<filename>perceiver/feedforward.py
import tensorflow as tf
from .geglu import GEGLU


class FeedForward(tf.keras.layers.Layer):
    def __init__(self, dim, mult=4, dropout=0.0):
        super(FeedForward, self).__init__()
        self.net = tf.keras.Sequential(
            [
                tf.keras.layers.Dense(dim * mult * 2, input_dim=dim),
                GEGLU(),
                tf.keras.layers.Dropout(dropout),
                tf.keras.layers.Dense(dim, input_dim=dim * mult),
            ]
        )

    def call(self, inputs):
        return self.net(inputs)

<filename>perceiver/feedforward.py
import tensorflow as tf
from .geglu import GEGLU


class FeedForward(tf.keras.layers.Layer):
    def __init__(self, dim, mult=4, dropout=0.0):
        super(FeedForward, self).__init__()
        self.net = tf.keras.Sequential(
            [
                tf.keras.layers.Dense(dim * mult * 2, input_dim=dim),
                GEGLU(),
                tf.keras.layers.Dropout(dropout),
                tf.keras.layers.Dense(dim, input_dim=dim * mult),
            ]
        )

    def call(self, inputs):
        return self.net(inputs)
