tf.ragged.cross_hashed
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Generates hashed feature cross from a list of tensors.
tf.ragged.cross_hashed(
inputs, num_buckets=0, hash_key=None, name=None
)
The input tensors must have rank=2, and must all have the same number of
rows. The result is a RaggedTensor with the same number of rows as the
inputs, where result[row] contains a list of all combinations of values
formed by taking a single value from each input's corresponding row
(inputs[i][row]). Values are combined by hashing together their
fingerprints. E.g.:
tf.ragged.cross_hashed([tf.ragged.constant([['a'], ['b', 'c']]),
tf.ragged.constant([['d'], ['e']]),
tf.ragged.constant([['f'], ['g']])],
num_buckets=100)
<tf.RaggedTensor [[78], [66, 74]]>
Args |
|---|
inputs
|
A list of RaggedTensor or Tensor or SparseTensor.
|
num_buckets
|
A non-negative int that used to bucket the hashed values. If
num_buckets != 0, then output = hashed_value % num_buckets.
|
hash_key
|
Integer hash_key that will be used by the FingerprintCat64
function. If not given, a default key is used.
|
name
|
Optional name for the op.
|
Returns |
|---|
A 2D RaggedTensor of type int64.
|
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Last updated 2024-04-26 UTC.
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26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.ragged.cross_hashed\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/ragged/ragged_array_ops.py#L768-L802) |\n\nGenerates hashed feature cross from a list of 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.ragged.cross_hashed`](https://www.tensorflow.org/api_docs/python/tf/ragged/cross_hashed)\n\n\u003cbr /\u003e\n\n tf.ragged.cross_hashed(\n inputs, num_buckets=0, hash_key=None, name=None\n )\n\nThe input tensors must have `rank=2`, and must all have the same number of\nrows. The result is a `RaggedTensor` with the same number of rows as the\ninputs, where `result[row]` contains a list of all combinations of values\nformed by taking a single value from each input's corresponding row\n(`inputs[i][row]`). Values are combined by hashing together their\nfingerprints. E.g.: \n\n tf.ragged.cross_hashed([tf.ragged.constant([['a'], ['b', 'c']]),\n tf.ragged.constant([['d'], ['e']]),\n tf.ragged.constant([['f'], ['g']])],\n num_buckets=100)\n \u003ctf.RaggedTensor [[78], [66, 74]]\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------------|--------------------------------------------------------------------------------------------------------------------------------|\n| `inputs` | A list of `RaggedTensor` or `Tensor` or `SparseTensor`. |\n| `num_buckets` | A non-negative `int` that used to bucket the hashed values. If `num_buckets != 0`, then `output = hashed_value % num_buckets`. |\n| `hash_key` | Integer hash_key that will be used by the `FingerprintCat64` function. If not given, a default key is used. |\n| `name` | Optional name for the op. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A 2D `RaggedTensor` of type `int64`. ||\n\n\u003cbr /\u003e"]]
View source on GitHub