185 lines
6.7 KiB
Python
185 lines
6.7 KiB
Python
# Copyright 2020 Huawei Technologies Co., Ltd
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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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# ==============================================================================
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"""
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Testing concatenate op
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"""
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import numpy as np
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import pytest
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import mindspore.dataset as ds
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import mindspore.dataset.transforms.c_transforms as data_trans
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def test_concatenate_op_all():
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def gen():
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yield (np.array([5., 6., 7., 8.], dtype=np.float),)
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prepend_tensor = np.array([1.4, 2., 3., 4., 4.5], dtype=np.float)
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append_tensor = np.array([9., 10.3, 11., 12.], dtype=np.float)
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data = ds.GeneratorDataset(gen, column_names=["col"])
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concatenate_op = data_trans.Concatenate(0, prepend_tensor, append_tensor)
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data = data.map(input_columns=["col"], operations=concatenate_op)
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expected = np.array([1.4, 2., 3., 4., 4.5, 5., 6., 7., 8., 9., 10.3,
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11., 12.])
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for data_row in data:
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np.testing.assert_array_equal(data_row[0], expected)
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def test_concatenate_op_none():
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def gen():
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yield (np.array([5., 6., 7., 8.], dtype=np.float),)
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data = ds.GeneratorDataset(gen, column_names=["col"])
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concatenate_op = data_trans.Concatenate()
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data = data.map(input_columns=["col"], operations=concatenate_op)
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for data_row in data:
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np.testing.assert_array_equal(data_row[0], np.array([5., 6., 7., 8.], dtype=np.float))
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def test_concatenate_op_string():
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def gen():
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yield (np.array(["ss", "ad"], dtype='S'),)
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prepend_tensor = np.array(["dw", "df"], dtype='S')
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append_tensor = np.array(["dwsdf", "df"], dtype='S')
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data = ds.GeneratorDataset(gen, column_names=["col"])
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concatenate_op = data_trans.Concatenate(0, prepend_tensor, append_tensor)
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data = data.map(input_columns=["col"], operations=concatenate_op)
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expected = np.array(["dw", "df", "ss", "ad", "dwsdf", "df"], dtype='S')
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for data_row in data:
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np.testing.assert_array_equal(data_row[0], expected)
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def test_concatenate_op_multi_input_string():
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prepend_tensor = np.array(["dw", "df"], dtype='S')
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append_tensor = np.array(["dwsdf", "df"], dtype='S')
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data = ([["1", "2", "d"]], [["3", "4", "e"]])
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data = ds.NumpySlicesDataset(data, column_names=["col1", "col2"])
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concatenate_op = data_trans.Concatenate(0, prepend=prepend_tensor, append=append_tensor)
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data = data.map(input_columns=["col1", "col2"], column_order=["out1"], output_columns=["out1"],
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operations=concatenate_op)
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expected = np.array(["dw", "df", "1", "2", "d", "3", "4", "e", "dwsdf", "df"], dtype='S')
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for data_row in data:
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np.testing.assert_array_equal(data_row[0], expected)
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def test_concatenate_op_multi_input_numeric():
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prepend_tensor = np.array([3, 5])
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data = ([[1, 2]], [[3, 4]])
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data = ds.NumpySlicesDataset(data, column_names=["col1", "col2"])
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concatenate_op = data_trans.Concatenate(0, prepend=prepend_tensor)
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data = data.map(input_columns=["col1", "col2"], column_order=["out1"], output_columns=["out1"],
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operations=concatenate_op)
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expected = np.array([3, 5, 1, 2, 3, 4])
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for data_row in data:
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np.testing.assert_array_equal(data_row[0], expected)
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def test_concatenate_op_type_mismatch():
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def gen():
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yield (np.array([3, 4], dtype=np.float),)
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prepend_tensor = np.array(["ss", "ad"], dtype='S')
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data = ds.GeneratorDataset(gen, column_names=["col"])
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concatenate_op = data_trans.Concatenate(0, prepend_tensor)
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data = data.map(input_columns=["col"], operations=concatenate_op)
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with pytest.raises(RuntimeError) as error_info:
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for _ in data:
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pass
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assert "Tensor types do not match" in str(error_info.value)
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def test_concatenate_op_type_mismatch2():
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def gen():
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yield (np.array(["ss", "ad"], dtype='S'),)
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prepend_tensor = np.array([3, 5], dtype=np.float)
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data = ds.GeneratorDataset(gen, column_names=["col"])
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concatenate_op = data_trans.Concatenate(0, prepend_tensor)
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data = data.map(input_columns=["col"], operations=concatenate_op)
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with pytest.raises(RuntimeError) as error_info:
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for _ in data:
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pass
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assert "Tensor types do not match" in str(error_info.value)
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def test_concatenate_op_incorrect_dim():
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def gen():
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yield (np.array([["ss", "ad"], ["ss", "ad"]], dtype='S'),)
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prepend_tensor = np.array(["ss", "ss"], dtype='S')
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concatenate_op = data_trans.Concatenate(0, prepend_tensor)
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data = ds.GeneratorDataset(gen, column_names=["col"])
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data = data.map(input_columns=["col"], operations=concatenate_op)
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with pytest.raises(RuntimeError) as error_info:
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for _ in data:
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pass
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assert "Only 1D tensors supported" in str(error_info.value)
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def test_concatenate_op_wrong_axis():
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with pytest.raises(ValueError) as error_info:
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data_trans.Concatenate(2)
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assert "only 1D concatenation supported." in str(error_info.value)
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def test_concatenate_op_negative_axis():
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def gen():
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yield (np.array([5., 6., 7., 8.], dtype=np.float),)
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prepend_tensor = np.array([1.4, 2., 3., 4., 4.5], dtype=np.float)
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append_tensor = np.array([9., 10.3, 11., 12.], dtype=np.float)
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data = ds.GeneratorDataset(gen, column_names=["col"])
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concatenate_op = data_trans.Concatenate(-1, prepend_tensor, append_tensor)
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data = data.map(input_columns=["col"], operations=concatenate_op)
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expected = np.array([1.4, 2., 3., 4., 4.5, 5., 6., 7., 8., 9., 10.3,
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11., 12.])
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for data_row in data:
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np.testing.assert_array_equal(data_row[0], expected)
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def test_concatenate_op_incorrect_input_dim():
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prepend_tensor = np.array([["ss", "ad"], ["ss", "ad"]], dtype='S')
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with pytest.raises(ValueError) as error_info:
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data_trans.Concatenate(0, prepend_tensor)
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assert "can only prepend 1D arrays." in str(error_info.value)
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if __name__ == "__main__":
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test_concatenate_op_all()
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test_concatenate_op_none()
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test_concatenate_op_string()
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test_concatenate_op_multi_input_string()
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test_concatenate_op_multi_input_numeric()
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test_concatenate_op_type_mismatch()
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test_concatenate_op_type_mismatch2()
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test_concatenate_op_incorrect_dim()
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test_concatenate_op_negative_axis()
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test_concatenate_op_wrong_axis()
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test_concatenate_op_incorrect_input_dim()
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