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simplified fix for pytorch MPS .type() issue

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Raf Gemmail
2023-05-07 16:10:33 +12:00
parent c95350f13f
commit 8660b7d7bb
1 changed files with 2 additions and 14 deletions
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16
bark/generation.py
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@@ -335,16 +335,6 @@ def preload_models(
_ = load_codec_model(use_gpu=codec_use_gpu, force_reload=force_reload) _ = load_codec_model(use_gpu=codec_use_gpu, force_reload=force_reload)
####
# Handle MPS immaturity in Pytorch
####
def _logits_to_device_float(logits):
if GLOBAL_ENABLE_MPS:
logits = logits.clone().detach().to("mps").to(torch.float)
else:
logits = logits.to(logits_device).type(logits_dtype)
return logits
#### ####
# Generation Functionality # Generation Functionality
#### ####
@@ -472,8 +462,7 @@ def generate_text_semantic(
sorted_indices_to_remove[0] = False sorted_indices_to_remove[0] = False
relevant_logits[sorted_indices[sorted_indices_to_remove]] = -np.inf relevant_logits[sorted_indices[sorted_indices_to_remove]] = -np.inf
relevant_logits = torch.from_numpy(relevant_logits) relevant_logits = torch.from_numpy(relevant_logits)
relevant_logits = _logits_to_device_float(relevant_logits) relevant_logits = relevant_logits.to(logits_device)
if top_k is not None: if top_k is not None:
v, _ = torch.topk(relevant_logits, min(top_k, relevant_logits.size(-1))) v, _ = torch.topk(relevant_logits, min(top_k, relevant_logits.size(-1)))
relevant_logits[relevant_logits < v[-1]] = -float("Inf") relevant_logits[relevant_logits < v[-1]] = -float("Inf")
@@ -669,8 +658,7 @@ def generate_coarse(
sorted_indices_to_remove[0] = False sorted_indices_to_remove[0] = False
relevant_logits[sorted_indices[sorted_indices_to_remove]] = -np.inf relevant_logits[sorted_indices[sorted_indices_to_remove]] = -np.inf
relevant_logits = torch.from_numpy(relevant_logits) relevant_logits = torch.from_numpy(relevant_logits)
relevant_logits = _logits_to_device_float(relevant_logits) relevant_logits = relevant_logits.to(logits_device)
if top_k is not None: if top_k is not None:
v, _ = torch.topk(relevant_logits, min(top_k, relevant_logits.size(-1))) v, _ = torch.topk(relevant_logits, min(top_k, relevant_logits.size(-1)))
relevant_logits[relevant_logits < v[-1]] = -float("Inf") relevant_logits[relevant_logits < v[-1]] = -float("Inf")