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env.py
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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.
import platform
import subprocess
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_bitsandbytes_available,
is_flax_available,
is_google_colab,
is_peft_available,
is_safetensors_available,
is_torch_available,
is_transformers_available,
is_xformers_available,
)
from . import BaseDiffusersCLICommand
def info_command_factory(_):
return EnvironmentCommand()
class EnvironmentCommand(BaseDiffusersCLICommand):
@staticmethod
def register_subcommand(parser: ArgumentParser) -> None:
download_parser = parser.add_parser("env")
download_parser.set_defaults(func=info_command_factory)
def run(self) -> dict:
hub_version = huggingface_hub.__version__
safetensors_version = "not installed"
if is_safetensors_available():
import safetensors
safetensors_version = safetensors.__version__
pt_version = "not installed"
pt_cuda_available = "NA"
if is_torch_available():
import torch
pt_version = torch.__version__
pt_cuda_available = torch.cuda.is_available()
flax_version = "not installed"
jax_version = "not installed"
jaxlib_version = "not installed"
jax_backend = "NA"
if is_flax_available():
import flax
import jax
import jaxlib
flax_version = flax.__version__
jax_version = jax.__version__
jaxlib_version = jaxlib.__version__
jax_backend = jax.lib.xla_bridge.get_backend().platform
transformers_version = "not installed"
if is_transformers_available():
import transformers
transformers_version = transformers.__version__
accelerate_version = "not installed"
if is_accelerate_available():
import accelerate
accelerate_version = accelerate.__version__
peft_version = "not installed"
if is_peft_available():
import peft
peft_version = peft.__version__
bitsandbytes_version = "not installed"
if is_bitsandbytes_available():
import bitsandbytes
bitsandbytes_version = bitsandbytes.__version__
xformers_version = "not installed"
if is_xformers_available():
import xformers
xformers_version = xformers.__version__
platform_info = platform.platform()
is_google_colab_str = "Yes" if is_google_colab() else "No"
accelerator = "NA"
if platform.system() in {"Linux", "Windows"}:
try:
sp = subprocess.Popen(
["nvidia-smi", "--query-gpu=gpu_name,memory.total", "--format=csv,noheader"],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
out_str, _ = sp.communicate()
out_str = out_str.decode("utf-8")
if len(out_str) > 0:
accelerator = out_str.strip()
except FileNotFoundError:
pass
elif platform.system() == "Darwin": # Mac OS
try:
sp = subprocess.Popen(
["system_profiler", "SPDisplaysDataType"],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
out_str, _ = sp.communicate()
out_str = out_str.decode("utf-8")
start = out_str.find("Chipset Model:")
if start != -1:
start += len("Chipset Model:")
end = out_str.find("\n", start)
accelerator = out_str[start:end].strip()
start = out_str.find("VRAM (Total):")
if start != -1:
start += len("VRAM (Total):")
end = out_str.find("\n", start)
accelerator += " VRAM: " + out_str[start:end].strip()
except FileNotFoundError:
pass
else:
print("It seems you are running an unusual OS. Could you fill in the accelerator manually?")
info = {
"🤗 Diffusers version": version,
"Platform": platform_info,
"Running on Google Colab?": is_google_colab_str,
"Python version": platform.python_version(),
"PyTorch version (GPU?)": f"{pt_version} ({pt_cuda_available})",
"Flax version (CPU?/GPU?/TPU?)": f"{flax_version} ({jax_backend})",
"Jax version": jax_version,
"JaxLib version": jaxlib_version,
"Huggingface_hub version": hub_version,
"Transformers version": transformers_version,
"Accelerate version": accelerate_version,
"PEFT version": peft_version,
"Bitsandbytes version": bitsandbytes_version,
"Safetensors version": safetensors_version,
"xFormers version": xformers_version,
"Accelerator": accelerator,
"Using GPU in script?": "<fill in>",
"Using distributed or parallel set-up in script?": "<fill in>",
}
print("\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n")
print(self.format_dict(info))
return info
@staticmethod
def format_dict(d: dict) -> str:
return "\n".join([f"- {prop}: {val}" for prop, val in d.items()]) + "\n"