torch-mlir/python/test/annotations-sugar.py

#  Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
#  See https://llvm.org/LICENSE.txt for license information.
#  SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception

# RUN: %PYTHON %s | FileCheck %s

import torch

import torch_mlir
from npcomp_torchscript.annotations import annotate_args, export
from torch_mlir.torchscript_annotations import extract_annotations

class MmModule(torch.nn.Module):
    def __init__(self):
        super().__init__()
    @export
    @annotate_args([
        None,
        ([3, 4], torch.float32, False),
        ([4, 5], torch.float32, True),
    ])
    def forward(self, lhs, rhs):
        return torch.mm(lhs, rhs)

module = MmModule()
annotator = torch_mlir.ClassAnnotator()
extract_annotations(module, torch.jit.script(module), annotator)
print(annotator)

# CHECK: ClassAnnotator {
# CHECK:   ClassAnnotation('__torch__.MmModule') {
# CHECK:     MethodAnnotation('forward') {
# CHECK:       isExported = true
# CHECK:       argAnnotations =
# CHECK:         ArgAnnotation(0) {
# CHECK:           dtype = <none>
# CHECK:           shape = <none>
# CHECK:         }
# CHECK:         ArgAnnotation(1) {
# CHECK:           dtype = Float
# CHECK:           shape = [3, 4]
# CHECK:           hasValueSemantics = false
# CHECK:         }
# CHECK:         ArgAnnotation(2) {
# CHECK:           dtype = Float
# CHECK:           shape = [4, 5]
# CHECK:           hasValueSemantics = true
# CHECK:         }
# CHECK:     }
# CHECK:   }
# CHECK: }