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Grounded-Segment-Anything / transformers_4_35_0 /models /biogpt /__init__.py

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	# 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.
	from typing import TYPE_CHECKING

	from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


	_import_structure = {
	"configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
	"tokenization_biogpt": ["BioGptTokenizer"],
	}

	try:
	if not is_torch_available():
	raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
	pass
	else:
	_import_structure["modeling_biogpt"] = [
	"BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
	"BioGptForCausalLM",
	"BioGptForTokenClassification",
	"BioGptForSequenceClassification",
	"BioGptModel",
	"BioGptPreTrainedModel",
	]


	if TYPE_CHECKING:
	from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
	from .tokenization_biogpt import BioGptTokenizer

	try:
	if not is_torch_available():
	raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
	pass
	else:
	from .modeling_biogpt import (
	BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
	BioGptForCausalLM,
	BioGptForSequenceClassification,
	BioGptForTokenClassification,
	BioGptModel,
	BioGptPreTrainedModel,
	)


	else:
	import sys

	sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)