From 5fd2a521e49f64eb00e0c9d74cd2e512e6f95833 Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Mon, 17 Apr 2017 17:18:35 -0800 Subject: [PATCH] Update ops-related pbtxt files. Change: 153415587 --- tensorflow/core/ops/ops.pbtxt | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/tensorflow/core/ops/ops.pbtxt b/tensorflow/core/ops/ops.pbtxt index 41353f0ea31..1866a2b4cca 100644 --- a/tensorflow/core/ops/ops.pbtxt +++ b/tensorflow/core/ops/ops.pbtxt @@ -19801,7 +19801,7 @@ op { } } summary: "Computes the maximum along segments of a tensor." - description: "Read [the section on Segmentation](../../api_docs/python/math_ops.md#segmentation)\nfor an explanation of segments.\n\nComputes a tensor such that\n\\\\(output_i = \\max_j(data_j)\\\\) where `max` is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the max is empty for a given segment ID `i`, `output[i] = 0`.\n\n
\n\n
" + description: "Read @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments.\n\nComputes a tensor such that\n\\\\(output_i = \\max_j(data_j)\\\\) where `max` is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the max is empty for a given segment ID `i`, `output[i] = 0`.\n\n
\n\n
" } op { name: "SegmentMean" @@ -19847,7 +19847,7 @@ op { } } summary: "Computes the mean along segments of a tensor." - description: "Read [the section on\nSegmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation\nof segments.\n\nComputes a tensor such that\n\\\\(output_i = \\frac{\\sum_j data_j}{N}\\\\) where `mean` is\nover `j` such that `segment_ids[j] == i` and `N` is the total number of\nvalues summed.\n\nIf the mean is empty for a given segment ID `i`, `output[i] = 0`.\n\n
\n\n
" + description: "Read @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments.\n\nComputes a tensor such that\n\\\\(output_i = \\frac{\\sum_j data_j}{N}\\\\) where `mean` is\nover `j` such that `segment_ids[j] == i` and `N` is the total number of\nvalues summed.\n\nIf the mean is empty for a given segment ID `i`, `output[i] = 0`.\n\n
\n\n
" } op { name: "SegmentMin" @@ -19893,7 +19893,7 @@ op { } } summary: "Computes the minimum along segments of a tensor." - description: "Read [the section on\nSegmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation\nof segments.\n\nComputes a tensor such that\n\\\\(output_i = \\min_j(data_j)\\\\) where `min` is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the min is empty for a given segment ID `i`, `output[i] = 0`.\n\n
\n\n
" + description: "Read @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments.\n\nComputes a tensor such that\n\\\\(output_i = \\min_j(data_j)\\\\) where `min` is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the min is empty for a given segment ID `i`, `output[i] = 0`.\n\n
\n\n
" } op { name: "SegmentProd" @@ -19944,7 +19944,7 @@ op { } } summary: "Computes the product along segments of a tensor." - description: "Read [the section on\nSegmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation\nof segments.\n\nComputes a tensor such that\n\\\\(output_i = \\prod_j data_j\\\\) where the product is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the product is empty for a given segment ID `i`, `output[i] = 1`.\n\n
\n\n
" + description: "Read @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments.\n\nComputes a tensor such that\n\\\\(output_i = \\prod_j data_j\\\\) where the product is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the product is empty for a given segment ID `i`, `output[i] = 1`.\n\n
\n\n
" } op { name: "SegmentSum" @@ -19995,7 +19995,7 @@ op { } } summary: "Computes the sum along segments of a tensor." - description: "Read [the section on Segmentation](../../api_docs/python/math_ops.md#segmentation)\nfor an explanation of segments.\n\nComputes a tensor such that\n\\\\(output_i = \\sum_j data_j\\\\) where sum is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the sum is empty for a given segment ID `i`, `output[i] = 0`.\n\n
\n\n
" + description: "Read @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments.\n\nComputes a tensor such that\n\\\\(output_i = \\sum_j data_j\\\\) where sum is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the sum is empty for a given segment ID `i`, `output[i] = 0`.\n\n
\n\n
