未验证 提交 125201ee 编写于 作者: O oyxuan-11 提交者: GitHub

[NPU] Support NPU kernel sum op (#31671)

上级 ef15544e
/* 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 <memory>
#include <string>
#include <vector>
#include "paddle/fluid/operators/sum_op.h"
#include "paddle/fluid/operators/npu_op_runner.h"
namespace paddle {
namespace operators {
using Tensor = framework::Tensor;
template <typename DeviceContext, typename T>
class SumNPUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto x = ctx.MultiInput<Tensor>("X");
auto* out = ctx.Output<Tensor>("Out");
out->mutable_data<T>(ctx.GetPlace());
auto place = ctx.GetPlace();
int n = static_cast<int>(x.size());
PADDLE_ENFORCE_EQ(n > 1, true,
platform::errors::InvalidArgument(
"The size of Input(x) list must larger or equal 2"));
auto stream =
ctx.template device_context<paddle::platform::NPUDeviceContext>()
.stream();
auto runner = NpuOpRunner("Add", {*x[0], *x[1]}, {*out}, {});
runner.Run(stream);
for (int i = 2; i < n; i++) {
runner = NpuOpRunner("Add", {*out, *x[i]}, {*out}, {});
runner.Run(stream);
}
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OP_NPU_KERNEL(
sum,
ops::SumNPUKernel<paddle::platform::NPUDeviceContext, float>,
ops::SumNPUKernel<paddle::platform::NPUDeviceContext,
paddle::platform::float16>);
# 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
import paddle.fluid.core as core
paddle.enable_static()
SEED = 2021
@unittest.skipIf(not paddle.is_compiled_with_npu(),
"core is not compiled with NPU")
class TestSum1(OpTest):
def setUp(self):
self.set_npu()
self.init_dtype()
self.op_type = "sum"
self.place = paddle.NPUPlace(0)
x0 = np.random.random((3, 40)).astype(self.dtype)
x1 = np.random.random((3, 40)).astype(self.dtype)
x2 = np.random.random((3, 40)).astype(self.dtype)
self.inputs = {'X': [("x0", x0), ("x1", x1), ("x2", x2)]}
y = x0 + x1 + x2
self.outputs = {'Out': y}
self.attrs = {'use_mkldnn': False}
def init_dtype(self):
self.dtype = np.float32
def set_npu(self):
self.__class__.use_npu = True
def test_check_output(self):
self.check_output_with_place(self.place, check_dygraph=False)
class TestSum2(OpTest):
def setUp(self):
self.set_npu()
self.init_dtype()
self.op_type = "sum"
self.place = paddle.NPUPlace(0)
x0 = np.random.random((3, 3)).astype(self.dtype)
x1 = np.random.random((3, 3)).astype(self.dtype)
x2 = np.random.random((3, 3)).astype(self.dtype)
x3 = np.random.random((3, 3)).astype(self.dtype)
self.inputs = {'X': [("x0", x0), ("x1", x1), ("x2", x2), ("x3", x3)]}
y = x0 + x1 + x2 + x3
self.outputs = {'Out': y}
self.attrs = {'use_mkldnn': False}
def init_dtype(self):
self.dtype = np.float16
def set_npu(self):
self.__class__.use_npu = True
def test_check_output(self):
self.check_output_with_place(self.place, check_dygraph=False)
if __name__ == '__main__':
unittest.main()
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