Sort some imports

modules/chat.py

@@ -14,8 +14,11 @@ import modules.shared as shared
 from modules.extensions import apply_extensions
 from modules.html_generator import chat_html_wrapper, make_thumbnail
 from modules.logging_colors import logger
-from modules.text_generation import (generate_reply, get_encoded_length,
-                                     get_max_prompt_length)
+from modules.text_generation import (
+    generate_reply,
+    get_encoded_length,
+    get_max_prompt_length
+)
 from modules.utils import delete_file, replace_all, save_file
 
 

modules/evaluate.py

@@ -8,8 +8,10 @@ from tqdm import tqdm
 
 from modules import shared
 from modules.models import load_model, unload_model
-from modules.models_settings import (get_model_settings_from_yamls,
-                                     update_model_parameters)
+from modules.models_settings import (
+    get_model_settings_from_yamls,
+    update_model_parameters
+)
 from modules.text_generation import encode
 
 

modules/html_generator.py

@@ -1,9 +1,3 @@
-'''
-
-This is a library for formatting text outputs as nice HTML.
-
-'''
-
 import os
 import re
 import time

modules/models.py

@@ -7,9 +7,15 @@ from pathlib import Path
 import torch
 import transformers
 from accelerate import infer_auto_device_map, init_empty_weights
-from transformers import (AutoConfig, AutoModel, AutoModelForCausalLM,
-                          AutoModelForSeq2SeqLM, AutoTokenizer,
-                          BitsAndBytesConfig, LlamaTokenizer)
+from transformers import (
+    AutoConfig,
+    AutoModel,
+    AutoModelForCausalLM,
+    AutoModelForSeq2SeqLM,
+    AutoTokenizer,
+    BitsAndBytesConfig,
+    LlamaTokenizer
+)
 
 import modules.shared as shared
 from modules import llama_attn_hijack, sampler_hijack
@@ -21,8 +27,10 @@ transformers.logging.set_verbosity_error()
 local_rank = None
 if shared.args.deepspeed:
     import deepspeed
-    from transformers.deepspeed import (HfDeepSpeedConfig,
-                                        is_deepspeed_zero3_enabled)
+    from transformers.deepspeed import (
+        HfDeepSpeedConfig,
+        is_deepspeed_zero3_enabled
+    )
 
     from modules.deepspeed_parameters import generate_ds_config
 

modules/monkey_patch_gptq_lora.py

@@ -7,10 +7,14 @@ sys.path.insert(0, str(Path("repositories/alpaca_lora_4bit")))
 
 import autograd_4bit
 from amp_wrapper import AMPWrapper
-from autograd_4bit import (Autograd4bitQuantLinear,
-                           load_llama_model_4bit_low_ram)
+from autograd_4bit import (
+    Autograd4bitQuantLinear,
+    load_llama_model_4bit_low_ram
+)
 from monkeypatch.peft_tuners_lora_monkey_patch import (
-    Linear4bitLt, replace_peft_model_with_gptq_lora_model)
+    Linear4bitLt,
+    replace_peft_model_with_gptq_lora_model
+)
 
 from modules import shared
 from modules.GPTQ_loader import find_quantized_model_file

modules/sampler_hijack.py

@@ -3,9 +3,11 @@ import math
 import torch
 import transformers
 from transformers import LogitsWarper
-from transformers.generation.logits_process import (LogitNormalization,
+from transformers.generation.logits_process import (
+    LogitNormalization,
     LogitsProcessorList,
-                                                    TemperatureLogitsWarper)
+    TemperatureLogitsWarper
+)
 
 
 class TailFreeLogitsWarper(LogitsWarper):

modules/training.py

@@ -11,12 +11,19 @@ import gradio as gr
 import torch
 import transformers
 from datasets import Dataset, load_dataset
-from peft import (LoraConfig, get_peft_model, prepare_model_for_kbit_training,
-                  set_peft_model_state_dict)
+from peft import (
+    LoraConfig,
+    get_peft_model,
+    prepare_model_for_kbit_training,
+    set_peft_model_state_dict
+)
 
 from modules import shared, ui, utils
-from modules.evaluate import (calculate_perplexity, generate_markdown_table,
-                              save_past_evaluations)
+from modules.evaluate import (
+    calculate_perplexity,
+    generate_markdown_table,
+    save_past_evaluations
+)
 from modules.logging_colors import logger
 
 # This mapping is from a very recent commit, not yet released.
@@ -25,8 +32,9 @@ try:
     from peft.utils.other import \
         TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING as \
         model_to_lora_modules
-    from transformers.models.auto.modeling_auto import \
+    from transformers.models.auto.modeling_auto import (
         MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
+    )
     MODEL_CLASSES = {v: k for k, v in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES}
 except:
     standard_modules = ["q_proj", "v_proj"]
@@ -201,8 +209,9 @@ def clean_path(base_path: str, path: str):
 def do_train(lora_name: str, always_override: bool, save_steps: int, micro_batch_size: int, batch_size: int, epochs: int, learning_rate: str, lr_scheduler_type: str, lora_rank: int, lora_alpha: int, lora_dropout: float, cutoff_len: int, dataset: str, eval_dataset: str, format: str, eval_steps: int, raw_text_file: str, overlap_len: int, newline_favor_len: int, higher_rank_limit: bool, warmup_steps: int, optimizer: str, hard_cut_string: str, train_only_after: str):
 
     if shared.args.monkey_patch:
-        from monkeypatch.peft_tuners_lora_monkey_patch import \
+        from monkeypatch.peft_tuners_lora_monkey_patch import (
             replace_peft_model_with_gptq_lora_model
+        )
         replace_peft_model_with_gptq_lora_model()
 
     global WANT_INTERRUPT

server.py

@@ -38,12 +38,17 @@ from modules.github import clone_or_pull_repository
 from modules.html_generator import chat_html_wrapper
 from modules.LoRA import add_lora_to_model
 from modules.models import load_model, unload_model
-from modules.models_settings import (apply_model_settings_to_state,
+from modules.models_settings import (
+    apply_model_settings_to_state,
     get_model_settings_from_yamls,
     save_model_settings,
-                                     update_model_parameters)
-from modules.text_generation import (generate_reply_wrapper,
-                                     get_encoded_length, stop_everything_event)
+    update_model_parameters
+)
+from modules.text_generation import (
+    generate_reply_wrapper,
+    get_encoded_length,
+    stop_everything_event
+)
 
 
 def load_model_wrapper(selected_model, loader, autoload=False):