Comments (4)
Can't you just use a merge layer with mode = mul?
http://keras.io/layers/core/#merge
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I mean the Caffe to Keras converter can't process the INNER_PRODUCT layer.If I use other layer to replace it,I don't know how to tranfer the weights in the caffe model to the keras model.
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Can anyone please post instructions how to extend the tool to support currently unsupported layer types?
@Cod1ng - did you try to add support for INNER_PRODUCT yourself?
I am trying to add support for CROP level. This is where I got:
- In file caffe_utils.py: added extra entry in layer_num_to_name
- Tried to modify caffe_pb2.py - added a few extra lines, such as:
_V1LAYERPARAMETER.fields_by_name['crop_param'].message_type = _CROPPARAMETER
DESCRIPTOR.message_types_by_name['CropParameter'] = _CROPPARAMETER
(copy paste from other layers, and changing layer name to crop)
but then noticed this comment at the beginning of the file:
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: caffe.proto
and stopped...
No idea how to regenerate this file, or what protocol buffer compiler is.
Any help would be highly appreciated! @MarcBS - can you help please?
from keras.
The file caffe_pb2.py is generated when you compile the "pycaffe" wrapper for Caffe. You can find it here:
/caffe_root_path/python/caffe/proto/caffe_pb2.py
If you need a newer version of it, you just have to compile the latest version of Caffe by yourself and copy it into the corresponding folder of Keras.
I am sorry for not being able to help you implementing these additional features right now, but you are welcome to submit any PR adding useful features to this library!
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Related Issues (20)
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