mirror of https://github.com/llvm/torch-mlir
69 lines
2.7 KiB
Python
69 lines
2.7 KiB
Python
# -*- Python -*-
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# This file is licensed under a pytorch-style license
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# See frontends/pytorch/LICENSE for license information.
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import torch
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import torch_mlir
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import collections
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from typing import Tuple, Optional, NamedTuple
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# RUN: %PYTHON %s | npcomp-opt | FileCheck %s
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mb = torch_mlir.ModuleBuilder()
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NT = NamedTuple('NT', [('f1', Optional[torch.Tensor]),
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('f2', Optional[torch.Tensor])])
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# CHECK-LABEL: builtin.func @__torch__.tuple(
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# CHECK-SAME: %[[T0:.*]]: !torch.tensor,
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# CHECK-SAME: %[[T1:.*]]: !torch.tensor) ->
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# CHECK-SAME: !torch.tuple<!torch.tensor, !torch.tensor> {
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# CHECK: %[[RET:.*]] = torch.prim.TupleConstruct %[[T0]], %[[T1]] :
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# CHECK-SAME: !torch.tensor, !torch.tensor -> !torch.tuple<!torch.tensor, !torch.tensor>
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# CHECK: return %[[RET]] : !torch.tuple<!torch.tensor, !torch.tensor>
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@mb.import_function
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@torch.jit.script
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def tuple(t0, t1):
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return t0, t1
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# CHECK-LABEL: builtin.func @__torch__.tuple_optional(
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# CHECK-SAME: %[[T0:.*]]: !torch.tensor,
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# CHECK-SAME: %[[T1:.*]]: !torch.tensor) ->
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# CHECK-SAME: !torch.tuple<!torch.optional<!torch.tensor>, !torch.optional<!torch.tensor>> {
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# CHECK: %[[TNEW:.*]] = torch.prim.TupleConstruct %[[T0]], %[[T1]] :
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# CHECK-SAME: !torch.tensor, !torch.tensor -> !torch.tuple<!torch.tensor, !torch.tensor>
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# CHECK: %[[RET:.*]] = torch.derefine %[[TNEW]] :
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# CHECK-SAME: !torch.tuple<!torch.tensor, !torch.tensor> to
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# CHECK-SAME: !torch.tuple<!torch.optional<!torch.tensor>, !torch.optional<!torch.tensor>>
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# CHECK: return %[[RET]] : !torch.tuple<!torch.optional<!torch.tensor>, !torch.optional<!torch.tensor>>
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@mb.import_function
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@torch.jit.script
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def tuple_optional(
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t0, t1) -> Tuple[Optional[torch.Tensor], Optional[torch.Tensor]]:
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return t0, t1
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# CHECK-LABEL: builtin.func @__torch__.namedtuple_optional(
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# CHECK-SAME: %[[T0:.*]]: !torch.tensor,
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# CHECK-SAME: %[[T1:.*]]: !torch.tensor) ->
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# CHECK-SAME: !torch.tuple<!torch.optional<!torch.tensor>, !torch.optional<!torch.tensor>> {
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# CHECK: %[[RET:.*]] = torch.prim.TupleConstruct %[[T0]], %[[T1]] :
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# CHECK-SAME: !torch.tensor, !torch.tensor ->
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# CHECK-SAME: !torch.tuple<!torch.optional<!torch.tensor>, !torch.optional<!torch.tensor>>
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# CHECK: return %[[RET]] : !torch.tuple<!torch.optional<!torch.tensor>, !torch.optional<!torch.tensor>>
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# CHECK: }
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#
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@mb.import_function
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@torch.jit.script
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def namedtuple_optional(
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t0, t1) -> Tuple[Optional[torch.Tensor], Optional[torch.Tensor]]:
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return NT(t0, t1)
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mb.module.operation.print()
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print()
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