Softmax
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Softmax converts a real vector to a vector of categorical probabilities.
The elements of the output vector are in range (0, 1) and sum to 1.
Each vector is handled independently. The axis argument sets which axis of the
input the function is applied along.
Softmax is often used as the activation for the last layer of a classification network because
the result could be interpreted as a probability distribution.
The softmax of each vector x is computed as: exp(x) / tf.sum(exp(x)).
The input values in are the log-odds of the resulting probability.
Public Constructors
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Softmax(Ops tf, int axis)
Creates a Softmax activation
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Inherited Methods
From class
java.lang.Object
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boolean
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equals(Object arg0)
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Class<?>
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getClass()
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int
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hashCode()
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void
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notify()
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notifyAll()
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wait(long arg0, int arg1)
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wait(long arg0)
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wait()
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Public Constructors
public
Softmax
(Ops tf)
Creates a softmax activation where the default axis is ERROR(/#AXIS_DEFAULT) which indicates
the last dimension.
public
Softmax
(Ops tf, int axis)
Creates a Softmax activation
Parameters
| tf |
the TensorFlow Ops |
| axis |
The dimension softmax would be performed on.
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Public Methods
Gets the calculation operation for the activation.
Returns
- The operand for the activation
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Last updated 2021-11-29 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 2021-11-29 UTC."],[],[],null,["# Softmax\n\npublic class **Softmax** \nSoftmax converts a real vector to a vector of categorical probabilities.\n\nThe elements of the output vector are in range (0, 1) and sum to 1.\n\nEach vector is handled independently. The `axis` argument sets which axis of the\ninput the function is applied along.\n\nSoftmax is often used as the activation for the last layer of a classification network because\nthe result could be interpreted as a probability distribution.\n\nThe softmax of each vector x is computed as: `exp(x) / tf.sum(exp(x))`.\n\nThe input values in are the log-odds of the resulting probability.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n### Public Constructors\n\n|---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| | [Softmax](/jvm/api_docs/java/org/tensorflow/framework/activations/Softmax#Softmax(Ops))(Ops tf) Creates a softmax activation where the default axis is [ERROR(/#AXIS_DEFAULT)]() which indicates the last dimension. |\n| | [Softmax](/jvm/api_docs/java/org/tensorflow/framework/activations/Softmax#Softmax(Ops, int))(Ops tf, int axis) Creates a Softmax activation |\n\n### Public Methods\n\n|-----------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e | [call](/jvm/api_docs/java/org/tensorflow/framework/activations/Softmax#call(org.tensorflow.Operand\u003cT\u003e))([Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e input) Gets the calculation operation for the activation. |\n\n### Inherited Methods\n\nFrom class [org.tensorflow.framework.activations.Activation](/jvm/api_docs/java/org/tensorflow/framework/activations/Activation) \n\n|--------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| abstract [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e | [call](/jvm/api_docs/java/org/tensorflow/framework/activations/Activation#call(org.tensorflow.Operand\u003cT\u003e))([Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e input) Gets the calculation operation for the activation. |\n\nFrom class java.lang.Object \n\n|------------------|---------------------------|\n| boolean | equals(Object arg0) |\n| final Class\\\u003c?\\\u003e | getClass() |\n| int | hashCode() |\n| final void | notify() |\n| final void | notifyAll() |\n| String | toString() |\n| final void | wait(long arg0, int arg1) |\n| final void | wait(long arg0) |\n| final void | wait() |\n\nPublic Constructors\n-------------------\n\n#### public\n**Softmax**\n(Ops tf)\n\nCreates a softmax activation where the default axis is [ERROR(/#AXIS_DEFAULT)]() which indicates\nthe last dimension. \n\n##### Parameters\n\n| tf | the TensorFlow Ops |\n|----|--------------------|\n\n#### public\n**Softmax**\n(Ops tf, int axis)\n\nCreates a Softmax activation \n\n##### Parameters\n\n| tf | the TensorFlow Ops |\n| axis | The dimension softmax would be performed on. |\n|------|----------------------------------------------|\n\nPublic Methods\n--------------\n\n#### public [Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e\n**call**\n([Operand](/jvm/api_docs/java/org/tensorflow/Operand)\\\u003cT\\\u003e input)\n\nGets the calculation operation for the activation. \n\n##### Parameters\n\n| input | the input tensor |\n|-------|------------------|\n\n##### Returns\n\n- The operand for the activation"]]
