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import torch as T
from TTS.tts.utils.helpers import average_over_durations, generate_path, rand_segments, segment, sequence_mask
def average_over_durations_test(): # pylint: disable=no-self-use
pitch = T.rand(1, 1, 128)
durations = T.randint(1, 5, (1, 21))
coeff = 128.0 / durations.sum()
durations = T.floor(durations * coeff)
diff = 128.0 - durations.sum()
durations[0, -1] += diff
durations = durations.long()
pitch_avg = average_over_durations(pitch, durations)
index = 0
for idx, dur in enumerate(durations[0]):
assert abs(pitch_avg[0, 0, idx] - pitch[0, 0, index : index + dur.item()].mean()) < 1e-5
index += dur
def seqeunce_mask_test():
lengths = T.randint(10, 15, (8,))
mask = sequence_mask(lengths)
for i in range(8):
l = lengths[i].item()
assert mask[i, :l].sum() == l
assert mask[i, l:].sum() == 0
def segment_test():
x = T.range(0, 11)
x = x.repeat(8, 1).unsqueeze(1)
segment_ids = T.randint(0, 7, (8,))
segments = segment(x, segment_ids, segment_size=4)
for idx, start_indx in enumerate(segment_ids):
assert x[idx, :, start_indx : start_indx + 4].sum() == segments[idx, :, :].sum()
try:
segments = segment(x, segment_ids, segment_size=10)
raise Exception("Should have failed")
except:
pass
segments = segment(x, segment_ids, segment_size=10, pad_short=True)
for idx, start_indx in enumerate(segment_ids):
assert x[idx, :, start_indx : start_indx + 10].sum() == segments[idx, :, :].sum()
def rand_segments_test():
x = T.rand(2, 3, 4)
x_lens = T.randint(3, 4, (2,))
segments, seg_idxs = rand_segments(x, x_lens, segment_size=3)
assert segments.shape == (2, 3, 3)
assert all(seg_idxs >= 0), seg_idxs
try:
segments, _ = rand_segments(x, x_lens, segment_size=5)
raise Exception("Should have failed")
except:
pass
x_lens_back = x_lens.clone()
segments, seg_idxs = rand_segments(x, x_lens.clone(), segment_size=5, pad_short=True, let_short_samples=True)
assert segments.shape == (2, 3, 5)
assert all(seg_idxs >= 0), seg_idxs
assert all(x_lens_back == x_lens)
def generate_path_test():
durations = T.randint(1, 4, (10, 21))
x_length = T.randint(18, 22, (10,))
x_mask = sequence_mask(x_length).unsqueeze(1).long()
durations = durations * x_mask.squeeze(1)
y_length = durations.sum(1)
y_mask = sequence_mask(y_length).unsqueeze(1).long()
attn_mask = (T.unsqueeze(x_mask, -1) * T.unsqueeze(y_mask, 2)).squeeze(1).long()
print(attn_mask.shape)
path = generate_path(durations, attn_mask)
assert path.shape == (10, 21, durations.sum(1).max().item())
for b in range(durations.shape[0]):
current_idx = 0
for t in range(durations.shape[1]):
assert all(path[b, t, current_idx : current_idx + durations[b, t].item()] == 1.0)
assert all(path[b, t, :current_idx] == 0.0)
assert all(path[b, t, current_idx + durations[b, t].item() :] == 0.0)
current_idx += durations[b, t].item()
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