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Functions137 in github.com/PacktPublishing/Hands-On-Deep-Learning-with-Go

⨍ Functions 137◇ Types & classes 31
↓ 18 callersMethodReset
Reset moves player back to start position
Chapter07/dqn_maze_solver/maze.go:167
↓ 14 callersMethodValue
()
Chapter05/h4_01_rnn_with_lstm_gru/gru.go:15
↓ 5 callersMethodCanMoveTo
(player Point, direction Vector)
Chapter07/dqn_maze_solver/maze.go:130
↓ 4 callersMethodStep
()
Chapter08/main.go:71
↓ 4 callersMethodlearnables
()
Chapter05/h4_01_rnn_with_lstm_gru/s2s.go:54
↓ 4 callersMethodlearnables
()
Chapter09/pachyderm_cifar_cnn/main.go:93
↓ 3 callersFunctiongetPossibleActions
(m *Maze)
Chapter07/dqn_maze_solver/main.go:146
↓ 3 callersMethodlearnables
()
Chapter04/mnist_feedforward_cuda/main.go:80
↓ 3 callersMethodlearnables
()
Chapter06/cifar_cnn/main.go:89
↓ 3 callersMethodlearnables
()
Chapter03/mnist_feedforward/main.go:80
↓ 3 callersMethodlearnables
()
Chapter03/mnist_autoencoder/main.go:81
↓ 3 callersMethodlearnables
()
Chapter02/h4_01_simple_neural_network/main.go:38
↓ 3 callersMethodlearnables
()
Chapter08/main.go:105
↓ 3 callersFunctionvisualizeRow
(x []float64)
Chapter03/mnist_autoencoder/main.go:130
↓ 3 callersFunctionvisualizeRow
(x []float64)
Chapter08/main.go:190
↓ 2 callersFunctionHeatmap
(a *tensor.Dense)
Chapter05/h4_01_rnn_with_lstm_gru/heatmap.go:35
↓ 2 callersMethodMove
(direction Vector)
Chapter07/dqn_maze_solver/maze.go:143
↓ 2 callersMethodStart
()
Chapter04/mnist_feedforward_cuda/main.go:62
↓ 2 callersMethodStart
()
Chapter06/cifar_cnn/main.go:55
↓ 2 callersMethodStart
()
Chapter03/mnist_feedforward/main.go:62
↓ 2 callersMethodStart
()
Chapter03/mnist_autoencoder/main.go:61
↓ 2 callersMethodStart
()
Chapter09/pachyderm_cifar_cnn/main.go:59
↓ 2 callersMethodStart
()
Chapter08/main.go:69
↓ 2 callersMethodbestAction
(state *Maze, moves []Vector)
Chapter07/dqn_maze_solver/main.go:124
↓ 2 callersFunctioncleanup
(sigChan chan os.Signal, doneChan chan bool, profiling bool)
Chapter06/cifar_cnn/main.go:446
↓ 2 callersFunctioncleanup
(sigChan chan os.Signal, doneChan chan bool, profiling bool)
Chapter09/pachyderm_cifar_cnn/main.go:471
↓ 2 callersMethodlearnables
()
Chapter07/dqn_maze_solver/nn.go:51
↓ 2 callersMethodpredict
(player Point, action Vector)
Chapter07/dqn_maze_solver/main.go:88
↓ 2 callersFunctionprintIntSlice
(filePath string, values []int)
Chapter06/cifar_cnn/main.go:475
↓ 2 callersFunctionprintIntSlice
(filePath string, values []int)
Chapter09/pachyderm_cifar_cnn/main.go:500
↓ 1 callersMethodActivate
(x, prev *Node)
Chapter05/h4_01_rnn_with_lstm_gru/gru.go:77
↓ 1 callersMethodDims
()
Chapter05/h4_01_rnn_with_lstm_gru/heatmap.go:20
↓ 1 callersMethodLet1
(x input)
