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[phi] move sigmoid_cross_entopy_with_logits log_loss cumsum auc infershape to phi #40200

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merged 7 commits into from
Mar 8, 2022
Merged

[phi] move sigmoid_cross_entopy_with_logits log_loss cumsum auc infershape to phi #40200

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2d9d4b7
move infershapes to phi
linjieccc Mar 6, 2022
1f30143
Merge branch 'develop' into move_infershapes
linjieccc Mar 7, 2022
a0b3c06
Merge branch 'PaddlePaddle:develop' into move_infershapes
linjieccc Mar 7, 2022
170baae
Merge branch 'PaddlePaddle:develop' into move_infershapes
linjieccc Mar 7, 2022
b736436
Merge branch 'develop' into move_infershapes
linjieccc Mar 7, 2022
341b683
update code format
linjieccc Mar 7, 2022
fd05059
update code format
linjieccc Mar 7, 2022
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20 changes: 7 additions & 13 deletions paddle/fluid/operators/cumsum_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -12,26 +12,18 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/unary.h"

namespace paddle {
namespace operators {

class CumOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;

void InferShape(framework::InferShapeContext *ctx) const override {
if (ctx->Attrs().Get<bool>("flatten")) {
ctx->SetOutputDim("Out",
phi::make_ddim({phi::product(ctx->GetInputDim("X"))}));
} else {
ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
}

ctx->ShareLoD("X", /*->*/ "Out");
}
};

class CumsumOpMaker : public framework::OpProtoAndCheckerMaker {
Expand Down Expand Up @@ -87,10 +79,12 @@ class CumsumGradMaker : public framework::SingleGradOpMaker<T> {

namespace ops = paddle::operators;
using CPU = paddle::platform::CPUDeviceContext;

DECLARE_INFER_SHAPE_FUNCTOR(cumsum, CumsumInferShapeFunctor,
PD_INFER_META(phi::CumsumInferMeta));
REGISTER_OPERATOR(cumsum, ops::CumOp, ops::CumsumOpMaker,
ops::CumsumGradMaker<paddle::framework::OpDesc>,
ops::CumsumGradMaker<paddle::imperative::OpBase>);
ops::CumsumGradMaker<paddle::imperative::OpBase>,
CumsumInferShapeFunctor);

REGISTER_OP_VERSION(cumsum)
.AddCheckpoint(
Expand Down
45 changes: 7 additions & 38 deletions paddle/fluid/operators/log_loss_op.cc
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Expand Up @@ -13,51 +13,17 @@ See the License for the specific language governing permissions and
limitations under the License. */

#include <memory>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/binary.h"

namespace paddle {
namespace operators {

class LogLossOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;

void InferShape(framework::InferShapeContext* ctx) const override {
OP_INOUT_CHECK(ctx->HasInput("Predicted"), "Input", "Predicted", "LogLoss");
OP_INOUT_CHECK(ctx->HasInput("Labels"), "Input", "Labels", "LogLoss");

auto pred_dims = ctx->GetInputDim("Predicted");
auto label_dims = ctx->GetInputDim("Labels");

if (ctx->IsRuntime() ||
(phi::product(pred_dims) > 0 && phi::product(label_dims) > 0)) {
PADDLE_ENFORCE_EQ(
pred_dims, label_dims,
platform::errors::InvalidArgument(
"The dimensions of Input(Predicted) must be equal to the"
"dimensions of Input(Labels), but received dimensions of "
"Input(Predicted)"
"is [%s], received dimensions of Input(Labels) is [%s].",
pred_dims, label_dims));
}
PADDLE_ENFORCE_EQ(pred_dims.size(), 2,
platform::errors::InvalidArgument(
"The dimensions of Input(Predicted) must be 2,"
"But received dimensions of Input(Predicted)"
"is [%d]",
pred_dims.size()));
if (ctx->IsRuntime()) {
PADDLE_ENFORCE_EQ(
pred_dims[1], 1,
platform::errors::InvalidArgument(
"Each row of Input(Predicted) contains a real value, "
"so the 2nd dimension of Input(X) must be 1,"
"But got [%d]",
pred_dims[1]));
}
ctx->SetOutputDim("Loss", {pred_dims[0], 1});
ctx->ShareLoD("Predicted", "Loss");
}
};

