





UpperCamelCase__					  = """
# Transformers installation
! pip install transformers datasets
# 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/transformers.git
"""

UpperCamelCase__					  = [{"""type""": """code""", """content""": INSTALL_CONTENT}]
UpperCamelCase__					  = {
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__   : List[Any]					  = {"""configuration_sew""": ["""SEW_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWConfig"""]}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__   : List[str]					  = [
				    """SEW_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """SEWForCTC""",
				    """SEWForSequenceClassification""",
				    """SEWModel""",
				    """SEWPreTrainedModel""",
				]

if TYPE_CHECKING:
				from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_sew import (
								    SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SEWForCTC,
								    SEWForSequenceClassification,
								    SEWModel,
								    SEWPreTrainedModel,
								)


else:
				import sys

				UpperCamelCase__   : str					  = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


