Module: tf.compat.v1.ragged
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Public API for tf._api.v2.ragged namespace
Classes
class RaggedTensorValue
: Represents the value of a RaggedTensor
.
Functions
boolean_mask(...)
: Applies a boolean mask to data
without flattening the mask dimensions.
constant(...)
: Constructs a constant RaggedTensor from a nested Python list.
constant_value(...)
: Constructs a RaggedTensorValue from a nested Python list.
cross(...)
: Generates feature cross from a list of tensors.
cross_hashed(...)
: Generates hashed feature cross from a list of tensors.
map_flat_values(...)
: Applies op
to the flat_values
of one or more RaggedTensors.
placeholder(...)
: Creates a placeholder for a tf.RaggedTensor
that will always be fed.
range(...)
: Returns a RaggedTensor
containing the specified sequences of numbers.
row_splits_to_segment_ids(...)
: Generates the segmentation corresponding to a RaggedTensor row_splits
.
segment_ids_to_row_splits(...)
: Generates the RaggedTensor row_splits
corresponding to a segmentation.
stack(...)
: Stacks a list of rank-R
tensors into one rank-(R+1)
RaggedTensor
.
stack_dynamic_partitions(...)
: Stacks dynamic partitions of a Tensor or RaggedTensor.
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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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26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,["# Module: tf.compat.v1.ragged\n\n\u003cbr /\u003e\n\nPublic API for tf._api.v2.ragged namespace\n\nClasses\n-------\n\n[`class RaggedTensorValue`](../../../tf/compat/v1/ragged/RaggedTensorValue): Represents the value of a `RaggedTensor`.\n\nFunctions\n---------\n\n[`boolean_mask(...)`](../../../tf/ragged/boolean_mask): Applies a boolean mask to `data` without flattening the mask dimensions.\n\n[`constant(...)`](../../../tf/ragged/constant): Constructs a constant RaggedTensor from a nested Python list.\n\n[`constant_value(...)`](../../../tf/compat/v1/ragged/constant_value): Constructs a RaggedTensorValue from a nested Python list.\n\n[`cross(...)`](../../../tf/ragged/cross): Generates feature cross from a list of tensors.\n\n[`cross_hashed(...)`](../../../tf/ragged/cross_hashed): Generates hashed feature cross from a list of tensors.\n\n[`map_flat_values(...)`](../../../tf/ragged/map_flat_values): Applies `op` to the `flat_values` of one or more RaggedTensors.\n\n[`placeholder(...)`](../../../tf/compat/v1/ragged/placeholder): Creates a placeholder for a [`tf.RaggedTensor`](../../../tf/RaggedTensor) that will always be fed.\n\n[`range(...)`](../../../tf/ragged/range): Returns a `RaggedTensor` containing the specified sequences of numbers.\n\n[`row_splits_to_segment_ids(...)`](../../../tf/ragged/row_splits_to_segment_ids): Generates the segmentation corresponding to a RaggedTensor `row_splits`.\n\n[`segment_ids_to_row_splits(...)`](../../../tf/ragged/segment_ids_to_row_splits): Generates the RaggedTensor `row_splits` corresponding to a segmentation.\n\n[`stack(...)`](../../../tf/ragged/stack): Stacks a list of rank-`R` tensors into one rank-`(R+1)` `RaggedTensor`.\n\n[`stack_dynamic_partitions(...)`](../../../tf/ragged/stack_dynamic_partitions): Stacks dynamic partitions of a Tensor or RaggedTensor."]]