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author | Taehoon Lee <me@taehoonlee.com> | 2018-07-24 20:18:51 +0900 |
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committer | Taehoon Lee <me@taehoonlee.com> | 2018-07-24 20:18:51 +0900 |
commit | 6f776c78f8824b962a00898eee8277104f978e94 (patch) | |
tree | 0d6f9108c3445dec8792afe091cb3b26bff629ff /tensorflow/contrib/distributions | |
parent | c21078f527023e3074b63109fb768413f82a8f8f (diff) |
Fix typos
Diffstat (limited to 'tensorflow/contrib/distributions')
-rw-r--r-- | tensorflow/contrib/distributions/python/ops/sample_stats.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/contrib/distributions/python/ops/sample_stats.py b/tensorflow/contrib/distributions/python/ops/sample_stats.py index f5aaa5cf34..aa680a92be 100644 --- a/tensorflow/contrib/distributions/python/ops/sample_stats.py +++ b/tensorflow/contrib/distributions/python/ops/sample_stats.py @@ -134,7 +134,7 @@ def auto_correlation( x_len = util.prefer_static_shape(x_rotated)[-1] # TODO(langmore) Investigate whether this zero padding helps or hurts. At - # the moment is is necessary so that all FFT implementations work. + # the moment is necessary so that all FFT implementations work. # Zero pad to the next power of 2 greater than 2 * x_len, which equals # 2**(ceil(Log_2(2 * x_len))). Note: Log_2(X) = Log_e(X) / Log_e(2). x_len_float64 = math_ops.cast(x_len, np.float64) @@ -198,7 +198,7 @@ def auto_correlation( # Recall R[m] is a sum of N / 2 - m nonzero terms x[n] Conj(x[n - m]). The # other terms were zeros arising only due to zero padding. # `denominator = (N / 2 - m)` (defined below) is the proper term to - # divide by by to make this an unbiased estimate of the expectation + # divide by to make this an unbiased estimate of the expectation # E[X[n] Conj(X[n - m])]. x_len = math_ops.cast(x_len, dtype.real_dtype) max_lags = math_ops.cast(max_lags, dtype.real_dtype) |