未验证 提交 1ef21855 编写于 作者: A Aganlengzi 提交者: GitHub

[NPU] add where_index op and tests (#34951)

上级 690f5831
/* 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 "paddle/fluid/operators/where_index_op.h"
#include "paddle/fluid/operators/npu_op_runner.h"
namespace paddle {
namespace operators {
using Tensor = framework::Tensor;
template <typename T>
class NPUWhereIndexKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
auto& dev_ctx =
context.template device_context<platform::NPUDeviceContext>();
auto* condition = context.Input<Tensor>("Condition");
auto* out = context.Output<Tensor>("Out");
auto dims = condition->dims();
const int rank = dims.size();
auto place = context.GetPlace();
const aclrtStream& stream = dev_ctx.stream();
// Run Cast and ReduceSum to get 0 dim of Out
Tensor booled_cond;
if (condition->type() != framework::proto::VarType::BOOL) {
auto bool_type = ConvertToNpuDtype(framework::proto::VarType::BOOL);
booled_cond.mutable_data<bool>(dims, place);
const auto& booled_runner =
NpuOpRunner("Cast", {*condition}, {booled_cond},
{{"dst_type", static_cast<int>(bool_type)}});
booled_runner.Run(stream);
} else {
booled_cond.ShareDataWith(*condition);
}
Tensor casted_cond;
auto dst_dtype = ConvertToNpuDtype(framework::proto::VarType::INT64);
casted_cond.mutable_data<int64_t>(dims, place);
const auto& cast_runner =
NpuOpRunner("Cast", {booled_cond}, {casted_cond},
{{"dst_type", static_cast<int>(dst_dtype)}});
cast_runner.Run(stream);
Tensor sumed_true_num;
sumed_true_num.mutable_data<int64_t>({1}, place);
Tensor cond_axes;
cond_axes.mutable_data<int>({dims.size()}, place);
std::vector<int> axes_vec;
for (int i = 0; i < dims.size(); ++i) {
axes_vec.push_back(i);
}
framework::TensorFromVector<int>(axes_vec, dev_ctx, &cond_axes);
const auto& sum_runner =
NpuOpRunner("ReduceSum", {casted_cond, cond_axes}, {sumed_true_num},
{{"keep_dims", false}});
sum_runner.Run(stream);
Tensor local_true_num;
TensorCopySync(sumed_true_num, platform::CPUPlace(), &local_true_num);
auto true_num = *local_true_num.data<int64_t>();
out->Resize(framework::make_ddim({true_num, rank}));
out->mutable_data<int64_t>(place);
if (true_num == 0) {
return;
}
out->set_layout(DataLayout::kAnyLayout);
NpuOpRunner runner{"Where", {*condition}, {*out}};
runner.Run(stream);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OP_NPU_KERNEL(where_index, ops::NPUWhereIndexKernel<int64_t>,
ops::NPUWhereIndexKernel<int>,
ops::NPUWhereIndexKernel<bool>,
ops::NPUWhereIndexKernel<float>,
ops::NPUWhereIndexKernel<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.
from __future__ import print_function
import numpy as np
import unittest
import paddle
import sys
sys.path.append("..")
from op_test import OpTest
from paddle.fluid.op import Operator
import paddle.fluid as fluid
from paddle.fluid import Program, program_guard
paddle.enable_static()
class TestWhereIndexOp(OpTest):
def setUp(self):
self.set_npu()
self.op_type = "where_index"
self.place = paddle.NPUPlace(0)
self.init_config()
def test_check_output(self):
self.check_output_with_place(self.place)
def init_config(self):
self.inputs = {'Condition': np.array([True, False, True]), }
self.outputs = {'Out': np.array([[0], [2]], dtype='int64')}
def set_npu(self):
self.__class__.use_npu = True
class TestNotBool(TestWhereIndexOp):
def init_config(self):
self.inputs = {'Condition': np.array([1, 0, 8]), }
self.outputs = {'Out': np.array([[0], [2]], dtype='int64')}
class TestAllFalse(TestWhereIndexOp):
def init_config(self):
self.inputs = {'Condition': np.array([False, False, False]), }
self.outputs = {'Out': np.array([], dtype='int64')}
class TestRank2(TestWhereIndexOp):
def init_config(self):
self.inputs = {'Condition': np.array([[True, False], [False, True]]), }
self.outputs = {'Out': np.array([[0, 0], [1, 1]], dtype='int64')}
class TestRank3(TestWhereIndexOp):
def init_config(self):
self.inputs = {
'Condition': np.array([[[True, False], [False, True]],
[[False, True], [True, False]],
[[False, False], [False, True]]]),
}
self.outputs = {
'Out': np.array(
[[0, 0, 0], [0, 1, 1], [1, 0, 1], [1, 1, 0], [2, 1, 1]],
dtype='int64')
}
class TestWhereOpError(unittest.TestCase):
def test_api(self):
with program_guard(Program(), Program()):
cond = fluid.layers.data(name='cond', shape=[4], dtype='bool')
result = fluid.layers.where(cond)
exe = fluid.Executor(paddle.NPUPlace(0))
exe.run(fluid.default_startup_program())
cond_i = np.array([True, False, False, False]).astype("bool")
out = exe.run(fluid.default_main_program(), feed={'cond': cond_i})
class TestWhereRaiseError(unittest.TestCase):
def test_errors(self):
def test_type():
fluid.layers.where([10])
self.assertRaises(TypeError, test_type)
if __name__ == "__main__":
unittest.main()
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