tensorflow:: ops:: Multinomial
#include <random_ops.h>
Draws samples from a multinomial distribution.
Summary
Arguments:
- scope: A Scope object
- logits: 2-D Tensor with shape
[batch_size, num_classes]
. Each slice[i, :]
represents the unnormalized log probabilities for all classes. - num_samples: 0-D. Number of independent samples to draw for each row slice.
Optional attributes (see Attrs
):
- seed: If either seed or seed2 is set to be non-zero, the internal random number generator is seeded by the given seed. Otherwise, a random seed is used.
- seed2: A second seed to avoid seed collision.
Returns:
Output
: 2-D Tensor with shape[batch_size, num_samples]
. Each slice[i, :]
contains the drawn class labels with range[0, num_classes)
.
Constructors and Destructors |
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Multinomial(const ::tensorflow::Scope & scope, ::tensorflow::Input logits, ::tensorflow::Input num_samples)
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Multinomial(const ::tensorflow::Scope & scope, ::tensorflow::Input logits, ::tensorflow::Input num_samples, const Multinomial::Attrs & attrs)
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Public attributes |
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operation
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output
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Public functions |
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node() const
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::tensorflow::Node *
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operator::tensorflow::Input() const
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operator::tensorflow::Output() const
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Public static functions |
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OutputDtype(DataType x)
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Seed(int64 x)
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Seed2(int64 x)
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Structs |
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tensorflow:: |
Optional attribute setters for Multinomial. |
Public attributes
operation
Operation operation
output
::tensorflow::Output output
Public functions
Multinomial
Multinomial( const ::tensorflow::Scope & scope, ::tensorflow::Input logits, ::tensorflow::Input num_samples )
Multinomial
Multinomial( const ::tensorflow::Scope & scope, ::tensorflow::Input logits, ::tensorflow::Input num_samples, const Multinomial::Attrs & attrs )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Public static functions
OutputDtype
Attrs OutputDtype( DataType x )
Seed
Attrs Seed( int64 x )
Seed2
Attrs Seed2( int64 x )