torch-mlir/e2e_testing/torchscript/index_select.py

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# Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
# See https://llvm.org/LICENSE.txt for license information.
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
# Also available under a BSD-style license. See LICENSE.
import torch
from torch_mlir_e2e_test.torchscript.framework import TestUtils
from torch_mlir_e2e_test.torchscript.registry import register_test_case
from torch_mlir_e2e_test.torchscript.annotations import annotate_args, export
# ==============================================================================
class IndexSelectSingleIdxModule(torch.nn.Module):
def __init__(self):
super().__init__()
@export
@annotate_args([
None,
([4, 5, 6], torch.float32, True),
([1], torch.int64, True),
])
def forward(self, input, indices):
return torch.index_select(input, 1, indices)
@register_test_case(module_factory=lambda: IndexSelectSingleIdxModule())
def IndexSelectSingleIdxModule_basic(module, tu: TestUtils):
module.forward(torch.randn(4, 5, 6), torch.tensor([2]))
class IndexSelectTwoIdxModule(torch.nn.Module):
def __init__(self):
super().__init__()
@export
@annotate_args([
None,
([4, 5, 6], torch.float32, True),
([2], torch.int64, True),
])
def forward(self, input, indices):
return torch.index_select(input, 2, indices)
@register_test_case(module_factory=lambda: IndexSelectTwoIdxModule())
def IndexSelectTwoIdxModule_basic(module, tu: TestUtils):
module.forward(torch.randn(4, 5, 6), torch.tensor([2, 4]))
class IndexSelectWholeDimensionModule(torch.nn.Module):
def __init__(self):
super().__init__()
@export
@annotate_args([
None,
([4, 5, 6], torch.float32, True),
([4], torch.int64, True),
])
def forward(self, input, indices):
return torch.index_select(input, 0, indices)
@register_test_case(module_factory=lambda: IndexSelectWholeDimensionModule())
def IndexSelectWholeDimensionModule_basic(module, tu: TestUtils):
module.forward(torch.randn(4, 5, 6), torch.tensor([0, 1, 2, 3]))
class IndexSelectWholeTensorModule(torch.nn.Module):
def __init__(self):
super().__init__()
@export
@annotate_args([
None,
([3], torch.float32, True),
([3], torch.int64, True),
])
def forward(self, input, indices):
return torch.index_select(input, 0, indices)
@register_test_case(module_factory=lambda: IndexSelectWholeTensorModule())
def IndexSelectWholeTensorModule_basic(module, tu: TestUtils):
module.forward(torch.randn(3), torch.tensor([0, 1, 2]))
class IndexSelectDynamicModule(torch.nn.Module):
def __init__(self):
super().__init__()
@export
@annotate_args([
None,
([-1, -1, -1], torch.float32, True),
([-1], torch.int64, True),
])
def forward(self, input, indices):
return torch.index_select(input, 2, indices)
@register_test_case(module_factory=lambda: IndexSelectDynamicModule())
def IndexSelectDynamicModulebasic(module, tu: TestUtils):
module.forward(torch.randn(4, 5, 6), torch.tensor([0, 4]))
class IndexSelectDynamicInputSizeModule(torch.nn.Module):
def __init__(self):
super().__init__()
@export
@annotate_args([
None,
([-1, -1, -1], torch.float32, True),
([2], torch.int64, True),
])
def forward(self, input, indices):
return torch.index_select(input, 2, indices)
@register_test_case(module_factory=lambda: IndexSelectDynamicInputSizeModule())
def IndexSelectDynamicInputSizeModule_basic(module, tu: TestUtils):
module.forward(torch.randn(4, 5, 6), torch.tensor([0, 2]))
class IndexSelectDynamicIndexSizeModule(torch.nn.Module):
def __init__(self):
super().__init__()
@export
@annotate_args([
None,
([4, 5, 6], torch.float32, True),
([-1], torch.int64, True),
])
def forward(self, input, indices):
return torch.index_select(input, 1, indices)
@register_test_case(module_factory=lambda: IndexSelectDynamicIndexSizeModule())
def IndexSelectDynamicIndexSizeModule_basic(module, tu: TestUtils):
module.forward(torch.randn(4, 5, 6), torch.tensor([1, 2]))