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mrq 2024-08-09 11:38:08 -05:00
parent c658a7b440
commit ed373957e2
2 changed files with 3 additions and 5 deletions
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6
vall_e/config.py
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@ -614,7 +614,7 @@ class Trainer:
amp: bool = False # automatic mixed precision amp: bool = False # automatic mixed precision
ddp: bool = False # torch's internal DDP, automatically set if local backend is used and multiple GPUs are requested ddp: bool = False # torch's internal DDP, automatically set if local backend is used and multiple GPUs are requested
scale_loss: bool = False # whether to perform loss scaling (for FP16 training) (it actually seems more harmful than not for this specific workload) #scale_loss: bool = False # whether to perform loss scaling (for FP16 training) (it actually seems more harmful than not for this specific workload)
load_webui: bool = False # not working, but loads the web UI to allow inferencing during training load_webui: bool = False # not working, but loads the web UI to allow inferencing during training
no_logger: bool = False # deprecated, but reroutes some logger calls to normal print statements for when logger broke because of BitNet no_logger: bool = False # deprecated, but reroutes some logger calls to normal print statements for when logger broke because of BitNet
@ -634,14 +634,12 @@ class Trainer:
return torch.float8_e4m3fn return torch.float8_e4m3fn
return torch.float32 return torch.float32
"""
@cached_property @cached_property
def scale_loss(self): def scale_loss(self):
# currently cannot feasibly apply loss scaling with DeepSpeed backend (it can handle it itself anyways) # currently cannot feasibly apply loss scaling with DeepSpeed backend (it can handle it itself anyways)
if self.backend != "local":
return False
return self.dtype == torch.float16 return self.dtype == torch.float16
""" """
"""
@dataclass() @dataclass()

2
vall_e/models/ar_nar.py
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@ -316,7 +316,7 @@ class AR_NAR(Base):
def example_usage(): def example_usage():
cfg.trainer.backend = "local" # cfg.trainer.backend = "local"
cfg.hyperparameters.gradient_accumulation_steps = 1 cfg.hyperparameters.gradient_accumulation_steps = 1
if cfg.audio_backend == "dac": if cfg.audio_backend == "dac":
cfg.sample_rate = 44_100 cfg.sample_rate = 44_100