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eff0898a13
Summary: Pull Request resolved: https://github.com/facebookresearch/faiss/pull/3966 This actually enables the linting. Manual changes: - tools/arcanist/lint/fbsource-licenselint-config.toml - tools/arcanist/lint/fbsource-lint-engine.toml Automated changes: `arc lint --apply-patches --take LICENSELINT --paths-cmd 'hg files faiss'` Reviewed By: asadoughi Differential Revision: D64484165 fbshipit-source-id: 4f2f6e953c94ef6ebfea8a5ae035ccfbea65ed04
54 lines
1.0 KiB
Python
54 lines
1.0 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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#
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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"""
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This contrib module contains Pytorch code for quantization.
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"""
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import numpy as np
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import torch
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import faiss
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from faiss.contrib import torch_utils
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class Quantizer:
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def __init__(self, d, code_size):
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self.d = d
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self.code_size = code_size
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def train(self, x):
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pass
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def encode(self, x):
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pass
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def decode(self, x):
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pass
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class VectorQuantizer(Quantizer):
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def __init__(self, d, k):
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code_size = int(torch.ceil(torch.log2(k) / 8))
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Quantizer.__init__(d, code_size)
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self.k = k
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def train(self, x):
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pass
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class ProductQuantizer(Quantizer):
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def __init__(self, d, M, nbits):
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code_size = int(torch.ceil(M * nbits / 8))
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Quantizer.__init__(d, code_size)
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self.M = M
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self.nbits = nbits
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def train(self, x):
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pass
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