Input channels limitation <= 128?

I've been told there is the limitation of <= 128 channels per input, could you please clarify?

I'm getting this message during the conversion using rknn-toolkit-1.3.3rc9.

W Channels(256) of input node: input_0> 128, mean/std values ​​will be set to default 0/1.
W Please do pre-processing manually before inference.
W Input channel 2 less then 3, please update NPU Driver to v1 .3.0 or later.
W Channels(512) of input node: input_3> 128, mean/std values ​​will be set to default 0/1.
W Please do pre-processing manually before inference.

After the conversion I have an *.rknn model which is probably not valid, because it's not running on a device.

Our model inputs are the following.

1) name: input_imgs
type: float32[1,12,128,256]

2) name: desire
type: float32[1,8]

3) name: traffic_convention
type: float32[1,2]

4) name: rnn_state
type: float32[1,512]

But converting Inception_ResNet_V2 or Inception_V4 that also have an input> 128 channels doesn't give any error.

name: input
type: float32[1,299,299,3]

https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_resnet_v2_2018_04_27.tgz
https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427 /inception_v4_2018_04_27.tgz