From ba6a312d1356a228e96911950fc2cd965ae0b496 Mon Sep 17 00:00:00 2001 From: June Weng Date: Fri, 3 Sep 2021 09:53:13 +0800 Subject: [PATCH] add log_softmax_op_npu (#35006) * add log_softmax_op_npu * log_softmax_op_v1 * import test_log_softmax_grad --- paddle/fluid/operators/log_softmax_op_npu.cc | 45 +++++++++ .../unittests/npu/test_log_softmax_op_npu.py | 95 +++++++++++++++++++ 2 files changed, 140 insertions(+) create mode 100644 paddle/fluid/operators/log_softmax_op_npu.cc create mode 100644 python/paddle/fluid/tests/unittests/npu/test_log_softmax_op_npu.py diff --git a/paddle/fluid/operators/log_softmax_op_npu.cc b/paddle/fluid/operators/log_softmax_op_npu.cc new file mode 100644 index 0000000000000..d955bef6ce2ac --- /dev/null +++ b/paddle/fluid/operators/log_softmax_op_npu.cc @@ -0,0 +1,45 @@ +// 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/log_softmax_op.h" +#include "paddle/fluid/operators/npu_op_runner.h" +namespace paddle { +namespace operators { +template +class LogSoftmaxNPUKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + auto* X = ctx.Input("X"); + auto* Out = ctx.Output("Out"); + const int rank = X->dims().size(); + const int axis = CanonicalAxis(ctx.Attr("axis"), rank); + std::vector axes; + axes.push_back(axis); + framework::NPUAttributeMap attr_input = {{"axes", axes}}; + Out->mutable_data(ctx.GetPlace()); + const auto& runner = NpuOpRunner("LogSoftmaxV2", {*X}, {*Out}, attr_input); + auto stream = + ctx.template device_context() + .stream(); + runner.Run(stream); + } +}; +} // namespace operators +} // namespace paddle +namespace ops = paddle::operators; +namespace plat = paddle::platform; + +REGISTER_OP_NPU_KERNEL( + log_softmax, + ops::LogSoftmaxNPUKernel); diff --git a/python/paddle/fluid/tests/unittests/npu/test_log_softmax_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_log_softmax_op_npu.py new file mode 100644 index 0000000000000..e8b680d1ddc1b --- /dev/null +++ b/python/paddle/fluid/tests/unittests/npu/test_log_softmax_op_npu.py @@ -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 +import paddle.nn.functional as F +from test_log_softmax import ref_log_softmax, ref_log_softmax_grad +paddle.enable_static() +np.random.seed(10) + + +class TestLogSoftmaxNPUOp(OpTest): + def setUp(self): + self.set_npu() + self.place = paddle.NPUPlace(0) + self.op_type = "log_softmax" + self.dtype = np.float32 + self.shape = [2, 3, 4, 5] + self.axis = -1 + self.set_attrs() + self.set_dtype() + x = np.random.uniform(0.1, 1., self.shape).astype(self.dtype) + out = np.apply_along_axis(ref_log_softmax, self.axis, x) + self.x_grad = ref_log_softmax_grad(x, self.axis) + self.inputs = {'X': x} + self.outputs = {'Out': out} + self.attrs = {'axis': self.axis} + + def set_npu(self): + self.__class__.use_npu = True + self.__class__.no_need_check_grad = True + + def set_attrs(self): + pass + + def set_dtype(self): + pass + + def test_check_output(self): + self.check_output_with_place(self.place) + + def test_check_grad(self): + pass + + +def test_class(op_type, typename): + class TestLogSoftmaxShape(TestLogSoftmaxNPUOp): + def set_attrs(self): + self.shape = [12, 10] + + def set_dtype(self): + self.dtype = typename + + cls_name = "{0}_{1}_1".format(op_type, typename) + TestLogSoftmaxShape.__name__ = cls_name + globals()[cls_name] = TestLogSoftmaxShape + + +def test_class2(op_type, typename): + class TestLogSoftmaxAxis(TestLogSoftmaxNPUOp): + def set_attrs(self): + self.axis = 0 + + def set_dtype(self): + self.dtype = typename + + cls_name = "{0}_{1}_2".format(op_type, typename) + + TestLogSoftmaxAxis.__name__ = cls_name + globals()[cls_name] = TestLogSoftmaxAxis + + +for _typename in {'float32'}: + test_class("logsoftmax", _typename) + test_class2("logsoftmax", _typename) +if __name__ == '__main__': + unittest.main()