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YuxiangLuxymyeah
YuxiangLu
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xymyeah
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[NPU] squeeze and unsqueeze op for ascend (#31452)
Co-authored-by: root <[email protected]>
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‎paddle/fluid/operators/squeeze_op_npu.cc‎

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/* Copyright (c) 2021 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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#ifdef PADDLE_WITH_ASCEND_CL
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#include <memory>
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#include <string>
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#include "paddle/fluid/operators/squeeze_op.h"
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#include "paddle/fluid/operators/npu_op_runner.h"
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namespace ops = paddle::operators;
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namespace plat = paddle::platform;
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REGISTER_OP_NPU_KERNEL(
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squeeze,
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ops::SqueezeKernel<plat::NPUDeviceContext, float>,
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ops::SqueezeKernel<plat::NPUDeviceContext, double>,
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ops::SqueezeKernel<plat::NPUDeviceContext, plat::float16>,
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ops::SqueezeKernel<plat::NPUDeviceContext, bool>,
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ops::SqueezeKernel<plat::NPUDeviceContext, int>,
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ops::SqueezeKernel<plat::NPUDeviceContext, uint8_t>,
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ops::SqueezeKernel<plat::NPUDeviceContext, int8_t>,
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ops::SqueezeKernel<plat::NPUDeviceContext, int64_t>);
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REGISTER_OP_NPU_KERNEL(
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squeeze2,
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ops::SqueezeKernel<plat::NPUDeviceContext, float>,
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ops::SqueezeKernel<plat::NPUDeviceContext, double>,
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ops::SqueezeKernel<plat::NPUDeviceContext, plat::float16>,
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ops::SqueezeKernel<plat::NPUDeviceContext, bool>,
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ops::SqueezeKernel<plat::NPUDeviceContext, int>,
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ops::SqueezeKernel<plat::NPUDeviceContext, uint8_t>,
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ops::SqueezeKernel<plat::NPUDeviceContext, int8_t>,
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ops::SqueezeKernel<plat::NPUDeviceContext, int64_t>);
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#endif

‎paddle/fluid/operators/squeeze_op_npu_test.cc‎

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/* Copyright (c) 2021 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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#ifndef _WIN32
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#include <unistd.h>
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#endif
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#include <string>
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#include <thread> // NOLINT
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#include <vector>
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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/operator.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/operators/dropout_op.h"
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#include "paddle/fluid/operators/math/math_function.h"
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#include "paddle/fluid/string/printf.h"
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namespace f = paddle::framework;
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namespace p = paddle::platform;
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namespace m = paddle::operators::math;
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USE_OP(squeeze);
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USE_OP_DEVICE_KERNEL(squeeze, NPU);
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template <typename T>
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void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
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// init
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auto x = scope->Var("X");
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auto tensor_x = x->GetMutable<f::LoDTensor>();
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int dim0 = 1;
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int dim1 = 10;
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int dim2 = 1;
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std::vector<T> init;
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for (int64_t i = 0; i < dim0 * dim1 * dim2; ++i) {
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init.push_back(static_cast<T>(0.1));
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}
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TensorFromVector(init, ctx, tensor_x);
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tensor_x->Resize({dim0, dim1, dim2});
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ctx.Wait();
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// run
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auto place = ctx.GetPlace();
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auto out = scope->Var("Out");
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auto tensor_out = out->GetMutable<f::LoDTensor>();
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std::vector<int> axis;
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axis.push_back(2);
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f::AttributeMap attrs = {{"axes", axis}};
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auto op =
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f::OpRegistry::CreateOp("squeeze", {{"X", {"X"}}},
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{{"Out", {"Out"}}}, attrs);
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op->Run(*scope, place);
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ctx.Wait();
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EXPECT_EQ((uint32_t)tensor_out->dims().size(), uint32_t(2));
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EXPECT_EQ((uint32_t)tensor_out->dims()[0], uint32_t(dim0));
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EXPECT_EQ((uint32_t)tensor_out->dims()[1], uint32_t(dim1));
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std::vector<T> out_vec;
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TensorToVector(*tensor_out, ctx, &out_vec);
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for (uint32_t i = 0; i < out_vec.size(); i++) {
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EXPECT_EQ(out_vec[i], static_cast<T>(0.1));
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}
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ctx.Wait();
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}
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TEST(squeeze, NPU_fp32) {
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f::Scope scope;
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p::NPUDeviceContext ctx(p::NPUPlace(0));
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Compare<float>(&scope, ctx);
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}
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‎paddle/fluid/operators/unsqueeze_op_npu.cc‎

