Great work on this library so far! I've been using it for a couple of weeks while implementing the PointNet model for 3d point cloud segmentation. Although I have 2 working implementations in Tensorflow and Torch for Python, I'd rather work in the .Net environ.
The Pointnet model has required extending Tensorflow.Net on a couple of fronts (of which I will check in after testing). New initializers (Constant), regularizers (OrthogonalRegularizer), and now an unimplemented keras.layer in the merging namespace. This would be keras.layers.Dot
The current keras.layers.reshape throws unimplemented for shapes where the second dimension is 'None' or Unknown in tensorflow.net. Looking here for any deeper reasons I can't create the Dot merge layer (inherit from Layer) considering my input tensors are None,None,3 and None,3,3 with an output of None,None,3 after the dot product merge operation. Was looking at linalg.tensordot but that does not support these batch unknown shapes.
Description
Hello,
Great work on this library so far! I've been using it for a couple of weeks while implementing the PointNet model for 3d point cloud segmentation. Although I have 2 working implementations in Tensorflow and Torch for Python, I'd rather work in the .Net environ.
The Pointnet model has required extending Tensorflow.Net on a couple of fronts (of which I will check in after testing). New initializers (Constant), regularizers (OrthogonalRegularizer), and now an unimplemented keras.layer in the merging namespace. This would be keras.layers.Dot
The current keras.layers.reshape throws unimplemented for shapes where the second dimension is 'None' or Unknown in tensorflow.net. Looking here for any deeper reasons I can't create the Dot merge layer (inherit from Layer) considering my input tensors are None,None,3 and None,3,3 with an output of None,None,3 after the dot product merge operation. Was looking at linalg.tensordot but that does not support these batch unknown shapes.
inputs [Unknown,Unknown,3] transformed_features [None,3,3]
returns [None,None,3] layers.Dot(axes = (2, 1))([inputs, transformed_features])
Looking to add more features to this project as I work with models that supersede this one... PointNet++ and PointNeXt over the coming weeks.
Thanks!
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