template <typename AttrType>
Expand Down Expand Up @@ -145,7 +111,10 @@ class LogLossGradMaker : public framework::SingleGradOpMaker<T> {
} // namespace paddle

namespace ops = paddle::operators;
DECLARE_INFER_SHAPE_FUNCTOR(log_loss, LogLossInferShapeFunctor,
PD_INFER_META(phi::LogLossInferMeta));
REGISTER_OPERATOR(log_loss, ops::LogLossOp, ops::LogLossOpMaker<float>,
ops::LogLossGradMaker<paddle::framework::OpDesc>,
ops::LogLossGradMaker<paddle::imperative::OpBase>);
ops::LogLossGradMaker<paddle::imperative::OpBase>,
LogLossInferShapeFunctor);
REGISTER_OPERATOR(log_loss_grad, ops::LogLossGradOp);
72 changes: 7 additions & 65 deletions paddle/fluid/operators/metrics/auc_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,10 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/multiary.h"

namespace paddle {
namespace operators {
Expand All @@ -21,70 +24,6 @@ class AucOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;

protected:
void InferShape(framework::InferShapeContext *ctx) const override {
OP_INOUT_CHECK(ctx->HasInput("Predict"), "Input", "Predict", "Auc");
OP_INOUT_CHECK(ctx->HasInput("Label"), "Input", "Label", "Auc");
auto predict_dims = ctx->GetInputDim("Predict");
auto label_dims = ctx->GetInputDim("Label");
PADDLE_ENFORCE_GE(
predict_dims.size(), 2,
platform::errors::InvalidArgument(
"The Input(Predict) has not been initialized properly. The "
"shape of Input(Predict) = [%s], the shape size must be "
"greater_equal 2.",
predict_dims));
auto predict_width = predict_dims[1];
PADDLE_ENFORCE_NE(
phi::product(predict_dims), 0,
platform::errors::InvalidArgument(
"The Input(Predict) has not been initialized properly. The "
"shape of Input(Predict) = [%s], the shape can not involes 0.",
predict_dims));
PADDLE_ENFORCE_NE(
phi::product(label_dims), 0,
platform::errors::InvalidArgument(
"The Input(Label) has not been initialized properly. The "
"shape of Input(Label) = [%s], the shape can not involes 0.",
label_dims));
if (ctx->IsRuntime()) {
PADDLE_ENFORCE_LE(predict_width, 2,
platform::errors::InvalidArgument(
"Only support binary classification,"
"prediction dims[1] should be 1 or 2"));
}
auto predict_height = ctx->GetInputDim("Predict")[0];
auto label_height = ctx->GetInputDim("Label")[0];

if (ctx->IsRuntime()) {
PADDLE_ENFORCE_EQ(predict_height, label_height,
platform::errors::InvalidArgument(
"Out and Label should have same height."));
}

int num_pred_buckets = ctx->Attrs().Get<int>("num_thresholds") + 1;
int slide_steps = ctx->Attrs().Get<int>("slide_steps");

PADDLE_ENFORCE_GE(
num_pred_buckets, 1,
platform::errors::InvalidArgument("num_thresholds must larger than 1"));
PADDLE_ENFORCE_GE(slide_steps, 0,
platform::errors::InvalidArgument(
"slide_steps must be natural number"));

ctx->SetOutputDim("AUC", {1});

if (slide_steps) {
ctx->SetOutputDim("StatPosOut",
{(1 + slide_steps) * num_pred_buckets + 1});
ctx->SetOutputDim("StatNegOut",
{(1 + slide_steps) * num_pred_buckets + 1});
} else {
ctx->SetOutputDim("StatPosOut", {1, num_pred_buckets});
ctx->SetOutputDim("StatNegOut", {1, num_pred_buckets});
}
}

protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext &ctx) const override {
Expand Down Expand Up @@ -145,4 +84,7 @@ There are two types of possible curves:
} // namespace paddle

namespace ops = paddle::operators;
REGISTER_OP_WITHOUT_GRADIENT(auc, ops::AucOp, ops::AucOpMaker);
DECLARE_INFER_SHAPE_FUNCTOR(auc, AucInferShapeFunctor,
PD_INFER_META(phi::AucInferMeta));
REGISTER_OP_WITHOUT_GRADIENT(auc, ops::AucOp, ops::AucOpMaker,
AucInferShapeFunctor);
50 changes: 9 additions & 41 deletions paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,10 @@ limitations under the License. */
#include <memory>
#include <string>
#include <vector>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/binary.h"

namespace paddle {
namespace operators {
Expand All @@ -26,46 +29,6 @@ const int kIgnoreIndex = -100;
class SigmoidCrossEntropyWithLogitsOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;

void InferShape(framework::InferShapeContext* ctx) const override {
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X",
"SigmoidCrossEntropyWithLogitsOp");
OP_INOUT_CHECK(ctx->HasInput("Label"), "Input", "Label",
"SigmoidCrossEntropyWithLogitsOp");
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out",
"SigmoidCrossEntropyWithLogitsOp");

auto x_dims = ctx->GetInputDim("X");
auto labels_dims = ctx->GetInputDim("Label");

int rank = x_dims.size();
PADDLE_ENFORCE_EQ(rank, labels_dims.size(),
platform::errors::InvalidArgument(
"Input(X) and Input(Label) shall have the same rank."
"But received: the rank of Input(X) is [%d], "
"the rank of Input(Label) is [%d].",
rank, labels_dims.size()));

bool check = true;
if ((!ctx->IsRuntime()) &&
(phi::product(x_dims) <= 0 || phi::product(labels_dims) <= 0)) {
check = false;
}

if (check) {
PADDLE_ENFORCE_EQ(
phi::slice_ddim(x_dims, 0, rank),
phi::slice_ddim(labels_dims, 0, rank),
platform::errors::InvalidArgument(
"Input(X) and Input(Label) shall have the same shape "
"except the last dimension. But received: the shape of "
"Input(X) is [%s], the shape of Input(Label) is [%s].",
x_dims, labels_dims));
}

ctx->ShareDim("X", /*->*/ "Out");
ctx->ShareLoD("X", /*->*/ "Out");
}
};

class SigmoidCrossEntropyWithLogitsGradOp
Expand Down Expand Up @@ -201,12 +164,17 @@ DECLARE_INPLACE_OP_INFERER(SigmoidCrossEntropyWithLogitsGradInplaceInferer,
} // namespace paddle

namespace ops = paddle::operators;
DECLARE_INFER_SHAPE_FUNCTOR(
sigmoid_cross_entropy_with_logits,
SigmoidCrossEntropyWithLogitsInferShapeFunctor,
PD_INFER_META(phi::SigmoidCrossEntropyWithLogitsInferMeta));
REGISTER_OPERATOR(
sigmoid_cross_entropy_with_logits, ops::SigmoidCrossEntropyWithLogitsOp,
ops::SigmoidCrossEntropyWithLogitsOpMaker,
ops::SigmoidCrossEntropyWithLogitsGradOpMaker<paddle::framework::OpDesc>,
ops::SigmoidCrossEntropyWithLogitsGradOpMaker<paddle::imperative::OpBase>,
ops::SigmoidCrossEntropyWithLogitsInplaceInferer);
ops::SigmoidCrossEntropyWithLogitsInplaceInferer,
SigmoidCrossEntropyWithLogitsInferShapeFunctor);
REGISTER_OPERATOR(sigmoid_cross_entropy_with_logits_grad,
ops::SigmoidCrossEntropyWithLogitsGradOp,
ops::SigmoidCrossEntropyWithLogitsGradInplaceInferer);
84 changes: 84 additions & 0 deletions paddle/phi/infermeta/binary.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -456,6 +456,90 @@ void BCELossInferMeta(const MetaTensor& input,
out->share_lod(input);
}

