wehub-resource-sync
97 lines
3.1 KiB
Python
97 lines
3.1 KiB
Python
# 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 unittest
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import numpy as np
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import paddle
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from paddle.base import core
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class TestDenseTensorArray(unittest.TestCase):
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def test_get_set(self):
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scope = core.Scope()
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arr = scope.var('tmp_lod_tensor_array')
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tensor_array = arr.get_dense_tensor_array()
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self.assertEqual(0, len(tensor_array))
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cpu = core.CPUPlace()
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for i in range(10):
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t = core.DenseTensor()
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t.set(np.array([i], dtype='float32'), cpu)
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tensor_array.append(t)
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self.assertEqual(10, len(tensor_array))
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for i in range(10):
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t = tensor_array[i]
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self.assertEqual(np.array(t), np.array([i], dtype='float32'))
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t = core.DenseTensor()
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t.set(np.array([i + 10], dtype='float32'), cpu)
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tensor_array[i] = t
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t = tensor_array[i]
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self.assertEqual(np.array(t), np.array([i + 10], dtype='float32'))
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class TestCreateArray(unittest.TestCase):
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def setUp(self):
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self.place = paddle.CPUPlace()
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self.shapes = [[10, 4], [8, 12], [1]]
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def test_initialized_list_and_error(self):
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paddle.disable_static()
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init_data = [
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np.random.random(shape).astype('float32') for shape in self.shapes
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]
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array = paddle.tensor.create_array(
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'float32', [paddle.to_tensor(x) for x in init_data]
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)
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for res, gt in zip(array, init_data):
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np.testing.assert_array_equal(res, gt)
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# test for None
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array = paddle.tensor.create_array('float32')
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self.assertTrue(isinstance(array, list))
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self.assertEqual(len(array), 0)
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# test error
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with self.assertRaises(TypeError):
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paddle.tensor.create_array('float32', 'str')
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def test_static(self):
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paddle.enable_static()
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init_data = [
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paddle.ones(shape, dtype='float32') for shape in self.shapes
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]
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array = paddle.tensor.create_array('float32', init_data)
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for res, gt in zip(array, init_data):
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self.assertTrue(res.shape, gt.shape)
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# test error with nest list
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with self.assertRaises(TypeError):
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paddle.tensor.create_array(
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'float32', [init_data[0], [init_data[1]]]
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)
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# test error with not variable
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with self.assertRaises(TypeError):
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paddle.tensor.create_array('float32', ("str"))
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paddle.enable_static()
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if __name__ == '__main__':
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unittest.main()
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