From: ManHyuk Date: Sun, 25 Feb 2018 16:09:28 +0000 (+0900) Subject: Fix typo (#17258) X-Git-Tag: upstream/v1.7.0~133 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=26ae3287a12c71fccaec9ea74f55b6a51a3d33c6;p=platform%2Fupstream%2Ftensorflow.git Fix typo (#17258) * fix typo --- diff --git a/tensorflow/contrib/slim/python/slim/data/parallel_reader.py b/tensorflow/contrib/slim/python/slim/data/parallel_reader.py index ad5e985..b3343ae 100644 --- a/tensorflow/contrib/slim/python/slim/data/parallel_reader.py +++ b/tensorflow/contrib/slim/python/slim/data/parallel_reader.py @@ -221,7 +221,7 @@ def parallel_read(data_sources, the data will be cycled through indefinitely. num_readers: a integer, number of Readers to create. reader_kwargs: an optional dict, of kwargs for the reader. - shuffle: boolean, wether should shuffle the files and the records by using + shuffle: boolean, whether should shuffle the files and the records by using RandomShuffleQueue as common_queue. dtypes: A list of types. The length of dtypes must equal the number of elements in each record. If it is None it will default to diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_diag_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_diag_test.py index 343d158..8cb9f9e 100644 --- a/tensorflow/python/kernel_tests/linalg/linear_operator_diag_test.py +++ b/tensorflow/python/kernel_tests/linalg/linear_operator_diag_test.py @@ -129,7 +129,7 @@ class LinearOperatorDiagTest( with self.test_session() as sess: x = random_ops.random_normal(shape=(2, 2, 3, 4)) - # This LinearOperatorDiag will be brodacast to (2, 2, 3, 3) during solve + # This LinearOperatorDiag will be broadcast to (2, 2, 3, 3) during solve # and matmul with 'x' as the argument. diag = random_ops.random_uniform(shape=(2, 1, 3)) operator = linalg.LinearOperatorDiag(diag, is_self_adjoint=True) diff --git a/tensorflow/python/ops/distributions/special_math.py b/tensorflow/python/ops/distributions/special_math.py index bed4cbb..1d605c5 100644 --- a/tensorflow/python/ops/distributions/special_math.py +++ b/tensorflow/python/ops/distributions/special_math.py @@ -213,7 +213,7 @@ def _ndtri(p): # Compute x for p <= exp(-2): x = z - log(z)/z - (1/z) P(1/z) / Q(1/z), # where z = sqrt(-2. * log(p)), and P/Q are chosen between two different - # arrays based on wether p < exp(-32). + # arrays based on whether p < exp(-32). z = math_ops.sqrt(-2. * math_ops.log(sanitized_mcp)) first_term = z - math_ops.log(z) / z second_term_small_p = (_create_polynomial(1. / z, p2) diff --git a/tensorflow/python/ops/linalg/linear_operator_diag.py b/tensorflow/python/ops/linalg/linear_operator_diag.py index b3ec3d5..e180e83 100644 --- a/tensorflow/python/ops/linalg/linear_operator_diag.py +++ b/tensorflow/python/ops/linalg/linear_operator_diag.py @@ -67,7 +67,7 @@ class LinearOperatorDiag(linear_operator.LinearOperator): operator = LinearOperatorDiag(diag) # Create a shape [2, 1, 4, 2] vector. Note that this shape is compatible - # since the batch dimensions, [2, 1], are brodcast to + # since the batch dimensions, [2, 1], are broadcast to # operator.batch_shape = [2, 3]. y = tf.random_normal(shape=[2, 1, 4, 2]) x = operator.solve(y)