Comments (2)
@simleo we are going to make a pull request that will try to fix the CMake file and it already includes all the modifications you have mentioned.
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As of 7b89d5a, these changes have been either integrated, or the problems they solved have been fixed in a different way. Closing
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Related Issues (20)
- Fallback of unsupported args for ONNX
- Load dynamic inputs shapes from ONNX
- Add Tile layer and Broadcast HOT 1
- Allow asymmetric padding in ONNX
- Add the name_id of each layer
- Different training results with Keras and EDDL
- The examples should be intendeed for begineers, not for testing internals.
- Avoid printing to standard output HOT 1
- Support n-dimensional dense HOT 1
- Add preprocessor directives for FPGA
- Download model params are not consistent with keras.
- Problem in deserialization of an ONNX model HOT 1
- Segmentation fault in eddl.forward() with a LSTM layer HOT 3
- non-recurrent LSTM cells with multiple GPUs HOT 1
- Import ONNX file with a different input channel dimension HOT 1
- Import ONNX with low_memory setting HOT 1
- LSTM training fail on single GPU, but not with multiple GPUs HOT 4
- Export to ONNX randomly fails HOT 9
- Import ONNX model from pytorch - LDense only works over 2D tensors (LDense) HOT 6
- Tensor manipulations HOT 9
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