wehub-resource-sync
74 lines
2.7 KiB
C++
74 lines
2.7 KiB
C++
/* Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/operators/controlflow/conditional_block_op.h"
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#include "gtest/gtest.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/scope.h"
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using DenseTensorArray = phi::TensorArray;
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using Scope = paddle::framework::Scope;
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using Variable = paddle::framework::Variable;
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using Place = phi::Place;
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TEST(ConditionalBlockGrad, NoNeedRunDenseTensorArray) {
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Place place = phi::CPUPlace();
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Scope scope;
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Variable* cond_var = scope.Var("condition");
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phi::DenseTensor* cond_tensor = cond_var->GetMutable<phi::DenseTensor>();
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phi::DDim cond_dims = common::make_ddim({1});
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bool* cond_data = cond_tensor->mutable_data<bool>(cond_dims, place);
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cond_data[0] = false;
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Variable* input_var = scope.Var("input_lod_tensor_array");
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DenseTensorArray* input_tensors = input_var->GetMutable<phi::TensorArray>();
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for (int i = 0; i < 5; ++i) {
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phi::DDim in_dims = common::make_ddim({i + 1, i + 2});
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phi::DenseTensor lod_tensor;
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float* in_data = lod_tensor.mutable_data<float>(in_dims, place);
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for (int j = 0; j < (i + 1) * (i + 2); ++j) {
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in_data[j] = static_cast<float>(j);
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}
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input_tensors->push_back(lod_tensor);
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}
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Variable* input_grad_var = scope.Var("input_lod_tensor_array@GRAD");
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DenseTensorArray* grad_tensors =
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input_grad_var->GetMutable<phi::TensorArray>();
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grad_tensors->resize(5);
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paddle::framework::AttributeMap attrs;
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attrs.insert({"is_scalar_condition", true});
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auto conditional_grad_op = paddle::framework::OpRegistry::CreateOp(
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"conditional_block_grad",
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{{"Input", {"input_lod_tensor_array"}}, {"Cond", {"condition"}}},
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{{"Input@GRAD", {"input_lod_tensor_array@GRAD"}}},
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attrs);
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conditional_grad_op->Run(scope, place);
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const DenseTensorArray& out_tensors = input_grad_var->Get<phi::TensorArray>();
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for (int i = 0; i < 5; ++i) {
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phi::DDim out_dims = out_tensors[i].dims();
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EXPECT_EQ(common::make_ddim({i + 1, i + 2}), out_dims);
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const float* out_data = out_tensors[i].data<float>();
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for (int j = 0; j < (i + 1) * (i + 2); ++j) {
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EXPECT_EQ(0, out_data[j]);
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}
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}
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}
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