caffe::ThresholdLayer< Dtype > Class Template Reference

Tests whether the input exceeds a threshold: outputs 1 for inputs above threshold; 0 otherwise. More...

`#include <threshold_layer.hpp>`

Inheritance diagram for caffe::ThresholdLayer< Dtype >:

## Public Member Functions

| ThresholdLayer (const LayerParameter &param)
virtual void | LayerSetUp (const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
| Does layer-specific setup: your layer should implement this function as well as Reshape. More...
virtual const char * | type () const
| Returns the layer type.
Public Member Functions inherited from caffe::NeuronLayer< Dtype >
| NeuronLayer (const LayerParameter &param)
virtual void | Reshape (const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
| Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs. More...
virtual int | ExactNumBottomBlobs () const
| Returns the exact number of bottom blobs required by the layer, or -1 if no exact number is required. More...
virtual int | ExactNumTopBlobs () const
| Returns the exact number of top blobs required by the layer, or -1 if no exact number is required. More...
Public Member Functions inherited from caffe::Layer< Dtype >
| Layer (const LayerParameter &param)
void | SetUp (const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
| Implements common layer setup functionality. More...
Dtype | Forward (const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
| Given the bottom blobs, compute the top blobs and the loss. More...
void | Backward (const vector< Blob< Dtype > * > &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > * > &bottom)
| Given the top blob error gradients, compute the bottom blob error gradients. More...
vector< shared_ptr< Blob< Dtype > > > & | blobs ()
| Returns the vector of learnable parameter blobs.
const LayerParameter & | layer_param () const
| Returns the layer parameter.
virtual void | ToProto (LayerParameter *param, bool write_diff=false)
| Writes the layer parameter to a protocol buffer.
Dtype | loss (const int top_index) const
| Returns the scalar loss associated with a top blob at a given index.
void | set_loss (const int top_index, const Dtype value)
| Sets the loss associated with a top blob at a given index.
virtual int | MinBottomBlobs () const
| Returns the minimum number of bottom blobs required by the layer, or -1 if no minimum number is required. More...
virtual int | MaxBottomBlobs () const
| Returns the maximum number of bottom blobs required by the layer, or -1 if no maximum number is required. More...
virtual int | MinTopBlobs () const
| Returns the minimum number of top blobs required by the layer, or -1 if no minimum number is required. More...
virtual int | MaxTopBlobs () const
| Returns the maximum number of top blobs required by the layer, or -1 if no maximum number is required. More...
virtual bool | EqualNumBottomTopBlobs () const
| Returns true if the layer requires an equal number of bottom and top blobs. More...
virtual bool | AutoTopBlobs () const
| Return whether "anonymous" top blobs are created automatically by the layer. More...
virtual bool | AllowForceBackward (const int bottom_index) const
| Return whether to allow force_backward for a given bottom blob index. More...
bool | param_propagate_down (const int param_id)
| Specifies whether the layer should compute gradients w.r.t. a parameter at a particular index given by param_id. More...
void | set_param_propagate_down (const int param_id, const bool value)
| Sets whether the layer should compute gradients w.r.t. a parameter at a particular index given by param_id.

## Protected Member Functions

virtual void | Forward_cpu (const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
virtual void | Forward_gpu (const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
| Using the GPU device, compute the layer output. Fall back to Forward_cpu() if unavailable.
virtual void | Backward_cpu (const vector< Blob< Dtype > * > &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > * > &bottom)
| Not implemented (non-differentiable function)
Protected Member Functions inherited from caffe::Layer< Dtype >
virtual void | Backward_gpu (const vector< Blob< Dtype > * > &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > * > &bottom)
| Using the GPU device, compute the gradients for any parameters and for the bottom blobs if propagate_down is true. Fall back to Backward_cpu() if unavailable.
virtual void | CheckBlobCounts (const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
void | SetLossWeights (const vector< Blob< Dtype > * > &top)

## Protected Attributes

Dtype | threshold_
Protected Attributes inherited from caffe::Layer< Dtype >
LayerParameter | layer_param_
Phase | phase_
vector< shared_ptr< Blob< Dtype > > > | blobs_
vector< bool > | param_propagate_down_
vector< Dtype > | loss_

## Detailed Description

### template<typename Dtype>
class caffe::ThresholdLayer< Dtype >

Tests whether the input exceeds a threshold: outputs 1 for inputs above threshold; 0 otherwise.

## Constructor & Destructor Documentation

## ThresholdLayer()

template<typename Dtype >

caffe::ThresholdLayer< Dtype >::ThresholdLayer | ( | const LayerParameter & | param | ) |

inline explicit

Parameters

  param

  provides ThresholdParameter threshold_param, with ThresholdLayer options:
  - threshold (optional, default 0). the threshold value to which the input values are compared.

## Member Function Documentation

## Forward_cpu()

template<typename Dtype >

void caffe::ThresholdLayer< Dtype >::Forward_cpu | ( | const vector< Blob< Dtype > * > & | bottom,
|  | const vector< Blob< Dtype > * > & | top
| ) |  |

protected virtual

Parameters

  bottom

  input Blob vector (length 1)
  1. the inputs

  top

  output Blob vector (length 1)
  1. the computed outputs

Implements caffe::Layer< Dtype >.

## LayerSetUp()

template<typename Dtype >

void caffe::ThresholdLayer< Dtype >::LayerSetUp | ( | const vector< Blob< Dtype > * > & | bottom,
|  | const vector< Blob< Dtype > * > & | top
| ) |  |

virtual

Does layer-specific setup: your layer should implement this function as well as Reshape.

Parameters

  bottom | the preshaped input blobs, whose data fields store the input data for this layer
  top | the allocated but unshaped output blobs

This method should do one-time layer specific setup. This includes reading and processing relevent parameters from the `layer_param_`. Setting up the shapes of top blobs and internal buffers should be done in `Reshape`, which will be called before the forward pass to adjust the top blob sizes.

Reimplemented from caffe::Layer< Dtype >.

The documentation for this class was generated from the following files:

- include/caffe/layers/threshold_layer.hpp
- src/caffe/layers/threshold_layer.cpp