diff --git a/paddle/fluid/operators/scatter_nd_add_op.cc b/paddle/fluid/operators/scatter_nd_add_op.cc deleted file mode 100644 index 4ed08a387f2a0..0000000000000 --- a/paddle/fluid/operators/scatter_nd_add_op.cc +++ /dev/null @@ -1,141 +0,0 @@ -/* Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. - -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -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 -#include - -#include "paddle/fluid/framework/infershape_utils.h" -#include "paddle/fluid/framework/op_registry.h" -#include "paddle/phi/core/ddim.h" -#include "paddle/phi/infermeta/backward.h" -#include "paddle/phi/infermeta/ternary.h" - -namespace paddle { -namespace operators { - -class ScatterNdAddOp : public framework::OperatorWithKernel { - public: - using framework::OperatorWithKernel::OperatorWithKernel; - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext& ctx) const override { - PADDLE_ENFORCE_EQ(OperatorWithKernel::IndicateVarDataType(ctx, "X"), - OperatorWithKernel::IndicateVarDataType(ctx, "Updates"), - platform::errors::InvalidArgument( - "Ref and Updates must have same type")); - return framework::OpKernelType( - framework::TransToProtoVarType( - ctx.Input("X")->type()), - ctx.device_context()); - } -}; - -class ScatterNdAddGradOp : public framework::OperatorWithKernel { - public: - using framework::OperatorWithKernel::OperatorWithKernel; - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext& ctx) const override { - return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType( - ctx, framework::GradVarName("Out")), - ctx.device_context()); - } -}; - -class ScatterNdAddOpMaker : public framework::OpProtoAndCheckerMaker { - public: - void Make() override { - AddInput("X", "The source input of scatter_nd_add op"); - AddInput("Index", - "The index input of scatter_nd_add op where X will be updated"); - AddInput("Updates", "The updated value of scatter_nd_add op"); - AddOutput("Out", "The output of scatter_nd_add op"); - AddComment(R"DOC( -Scatter_nd_add Operator. - -Output is obtained by applying sparse addition to a single value or slice in a Variable. - - Given: - * Case 1: - ref = [0, 1, 2, 3, 4, 5] - index = [[1], [2], [3], [1]] - updates = [9, 10, 11, 12] - - we get: - - output = [0, 22, 12, 14, 4, 5] - - * Case 2: - ref = [[65, 17], [-14, -25]] - index = [[], []] - updates = [[[-1, -2], [1, 2]], - [[3, 4], [-3, -4]]] - ref.shape = (2, 2) - index.shape = (2, 0) - updates.shape = (2, 2, 2) - - we get: - - output = [[67, 19], [-16, -27]] -)DOC"); - } -}; - -template -class ScatterNdAddGradMaker : public framework::SingleGradOpMaker { - public: - using framework::SingleGradOpMaker::SingleGradOpMaker; - - protected: - void Apply(GradOpPtr op) const override { - op->SetType("scatter_nd_add_grad"); - op->SetInput("Index", this->Input("Index")); - op->SetInput("Updates", this->Input("Updates")); - op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); - op->SetOutput(framework::GradVarName("X"), this->InputGrad("X")); - op->SetOutput(framework::GradVarName("Updates"), - this->InputGrad("Updates")); - op->SetAttrMap(this->Attrs()); - } -}; - -DECLARE_NO_NEED_BUFFER_VARS_INFERER(ScatterNdAddGradNoNeedBufferVarsInferer, - "Updates"); - -} // namespace operators -} // namespace paddle - -namespace ops = paddle::operators; - -DECLARE_INFER_SHAPE_FUNCTOR(scatter_nd_add, - ScatterNdAddInferShapeFunctor, - PD_INFER_META(phi::ScatterNdAddInferMeta)); - -DECLARE_INFER_SHAPE_FUNCTOR(scatter_nd_add_grad, - ScatterNdAddGradInferShapeFunctor, - PD_INFER_META(phi::ScatterNdAddGradInferMeta)); - -REGISTER_OPERATOR(scatter_nd_add, - ops::ScatterNdAddOp, - ops::ScatterNdAddOpMaker, - ops::ScatterNdAddGradMaker, - ops::ScatterNdAddGradMaker, - ScatterNdAddInferShapeFunctor); - -REGISTER_OPERATOR(scatter_nd_add_grad, - ops::ScatterNdAddGradOp, - ops::ScatterNdAddGradNoNeedBufferVarsInferer, - ScatterNdAddGradInferShapeFunctor); diff --git a/paddle/fluid/operators/scatter_op.cc b/paddle/fluid/operators/scatter_op.cc deleted file mode 100644 index dd758fcbe39cd..0000000000000 --- a/paddle/fluid/operators/scatter_op.cc +++ /dev/null @@ -1,126 +0,0 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. - -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -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 - -#include "paddle/fluid/framework/infershape_utils.h" -#include "paddle/fluid/framework/op_registry.h" -#include "paddle/phi/core/ddim.h" -#include "paddle/phi/infermeta/backward.h" -#include "paddle/phi/infermeta/ternary.h" - -namespace paddle { -namespace operators { - -class ScatterOp : public framework::OperatorWithKernel { - public: - using framework::OperatorWithKernel::OperatorWithKernel; - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext& ctx) const override { - return framework::OpKernelType( - OperatorWithKernel::IndicateVarDataType(ctx, "X"), - ctx.device_context()); - } -}; - -class ScatterGradOp : public framework::OperatorWithKernel { - public: - using framework::OperatorWithKernel::OperatorWithKernel; - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext& ctx) const override { - return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType( - ctx, framework::GradVarName("Out")), - ctx.device_context()); - } -}; - -class ScatterOpMaker : public framework::OpProtoAndCheckerMaker { - public: - void Make() override { - AddInput("X", "The source input of scatter op"); - AddInput("Ids", "The index input of scatter op where X will be updated"); - AddInput("Updates", "The updated value of scatter op"); - AddOutput("Out", "The output of scatter op"); - AddAttr("overwrite", - "(bool, default: True) " - "The mode that updating the output when has same index," - "If True, use the overwrite mode to update the output" - "of the same index, if False, use the accumulate mode to" - "update the output of the same index,Default value is True." - "You can set overwrite=False to implement scatter_add.") - .SetDefault(true); - AddComment(R"DOC( -Scatter Operator. - -This operator obtains output by updating the input on selected indices on the first axis: - -$$ -Out = X \\ -Out[Ids] = Updates -$$ - -)DOC"); - } -}; - -template -class ScatterGradMaker : public framework::SingleGradOpMaker { - public: - using framework::SingleGradOpMaker::SingleGradOpMaker; - - protected: - void Apply(GradOpPtr op) const override { - op->SetType("scatter_grad"); - op->SetInput("Ids", this->Input("Ids")); - op->SetInput("Updates", this->Input("Updates")); - op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); - op->SetOutput(framework::GradVarName("X"), this->InputGrad("X")); - op->SetOutput(framework::GradVarName("Updates"), - this->InputGrad("Updates")); - op->SetAttrMap(this->Attrs()); - } -}; - -DECLARE_NO_NEED_BUFFER_VARS_INFERER(ScatterGradNoNeedBufferVarsInferer, - "Updates"); - -DECLARE_INPLACE_OP_INFERER(ScatterInplaceInferer, {"X", "Out"}); - -} // namespace operators -} // namespace paddle - -DECLARE_INFER_SHAPE_FUNCTOR(scatter, - ScatterInferShapeFunctor, - PD_INFER_META(phi::ScatterInferMeta)); - -DECLARE_INFER_SHAPE_FUNCTOR(scatter_grad, - ScatterGradInferShapeFunctor, - PD_INFER_META(phi::ScatterGradInferMeta)); - -namespace ops = paddle::operators; -REGISTER_OPERATOR(scatter, - ops::ScatterOp, - ops::ScatterOpMaker, - ops::ScatterGradMaker, - ops::ScatterGradMaker, - ops::ScatterInplaceInferer, - ScatterInferShapeFunctor); -REGISTER_OPERATOR(scatter_grad, - ops::ScatterGradOp, - ops::ScatterGradNoNeedBufferVarsInferer, - ScatterGradInferShapeFunctor); diff --git a/paddle/fluid/operators/selu_op.cc b/paddle/fluid/operators/selu_op.cc deleted file mode 100644 index 0bf180e27d142..0000000000000 --- a/paddle/fluid/operators/selu_op.cc +++ /dev/null @@ -1,138 +0,0 @@ -/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. - -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -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 -#include -#include - -#include "paddle/fluid/framework/infershape_utils.h" -#include "paddle/fluid/framework/op_registry.h" -#include "paddle/fluid/framework/operator.h" -#include "paddle/phi/infermeta/unary.h" - -namespace paddle { -namespace operators { - -class SeluOp : public framework::OperatorWithKernel { - public: - SeluOp(const std::string &type, - const framework::VariableNameMap &inputs, - const framework::VariableNameMap &outputs, - const framework::AttributeMap &attrs) - : OperatorWithKernel(type, inputs, outputs, attrs) {} - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext &ctx) const override { - return framework::OpKernelType( - OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace()); - } -}; - -class