[NPU] add NPU add topk (#31596)
* add topk op * add cmake * update topk npu op * refactor func * fix test not go npu TopKD bug * NPUPlace(4) to NPUPlace(0) * update comment Co-authored-by: oyjxer <1728722986@qq.com>ascendrc
OleNet
4 years ago
committed by
GitHub
parent
743cc9b29b
commit
ef15544ee0
@ -0,0 +1,89 @@
|
|||||||
|
/* 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 "paddle/fluid/operators/top_k_op.h"
|
||||||
|
#include "paddle/fluid/operators/npu_op_runner.h"
|
||||||
|
|
||||||
|
namespace paddle {
|
||||||
|
namespace operators {
|
||||||
|
|
||||||
|
void gen_assist_seq(framework::Tensor* assit_tensor,
|
||||||
|
int64_t dim, const framework::ExecutionContext& ctx) {
|
||||||
|
const int64_t dimx2 = dim;
|
||||||
|
std::vector<paddle::platform::float16> assit;
|
||||||
|
assit.resize(2 * dimx2);
|
||||||
|
for (int64_t i = 0; i < dimx2; i++) {
|
||||||
|
// for i in range [0, dim]
|
||||||
|
assit[i] = static_cast<paddle::platform::float16>(i);
|
||||||
|
|
||||||
|
// for i in range [dim, dimx2]
|
||||||
|
int64_t idx = static_cast<int64_t>(
|
||||||
|
static_cast<paddle::platform::float16>(i));
|
||||||
|
int64_t gap = i - idx;
|
||||||
|
assit[i + dim] = static_cast<paddle::platform::float16>(gap);
|
||||||
|
}
|
||||||
|
framework::TensorFromVector(assit, ctx.device_context(), assit_tensor);
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
template <typename DeviceContext, typename T>
|
||||||
|
class TopkNPUKernel : public framework::OpKernel<T> {
|
||||||
|
public:
|
||||||
|
void Compute(const framework::ExecutionContext& ctx) const override {
|
||||||
|
// read input
|
||||||
|
auto* input = ctx.Input<framework::LoDTensor>("X");
|
||||||
|
auto* output = ctx.Output<framework::LoDTensor>("Out");
|
||||||
|
auto* indices = ctx.Output<framework::LoDTensor>("Indices");
|
||||||
|
|
||||||
|
size_t k = static_cast<int>(ctx.Attr<int>("k"));
|
||||||
|
|
||||||
|
output->mutable_data<T>(ctx.GetPlace());
|
||||||
|
indices->mutable_data<int>(ctx.GetPlace());
|
||||||
|
|
||||||
|
// prepare assit
|
||||||
|
auto dim = input->dims().size();
|
||||||
|
framework::Tensor assist_seq_tensor;
|
||||||
|
assist_seq_tensor.Resize({2 * dim});
|
||||||
|
assist_seq_tensor.mutable_data<T>(ctx.GetPlace());
|
||||||
|
gen_assist_seq(&assist_seq_tensor, dim, ctx);
|
||||||
|
|
||||||
|
framework::NPUAttributeMap attr_input = {{"sorted", "true"},
|
||||||
|
{"k", static_cast<int>(k)},
|
||||||
|
{"dim", -1},
|
||||||
|
{"largest", true}};
|
||||||
|
|
||||||
|
// run ascend
|
||||||
|
auto runner = NpuOpRunner("TopKD",
|
||||||
|
{*input, assist_seq_tensor},
|
||||||
|
{*output, *indices},
|
||||||
|
attr_input);
|
||||||
|
|
||||||
|
auto stream =
|
||||||
|
ctx.template device_context<paddle::platform::NPUDeviceContext>()
|
||||||
|
.stream();
|
||||||
|
|
||||||
|
runner.Run(stream);
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
} // namespace operators
|
||||||
|
} // namespace paddle
|
||||||
|
|
||||||
|
namespace ops = paddle::operators;
|
||||||
|
|
||||||
|
// Ascend Op TopKD only support input float 16 dtype
|
||||||
|
REGISTER_OP_NPU_KERNEL(
|
||||||
|
top_k,
|
||||||
|
ops::TopkNPUKernel<paddle::platform::NPUDeviceContext,
|
||||||
|
paddle::platform::float16>);
|
||||||
@ -0,0 +1,95 @@
|
|||||||
|
# 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 TestTopk(OpTest):
|
||||||
|
def setUp(self):
|
||||||
|
self.set_npu()
|
||||||
|
self.place = paddle.NPUPlace(0)
|
||||||
|
self.op_type = "top_k"
|
||||||
|
self.init_dtype()
|
||||||
|
|
||||||
|
x = np.array([[0.78104149, 0.88745828, 0.32362268],
|
||||||
|
[0.82196718, 0.48763277, 0.42826136],
|
||||||
|
[0.96527182, 0.34851612, 0.12959783]]).astype(self.dtype)
|
||||||
|
|
||||||
|
self.inputs = {'X': x}
|
||||||
|
np_out = np.array([[0.88745828], [0.82196718], [0.96527182]]).astype(self.dtype)
|
||||||
|
np_indices = np.array([[1], [0], [0]])
|
||||||
|
|
||||||
|
self.attrs = {'k': 1, "axis": -1}
|
||||||
|
self.outputs = {'Out': np_out, 'Indices':np_indices}
|
||||||
|
|
||||||
|
def set_npu(self):
|
||||||
|
self.__class__.use_npu = True
|
||||||
|
self.__class__.no_need_check_grad = True
|
||||||
|
|
||||||
|
def init_dtype(self):
|
||||||
|
self.dtype = np.float16
|
||||||
|
|
||||||
|
def test_check_output(self):
|
||||||
|
self.check_output_with_place(self.place, check_dygraph=False)
|
||||||
|
|
||||||
|
|
||||||
|
@unittest.skipIf(not paddle.is_compiled_with_npu(),
|
||||||
|
"core is not compiled with NPU")
|
||||||
|
class TestTopkV2(OpTest):
|
||||||
|
def setUp(self):
|
||||||
|
self.set_npu()
|
||||||
|
self.place = paddle.NPUPlace(0)
|
||||||
|
self.op_type = "top_k"
|
||||||
|
self.init_dtype()
|
||||||
|
|
||||||
|
x = np.array([[0.78104149, 0.88745828, 0.32362268],
|
||||||
|
[0.82196718, 0.48763277, 0.42826136],
|
||||||
|
[0.96527182, 0.34851612, 0.12959783]]).astype(self.dtype)
|
||||||
|
|
||||||
|
self.inputs = {'X': x}
|
||||||
|
np_out = np.array([[0.88745828, 0.78104149], [0.82196718, 0.48763277], [0.96527182, 0.34851612]]).astype(self.dtype)
|
||||||
|
np_indices = np.array([[1, 0], [0, 1], [0, 1]])
|
||||||
|
|
||||||
|
self.attrs = {'k': 2, "axis": -1}
|
||||||
|
self.outputs = {'Out': np_out, 'Indices':np_indices}
|
||||||
|
|
||||||
|
def set_npu(self):
|
||||||
|
self.__class__.use_npu = True
|
||||||
|
self.__class__.no_need_check_grad = True
|
||||||
|
|
||||||
|
def init_dtype(self):
|
||||||
|
self.dtype = np.float16
|
||||||
|
|
||||||
|
def test_check_output(self):
|
||||||
|
self.check_output_with_place(self.place, check_dygraph=False)
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
unittest.main()
|
||||||
|
|
||||||
|
|
||||||
Loading…
Reference in new issue