Fix conflicting `--no_cuda` argument

src/evaluate.py

@@ -138,7 +138,7 @@ def main():
         GeneralArguments
     ))
 
-    evaluation_args, dataset_args, segmentation_args, classifier_args, _ = hf_parser.parse_args_into_dataclasses()
+    evaluation_args, dataset_args, segmentation_args, classifier_args, general_args = hf_parser.parse_args_into_dataclasses()
 
     # Load labelled data:
     final_path = os.path.join(
@@ -150,7 +150,7 @@ def main():
         return
 
     model, tokenizer = get_model_tokenizer(
-        evaluation_args.model_path, evaluation_args.cache_dir, evaluation_args.no_cuda)
+        evaluation_args.model_path, evaluation_args.cache_dir, general_args.no_cuda)
 
     with open(final_path) as fp:
         final_data = json.load(fp)

src/model.py

@@ -23,8 +23,6 @@ class ModelArguments:
             'help': 'Path to pretrained model or model identifier from huggingface.co/models'
         }
     )
-    no_cuda: bool = field(default=False, metadata={
-                          'help': 'Do not use CUDA even when it is available'})
 
     # config_name: Optional[str] = field( # TODO remove?
     #     default=None, metadata={'help': 'Pretrained config name or path if not the same as model_name'}

src/predict.py

@@ -10,7 +10,7 @@ import logging
 import os
 import itertools
 from utils import re_findall
-from shared import CustomTokens, START_SEGMENT_TEMPLATE, END_SEGMENT_TEMPLATE, OutputArguments, seconds_to_time
+from shared import CustomTokens, START_SEGMENT_TEMPLATE, END_SEGMENT_TEMPLATE, GeneralArguments, OutputArguments, seconds_to_time
 from typing import Optional
 from segment import (
     generate_segments,
@@ -115,8 +115,6 @@ class InferenceArguments:
     output_as_json: bool = field(default=False, metadata={
                                  'help': 'Output evaluations as JSON'})
 
-    no_cuda: bool = ModelArguments.__dataclass_fields__['no_cuda']
-
     def __post_init__(self):
         # Try to load model from latest checkpoint
         if self.model_path is None:
@@ -398,9 +396,10 @@ def main():
     hf_parser = HfArgumentParser((
         PredictArguments,
         SegmentationArguments,
-        ClassifierArguments
+        ClassifierArguments,
+        GeneralArguments
     ))
-    predict_args, segmentation_args, classifier_args = hf_parser.parse_args_into_dataclasses()
+    predict_args, segmentation_args, classifier_args, general_args = hf_parser.parse_args_into_dataclasses()
 
     if not predict_args.video_ids:
         logger.error(
@@ -408,7 +407,7 @@ def main():
         return
 
     model, tokenizer = get_model_tokenizer(
-        predict_args.model_path, predict_args.cache_dir, predict_args.no_cuda)
+        predict_args.model_path, predict_args.cache_dir, general_args.no_cuda)
 
     for video_id in predict_args.video_ids:
         video_id = video_id.strip()

src/shared.py

@@ -99,6 +99,8 @@ class GeneralArguments:
     seed: Optional[int] = field(default_factory=seed_factory, metadata={
         'help': 'Set seed for deterministic training and testing. By default, it uses the current time (results in essentially random results).'
     })
+    no_cuda: bool = field(default=False, metadata={
+                          'help': 'Do not use CUDA even when it is available'})
 
     def __post_init__(self):
         random.seed(self.seed)

src/train.py

@@ -297,7 +297,7 @@ def main():
 
         from model import get_model_tokenizer
         model, tokenizer = get_model_tokenizer(
-            model_args.model_name_or_path, model_args.cache_dir, model_args.no_cuda)
+            model_args.model_name_or_path, model_args.cache_dir, training_args.no_cuda)
         # max_tokenizer_length = model.config.d_model
 
         # Preprocessing the datasets.