anirudh2290 commented on a change in pull request #14150: Fix entropy for uint8
URL: https://github.com/apache/incubator-mxnet/pull/14150#discussion_r262300597
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File path: tests/python/quantization/test_quantization.py
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@@ -673,8 +673,9 @@ def test_optimal_threshold_adversarial_case():
# The worst case for the optimal_threshold function is when the values are
concentrated
# at one edge: [0, 0, ..., 1000]. (histogram)
# We want to make sure that the optimal threshold in this case is the max.
- arr = np.array([2]*1000)
- res = mx.contrib.quant._get_optimal_threshold(arr, num_quantized_bins=5)
+ arr = np.array([2] * 1000)
+ for dtype in ['uint8', 'int8', 'auto']:
+ res = mx.contrib.quant._get_optimal_threshold(arr, dtype,
num_quantized_bins=5)
# The threshold should be 2.
assert res[3] - 2 < 1e-5
Review comment:
can we move the assert inside the for loop in this case ?
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