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193 lines
6.0 KiB
193 lines
6.0 KiB
# Copyright (c) 2020 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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import paddle
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import paddle.fluid as fluid
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from paddle.fluid.data_feeder import convert_dtype
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import paddle.fluid.core as core
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from paddle.static import program_guard, Program
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class TestEmptyLikeAPICommon(unittest.TestCase):
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def __check_out__(self, out):
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data_type = convert_dtype(out.dtype)
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self.assertEqual(data_type, self.dst_dtype,
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'dtype should be %s, but get %s' %
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(self.dst_dtype, data_type))
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shape = out.shape
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self.assertTupleEqual(shape, self.dst_shape,
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'shape should be %s, but get %s' %
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(self.dst_shape, shape))
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if data_type in ['float32', 'float64', 'int32', 'int64']:
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max_value = np.nanmax(out)
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min_value = np.nanmin(out)
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always_non_full_zero = max_value > min_value
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always_full_zero = max_value == 0.0 and min_value == 0.0
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self.assertTrue(always_full_zero or always_non_full_zero,
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'always_full_zero or always_non_full_zero.')
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elif data_type in ['bool']:
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total_num = out.size
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true_num = np.sum(out == True)
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false_num = np.sum(out == False)
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self.assertTrue(total_num == true_num + false_num,
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'The value should always be True or False.')
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else:
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self.assertTrue(False, 'invalid data type')
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class TestEmptyLikeAPI(TestEmptyLikeAPICommon):
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def setUp(self):
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self.init_config()
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def test_dygraph_api_out(self):
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paddle.disable_static()
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out = paddle.empty_like(self.x, self.dtype)
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self.__check_out__(out.numpy())
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paddle.enable_static()
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("float32")
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self.dtype = self.x.dtype
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI2(TestEmptyLikeAPI):
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("float64")
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self.dtype = self.x.dtype
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI3(TestEmptyLikeAPI):
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("int")
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self.dtype = self.x.dtype
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI4(TestEmptyLikeAPI):
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("int64")
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self.dtype = self.x.dtype
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI5(TestEmptyLikeAPI):
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("bool")
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self.dtype = self.x.dtype
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI6(TestEmptyLikeAPI):
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("float64")
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self.dtype = "float32"
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI7(TestEmptyLikeAPI):
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("int")
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self.dtype = "float32"
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI8(TestEmptyLikeAPI):
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("int64")
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self.dtype = "float32"
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI9(TestEmptyLikeAPI):
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("bool")
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self.dtype = "float32"
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI10(TestEmptyLikeAPI):
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def init_config(self):
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self.x = np.random.random((200, 3)).astype("float32")
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self.dtype = "bool"
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self.dst_shape = self.x.shape
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self.dst_dtype = self.dtype
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class TestEmptyLikeAPI_Static(TestEmptyLikeAPICommon):
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def setUp(self):
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self.init_config()
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def test_static_graph(self):
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dtype = 'float32'
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train_program = Program()
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startup_program = Program()
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with program_guard(train_program, startup_program):
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x = np.random.random(self.x_shape).astype(dtype)
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data_x = paddle.static.data(
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'x', shape=self.data_x_shape, dtype=dtype)
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out = paddle.empty_like(data_x)
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place = paddle.CUDAPlace(0) if core.is_compiled_with_cuda(
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) else paddle.CPUPlace()
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exe = paddle.static.Executor(place)
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res = exe.run(train_program, feed={'x': x}, fetch_list=[out])
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self.dst_dtype = dtype
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self.dst_shape = x.shape
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self.__check_out__(res[0])
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def init_config(self):
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self.x_shape = (200, 3)
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self.data_x_shape = [200, 3]
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class TestEmptyLikeAPI_Static2(TestEmptyLikeAPI_Static):
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def init_config(self):
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self.x_shape = (3, 200, 3)
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self.data_x_shape = [-1, 200, 3]
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class TestEmptyError(unittest.TestCase):
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def test_attr(self):
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def test_dtype():
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x = np.random.random((200, 3)).astype("float64")
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dtype = 'uint8'
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result = paddle.empty_like(x, dtype=dtype)
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self.assertRaises(TypeError, test_dtype)
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if __name__ == '__main__':
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unittest.main()
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