wehub-resource-sync
56 lines
1.3 KiB
Python
56 lines
1.3 KiB
Python
# Copyright (c) Microsoft Corporation.
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# SPDX-License-Identifier: Apache-2.0
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# DeepSpeed Team
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import torch
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import random
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from deepspeed.runtime.sparse_tensor import SparseTensor
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def test_csr_addition_self():
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row_count = 10
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random.seed(1234)
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x = torch.ones(1, 5)
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for i in range(row_count - 1):
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if random.random() > 0.75:
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x = torch.cat([x, torch.ones(1, 5)])
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else:
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x = torch.cat([x, torch.zeros(1, 5)])
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dense_x = x.clone()
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cx = SparseTensor(x)
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assert torch.all(dense_x == cx.to_dense())
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cx.add(cx)
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assert torch.all(dense_x + dense_x == cx.to_dense())
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def test_csr_addition_different():
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row_count = 10
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random.seed(1234)
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x = torch.ones(1, 5)
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for i in range(row_count - 1):
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if random.random() > 0.75:
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x = torch.cat([x, torch.ones(1, 5)])
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else:
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x = torch.cat([x, torch.zeros(1, 5)])
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dense_x = x.clone()
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cx = SparseTensor(x)
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y = torch.ones(1, 5)
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for i in range(row_count - 1):
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if random.random() > 0.75:
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y = torch.cat([y, torch.ones(1, 5)])
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else:
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y = torch.cat([y, torch.zeros(1, 5)])
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dense_y = y.clone()
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cy = SparseTensor(y)
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dense_sum = dense_x + dense_y
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cx.add(cy)
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assert torch.all(dense_sum == cx.to_dense())
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