Chapter07/dqn_maze_solver/nn.go:103
↓ 1 callersFunctionMakeLSTM
(g *ExprGraph, hiddenSize, prevSize int)
Chapter05/h4_01_rnn_with_lstm_gru/lstm.go:25
↓ 1 callersFunctionNewMaze
(h, w int)
Chapter07/dqn_maze_solver/maze.go:49
↓ 1 callersFunctionNewNN
(batchsize int)
Chapter07/dqn_maze_solver/nn.go:33
↓ 1 callersFunctionNewS2S
NewS2S creates a new Seq2Seq network. Input size is the size of the embedding. Hidden size is the size of the hidden layer
Chapter05/h4_01_rnn_with_lstm_gru/s2s.go:32
↓ 1 callersMethodStep
()
Chapter04/mnist_feedforward_cuda/main.go:64
↓ 1 callersMethodStep
()
Chapter06/cifar_cnn/main.go:57
↓ 1 callersMethodStep
()
Chapter03/mnist_feedforward/main.go:64
↓ 1 callersMethodStep
()
Chapter03/mnist_autoencoder/main.go:63
↓ 1 callersMethodStep
()
Chapter09/pachyderm_cifar_cnn/main.go:61
↓ 1 callersMethodValue
(action Vector)
Chapter07/dqn_maze_solver/maze.go:152
↓ 1 callersMethodbuild
()
Chapter05/h4_01_rnn_with_lstm_gru/s2s.go:62
↓ 1 callersMethodcons
()
Chapter07/dqn_maze_solver/nn.go:61
↓ 1 callersMethodfwd
(x *gorgonia.Node)
Chapter04/mnist_feedforward_cuda/main.go:84
↓ 1 callersMethodfwd
(x *Node)
Chapter07/dqn_maze_solver/nn.go:15
↓ 1 callersMethodfwd
This function is particularly verbose for educational reasons. In reality, you'd wrap up the layers within a layer struct type and perform per-layer a
Chapter06/cifar_cnn/main.go:94
↓ 1 callersMethodfwd
(x *gorgonia.Node)
Chapter03/mnist_feedforward/main.go:84
↓ 1 callersMethodfwd
(x *gorgonia.Node)
Chapter03/mnist_autoencoder/main.go:85
↓ 1 callersMethodfwd
This function is particularly verbose for educational reasons. In reality, you'd wrap up the layers within a layer struct type and perform per-layer a
Chapter09/pachyderm_cifar_cnn/main.go:116
↓ 1 callersMethodfwd
(x *Node)
Chapter02/h4_01_simple_neural_network/main.go:42
↓ 1 callersMethodfwd
(x *gorgonia.Node)
Chapter08/main.go:109
↓ 1 callersMethodinit
()
Chapter07/dqn_maze_solver/main.go:31
↓ 1 callersFunctioninitVocab
(ss []string, thresh int)
Chapter05/h4_01_rnn_with_lstm_gru/vocab.go:18
↓ 1 callersFunctionmax
(a []float32)
Chapter07/dqn_maze_solver/main.go:155
↓ 1 callersMethodmodel
()
Chapter07/dqn_maze_solver/nn.go:59
↓ 1 callersFunctionnewConvNet
(g *gorgonia.ExprGraph)
Chapter06/cifar_cnn/main.go:68
↓ 1 callersFunctionnewConvNet
(g *gorgonia.ExprGraph)
Chapter09/pachyderm_cifar_cnn/main.go:72
↓ 1 callersFunctionnewNN
(g *gorgonia.ExprGraph)
Chapter04/mnist_feedforward_cuda/main.go:66
↓ 1 callersFunctionnewNN
(g *gorgonia.ExprGraph)
Chapter03/mnist_feedforward/main.go:66
↓ 1 callersFunctionnewNN
(g *gorgonia.ExprGraph)
Chapter03/mnist_autoencoder/main.go:65
↓ 1 callersFunctionnewNN
(g *ExprGraph)
Chapter02/h4_01_simple_neural_network/main.go:22
↓ 1 callersFunctionnewNN
