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[Group conv support] ValueError: number of input channels does not match corresponding dimension of filter, 96 != 48 #10
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Hi @seanchung2 . Same problem with xception. Not support Conv with groups now. Will implement it soon. Thanks. |
@seanchung2 master branch enables the groups convolution. Please try it. Thanks. |
Hi @seanchung2 , master branch with following scripts: $ python -m mmdnn.conversion._script.convertToIR -f caffe -d kit_imagenet -n examples/caffe/models/bvlc_alexnet.prototxt -w examples/caffe/models/bvlc_alexnet.caffemodel
$ python -m mmdnn.conversion._script.IRToCode -f tensorflow --IRModelPath kit_imagenet.pb --dstModelPath kit_imagenet.py -w kit_imagenet.npy
$ python -m mmdnn.conversion.examples.tensorflow.imagenet_test -n kit_imagenet.py -w kit_imagenet.npy --dump ./caffe_alexnet.ckpt
Tensorflow file is saved as [./caffe_alexnet.ckpt], generated by [kit_imagenet.py] and [kit_imagenet.npy]. |
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ValueError: number of input channels does not match corresponding dimension of filter, 96 != 48
[Group conv support] ValueError: number of input channels does not match corresponding dimension of filter, 96 != 48
Dec 7, 2017
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Hi,
I converted BVLC_AlexNet from Caffe to IR first. Then converted IR to Tensorflow code snippet in order to use it to get the checkpoint file. But when I tried to test my converted model by executing
python -m mmdnn.conversion.examples.tensorflow.imagenet_test -s tensorflow -p AlexNet -n BVLC_AlexNet -w BVLC_AlexNet.npy
, the error happened below:If you wanna take a look at my converted model, here is the link
Can you please deal with it?
Thanks.
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