[examples] max samples can't be bigger than the len of dataset (#16501)

* [examples] max samples can't be bigger than then len of dataset

* do tf and flax

examples/flax/image-captioning/run_image_captioning_flax.py

@@ -613,7 +613,8 @@ def main():
             raise ValueError("--do_train requires a train dataset")
         train_dataset = dataset["train"]
         if data_args.max_train_samples is not None:
-            train_dataset = train_dataset.select(range(data_args.max_train_samples))
+            max_train_samples = min(len(train_dataset), data_args.max_train_samples)
+            train_dataset = train_dataset.select(range(max_train_samples))
         # remove problematic examples
         # (if feature extraction is performed at the beginning, the filtering is done during preprocessing below
         # instead here.)
@@ -646,7 +647,8 @@ def main():
             raise ValueError("--do_eval requires a validation dataset")
         eval_dataset = dataset["validation"]
         if data_args.max_eval_samples is not None:
-            eval_dataset = eval_dataset.select(range(data_args.max_eval_samples))
+            max_eval_samples = min(len(eval_dataset), data_args.max_eval_samples)
+            eval_dataset = eval_dataset.select(range(max_eval_samples))
         # remove problematic examples
         # (if feature extraction is performed at the beginning, the filtering is done during preprocessing below
         # instead here.)
@@ -675,7 +677,8 @@ def main():
             raise ValueError("--do_predict requires a test dataset")
         predict_dataset = dataset["test"]
         if data_args.max_predict_samples is not None:
-            predict_dataset = predict_dataset.select(range(data_args.max_predict_samples))
+            max_predict_samples = min(len(predict_dataset), data_args.max_predict_samples)
+            predict_dataset = predict_dataset.select(range(max_predict_samples))
         # remove problematic examples
         # (if feature extraction is performed at the beginning, the filtering is done during preprocessing below
         # instead here.)