wehub-resource-sync
261 lines
9.0 KiB
C++
261 lines
9.0 KiB
C++
// 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.
|
|
|
|
//
|
|
// Created by Jiabin on 2019-08-19.
|
|
//
|
|
|
|
#include <paddle/fluid/framework/op_registry.h>
|
|
|
|
#include <memory>
|
|
#include <string>
|
|
#include <vector>
|
|
|
|
#include "gtest/gtest.h"
|
|
#include "paddle/fluid/framework/op_info.h"
|
|
#include "paddle/fluid/imperative/prepared_operator.h"
|
|
#include "paddle/fluid/imperative/type_defs.h"
|
|
#include "paddle/phi/core/kernel_registry.h"
|
|
|
|
PD_DECLARE_KERNEL(split, CPU, ALL_LAYOUT);
|
|
PD_DECLARE_KERNEL(relu, CPU, ALL_LAYOUT);
|
|
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
|
|
PD_DECLARE_KERNEL(relu, GPU, ALL_LAYOUT);
|
|
#endif
|
|
|
|
namespace paddle {
|
|
namespace imperative {
|
|
|
|
extern void TestHandleComplexGradToRealGradEager(
|
|
const NameVarMap<egr::EagerVariable>& outs);
|
|
|
|
static framework::VariableNameMap CreateVarNameMap(
|
|
const framework::OpInfo& op_info,
|
|
const std::string& op_type,
|
|
const NameVarBaseMap& varbase_map,
|
|
bool is_input) {
|
|
if (op_info.proto_ == nullptr) {
|
|
return {};
|
|
}
|
|
|
|
framework::VariableNameMap result;
|
|
|
|
for (auto& var :
|
|
is_input ? op_info.Proto().inputs() : op_info.Proto().outputs()) {
|
|
auto it = varbase_map.find(var.name());
|
|
if (it == varbase_map.end()) {
|
|
PADDLE_ENFORCE_EQ(
|
|
var.dispensable(),
|
|
true,
|
|
common::errors::NotFound("Variable %s is not dispensable and "
|
|
"there are no such var in inputs",
|
|
var.name()));
|
|
result[var.name()] = {};
|
|
} else {
|
|
auto& var_vector = it->second;
|
|
std::vector<std::string> args;
|
|
args.reserve(var_vector.size());
|
|
for (auto& var_base : var_vector) {
|
|
args.emplace_back(var_base->Name());
|
|
}
|
|
result[var.name()] = std::move(args);
|
|
}
|
|
}
|
|
return result;
|
|
}
|
|
|
|
using vb_vector = std::vector<std::shared_ptr<imperative::VarBase>>;
|
|
|
|
using var_pair = std::pair<std::string, vb_vector>;
|
|
|
|
TEST(test_prepare_op, test_prepare_op) {
|
|
std::shared_ptr<imperative::VarBase> vin(
|
|
new imperative::VarBase(false, "vin"));
|
|
std::shared_ptr<imperative::VarBase> vout(
|
|
new imperative::VarBase(false, "vout"));
|
|
framework::OpDesc desc;
|
|
phi::CPUPlace place;
|
|
vin->MutableVar()->GetMutable<phi::DenseTensor>()->mutable_data<float>(place);
|
|
var_pair x_pair = var_pair("X", vb_vector(1, vin));
|
|
var_pair out_pair = var_pair("Out", vb_vector(1, vout));
|
|
imperative::NameVarBaseMap ins = {x_pair};
|
|
imperative::NameVarBaseMap outs = {out_pair};
|
|
framework::AttributeMap split_attr_map;
|
|
const auto& info = framework::OpInfoMap::Instance().Get("split");
|
|
if (info.Checker()) info.Checker()->Check(&split_attr_map);
|
|
