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68 lines
1.8 KiB
Python
68 lines
1.8 KiB
Python
import torch
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from refiners.fluxion.layers.basics import Slicing
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def test_slicing_positive_indices() -> None:
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x = torch.randn(5, 5, 5)
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slicing_layer = Slicing(dim=0, start=2, end=5)
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sliced = slicing_layer(x)
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expected = x[2:5, :]
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assert torch.equal(sliced, expected)
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def test_slicing_negative_indices() -> None:
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x = torch.randn(5, 5, 5)
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slicing_layer = Slicing(dim=1, start=-3, end=-1)
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sliced = slicing_layer(x)
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expected = x[:, -3:-1]
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assert torch.equal(sliced, expected)
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def test_slicing_step() -> None:
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x = torch.randn(5, 5, 5)
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slicing_layer = Slicing(dim=1, start=0, end=5, step=2)
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sliced = slicing_layer(x)
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expected = x[:, 0:5:2]
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assert torch.equal(sliced, expected)
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def test_slicing_empty_slice():
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x = torch.randn(5, 5, 5)
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slicing_layer = Slicing(dim=1, start=3, end=3)
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sliced = slicing_layer(x)
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expected = x[:, 3:3]
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assert torch.equal(sliced, expected)
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def test_slicing_full_dimension():
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x = torch.randn(5, 5, 5)
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slicing_layer = Slicing(dim=2, start=0, end=5)
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sliced = slicing_layer(x)
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expected = x[:, :, :]
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assert torch.equal(sliced, expected)
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def test_slicing_step_greater_than_range():
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x = torch.randn(5, 5, 5)
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slicing_layer = Slicing(dim=1, start=1, end=3, step=4)
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sliced = slicing_layer(x)
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expected = x[:, 1:3:4]
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assert torch.equal(sliced, expected)
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def test_slicing_reversed_start_end():
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x = torch.randn(5, 5, 5)
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slicing_layer = Slicing(dim=1, start=4, end=2)
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sliced = slicing_layer(x)
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expected = x[:, 4:2]
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assert torch.equal(sliced, expected)
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def test_slicing_out_of_bounds_indices():
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x = torch.randn(5, 5, 5)
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slicing_layer = Slicing(dim=1, start=-10, end=10)
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sliced = slicing_layer(x)
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expected = x[:, -10:10]
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assert torch.equal(sliced, expected)
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