tf.sparse.cross
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Generates sparse cross from a list of sparse and dense tensors.
tf.sparse.cross(
inputs, name=None, separator=None
)
For example, if the inputs are
* inputs[0]: SparseTensor with shape = [2, 2]
[0, 0]: "a"
[1, 0]: "b"
[1, 1]: "c"
* inputs[1]: SparseTensor with shape = [2, 1]
[0, 0]: "d"
[1, 0]: "e"
* inputs[2]: Tensor [["f"], ["g"]]
then the output will be:
shape = [2, 2]
[0, 0]: "a_X_d_X_f"
[1, 0]: "b_X_e_X_g"
[1, 1]: "c_X_e_X_g"
Customized separator "Y":
inp_0 = tf.constant([['a'], ['b']])
inp_1 = tf.constant([['c'], ['d']])
output = tf.sparse.cross([inp_0, inp_1], separator='_Y_')
output.values
<tf.Tensor: shape=(2,), dtype=string, numpy=array([b'a_Y_c', b'b_Y_d'],
dtype=object)>
Args |
|---|
inputs
|
An iterable of Tensor or SparseTensor.
|
name
|
Optional name for the op.
|
separator
|
A string added between each string being joined. Defaults to
'X'.
|
Returns |
|---|
A SparseTensor of type string.
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.sparse.cross\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#L608-L660) |\n\nGenerates sparse cross from a list of sparse and dense tensors.\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.cross`](https://www.tensorflow.org/api_docs/python/tf/sparse/cross)\n\n\u003cbr /\u003e\n\n tf.sparse.cross(\n inputs, name=None, separator=None\n )\n\nFor example, if the inputs are \n\n * inputs[0]: SparseTensor with shape = [2, 2]\n [0, 0]: \"a\"\n [1, 0]: \"b\"\n [1, 1]: \"c\"\n * inputs[1]: SparseTensor with shape = [2, 1]\n [0, 0]: \"d\"\n [1, 0]: \"e\"\n * inputs[2]: Tensor [[\"f\"], [\"g\"]]\n\nthen the output will be: \n\n shape = [2, 2]\n [0, 0]: \"a_X_d_X_f\"\n [1, 0]: \"b_X_e_X_g\"\n [1, 1]: \"c_X_e_X_g\"\n\nCustomized separator \"*Y*\": \n\n inp_0 = tf.constant([['a'], ['b']])\n inp_1 = tf.constant([['c'], ['d']])\n output = tf.sparse.cross([inp_0, inp_1], separator='_Y_')\n output.values\n \u003ctf.Tensor: shape=(2,), dtype=string, numpy=array([b'a_Y_c', b'b_Y_d'],\n dtype=object)\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-------------|---------------------------------------------------------------------|\n| `inputs` | An iterable of `Tensor` or `SparseTensor`. |\n| `name` | Optional name for the op. |\n| `separator` | A string added between each string being joined. Defaults to '*X*'. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `SparseTensor` of type `string`. ||\n\n\u003cbr /\u003e"]]
View source on GitHub