Spaces:
Running
on
Zero
Running
on
Zero
remove unnecessary code
Browse files
cosyvoice/flow/flow.py
CHANGED
@@ -113,7 +113,7 @@ class MaskedDiffWithXvec(torch.nn.Module):
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# concat text and prompt_text
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token_len1, token_len2 = prompt_token.shape[1], token.shape[1]
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token, token_len = torch.concat([prompt_token, token], dim=1), prompt_token_len + token_len
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-
mask = (~make_pad_mask(token_len)).
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token = self.input_embedding(torch.clamp(token, min=0)) * mask
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# text encode
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# concat text and prompt_text
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token_len1, token_len2 = prompt_token.shape[1], token.shape[1]
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token, token_len = torch.concat([prompt_token, token], dim=1), prompt_token_len + token_len
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+
mask = (~make_pad_mask(token_len)).unsqueeze(-1).to(embedding)
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token = self.input_embedding(torch.clamp(token, min=0)) * mask
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# text encode
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cosyvoice/flow/flow_matching.py
CHANGED
@@ -14,8 +14,6 @@
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import torch
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import torch.nn.functional as F
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from matcha.models.components.flow_matching import BASECFM
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import onnxruntime as ort
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import numpy as np
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class ConditionalCFM(BASECFM):
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def __init__(self, in_channels, cfm_params, n_spks=1, spk_emb_dim=64, estimator: torch.nn.Module = None):
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import torch
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import torch.nn.functional as F
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from matcha.models.components.flow_matching import BASECFM
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class ConditionalCFM(BASECFM):
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def __init__(self, in_channels, cfm_params, n_spks=1, spk_emb_dim=64, estimator: torch.nn.Module = None):
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