caffe::EmbedLayer< Dtype > Class Template Reference

A layer for learning "embeddings" of one-hot vector input. Equivalent to an InnerProductLayer with one-hot vectors as input, but for efficiency the input is the "hot" index of each column itself. More...

`#include <embed_layer.hpp>`

Inheritance diagram for caffe::EmbedLayer< Dtype >:

## Public Member Functions

| EmbedLayer (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 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 const char * | type () const
| Returns the layer type.
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)
| Using the CPU device, compute the layer output.
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)
| Using the CPU device, compute the gradients for any parameters and for the bottom blobs if propagate_down is true.
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.
Protected Member Functions inherited from caffe::Layer< Dtype >
virtual void | CheckBlobCounts (const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
void | SetLossWeights (const vector< Blob< Dtype > * > &top)

## Protected Attributes

int | M_
int | K_
int | N_
bool | bias_term_
Blob< Dtype > | bias_multiplier_
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::EmbedLayer< Dtype >

A layer for learning "embeddings" of one-hot vector input. Equivalent to an InnerProductLayer with one-hot vectors as input, but for efficiency the input is the "hot" index of each column itself.

TODO(dox): thorough documentation for Forward, Backward, and proto params.

## Member Function Documentation

## ExactNumBottomBlobs()

template<typename Dtype >

virtual int caffe::EmbedLayer< Dtype >::ExactNumBottomBlobs | ( |  | ) | const

inline virtual

Returns the exact number of bottom blobs required by the layer, or -1 if no exact number is required.

This method should be overridden to return a non-negative value if your layer expects some exact number of bottom blobs.

Reimplemented from caffe::Layer< Dtype >.

## ExactNumTopBlobs()

template<typename Dtype >

virtual int caffe::EmbedLayer< Dtype >::ExactNumTopBlobs | ( |  | ) | const

inline virtual

Returns the exact number of top blobs required by the layer, or -1 if no exact number is required.

This method should be overridden to return a non-negative value if your layer expects some exact number of top blobs.

Reimplemented from caffe::Layer< Dtype >.

## LayerSetUp()

template<typename Dtype >

void caffe::EmbedLayer< 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 >.

## Reshape()

template<typename Dtype >

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

virtual

Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs.

Parameters

  bottom | the input blobs, with the requested input shapes
  top | the top blobs, which should be reshaped as needed

This method should reshape top blobs as needed according to the shapes of the bottom (input) blobs, as well as reshaping any internal buffers and making any other necessary adjustments so that the layer can accommodate the bottom blobs.

Implements caffe::Layer< Dtype >.

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

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