Cleanup unused imports

eval/humaneval.py

@@ -3,7 +3,7 @@ import os, sys
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 from exllamav3 import model_init, Generator, Job, ComboSampler
 from exllamav3.util.progress import ProgressBar
-import argparse, contextlib, subprocess
+import argparse, subprocess
 from human_eval.data import write_jsonl, read_problems
 from pathlib import Path
 

eval/mmlu.py

@@ -1,14 +1,12 @@
 from __future__ import annotations
 import sys, os
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-from exllamav3 import model_init
 from exllamav3 import model_init, Generator, Job
-import argparse, contextlib
+import argparse
 import torch
-import util
 import random, math
 from datasets import load_dataset
-from exllamav3.util.file import disk_lru_cache, disk_lru_cache_clear
+from exllamav3.util.file import disk_lru_cache
 from exllamav3.util.progress import ProgressBar
 
 @disk_lru_cache("get_dataset_mmlu")

eval/ppl.py

@@ -2,10 +2,9 @@ import sys, os
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
 import argparse
-from exllamav3.util.file import disk_lru_cache, disk_lru_cache_clear
+from exllamav3.util.file import disk_lru_cache
 from exllamav3.util.progress import ProgressBar
-from exllamav3.util.memory import free_mem
-from exllamav3 import Config, Model, Cache, Tokenizer, model_init
+from exllamav3 import model_init
 from datasets import load_dataset
 import torch
 import torch.nn.functional as F

eval/ppl_transformers.py

@@ -5,8 +5,8 @@ import argparse
 from exllamav3.util.file import disk_lru_cache, disk_lru_cache_clear
 from exllamav3.util.progress import ProgressBar
 from exllamav3.util.memory import free_mem
-from exllamav3 import Config, Model, Cache, Tokenizer, model_init
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from exllamav3 import Config, Tokenizer, model_init
+from transformers import AutoModelForCausalLM
 from datasets import load_dataset
 import torch
 import torch.nn.functional as F

eval/prequant_test.py

@@ -2,20 +2,17 @@ import sys, os
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
 import argparse
-from exllamav3.util.file import disk_lru_cache, disk_lru_cache_clear
+from exllamav3.util.file import disk_lru_cache
 from exllamav3.util.progress import ProgressBar
 from exllamav3.util.memory import free_mem
-from exllamav3 import Config, Model, Cache, Tokenizer, model_init
+from exllamav3 import Config, Model, Tokenizer
 from exllamav3.ext import exllamav3_ext as ext
 from datasets import load_dataset
 from exllamav3.modules import Linear
-from exllamav3.modules.quant import LinearFP16, LinearEXL3
 from exllamav3.modules.quant.exl3_lib.quantize import regularize
 import torch
 import torch.nn.functional as F
 import math
-import numpy as np
-import termplotlib as tpl
 
 # ANSI codes
 ESC = "\u001b"

examples/async_generator.py

@@ -1,6 +1,6 @@
 import sys, os
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-from exllamav3 import Model, Config, Cache, Tokenizer, AsyncGenerator, AsyncJob, Sampler
+from exllamav3 import Model, Config, Cache, Tokenizer, AsyncGenerator, AsyncJob
 import asyncio
 
 """

examples/banned_strings.py

@@ -1,7 +1,6 @@
 import sys, os
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 from exllamav3 import Model, Config, Cache, Tokenizer, Generator, Job, GreedySampler
-from exllamav3.util import Timer
 from common import format_prompt, get_stop_conditions
 
 """

examples/batched_translation.py

@@ -3,8 +3,8 @@ sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 import argparse
 from transformers import AutoTokenizer
 from exllamav3.util.progress import ProgressBar
-from exllamav3.util.file import disk_lru_cache, disk_lru_cache_clear
-from exllamav3 import Config, Model, Cache, Tokenizer, model_init, Generator, Job
+from exllamav3.util.file import disk_lru_cache
+from exllamav3 import model_init, Generator, Job
 from datasets import load_dataset
 import torch
 import time

examples/chat_console.py

@@ -1,7 +1,6 @@
 import sys, shutil
 
 from rich.prompt import Prompt
-from rich.live import Live
 from rich.markdown import Markdown
 from rich.console import Console
 from prompt_toolkit import prompt as ptk_prompt

