tree 0e1ee5dfe8bb237cc5061ec64573753d2b5e3d48
parent ed14b5da3f7e9105bea3f7314706d04a68969edc
author A. Unique TensorFlower <gardener@tensorflow.org> 1566062388 -0700
committer TensorFlower Gardener <gardener@tensorflow.org> 1566062705 -0700

Add spirv::GlobalVariableOp that allows module level definition of variables

FuncOps in MLIR use explicit capture. So global variables defined in
module scope need to have a symbol name and this should be used to
refer to the variable within the function. This deviates from SPIR-V
spec, which assigns an SSA value to variables at all scopes that can
be used to refer to the variable, which requires SPIR-V functions to
allow implicit capture. To handle this add a new op,
spirv::GlobalVariableOp that can be used to define module scope
variables.
Since instructions need an SSA value, an new spirv::AddressOfOp is
added to convert a symbol reference to an SSA value for use with other
instructions.
This also means the spirv::EntryPointOp instruction needs to change to
allow initializers to be specified using symbol reference instead of
SSA value
The current spirv::VariableOp which returns an SSA value (as defined
by SPIR-V spec) can still be used to define function-scope variables.
PiperOrigin-RevId: 263951109