mirror of https://github.com/llvm/torch-mlir
146 lines
4.2 KiB
Python
146 lines
4.2 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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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 IndexSelectSingleIdxModule(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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([4, 5, 6], torch.float32, True),
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([1], torch.int64, True),
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])
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def forward(self, input, indices):
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return torch.index_select(input, 1, indices)
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@register_test_case(module_factory=lambda: IndexSelectSingleIdxModule())
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def IndexSelectSingleIdxModule_basic(module, tu: TestUtils):
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module.forward(torch.randn(4, 5, 6), torch.tensor([2]))
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class IndexSelectTwoIdxModule(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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([4, 5, 6], torch.float32, True),
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([2], torch.int64, True),
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])
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def forward(self, input, indices):
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return torch.index_select(input, 2, indices)
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@register_test_case(module_factory=lambda: IndexSelectTwoIdxModule())
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def IndexSelectTwoIdxModule_basic(module, tu: TestUtils):
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module.forward(torch.randn(4, 5, 6), torch.tensor([2, 4]))
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class IndexSelectWholeDimensionModule(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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([4, 5, 6], torch.float32, True),
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([4], torch.int64, True),
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])
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def forward(self, input, indices):
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return torch.index_select(input, 0, indices)
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@register_test_case(module_factory=lambda: IndexSelectWholeDimensionModule())
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def IndexSelectWholeDimensionModule_basic(module, tu: TestUtils):
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module.forward(torch.randn(4, 5, 6), torch.tensor([0, 1, 2, 3]))
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class IndexSelectWholeTensorModule(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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([3], torch.float32, True),
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([3], torch.int64, True),
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])
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def forward(self, input, indices):
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return torch.index_select(input, 0, indices)
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@register_test_case(module_factory=lambda: IndexSelectWholeTensorModule())
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def IndexSelectWholeTensorModule_basic(module, tu: TestUtils):
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module.forward(torch.randn(3), torch.tensor([0, 1, 2]))
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class IndexSelectDynamicModule(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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([-1], torch.int64, True),
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])
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def forward(self, input, indices):
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return torch.index_select(input, 2, indices)
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@register_test_case(module_factory=lambda: IndexSelectDynamicModule())
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def IndexSelectDynamicModulebasic(module, tu: TestUtils):
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module.forward(torch.randn(4, 5, 6), torch.tensor([0, 4]))
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class IndexSelectDynamicInputSizeModule(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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([2], torch.int64, True),
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])
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def forward(self, input, indices):
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return torch.index_select(input, 2, indices)
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@register_test_case(module_factory=lambda: IndexSelectDynamicInputSizeModule())
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def IndexSelectDynamicInputSizeModule_basic(module, tu: TestUtils):
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module.forward(torch.randn(4, 5, 6), torch.tensor([0, 2]))
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class IndexSelectDynamicIndexSizeModule(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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([4, 5, 6], torch.float32, True),
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([-1], torch.int64, True),
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])
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def forward(self, input, indices):
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return torch.index_select(input, 1, indices)
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@register_test_case(module_factory=lambda: IndexSelectDynamicIndexSizeModule())
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def IndexSelectDynamicIndexSizeModule_basic(module, tu: TestUtils):
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module.forward(torch.randn(4, 5, 6), torch.tensor([1, 2]))
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