"""
    #################################################################################################################################################################################################
    # 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_torch_available
_import_structure = {'aqlm': ['replace_with_aqlm_linear'], 'awq': ['fuse_awq_modules', 'post_init_awq_exllama_modules', 'replace_quantization_scales', 'replace_with_awq_linear'],
'sapiens_machine': ['dequantize_and_replace', 'get_keys_to_not_convert', 'replace_8bit_linear', 'replace_with_sapiens_linear', 'set_module_8bit_tensor_to_device', 'set_module_quantized_tensor_to_device', 'validate_sapiens_backend_availability'],
'deepspeed': ['HfDeepSpeedConfig', 'HfTrainerDeepSpeedConfig', 'deepspeed_config', 'deepspeed_init', 'deepspeed_load_checkpoint', 'deepspeed_optim_sched', 'is_deepspeed_available', 'is_deepspeed_zero3_enabled', 'set_hf_deepspeed_config', 'unset_hf_deepspeed_config'],
'eetq': ['replace_with_eetq_linear'], 'fbgemm_fp8': ['FbgemmFp8Linear', 'replace_with_fbgemm_fp8_linear'], 'ggml': ['GGUF_CONFIG_MAPPING', 'GGUF_TENSOR_MAPPING', 'GGUF_TOKENIZER_MAPPING', '_gguf_parse_value', 'load_dequant_gguf_tensor', 'load_gguf'],
'hqq': ['prepare_for_hqq_linear'], 'integration_utils': ['INTEGRATION_TO_CALLBACK', 'AzureMLCallback', 'ClearMLCallback', 'CodeCarbonCallback', 'CometCallback', 'DagsHubCallback', 'DVCLiveCallback', 'FlyteCallback', 'MLflowCallback', 'NeptuneCallback',
'NeptuneMissingConfiguration', 'TensorBoardCallback', 'WandbCallback', 'get_available_reporting_integrations', 'get_reporting_integration_callbacks', 'hp_params', 'is_azureml_available', 'is_clearml_available', 'is_codecarbon_available', 'is_comet_available',
'is_dagshub_available', 'is_dvclive_available', 'is_flyte_deck_standard_available', 'is_flytekit_available', 'is_mlflow_available', 'is_neptune_available', 'is_optuna_available', 'is_ray_available', 'is_ray_tune_available', 'is_sigopt_available', 'is_tensorboard_available',
'is_wandb_available', 'rewrite_logs', 'run_hp_search_optuna', 'run_hp_search_ray', 'run_hp_search_sigopt', 'run_hp_search_wandb'], 'peft': ['PeftAdapterMixin'], 'quanto': ['replace_with_quanto_layers']}
try:
    if not is_torch_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else: _import_structure["executorch"] = ["TorchExportableModuleWithStaticCache", "convert_and_export_with_cache"]
if TYPE_CHECKING:
    from .aqlm import replace_with_aqlm_linear
    from .awq import (fuse_awq_modules, post_init_awq_exllama_modules, replace_quantization_scales, replace_with_awq_linear)
    from .sapiens_machine import (dequantize_and_replace, get_keys_to_not_convert, replace_8bit_linear, replace_with_sapiens_linear, set_module_8bit_tensor_to_device, set_module_quantized_tensor_to_device, validate_sapiens_backend_availability)
    from .deepspeed import (HfDeepSpeedConfig, HfTrainerDeepSpeedConfig, deepspeed_config, deepspeed_init, deepspeed_load_checkpoint, deepspeed_optim_sched, is_deepspeed_available, is_deepspeed_zero3_enabled, set_hf_deepspeed_config, unset_hf_deepspeed_config)
    from .eetq import replace_with_eetq_linear
    from .fbgemm_fp8 import FbgemmFp8Linear, replace_with_fbgemm_fp8_linear
    from .ggml import (GGUF_CONFIG_MAPPING, GGUF_TENSOR_MAPPING, GGUF_TOKENIZER_MAPPING, _gguf_parse_value, load_dequant_gguf_tensor, load_gguf)
    from .hqq import prepare_for_hqq_linear
    from .integration_utils import (INTEGRATION_TO_CALLBACK, AzureMLCallback, ClearMLCallback, CodeCarbonCallback, CometCallback, DagsHubCallback, DVCLiveCallback, FlyteCallback, MLflowCallback,
    NeptuneCallback, NeptuneMissingConfiguration, TensorBoardCallback, WandbCallback, get_available_reporting_integrations, get_reporting_integration_callbacks, hp_params, is_azureml_available,
    is_clearml_available, is_codecarbon_available, is_comet_available, is_dagshub_available, is_dvclive_available, is_flyte_deck_standard_available, is_flytekit_available, is_mlflow_available,
    is_neptune_available, is_optuna_available, is_ray_available, is_ray_tune_available, is_sigopt_available, is_tensorboard_available, is_wandb_available, rewrite_logs, run_hp_search_optuna,
    run_hp_search_ray, run_hp_search_sigopt, run_hp_search_wandb)
    from .peft import PeftAdapterMixin
    from .quanto import replace_with_quanto_layers
    try:
        if not is_torch_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else: from .executorch import TorchExportableModuleWithStaticCache, convert_and_export_with_cache
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.                                                                 #
    #################################################################################################################################################################################################
"""
