Acts like Batch but using the given batch_index index of batching things as they
become available. This ensures that the gradients are propagated back in the
same session which did the forward pass.
original_input: The input to the Unbatch operation this is the gradient of.
batch_index: The batch_index given to the Unbatch operation this is the gradient
of.
grad: The downstream gradient.
id: The id scalar emitted by Batch.
batched_grad: The return value, either an empty tensor or the batched gradient.
container: Container to control resource sharing.
shared_name: Instances of UnbatchGrad with the same container and shared_name
are assumed to possibly belong to the same batch. If left empty, the op name
will be used as the shared name.
Args
original_input
A Tensor.
batch_index
A Tensor of type int64.
grad
A Tensor. Must have the same type as original_input.
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-01-23 UTC."],[],[]]