Making large AI models cheaper, faster and more accessible
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from contextlib import contextmanager
import torch
import torch.nn as nn
@contextmanager
def low_precision_init(target_dtype: torch.dtype = torch.float16):
dtype = torch.get_default_dtype()
try:
torch.set_default_dtype(target_dtype)
yield
finally:
torch.set_default_dtype(dtype)
def get_model_numel(model: nn.Module) -> int:
return sum(p.numel() for p in model.parameters())
def format_numel_str(numel: int) -> str:
B = 1024**3
M = 1024**2
K = 1024
if numel >= B:
return f"{numel / B:.2f} B"
elif numel >= M:
return f"{numel / M:.2f} M"
elif numel >= K:
return f"{numel / K:.2f} K"
else:
return f"{numel}"