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The Tensor Computations library provides a succinct and efficient way of writing computations on arrays. It also agnostic to the memory backend. I think we should be able to provide an xnd wrapper, so that memory is allocated in xnd, but can be computed with TC. See https://facebookresearch.github.io/TensorComprehensions/integrating_any_ml_framework.html
We have to be able to attach some metadata to xnd tensors to be able to wrap them in the dlpack format: https://github.com/dmlc/dlpack
The text was updated successfully, but these errors were encountered:
Possibly relevant issue around nesting function computation facebookresearch/TensorComprehensions#56
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The Tensor Computations library provides a succinct and efficient way of writing computations on arrays. It also agnostic to the memory backend. I think we should be able to provide an xnd wrapper, so that memory is allocated in xnd, but can be computed with TC. See https://facebookresearch.github.io/TensorComprehensions/integrating_any_ml_framework.html
We have to be able to attach some metadata to xnd tensors to be able to wrap them in the dlpack format: https://github.com/dmlc/dlpack
The text was updated successfully, but these errors were encountered: