src/transformers/models/cvt/modeling_tf_cvt.py/TFCvtConvEmbeddings/__init__
class TFCvtConvEmbeddings:    def __init__(self, config: CvtConfig, patch_size: int, embed_dim: int, stride: int, padding: int, **kwargs):
        super().__init__(**kwargs)
        self.padding = tf.keras.layers.ZeroPadding2D(padding=padding)
        self.patch_size = patch_size if isinstance(patch_size, collections.abc.Iterable) else (patch_size, patch_size)
        self.projection = tf.keras.layers.Conv2D(
            filters=embed_dim,
            kernel_size=patch_size,
            strides=stride,
            padding="valid",
            data_format="channels_last",
            kernel_initializer=get_initializer(config.initializer_range),
            name="projection",
        )
        # Using the same default epsilon as PyTorch
        self.normalization = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="normalization")