coreml - Fail to convert Caffe model to Core ML model -


when try convert model caffe core ml model coremltools, following:

================= starting conversion caffe coreml ====================== layer 0: type: 'data', name: 'data'. output(s): 'data', 'label'. warning: skipping data layer 'data' of type 'data'. recommended use input layer deployment. layer 1: type: 'split', name: 'label_data_1_split'. input(s): 'label'. output(s): 'label_data_1_split_0', 'label_data_1_split_1'. layer 2: type: 'convolution', name: 'conv1'. input(s): 'data'. output(s): 'conv1'. layer 3: type: 'slice', name: 'slice1'. input(s): 'conv1'. output(s): 'slice1_1', 'slice1_2'. layer 4: type: 'eltwise', name: 'etlwise1'. input(s): 'slice1_1', 'slice1_2'. output(s): 'eltwise1'. traceback (most recent call last):   file "test.py", line 2, in <module>     coreml_model = coremltools.converters.caffe.convert('_iter_3560000.caffemodel')   file "/users/zfh/desktop/face_verification_experiment/model/python27/lib/python2.7/site-packages/coremltools/converters/caffe/_caffe_converter.py", line 142, in convert     predicted_feature_name)   file "/users/zfh/desktop/face_verification_experiment/model/python27/lib/python2.7/site-packages/coremltools/converters/caffe/_caffe_converter.py", line 187, in _export     predicted_feature_name runtimeerror: unsupported option 'max' parameter 'operation' in layer 'etlwise1' of type 'elementwise' during caffe conversion.

this code using:

import coremltools coreml_model = coremltools.converters.caffe.convert(('_iter_3560000.caffemodel', 'lcnn_deploy.prototxt'))  coreml_model.save('_iter_3560000.mlmodel')

any ideas problem is? thank much!

as error message says, problem max operation in eltwise layer not supported coremltools. core ml supports limited number of layers.

however... seems maybe you're trying convert .prototxt used training (even though filename lcnn_deploy.prototxt). sure correct deploy.prototxt?


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