nvidia-nemo--speech/nemo/utils/dtype.py

# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES.  All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import Dict, Union

import torch

_str_to_dtype: Dict[str, torch.dtype] = dict(
    float32=torch.float32,
    float=torch.float32,
    float64=torch.float64,
    double=torch.float64,
    float16=torch.float16,
    half=torch.float16,
    bfloat16=torch.bfloat16,
    bf16=torch.bfloat16,
    uint8=torch.uint8,
    byte=torch.uint8,
    int8=torch.int8,
    char=torch.int8,
    int16=torch.int16,
    short=torch.int16,
    int32=torch.int32,
    int=torch.int32,
    int64=torch.int64,
    long=torch.int64,
    bool=torch.bool,
)


def str_to_dtype(dtype: Union[str, torch.dtype]) -> torch.dtype:
    """Convert a data type name to a PyTorch data type"""
    if isinstance(dtype, torch.dtype):
        return dtype
    name = str(dtype).strip().lower()
    if name.startswith("torch."):
        name = name.replace("torch.", "", 1)
    if name.startswith("fp"):
        name = name.replace("fp", "float", 1)
    if name not in _str_to_dtype:
        raise ValueError(f"Unrecognized dtype ({name})")
    return _str_to_dtype[name]