mirror of
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64 lines
2.3 KiB
Python
64 lines
2.3 KiB
Python
from typing import Any, Dict, Tuple
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from openllm_core.utils import (
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DEBUG as DEBUG,
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DEBUG_ENV_VAR as DEBUG_ENV_VAR,
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DEV_DEBUG_VAR as DEV_DEBUG_VAR,
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ENV_VARS_TRUE_VALUES as ENV_VARS_TRUE_VALUES,
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MYPY as MYPY,
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OPTIONAL_DEPENDENCIES as OPTIONAL_DEPENDENCIES,
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QUIET_ENV_VAR as QUIET_ENV_VAR,
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SHOW_CODEGEN as SHOW_CODEGEN,
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LazyLoader as LazyLoader,
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LazyModule as LazyModule,
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ReprMixin as ReprMixin,
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VersionInfo as VersionInfo,
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analytics as analytics,
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calc_dir_size as calc_dir_size,
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check_bool_env as check_bool_env,
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codegen as codegen,
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configure_logging as configure_logging,
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dantic as dantic,
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field_env_key as field_env_key,
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first_not_none as first_not_none,
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flatten_attrs as flatten_attrs,
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gen_random_uuid as gen_random_uuid,
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generate_context as generate_context,
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generate_hash_from_file as generate_hash_from_file,
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get_debug_mode as get_debug_mode,
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get_disable_warnings as get_disable_warnings,
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get_quiet_mode as get_quiet_mode,
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getenv as getenv,
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in_notebook as in_notebook,
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is_autoawq_available as is_autoawq_available,
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is_autogptq_available as is_autogptq_available,
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is_bentoml_available as is_bentoml_available,
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is_bitsandbytes_available as is_bitsandbytes_available,
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is_ctranslate_available as is_ctranslate_available,
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is_flash_attn_2_available as is_flash_attn_2_available,
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is_grpc_available as is_grpc_available,
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is_jupyter_available as is_jupyter_available,
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is_jupytext_available as is_jupytext_available,
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is_notebook_available as is_notebook_available,
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is_peft_available as is_peft_available,
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is_torch_available as is_torch_available,
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is_triton_available as is_triton_available,
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is_transformers_available as is_transformers_available,
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is_vllm_available as is_vllm_available,
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lenient_issubclass as lenient_issubclass,
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resolve_filepath as resolve_filepath,
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resolve_user_filepath as resolve_user_filepath,
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serde as serde,
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set_debug_mode as set_debug_mode,
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set_disable_warnings as set_disable_warnings,
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set_quiet_mode as set_quiet_mode,
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validate_is_path as validate_is_path,
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)
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from openllm_core.utils.serde import converter as converter
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from ._llm import LLM
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def available_devices() -> Tuple[str, ...]: ...
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def device_count() -> int: ...
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def generate_labels(llm: LLM[Any, Any]) -> Dict[str, Any]: ...
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