// 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 #include #include #include #include #include #include "paddle/fluid/framework/block_desc.h" #include "paddle/fluid/framework/op_desc.h" #include "paddle/fluid/framework/op_proto_maker.h" #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/framework/program_desc.h" #include "paddle/fluid/framework/convert_utils.h" #include "paddle/fluid/prim/api/manual_prim/prim_manual_api.h" #include "paddle/fluid/prim/api/manual_prim/utils/utils.h" #include "paddle/fluid/prim/utils/static/composite_grad_desc_maker.h" #include "paddle/fluid/prim/utils/static/desc_tensor.h" #include "paddle/phi/api/include/tensor.h" #include "paddle/phi/common/data_type.h" #include "paddle/phi/common/float16.h" #include "paddle/phi/core/enforce.h" namespace paddle { namespace prim { template <> Tensor reshape(const Tensor& x, const IntArray& shape) { framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock(); framework::OpDesc* op = block->AppendOp(); // TODO(cxxly): Fix test_resnet_prim_cinn error when SetType("reshape2") op->SetType("reshape"); op->SetInput("X", {std::static_pointer_cast(x.impl())->Name()}); // Tensor out = empty({}, x.dtype(), paddle::Place()); auto out = empty({}, x.dtype(), paddle::Place()); op->SetOutput( "Out", {std::static_pointer_cast(out.impl())->Name()}); op->SetAttr("shape", unsafe_vector_cast(shape.GetData())); op->CheckAttrs(); op->InferVarType(block); op->InferShape(*block); return out; } template <> Tensor full(const IntArray& shape, const Scalar& value, DataType dtype, const Place& place) { // Grad infershape Tensor out = empty({}, dtype, place); framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock(); framework::OpDesc* op = block->AppendOp(); op->SetType("fill_constant"); op->SetAttr("shape", shape.GetData()); switch (dtype) { case phi::DataType::FLOAT16: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::BFLOAT16: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::FLOAT32: op->SetAttr("value", value.to()); break; case phi::DataType::FLOAT64: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::BOOL: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::INT8: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::UINT8: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::INT16: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::UINT16: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::INT32: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::UINT32: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::INT64: op->SetAttr("str_value", std::to_string(value.to())); break; case phi::DataType::UINT64: op->SetAttr("str_value", std::to_string(value.to())); break; default: PADDLE_THROW(phi::errors::Unimplemented( "We support " "bool/float16/bfloat16/float32/float64/int8/int16/int32/int64/uint8/" "uint16/" "uint32/uint64 for full, but we got data type: %s", phi::DataTypeToString(dtype))); } op->SetAttr("dtype", paddle::framework::TransToProtoVarType(dtype)); op->SetOutput( "Out", {std::static_pointer_cast(out.impl())->Name()}); op->CheckAttrs(); op->InferVarType(block); op->InferShape(*block); return out; } template <> std::vector split(const Tensor& x, const IntArray& sections, const Scalar& axis) { int elem_num = sections.size(); std::vector outs_name; std::vector outs; for (int i = 0; i < elem_num; ++i) { Tensor out = empty({}, x.dtype(), paddle::Place()); std::string out_name = std::static_pointer_cast(out.impl())->Name(); outs_name.push_back(std::move(out_name)); outs.push_back(out); } framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock(); framework::OpDesc* op = block->AppendOp(); op->SetType("split"); op->SetAttr("sections", sections.GetData()); op->SetAttr("axis", axis.to()); op->SetOutput("Out", outs_name); op->CheckAttrs(); op->InferVarType(block); op->InferShape(*block); return outs; } template <> Tensor cast(const Tensor& x, DataType dtype) { Tensor out = empty({}, DataType::FLOAT32, paddle::Place()); framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock(); framework::OpDesc* op = block->AppendOp(); op->SetType("cast"); op->SetInput("X", {std::static_pointer_cast(x.impl())->Name()}); op->SetOutput( "Out", {std::static_pointer_cast(out.impl())->Name()}); op->SetAttr("in_dtype", static_cast(x.dtype())); op->SetAttr("out_dtype", static_cast(dtype)); op->CheckAttrs(); op->InferVarType(block); op->InferShape(*block); return out; } } // namespace prim } // namespace paddle