mirror of https://github.com/llvm/torch-mlir
49 lines
1.6 KiB
MLIR
49 lines
1.6 KiB
MLIR
// RUN: npcomp-opt -split-input-file -verify-diagnostics %s -torch-annotate-abi
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// -----
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// CHECK-LABEL: builtin.func @basic_arg_and_ret(
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// CHECK-SAME: attributes {iree.abi = "{\22a\22:[\22f64\22,\22i64\22,\22i1\22],\22r\22:[\22f64\22,\22i64\22,\22i1\22],\22v\22:1}"} {
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builtin.func @basic_arg_and_ret(%arg0: !torch.float, %arg1: !torch.int, %arg2: !torch.bool) -> (!torch.float, !torch.int, !torch.bool) {
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return %arg0, %arg1, %arg2 : !torch.float, !torch.int, !torch.bool
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}
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// -----
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// CHECK-LABEL: builtin.func @list(
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// CHECK-SAME: attributes {iree.abi = "{\22a\22:{{\[\[}}\22py_uniform_list\22,\22f64\22]],\22r\22:[],\22v\22:1}"} {
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builtin.func @list(%arg0: !torch.list<!torch.float>) {
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return
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}
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// -----
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// CHECK-LABEL: builtin.func @tuple(
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// CHECK-SAME: attributes {iree.abi = "{\22a\22:{{\[\[}}\22pytuple\22,\22f64\22,\22i64\22]],\22r\22:[],\22v\22:1}"} {
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builtin.func @tuple(%arg0: !torch.tuple<!torch.float, !torch.int>) {
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return
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}
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// -----
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// CHECK-LABEL: builtin.func @dict(
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// CHECK-SAME: attributes {iree.abi = "{\22a\22:{{\[\[}}\22py_uniform_dict\22,\22pystr\22,\22f64\22]],\22r\22:[],\22v\22:1}"} {
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builtin.func @dict(%arg0: !torch.dict<!torch.str, !torch.float>) {
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return
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}
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// -----
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// CHECK-LABEL: builtin.func @tensor(
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// CHECK-SAME: attributes {iree.abi = "{\22a\22:{{\[\[}}\22ndarray\22,\22f32\22,2,null,3]],\22r\22:[],\22v\22:1}"} {
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builtin.func @tensor(%arg0: !torch.tensor<[?,3],f32>) {
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return
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}
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// -----
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// expected-error @+1 {{at function argument 0: unimplemented: ABI annotation for type '!torch.any'}}
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builtin.func @unsupported(%arg0: !torch.any) {
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return
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}
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