examples/chat_util.py

@@ -1,8 +1,5 @@
 import re
-import sys
 import pyperclip
-import time
-import os
 
 def copy_last_codeblock(text: str, num) -> str | None:
     pattern = re.compile(r"```[^\n`]*\n(.*?)```", re.DOTALL)

examples/constrained_generation.py

@@ -6,7 +6,6 @@ from formatron.formatter import FormatterBuilder
 from pydantic import conlist
 from typing import Literal, Optional
 from formatron.extractor import NonterminalExtractor
-import json
 
 def get_superhero_filter(tokenizer) -> list[Filter]:
 

examples/generation_loop.py

@@ -1,7 +1,7 @@
 import sys, os
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from exllamav3 import Config, Model, Cache, Tokenizer, DefaultSampler, GreedySampler
+from exllamav3 import Config, Model, Cache, Tokenizer, GreedySampler
 from exllamav3.util import Timer
 from common import format_prompt, get_stop_conditions
 import torch

exllamav3/architecture/gemma3.py

@@ -7,7 +7,7 @@ import torch.nn.functional as F
 from ..model.config import Config
 from ..model.model import Model
 from ..util.rope import RopeStyle
-from ..util.file import read_dict, no_value, no_default
+from ..util.file import read_dict, no_default
 from ..util.vision import convert_to_rgb, normalize_image
 from ..modules import (
     Module,

exllamav3/architecture/glm4v.py

@@ -3,15 +3,14 @@ from typing_extensions import override
 import numpy as np
 import torch
 import torch.nn.functional as F
-from ..model.config import Config, no_default
+from ..model.config import Config
 from ..model.model import Model
 from ..util.rope import RopeStyle, position_embedding_grid_2d, RopeSettings
-from ..util.file import read_dict, no_value, no_default
+from ..util.file import read_dict, no_default
 from ..util.vision import convert_to_rgb, normalize_image, smart_resize
 from ..modules import (
     Module,
     RMSNorm,
-    Embedding,
     TransformerBlock,
     Attention,
     GatedMLP,
@@ -19,9 +18,7 @@ from ..modules import (
     Conv,
     LayerNorm,
     Glm4VPosEmbedding,
-    MLP
 )
-from ..modules.attn import prepare_for_attn
 from .glm4 import Glm4Model
 from types import SimpleNamespace
 from ..tokenizer import Tokenizer, MMEmbedding

exllamav3/architecture/glm4v_moe.py

@@ -1,31 +1,7 @@
 from __future__ import annotations
-from typing_extensions import override
-import numpy as np
-import torch
-import torch.nn.functional as F
 from ..model.config import Config, no_default
-from ..model.model import Model
-from ..util.rope import RopeStyle, position_embedding_grid_2d, RopeSettings
-from ..util.file import read_dict, no_value, no_default
-from ..util.vision import convert_to_rgb, normalize_image, smart_resize
-from ..modules import (
-    Module,
-    RMSNorm,
-    Embedding,
-    TransformerBlock,
-    Attention,
-    GatedMLP,
-    Linear,
-    Conv,
-    LayerNorm,
-    Glm4VPosEmbedding,
-    MLP
-)
-from ..modules.attn import prepare_for_attn
+from ..util.rope import RopeStyle
 from .glm4_moe import Glm4MoeModel
-from types import SimpleNamespace
-from ..tokenizer import Tokenizer, MMEmbedding
-from PIL import Image
 import os, json
 from .glm4v import read_glm4v_vision_config, read_glm4v_pp_config, Glm4VVisionModel
 

exllamav3/architecture/mistral3.py

@@ -7,7 +7,7 @@ import torch.nn.functional as F
 from ..model.config import Config
 from ..model.model import Model
 from ..util.rope import RopeSettings, RopeStyle
-from ..util.file import read_dict, no_value, no_default
+from ..util.file import read_dict, no_default
 from ..util.vision import size_to_longest_edge_and_patch_size, convert_to_rgb, normalize_image
 from ..util.tensor import to2
 from ..modules import (
@@ -20,7 +20,6 @@ from ..modules import (
     Linear,
     Conv,
     MLP,
-    LayerNorm,
 )
 from ..modules.attn import prepare_for_attn
 from ..tokenizer import Tokenizer, MMEmbedding

