未验证 提交 09bf2cfc 编写于 作者: O OleNet 提交者: GitHub

[NPU] add Assign OP (#31561)

* add assign op

* add test assign npu test

* dele if def
Co-authored-by: Noyjxer <1728722986@qq.com>
上级 f1fdddfd
...@@ -120,6 +120,7 @@ if (WITH_ASCEND) ...@@ -120,6 +120,7 @@ if (WITH_ASCEND)
endif() endif()
if (WITH_ASCEND_CL) if (WITH_ASCEND_CL)
cc_test(assign_op_test SRCS assign_op_test.cc DEPS assign_op)
cc_library(npu_op_runner SRCS npu_op_runner.cc DEPS operator npu_info) cc_library(npu_op_runner SRCS npu_op_runner.cc DEPS operator npu_info)
set(COMMON_OP_DEPS ${COMMON_OP_DEPS} npu_op_runner) set(COMMON_OP_DEPS ${COMMON_OP_DEPS} npu_op_runner)
endif() endif()
......
/* 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. */
#include <string>
#include "paddle/fluid/operators/assign_op.h"
#include "paddle/fluid/platform/float16.h"
#include "paddle/fluid/operators/npu_op_runner.h"
namespace paddle {
namespace framework {
class OpDesc;
class Variable;
} // namespace framework
namespace imperative {
class OpBase;
} // namespace imperative
namespace platform {
struct CPUPlace;
struct CUDAPlace;
struct float16;
} // namespace platform
} // namespace paddle
namespace paddle {
namespace operators {
template <typename DeviceContext, typename T>
class AssignNPUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto* x = ctx.Input<framework::LoDTensor>("X");
auto* out = ctx.Output<framework::LoDTensor>("Out");
out->mutable_data<T>(ctx.GetPlace());
auto runner = NpuOpRunner("Assign", {*out, *x}, {*out}, {});
auto stream =
ctx.template device_context<paddle::platform::NPUDeviceContext>()
.stream();
runner.Run(stream);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
namespace plat = paddle::platform;
REGISTER_OP_NPU_KERNEL(assign,
ops::AssignNPUKernel<paddle::platform::NPUDeviceContext, int>,
ops::AssignNPUKernel<paddle::platform::NPUDeviceContext, float>,
ops::AssignNPUKernel<paddle::platform::NPUDeviceContext, double>)
/* 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(assign);
USE_OP_DEVICE_KERNEL(assign, NPU);
template <typename T>
void Compare(f::Scope* scope, const p::DeviceContext& ctx,
std::string op_type) {
// init
auto x = scope->Var("X");
auto tensor_x = x->GetMutable<f::LoDTensor>();
std::vector<T> init;
init.push_back(static_cast<T>(1.0));
init.push_back(static_cast<T>(2.0));
init.push_back(static_cast<T>(3.0));
init.push_back(static_cast<T>(4.0));
TensorFromVector(init, ctx, tensor_x);
tensor_x->Resize({4});
ctx.Wait();
auto place = ctx.GetPlace();
auto out = scope->Var("Out");
auto tensor_out = out->GetMutable<f::LoDTensor>();
auto op = f::OpRegistry::CreateOp(op_type,
{{"X", {"X"}}},
{{"Out", {"Out"}}},
{});
op->Run(*scope, place);
std::vector<T> out_vec;
TensorToVector(*tensor_out, ctx, &out_vec);
ctx.Wait();
EXPECT_EQ((uint32_t)out_vec.size(), (uint32_t)4);
EXPECT_EQ(out_vec[0], static_cast<T>(1.0));
EXPECT_EQ(out_vec[1], static_cast<T>(2.0));
EXPECT_EQ(out_vec[2], static_cast<T>(3.0));
EXPECT_EQ(out_vec[3], static_cast<T>(4.0));
}
TEST(assign, NPU_fp32) {
f::Scope scope;
p::NPUDeviceContext ctx(p::NPUPlace(0));
Compare<float>(&scope, ctx, "assign");
}
# 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.
from __future__ import print_function
import numpy as np
import unittest
import sys
sys.path.append("..")
from op_test import OpTest
import paddle
import paddle.fluid as fluid
from paddle.fluid import core
paddle.enable_static()
SEED = 2021
@unittest.skipIf(not paddle.is_compiled_with_npu(),
"core is not compiled with NPU")
class TestAssign(OpTest):
def setUp(self):
self.set_npu()
self.place = paddle.NPUPlace(0)
self.op_type = "assign"
self.init_dtype()
x = np.rand.random([3,3])
self.inputs = {'X': x}
self.attrs = {}
self.outputs = {'Out': x}
def set_npu(self):
self.__class__.use_npu = True
def init_dtype(self):
self.dtype = np.int64
def test_check_output(self):
self.check_output_with_place(self.place, check_dygraph=False)
if __name__ == '__main__':
unittest.main()
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