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__init__.py
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# Copyright 2022 The HuggingFace Inc. 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 os
from packaging import version
from .. import __version__
from .constants import (
CONFIG_NAME,
DIFFUSERS_CACHE,
DIFFUSERS_DYNAMIC_MODULE_NAME,
FLAX_WEIGHTS_NAME,
HF_MODULES_CACHE,
HUGGINGFACE_CO_RESOLVE_ENDPOINT,
ONNX_EXTERNAL_WEIGHTS_NAME,
ONNX_WEIGHTS_NAME,
SAFETENSORS_WEIGHTS_NAME,
WEIGHTS_NAME,
)
from .deprecation_utils import deprecate
from .doc_utils import replace_example_docstring
from .dynamic_modules_utils import get_class_from_dynamic_module
from .hub_utils import HF_HUB_OFFLINE, http_user_agent
from .import_utils import (
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
USE_JAX,
USE_TF,
USE_TORCH,
DummyObject,
OptionalDependencyNotAvailable,
is_accelerate_available,
is_flax_available,
is_inflect_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_librosa_available,
is_omegaconf_available,
is_onnx_available,
is_safetensors_available,
is_scipy_available,
is_tf_available,
is_torch_available,
is_torch_version,
is_transformers_available,
is_transformers_version,
is_unidecode_available,
is_wandb_available,
is_xformers_available,
requires_backends,
)
from .logging import get_logger
from .outputs import BaseOutput
from .pil_utils import PIL_INTERPOLATION
from .torch_utils import randn_tensor
if is_torch_available():
from .testing_utils import (
floats_tensor,
load_hf_numpy,
load_image,
load_numpy,
nightly,
parse_flag_from_env,
print_tensor_test,
require_torch_gpu,
slow,
torch_all_close,
torch_device,
)
logger = get_logger(__name__)
def check_min_version(min_version):
if version.parse(__version__) < version.parse(min_version):
if "dev" in min_version:
error_message = (
"This example requires a source install from HuggingFace diffusers (see "
"`https://huggingface.co/docs/diffusers/installation#install-from-source`),"
)
else:
error_message = f"This example requires a minimum version of {min_version},"
error_message += f" but the version found is {__version__}.\n"
raise ImportError(error_message)