"""
    #################################################################################################################################################################################################
    # This code library is an adaptation of the original Transformers and was designed, developed and programmed by Sapiens Technology®.                                                            #
    # Any alteration and/or disclosure of this code without prior authorization is strictly prohibited and is subject to legal action that will be forwarded by the Sapiens Technology® legal team. #
    # This set of algorithms aims to download, train, fine-tune and/or infer large language models from various sources and slopes.                                                                 #
    #################################################################################################################################################################################################
"""
from typing import TYPE_CHECKING
from ...utils import (OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available)
_import_structure = {'configuration_seamless_m4t': ['SeamlessM4TConfig'], 'feature_extraction_seamless_m4t': ['SeamlessM4TFeatureExtractor'], 'processing_seamless_m4t': ['SeamlessM4TProcessor']}
try:
    if not is_sentencepiece_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else: _import_structure["tokenization_seamless_m4t"] = ["SeamlessM4TTokenizer"]
try:
    if not is_tokenizers_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else: _import_structure["tokenization_seamless_m4t_fast"] = ["SeamlessM4TTokenizerFast"]
try:
    if not is_torch_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else: _import_structure["modeling_seamless_m4t"] = ["SeamlessM4TForTextToSpeech", "SeamlessM4TForSpeechToSpeech", "SeamlessM4TForTextToText", "SeamlessM4TForSpeechToText",
"SeamlessM4TModel", "SeamlessM4TPreTrainedModel", "SeamlessM4TCodeHifiGan", "SeamlessM4THifiGan", "SeamlessM4TTextToUnitForConditionalGeneration", "SeamlessM4TTextToUnitModel"]
if TYPE_CHECKING:
    from .configuration_seamless_m4t import SeamlessM4TConfig
    from .feature_extraction_seamless_m4t import SeamlessM4TFeatureExtractor
    from .processing_seamless_m4t import SeamlessM4TProcessor
    try:
        if not is_sentencepiece_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else: from .tokenization_seamless_m4t import SeamlessM4TTokenizer
    try:
        if not is_tokenizers_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else: from .tokenization_seamless_m4t_fast import SeamlessM4TTokenizerFast
    try:
        if not is_torch_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else: from .modeling_seamless_m4t import (SeamlessM4TCodeHifiGan, SeamlessM4TForSpeechToSpeech, SeamlessM4TForSpeechToText, SeamlessM4TForTextToSpeech,
    SeamlessM4TForTextToText, SeamlessM4THifiGan, SeamlessM4TModel, SeamlessM4TPreTrainedModel, SeamlessM4TTextToUnitForConditionalGeneration, SeamlessM4TTextToUnitModel)
else:
    import sys
    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
"""
    #################################################################################################################################################################################################
    # This code library is an adaptation of the original Transformers and was designed, developed and programmed by Sapiens Technology®.                                                            #
    # Any alteration and/or disclosure of this code without prior authorization is strictly prohibited and is subject to legal action that will be forwarded by the Sapiens Technology® legal team. #
    # This set of algorithms aims to download, train, fine-tune and/or infer large language models from various sources and slopes.                                                                 #
    #################################################################################################################################################################################################
"""
