Ahmadzei's picture
added 3 more tables for large emb model
5fa1a76
images = [
train_data_augmentation(convert_to_tf_tensor(image.convert("RGB"))) for image in example_batch["image"]
]
example_batch["pixel_values"] = [tf.transpose(tf.squeeze(image)) for image in images]
return example_batch
def preprocess_val(example_batch):
"""Apply val_transforms across a batch."""