b16131429ff9ad2952b44d9ba514d6811e98c6cf,batchflow/models/tf/mobilenet.py,MobileNet_v2,block,#Any#Any#Any#Any#Any#Any#Any#Any#,200

Before Change

        tf.Tensor
        
        num_filters = int(cls.num_channels(inputs, kwargs.get("data_format")) * expansion_factor * width_factor)
        conv_filters = [num_filters, num_filters, filters]
        x = conv_block(inputs, "cna Cna cn", conv_filters, [1, 3, 1], name=name, strides=[1, strides, 1], **kwargs)
        if residual:
            x = inputs + x
        return x

After Change

        
        num_filters = int(cls.num_channels(inputs, kwargs.get("data_format")) * expansion_factor * width_factor)

        x = conv_block(inputs, "cna", num_filters, kernel_size=1, name="%s-exp" % name, strides=1, **kwargs)
        x = depthwise_conv(x, kernel_size=3, strides=strides, padding="same",
                           data_format=kwargs["data_format"], name="%s-depthwise" % name)
        x = conv_block(x, "nacn", filters, kernel_size=1, strides=1, name="%s-down" % name, **kwargs)

        if residual:
            x = inputs + x

Instances