python - image similarity training using TFRecord

Question

I am learning image similarity training from Keras sample code at below link. However, I have large volumn of image data and it is in TFRecord. How to create AnchorPositivePairs class by using of TFRecord and train in TPU?

https://keras.io/examples/vision/metric_learning/

class_idx_to_train_idxs = defaultdict(list)
for y_train_idx, y in enumerate(y_train):
    class_idx_to_train_idxs[y].append(y_train_idx)

class_idx_to_test_idxs = defaultdict(list)
for y_test_idx, y in enumerate(y_test):
    class_idx_to_test_idxs[y].append(y_test_idx)

num_classes = 3

class AnchorPositivePairs(keras.utils.Sequence):
    def __init__(self, num_batchs):
        self.num_batchs = num_batchs

    def __len__(self):
        return self.num_batchs

    def __getitem__(self, _idx):
        x = np.empty((2, num_classes, height_width, height_width, 3), dtype=np.float32)
        for class_idx in range(num_classes):
            examples_for_class = class_idx_to_train_idxs[class_idx]
            anchor_idx = random.choice(examples_for_class)
            positive_idx = random.choice(examples_for_class)
            while positive_idx == anchor_idx:
                positive_idx = random.choice(examples_for_class)
            x[0, class_idx] = x_train[anchor_idx]
            x[1, class_idx] = x_train[positive_idx]
        return x

question from:https://stackoverflow.com/questions/66056034/image-similarity-training-using-tfrecord

Answer 1

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