# Copyright (c) 2018 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. import unittest import numpy as np from op_test import OpTest from test_softmax_op import stable_softmax import paddle.fluid.core as core class TestSequenceSoftmaxOp(OpTest): def setUp(self): self.op_type = "sequence_softmax" self.use_cudnn = False self.init_op_type() x = np.random.uniform(0.1, 1, (11, 1)).astype("float32") lod = [[4, 1, 3, 3]] out = np.zeros((11, 1)).astype("float32") offset = 0 for i in range(len(lod[0])): sub_x = x[offset:offset + lod[0][i], :] sub_x = sub_x.reshape(1, lod[0][i]) sub_out = stable_softmax(sub_x) out[offset:offset + lod[0][i], :] = sub_out.reshape(lod[0][i], 1) offset += lod[0][i] self.inputs = {"X": (x, lod)} self.outputs = {"Out": out} self.attrs = {'use_cudnn': self.use_cudnn, } def init_op_type(self): pass def test_check_output(self): if self.use_cudnn: place = core.CUDAPlace(0) self.check_output_with_place(place, atol=1e-5) else: self.check_output() def test_check_grad(self): if self.use_cudnn: place = core.CUDAPlace(0) self.check_grad_with_place( place, ["X"], "Out", max_relative_error=0.01) else: self.check_grad(["X"], "Out", max_relative_error=0.01) # ----------------cudnn Sequencesoftmax---------------- @unittest.skipIf(not core.is_compiled_with_cuda(), "core is not compiled with CUDA") class TestSequenceSoftmaxCUDNNOp(TestSequenceSoftmaxOp): def init_op_type(self): self.use_cudnn = True if __name__ == "__main__": unittest.main()