transformer.py 文件源码

def get_padding_type(kernel_params, input_shape, output_shape):
    '''Translates Caffe's numeric padding to one of ('SAME', 'VALID').
    Caffe supports arbitrary padding values, while TensorFlow only
    supports 'SAME' and 'VALID' modes. So, not all Caffe paddings
    can be translated to TensorFlow. There are some subtleties to
    how the padding edge-cases are handled. These are described here:
    https://github.com/Yangqing/caffe2/blob/master/caffe2/proto/caffe2_legacy.proto
    '''
    k_h, k_w, s_h, s_w, p_h, p_w = kernel_params
    s_o_h = np.ceil(input_shape.height / float(s_h))
    s_o_w = np.ceil(input_shape.width / float(s_w))
    if (output_shape.height == s_o_h) and (output_shape.width == s_o_w):
        return 'SAME'
    v_o_h = np.ceil((input_shape.height - k_h + 1.0) / float(s_h))
    v_o_w = np.ceil((input_shape.width - k_w + 1.0) / float(s_w))
    if (output_shape.height == v_o_h) and (output_shape.width == v_o_w):
        return 'VALID'
    return None