" } op { name: "Select" @@ -22528,7 +22528,7 @@ op { } } summary: "Computes the mean along sparse segments of a tensor." - description: "Read [the section on\nSegmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation\nof segments.\n\nLike `SegmentMean`, but `segment_ids` can have rank less than `data`\'s first\ndimension, selecting a subset of dimension 0, specified by `indices`." + description: "Read @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments.\n\nLike `SegmentMean`, but `segment_ids` can have rank less than `data`\'s first\ndimension, selecting a subset of dimension 0, specified by `indices`." } op { name: "SparseSegmentMeanGrad" @@ -22627,7 +22627,7 @@ op { } } summary: "Computes the sum along sparse segments of a tensor divided by the sqrt of N." - description: "N is the size of the segment being reduced.\n\nRead [the section on\nSegmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation\nof segments." + description: "N is the size of the segment being reduced.\n\nRead @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments." } op { name: "SparseSegmentSqrtNGrad" @@ -22733,7 +22733,7 @@ op { } } summary: "Computes the sum along sparse segments of a tensor." - description: "Read [the section on\nSegmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation\nof segments.\n\nLike `SegmentSum`, but `segment_ids` can have rank less than `data`\'s first\ndimension, selecting a subset of dimension 0, specified by `indices`.\n\nFor example:\n\n```prettyprint\nc = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])\n\n# Select two rows, one segment.\ntf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 0]))\n ==> [[0 0 0 0]]\n\n# Select two rows, two segment.\ntf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 1]))\n ==> [[ 1 2 3 4]\n [-1 -2 -3 -4]]\n\n# Select all rows, two segments.\ntf.sparse_segment_sum(c, tf.constant([0, 1, 2]), tf.constant([0, 0, 1]))\n ==> [[0 0 0 0]\n [5 6 7 8]]\n\n# Which is equivalent to:\ntf.segment_sum(c, tf.constant([0, 0, 1]))\n```" + description: "Read @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments.\n\nLike `SegmentSum`, but `segment_ids` can have rank less than `data`\'s first\ndimension, selecting a subset of dimension 0, specified by `indices`.\n\nFor example:\n\n```prettyprint\nc = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])\n\n# Select two rows, one segment.\ntf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 0]))\n ==> [[0 0 0 0]]\n\n# Select two rows, two segment.\ntf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 1]))\n ==> [[ 1 2 3 4]\n [-1 -2 -3 -4]]\n\n# Select all rows, two segments.\ntf.sparse_segment_sum(c, tf.constant([0, 1, 2]), tf.constant([0, 0, 1]))\n ==> [[0 0 0 0]\n [5 6 7 8]]\n\n# Which is equivalent to:\ntf.segment_sum(c, tf.constant([0, 0, 1]))\n```" } op { name: "SparseSoftmax" @@ -26306,7 +26306,7 @@ op { } } summary: "Computes the Max along segments of a tensor." - description: "Read [the section on\nSegmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation\nof segments.\n\nThis operator is similar to the [unsorted segment sum operator](../../api_docs/python/math_ops.md#UnsortedSegmentSum).\nInstead of computing the sum over segments, it computes the maximum\nsuch that:\n\n\\\\(output_i = \\max_j data_j\\\\) where max is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the maximum is empty for a given segment ID `i`, it outputs the smallest possible value for specific numeric type,\n `output[i] = numeric_limits::min()`.\n\n
\n\n
" + description: "Read @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments.\n\nThis operator is similar to the [unsorted segment sum operator](../../../api_docs/python/math_ops.md#UnsortedSegmentSum).\nInstead of computing the sum over segments, it computes the maximum\nsuch that:\n\n\\\\(output_i = \\max_j data_j\\\\) where max is over `j` such\nthat `segment_ids[j] == i`.\n\nIf the maximum is empty for a given segment ID `i`, it outputs the smallest possible value for specific numeric type,\n `output[i] = numeric_limits::min()`.\n\n
\n\n
" } op { name: "UnsortedSegmentSum" @@ -26361,7 +26361,7 @@ op { } } summary: "Computes the sum along segments of a tensor." - description: "Read [the section on\nSegmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation\nof segments.\n\nComputes a tensor such that\n`(output[i] = sum_{j...} data[j...]` where the sum is over tuples `j...` such\nthat `segment_ids[j...] == i`. Unlike `SegmentSum`, `segment_ids`\nneed not be sorted and need not cover all values in the full\nrange of valid values.\n\nIf the sum is empty for a given segment ID `i`, `output[i] = 0`.\n\n`num_segments` should equal the number of distinct segment IDs.\n\n
\n\n
" + description: "Read @{$math_ops#segmentation$the section on segmentation} for an explanation of\nsegments.\n\nComputes a tensor such that\n`(output[i] = sum_{j...} data[j...]` where the sum is over tuples `j...` such\nthat `segment_ids[j...] == i`. Unlike `SegmentSum`, `segment_ids`\nneed not be sorted and need not cover all values in the full\nrange of valid values.\n\nIf the sum is empty for a given segment ID `i`, `output[i] = 0`.\n\n`num_segments` should equal the number of distinct segment IDs.\n\n
\n\n
" } op { name: "Unstage"