This Op takes a SparseTensor and is the sparse counterpart to
tf.reduce_max(). In contrast to SparseReduceSum, this Op returns a
SparseTensor.
Reduces sp_input along the dimensions given in reduction_axes. Unless
keepdims is true, the rank of the tensor is reduced by 1 for each entry in
reduction_axes. If keepdims is true, the reduced dimensions are retained
with length 1.
If reduction_axes has no entries, all dimensions are reduced, and a tensor
with a single element is returned. Additionally, the axes can be negative,
which are interpreted according to the indexing rules in Python.
Args
sp_input
The SparseTensor to reduce. Should have numeric type.
axis
The dimensions to reduce; list or scalar. If None (the
default), reduces all dimensions.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.compat.v1.sparse_reduce_max_sparse\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/sparse_ops.py#L1427-L1477) |\n\nComputes the max of elements across dimensions of a SparseTensor. (deprecated arguments)\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.sparse.reduce_max_sparse`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/sparse_reduce_max_sparse)\n\n\u003cbr /\u003e\n\n tf.compat.v1.sparse_reduce_max_sparse(\n sp_input, axis=None, keepdims=None, reduction_axes=None, keep_dims=None\n )\n\n| **Deprecated:** SOME ARGUMENTS ARE DEPRECATED: `(keep_dims)`. They will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead\n\nThis Op takes a SparseTensor and is the sparse counterpart to\n[`tf.reduce_max()`](../../../tf/math/reduce_max). In contrast to SparseReduceSum, this Op returns a\nSparseTensor.\n| **Note:** A gradient is not defined for this function, so it can't be used in training models that need gradient descent.\n\nReduces `sp_input` along the dimensions given in `reduction_axes`. Unless\n`keepdims` is true, the rank of the tensor is reduced by 1 for each entry in\n`reduction_axes`. If `keepdims` is true, the reduced dimensions are retained\nwith length 1.\n\nIf `reduction_axes` has no entries, all dimensions are reduced, and a tensor\nwith a single element is returned. Additionally, the axes can be negative,\nwhich are interpreted according to the indexing rules in Python.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------------|--------------------------------------------------------------------------------------------|\n| `sp_input` | The SparseTensor to reduce. Should have numeric type. |\n| `axis` | The dimensions to reduce; list or scalar. If `None` (the default), reduces all dimensions. |\n| `keepdims` | If true, retain reduced dimensions with length 1. |\n| `reduction_axes` | Deprecated name of axis. |\n| `keep_dims` | Deprecated alias for `keepdims`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| The reduced SparseTensor. ||\n\n\u003cbr /\u003e"]]
View source on GitHub