torch-mlir/test/Dialect/Torch/invalid.mlir

172 lines
4.5 KiB
MLIR

// RUN: npcomp-opt <%s -split-input-file -verify-diagnostics
// -----
torch.class_type @c {}
%0 = torch.nn_module {
// expected-error @+1 {{'builtin.func' op is not allowed inside 'torch.nn_module'}}
builtin.func @f()
} : !torch.nn.Module<"c">
// -----
torch.class_type @c {}
%c0 = torch.constant.int 0
// expected-error @+1 {{number of 'torch.slot's in a 'torch.nn_module' must match number of 'torch.attr's in the corresponding 'torch.class_type'}}
%0 = torch.nn_module {
torch.slot "f", %c0 : !torch.int
} : !torch.nn.Module<"c">
// -----
torch.class_type @c {
// expected-note @+1 {{see torch.attr at corresponding index 0 here}}
torch.attr "g" : !torch.int
}
%c0 = torch.constant.int 0
%0 = torch.nn_module {
// expected-error @+1 {{'torch.slot' op is expected to match type and name of 'torch.attr "g" : !torch.int'}}
torch.slot "f", %c0 : !torch.int
} : !torch.nn.Module<"c">
// -----
torch.class_type @c {
// expected-error @+1 {{'builtin.func' op is not allowed inside `torch.class_type`}}
builtin.func @f()
}
// -----
// expected-error @+1 {{has duplicate attr/method with name 'a'}}
torch.class_type @c {
// expected-note @+1 {{see first conflicting attr/method here}}
torch.attr "a" : !torch.int
// expected-note @+1 {{see second conflicting attr/method here}}
torch.attr "a" : !torch.int
}
// -----
torch.class_type @c {
// expected-error @+1 {{'@invalidSym' does not reference a valid function}}
torch.method "f", @invalidSym
}
// -----
torch.class_type @c {
// expected-error @+1 {{'@f' must reference a private function}}
torch.method "f", @f
}
builtin.func @f(%arg0: !torch.nn.Module<"c">) {
return
}
// -----
torch.class_type @c {
// expected-error @+1 {{'@f' must reference a function that is defined (not merely declared)}}
torch.method "f", @f
}
builtin.func private @f(%arg0: !torch.nn.Module<"c">)
// -----
builtin.func private @f() {
return
}
torch.class_type @c {
// expected-error @+1 {{the referenced function 'f' must have a first argument of type '!torch.nn.Module<"c">'}}
torch.method "f", @f
}
// -----
builtin.func private @f(!torch.nn.Module<"other_c">) {
return
}
torch.class_type @c {
// expected-error @+1 {{the referenced function 'f' must have a first argument of type '!torch.nn.Module<"c">'}}
torch.method "f", @f
}
// -----
// expected-error @+1 {{'a' does not reference a valid class type}}
%m = torch.nn_module {} : !torch.nn.Module<"a">
// -----
// expected-error @+1 {{'torch.type_bound' must be attached to an argument of !torch.tensor/!torch.vtensor type}}
builtin.func @f(%arg0: i32 {torch.type_bound = !torch.tensor<*,f32>})
// -----
// expected-error @+1 {{'torch.type_bound' must be TypeAttr}}
builtin.func @f(%arg0: i32 {torch.type_bound = 1})
// -----
// expected-error @+1 {{'torch.type_bound' must be of !torch.tensor/!torch.vtensor type}}
builtin.func @f(%arg0: i32 {torch.type_bound = i32})
// -----
builtin.func @derefine(%arg0: !torch.optional<!torch.tensor>) -> !torch.tensor {
// expected-error @+1 {{operand type '!torch.optional<!torch.tensor>' and result type '!torch.tensor' are cast incompatible}}
%0 = torch.derefine %arg0 : !torch.optional<!torch.tensor> to !torch.tensor
return %0 : !torch.tensor
}
// -----
builtin.func @torch.prim.unchecked_cast$invalid_types(%arg0: !torch.tensor) -> !torch.optional<!torch.tensor> {
// expected-error @+1 {{operand type '!torch.tensor' and result type '!torch.optional<!torch.tensor>' are cast incompatible}}
%0 = torch.prim.unchecked_cast %arg0 : !torch.tensor -> !torch.optional<!torch.tensor>
return %0 : !torch.optional<!torch.tensor>
}
// -----
// expected-error @+1 {{invalid dtype 'tuple<>' for !torch.tensor type}}
builtin.func private @tensor.invalid_dtype() -> !torch.tensor<*,tuple<>>
// -----
builtin.func @torch.tensor() {
// Incompatible shape.
// expected-error@+1 {{incompatible}}
%0 = torch.tensor.literal(dense<42.0> : tensor<3x2xf32>) : !torch.vtensor<[],f32>
return
}
// -----
builtin.func @torch.tensor() {
// Incompatible dtype.
// expected-error@+1 {{incompatible}}
%0 = torch.tensor.literal(dense<42.0> : tensor<f32>) : !torch.vtensor<[],f64>
return
}
// -----
builtin.func @torch.tensor() {
// Incompatible type.
// expected-error@+1 {{incompatible}}
%0 = torch.tensor.literal(dense<42.0> : tensor<f32>) : i1
return
}
// -----
builtin.func @torch.prim.ListConstruct() {
%int2 = torch.constant.int 2
// expected-error@+1 {{operand types should have the same type as the list contained type}}
torch.prim.ListConstruct %int2 : (!torch.int) -> !torch.list<!torch.tensor>
return
}