[Trainer] Allow passing image processor (#29896)
* Add image processor to trainer * Replace tokenizer=image_processor everywhere
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@@ -328,7 +328,7 @@ food["test"].set_transform(preprocess_val)
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... data_collator=data_collator,
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... train_dataset=food["train"],
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... eval_dataset=food["test"],
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... tokenizer=image_processor,
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... image_processor=image_processor,
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... compute_metrics=compute_metrics,
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... )
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@@ -426,7 +426,7 @@ Convert your datasets to the `tf.data.Dataset` format using the [`~datasets.Data
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>>> metric_callback = KerasMetricCallback(metric_fn=compute_metrics, eval_dataset=tf_eval_dataset)
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>>> push_to_hub_callback = PushToHubCallback(
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... output_dir="food_classifier",
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... tokenizer=image_processor,
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... image_processor=image_processor,
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... save_strategy="no",
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... )
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>>> callbacks = [metric_callback, push_to_hub_callback]
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@@ -376,7 +376,7 @@ DETR モデルをトレーニングできる「ラベル」。画像プロセッ
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... args=training_args,
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... data_collator=collate_fn,
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... train_dataset=cppe5["train"],
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... tokenizer=image_processor,
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... image_processor=image_processor,
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... )
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>>> trainer.train()
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@@ -434,7 +434,7 @@ TensorFlow でモデルを微調整するには、次の手順に従います。
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... metric_fn=compute_metrics, eval_dataset=tf_eval_dataset, batch_size=batch_size, label_cols=["labels"]
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... )
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>>> push_to_hub_callback = PushToHubCallback(output_dir="scene_segmentation", tokenizer=image_processor)
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>>> push_to_hub_callback = PushToHubCallback(output_dir="scene_segmentation", image_processor=image_processor)
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>>> callbacks = [metric_callback, push_to_hub_callback]
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```
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@@ -436,7 +436,7 @@ TensorFlow でモデルを微調整するには、次の手順に従います。
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... metric_fn=compute_metrics, eval_dataset=tf_eval_dataset, batch_size=batch_size, label_cols=["labels"]
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... )
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>>> push_to_hub_callback = PushToHubCallback(output_dir="scene_segmentation", tokenizer=image_processor)
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>>> push_to_hub_callback = PushToHubCallback(output_dir="scene_segmentation", image_processor=image_processor)
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>>> callbacks = [metric_callback, push_to_hub_callback]
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```
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@@ -414,7 +414,7 @@ def compute_metrics(eval_pred):
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... args,
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... train_dataset=train_dataset,
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... eval_dataset=val_dataset,
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... tokenizer=image_processor,
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... image_processor=image_processor,
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... compute_metrics=compute_metrics,
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... data_collator=collate_fn,
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... )
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