# Test that expansion of ONNX operators that are functions works for a simple
# example. The exact name mangling scheme used is not matched against, all that
# matters is that it has the name of the operator (GreaterOrEqual here) in it.
# Attributes are also not checked here. What we are interested in is the types
# and operations.
#
# The model comes from an upstream ONNX test: backend/test/data/node/test_greater_equal/model.onnx

# RUN: %PYTHON -m torch_mlir.tools.import_onnx --disable-function-expansion-allowlist %s.onnx | FileCheck %s

# CHECK-LABEL: func.func @test_greater_equal(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1>
# CHECK:         %0 = call @"{{.*}}GreaterOrEqual{{.*}}"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1>

# CHECK-LABEL: func.func private @"{{.*}}GreaterOrEqual{{.*}}"(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1>
# CHECK:         %0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1>
# CHECK:         %1 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1>
# CHECK:         %2 = torch.operator "onnx.Or"(%0, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1>
# CHECK:         return %2 : !torch.vtensor<[3,4,5],i1>