exllamav3/architecture/qwen3_vl.py

@@ -2,21 +2,16 @@ from __future__ import annotations
 from typing_extensions import override
 import numpy as np
 import torch
-import torch.nn as nn
 import torch.nn.functional as F
-from ..model.config import Config, no_default
+from ..model.config import Config
 from ..model.model import Model
-from ..util.rope import RopeStyle, position_embedding_grid_2d, RopeSettings, RoPE
+from ..util.rope import RopeStyle, position_embedding_grid_2d, RopeSettings
 from ..util.vision import convert_to_rgb, normalize_image, smart_resize
-from ..modules.attn import prepare_for_attn
-from ..util.file import read_dict, no_value, no_default
+from ..util.file import read_dict,  no_default
 from ..modules import (
     Module,
-    RMSNorm,
-    Embedding,
     TransformerBlock,
     Attention,
-    GatedMLP,
     Linear,
     Conv,
     MLP,
@@ -24,7 +19,6 @@ from ..modules import (
     Qwen3VLPosEmbedding
 )
 from .qwen3 import Qwen3Model
-from ..modules.attn import prepare_for_attn
 from ..tokenizer import Tokenizer, MMEmbedding
 from types import SimpleNamespace
 from PIL import Image

exllamav3/architecture/qwen3_vl_moe.py

@@ -1,33 +1,7 @@
 from __future__ import annotations
-from typing_extensions import override
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
 from ..model.config import Config, no_default
-from ..model.model import Model
-from ..util.rope import RopeStyle, position_embedding_grid_2d, RopeSettings, RoPE
-from ..util.vision import convert_to_rgb, normalize_image, smart_resize
-from ..modules.attn import prepare_for_attn
-from ..util.file import read_dict, no_value, no_default
-from ..modules import (
-    Module,
-    RMSNorm,
-    Embedding,
-    TransformerBlock,
-    Attention,
-    GatedMLP,
-    Linear,
-    Conv,
-    MLP,
-    LayerNorm,
-    Qwen3VLPosEmbedding
-)
+from ..util.rope import RopeStyle
 from .qwen3_moe import Qwen3MoeModel
-from ..modules.attn import prepare_for_attn
-from ..tokenizer import Tokenizer, MMEmbedding
-from types import SimpleNamespace
-from PIL import Image
 import os, json
 from .qwen3_vl import read_qwen3_vl_vision_config, read_qwen3_vl_pp_config, Qwen3VLVisionModel
 

exllamav3/cache/cache.py

@@ -2,8 +2,6 @@ from __future__ import annotations
 from abc import ABC, abstractmethod
 from typing import Type
 import torch
-import torch.nn.functional as F
-from torch import nn
 from ..model import Model, Config
 from typing import TYPE_CHECKING
 if TYPE_CHECKING:

exllamav3/cache/fp16.py

@@ -1,8 +1,6 @@
 from __future__ import annotations
 from typing_extensions import override
 import torch
-import torch.nn.functional as F
-from torch import nn
 from ..constants import PAGE_SIZE
 from ..model import Model, Config
 from .cache import CacheLayer

exllamav3/cache/quant.py

@@ -1,10 +1,8 @@
 from __future__ import annotations
 from typing_extensions import override
 import torch
-import torch.nn.functional as F
-from torch import nn
 from ..constants import PAGE_SIZE
-from ..model import Model, Config
+from ..model import Config
 from .cache import CacheLayer
 from typing import TYPE_CHECKING
 from exllamav3.ext import exllamav3_ext as ext

exllamav3/cache/recurrent.py

@@ -1,7 +1,5 @@
 from collections import OrderedDict
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING
-
 
 class CacheableState(ABC):
     def __init__(self):

exllamav3/conversion/allocation.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 import math
 import bisect
-from functools import lru_cache
 from typing import TYPE_CHECKING
 if TYPE_CHECKING:
     from ..modules.linear import Linear

