ccd8a225512ac736b181792c72a3d45e4ff3160b,keras_/models/darknet.py,,dark_conv,#Any#Any#Any#Any#Any#Any#,13

Before Change

        padding=ke_padding,
        use_bias=False,
        name=name + "/conv")(x)
    x = nn.BatchNormalization(
        axis=-1,
        momentum=0.9,
        epsilon=1e-5,
        name=name+"/bn")(x)
    x = nn.LeakyReLU(alpha=0.1, name=name+"/activ")(x)
    return x

After Change

        padding=ke_padding,
        use_bias=False,
        name=name + "/conv")
    bn = nn.BatchNormalization(
        axis=(1 if K.image_data_format() == "channels_first" else 3),
        momentum=0.9,
        epsilon=1e-5,
        name=name+"/bn")
    activ = nn.LeakyReLU(alpha=0.1, name=name+"/activ")

    x = conv(x)
    x = bn(x)

Instances