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This item represents a container for an additional functionality item and an instance in the vector_normalizer object. It quickly normalizes all inputs before passing them off into the contained function object.
Program calls for features in an effort to execute expected duties. Functions help program developers to easily group their code for much easier debugging and documentation applications.
You may optionally normalize Just about every distance using a consumer equipped scale. One example is, when executing face landmarking, you might want to normalize the distances by the interocular distance.
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Nonetheless, any transfers from the product to your host take place synchronously within the default CUDA stream. Hence, you must accomplish all your CUDA kernel launches to the default stream making sure that transfers back again for the host don't come about prior to the related computations have done.
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This function performs a canonical correlation Assessment among two sets of vectors. On top of that, it's made to be quite quickly, even for giant datasets of more than a million higher dimensional vectors.