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[NPU] squeeze and unsqueeze op for ascend (#31452)

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Co-authored-by: root <xiayanming@baidu.com>
revert-31562-mean
Reventon_L 5 years ago committed by GitHub
parent c956c035dc
commit 388c69f27d
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45
paddle/fluid/operators/squeeze_op_npu.cc
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/* 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. */
#ifdef PADDLE_WITH_ASCEND_CL
#include <memory>
#include <string>
#include "paddle/fluid/operators/squeeze_op.h"
#include "paddle/fluid/operators/npu_op_runner.h"
namespace ops = paddle::operators;
namespace plat = paddle::platform;
REGISTER_OP_NPU_KERNEL(
squeeze,
ops::SqueezeKernel<plat::NPUDeviceContext, float>,
ops::SqueezeKernel<plat::NPUDeviceContext, double>,
ops::SqueezeKernel<plat::NPUDeviceContext, plat::float16>,
ops::SqueezeKernel<plat::NPUDeviceContext, bool>,
ops::SqueezeKernel<plat::NPUDeviceContext, int>,
ops::SqueezeKernel<plat::NPUDeviceContext, uint8_t>,
ops::SqueezeKernel<plat::NPUDeviceContext, int8_t>,
ops::SqueezeKernel<plat::NPUDeviceContext, int64_t>);
REGISTER_OP_NPU_KERNEL(
squeeze2,
ops::SqueezeKernel<plat::NPUDeviceContext, float>,
ops::SqueezeKernel<plat::NPUDeviceContext, double>,
ops::SqueezeKernel<plat::NPUDeviceContext, plat::float16>,
ops::SqueezeKernel<plat::NPUDeviceContext, bool>,
ops::SqueezeKernel<plat::NPUDeviceContext, int>,
ops::SqueezeKernel<plat::NPUDeviceContext, uint8_t>,
ops::SqueezeKernel<plat::NPUDeviceContext, int8_t>,
ops::SqueezeKernel<plat::NPUDeviceContext, int64_t>);
#endif

92
paddle/fluid/operators/squeeze_op_npu_test.cc
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/* 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. */
#ifndef _WIN32
#include <unistd.h>
#endif
#include <string>
#include <thread> // NOLINT
#include <vector>
#include "gtest/gtest.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/operators/dropout_op.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/string/printf.h"
namespace f = paddle::framework;
namespace p = paddle::platform;
namespace m = paddle::operators::math;
USE_OP(squeeze);
USE_OP_DEVICE_KERNEL(squeeze, NPU);
template <typename T>
void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
// init
auto x = scope->Var("X");
auto tensor_x = x->GetMutable<f::LoDTensor>();
int dim0 = 1;
int dim1 = 10;
int dim2 = 1;
std::vector<T> init;
for (int64_t i = 0; i < dim0 * dim1 * dim2; ++i) {
init.push_back(static_cast<T>(0.1));
}
TensorFromVector(init, ctx, tensor_x);
tensor_x->Resize({dim0, dim1, dim2});
ctx.Wait();
// run
auto place = ctx.GetPlace();
auto out = scope->Var("Out");
auto tensor_out = out->GetMutable<f::LoDTensor>();
std::vector<int> axis;
axis.push_back(2);
f::AttributeMap attrs = {{"axes", axis}};
auto op =
f::OpRegistry::CreateOp("squeeze", {{"X", {"X"}}},
{{"Out", {"Out"}}}, attrs);
op->Run(*scope, place);
ctx.Wait();
EXPECT_EQ((uint32_t)tensor_out->dims().size(), uint32_t(2));
EXPECT_EQ((uint32_t)tensor_out->dims()[0], uint32_t(dim0));
EXPECT_EQ((uint32_t)tensor_out->dims()[1], uint32_t(dim1));
std::vector<T> out_vec;
TensorToVector(*tensor_out, ctx, &out_vec);
for (uint32_t i = 0; i < out_vec.size(); i++) {
EXPECT_EQ(out_vec[i], static_cast<T>(0.1));
}
ctx.Wait();
}
TEST(squeeze, NPU_fp32) {
f::Scope scope;
p::NPUDeviceContext ctx(p::NPUPlace(0));
Compare<float>(&scope, ctx);
}

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paddle/fluid/operators/unsqueeze_op_npu.cc
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/* 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. */
#ifdef PADDLE_WITH_ASCEND_CL
#include <memory>
#include <string>
#include "paddle/fluid/operators/unsqueeze_op.h"
#include "paddle/fluid/operators/npu_op_runner.h"
namespace ops = paddle::operators;
namespace plat = paddle::platform;
REGISTER_OP_NPU_KERNEL(
unsqueeze,
ops::UnsqueezeKernel<plat::NPUDeviceContext, float>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, double>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, plat::float16>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, bool>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, int>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, int8_t>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, int64_t>);
REGISTER_OP_NPU_KERNEL(
unsqueeze2,
ops::UnsqueezeKernel<plat::NPUDeviceContext, float>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, double>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, plat::float16>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, bool>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, int>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, int8_t>,
ops::UnsqueezeKernel<plat::NPUDeviceContext, int64_t>);
#endif

92
paddle/fluid/operators/unsqueeze_op_npu_test.cc
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/* 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. */
#ifndef _WIN32
#include <unistd.h>
#endif
#include <string>
#include <thread> // NOLINT
#include <vector>
#include "gtest/gtest.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/operators/dropout_op.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/string/printf.h"
namespace f = paddle::framework;
namespace p = paddle::platform;
namespace m = paddle::operators::math;
USE_OP(unsqueeze);
USE_OP_DEVICE_KERNEL(unsqueeze, NPU);
template <typename T>
void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
// init
auto x = scope->Var("X");
auto tensor_x = x->GetMutable<f::LoDTensor>();
int dim0 = 5;
int dim1 = 10;
std::vector<T> init;
for (int64_t i = 0; i < dim0 * dim1; ++i) {
init.push_back(static_cast<T>(0.1));
}
TensorFromVector(init, ctx, tensor_x);
tensor_x->Resize({dim0, dim1});
ctx.Wait();
// run
auto place = ctx.GetPlace();
auto out = scope->Var("Out");
auto tensor_out = out->GetMutable<f::LoDTensor>();
std::vector<int> axis;
axis.push_back(1);
f::AttributeMap attrs = {{"axes", axis}};
auto op =
f::OpRegistry::CreateOp("unsqueeze", {{"X", {"X"}}},
{{"Out", {"Out"}}}, attrs);
op->Run(*scope, place);
ctx.Wait();
EXPECT_EQ((uint32_t)tensor_out->dims().size(), uint32_t(3));
EXPECT_EQ((uint32_t)tensor_out->dims()[0], uint32_t(5));
EXPECT_EQ((uint32_t)tensor_out->dims()[1], uint32_t(1));
EXPECT_EQ((uint32_t)tensor_out->dims()[2], uint32_t(10));
std::vector<T> out_vec;
TensorToVector(*tensor_out, ctx, &out_vec);
for (uint32_t i = 0; i < out_vec.size(); i++) {
EXPECT_EQ(out_vec[i], static_cast<T>(0.1));
}
ctx.Wait();
}
TEST(unsqueeze, NPU_fp32) {
f::Scope scope;
p::NPUDeviceContext ctx(p::NPUPlace(0));
Compare<float>(&scope, ctx);
}
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