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Diffstat (limited to 'tensorflow/core/api_def/base_api/api_def_UniqueWithCountsV2.pbtxt')
-rw-r--r-- | tensorflow/core/api_def/base_api/api_def_UniqueWithCountsV2.pbtxt | 85 |
1 files changed, 85 insertions, 0 deletions
diff --git a/tensorflow/core/api_def/base_api/api_def_UniqueWithCountsV2.pbtxt b/tensorflow/core/api_def/base_api/api_def_UniqueWithCountsV2.pbtxt new file mode 100644 index 0000000000..e21f56ba5b --- /dev/null +++ b/tensorflow/core/api_def/base_api/api_def_UniqueWithCountsV2.pbtxt @@ -0,0 +1,85 @@ +op { + graph_op_name: "UniqueWithCountsV2" + in_arg { + name: "x" + description: <<END +A `Tensor`. +END + } + in_arg { + name: "axis" + description: <<END +A `Tensor` of type `int32` (default: None). The axis of the Tensor to +find the unique elements. +END + } + out_arg { + name: "y" + description: <<END +A `Tensor`. Unique elements along the `axis` of `Tensor` x. +END + } + out_arg { + name: "idx" + description: <<END +A 1-D Tensor. Has the same type as x that contains the index of each +value of x in the output y. +END + } + out_arg { + name: "count" + description: <<END +A 1-D Tensor. The count of each value of x in the output y. +END + } + summary: "Finds unique elements along an axis of a tensor." + description: <<END +This operation either returns a tensor `y` containing unique elements +along the `axis` of a tensor. The returned unique elements is sorted +in the same order as they occur along `axis` in `x`. +This operation also returns a tensor `idx` and a tensor `count` +that are the same size as the number of the elements in `x` along the +`axis` dimension. The `idx` contains the index in the unique output `y` +and the `count` contains the count in the unique output `y`. +In other words, for an `1-D` tensor `x` with `axis = None: + +`y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1]` + +For example: + +``` +# tensor 'x' is [1, 1, 2, 4, 4, 4, 7, 8, 8] +y, idx, count = unique_with_counts(x) +y ==> [1, 2, 4, 7, 8] +idx ==> [0, 0, 1, 2, 2, 2, 3, 4, 4] +count ==> [2, 1, 3, 1, 2] +``` + +For an `2-D` tensor `x` with `axis = 0`: + +``` +# tensor 'x' is [[1, 0, 0], +# [1, 0, 0], +# [2, 0, 0]] +y, idx, count = unique_with_counts(x, axis=0) +y ==> [[1, 0, 0], + [2, 0, 0]] +idx ==> [0, 0, 1] +count ==> [2, 1] +``` + +For an `2-D` tensor `x` with `axis = 1`: + +``` +# tensor 'x' is [[1, 0, 0], +# [1, 0, 0], +# [2, 0, 0]] +y, idx, count = unique_with_counts(x, axis=1) +y ==> [[1, 0], + [1, 0], + [2, 0]] +idx ==> [0, 1, 1] +count ==> [1, 2] +``` +END +} |