// 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 "paddle/fluid/framework/framework.pb.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/reader.h" #include "paddle/fluid/platform/profiler.h" namespace paddle { namespace operators { // Returns true if the two dimensions are compatible. // A dimension is compatible with the other if: // 1. The length of the dimensions are same. // 2. Each non-negative number of the two dimensions are same. // 3. For negative number in a dimension, it means unknown so it is compatible // with any number. bool DimensionIsCompatibleWith(const framework::DDim& first, const framework::DDim& second) { int dim_size = first.size(); if (dim_size != second.size()) { return false; } for (int i = 0; i < dim_size; ++i) { if (first[i] >= 0 && second[i] >= 0 && first[i] != second[i]) { return false; } } return true; } class ReadInferShape : public framework::InferShapeBase { public: void operator()(framework::InferShapeContext* ctx) const override { OP_INOUT_CHECK(ctx->HasInput("Reader"), "Input", "Reader", "read"); OP_INOUT_CHECK(ctx->HasOutputs("Out"), "Output", "Out", "read"); if (!ctx->IsRuntime() && ctx->Attrs().Get("infer_out")) { std::vector reader_dims = ctx->GetReaderDims("Reader"); std::vector out_names = ctx->Outputs("Out"); PADDLE_ENFORCE_EQ( reader_dims.size(), out_names.size(), platform::errors::InvalidArgument( "The reader's dim number doesn't match the output number.")); ctx->SetOutputsDim("Out", reader_dims); auto in_desc = BOOST_GET(framework::VarDesc*, ctx->GetInputVarPtrs("Reader")[0]); auto in_lod_levels = in_desc->GetLoDLevels(); auto out_var_ptrs = ctx->GetOutputVarPtrs("Out"); PADDLE_ENFORCE_EQ( in_lod_levels.size(), out_var_ptrs.size(), platform::errors::InvalidArgument( "LoDLevels of Input(Reader) must be the same as the " "number of Outputs(Out).")); for (size_t i = 0; i < out_var_ptrs.size(); ++i) { auto* out_desc = BOOST_GET(framework::VarDesc*, out_var_ptrs[i]); out_desc->SetLoDLevel(in_lod_levels[i]); } } } }; class ReadInferVarType : public framework::StaticGraphVarTypeInference { public: void operator()(framework::InferVarTypeContext* ctx) const override { bool infer_out = BOOST_GET_CONST(bool, ctx->GetAttr("infer_out")); if (infer_out) { std::string reader_name = Input(ctx, "Reader")[0]; auto& out_names = Output(ctx, "Out"); auto dtypes = GetDataTypes(ctx, reader_name); PADDLE_ENFORCE_EQ(dtypes.size(), out_names.size(), platform::errors::InvalidArgument( "The number of input reader's dtypes do not match " "the output variable number.")); for (size_t i = 0; i < dtypes.size(); ++i) { SetType(ctx, out_names[i], framework::proto::VarType::LOD_TENSOR); SetDataType(ctx, out_names[i], dtypes[i]); } } } }; class ReadOp : public framework::OperatorBase { public: using framework::OperatorBase::OperatorBase; private: void RunImpl(const framework::Scope& scope, const platform::Place& dev_place) const override { VLOG(3) << "read op in"; framework::ReaderHolder* reader = GET_DATA_SAFELY(scope.FindVar(Input("Reader")), "Input", "Reader", "Read") .GetMutable(); std::vector out_arg_names = Outputs("Out"); std::vector ins; // For profiling platform::RecordEvent record_event(Type()); reader->ReadNext(&ins); if (ins.empty()) { VLOG(3) << "throw_eof_exp"; PADDLE_THROW_EOF(); } PADDLE_ENFORCE_EQ( ins.size(), out_arg_names.size(), platform::errors::InvalidArgument("input data number and output data " "number of read_op do not match")); const std::vector& shapes = reader->Shapes(); const std::vector& var_types = reader->VarTypes(); const std::vector& need_check_feed = reader->NeedCheckFeed(); PADDLE_ENFORCE_EQ( out_arg_names.size(), need_check_feed.size(), platform::errors::InvalidArgument( "Output size of read_op and the number of fed " "variables of reader do not match. Received size of output is %d, " "number of fed variables of reader is %d", out_arg_names.size(), need_check_feed.size())); for (size_t i = 0; i < out_arg_names.size(); ++i) { auto* out = scope.FindVar(out_arg_names[i])->GetMutable(); if (need_check_feed[i]) { auto in_dims = ins[i].dims(); PADDLE_ENFORCE_EQ( DimensionIsCompatibleWith(shapes[i], in_dims), true, platform::errors::InvalidArgument( "The fed Variable %s should have dimensions = %d, " "shape = [%s], but received fed shape [%s]", out_arg_names[i], shapes[i].size(), shapes[i], in_dims)); PADDLE_ENFORCE_EQ( ins[i].type(), var_types[i], platform::errors::InvalidArgument( "The data type of fed Variable %s must be %s, but received %s", out_arg_names[i], var_types[i], ins[i].type())); } out->ShareDataWith(ins[i]); out->set_lod(ins[i].lod()); } } }; class ReadOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("Reader", "(ReaderHolder) The executed reader."); AddOutput("Out", "(LoDTensor) The output data.").AsDuplicable(); AddAttr( "throw_eof_exp", "If set true, an exception will be thrown when the Reader " "yields empty (which means there is no next data).\n" "NOTES: This flag must be true always. It will be set to false" " only when the data-balance is enabled in ParallelExecutor" " and it is set by ParallelExecutor instance, not users.") .SetDefault(true); AddAttr("infer_out", "").SetDefault(true); AddAttr("drop_last", "Whether to drop last batches whose number is less than " "actual used device number.") .SetDefault(true); AddComment(R"DOC( Read Operator Execute a given reader once and output data. )DOC"); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OPERATOR( read, ops::ReadOp, ops::ReadInferShape, ops::ReadOpMaker, paddle::framework::EmptyGradOpMaker, paddle::framework::EmptyGradOpMaker, ops::ReadInferVarType);