From 999471256c0626bb29e9caa65bbf96b8d2cb52d6 Mon Sep 17 00:00:00 2001 From: oobabooga <112222186+oobabooga@users.noreply.github.com> Date: Mon, 11 Aug 2025 12:32:17 -0700 Subject: [PATCH] Lint --- modules/exllamav2.py | 2 +- modules/exllamav3.py | 11 ++++------- 2 files changed, 5 insertions(+), 8 deletions(-) diff --git a/modules/exllamav2.py b/modules/exllamav2.py index 5d5c5b56..3b3233d2 100644 --- a/modules/exllamav2.py +++ b/modules/exllamav2.py @@ -3,6 +3,7 @@ import traceback from pathlib import Path import torch + from exllamav2 import ( ExLlamaV2, ExLlamaV2Cache, @@ -15,7 +16,6 @@ from exllamav2 import ( ExLlamaV2Tokenizer ) from exllamav2.generator import ExLlamaV2Sampler, ExLlamaV2StreamingGenerator - from modules import shared from modules.logging_colors import logger from modules.text_generation import get_max_prompt_length diff --git a/modules/exllamav3.py b/modules/exllamav3.py index 3fabdb6b..980230f8 100644 --- a/modules/exllamav3.py +++ b/modules/exllamav3.py @@ -2,12 +2,9 @@ import traceback from pathlib import Path from typing import Any, List, Tuple -import torch from exllamav3 import Cache, Config, Generator, Model, Tokenizer from exllamav3.cache import CacheLayer_fp16, CacheLayer_quant from exllamav3.generator import Job - -from modules import shared from exllamav3.generator.sampler import ( CustomSampler, SS_Argmax, @@ -19,13 +16,13 @@ from exllamav3.generator.sampler import ( SS_TopK, SS_TopP ) +from modules import shared from modules.image_utils import ( convert_image_attachments_to_pil, convert_openai_messages_to_images ) from modules.logging_colors import logger from modules.text_generation import get_max_prompt_length -from modules.torch_utils import clear_torch_cache try: import flash_attn @@ -205,13 +202,13 @@ class Exllamav3Model: penalty_range = state['repetition_penalty_range'] if penalty_range <= 0: penalty_range = int(10e7) # Use large number for "full context" - rep_decay = 0 # Not a configurable parameter + rep_decay = 0 # Not a configurable parameter # Add penalty samplers if they are active if state['repetition_penalty'] != 1.0: - unordered_samplers.append(SS_RepP(state['repetition_penalty'], penalty_range, rep_decay)) + unordered_samplers.append(SS_RepP(state['repetition_penalty'], penalty_range, rep_decay)) if state['presence_penalty'] != 0.0 or state['frequency_penalty'] != 0.0: - unordered_samplers.append(SS_PresFreqP(state['presence_penalty'], state['frequency_penalty'], penalty_range, rep_decay)) + unordered_samplers.append(SS_PresFreqP(state['presence_penalty'], state['frequency_penalty'], penalty_range, rep_decay)) # Standard samplers if state['top_k'] > 0: