.. _op_ai_onnx_NegativeLogLikelihoodLoss:

NegativeLogLikelihoodLoss
=========================

- **Domain**: ``ai.onnx``
- **Since version**: 22

A NegativeLogLikelihoodLoss operator computes (weighted) negative log likelihood loss.
Its "input" tensor has the shape of (N, C, d1, d2, ..., dk) where k >= 0.
The "input" tensor contains log-probabilities for input[n, :, d_1, d_2,..., d_k] being in a class of [0, C).
The operator's "target" input tensor has the shape of (N, d1, d2, ..., dk). It encodes class labels (one of C classes)
or it may contain a special value (indicated by an attribute ignore_index) for N x d1 x d2 x ... x dk samples.
The loss value for input[n, :, d_1, d_2,...d_k] being classified as class c = target[n][d_1][d_2]...[d_k] is computed as:

.. code-block::

    loss[n][d_1][d_2]...[d_k] = -input[n][c][d_1][d_2]...[d_k].


**Inputs**

- **input** (*T*): Input tensor of shape (N, C) or (N, C, d1, d2, ..., dk).
- **target** (*Tind*): Target tensor of shape (N) or (N, d1, d2, ..., dk). Target element value shall be in range of [0, C). If ignore_index is specified, it may have a value outside [0, C) and the target values should either be in the range [0, C) or have the value ignore_index.
- **weight** (*T*): Optional rescaling weight tensor. If given, it has to be a tensor of size C. Otherwise, it is treated as if having all ones.

**Outputs**

- **loss** (*T*): The negative log likelihood loss

**Attributes**

- **ignore_index** (*int*): Specifies a target value that is ignored and does not contribute to the input gradient. It's an optional value.
- **reduction** (*string*): Type of reduction to apply to loss: none, sum, mean (default). 'none': the output is the loss for each sample. 'sum': the output will be summed. 'mean': the sum of the output will be divided by the sum of applied weights.

**Type Constraints**

- **T**: Constrain input, weight, and output types to floating-point tensors.
  Allowed types: tensor(bfloat16), tensor(double), tensor(float), tensor(float16).
- **Tind**: Constrain target to integer types
  Allowed types: tensor(int32), tensor(int64).

Differences with previous version (13)
--------------------------------------

**SchemaDiff**: ``NegativeLogLikelihoodLoss`` (domain ``'ai.onnx'``)

* old version: 13
* new version: 22
* breaking: no

**Type constraints:**

* changed 'T': added types: ['tensor(bfloat16)']

Version History
---------------

- :doc:`Version 13 <NegativeLogLikelihoodLoss-13>`
- :doc:`Version 12 <NegativeLogLikelihoodLoss-12>`