You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
73 lines
2.9 KiB
73 lines
2.9 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
# ==============================================================================
|
|
import numpy as np
|
|
|
|
import mindspore.dataset as ds
|
|
|
|
|
|
def test_tensor_empty():
|
|
def gen():
|
|
for _ in range(4):
|
|
(yield np.array([], dtype=np.int64), np.array([], dtype='S').reshape([0, 4]), np.array([1],
|
|
dtype=np.float64))
|
|
|
|
data = ds.GeneratorDataset(gen, column_names=["col1", "col2", "col3"])
|
|
|
|
for d in data.create_tuple_iterator(output_numpy=True):
|
|
np.testing.assert_array_equal(np.array([], dtype=np.int64), d[0])
|
|
np.testing.assert_array_equal(np.array([], dtype='S').reshape([0, 4]), d[1])
|
|
np.testing.assert_array_equal(np.array([1], dtype=np.float64), d[2])
|
|
|
|
|
|
def test_tensor_empty_map():
|
|
def gen():
|
|
for _ in range(4):
|
|
(yield np.array([], dtype=np.int64), np.array([], dtype='S'), np.array([1], dtype=np.float64))
|
|
|
|
data = ds.GeneratorDataset(gen, column_names=["col1", "col2", "col3"])
|
|
|
|
def func(x, y, z):
|
|
x = np.array([1], dtype=np.int64)
|
|
y = np.array(["Hi"], dtype='S')
|
|
z = np.array([], dtype=np.float64)
|
|
return x, y, z
|
|
|
|
data = data.map(operations=func, input_columns=["col1", "col2", "col3"])
|
|
|
|
for d in data.create_tuple_iterator(output_numpy=True):
|
|
np.testing.assert_array_equal(np.array([1], dtype=np.int64), d[0])
|
|
np.testing.assert_array_equal(np.array(["Hi"], dtype='S'), d[1])
|
|
np.testing.assert_array_equal(np.array([], dtype=np.float64), d[2])
|
|
|
|
|
|
def test_tensor_empty_batch():
|
|
def gen():
|
|
for _ in range(4):
|
|
(yield np.array([], dtype=np.int64), np.array([], dtype='S').reshape([0, 4]), np.array([1],
|
|
dtype=np.float64))
|
|
|
|
data = ds.GeneratorDataset(gen, column_names=["col1", "col2", "col3"]).batch(2)
|
|
|
|
for d in data.create_tuple_iterator(output_numpy=True):
|
|
np.testing.assert_array_equal(np.array([], dtype=np.int64).reshape([2, 0]), d[0])
|
|
np.testing.assert_array_equal(np.array([], dtype='S').reshape([2, 0, 4]), d[1])
|
|
np.testing.assert_array_equal(np.array([[1], [1]], dtype=np.float64), d[2])
|
|
|
|
|
|
if __name__ == '__main__':
|
|
test_tensor_empty()
|
|
test_tensor_empty_map()
|
|
test_tensor_empty_batch()
|