});

} // namespace operators
Expand All @@ -122,6 +143,7 @@ DECLARE_INFER_SHAPE_FUNCTOR(assign,
PD_INFER_META(phi::UnchangedInferMeta));
REGISTER_OPERATOR(assign,
ops::AssignOp,
ops::AssignCompositeGradOpMaker,
ops::AssignGradMaker<paddle::framework::OpDesc>,
ops::AssignGradMaker<paddle::imperative::OpBase>,
ops::AssignOpProtoMaker,
Expand Down
7 changes: 7 additions & 0 deletions paddle/fluid/prim/api/composite_backward/composite_backward_api.h
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Expand Up @@ -897,6 +897,13 @@ void gather_nd_grad(const Tensor& x,
}
}

template <typename T>
void assign_grad(const Tensor& out_grad, Tensor* x_grad) {
if (x_grad) {
by_pass<T>(out_grad, x_grad);
}
}

template <typename T>
void erf_grad(const Tensor& x, const Tensor& out_grad, Tensor* x_grad) {
if (x_grad) {
Expand Down
1 change: 1 addition & 0 deletions paddle/phi/api/yaml/legacy_backward.yaml
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Expand Up @@ -94,6 +94,7 @@
forward : assign (Tensor x) -> Tensor(out)
args : (Tensor out_grad)
output : Tensor(x_grad)
composite: assign_grad(out_grad, x_grad)
invoke : assign(out_grad)

- backward_op : assign_out__grad
Expand Down
8 changes: 6 additions & 2 deletions python/paddle/fluid/tests/unittests/test_assign_op.py
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Expand Up @@ -30,6 +30,8 @@ class TestAssignOp(op_test.OpTest):
def setUp(self):
self.python_api = paddle.assign
self.op_type = "assign"
self.prim_op_type = "prim"
self.enable_cinn = False
x = np.random.random(size=(100, 10)).astype('float64')
self.inputs = {'X': x}
self.outputs = {'Out': x}
Expand All @@ -41,14 +43,16 @@ def test_forward(self):

def test_backward(self):
paddle.enable_static()
self.check_grad(['X'], 'Out', check_eager=True)
self.check_grad(['X'], 'Out', check_eager=True, check_prim=True)
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pr标注下原算子缺少bfloat16单测，所以组合算子也没有进行测试

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done

paddle.disable_static()


class TestAssignFP16Op(op_test.OpTest):
def setUp(self):
self.python_api = paddle.assign
self.op_type = "assign"
self.prim_op_type = "prim"
self.enable_cinn = False
x = np.random.random(size=(100, 10)).astype('float16')
self.inputs = {'X': x}
self.outputs = {'Out': x}
Expand All @@ -60,7 +64,7 @@ def test_forward(self):

def test_backward(self):
paddle.enable_static()
self.check_grad(['X'], 'Out', check_eager=True)
self.check_grad(['X'], 'Out', check_eager=True, check_prim=True)
paddle.disable_static()


Expand Down