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- import numpy as np
- import pytest
- from sklearn.utils._weight_vector import (
- WeightVector32,
- WeightVector64,
- )
- @pytest.mark.parametrize(
- "dtype, WeightVector",
- [
- (np.float32, WeightVector32),
- (np.float64, WeightVector64),
- ],
- )
- def test_type_invariance(dtype, WeightVector):
- """Check the `dtype` consistency of `WeightVector`."""
- weights = np.random.rand(100).astype(dtype)
- average_weights = np.random.rand(100).astype(dtype)
- weight_vector = WeightVector(weights, average_weights)
- assert np.asarray(weight_vector.w).dtype is np.dtype(dtype)
- assert np.asarray(weight_vector.aw).dtype is np.dtype(dtype)
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