mirror of https://github.com/llvm/torch-mlir
67 lines
1.8 KiB
Python
67 lines
1.8 KiB
Python
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# 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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import torch
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from torch_mlir_e2e_test.torchscript.framework import TestUtils
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from torch_mlir_e2e_test.torchscript.registry import register_test_case
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from torch_mlir_e2e_test.torchscript.annotations import annotate_args, export
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# ==============================================================================
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class ArgmaxModule(torch.nn.Module):
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def __init__(self):
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super().__init__()
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@export
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@annotate_args([
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None,
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([-1, -1], torch.float32, True),
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])
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def forward(self, a):
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return torch.argmax(a)
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@register_test_case(module_factory=lambda: ArgmaxModule())
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def ArgmaxModule_basic(module, tu: TestUtils):
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module.forward(tu.rand(3, 4))
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# ==============================================================================
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class ArgmaxWithDimModule(torch.nn.Module):
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def __init__(self):
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super().__init__()
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@export
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@annotate_args([
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None,
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([-1, -1, -1], torch.float32, True),
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])
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def forward(self, a):
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return torch.argmax(a, dim=1)
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@register_test_case(module_factory=lambda: ArgmaxWithDimModule())
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def ArgmaxModule_with_dim(module, tu: TestUtils):
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module.forward(tu.rand(3, 4, 5))
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# ==============================================================================
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class ArgmaxKeepDimsModule(torch.nn.Module):
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def __init__(self):
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super().__init__()
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@export
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@annotate_args([
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None,
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([-1, -1], torch.float32, True),
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])
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def forward(self, a):
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return torch.argmax(a, 0, True)
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@register_test_case(module_factory=lambda: ArgmaxKeepDimsModule())
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def ArgmaxModule_keepDim(module, tu: TestUtils):
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module.forward(tu.rand(4, 6))
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