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torch-mlir/frontends/pytorch/test/node_import
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Sean Silva 4a0eb44d17 Add a !torch.float type. 
This removes the dependence of the `torch` dialect on the low-level
builtin types.
Now the `torch` dialect is a standalone layer, suitable for targeting
from higher-level Python abstractions without any premature lowering to
primitive types.
 		2021-06-17 09:24:18 -07:00
..
README.md Rename tests to match the code they test 2021-02-25 13:31:33 -08:00
debug-info.py Properly model "derefinement". 2021-03-03 15:09:44 -08:00
elif.py Add `torch.prim.If` 2021-06-16 14:04:31 -07:00
errors.py Properly model "derefinement". 2021-03-03 15:09:44 -08:00
function-derefine.py Add `!torch.int` type. 2021-06-17 07:28:23 -07:00
if.py Add `!torch.int` type. 2021-06-17 07:28:23 -07:00
list.py Add TorchList type and prim::ListConstruct #218 2021-06-10 14:31:35 -07:00
loop.py Add a !torch.float type. 2021-06-17 09:24:18 -07:00
prim.py Add `!torch.int` type. 2021-06-17 07:28:23 -07:00
tuple.py Add `!torch.tuple<T1, T2>` type. 2021-06-15 08:15:22 -07:00
types-bool.py Add `!torch.bool` type. 2021-06-16 13:22:00 -07:00
types-none.py Introduce native `!torch.none` type. 2021-06-14 13:30:58 -07:00

README.md

node_import

Most of the tests in this directory test the importing of TorchScript torch::jit::Graph's.

However, TorchScript graphs don't really correspond directly to anything on the MLIR side. They are a weird combination of a context, builder, and function and just holds a torch::jit::Block. It is torch::jit::Node and torch::jit::Block which form the recursive structure analogous to MLIR's operation/region/block.

  • torch::jit::Node == mlir::Operation,
  • torch::jit::Block == mlir::Region containing single mlir::Block

Hence the name of this directory and the corresponding code in node_importer.h/cpp.