(g *gorgonia.ExprGraph)
Chapter08/main.go:73
↓ 1 callersFunctionparseDtype
()
Chapter04/mnist_feedforward_cuda/main.go:39
↓ 1 callersFunctionparseDtype
()
Chapter06/cifar_cnn/main.go:40
↓ 1 callersFunctionparseDtype
()
Chapter03/mnist_feedforward/main.go:39
↓ 1 callersFunctionparseDtype
()
Chapter03/mnist_autoencoder/main.go:38
↓ 1 callersFunctionparseDtype
()
Chapter09/pachyderm_cifar_cnn/main.go:44
↓ 1 callersFunctionparseDtype
()
Chapter08/main.go:38
↓ 1 callersFunctionpixelWeight
(px byte)
Chapter06/cifar_cnn/cifar/cifar.go:16
↓ 1 callersFunctionpixelWeight
(px byte)
Chapter09/pachyderm_cifar_cnn/cifar/cifar.go:16
↓ 1 callersMethodpredict
(in []rune)
Chapter05/h4_01_rnn_with_lstm_gru/s2s.go:137
↓ 1 callersFunctionreversePixelWeight
(px float64)
Chapter04/mnist_feedforward_cuda/main.go:126
↓ 1 callersFunctionreversePixelWeight
(px float64)
Chapter03/mnist_feedforward/main.go:126
↓ 1 callersFunctionreversePixelWeight
(px float64)
Chapter03/mnist_autoencoder/main.go:125
↓ 1 callersFunctionreversePixelWeight
(px float64)
Chapter08/main.go:185
↓ 1 callersFunctionsample
(val gorgonia.Value)
Chapter05/h4_01_rnn_with_lstm_gru/utils.go:20
↓ 1 callersMethodsavemodel
()
Chapter09/pachyderm_cifar_cnn/main.go:97
↓ 1 callersFunctionshuffle
(a []string)
Chapter05/h4_01_rnn_with_lstm_gru/utils.go:37
↓ 1 callersFunctiontrain
(s *seq2seq, epochs int, solver Solver, data []string)
Chapter05/h4_01_rnn_with_lstm_gru/s2s.go:198
↓ 1 callersMethodtrain
(mz *Maze)
Chapter07/dqn_maze_solver/main.go:99
↓ 1 callersMethodtrain
(in []rune)
Chapter05/h4_01_rnn_with_lstm_gru/s2s.go:101
↓ 1 callersFunctionvisualizeRow
(x []float64)
Chapter04/mnist_feedforward_cuda/main.go:131
↓ 1 callersFunctionvisualizeRow
(x []float64)
Chapter03/mnist_feedforward/main.go:131
MethodActivate
(inputVector *Node, prev lstmout)
Chapter05/h4_01_rnn_with_lstm_gru/lstm.go:61
FunctionAvg
(a []float64)
Chapter05/h4_01_rnn_with_lstm_gru/heatmap.go:68
MethodEnd
()
Chapter04/mnist_feedforward_cuda/main.go:63
MethodEnd
()
Chapter06/cifar_cnn/main.go:56
MethodEnd
()
Chapter03/mnist_feedforward/main.go:63
MethodEnd
()
Chapter03/mnist_autoencoder/main.go:62
MethodEnd
()
Chapter09/pachyderm_cifar_cnn/main.go:60
MethodEnd
()
Chapter08/main.go:70
MethodErr
()
Chapter05/h4_01_rnn_with_lstm_gru/gru.go:17
MethodInstructionID
()
Chapter05/h4_01_rnn_with_lstm_gru/gru.go:16
MethodLen
()
Chapter05/h4_01_rnn_with_lstm_gru/utils.go:46
MethodLen
()
Chapter05/h4_01_rnn_with_lstm_gru/utils.go:52
MethodLess
(i, j int)
Chapter05/h4_01_rnn_with_lstm_gru/utils.go:47
MethodLess
(i, j int)
Chapter05/h4_01_rnn_with_lstm_gru/utils.go:53
MethodLet2
(xs []input, y []float32)
Chapter07/dqn_maze_solver/nn.go:84
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