mirror of https://github.com/llvm/torch-mlir
73 lines
2.5 KiB
Python
73 lines
2.5 KiB
Python
# Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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# See https://llvm.org/LICENSE.txt for license information.
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# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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# Also available under a BSD-style license. See LICENSE.
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# RUN: %PYTHON %s | FileCheck %s
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import torch
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import torch_mlir
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class TanhModule(torch.nn.Module):
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def forward(self, x):
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return torch.ops.aten.tanh(x)
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tanh_example_input = torch.ones(2, 3)
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# Simplest case: One example argument.
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print(torch_mlir.compile(TanhModule(), tanh_example_input, use_tracing=True))
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# CHECK-LABEL: @forward
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# CHECK: torch.aten.tanh %{{.*}} : !torch.vtensor<[2,3],f32> -> !torch.vtensor<[2,3],f32>
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# Simplest case: Passed as a tuple.
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print(torch_mlir.compile(TanhModule(), (tanh_example_input,), use_tracing=True))
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# CHECK-LABEL: @forward
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# CHECK: torch.aten.tanh %{{.*}} : !torch.vtensor<[2,3],f32> -> !torch.vtensor<[2,3],f32>
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# Simplest case: Passed as a list.
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print(torch_mlir.compile(TanhModule(), [tanh_example_input], use_tracing=True))
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# CHECK-LABEL: @forward
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# CHECK: torch.aten.tanh %{{.*}} : !torch.vtensor<[2,3],f32> -> !torch.vtensor<[2,3],f32>
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# TensorPlaceholder support.
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placeholder = torch_mlir.TensorPlaceholder.like(
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tanh_example_input, dynamic_axes=[1])
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print(torch_mlir.compile(TanhModule(), [placeholder],
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use_tracing=True, ignore_traced_shapes=True))
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# CHECK-LABEL: @forward
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# CHECK: torch.aten.tanh %{{.*}} : !torch.vtensor<[2,?],f32> -> !torch.vtensor<[2,?],f32>
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try:
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# CHECK: `ignore_traced_shapes` requires `use_tracing`
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torch_mlir.compile(TanhModule(), [placeholder], ignore_traced_shapes=True)
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except Exception as e:
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print(e)
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try:
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# CHECK: TensorPlaceholder can only be used with tracing when `ignore_traced_shapes=True`
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torch_mlir.compile(TanhModule(), [placeholder], use_tracing=True)
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except Exception as e:
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print(e)
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class DictModule(torch.nn.Module):
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def forward(self, x):
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return x['a'] * 2.0
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try:
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# CHECK: Only Tensor's, TensorPlaceholder's, or sequences of Tensor's and TensorPlaceholder's are supported as example args for method inputs. Got '{'a': tensor(3.)}'
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torch_mlir.compile(DictModule(), {'a': torch.tensor(3.0)}, use_tracing=True)
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except Exception as e:
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print(e)
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try:
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# CHECK: Only Tensor's, TensorPlaceholder's, or sequences of Tensor's and TensorPlaceholder's are supported as example args for method inputs. Got '{'a': tensor(3.)}'
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torch_mlir.compile(DictModule(), [{'a': torch.tensor(3.0)}], use_tracing=True)
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except Exception as e:
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print(e)
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