SeluOpInferVarType : public framework::PassInDtypeAndVarTypeToOutput { - protected: - std::unordered_map &GetInputOutputWithSameType() - const override { - static std::unordered_map m{{"X", /*->*/ "Out"}}; - return m; - } -}; - -class SeluOpMaker : public framework::OpProtoAndCheckerMaker { - public: - void Make() override { - AddInput("X", "The input tensor of selu operator."); - AddOutput("Out", "The output tensor of selu operator."); - AddAttr("scale", - "(float) the default value is 1.0507~. For more " - "information about this value, please refer to:" - "https://arxiv.org/abs/1706.02515.") - .SetDefault(1.0507009873554804934193349852946); - AddAttr("alpha", - "(float) the default value is 1.6732~. For more " - "information about this value, please refer to:" - "https://arxiv.org/abs/1706.02515.") - .SetDefault(1.6732632423543772848170429916717); - AddComment(R"DOC( -Selu Operator. - -The equation is: -$$ -f(x) =\lambda* -\begin{cases} - \quad \quad x, \quad \quad \quad \text{if} \ x > 0 \\ - \alpha * e^x - \alpha, \qquad \text{if} \ x <= 0 -\end{cases} -$$ - -The input `X` can carry the LoD (Level of Details) information, -or not. And the output shares the LoD information with input `X`. -)DOC"); - } -}; - -template -class SeluGradMaker : public framework::SingleGradOpMaker { - public: - using framework::SingleGradOpMaker::SingleGradOpMaker; - - void Apply(GradOpPtr grad_op) const override { - grad_op->SetType("selu_grad"); - grad_op->SetInput("Out", this->Output("Out")); - grad_op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); - grad_op->SetOutput(framework::GradVarName("X"), this->InputGrad("X")); - grad_op->SetAttrMap(this->Attrs()); - } -}; - -class SeluGradOp : public framework::OperatorWithKernel { - public: - using framework::OperatorWithKernel::OperatorWithKernel; - - void InferShape(framework::InferShapeContext *ctx) const override { - OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), - "Input", - "Out@GRAD", - "selu_grad"); - OP_INOUT_CHECK(ctx->HasInput("Out"), "Input", "Out", "selu_grad"); - auto x_grad_name = framework::GradVarName("X"); - ctx->SetOutputDim(x_grad_name, ctx->GetInputDim("Out")); - } - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext &ctx) const override { - return framework::OpKernelType( - OperatorWithKernel::IndicateVarDataType(ctx, "Out"), ctx.GetPlace()); - } -}; - -} // namespace operators -} // namespace paddle - -namespace ops = paddle::operators; - -DECLARE_INFER_SHAPE_FUNCTOR(selu, - SeluInferShapeFunctor, - PD_INFER_META(phi::UnchangedInferMeta)); - -REGISTER_OPERATOR(selu, - ops::SeluOp, - ops::SeluOpMaker, - ops::SeluOpInferVarType, - ops::SeluGradMaker, - ops::SeluGradMaker, - SeluInferShapeFunctor); - -REGISTER_OPERATOR(selu_grad, ops::SeluGradOp); diff --git a/paddle/fluid/operators/shard_index_op.cc b/paddle/fluid/operators/shard_index_op.cc deleted file mode 100644 index 4c22efc2af299..0000000000000 --- a/paddle/fluid/operators/shard_index_op.cc +++ /dev/null @@ -1,109 +0,0 @@ -// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// 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/unary.h" - -namespace paddle { -namespace operators { - -class ShardIndexOp : public framework::OperatorWithKernel { - public: - using framework::OperatorWithKernel::OperatorWithKernel; - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext& ctx) const override { - return framework::OpKernelType( - OperatorWithKernel::IndicateVarDataType(ctx, "X"), - ctx.device_context()); - } -}; - -class ShardIndexOpMaker : public framework::OpProtoAndCheckerMaker { - public: - void Make() override { - AddInput("X", - "(phi::DenseTensor, phi::DenseTensor) Input variable. " - "Each value " - "of X is an index."); - AddOutput( - "Out", - "(Tensor, Tensor) Output tensor with same shape as X. " - "The tensor consists of sharding representations of values in X."); - AddAttr("index_num", - "A positive integer to specify the range of the input X."); - - AddAttr("nshards", - "A positive integer to specify the number of shards."); - AddAttr("shard_id", "The current shard id"); - AddAttr("ignore_value", "An integer value out of sharded range") - .SetDefault(-1); - AddComment(R"DOC( -This layer creates the sharded index for input. This