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130 lines
3.6 KiB
130 lines
3.6 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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import numpy as np
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import unittest
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import paddle.fluid as fluid
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from op_test import OpTest
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class TestStackOpBase(OpTest):
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def initDefaultParameters(self):
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self.num_inputs = 4
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self.input_dim = (5, 6, 7)
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self.axis = 0
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self.dtype = 'float64'
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def initParameters(self):
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pass
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def get_x_names(self):
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x_names = []
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for i in range(self.num_inputs):
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x_names.append('x{}'.format(i))
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return x_names
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def setUp(self):
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self.initDefaultParameters()
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self.initParameters()
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self.op_type = 'stack'
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self.x = []
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for i in range(self.num_inputs):
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self.x.append(
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np.random.random(size=self.input_dim).astype(self.dtype))
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tmp = []
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x_names = self.get_x_names()
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for i in range(self.num_inputs):
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tmp.append((x_names[i], self.x[i]))
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self.inputs = {'X': tmp}
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self.outputs = {'Y': np.stack(self.x, axis=self.axis)}
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self.attrs = {'axis': self.axis}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(self.get_x_names(), 'Y')
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class TestStackOp1(TestStackOpBase):
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def initParameters(self):
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self.num_inputs = 16
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class TestStackOp2(TestStackOpBase):
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def initParameters(self):
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self.num_inputs = 20
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class TestStackOp3(TestStackOpBase):
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def initParameters(self):
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self.axis = -1
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class TestStackOp4(TestStackOpBase):
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def initParameters(self):
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self.axis = -4
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class TestStackOp5(TestStackOpBase):
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def initParameters(self):
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self.axis = 1
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class TestStackOp6(TestStackOpBase):
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def initParameters(self):
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self.axis = 3
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class TestStackAPIWithLoDTensorArray(unittest.TestCase):
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"""
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Test stack api when the input(x) is a LoDTensorArray.
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"""
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def setUp(self):
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self.axis = 1
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self.iter_num = 3
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self.input_shape = [2, 3]
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self.x = np.random.random(self.input_shape).astype("float32")
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self.place = fluid.CUDAPlace(0) \
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if fluid.is_compiled_with_cuda() else fluid.CPUPlace()
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self.set_program()
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def set_program(self):
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self.program = fluid.Program()
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with fluid.program_guard(self.program):
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input = fluid.layers.assign(self.x)
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tensor_array = fluid.layers.create_array(dtype='float32')
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zero = fluid.layers.fill_constant(shape=[1], value=0, dtype="int64")
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for i in range(self.iter_num):
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fluid.layers.array_write(input, zero + i, tensor_array)
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self.out_var = fluid.layers.stack(tensor_array, axis=self.axis)
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def test_case(self):
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self.assertTrue(self.out_var.shape[self.axis] == -1)
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exe = fluid.Executor(self.place)
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res = exe.run(self.program, fetch_list=self.out_var)
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self.assertTrue(
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np.array_equal(
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res[0], np.stack(
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[self.x] * self.iter_num, axis=self.axis)))
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if __name__ == '__main__':
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unittest.main()
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