Answers for "residual block keras"

1

residual block keras

from keras import layers


def residual_block(y, nb_channels, _strides=(1, 1), _project_shortcut=False):
    shortcut = y

    # down-sampling is performed with a stride of 2
    y = layers.Conv2D(nb_channels, kernel_size=(3, 3), strides=_strides, padding='same')(y)
    y = layers.BatchNormalization()(y)
    y = layers.LeakyReLU()(y)

    y = layers.Conv2D(nb_channels, kernel_size=(3, 3), strides=(1, 1), padding='same')(y)
    y = layers.BatchNormalization()(y)

    # identity shortcuts used directly when the input and output are of the same dimensions
    if _project_shortcut or _strides != (1, 1):
        # when the dimensions increase projection shortcut is used to match dimensions (done by 1×1 convolutions)
        # when the shortcuts go across feature maps of two sizes, they are performed with a stride of 2
        shortcut = layers.Conv2D(nb_channels, kernel_size=(1, 1), strides=_strides, padding='same')(shortcut)
        shortcut = layers.BatchNormalization()(shortcut)

    y = layers.add([shortcut, y])
    y = layers.LeakyReLU()(y)

    return y
Posted by: Guest on April-29-2021

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