exllamav3/conversion/optimize_model.py

@@ -1,14 +1,9 @@
 import argparse
 import torch
 from .. import Config, Model, Tokenizer
-from ..util.progress import ProgressBar
-from .calibration_data import get_default_calibration
-from ..modules import Linear
 import json
-import torch.nn.functional as F
-import math
 from .compile import compile_model
-from ..loader.safetensors import SafetensorsCollection, VariantSafetensorsCollection
+from ..loader.safetensors import VariantSafetensorsCollection
 
 col_default = "\u001b[0m"
 col_red = "\u001b[31;1m"

exllamav3/ext.py

@@ -1,10 +1,8 @@
 from __future__ import annotations
 import torch
 from torch.utils.cpp_extension import load
-import os, glob
+import os
 import sys
-import platform
-import threading
 from .util.arch_list import maybe_set_arch_list_env
 
 extension_name = "exllamav3_ext"

exllamav3/generator/generator.py

@@ -10,12 +10,10 @@ from .pagetable import PageTable
 from .job import Job
 from .filter import Filter
 from concurrent.futures import ThreadPoolExecutor
-from .sampler import Sampler, GumbelSampler
+from .sampler import Sampler
 from .visualizer import CacheVisualizer
 import time
 import threading
-import numpy as np
-from ..util import profile_opt
 from ..tokenizer import MMEmbedding
 from ..util import profile_opt
 

exllamav3/generator/job.py

@@ -1,21 +1,17 @@
 from __future__ import annotations
 import torch
-from dataclasses import dataclass
 from typing import TYPE_CHECKING
-from ..cache.cache import Cache
 if TYPE_CHECKING:
     from .generator import Generator
 from ..constants import PAGE_SIZE
 import numpy as np
-from .pagetable import CachePage, Sequence, tensor_hash_checksum, random_hash
+from .pagetable import Sequence, tensor_hash_checksum, random_hash
 from .filter import Filter
 import random
-from collections import deque
 import time
 from ..ext import exllamav3_ext as ext
 from .sampler import Sampler, DefaultSampler
 from ..util.tensor import SeqTensor
-from ..util import profile_opt
 from ..tokenizer import MMEmbedding
 from functools import lru_cache
 from ..util import profile_opt

exllamav3/loader/safetensors.py

@@ -6,11 +6,9 @@ import torch
 import os, glob
 import numpy as np
 import json
-import mmap
 from ..util import Timer, cuda_sync_active
 from ..ext import exllamav3_ext as ext
 from functools import cached_property
-from fnmatch import fnmatch
 import time
 
 MAX_DEFERRED_LOAD_CHUNK = 2*1024**2

exllamav3/model/config.py

@@ -1,8 +1,5 @@
 from __future__ import annotations
-from abc import ABC, abstractproperty, abstractmethod
-import torch
-import torch.nn.functional as F
-from torch import nn
+from abc import ABC
 import os, json
 from ..util.rope import RopeSettings, RopeStyle
 from ..loader import SafetensorsCollection

exllamav3/model/model_ls.py

@@ -1,5 +1,4 @@
 from __future__ import annotations
-from functools import lru_cache
 from typing import Callable
 import torch
 from ..util.memory import (

exllamav3/model/model_tp.py

@@ -1,8 +1,6 @@
 from __future__ import annotations
-import torch
 import multiprocessing
 from multiprocessing import Process, Pipe
-import torch.distributed as dist
 from ..util import find_free_port
 from .model_tp_alloc import TPAllocator
 import os
@@ -11,9 +9,7 @@ from ..util.memory import touch_device_measure_vram
 from ..util.progress import ProgressBar
 from .config import Config
 from ..util.misc import Cleanupper
-from .model_tp_shared import SMProducer
 from .model_tp_fn import *
-from .model_tp_backend import TPBackend, TPBackendNCCL, TPBackendNative
 import uuid
 from ..util import log_tp, global_t0
 

exllamav3/model/model_tp_backend.py

@@ -4,7 +4,7 @@ import time
 import numpy as np
 from .model_tp_cuda import cuda_host_register, cuda_host_unregister, CUDA_HOST_REGISTER_PORTABLE
 from ..ext import exllamav3_ext as ext
-from multiprocessing import shared_memory, Barrier
+from multiprocessing import shared_memory
 from ..util import log_tp
 
