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75 lines
2.3 KiB
75 lines
2.3 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest
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from test_softmax_op import stable_softmax
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import paddle.fluid.core as core
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class TestSequenceSoftmaxOp(OpTest):
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def setUp(self):
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self.op_type = "sequence_softmax"
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self.use_cudnn = False
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self.init_op_type()
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x = np.random.uniform(0.1, 1, (11, 1)).astype("float32")
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lod = [[4, 1, 3, 3]]
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out = np.zeros((11, 1)).astype("float32")
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offset = 0
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for i in range(len(lod[0])):
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sub_x = x[offset:offset + lod[0][i], :]
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sub_x = sub_x.reshape(1, lod[0][i])
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sub_out = stable_softmax(sub_x)
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out[offset:offset + lod[0][i], :] = sub_out.reshape(lod[0][i], 1)
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offset += lod[0][i]
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self.inputs = {"X": (x, lod)}
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self.outputs = {"Out": out}
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self.attrs = {'use_cudnn': self.use_cudnn, }
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def init_op_type(self):
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pass
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def test_check_output(self):
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if self.use_cudnn:
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place = core.CUDAPlace(0)
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self.check_output_with_place(place, atol=1e-5)
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else:
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self.check_output()
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def test_check_grad(self):
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if self.use_cudnn:
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place = core.CUDAPlace(0)
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self.check_grad_with_place(
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place, ["X"], "Out", max_relative_error=0.01)
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else:
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self.check_grad(["X"], "Out", max_relative_error=0.01)
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# ----------------cudnn Sequencesoftmax----------------
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@unittest.skipIf(not core.is_compiled_with_cuda(),
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"core is not compiled with CUDA")
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class TestSequenceSoftmaxCUDNNOp(TestSequenceSoftmaxOp):
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def init_op_type(self):
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self.use_cudnn = True
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if __name__ == "__main__":
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unittest.main()
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