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CosineSimilarity

public class CosineSimilarity

Computes the cosine similarity between labels and predictions.

Note that it is a number between ``` -1 ``` and ``` 1 ``` . When it is a negative number between ``` -1 ``` and ``` 0 ``` , ``` 0 ``` indicates orthogonality and values closer to ``` -1 ``` indicate greater similarity. The values closer to ``` 1 ``` indicate greater dissimilarity. This makes it usable as a loss function in a setting where you try to maximize the proximity between predictions and targets. If either ``` labels ``` or ``` predictions ``` is a zero vector, cosine similarity will be ``` 0 ``` regardless of the proximity between predictions and targets.

``` loss = -sum(l2Norm(labels) * l2Norm(predictions)) ```

Standalone usage:

```    Operand<TFloat32> labels =
tf.constant(new float[][] { {0.f, 1.f}, {1.f, 1.f} });
Operand<TFloat32> predictions =
tf.constant(new float[][] { {1.f, 0.f}, {1.f, 1.f} });
CosineSimilarity cosineLoss = new CosineSimilarity(tf);
Operand<TFloat32> result = cosineLoss.call(labels, predictions);
// produces -0.5
```

Calling with sample weight:

```    Operand<TFloat32> sampleWeight = tf.constant(new float[] {0.8f, 0.2f});
Operand<TFloat32> result = cosineLoss.call(labels, predictions, sampleWeight);
// produces -0.0999f
```

Using ``` SUM ``` reduction type:

```    CosineSimilarity cosineLoss = new CosineSimilarity(tf, Reduction.SUM);
Operand<TFloat32> result = cosineLoss.call(labels, predictions);
// produces -0.999f
```

Using ``` NONE ``` reduction type:

```    CosineSimilarity cosineLoss = new CosineSimilarity(tf, Reduction.NONE);
Operand<TFloat32> result = cosineLoss.call(labels, predictions);
// produces [-0.f, -0.999f]
```

Constants

 int DEFAULT_AXIS

Fields

 public static final Reduction DEFAULT_REDUCTION

Public Constructors

 (Ops tf) Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name, an axis of ``` DEFAULT_AXIS ``` , and a Loss Reduction of ``` DEFAULT_REDUCTION ``` (Ops tf, String name) Creates a Cosine Similarity Loss using an axis of ``` DEFAULT_AXIS ``` , and a Loss Reduction of ``` DEFAULT_REDUCTION ``` (Ops tf, int axis) Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name, and a Loss Reduction of ``` DEFAULT_REDUCTION ``` (Ops tf, int[] axis) Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name, and a Loss Reduction of ``` DEFAULT_REDUCTION ``` (Ops tf, String name, int axis) Creates a Cosine Similarity Loss using a Loss Reduction of ``` DEFAULT_REDUCTION ``` (Ops tf, String name, int[] axis) Creates a Cosine Similarity Loss using a Loss Reduction of ``` DEFAULT_REDUCTION ``` (Ops tf, Reduction reduction) Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name and an axis of ``` DEFAULT_AXIS ``` (Ops tf, String name, Reduction reduction) Creates a Cosine Similarity Loss using an axis of ``` DEFAULT_AXIS ``` (Ops tf, int axis, Reduction reduction) Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name (Ops tf, int[] axis, Reduction reduction) Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name (Ops tf, String name, int axis, Reduction reduction) Creates a Cosine Similarity Loss (Ops tf, String name, int[] axis, Reduction reduction) Creates a Cosine Similarity Loss

Public Methods

 Operand ( Operand labels, Operand predictions, Operand sampleWeights) Generates an Operand that calculates the loss.

Constants

public static final int DEFAULT_AXIS

Constant Value: -1

Public Constructors

public CosineSimilarity (Ops tf)

Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name, an axis of ``` DEFAULT_AXIS ``` , and a Loss Reduction of ``` DEFAULT_REDUCTION ```

Parameters
 tf the TensorFlow Ops

public CosineSimilarity (Ops tf, String name)

Creates a Cosine Similarity Loss using an axis of ``` DEFAULT_AXIS ``` , and a Loss Reduction of ``` DEFAULT_REDUCTION ```

Parameters
 tf the TensorFlow Ops the name of the loss

public CosineSimilarity (Ops tf, int axis)

Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name, and a Loss Reduction of ``` DEFAULT_REDUCTION ```

Parameters
 tf the TensorFlow Ops The dimension along which the cosine similarity is computed.

public CosineSimilarity (Ops tf, int[] axis)

Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name, and a Loss Reduction of ``` DEFAULT_REDUCTION ```

Parameters
 tf the TensorFlow Ops The dimension along which the cosine similarity is computed.

public CosineSimilarity (Ops tf, String name, int axis)

Creates a Cosine Similarity Loss using a Loss Reduction of ``` DEFAULT_REDUCTION ```

Parameters
 tf the TensorFlow Ops the name of the loss The dimension along which the cosine similarity is computed.

public CosineSimilarity (Ops tf, String name, int[] axis)

Creates a Cosine Similarity Loss using a Loss Reduction of ``` DEFAULT_REDUCTION ```

Parameters
 tf the TensorFlow Ops the name of the loss The dimension along which the cosine similarity is computed.

public CosineSimilarity (Ops tf, Reduction reduction)

Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name and an axis of ``` DEFAULT_AXIS ```

Parameters
 tf the TensorFlow Ops Type of Reduction to apply to the loss.

public CosineSimilarity (Ops tf, String name, Reduction reduction)

Creates a Cosine Similarity Loss using an axis of ``` DEFAULT_AXIS ```

Parameters
 tf the TensorFlow Ops the name of the loss Type of Reduction to apply to the loss.

public CosineSimilarity (Ops tf, int axis, Reduction reduction)

Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name

Parameters
 tf the TensorFlow Ops The dimension along which the cosine similarity is computed. Type of Reduction to apply to the loss.

public CosineSimilarity (Ops tf, int[] axis, Reduction reduction)

Creates a Cosine Similarity Loss using ``` getSimpleName() ``` as the loss name

Parameters
 tf the TensorFlow Ops The dimension along which the cosine similarity is computed. Type of Reduction to apply to the loss.

public CosineSimilarity (Ops tf, String name, int axis, Reduction reduction)

Creates a Cosine Similarity Loss

Parameters
 tf the TensorFlow Ops the name of the loss The dimension along which the cosine similarity is computed. Type of Reduction to apply to the loss.

public CosineSimilarity (Ops tf, String name, int[] axis, Reduction reduction)

Creates a Cosine Similarity Loss

Parameters
 tf the TensorFlow Ops the name of the loss The dimension along which the cosine similarity is computed. Type of Reduction to apply to the loss.

Public Methods

public Operand <T> call ( Operand <? extends TNumber > labels, Operand <T> predictions, Operand <T> sampleWeights)

Generates an Operand that calculates the loss.

Parameters
 labels the truth values or labels the predictions Optional sampleWeights acts as a coefficient for the loss. If a scalar is provided, then the loss is simply scaled by the given value. If SampleWeights is a tensor of size [batch_size], then the total loss for each sample of the batch is rescaled by the corresponding element in the SampleWeights vector. If the shape of SampleWeights is [batch_size, d0, .. dN-1] (or can be broadcast to this shape), then each loss element of predictions is scaled by the corresponding value of SampleWeights. (Note on dN-1: all loss functions reduce by 1 dimension, usually axis=-1.)
Returns
• the loss
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]