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73 lines
2.9 KiB
73 lines
2.9 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.fluid as fluid
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import paddle.fluid.layers as layers
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import paddle.fluid.core as core
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from paddle.fluid import compiler, Program, program_guard
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from paddle.fluid.op import Operator
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from paddle.fluid.backward import append_backward
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class TestLoDAppendAPI(unittest.TestCase):
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def test_api(self, use_cuda=False):
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main_program = Program()
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with fluid.program_guard(main_program):
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x = fluid.layers.data(name='x', shape=[6], dtype='float32')
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level = fluid.layers.data(
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name='level', shape=[3], dtype='int32', lod_level=0)
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result = fluid.layers.lod_append(x, level)
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x_i = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0]).astype("float32")
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level_i = np.array([0, 2, 6]).astype("int32")
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for use_cuda in [False, True]:
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if use_cuda and not fluid.core.is_compiled_with_cuda():
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return
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place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
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exe = fluid.Executor(place)
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[out] = exe.run(fluid.default_main_program(),
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feed={'x': x_i,
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'level': level_i},
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fetch_list=[result],
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return_numpy=False)
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self.assertEqual(out.recursive_sequence_lengths(), [[2, 4]])
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class TestLodAppendOpError(unittest.TestCase):
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def test_error(self):
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# The input(x) must be Variable.
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x1 = np.array([0.9383, 0.1983, 3.2, 1.2]).astype("float64")
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level1 = [0, 2, 4]
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self.assertRaises(TypeError, fluid.layers.lod_append, x1, level1)
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#The input(level) must be Variable or list.
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x2 = fluid.layers.data(name='x2', shape=[4], dtype='float32')
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self.assertRaises(ValueError, fluid.layers.lod_append, x2, 2)
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# Input(x) dtype must be float32 or float64 or int32 or int64
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for dtype in ["bool", "float16"]:
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x3 = fluid.layers.data(name='x3_' + dtype, shape=[4], dtype=dtype)
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level3 = fluid.layers.data(
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name='level3' + dtype, shape=[4], dtype='int32', lod_level=2)
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self.assertRaises(TypeError, fluid.layers.lod_append, x3, level3)
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if __name__ == "__main__":
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unittest.main()
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