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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/01/25 23:47:51 UTC

[GitHub] ChaiBapchya edited a comment on issue #13965: mxnet_coreml_converter unsupported type error

ChaiBapchya edited a comment on issue #13965: mxnet_coreml_converter unsupported type error
URL: https://github.com/apache/incubator-mxnet/issues/13965#issuecomment-457773097
 
 
   @matthewberryman 
   
   _Short answer_ - op variable needs to contain layers that are in MXNET_LAYER_REGISTRY
   
   Why?
   _Long answer_ -
   Upon digging in the file https://github.com/apache/incubator-mxnet/blob/master/tools/coreml/converter/_mxnet_converter.py
   
   I found that : Most likely reason why it's giving `unsupported type error` is because in your __image-classification-symbol.json__
   ```
   "op" : "_copy"
   ```
   is mentioned
   
   Your error is thrown because of this line 
   https://github.com/apache/incubator-mxnet/blob/5dc138d95f6ac302e3f0e1c9dc9dcb774d83f69e/tools/coreml/converter/_mxnet_converter.py#L98
   
   which is triggered when the layer variable isn't part of the MXNet layer registry (i.e. permissible layers)
   https://github.com/apache/incubator-mxnet/blob/5dc138d95f6ac302e3f0e1c9dc9dcb774d83f69e/tools/coreml/converter/_mxnet_converter.py#L95
   
   Permissible layers are
   https://github.com/apache/incubator-mxnet/blob/5dc138d95f6ac302e3f0e1c9dc9dcb774d83f69e/tools/coreml/converter/_mxnet_converter.py#L28
   ```
       'FullyConnected' : _layers.convert_dense,
       'Activation'     : _layers.convert_activation,
       'SoftmaxOutput'  : _layers.convert_softmax,
       'Convolution'    : _layers.convert_convolution,
       'Pooling'        : _layers.convert_pooling,
       'Flatten'        : _layers.convert_flatten,
       'transpose'      : _layers.convert_transpose,
       'Concat'         : _layers.convert_concat,
       'BatchNorm'      : _layers.convert_batchnorm,
       'elemwise_add'   : _layers.convert_elementwise_add,
       'Reshape'        : _layers.convert_reshape,
       'Deconvolution'  : _layers.convert_deconvolution,
   ```
   
   Hope this helps.
   
   Solution - Use only above permitted layers.

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