1# Copyright 2021 Huawei Technologies Co., Ltd 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15""" 16Eager Tests for Transform Tensor ops 17""" 18 19import numpy as np 20import mindspore.common.dtype as mstype 21import mindspore.dataset.transforms.c_transforms as data_trans 22 23 24def test_eager_concatenate(): 25 """ 26 Test Concatenate op is callable 27 """ 28 prepend_tensor = np.array([1.4, 2., 3., 4., 4.5], dtype=np.float) 29 append_tensor = np.array([9., 10.3, 11., 12.], dtype=np.float) 30 concatenate_op = data_trans.Concatenate(0, prepend_tensor, append_tensor) 31 expected = np.array([1.4, 2., 3., 4., 4.5, 5., 6., 7., 8., 9., 10.3, 32 11., 12.]) 33 assert np.array_equal(concatenate_op([5., 6., 7., 8.]), expected) 34 35 36def test_eager_fill(): 37 """ 38 Test Fill op is callable 39 """ 40 fill_op = data_trans.Fill(3) 41 expected = np.array([3, 3, 3, 3]) 42 assert np.array_equal(fill_op([4, 5, 6, 7]), expected) 43 44 45def test_eager_mask(): 46 """ 47 Test Mask op is callable 48 """ 49 mask_op = data_trans.Mask(data_trans.Relational.EQ, 3, mstype.bool_) 50 expected = np.array([False, False, True, False, False]) 51 assert np.array_equal(mask_op([1, 2, 3, 4, 5]), expected) 52 53 54def test_eager_pad_end(): 55 """ 56 Test PadEnd op is callable 57 """ 58 pad_end_op = data_trans.PadEnd([3], -1) 59 expected = np.array([1, 2, -1]) 60 assert np.array_equal(pad_end_op([1, 2]), expected) 61 62 63def test_eager_slice(): 64 """ 65 Test Slice op is callable 66 """ 67 indexing = [[0], [0, 3]] 68 slice_op = data_trans.Slice(*indexing) 69 expected = np.array([[1, 4]]) 70 assert np.array_equal(slice_op([[1, 2, 3, 4, 5]]), expected) 71 72 73if __name__ == "__main__": 74 test_eager_concatenate() 75 test_eager_fill() 76 test_eager_mask() 77 test_eager_pad_end() 78 test_eager_slice() 79