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/* Copyright (c) 2021 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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#ifdef PADDLE_WITH_ASCEND_CL
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#include <memory>
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#include <string>
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#include "paddle/fluid/operators/unsqueeze_op.h"
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#include "paddle/fluid/operators/npu_op_runner.h"
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namespace ops = paddle::operators;
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namespace plat = paddle::platform;
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REGISTER_OP_NPU_KERNEL(
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unsqueeze,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, float>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, double>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, plat::float16>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, bool>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, int>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, int8_t>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, int64_t>);
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REGISTER_OP_NPU_KERNEL(
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unsqueeze2,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, float>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, double>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, plat::float16>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, bool>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, int>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, int8_t>,
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ops::UnsqueezeKernel<plat::NPUDeviceContext, int64_t>);
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#endif
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‎paddle/fluid/operators/unsqueeze_op_npu_test.cc‎

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/* Copyright (c) 2021 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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#ifndef _WIN32
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#include <unistd.h>
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#endif
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#include <string>
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#include <thread> // NOLINT
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#include <vector>
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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/operator.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/operators/dropout_op.h"
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#include "paddle/fluid/operators/math/math_function.h"
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#include "paddle/fluid/string/printf.h"
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namespace f = paddle::framework;
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namespace p = paddle::platform;
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namespace m = paddle::operators::math;
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USE_OP(unsqueeze);
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USE_OP_DEVICE_KERNEL(unsqueeze, NPU);
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template <typename T>
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void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
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// init
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auto x = scope->Var("X");
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auto tensor_x = x->GetMutable<f::LoDTensor>();
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int dim0 = 5;
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int dim1 = 10;
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std::vector<T> init;
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for (int64_t i = 0; i < dim0 * dim1; ++i) {
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init.push_back(static_cast<T>(0.1));
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}
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TensorFromVector(init, ctx, tensor_x);
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tensor_x->Resize({dim0, dim1});
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ctx.Wait();
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// run
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auto place = ctx.GetPlace();
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auto out = scope->Var("Out");
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auto tensor_out = out->GetMutable<f::LoDTensor>();
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std::vector<int> axis;
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axis.push_back(1);
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f::AttributeMap attrs = {{"axes", axis}};
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auto op =
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f::OpRegistry::CreateOp("unsqueeze", {{"X", {"X"}}},
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{{"Out", {"Out"}}}, attrs);
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op->Run(*scope, place);
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ctx.Wait();
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EXPECT_EQ((uint32_t)tensor_out->dims().size(), uint32_t(3));
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EXPECT_EQ((uint32_t)tensor_out->dims()[0], uint32_t(5));
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EXPECT_EQ((uint32_t)tensor_out->dims()[1], uint32_t(1));
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EXPECT_EQ((uint32_t)tensor_out->dims()[2], uint32_t(10));
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std::vector<T> out_vec;
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TensorToVector(*tensor_out, ctx, &out_vec);
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for (uint32_t i = 0; i < out_vec.size(); i++) {
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EXPECT_EQ(out_vec[i], static_cast<T>(0.1));
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}
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ctx.Wait();
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}
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TEST(unsqueeze, NPU_fp32) {
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f::Scope scope;
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p::NPUDeviceContext ctx(p::NPUPlace(0));
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Compare<float>(&scope, ctx);
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}
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