d101b12daaae0768d83efe2e70e88462e87b47b8,keras_/kerascv/models/preresnet.py,,preres_init_block,#Any#Any#Any#Any#,174

Before Change

        padding=3,
        use_bias=False,
        name=name + "/conv")
    if K.backend() == "mxnet":
        x = GluonBatchNormalization(name=name + "/bn")(x)
    else:
        x = nn.BatchNormalization(
            axis=(1 if K.image_data_format() == "channels_first" else 3),
            momentum=0.9,
            epsilon=1e-5,
            name=name + "/bn")(x)
    x = nn.Activation("relu", name=name + "/activ")(x)
    x = nn.MaxPool2D(
        pool_size=3,
        strides=2,

After Change

        padding=3,
        use_bias=False,
        name=name + "/conv")
    x = batchnorm(
        x=x,
        name=name + "/bn")
    x = nn.Activation("relu", name=name + "/activ")(x)
    x = nn.MaxPool2D(
        pool_size=3,
        strides=2,

Instances