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tensorflow::ops::SparseSoftmaxCrossEntropyWithLogits
#include <nn_ops.h>
Computes softmax cross entropy cost and gradients to backpropagate.
Summary
Unlike SoftmaxCrossEntropyWithLogits, this operation does not accept a matrix of label probabilities, but rather a single label per row of features. This label is considered to have probability 1.0 for the given row.
Inputs are the logits, not probabilities.
Args:
- scope: A Scope object
- features: batch_size x num_classes matrix
- labels: batch_size vector with values in [0, num_classes). This is the label for the given minibatch entry.
Returns:
Output loss: Per example loss (batch_size vector).Output backprop: backpropagated gradients (batch_size x num_classes matrix).
Public attributes
Public functions
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Last updated 2021-11-15 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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2021-11-15 UTC."],[],[],null,["# tensorflow::ops::SparseSoftmaxCrossEntropyWithLogits Class Reference\n\ntensorflow::ops::SparseSoftmaxCrossEntropyWithLogits\n====================================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes softmax cross entropy cost and gradients to backpropagate.\n\nSummary\n-------\n\nUnlike [SoftmaxCrossEntropyWithLogits](/api_docs/cc/class/tensorflow/ops/softmax-cross-entropy-with-logits#classtensorflow_1_1ops_1_1_softmax_cross_entropy_with_logits), this operation does not accept a matrix of label probabilities, but rather a single label per row of features. This label is considered to have probability 1.0 for the given row.\n\nInputs are the logits, not probabilities.\n\nArgs:\n\n- scope: A [Scope](/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- features: batch_size x num_classes matrix\n- labels: batch_size vector with values in \\[0, num_classes). This is the label for the given minibatch entry.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) loss: Per example loss (batch_size vector).\n- [Output](/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) backprop: backpropagated gradients (batch_size x num_classes matrix).\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseSoftmaxCrossEntropyWithLogits](#classtensorflow_1_1ops_1_1_sparse_softmax_cross_entropy_with_logits_1a965e868e103e3908d2bfb1dcd368e90d)`(const ::`[tensorflow::Scope](/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` features, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` labels)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------|\n| [backprop](#classtensorflow_1_1ops_1_1_sparse_softmax_cross_entropy_with_logits_1a9e77b4f5efe0d0762f8fc95a3f7cdbaa) | `::`[tensorflow::Output](/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [loss](#classtensorflow_1_1ops_1_1_sparse_softmax_cross_entropy_with_logits_1aa3c9d1b704d919039c2cd2686fbea683) | `::`[tensorflow::Output](/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [operation](#classtensorflow_1_1ops_1_1_sparse_softmax_cross_entropy_with_logits_1ac581285ea4e5d57f85d8f317aed838fa) | [Operation](/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n\nPublic attributes\n-----------------\n\n### backprop\n\n```text\n::tensorflow::Output backprop\n``` \n\n### loss\n\n```text\n::tensorflow::Output loss\n``` \n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### SparseSoftmaxCrossEntropyWithLogits\n\n```gdscript\n SparseSoftmaxCrossEntropyWithLogits(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input features,\n ::tensorflow::Input labels\n)\n```"]]
