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HowToSD-ComfyUI-Data-Analysis/modules/pytorch_wrapper/utils.py
T

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1.5 KiB
Python

import ast
from typing import Optional, Tuple, Union
import torch
DTYPE_MAPPING = {
"float32": torch.float32,
"float16": torch.float16,
"bfloat16": torch.bfloat16,
"float64": torch.float64,
"uint8": torch.uint8,
"int8": torch.int8,
"int16": torch.int16,
"int32": torch.int32,
"int64": torch.int64,
"bool": torch.bool
}
def str_to_dim(dim: str) -> Optional[Union[int, Tuple[int, ...]]]:
"""
Converts a string representation of a dimension into an integer or a tuple of integers.
Args:
dim (str): A string representing an integer or a tuple of integers.
Returns:
Optional[Union[int, Tuple[int, ...]]]:
- An integer if the input represents a single integer.
- A tuple of integers if the input represents a list or tuple.
- None if the input is empty.
Raises:
ValueError: If the parsed value is not an integer or a tuple of integers.
"""
if dim:
# Convert string to an integer, list, or tuple of integers
parsed_dim = ast.literal_eval(dim)
# Convert list to tuple
if isinstance(parsed_dim, list):
parsed_dim = tuple(parsed_dim)
# Ensure the parsed dim is valid
if not isinstance(parsed_dim, (int, tuple)) or (
isinstance(parsed_dim, tuple) and not all(isinstance(i, int) for i in parsed_dim)
):
raise ValueError(f"Invalid format for dim: {parsed_dim}. Must be an integer or a tuple of integers.")
return parsed_dim
return None