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186aa49 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 | # Copyright 2026 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 importlib.metadata
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_gguf_available,
is_google_colab,
is_nvidia_modelopt_available,
is_optimum_quanto_available,
is_peft_available,
is_safetensors_available,
is_torch_available,
is_torchao_available,
is_transformers_available,
is_xformers_available,
)
from . import BaseDiffusersCLICommand
# (display name, availability_fn, pypi distribution name for importlib.metadata.version)
_QUANTIZATION_BACKENDS = (
("bitsandbytes", is_bitsandbytes_available, "bitsandbytes"),
("gguf", is_gguf_available, "gguf"),
("optimum-quanto", is_optimum_quanto_available, "optimum-quanto"),
("torchao", is_torchao_available, "torchao"),
("nvidia-modelopt", is_nvidia_modelopt_available, "nvidia-modelopt"),
)
def info_command_factory(_):
return EnvironmentCommand()
class EnvironmentCommand(BaseDiffusersCLICommand):
@staticmethod
def register_subcommand(parser: ArgumentParser) -> None:
download_parser = parser.add_parser(
"env",
help="Print versions of diffusers and its dependencies (for bug reports).",
usage="\n diffusers-cli env",
)
download_parser._optionals.title = "Options"
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()
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__
quantization_versions = {}
for backend_name, is_available_fn, dist_name in _QUANTIZATION_BACKENDS:
if not is_available_fn():
continue
try:
quantization_versions[backend_name] = importlib.metadata.version(dist_name)
except importlib.metadata.PackageNotFoundError:
quantization_versions[backend_name] = "N/A"
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})",
"Huggingface_hub version": hub_version,
"Transformers version": transformers_version,
"Accelerate version": accelerate_version,
"PEFT version": peft_version,
**{f"{name} version": ver for name, ver in quantization_versions.items()},
"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"
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