def test_sliding_window_exception():
try:
_ = text.SlidingWindow(0, 0)
assert False
except ValueError:
pass
try:
_ = text.SlidingWindow("1", 0)
assert False
except TypeError:
pass
try:
_ = text.SlidingWindow(1, "0")
assert False
except TypeError:
pass
try:
inputs = [[1, 2, 3, 4, 5]]
dataset = ds.NumpySlicesDataset(inputs,
column_names=["text"],
shuffle=False)
dataset = dataset.map(operations=text.SlidingWindow(3, -100),
input_columns=["text"])
for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
pass
assert False
except RuntimeError as e:
assert "axis supports 0 or -1 only for now." in str(e)
try:
inputs = ["aa", "bb", "cc"]
dataset = ds.NumpySlicesDataset(inputs,
column_names=["text"],
shuffle=False)
dataset = dataset.map(operations=text.SlidingWindow(2, 0),
input_columns=["text"])
for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
pass
assert False
except RuntimeError as e:
assert "SlidingWindosOp supports 1D Tensors only for now." in str(e)
def test_sliding_window_big_width():
inputs = [[1, 2, 3, 4, 5]]
expect = np.array([])
dataset = ds.NumpySlicesDataset(inputs,
column_names=["number"],
shuffle=False)
dataset = dataset.map(operations=text.SlidingWindow(30, 0),
input_columns=["number"])
for data in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
np.testing.assert_array_equal(data['number'], expect)
def test_sliding_window_number():
inputs = [1]
expect = np.array([[1]])
def gen(nums):
yield (np.array(nums), )
dataset = ds.GeneratorDataset(gen(inputs), column_names=["number"])
dataset = dataset.map(operations=text.SlidingWindow(1, -1),
input_columns=["number"])
for data in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
np.testing.assert_array_equal(data['number'], expect)
def test_sliding_window_string():
""" test sliding_window with string type"""
inputs = [["大", "家", "早", "上", "好"]]
expect = np.array([['大', '家'], ['家', '早'], ['早', '上'], ['上', '好']])
dataset = ds.NumpySlicesDataset(inputs,
column_names=["text"],
shuffle=False)
dataset = dataset.map(operations=text.SlidingWindow(2, 0),
input_columns=["text"])
result = []
for data in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
for i in range(data['text'].shape[0]):
result.append([])
for j in range(data['text'].shape[1]):
result[i].append(data['text'][i][j].decode('utf8'))
result = np.array(result)
np.testing.assert_array_equal(result, expect)
def test_sliding_window_callable():
"""
Test sliding window op is callable
"""
op = text.SlidingWindow(2, 0)
input1 = ["大", "家", "早", "上", "好"]
expect = np.array([['大', '家'], ['家', '早'], ['早', '上'], ['上', '好']])
result = op(input1)
assert np.array_equal(result, expect)
# test 2D input
input2 = [["大", "家", "早", "上", "好"]]
with pytest.raises(RuntimeError) as info:
_ = op(input2)
assert "SlidingWindow: SlidingWindow supports 1D input only for now." in str(
info.value)
# test input multiple tensors
with pytest.raises(RuntimeError) as info:
_ = op(input1, input1)
assert "The op is OneToOne, can only accept one tensor as input." in str(
info.value)