team-10/venv/Lib/site-packages/transformers/integrations/__init__.py
2025-08-02 02:00:33 +02:00

293 lines
8.9 KiB
Python

# Copyright 2023 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_torch_available, is_torch_greater_or_equal
_import_structure = {
"aqlm": ["replace_with_aqlm_linear"],
"awq": [
"fuse_awq_modules",
"post_init_awq_exllama_modules",
"post_init_awq_ipex_modules",
"replace_quantization_scales",
"replace_with_awq_linear",
],
"bitnet": [
"BitLinear",
"pack_weights",
"replace_with_bitnet_linear",
"unpack_weights",
],
"bitsandbytes": [
"dequantize_and_replace",
"get_keys_to_not_convert",
"replace_8bit_linear",
"replace_with_bnb_linear",
"set_module_8bit_tensor_to_device",
"set_module_quantized_tensor_to_device",
"validate_bnb_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", "FbgemmFp8Llama4TextExperts", "replace_with_fbgemm_fp8_linear"],
"finegrained_fp8": ["FP8Linear", "replace_with_fp8_linear"],
"fsdp": ["is_fsdp_managed_module"],
"ggml": [
"GGUF_CONFIG_MAPPING",
"GGUF_TOKENIZER_MAPPING",
"_gguf_parse_value",
"load_dequant_gguf_tensor",
"load_gguf",
],
"higgs": [
"HiggsLinear",
"dequantize_higgs",
"quantize_with_higgs",
"replace_with_higgs_linear",
],
"hqq": ["prepare_for_hqq_linear"],
"hub_kernels": [
"LayerRepository",
"register_kernel_mapping",
"replace_kernel_forward_from_hub",
"use_kernel_forward_from_hub",
],
"integration_utils": [
"INTEGRATION_TO_CALLBACK",
"AzureMLCallback",
"ClearMLCallback",
"CodeCarbonCallback",
"CometCallback",
"DagsHubCallback",
"DVCLiveCallback",
"FlyteCallback",
"MLflowCallback",
"NeptuneCallback",
"NeptuneMissingConfiguration",
"SwanLabCallback",
"TensorBoardCallback",
"TrackioCallback",
"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_swanlab_available",
"is_tensorboard_available",
"is_trackio_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"],
"spqr": ["replace_with_spqr_linear"],
"vptq": ["replace_with_vptq_linear"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["executorch"] = [
"TorchExportableModuleWithStaticCache",
"convert_and_export_with_cache",
]
try:
if not is_torch_greater_or_equal("2.3"):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["tensor_parallel"] = [
"shard_and_distribute_module",
"ALL_PARALLEL_STYLES",
"translate_to_torch_parallel_style",
]
try:
if not is_torch_greater_or_equal("2.5"):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["flex_attention"] = [
"make_flex_block_causal_mask",
]
if TYPE_CHECKING:
from .aqlm import replace_with_aqlm_linear
from .awq import (
fuse_awq_modules,
post_init_awq_exllama_modules,
post_init_awq_ipex_modules,
replace_quantization_scales,
replace_with_awq_linear,
)
from .bitnet import (
BitLinear,
pack_weights,
replace_with_bitnet_linear,
unpack_weights,
)
from .bitsandbytes import (
dequantize_and_replace,
get_keys_to_not_convert,
replace_8bit_linear,
replace_with_bnb_linear,
set_module_8bit_tensor_to_device,
set_module_quantized_tensor_to_device,
validate_bnb_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, FbgemmFp8Llama4TextExperts, replace_with_fbgemm_fp8_linear
from .finegrained_fp8 import FP8Linear, replace_with_fp8_linear
from .fsdp import is_fsdp_managed_module
from .ggml import (
GGUF_CONFIG_MAPPING,
GGUF_TOKENIZER_MAPPING,
_gguf_parse_value,
load_dequant_gguf_tensor,
load_gguf,
)
from .higgs import HiggsLinear, dequantize_higgs, quantize_with_higgs, replace_with_higgs_linear
from .hqq import prepare_for_hqq_linear
from .hub_kernels import (
LayerRepository,
register_kernel_mapping,
replace_kernel_forward_from_hub,
use_kernel_forward_from_hub,
)
from .integration_utils import (
INTEGRATION_TO_CALLBACK,
AzureMLCallback,
ClearMLCallback,
CodeCarbonCallback,
CometCallback,
DagsHubCallback,
DVCLiveCallback,
FlyteCallback,
MLflowCallback,
NeptuneCallback,
NeptuneMissingConfiguration,
SwanLabCallback,
TensorBoardCallback,
TrackioCallback,
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_swanlab_available,
is_tensorboard_available,
is_trackio_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
from .spqr import replace_with_spqr_linear
from .vptq import replace_with_vptq_linear
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .executorch import TorchExportableModuleWithStaticCache, convert_and_export_with_cache
try:
if not is_torch_greater_or_equal("2.3"):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .tensor_parallel import (
ALL_PARALLEL_STYLES,
shard_and_distribute_module,
translate_to_torch_parallel_style,
)
try:
if not is_torch_greater_or_equal("2.5"):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .flex_attention import make_flex_block_causal_mask
else:
import sys
sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)