 GLOBALS_SIZE = 128*1024

exllamav3/model_init.py

@@ -2,7 +2,6 @@ from . import Model, Config, Cache, Tokenizer
 from .loader import SafetensorsCollection, VariantSafetensorsCollection
 from .cache import CacheLayer_fp16, CacheLayer_quant
 from argparse import ArgumentParser
-import torch
 import yaml
 
 def add_args(

exllamav3/modules/attn.py

@@ -7,13 +7,11 @@ from ..util.rope import RopeSettings, RoPE
 from ..util.tensor import get_for_device, to2
 from . import Module, Linear, RMSNorm, LayerNorm
 from ..constants import PAGE_SIZE
-from ..cache import Cache
 from flash_attn import flash_attn_func, flash_attn_with_kvcache
-from ..util import profile_opt
 from .multilinear import MultiLinear
 from ..ext import exllamav3_ext as ext
 from ..model.model_tp_alloc import TPAllocation
-import torch.distributed as dist
+from ..util import profile_opt
 
 """
 SDPA:

exllamav3/modules/block_sparse_mlp.py

@@ -2,19 +2,15 @@ from __future__ import annotations
 from typing_extensions import override
 import torch
 import torch.nn.functional as F
-from torch import nn
 from ..model.config import Config
 from ..util.tensor import to2
 from . import Module, Linear
 from .multilinear import MultiLinear
 from ..ext import exllamav3_ext as ext
-from ..constants import MAX_MLP_INTERMEDIATE
-from ..util import first_not_none
-from ..util import profile_opt
 from dataclasses import dataclass
 from .mlp import MLP, GatedMLP
 from ..model.model_tp_alloc import TPAllocation
-import torch.distributed as dist
+from ..util import profile_opt
 
 
 @dataclass

exllamav3/modules/conv.py

@@ -2,7 +2,6 @@ from __future__ import annotations
 from typing_extensions import override
 import torch
 import torch.nn.functional as F
-from torch import nn
 from ..model.config import Config
 from . import Module
 from ..ext import exllamav3_ext as ext

exllamav3/modules/embedding.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 from typing_extensions import override
 import torch
-import torch.nn.functional as F
 from torch import nn
 from ..model.config import Config
 from ..util.tensor import to2

exllamav3/modules/gated_delta_net.py

@@ -5,12 +5,12 @@ import torch.nn.functional as F
 from ..model.config import Config
 from ..util.tensor import get_for_device, to2
 from . import Module, Linear
-from ..util import profile_opt
 from ..ext import exllamav3_ext as ext
 from ..model.model_tp_alloc import TPAllocation
 from .gated_rmsnorm import GatedRMSNorm
 from ..cache import CacheableState
 from ..util.tensor import g_tensor_cache
+from ..util import profile_opt
 
 """
 causal_conv1d wrappers and fallback functions 

exllamav3/modules/gather.py

@@ -2,7 +2,6 @@ from __future__ import annotations
 from typing_extensions import override
 from . import Module
 import torch
-import torch.distributed as dist
 
 class OutputGather(Module):
     def __init__(

exllamav3/modules/glm4v_pos_embedding.py

@@ -2,11 +2,8 @@ from __future__ import annotations
 from typing_extensions import override
 import torch
 import torch.nn.functional as F
-from torch import nn
 from ..model.config import Config
 from . import Module
-from ..ext import exllamav3_ext as ext
-from ..model.model_tp_alloc import TPAllocation
 from ..util.tensor import get_for_device, to2
 
 class Glm4VPosEmbedding(Module):

exllamav3/modules/layernorm.py

@@ -5,7 +5,6 @@ import torch.nn.functional as F
 from torch import nn
 from ..model.config import Config
 from . import Module
-from ..ext import exllamav3_ext as ext
 from ..model.model_tp_alloc import TPAllocation
 
 class LayerNorm(Module):

exllamav3/modules/linear.py

@@ -2,16 +2,13 @@ from __future__ import annotations
 from functools import cached_property
 from typing_extensions import override
 import torch
-import torch.nn.functional as F
 import numpy as np
-from torch import nn
 from ..model.config import Config
 from . import Module
-from .quant import LinearFP16, LinearFP16_torch, LinearEXL3
+from .quant import LinearFP16, LinearEXL3
 from .quant.exl3_lib import quantize_exl3
 from ..ext import exllamav3_ext as ext
 from ..conversion.allocation import allocate_linear
-from ..util.memory import free_mem
 from ..model.model_tp_alloc import TPAllocation
 
