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Use numpy tile instead of matrix (#1170)
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Signed-off-by: zethson <[email protected]>
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Zethson authored May 4, 2024
1 parent a65d3d5 commit 517a9eb
Showing 1 changed file with 1 addition and 2 deletions.
3 changes: 1 addition & 2 deletions dowhy/gcm/stats.py
Original file line number Diff line number Diff line change
@@ -1,7 +1,6 @@
from typing import Callable, List, Optional, Union

import numpy as np
from numpy.matlib import repmat
from scipy import stats
from sklearn.linear_model import LinearRegression

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# baseline_noise_samples.shape[0] * feature_samples.shape[0]. Here, we reduce it to
# batch_size * feature_samples.shape[0]. If the batch_size would be set 1, then each baseline_noise_samples is
# evaluated one by one in a for-loop.
inputs = repmat(feature_samples, batch_size, 1)
inputs = np.tile(feature_samples, (batch_size, 1))
for offset in range(0, baseline_samples.shape[0], batch_size):
# Each batch consist of at most batch_size * feature_samples.shape[0] many samples. If there are multiple
# batches, the offset indicates the index of the current baseline_noise_samples that has not been evaluated yet.
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