def __assert_wcqt_slicer(dataset, t_len, *slicer_args):
slicer = streams.wcqt_slices(dataset.to_df().iloc[0], t_len,
*slicer_args, random_seed=RANDOM_SEED)
for i in range(10):
data = next(slicer)['x_in']
assert len(data.shape) == 4
assert data.shape[1] > 1 and data.shape[1] < 10
assert data.shape[2] == t_len
def __assert_wcqt_slicer(dataset, t_len, *slicer_args):
slicer = streams.wcqt_slices(dataset.to_df().iloc[0],
t_len,
*slicer_args,
random_seed=RANDOM_SEED)
for i in range(10):
data = next(slicer)['x_in']
assert len(data.shape) == 4
assert data.shape[1] > 1 and data.shape[1] < 10
assert data.shape[2] == t_len
def __assert_wcqt_slicer_predict(dataset, t_len, *slicer_args):
slicer = streams.wcqt_slices(dataset.to_df().iloc[0], t_len,
*slicer_args, random_seed=RANDOM_SEED)
# The first one should work
data = next(slicer)['x_in']
assert len(data.shape) == 4
assert data.shape[1] > 1 and data.shape[1] < 10
assert data.shape[2] == t_len
# The second one should raise stopiteration
with pytest.raises(StopIteration):
data = next(slicer)['x_in']
def __assert_wcqt_slicer_predict(dataset, t_len, *slicer_args):
slicer = streams.wcqt_slices(dataset.to_df().iloc[0],
t_len,
*slicer_args,
random_seed=RANDOM_SEED)
# The first one should work
data = next(slicer)['x_in']
assert len(data.shape) == 4
assert data.shape[1] > 1 and data.shape[1] < 10
assert data.shape[2] == t_len
# The second one should raise stopiteration
with pytest.raises(StopIteration):
data = next(slicer)['x_in']
def test_wcqt_slicer_with_data_less_tlen(generated_data):
df, t_len = generated_data
slicer = streams.wcqt_slices(df.iloc[0], t_len)
batch = next(slicer)
assert batch['x_in'].shape[2] == t_len
def test_wcqt_slicer_with_data_less_tlen(generated_data):
df, t_len = generated_data
slicer = streams.wcqt_slices(df.iloc[0], t_len)
batch = next(slicer)
assert batch['x_in'].shape[2] == t_len
