def __init__(self, n_ctx, config, scale=False, **kwargs):
    super(TFBlock, self).__init__(**kwargs)
    nx = config.n_embd
    self.attn = TFAttention(nx, n_ctx, config, scale, name='attn')
    self.ln_1 = tf.keras.layers.LayerNormalization(epsilon=config.layer_norm_epsilon, name='ln_1')
    self.mlp = TFMLP((4 * nx), config, name='mlp')
    self.ln_2 = tf.keras.layers.LayerNormalization(epsilon=config.layer_norm_epsilon, name='ln_2')
def __init__(self, n_ctx, config, scale=False, **kwargs):
    super(TFBlock, self).__init__(**kwargs)
    nx = config.n_embd
    self.attn = TFAttention(nx, n_ctx, config, scale, name='attn')
    self.ln_1 = tf.keras.layers.LayerNormalization(epsilon=config.layer_norm_epsilon, name='ln_1')
    self.mlp = TFMLP((4 * nx), config, name='mlp')
    self.ln_2 = tf.keras.layers.LayerNormalization(epsilon=config.layer_norm_epsilon, name='ln_2')