src/transformers/models/cvt/modeling_tf_cvt.py/TFCvtConvEmbeddings/call
class TFCvtConvEmbeddings:    def call(self, pixel_values: tf.Tensor) -> tf.Tensor:
        if isinstance(pixel_values, dict):
            pixel_values = pixel_values["pixel_values"]

        pixel_values = self.projection(self.padding(pixel_values))

        # "batch_size, height, width, num_channels -> batch_size, (height*width), num_channels"
        batch_size, height, width, num_channels = shape_list(pixel_values)
        hidden_size = height * width
        pixel_values = tf.reshape(pixel_values, shape=(batch_size, hidden_size, num_channels))
        pixel_values = self.normalization(pixel_values)

        # "batch_size, (height*width), num_channels -> batch_size, height, width, num_channels"
        pixel_values = tf.reshape(pixel_values, shape=(batch_size, height, width, num_channels))
        return pixel_values