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117 lines
3.3 KiB
117 lines
3.3 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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import paddle.fluid.core as core
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import paddle.fluid as fluid
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from paddle.fluid import Program, program_guard
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class TestPadOp(OpTest):
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def setUp(self):
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self.initTestCase()
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self.dtype = self.get_dtype()
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self.op_type = "pad"
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self.inputs = {'X': np.random.random(self.shape).astype(self.dtype), }
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self.attrs = {}
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self.attrs['paddings'] = np.array(self.paddings).flatten()
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self.attrs['pad_value'] = self.pad_value
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self.outputs = {
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'Out': np.pad(self.inputs['X'],
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self.paddings,
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mode='constant',
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constant_values=self.pad_value)
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}
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def get_dtype(self):
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return np.float64
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def test_check_output(self):
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self.check_output()
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def test_check_grad_normal(self):
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self.check_grad(['X'], 'Out')
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def initTestCase(self):
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self.shape = (16, 16)
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self.paddings = [(0, 1), (2, 3)]
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self.pad_value = 0.0
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class TestCase1(TestPadOp):
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def initTestCase(self):
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self.shape = (2, 3, 4, 5)
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self.paddings = [(0, 1), (2, 3), (2, 1), (1, 1)]
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self.pad_value = 0.5
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class TestCase2(TestPadOp):
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def initTestCase(self):
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self.shape = (5, 5, 5)
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self.paddings = [(0, 0), (0, 0), (1, 2)]
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self.pad_value = 1.0
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class TestCase3(TestPadOp):
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def initTestCase(self):
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self.shape = (100)
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self.paddings = [(0, 1)]
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self.pad_value = 0.9
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#----------------Pad Fp16----------------
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def create_test_fp16(parent):
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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 TestPadFp16(parent):
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def get_dtype(self):
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return np.float16
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def test_check_grad_normal(self):
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self.check_grad(['X'], 'Out', max_relative_error=0.3)
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cls_name = "{0}_{1}".format(parent.__name__, "Fp16")
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TestPadFp16.__name__ = cls_name
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globals()[cls_name] = TestPadFp16
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create_test_fp16(TestPadOp)
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create_test_fp16(TestCase1)
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create_test_fp16(TestCase2)
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create_test_fp16(TestCase3)
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class TestPadOpError(unittest.TestCase):
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def test_errors(self):
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with program_guard(Program(), Program()):
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input_data = np.random.random((2, 2)).astype("float32")
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def test_Variable():
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fluid.layers.pad(x=input_data, paddings=[1, 1, 1, 1])
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self.assertRaises(TypeError, test_Variable)
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data = fluid.data(name='data', shape=[4], dtype='float16')
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fluid.layers.pad(x=data, paddings=[0, 1])
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if __name__ == '__main__':
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unittest.main()
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