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WIP: Float16 KV Cache in voicecraft.py #72

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WIP: Float16 KV Cache in voicecraft.py #72

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8 changes: 4 additions & 4 deletions models/voicecraft.py
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Original file line number Diff line number Diff line change
Expand Up @@ -678,7 +678,7 @@ def inference(
##################### silence repetition handling #####################
# prepare the cache placeholder
# n_layers, 2, bsz, num_heads, src_len, head_dim
past = torch.ones([self.args.num_decoder_layers, 2, x.shape[0]], device=x.device, dtype=torch.float32) if kvcache else None
past = torch.ones([self.args.num_decoder_layers, 2, x.shape[0]], device=x.device, dtype=torch.float16) if kvcache else None
# handle multi-span kv-cache
new_masked_span = False

Expand Down Expand Up @@ -978,7 +978,7 @@ def inference_tts(

# prepare the cache placeholder
# n_layers, 2, bsz, num_heads, src_len, head_dim
past = torch.ones([self.args.num_decoder_layers, 2, x.shape[0]], device=x.device, dtype=torch.float32) if kvcache else None
past = torch.ones([self.args.num_decoder_layers, 2, x.shape[0]], device=x.device, dtype=torch.float16) if kvcache else None
# logging.info(f"number of decoder layers: {self.args.num_decoder_layers}")
# logging.info(f"number of decoder layers: {self.args.num_decoder_layers}")
# logging.info(f"number of decoder layers: {self.args.num_decoder_layers}")
Expand Down Expand Up @@ -1228,7 +1228,7 @@ def inference_tts_batch(

# prepare the cache placeholder
# n_layers, 2, bsz, num_heads, src_len, head_dim
past = torch.ones([self.args.num_decoder_layers, 2, x.shape[0]], device=x.device, dtype=torch.float32) if kvcache else None
past = torch.ones([self.args.num_decoder_layers, 2, x.shape[0]], device=x.device, dtype=torch.float16) if kvcache else None
# logging.info(f"number of decoder layers: {self.args.num_decoder_layers}")
# logging.info(f"number of decoder layers: {self.args.num_decoder_layers}")
# logging.info(f"number of decoder layers: {self.args.num_decoder_layers}")
Expand Down Expand Up @@ -1403,4 +1403,4 @@ def sample_helper(n_eog, logits, codebook_eog, top_k, top_p, temperature, prev_t
res = res - int(self.args.n_special)
flatten_gen = flatten_gen - int(self.args.n_special)

return res, flatten_gen[0].unsqueeze(0)
return res, flatten_gen[0].unsqueeze(0)