convert the ckpt model to movidius graph

[zhanghanbin3159]

when I convert the ckpt model to movidius graph, I meet the problem: InvalidArgumentError (see above for traceback): Number of ways to split should evenly divide the split dimension, but got split_dim 3 (size = 224) and num_split 3 [[Node: Validation/Validation/Processing/split = Split[T=DT_FLOAT, num_split=3, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Validation/Validation/Processing/split/split_dim, Validation/ExpandDims)]]」

then I find the code in tensorflow split_op.cc OP_REQUIRES(context, input_shape.dim_size(split_dim) % num_split == 0, errors::InvalidArgument( "Number of ways to split should evenly divide the split " "dimension, but got split_dim ", split_dim, " (size = ", input_shape.dim_size(split_dim), ") ", "and num_split ", num_split));

I read code in KittiSeg/submodules/tensorflow-fcn/fcn8_vgg.py , the following code execute "tf.split()" function.

     red, green, blue = tf.split(rgb, 3, 3)

assert red.get_shape().as_list()[1:] == [224, 224, 1]

assert green.get_shape().as_list()[1:] == [224, 224, 1]

assert blue.get_shape().as_list()[1:] == [224, 224, 1]

bgr = tf.concat([ blue - VGG_MEAN[0], green - VGG_MEAN[1], red - VGG_MEAN[2], ], 3)

this code means the image channels which divided by 3, but the log shows 224 divided 3 , so 224%3 != 0.

[zhanghanbin3159]

@MarvinTeichmann