torch-mlir/test/Dialect/Torch/prepare-for-globalize-objec...

33 lines
1.7 KiB
MLIR

// RUN: npcomp-opt -torch-prepare-for-globalize-object-graph -split-input-file %s | FileCheck %s
torch.class_type @c {
torch.method "test_call_method", @test_call_method
torch.method "test_call_indirect", @test_call_indirect
}
// CHECK-LABEL: func private @test_call_method(
// CHECK-SAME: %[[RECEIVER:.*]]: !torch.nn.Module<"c">,
// CHECK-SAME: %[[F:.*]]: !torch.float) -> !torch.float {
// CHECK: %[[RET:.*]] = call @test_call_method(%[[RECEIVER]], %[[F]]) : (!torch.nn.Module<"c">, !torch.float) -> !torch.float
// CHECK: return %[[RET]] : !torch.float
func private @test_call_method(%arg0: !torch.nn.Module<"c">, %arg1: !torch.float) -> !torch.float {
%0 = torch.prim.CallMethod %arg0["test_call_method"] (%arg1) : !torch.nn.Module<"c">, (!torch.float) -> !torch.float
return %0 : !torch.float
}
// CHECK-LABEL: func private @test_call_indirect(
// CHECK-SAME: %[[RECEIVER:.*]]: !torch.nn.Module<"c">,
// CHECK-SAME: %[[F:.*]]: !torch.float) -> !torch.float {
// Ensure no std.constant.
// CHECK-NEXT: %[[VAL_2:.*]] = call @test_call_method(%[[RECEIVER]], %[[F]]) : (!torch.nn.Module<"c">, !torch.float) -> !torch.float
// CHECK-NEXT: return %[[VAL_2]] : !torch.float
func private @test_call_indirect(%arg0: !torch.nn.Module<"c">, %arg1: !torch.float) -> !torch.float {
%0 = constant @test_call_method : (!torch.nn.Module<"c">, !torch.float) -> !torch.float
%1 = call_indirect %0(%arg0, %arg1) : (!torch.nn.Module<"c">, !torch.float) -> !torch.float
return %1 : !torch.float
}
torch.nn_module {
} : !torch.nn.Module<"c">