void SigmoidCrossEntropyWithLogitsInferMeta(const MetaTensor& x,
const MetaTensor& label,
bool normalize,
int ignore_index,
MetaTensor* out,
MetaConfig config) {
auto x_dims = x.dims();
auto labels_dims = label.dims();

int rank = x_dims.size();
PADDLE_ENFORCE_EQ(rank,
labels_dims.size(),
phi::errors::InvalidArgument(
"Input(X) and Input(Label) shall have the same rank."
"But received: the rank of Input(X) is [%d], "
"the rank of Input(Label) is [%d].",
rank,
labels_dims.size()));

bool check = true;
if ((!config.is_runtime) &&
(phi::product(x_dims) <= 0 || phi::product(labels_dims) <= 0)) {
check = false;
}

if (check) {
PADDLE_ENFORCE_EQ(
phi::slice_ddim(x_dims, 0, rank),
phi::slice_ddim(labels_dims, 0, rank),
phi::errors::InvalidArgument(
"Input(X) and Input(Label) shall have the same shape "
"except the last dimension. But received: the shape of "
"Input(X) is [%s], the shape of Input(Label) is [%s].",
x_dims,
labels_dims));
}

out->set_dims(x_dims);
out->set_dtype(x.dtype());
out->share_lod(x);
}

void LogLossInferMeta(const MetaTensor& input,
const MetaTensor& label,
float epsilon,
MetaTensor* out,
MetaConfig config) {
auto pred_dims = input.dims();
auto label_dims = label.dims();

if (config.is_runtime ||
(phi::product(pred_dims) > 0 && phi::product(label_dims) > 0)) {
PADDLE_ENFORCE_EQ(
pred_dims,
label_dims,
phi::errors::InvalidArgument(
"The dimensions of Input(Predicted) must be equal to the"
"dimensions of Input(Labels), but received dimensions of "
"Input(Predicted)"
"is [%s], received dimensions of Input(Labels) is [%s].",
pred_dims,
label_dims));
}
PADDLE_ENFORCE_EQ(pred_dims.size(),
2,
phi::errors::InvalidArgument(
"The dimensions of Input(Predicted) must be 2,"
"But received dimensions of Input(Predicted)"
"is [%d]",
pred_dims.size()));
if (config.is_runtime) {
PADDLE_ENFORCE_EQ(pred_dims[1],
1,
phi::errors::InvalidArgument(
"Each row of Input(Predicted) contains a real value, "
"so the 2nd dimension of Input(X) must be 1,"
"But got [%d]",
pred_dims[1]));
}
out->set_dims({pred_dims[0], 1});
out->set_dtype(input.dtype());
out->share_lod(input);
}

void DistInferMeta(const MetaTensor& x,
const MetaTensor& y,
float p,
Expand Down
13 changes: 13 additions & 0 deletions paddle/phi/infermeta/binary.h
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Original file line number Diff line number Diff line change
Expand Up @@ -85,6 +85,19 @@ void BCELossInferMeta(const MetaTensor& input,
MetaTensor* out,
MetaConfig config = MetaConfig());

void SigmoidCrossEntropyWithLogitsInferMeta(const MetaTensor& x,
const MetaTensor& label,
bool normalize,
int ignore_index,
MetaTensor* out,
MetaConfig config = MetaConfig());

void LogLossInferMeta(const MetaTensor& input,
const MetaTensor& label,
float epsilon,
MetaTensor* out,
MetaConfig config = MetaConfig());

void DistInferMeta(const MetaTensor& x,
const MetaTensor& y,
float p,
Expand Down
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