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# Copyright 2025 The HuggingFace Team. 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.
"""Contains commands to print information about the environment and version.
Usage:
transformers env
transformers version
"""
import contextlib
import io
import os
import platform
from typing import Annotated
import huggingface_hub
import typer
from .. import __version__
from ..integrations.deepspeed import is_deepspeed_available
from ..utils import (
is_accelerate_available,
is_torch_available,
is_torch_hpu_available,
is_torch_npu_available,
is_torch_xpu_available,
)
def env(
accelerate_config_file: Annotated[
str | None,
typer.Argument(help="The accelerate config file to use for the default values in the launching script."),
] = None,
) -> None:
"""Print information about the environment."""
import safetensors
safetensors_version = safetensors.__version__
accelerate_version = "not installed"
accelerate_config = accelerate_config_str = "not found"
if is_accelerate_available():
import accelerate
from accelerate.commands.config import default_config_file, load_config_from_file
accelerate_version = accelerate.__version__
# Get the default from the config file.
if accelerate_config_file is not None or os.path.isfile(default_config_file):
accelerate_config = load_config_from_file(accelerate_config_file).to_dict()
accelerate_config_str = (
"\n".join([f"\t- {prop}: {val}" for prop, val in accelerate_config.items()])
if isinstance(accelerate_config, dict)
else f"\t{accelerate_config}"
)
pt_version = "not installed"
pt_cuda_available = "NA"
pt_accelerator = "NA"
if is_torch_available():
import torch
pt_version = torch.__version__
pt_cuda_available = torch.cuda.is_available()
pt_xpu_available = is_torch_xpu_available()
pt_npu_available = is_torch_npu_available()
pt_hpu_available = is_torch_hpu_available()
if pt_cuda_available:
pt_accelerator = "CUDA"
elif pt_xpu_available:
pt_accelerator = "XPU"
elif pt_npu_available:
pt_accelerator = "NPU"
elif pt_hpu_available:
pt_accelerator = "HPU"
deepspeed_version = "not installed"
if is_deepspeed_available():
# Redirect command line output to silence deepspeed import output.
with contextlib.redirect_stdout(io.StringIO()):
import deepspeed
deepspeed_version = deepspeed.__version__
info = {
"`transformers` version": __version__,
"Platform": platform.platform(),
"Python version": platform.python_version(),
"Huggingface_hub version": huggingface_hub.__version__,
"Safetensors version": f"{safetensors_version}",
"Accelerate version": f"{accelerate_version}",
"Accelerate config": f"{accelerate_config_str}",
"DeepSpeed version": f"{deepspeed_version}",
"PyTorch version (accelerator?)": f"{pt_version} ({pt_accelerator})",
"Using distributed or parallel set-up in script?": "<fill in>",
}
if is_torch_available():
if pt_cuda_available:
info["Using GPU in script?"] = "<fill in>"
info["GPU type"] = torch.cuda.get_device_name()
elif pt_xpu_available:
info["Using XPU in script?"] = "<fill in>"
info["XPU type"] = torch.xpu.get_device_name()
elif pt_hpu_available:
info["Using HPU in script?"] = "<fill in>"
info["HPU type"] = torch.hpu.get_device_name()
elif pt_npu_available:
info["Using NPU in script?"] = "<fill in>"
info["NPU type"] = torch.npu.get_device_name()
info["CANN version"] = torch.version.cann
print("\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n")
print(_format_dict(info))
return info
def version() -> None:
"""Print CLI version."""
print(__version__)
def _format_dict(d: dict) -> str:
return "\n".join([f"- {prop}: {val}" for prop, val in d.items()]) + "\n"