 

exllamav3/modules/mlp.py

@@ -9,7 +9,6 @@ from . import Module, Linear
 from ..ext import exllamav3_ext as ext
 from ..constants import MAX_MLP_INTERMEDIATE
 from ..model.model_tp_alloc import TPAllocation
-import torch.distributed as dist
 from .multilinear import MultiLinear
 from ..util.tensor import g_tensor_cache
 

exllamav3/modules/module.py

@@ -2,8 +2,6 @@ from __future__ import annotations
 from abc import ABC, abstractmethod
 import torch
 import os
-import torch.nn.functional as F
-from torch import nn
 from typing import TYPE_CHECKING
 if TYPE_CHECKING:
     from ..model.config import Config

exllamav3/modules/pos_embedding.py

@@ -1,11 +1,9 @@
 from __future__ import annotations
 from typing_extensions import override
 import torch
-import torch.nn.functional as F
 from torch import nn
 from ..model.config import Config
 from . import Module
-from ..ext import exllamav3_ext as ext
 from ..util.tensor import to2
 from ..model.model_tp_alloc import TPAllocation
 

exllamav3/modules/quant/exl3.py

@@ -3,8 +3,8 @@ import torch
 from ...model.config import Config
 from .exl3_lib.quantize import preapply_had_l, preapply_had_r, had_k, had_n
 from ...ext import exllamav3_ext as ext
-from ...util import profile_opt
 from ...util.tensor import g_tensor_cache
+from ...util import profile_opt
 
 class LinearEXL3:
 

exllamav3/modules/quant/fp16.py

@@ -1,7 +1,5 @@
 from __future__ import annotations
-from typing_extensions import override
 import torch
-import torch.nn.functional as F
 from torch import nn
 from ...ext import exllamav3_ext as ext
 from ...util.tensor import to2

exllamav3/modules/qwen3_vl_pos_embedding.py

@@ -1,13 +1,10 @@
 from __future__ import annotations
 from typing_extensions import override
 import torch
-import torch.nn.functional as F
 from torch import nn
 from ..model.config import Config
 from . import Module
-from ..ext import exllamav3_ext as ext
 from ..util.tensor import to2
-from ..model.model_tp_alloc import TPAllocation
 
 
 class Qwen3VLPosEmbedding(Module):

exllamav3/modules/rmsnorm.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 from typing_extensions import override
 import torch
-import torch.nn.functional as F
 from torch import nn
 from ..model.config import Config
 from . import Module

exllamav3/modules/transformer.py

@@ -1,14 +1,11 @@
 from __future__ import annotations
 from typing_extensions import override
 import torch
-import torch.nn.functional as F
-from torch import nn
 from ..util.tensor import to2
 from ..model.config import Config
 from . import Module, RMSNorm, LayerNorm, Attention, GatedDeltaNet, GatedMLP, MLP, BlockSparseMLP
 from ..conversion.allocation import allocate_transformer
 from ..util import profile_opt
-import torch.distributed as dist
 
 class TransformerBlock(Module):
 

exllamav3/tokenizer/tokenizer.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 import torch
-import os, json, re
+import os, re
 from tokenizers import Tokenizer as HFTokenizer, models
 from ..util import synchronized
 from ..util.file import maybe_read_json

exllamav3/util/file.py

@@ -2,8 +2,8 @@ import os
 import shelve
 import sys
 import json
-from typing import Any, Dict, List, TypeVar, Union, cast
-from functools import lru_cache, wraps
+from typing import Any, TypeVar, cast
+from functools import wraps
 
 
 def disk_lru_cache_name(filename):