
from typing import TYPE_CHECKING

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


snake_case__  							=							{
    """configuration_markuplm""": ["""MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarkupLMConfig"""],
    """feature_extraction_markuplm""": ["""MarkupLMFeatureExtractor"""],
    """processing_markuplm""": ["""MarkupLMProcessor"""],
    """tokenization_markuplm""": ["""MarkupLMTokenizer"""],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case__  							=							["""MarkupLMTokenizerFast"""]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case__  							=							[
				    """MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """MarkupLMForQuestionAnswering""",
				    """MarkupLMForSequenceClassification""",
				    """MarkupLMForTokenClassification""",
				    """MarkupLMModel""",
				    """MarkupLMPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
				from .feature_extraction_markuplm import MarkupLMFeatureExtractor
				from .processing_markuplm import MarkupLMProcessor
				from .tokenization_markuplm import MarkupLMTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_markuplm_fast import MarkupLMTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_markuplm import (
								    MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MarkupLMForQuestionAnswering,
								    MarkupLMForSequenceClassification,
								    MarkupLMForTokenClassification,
								    MarkupLMModel,
								    MarkupLMPreTrainedModel,
								)


else:
				import sys

				snake_case__  							=							_LazyModule(__name__, globals()["""__file__"""], _import_structure)







snake_case__  							=							"""
# Diffusers installation
! pip install diffusers transformers datasets accelerate
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/diffusers.git
"""

snake_case__  							=							[{"""type""": """code""", """content""": INSTALL_CONTENT}]


