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ConvNet
1.0
A GPU-based C++ implementation of Convolutional Neural Nets
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Implements a layer with a softmax activation function. More...
#include <layer.h>
Public Member Functions | |
| SoftmaxDistLayer (const config::Layer &config) | |
| virtual void | AllocateMemory (int imgsize, int batch_size) |
| Allocate memory for storing the state and derivative at this layer. More... | |
| virtual void | ComputeDeriv () |
| Compute derivative of loss function. More... | |
| virtual float | GetLoss () |
| Compute the value of the loss function that is displayed during training. More... | |
Public Member Functions inherited from SoftmaxLayer | |
| SoftmaxLayer (const config::Layer &config) | |
| virtual void | ApplyActivation (bool train) |
| Apply the activation function. More... | |
| virtual void | ApplyDerivativeOfActivation () |
| Apply the derivative of the activation. More... | |
| virtual float | GetLoss2 () |
| Compute the value of the actual loss function. More... | |
Public Member Functions inherited from Layer | |
| Layer (const config::Layer &config) | |
| Instantiate a layer from config. More... | |
| void | ApplyDropout (bool train) |
| Apply dropout to this layer. More... | |
| void | ApplyDerivativeofDropout () |
| Apply derivative of dropout. More... | |
| void | AccessStateBegin () |
| void | AccessStateEnd () |
| void | AccessDerivBegin () |
| void | AccessDerivEnd () |
| Edge * | GetIncomingEdge (int index) |
| Returns the incoming edge by index. More... | |
| Matrix & | GetState () |
| Returns a reference to the state of the layer. More... | |
| Matrix & | GetDeriv () |
| Returns a reference to the deriv at this layer. More... | |
| Matrix & | GetData () |
| Returns a reference to the data at this layer. More... | |
| void | Display () |
| void | Display (int image_id) |
| void | AddIncoming (Edge *e) |
| Add an incoming edge to this layer. More... | |
| void | AddOutgoing (Edge *e) |
| Add an outgoing edge from this layer. More... | |
| const string & | GetName () const |
| int | GetNumChannels () const |
| int | GetSize () const |
| bool | IsInput () const |
| bool | IsOutput () const |
| int | GetGPUId () const |
| void | AllocateMemoryOnOtherGPUs () |
| Matrix & | GetOtherState (int gpu_id) |
| Matrix & | GetOtherDeriv (int gpu_id) |
| void | SyncIncomingState () |
| void | SyncOutgoingState () |
| void | SyncIncomingDeriv () |
| void | SyncOutgoingDeriv () |
Additional Inherited Members | |
Static Public Member Functions inherited from Layer | |
| static Layer * | ChooseLayerClass (const config::Layer &layer_config) |
Public Attributes inherited from Layer | |
| vector< Edge * > | incoming_edge_ |
| vector< Edge * > | outgoing_edge_ |
| bool | has_incoming_from_same_gpu_ |
| bool | has_outgoing_to_same_gpu_ |
| bool | has_incoming_from_other_gpus_ |
| bool | has_outgoing_to_other_gpus_ |
Protected Member Functions inherited from Layer | |
| void | ApplyDropoutAtTrainTime () |
| void | ApplyDropoutAtTestTime () |
Protected Attributes inherited from Layer | |
| const string | name_ |
| const int | num_channels_ |
| const bool | is_input_ |
| const bool | is_output_ |
| const float | dropprob_ |
| const bool | display_ |
| const bool | dropout_scale_up_at_train_time_ |
| const bool | gaussian_dropout_ |
| const float | max_act_gaussian_dropout_ |
| int | scale_targets_ |
| int | image_size_ |
| Matrix | state_ |
| Matrix | deriv_ |
| State (activation) of the layer. More... | |
| Matrix | data_ |
| Deriv of the loss function w.r.t. More... | |
| Matrix | rand_gaussian_ |
| Data (targets) associated with this layer. More... | |
| map< int, Matrix > | other_states_ |
| Need to store random variates when doing gaussian dropout. More... | |
| map< int, Matrix > | other_derivs_ |
| Copies of this layer's state on other gpus. More... | |
| ImageDisplayer * | img_display_ |
| Copies of this layer's deriv on other gpus. More... | |
| const int | gpu_id_ |
| set< int > | other_incoming_gpu_ids_ |
| set< int > | other_outgoing_gpu_ids_ |
Implements a layer with a softmax activation function.
This must be an output layer. The target must be a distribution over K choices.
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Allocate memory for storing the state and derivative at this layer.
| imgsize | The spatial size of the layer (width and height). |
| batch_size | The mini-batch size. |
Reimplemented from SoftmaxLayer.
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virtual |
Compute derivative of loss function.
This is applicable only if this layer is an output layer.
Reimplemented from SoftmaxLayer.
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virtual |
Compute the value of the loss function that is displayed during training.
This is applicable only if this layer is an output layer.
Reimplemented from SoftmaxLayer.
1.8.7