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Go: Update generated wrapper functions for TensorFlow ops.

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Change: 153416197
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A. Unique TensorFlower 2017-04-17 17:26:06 -08:00 committed by TensorFlower Gardener
parent 5fd2a521e4
commit 6a498a4d67
1 changed files with 28 additions and 36 deletions
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64
tensorflow/go/op/wrappers.go
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@ -6709,8 +6709,8 @@ func AvgPoolGrad(scope *Scope, orig_input_shape tf.Output, grad tf.Output, ksize
// Computes the maximum along segments of a tensor.
//
// Read [the section on Segmentation](../../api_docs/python/math_ops.md#segmentation)
// for an explanation of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// Computes a tensor such that
// \\(output_i = \max_j(data_j)\\) where `max` is over `j` such
@ -6719,7 +6719,7 @@ func AvgPoolGrad(scope *Scope, orig_input_shape tf.Output, grad tf.Output, ksize
// If the max is empty for a given segment ID `i`, `output[i] = 0`.
//
// <div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
// <img style="width:100%" src="../../images/SegmentMax.png" alt>
// <img style="width:100%" src="https://www.tensorflow.org/images/SegmentMax.png" alt>
// </div>
//
// Arguments:
@ -7879,9 +7879,8 @@ func SdcaOptimizer(scope *Scope, sparse_example_indices []tf.Output, sparse_feat
// Computes the minimum along segments of a tensor.
//
// Read [the section on
// Segmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation
// of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// Computes a tensor such that
// \\(output_i = \min_j(data_j)\\) where `min` is over `j` such
@ -7890,7 +7889,7 @@ func SdcaOptimizer(scope *Scope, sparse_example_indices []tf.Output, sparse_feat
// If the min is empty for a given segment ID `i`, `output[i] = 0`.
//
// <div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
// <img style="width:100%" src="../../images/SegmentMin.png" alt>
// <img style="width:100%" src="https://www.tensorflow.org/images/SegmentMin.png" alt>
// </div>
//
// Arguments:
@ -11313,9 +11312,8 @@ func ResourceSparseApplyCenteredRMSProp(scope *Scope, var_ tf.Output, mg tf.Outp
// Computes the mean along segments of a tensor.
//
// Read [the section on
// Segmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation
// of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// Computes a tensor such that
// \\(output_i = \frac{\sum_j data_j}{N}\\) where `mean` is
@ -11325,7 +11323,7 @@ func ResourceSparseApplyCenteredRMSProp(scope *Scope, var_ tf.Output, mg tf.Outp
// If the mean is empty for a given segment ID `i`, `output[i] = 0`.
//
// <div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
// <img style="width:100%" src="../../images/SegmentMean.png" alt>
// <img style="width:100%" src="https://www.tensorflow.org/images/SegmentMean.png" alt>
// </div>
//
// Arguments:
@ -14014,9 +14012,8 @@ func IFFT(scope *Scope, input tf.Output) (output tf.Output) {
//
// N is the size of the segment being reduced.
//
// Read [the section on
// Segmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation
// of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// Arguments:
//
@ -17662,11 +17659,10 @@ func Exp(scope *Scope, x tf.Output) (y tf.Output) {
// Computes the Max along segments of a tensor.
//
// Read [the section on
// Segmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation
// of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// This operator is similar to the [unsorted segment sum operator](../../api_docs/python/math_ops.md#UnsortedSegmentSum).
// This operator is similar to the [unsorted segment sum operator](../../../api_docs/python/math_ops.md#UnsortedSegmentSum).
// Instead of computing the sum over segments, it computes the maximum
// such that:
//
@ -17677,7 +17673,7 @@ func Exp(scope *Scope, x tf.Output) (y tf.Output) {
// `output[i] = numeric_limits<T>::min()`.
//
// <div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
// <img style="width:100%" src="../../images/UnsortedSegmentSum.png" alt>
// <img style="width:100%" src="https://www.tensorflow.org/images/UnsortedSegmentSum.png" alt>
// </div>
//
// Arguments:
@ -18413,8 +18409,8 @@ func ArgMax(scope *Scope, input tf.Output, dimension tf.Output) (output tf.Outpu
// Computes the sum along segments of a tensor.
//
// Read [the section on Segmentation](../../api_docs/python/math_ops.md#segmentation)
// for an explanation of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// Computes a tensor such that
// \\(output_i = \sum_j data_j\\) where sum is over `j` such
@ -18423,7 +18419,7 @@ func ArgMax(scope *Scope, input tf.Output, dimension tf.Output) (output tf.Outpu
// If the sum is empty for a given segment ID `i`, `output[i] = 0`.
//
// <div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
// <img style="width:100%" src="../../images/SegmentSum.png" alt>
// <img style="width:100%" src="https://www.tensorflow.org/images/SegmentSum.png" alt>
// </div>
//
// Arguments:
@ -18577,9 +18573,8 @@ func SparseReshape(scope *Scope, input_indices tf.Output, input_shape tf.Output,
// Computes the product along segments of a tensor.
//
// Read [the section on
// Segmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation
// of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// Computes a tensor such that
// \\(output_i = \prod_j data_j\\) where the product is over `j` such
@ -18588,7 +18583,7 @@ func SparseReshape(scope *Scope, input_indices tf.Output, input_shape tf.Output,
// If the product is empty for a given segment ID `i`, `output[i] = 1`.
//
// <div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
// <img style="width:100%" src="../../images/SegmentProd.png" alt>
// <img style="width:100%" src="https://www.tensorflow.org/images/SegmentProd.png" alt>
// </div>
//
// Arguments:
@ -18614,9 +18609,8 @@ func SegmentProd(scope *Scope, data tf.Output, segment_ids tf.Output) (output tf
// Computes the sum along segments of a tensor.
//
// Read [the section on
// Segmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation
// of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// Computes a tensor such that
// `(output[i] = sum_{j...} data[j...]` where the sum is over tuples `j...` such
@ -18629,7 +18623,7 @@ func SegmentProd(scope *Scope, data tf.Output, segment_ids tf.Output) (output tf
// `num_segments` should equal the number of distinct segment IDs.
//
// <div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
// <img style="width:100%" src="../../images/UnsortedSegmentSum.png" alt>
// <img style="width:100%" src="https://www.tensorflow.org/images/UnsortedSegmentSum.png" alt>
// </div>
//
// Arguments:
@ -18656,9 +18650,8 @@ func UnsortedSegmentSum(scope *Scope, data tf.Output, segment_ids tf.Output, num
// Computes the sum along sparse segments of a tensor.
//
// Read [the section on
// Segmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation
// of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// Like `SegmentSum`, but `segment_ids` can have rank less than `data`'s first
// dimension, selecting a subset of dimension 0, specified by `indices`.
@ -20023,9 +20016,8 @@ func AvgPool(scope *Scope, value tf.Output, ksize []int64, strides []int64, padd
// Computes the mean along sparse segments of a tensor.
//
// Read [the section on
// Segmentation](../../api_docs/python/math_ops.md#segmentation) for an explanation
// of segments.
// Read @{$math_ops#segmentation$the section on segmentation} for an explanation of
// segments.
//
// Like `SegmentMean`, but `segment_ids` can have rank less than `data`'s first
// dimension, selecting a subset of dimension 0, specified by `indices`.