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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. | |
# Copyright 2022 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 | |
from argparse import ArgumentParser | |
from .. import __version__ as version | |
from ..utils import is_paddle_available, is_paddlenlp_available | |
from . import BasePPDiffusersCLICommand | |
def info_command_factory(_): | |
return EnvironmentCommand() | |
class EnvironmentCommand(BasePPDiffusersCLICommand): | |
def register_subcommand(parser: ArgumentParser): | |
download_parser = parser.add_parser("env") | |
download_parser.set_defaults(func=info_command_factory) | |
def run(self): | |
pd_version = "not installed" | |
pd_cuda_available = "NA" | |
if is_paddle_available(): | |
import paddle | |
pd_version = paddle.__version__ | |
pd_cuda_available = paddle.device.is_compiled_with_cuda() | |
paddlenlp_version = "not installed" | |
if is_paddlenlp_available: | |
import paddlenlp | |
paddlenlp_version = paddlenlp.__version__ | |
info = { | |
"`ppdiffusers` version": version, | |
"Platform": platform.platform(), | |
"Python version": platform.python_version(), | |
"Paddle version (GPU?)": f"{pd_version} ({pd_cuda_available})", | |
"PaddleNLP version": paddlenlp_version, | |
"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 | |
def format_dict(d): | |
return "\n".join([f"- {prop}: {val}" for prop, val in d.items()]) + "\n" | |