fix

run_image_captioning_flax.py

@@ -22,8 +22,8 @@ import logging
 import os
 import sys
 import time
-from dataclasses import dataclass, field
-import datetime
+from dataclasses import asdict, dataclass, field
+from enum import Enum
 from functools import partial
 from pathlib import Path
 from typing import Callable, Optional
@@ -61,9 +61,6 @@ from transformers.file_utils import get_full_repo_name, is_offline_mode
 
 logger = logging.getLogger(__name__)
 
-os.environ["TOKENIZERS_PARALLELISM"] = "false"
-
-
 try:
     nltk.data.find("tokenizers/punkt")
 except (LookupError, OSError):
@@ -115,6 +112,7 @@ class TrainingArguments:
     per_device_eval_batch_size: int = field(
         default=8, metadata={"help": "Batch size per GPU/TPU core/CPU for evaluation."}
     )
+    block_size: int = field(default=None, metadata={"help": "???"})
     learning_rate: float = field(default=5e-5, metadata={"help": "The initial learning rate for AdamW."})
     weight_decay: float = field(default=0.0, metadata={"help": "Weight decay for AdamW if we apply some."})
     adam_beta1: float = field(default=0.9, metadata={"help": "Beta1 for AdamW optimizer"})
@@ -159,14 +157,6 @@ class TrainingArguments:
         return d
 
 
-@dataclass
-class CustomTrainingArguments(TrainingArguments):
-
-    do_predict_during_training: bool = field(default=None, metadata={"help": "???"})
-    do_predict_after_evaluation: bool = field(default=None, metadata={"help": "???"})
-    block_size: int = field(default=None, metadata={"help": "???"})
-
-
 @dataclass
 class ModelArguments:
     """
@@ -417,7 +407,7 @@ def main():
     # or by passing the --help flag to this script.
     # We now keep distinct sets of args, for a cleaner separation of concerns.
 
-    parser = HfArgumentParser((ModelArguments, DataTrainingArguments, CustomTrainingArguments))
+    parser = HfArgumentParser((ModelArguments, DataTrainingArguments, TrainingArguments))
     if len(sys.argv) == 2 and sys.argv[1].endswith(".json"):
         # If we pass only one argument to the script and it's the path to a json file,
         # let's parse it to get our arguments.