framework::VariableNameMap var_in_map =
|
|
CreateVarNameMap(info, "split", ins, true);
|
|
framework::VariableNameMap var_out_map =
|
|
CreateVarNameMap(info, "split", outs, false);
|
|
auto op = framework::OpRegistry::CreateOp(
|
|
"split", var_in_map, var_out_map, split_attr_map);
|
|
ASSERT_NO_FATAL_FAILURE(PreparedOp preparedOp = PreparedOp::Prepare(
|
|
ins,
|
|
outs,
|
|
dynamic_cast<framework::OperatorWithKernel&>(*op),
|
|
place,
|
|
split_attr_map,
|
|
{}));
|
|
}
|
|
|
|
const phi::DenseTensor* GetTensorFromVar(const framework::Variable& var);
|
|
|
|
TEST(test_prepare_op, test_get_tensor_from_var) {
|
|
std::shared_ptr<imperative::VarBase> vout_error(
|
|
new imperative::VarBase(false, "vout_error"));
|
|
vout_error->MutableVar()->GetMutable<phi::SelectedRows>();
|
|
auto* ts = GetTensorFromVar(*vout_error->MutableVar());
|
|
ASSERT_TRUE(ts != nullptr);
|
|
}
|
|
|
|
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
|
|
TEST(test_prepare_op, test_prepare_data) {
|
|
std::shared_ptr<imperative::VarBase> vin(
|
|
new imperative::VarBase(false, "vin"));
|
|
std::shared_ptr<imperative::VarBase> vout(
|
|
new imperative::VarBase(false, "vout"));
|
|
|
|
framework::OpDesc desc;
|
|
phi::CPUPlace cpu_place;
|
|
phi::GPUPlace gpu_place(0);
|
|
std::vector<float> src_data(10, 2.0);
|
|
std::vector<int64_t> dims = {2, 5};
|
|
|
|
// prepare an cpu only input
|
|
auto* vin_tensor = vin->MutableVar()->GetMutable<phi::DenseTensor>();
|
|
vin_tensor->Resize(common::make_ddim(dims));
|
|
auto* vin_mutable_tensor = vin_tensor->mutable_data<float>(cpu_place);
|
|
paddle::memory::Copy(cpu_place,
|
|
vin_mutable_tensor,
|
|
cpu_place,
|
|
src_data.data(),
|
|
sizeof(float) * src_data.size());
|
|
|
|
var_pair x_pair = var_pair("X", vb_vector(1, vin));
|
|
var_pair out_pair = var_pair("Out", vb_vector(1, vout));
|
|
imperative::NameVarBaseMap ins = {x_pair};
|
|
imperative::NameVarBaseMap outs = {out_pair};
|
|
const std::string op_type = "relu";
|
|
framework::AttributeMap attr_map;
|
|
const auto& info = framework::OpInfoMap::Instance().Get(op_type);
|
|
if (info.Checker()) info.Checker()->Check(&attr_map);
|
|
framework::VariableNameMap var_in_map =
|
|
CreateVarNameMap(info, op_type, ins, true);
|
|
framework::VariableNameMap var_out_map =
|
|
CreateVarNameMap(info, op_type, outs, false);
|
|
auto op = framework::OpRegistry::CreateOp(
|
|
op_type, var_in_map, var_out_map, attr_map);
|
|
|
|
// test if it can be transformed to GPU place
|
|
auto prepared_op =
|
|
PreparedOp::Prepare(ins,
|
|
outs,
|
|
dynamic_cast<framework::OperatorWithKernel&>(*op),
|
|
gpu_place,
|
|
attr_map,
|
|
{});
|
|
PrepareData<imperative::VarBase>(
|
|
dynamic_cast<framework::OperatorWithKernel&>(*op),
|
|
ins,
|
|
prepared_op.kernel_key(),
|
|
gpu_place);
|
|
for (const auto& name_pair : ins) {