layers is used in -model- and data- parallel mixed training generally, in which the index -data (usually the label) should be recaculated in each trainer according -to - -.. math:: - - assert index_num % nshards == 0 - - shard_size = index_num / nshards - - y = x % shard_size if x / shard_size == shard_id else ignore_value - -We take the distributed one-hot representation to show what this layer is -used for. The distributed one-hot representation is separated into multiple -shards, and each shard is filling zeros except the one with the index -inside. In order to create these sharded representation in each trainer, -the original index should be recalculated (i.e. sharded) before. - -Examples: - - X is a Tensor of integer values: - X.shape = [4, 1] - X.data = [[1], [6], [12], [19]] - - suppose index_num = 20 and nshards = 2, then we get shard_size = 10 - - if shard_id == 0, we get the Out: - Out.shape = [4, 1] - Out.data = [[1], [6], [-1], [-1]] - - if shard_id == 1, we get the Out: - Out.shape = [4, 1] - Out.data = [[-1], [-1], [2], [9]] - - the default `ignore_value` -1 is used in this example. -)DOC"); - } -}; - -} // namespace operators -} // namespace paddle - -namespace ops = paddle::operators; -DECLARE_INFER_SHAPE_FUNCTOR(shard_index, - ShardIndexInferShapeFunctor, - PD_INFER_META(phi::ShardIndexInferMeta)); -REGISTER_OPERATOR( - shard_index, - ops::ShardIndexOp, - ops::ShardIndexOpMaker, - paddle::framework::EmptyGradOpMaker, - paddle::framework::EmptyGradOpMaker, - ShardIndexInferShapeFunctor); diff --git a/paddle/fluid/operators/viterbi_decode_op.cc b/paddle/fluid/operators/viterbi_decode_op.cc deleted file mode 100644 index 13c25a80dd731..0000000000000 --- a/paddle/fluid/operators/viterbi_decode_op.cc +++ /dev/null @@ -1,72 +0,0 @@ -/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at -http://www.apache.org/licenses/LICENSE-2.0 -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -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/ternary.h" - -namespace paddle { -namespace operators { - -class ViterbiDecodeOp : public framework::OperatorWithKernel { - public: - using framework::OperatorWithKernel::OperatorWithKernel; - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext& ctx) const override { - return framework::OpKernelType( - OperatorWithKernel::IndicateVarDataType(ctx, "Input"), - ctx.device_context()); - } -}; - -class ViterbiDecodeOpMaker : public framework::OpProtoAndCheckerMaker { - public: - void Make() override { - AddInput( - "Input", - "The unary emission tensor. The shape of Input must be (batch_size," - "sequence_length, num_tags). "); - AddInput("Transition", - "The transition matrix. The shape of Transition must be ( " - "num_tags, num_tags). "); - AddInput("Length", - "The input length tensor storing real length of each sequence for " - "correctness. The shape of Length MUST be (batch_size)."); - AddOutput("Scores", - "The scores tensor containing the score for the Viterbi " - "sequence. The shape of Scores MUST be (batch_size)."); - AddOutput("Path", - "The paths tensor containing the highest scoring tag indices. " - "The shape of Scores MUST be (batch_size, sequence_length)."); - AddAttr("include_bos_eos_tag", - "If set to True, the last row and the last column of " - "transitions will be considered as start tag.") - .SetDefault(true); - AddComment(R"DOC( - )DOC"); - } -}; - -} // namespace operators -} // namespace paddle - -namespace ops = paddle::operators; -namespace platform = paddle::platform; -DECLARE_INFER_SHAPE_FUNCTOR(viterbi_decode, - ViterbiDecodeInferShapeFunctor, - PD_INFER_META(phi::ViterbiDecodeInferMeta)); -REGISTER_OP_WITHOUT_GRADIENT(viterbi_decode, - ops::ViterbiDecodeOp, - ops::ViterbiDecodeOpMaker, - ViterbiDecodeInferShapeFunctor); diff --git a/paddle/fluid/operators/where_op.cc b/paddle/fluid/operators/where_op.cc deleted file mode 100644 index 420ef74b83080..0000000000000 --- a/paddle/fluid/operators/where_op.cc +++ /dev/null @@ -1,134 +0,0 @@ -// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// 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 { - -class WhereOp : public framework::OperatorWithKernel { - public: - using framework::OperatorWithKernel::OperatorWithKernel; - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext& ctx) const