37 lines
921 B
Python
37 lines
921 B
Python
import torch, scipy
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import numpy as np
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import argparse
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import time
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parser = argparse.ArgumentParser()
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parser.add_argument('matrix_file', help='the input matrix (.mtx) file')
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parser.add_argument('iterations', type=int, help='the number of iterations of multiplication to perform')
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args = parser.parse_args()
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device = 'cpu'
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matrix = scipy.io.mmread(args.matrix_file)
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matrix = torch.sparse_coo_tensor(
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np.vstack((matrix.row, matrix.col)),
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matrix.data, matrix.shape,
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device=device
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).to_sparse_csr().type(torch.float)
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vector = torch.rand(matrix.shape[1], device=device)
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print(matrix)
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print(vector)
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start = time.time()
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for i in range(0, args.iterations):
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torch.sparse.mm(matrix, vector.unsqueeze(-1)).squeeze(-1)
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#print(i)
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end = time.time()
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if matrix.shape[0] == matrix.shape[1]:
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print(f"Shape: {matrix.shape[1]}")
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else:
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print(f"Shape: {matrix.shape}")
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print(f"Time: {end - start} seconds")
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