|
|
for (const auto& vb : name_pair.second) {
|
|
ASSERT_TRUE(phi::is_same_place(vb->Var().Get<phi::DenseTensor>().place(),
|
|
gpu_place));
|
|
}
|
|
}
|
|
}
|
|
#endif
|
|
|
|
void TestPrepareDataSamePlace(framework::AttributeMap attr_map) {
|
|
std::shared_ptr<imperative::VarBase> vin(
|
|
new imperative::VarBase(false, "vin"));
|
|
std::shared_ptr<imperative::VarBase> vout(
|
|
new imperative::VarBase(false, "vout"));
|
|
|
|
framework::OpDesc desc;
|
|
phi::CPUPlace cpu_place;
|
|
std::vector<float> src_data(10, 2.0);
|
|
std::vector<int64_t> dims = {2, 5};
|
|
|
|
// prepare an cpu only input
|
|
auto* vin_tensor = vin->MutableVar()->GetMutable<phi::DenseTensor>();
|
|
vin_tensor->Resize(common::make_ddim(dims));
|
|
auto* vin_mutable_tensor = vin_tensor->mutable_data<float>(cpu_place);
|
|
paddle::memory::Copy(cpu_place,
|
|
vin_mutable_tensor,
|
|
cpu_place,
|
|
src_data.data(),
|
|
sizeof(float) * src_data.size());
|
|
|
|
var_pair x_pair = var_pair("X", vb_vector(1, vin));
|
|
var_pair out_pair = var_pair("Out", vb_vector(1, vout));
|
|
imperative::NameVarBaseMap ins = {x_pair};
|
|
imperative::NameVarBaseMap outs = {out_pair};
|
|
const std::string op_type = "relu";
|
|
const auto& info = framework::OpInfoMap::Instance().Get(op_type);
|
|
if (info.Checker()) info.Checker()->Check(&attr_map);
|
|
framework::VariableNameMap var_in_map =
|
|
CreateVarNameMap(info, op_type, ins, true);
|
|
framework::VariableNameMap var_out_map =
|
|
CreateVarNameMap(info, op_type, outs, false);
|
|
|
|
auto op = framework::OpRegistry::CreateOp(
|
|
op_type, var_in_map, var_out_map, attr_map);
|
|
|
|
// test if it never transferred on GPU place
|
|
auto prepared_op =
|
|
PreparedOp::Prepare(ins,
|
|
outs,
|
|
dynamic_cast<framework::OperatorWithKernel&>(*op),
|
|
cpu_place,
|
|
attr_map,
|
|
{});
|
|
PrepareData<imperative::VarBase>(
|
|
dynamic_cast<framework::OperatorWithKernel&>(*op),
|
|
ins,
|
|
prepared_op.kernel_key(),
|
|
cpu_place);
|
|
for (const auto& name_pair : ins) {
|
|
for (const auto& vb : name_pair.second) {
|
|
ASSERT_TRUE(phi::is_same_place(vb->Var().Get<phi::DenseTensor>().place(),
|
|
cpu_place));
|
|
}
|
|
}
|
|
}
|
|
|
|
TEST(test_prepare_op, test_prepare_data_same_place) {
|
|
TestPrepareDataSamePlace({});
|
|
}
|
|
|
|
TEST(test_prepare_op, test_complex_eager) {
|
|
NameVarMap<egr::EagerVariable> outs = {};
|
|
TestHandleComplexGradToRealGradEager(outs);
|
|
}
|
|
|
|
#ifdef PADDLE_WITH_DNNL
|
|
TEST(test_prepare_op, test_prepare_data_cpu_onednn) {
|
|
TestPrepareDataSamePlace({{"use_onednn", true}});
|
|
}
|
|
#endif
|
|
} // namespace imperative
|
|
} // namespace paddle
|
|
|
|
USE_OP_ITSELF(split);
|
|
USE_OP_ITSELF(relu);
|
|
#ifdef PADDLE_WITH_DNNL
|
|
PD_DECLARE_KERNEL(relu, OneDNN, ONEDNN);
|
|
#endif
|