override { - return framework::OpKernelType( - OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace()); - } -}; - -class WhereGradOp : public framework::OperatorWithKernel { - public: - using framework::OperatorWithKernel::OperatorWithKernel; - - void InferShape(framework::InferShapeContext* ctx) const override { - OP_INOUT_CHECK(ctx->HasInput("Condition"), "Input", "Condition", "Where"); - OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Where"); - OP_INOUT_CHECK(ctx->HasInput("Y"), "Input", "Y", "Where"); - OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), - "Input", - framework::GradVarName("Out"), - "Where"); - - auto x_dims = ctx->GetInputDim("X"); - auto y_dims = ctx->GetInputDim("Y"); - - auto x_grad_name = framework::GradVarName("X"); - auto y_grad_name = framework::GradVarName("Y"); - - if (ctx->HasOutput(x_grad_name)) { - ctx->SetOutputDim(x_grad_name, x_dims); - } - if (ctx->HasOutput(y_grad_name)) { - ctx->SetOutputDim(y_grad_name, y_dims); - } - } - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext& ctx) const override { - return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType( - ctx, framework::GradVarName("Out")), - ctx.GetPlace()); - } -}; - -class WhereOpMaker : public framework::OpProtoAndCheckerMaker { - public: - void Make() override { - AddInput("Condition", - "(Tensor) A bool tensor whose rank is at least 1. When Condition " - "is True, yield x, otherwise yield y"); - AddInput("X", - "(Tensor), The first input tensor of where op. When the " - "corresponding position of the condition is true, the output " - "takes the element of X."); - AddInput("Y", - "(Tensor), The second input tensor of where op. When the " - "corresponding position of condition is false, the output takes " - "the element of Y."); - AddOutput("Out", "(Tensor), The output tensor of where op."); - AddComment(R"DOC( - Where Operator. - Return a tensor of elements selected from either $X$ or $Y$, depending on condition. - The equation is: - $$ - Out_i = - \begin{cases} - \X_i, \quad \text{if} \ cond_i is True \\ - \Y_i, \quad \text{if} \ cond_i is False \\ - \end{cases} - $$ -)DOC"); - } -}; - -template -class WhereOpGradMaker : public framework::SingleGradOpMaker { - public: - using framework::SingleGradOpMaker::SingleGradOpMaker; - - protected: - void Apply(GradOpPtr grad) const override { - grad->SetType("where_grad"); - grad->SetInput("Condition", this->Input("Condition")); - grad->SetInput("X", this->Input("X")); - grad->SetInput("Y", this->Input("Y")); - grad->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); - grad->SetOutput(framework::GradVarName("X"), this->InputGrad("X")); - grad->SetOutput(framework::GradVarName("Y"), this->InputGrad("Y")); - } -}; - -DECLARE_NO_NEED_BUFFER_VARS_INFERER(WhereGradNoNeedBufferVarsInferer, "X", "Y"); -} // namespace operators -} // namespace paddle - -namespace ops = paddle::operators; -DECLARE_INFER_SHAPE_FUNCTOR(where, - WhereInferShapeFunctor, - PD_INFER_META(phi::WhereInferMeta)); -REGISTER_OPERATOR(where, - ops::WhereOp, - ops::WhereOpMaker, - ops::WhereOpGradMaker, - ops::WhereOpGradMaker, - WhereInferShapeFunctor); - -REGISTER_OPERATOR(where_grad, - ops::WhereGradOp, - ops::WhereGradNoNeedBufferVarsInferer); diff --git a/paddle/phi/api/yaml/backward.yaml b/paddle/phi/api/yaml/backward.yaml index 4cd0c5ab341c7..ef674f43cae6f 100644 --- a/paddle/phi/api/yaml/backward.yaml +++ b/paddle/phi/api/yaml/backward.yaml @@ -887,6 +887,39 @@ backward : rsqrt_double_grad inplace : (out_grad -> x_grad) +- backward_op : scatter_grad + forward : scatter (Tensor x, Tensor index, Tensor updates, bool overwrite=true) -> Tensor(out) + args : (Tensor index, Tensor updates, Tensor out_grad, bool overwrite) + output : Tensor(x_grad), Tensor(updates_grad) + infer_meta : + func : ScatterGradInferMeta + param : [index, updates, out_grad, overwrite] + kernel : + func : scatter_grad + no_need_buffer : updates + +- backward_op : scatter_nd_add_grad + forward : scatter_nd_add (Tensor x, Tensor index, Tensor updates) -> Tensor(out) + args : (Tensor index, Tensor updates, Tensor out_grad) + output : Tensor(x_grad), Tensor(updates_grad) + infer_meta : + func : ScatterNdAddGradInferMeta + param : [index, updates, out_grad] + kernel : + func : scatter_nd_add_grad + no_need_buffer : updates + +- backward_op : selu_grad + forward : selu (Tensor x, float scale=1.0507009873554804934193349852946, float alpha=1.6732632423543772848170429916717) -> Tensor(out) + args : (Tensor out, Tensor out_grad, float scale, float alpha) + output : Tensor(x_grad) + infer_meta : + func : UnchangedInferMeta + param : [out] + kernel : + func : selu_grad + data_type : out + - backward_op : send_uv_grad forward : send_uv (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op = "ADD") -> Tensor(out) args: (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, Tensor out_grad, str message_op = "ADD") @@ -1216,3 +1249,14 @@ func : unfold_grad data_type : out_grad no_need_buffer : x + +- backward_op : where_grad + forward : where (Tensor condition, Tensor x, Tensor y) -> Tensor(out) + args : (Tensor condition, Tensor x, Tensor y, Tensor out_grad) + output : Tensor(x_grad), Tensor(y_grad) + infer_meta : + func : GeneralBinaryGradInferMeta + param : [x, y] + kernel : + func : where_grad + no_need_buffer : x, y diff --git a/paddle/phi/api/yaml/legacy_backward.yaml b/paddle/phi/api/yaml/legacy_backward.yaml index 51e49ef831c47..b35f2c270cda8 100755 --- a/paddle/phi/api/yaml/legacy_backward.yaml +++ b/paddle/phi/api/yaml/legacy_backward.yaml @@ -1312,28 +1312,6 @@ output : Tensor(x_grad) invoke : scale(out_grad, scale, 0.0, bias_after_scale) -- backward_op : scatter_grad - forward : scatter (Tensor x, Tensor index, Tensor updates, bool overwrite) -> Tensor(out) - args : (Tensor index, Tensor updates, Tensor out_grad, bool overwrite) - output : Tensor(x_grad), Tensor(updates_grad) - infer_meta : - func : ScatterGradInferMeta - param : [index, updates, out_grad, overwrite] - kernel : - func : scatter_grad - no_need_buffer : updates - -- backward_op : scatter_nd_add_grad - forward : scatter_nd_add (Tensor x, Tensor index, Tensor updates) -> Tensor(out) - args : (Tensor index, Tensor updates, Tensor out_grad) - output : Tensor(x_grad), Tensor(updates_grad) - infer_meta : - func : ScatterNdAddGradInferMeta - param : [index, updates, out_grad] - kernel : - func : scatter_nd_add_grad - no_need_buffer : updates - - backward_op : segment_pool_grad forward : segment_pool (Tensor x, Tensor segment_ids, str pooltype) -> Tensor(out), Tensor(summed_ids) args : (Tensor x, Tensor segment_ids, Tensor out, Tensor summed_ids, Tensor out_grad, str pooltype) @@ -1346,16 +1324,6 @@ data_type : x optional : summed_ids -- backward_op : selu_grad - forward : selu (Tensor x, float scale, float alpha) -> Tensor(out) - args : (Tensor out, Tensor out_grad, float scale, float alpha) - output : Tensor(x_grad) - infer_meta : - func : UnchangedInferMeta - param : [out] - kernel : - func : selu_grad - - backward_op : send_u_recv_grad forward : send_u_recv (Tensor x, Tensor src_index, Tensor dst_index, str reduce_op = "SUM", IntArray out_size = {0}) -> Tensor(out), Tensor(dst_count) args : (Tensor x, Tensor src_index, Tensor dst_index, Tensor out, Tensor dst_count, Tensor out_grad, str reduce_op = "SUM") @@ -1719,17 +1687,6 @@ optional : logits_length no_need_buffer : logits -- backward_op : where_grad - forward : where (Tensor condition, Tensor x, Tensor y) -> Tensor(out) - args : (Tensor condition, Tensor x, Tensor y, Tensor out_grad) - output : Tensor(x_grad), Tensor(y_grad) - infer_meta : - func : GeneralBinaryGradInferMeta - param : [x, y] - kernel : - func : where_grad - no_need_buffer : x, y - - backward_op : yolo_loss_grad forward : yolo_loss(Tensor x, Tensor gt_box, Tensor gt_label, Tensor gt_score, int[] anchors, int[] anchor_mask, int class_num, float ignore_thresh, int downsample_ratio, bool use_label_smooth=true, float scale_x_y=1.0) -> Tensor(loss), Tensor(objectness_mask), Tensor(gt_match_mask) args : (Tensor x, Tensor gt_box, Tensor gt_label, Tensor gt_score, Tensor objectness_mask, Tensor gt_match_mask, Tensor loss_grad, int[] anchors, int[] anchor_mask, int class_num, float ignore_thresh, int downsample_ratio, bool use_label_smooth=true, float scale_x_y=1.0) diff --git a/paddle/phi/api/yaml/legacy_ops.yaml b/paddle/phi/api/yaml/legacy_ops.yaml index 4b697f0182be2..f228a70857edc 100755 --- a/paddle/phi/api/yaml/legacy_ops.yaml +++ b/paddle/phi/api/yaml/legacy_ops.yaml @@ -1708,27 +1708,6 @@ inplace : (x -> out) backward : scale_grad -- op : scatter - args : (Tensor x, Tensor index, Tensor updates, bool overwrite) - output : Tensor(out) - infer_meta : - func : ScatterInferMeta - dtype : x - kernel : - func : scatter - inplace : (x -> out) - backward : scatter_grad - -- op : scatter_nd_add - args : (Tensor x, Tensor index, Tensor updates) - output : Tensor - infer_meta : - func : ScatterNdAddInferMeta - dtype : x - kernel : - func : scatter_nd_add - backward : scatter_nd_add_grad - - op : segment_pool args : (Tensor x, Tensor segment_ids, str pooltype) output : Tensor(out), Tensor(summed_ids) @@ -1739,16 +1718,6 @@ data_type : x backward : segment_pool_grad -- op : selu - args : (Tensor x, float scale, float alpha) - output : Tensor - infer_meta : - func : UnchangedInferMeta - param : [x] - kernel : - func : selu - backward : selu_grad - - op : send_u_recv args : (Tensor x, Tensor src_index, Tensor dst_index, str reduce_op = "SUM", IntArray out_size = {0}) output : Tensor(out), Tensor(dst_count) @@ -1797,14 +1766,6 @@ data_transform: skip_transform : input -- op : shard_index - args : (Tensor input, int index_num, int nshards, int shard_id, int ignore_value) - output : Tensor(out) - infer_meta : - func : ShardIndexInferMeta - kernel : - func : shard_index - - op : sigmoid_cross_entropy_with_logits args : (Tensor x, Tensor label, bool normalize, int ignore_index) output : Tensor @@ -1993,6 +1954,7 @@ func : TriangularSolveInferMeta kernel : func : triangular_solve + data_type : x backward : triangular_solve_grad - op : tril @@ -2164,15 +2126,6 @@ data_type : x inplace : (x -> out), (prev_loss_scaling -> loss_scaling), (in_good_steps -> out_good_steps), (in_bad_steps -> out_bad_steps) -- op : viterbi_decode - args : (Tensor potentials, Tensor transition_params, Tensor lengths, bool include_bos_eos_tag) - output : Tensor(scores), Tensor(path) - infer_meta : - func : ViterbiDecodeInferMeta - kernel : - func : viterbi_decode - data_type : potentials - - op : warpctc args : (Tensor logits, Tensor label, Tensor logits_length, Tensor labels_length, int blank, bool norm_by_times) output : Tensor(loss), Tensor(warpctcgrad) @@ -2185,15 +2138,6 @@ intermediate: warpctcgrad backward : warpctc_grad -- op : where - args : (Tensor condition, Tensor x, Tensor y) - output : Tensor - infer_meta : - func : WhereInferMeta - kernel : - func : where - backward : where_grad - - op : yolo_box args : (Tensor x, Tensor img_size, int[] anchors, int class_num, float conf_thresh, int downsample_ratio, bool clip_bbox, float scale_x_y=1.0, bool iou_aware=false, float iou_aware_factor=0.5) output : Tensor(boxes), Tensor(scores) diff --git a/paddle/phi/api/yaml/op_compat.yaml b/paddle/phi/api/yaml/op_compat.yaml index 63c6c5c38f54f..5033a1932862a 100644 --- a/paddle/phi/api/yaml/op_compat.yaml +++ b/paddle/phi/api/yaml/op_compat.yaml @@ -1045,6 +1045,20 @@ extra : attrs : [bool use_mkldnn = false] +- op : scatter + backward : scatter_grad + inputs : + {x : X, index : Ids, updates : Updates} + outputs : + out : Out + +- op : scatter_nd_add + backward : scatter_nd_add_grad + inputs : + {x : X, index : Index, updates : Updates} + outputs : + out : Out + - op : searchsorted inputs : {sorted_sequence : SortedSequence, values : Values} @@ -1055,6 +1069,13 @@ extra : attrs : [bool deterministic = false, str rng_name = "", bool force_cpu = false] +- op : selu + backward : selu_grad + inputs : + x : X + outputs : + out : Out + - op : send_uv (graph_send_uv) backward : send_uv_grad (graph_send_uv_grad) @@ -1067,6 +1088,12 @@ extra : attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"] +- op : shard_index + inputs : + input : X + outputs : + out : Out + - op : share_buffer inputs : x : X @@ -1297,6 +1324,19 @@ outputs : out : Y +- op : viterbi_decode + inputs : + {potentials : Input, transition_params : Transition, lengths : Length} + outputs : + {scores : Scores, path : Path} + +- op : where + backward : where_grad + inputs : + {condition : Condition, x : X, y : Y} + outputs : + out : Out + - op : while backward : while_grad extra : diff --git a/paddle/phi/api/yaml/ops.yaml b/paddle/phi/api/yaml/ops.yaml index 32fe25624fe7b..967ce5ad60112 100644 --- a/paddle/phi/api/yaml/ops.yaml +++ b/paddle/phi/api/yaml/ops.yaml @@ -821,6 +821,27 @@ inplace : (x -> out) backward : rsqrt_grad +- op : scatter + args : (Tensor x, Tensor index, Tensor updates, bool overwrite=true) + output : Tensor(out) + infer_meta : + func : ScatterInferMeta + kernel : + func : scatter + data_type : x + inplace : (x -> out) + backward : scatter_grad + +- op : scatter_nd_add + args : (Tensor x, Tensor index, Tensor updates) + output : Tensor + infer_meta : + func : ScatterNdAddInferMeta + kernel : + func : scatter_nd_add + data_type : x + backward : scatter_nd_add_grad + - op : searchsorted args : (Tensor sorted_sequence, Tensor values, bool out_int32 = false, bool right = false) output : Tensor(out) @@ -830,6 +851,16 @@ func : searchsorted data_type : sorted_sequence +- op : selu + args : (Tensor x, float scale=1.0507009873554804934193349852946, float alpha=1.6732632423543772848170429916717) + output : Tensor + infer_meta : + func : UnchangedInferMeta + param : [x] + kernel : + func : selu + backward : selu_grad + - op : send_uv args : (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op = "ADD") output : Tensor(out) @@ -840,6 +871,14 @@ data_type : x backward : send_uv_grad +- op : shard_index + args : (Tensor input, int index_num, int nshards, int shard_id, int ignore_value=-1) + output : Tensor(out) + infer_meta : + func : ShardIndexInferMeta + kernel : + func : shard_index + - op : sigmoid args : (Tensor x) output : Tensor @@ -1031,3 +1070,21 @@ kernel : func : unfold backward : unfold_grad + +- op : viterbi_decode + args : (Tensor potentials, Tensor transition_params, Tensor lengths, bool include_bos_eos_tag = true) + output : Tensor(scores), Tensor(path) + infer_meta : + func : ViterbiDecodeInferMeta + kernel : + func : viterbi_decode + data_type : potentials + +- op : where + args : (Tensor condition, Tensor x, Tensor y) + output : Tensor + infer_meta : + func : WhereInferMeta + kernel : + func : where + backward : where_grad diff --git a/paddle/phi/ops/compat/gather_scatter_sig.cc b/paddle/phi/ops/compat/gather_scatter_sig.cc index a942ebb44086f..e37ba0ff401eb 100644 --- a/paddle/phi/ops/compat/gather_scatter_sig.cc +++ b/paddle/phi/ops/compat/gather_scatter_sig.cc @@ -21,24 +21,6 @@ KernelSignature GatherNdGradArgumentMapping(const ArgumentMappingContext& ctx) { "gather_nd_grad", {"X", "Index", "Out@GRAD"}, {}, {"X@GRAD"}); } -KernelSignature ScatterGradArgumentMapping(const ArgumentMappingContext& ctx) { - return KernelSignature("scatter_grad", - {"Ids", "Updates", "Out@GRAD"}, - {"overwrite"}, - {"X@GRAD", "Updates@GRAD"}); -} - -KernelSignature ScatterNdAddGradArgumentMapping( - const ArgumentMappingContext& ctx) { - return KernelSignature("scatter_nd_add_grad", - {"Index", "Updates", "Out@GRAD"}, - {}, - {"X@GRAD", "Updates@GRAD"}); -} - } // namespace phi PD_REGISTER_ARG_MAPPING_FN(gather_nd_grad, phi::GatherNdGradArgumentMapping); -PD_REGISTER_ARG_MAPPING_FN(scatter_grad, phi::ScatterGradArgumentMapping); -PD_REGISTER_ARG_MAPPING_FN(scatter_nd_add_grad, - phi::ScatterNdAddGradArgumentMapping); diff --git a/paddle/phi/ops/compat/selu_sig.cc b/paddle/phi/ops/compat/selu_sig.cc deleted file mode 100644 index 08087584a1094..0000000000000 --- a/paddle/phi/ops/compat/selu_sig.cc +++ /dev/null @@ -1,26 +0,0 @@ - -// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// 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/phi/core/compat/op_utils.h" - -namespace phi { - -KernelSignature SeluGradGradOpArgumentMapping( - const ArgumentMappingContext& ctx) { - return KernelSignature( - "selu_grad", {"Out", "Out@GRAD"}, {"scale", "alpha"}, {"X@GRAD"}); -} -} // namespace phi -PD_REGISTER_ARG_MAPPING_FN(selu_grad, phi::SeluGradGradOpArgumentMapping); diff --git a/paddle/phi/ops/compat/where_grad_sig.cc b/paddle/phi/ops/compat/where_grad_sig.cc deleted file mode 100644 index e0c380672c895..0000000000000 --- a/paddle/phi/ops/compat/where_grad_sig.cc +++ /dev/null @@ -1,28 +0,0 @@ -// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// 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/phi/core/compat/op_utils.h" - -namespace phi { - -KernelSignature WhereGradOpArgumentMapping(const ArgumentMappingContext& ctx) { - return KernelSignature("where_grad", - {"Condition", "X", "Y", "Out@GRAD"}, - {}, - {"X@GRAD", "Y@GRAD"}); -} - -} // namespace phi - -PD_REGISTER_ARG_MAPPING_FN(where_grad, phi::WhereGradOpArgumentMapping);