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Better numpy compatibility #48

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merged 9 commits into from
Oct 16, 2023
Merged

Better numpy compatibility #48

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d267b2b
:art: lessen dependencies
Oct 14, 2023
8a3cbfe
:fire: remove py3.5 tests
Oct 14, 2023
aa95a04
texmex-python as extra package
Oct 14, 2023
ebaceca
cannot installed with python3.10
Oct 14, 2023
ac2960d
:star: fix to be able to use recent numpy
Oct 14, 2023
08bd4e1
:star: test with recent python
Oct 14, 2023
501db9f
3.11 is not yet supported
Oct 14, 2023
183236e
Merge branch 'master' into feature/numpy_compatibility
Hi-king Oct 15, 2023
9b1ea0e
not yet compatible with 3.10
Hi-king Oct 16, 2023
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2 changes: 1 addition & 1 deletion .github/workflows/test.yml
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Expand Up @@ -13,7 +13,7 @@ jobs:
max-parallel: 3
matrix:
platform: [ubuntu-latest]
python-version: ["3.7", "3.8", "3.9"]
python-version: ["3.7", "3.8", "3.9", "3.10"] # 3.11 is not yet supported

steps:
- uses: actions/checkout@v2
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6 changes: 3 additions & 3 deletions pqkmeans/encoder/pq_encoder.py
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Expand Up @@ -22,9 +22,9 @@ def fit(self, x_train):
self.Ds = int(D / self.M)
assert self.trained_encoder is None, "fit must be called only once"

codewords = numpy.zeros((self.M, self.Ks, self.Ds), dtype=numpy.float)
codewords = numpy.zeros((self.M, self.Ks, self.Ds), dtype=float)
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I wasn't aware that the numpy.float style has been deprecated!

for m in range(self.M):
x_train_sub = x_train[:, m * self.Ds: (m + 1) * self.Ds].astype(numpy.float)
x_train_sub = x_train[:, m * self.Ds: (m + 1) * self.Ds].astype(float)
codewords[m], _ = kmeans2(x_train_sub, self.Ks, iter=self.iteration, minit='points')
self.trained_encoder = TrainedPQEncoder(codewords, self.code_dtype)

Expand Down Expand Up @@ -66,7 +66,7 @@ def decode_multi(self, codes):
assert M == self.M
assert codes.dtype == self.code_dtype

decoded = numpy.empty((N, self.Ds * self.M), dtype=numpy.float)
decoded = numpy.empty((N, self.Ds * self.M), dtype=float)
for m in range(self.M):
decoded[:, m * self.Ds: (m + 1) * self.Ds] = self.codewords[m][codes[:, m], :]
return decoded
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