fixing conversion of chanels, config update
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@ -5,7 +5,7 @@ output_model_path: "Zombely/plwiki-proto-fine-tuned-v3"
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wandb_test_name: "fiszki-ocr-fine-tune"
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wandb_test_name: "fiszki-ocr-fine-tune"
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checkpoint_path: "./checkpoint"
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checkpoint_path: "./checkpoint"
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max_length: 768
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max_length: 768
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image_size: [1920, 2560]
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image_size: [2560, 1920]
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train_config:
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train_config:
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max_epochs: 1
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max_epochs: 1
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val_check_interval: 0.5
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val_check_interval: 0.5
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@ -7,7 +7,6 @@ import torch
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from transformers import DonutProcessor, VisionEncoderDecoderModel
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from transformers import DonutProcessor, VisionEncoderDecoderModel
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class DonutDataset(Dataset):
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class DonutDataset(Dataset):
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"""
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"""
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DonutDataset which is saved in huggingface datasets format. (see details in https://huggingface.co/docs/datasets)
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DonutDataset which is saved in huggingface datasets format. (see details in https://huggingface.co/docs/datasets)
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@ -132,7 +131,7 @@ class DonutDataset(Dataset):
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sample = self.dataset[idx]
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sample = self.dataset[idx]
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# inputs
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# inputs
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pixel_values = self.processor(sample["image"], random_padding=self.split == "train", return_tensors="pt").pixel_values
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pixel_values = self.processor(sample["image"].convert("RGB"), random_padding=self.split == "train", return_tensors="pt").pixel_values
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pixel_values = pixel_values.squeeze()
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pixel_values = pixel_values.squeeze()
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# targets
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# targets
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