deviandice/DL-Art-School
1
0
Fork 0
forked from mrq/DL-Art-School
Code Issues Pull Requests Packages Projects Releases Wiki Activity

.

Browse Source
This commit is contained in:
James Betker 2022-05-23 08:47:15 -06:00
parent 40f844657b
commit 2270c89fdc
1 changed files with 3 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
codes/models/audio/mel2vec.py
View File

@ -633,6 +633,7 @@ class ContrastiveTrainingWrapper(nn.Module):
def forward(self, mel, inp_lengths=None):
mel = mel[:, :, :-1] # The MEL computation always pads with 1, throwing off optimal tensor math.
features_shape = (mel.shape[0], mel.shape[-1]//self.m2v.dim_reduction_mult)
# Frequency masking
freq_mask_width = int(random.random() * self.freq_mask_percent * mel.shape[1])
@ -641,13 +642,12 @@ class ContrastiveTrainingWrapper(nn.Module):
mel[:, freq_start:freq_start+freq_mask_width] = 0
# Build input masks from inp_lengths if possible.
attention_mask = torch.ones_like(mel).long()
attention_mask = torch.ones(features_shape, device=mel.device, dtype=torch.long)
if inp_lengths is not None:
inp_lengths = inp_lengths // self.inp_length_factor
inp_lengths = inp_lengths // (self.inp_length_factor*self.m2v.dim_reduction_mult)
for i, l in enumerate(inp_lengths):
attention_mask[i, l:] = 0
features_shape = (mel.shape[0], mel.shape[-1]//self.m2v.dim_reduction_mult)
mask_time_indices = _compute_mask_indices(features_shape, self.mask_time_prob, self.mask_time_length, attention_mask=attention_mask)
sampled_negative_indices = torch.tensor(_sample_negative_indices(features_shape, self.num_negatives, mask_time_indices=mask_time_indices), device=mel.device)
mask_time_indices = torch.tensor(mask_time_indices, device=mel.device)