TensorSpec encapsulates the specification of a tensor: its dimensions, or "shape" (row‐major), its type (see TensorSpec::getDataType specializations for supported types), its name and port (see "TensorFlow: Large‐Scale Machine Learning on Heterogeneous Distributed Systems", section 4.2, para 2: https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/45166.pdf)
Synopsis
Declared in <llvm/Analysis/TensorSpec.h>
#define SUPPORTED_TENSOR_TYPES(M)Description
Note that the design is motivated by Tensorflow, but it is not intended to be Tensorflow‐specific.
Known tensor types. The left part is the C type, the right is a name we can use to identify the type (to implement TensorSpec equality checks), and to use, if needed, when mapping to an underlying evaluator's type system. The main requirement is that the C type we use has the same size and encoding (e.g. endian‐ness) as the one used by the evaluator.
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