src/transformers/models/convnext/modeling_tf_convnext.py/TFConvNextEmbeddings/__init__
class TFConvNextEmbeddings:    def __init__(self, config, **kwargs):
        super().__init__(**kwargs)
        self.patch_embeddings = tf.keras.layers.Conv2D(
            filters=config.hidden_sizes[0],
            kernel_size=config.patch_size,
            strides=config.patch_size,
            name="patch_embeddings",
            kernel_initializer=get_initializer(config.initializer_range),
            bias_initializer="zeros",
        )
        self.layernorm = tf.keras.layers.LayerNormalization(epsilon=1e-6, name="layernorm")
        self.num_channels = config.num_channels