SYMBOL INDEX (1036 symbols across 118 files)

FILE: cnn/cnn/aligned-mem-pool.h
  function namespace (line 7) | namespace cnn {
  function zero_all (line 47) | void zero_all() {

FILE: cnn/cnn/c2w.h
  function namespace (line 11) | namespace cnn {

FILE: cnn/cnn/cfsm-builder.cc
  type cnn (line 8) | namespace cnn {
    function is_ws (line 12) | inline bool is_ws(char x) { return (x == ' ' || x == '\t'); }
    function not_ws (line 13) | inline bool not_ws(char x) { return (x != ' ' && x != '\t'); }
    function Expression (line 26) | Expression NonFactoredSoftmaxBuilder::neg_log_softmax(const Expression...
    function Expression (line 78) | Expression ClassFactoredSoftmaxBuilder::neg_log_softmax(const Expressi...

FILE: cnn/cnn/cfsm-builder.h
  function namespace (line 10) | namespace cnn {

FILE: cnn/cnn/cnn-helper.h
  function namespace (line 8) | namespace cnn {

FILE: cnn/cnn/cnn.cc
  type cnn (line 11) | namespace cnn {
    function VariableIndex (line 80) | VariableIndex ComputationGraph::add_input(real s) {
    function VariableIndex (line 87) | VariableIndex ComputationGraph::add_input(const real* ps) {
    function VariableIndex (line 94) | VariableIndex ComputationGraph::add_input(const Dim& d, const vector<f...
    function VariableIndex (line 101) | VariableIndex ComputationGraph::add_input(const Dim& d, const vector<f...
    function VariableIndex (line 108) | VariableIndex ComputationGraph::add_parameters(Parameters* p) {
    function VariableIndex (line 117) | VariableIndex ComputationGraph::add_const_parameters(Parameters* p) {
    function VariableIndex (line 125) | VariableIndex ComputationGraph::add_lookup(LookupParameters* p, const ...
    function VariableIndex (line 134) | VariableIndex ComputationGraph::add_lookup(LookupParameters* p, unsign...
    function VariableIndex (line 143) | VariableIndex ComputationGraph::add_lookup(LookupParameters* p, const ...
    function VariableIndex (line 152) | VariableIndex ComputationGraph::add_lookup(LookupParameters* p, const ...
    function VariableIndex (line 162) | VariableIndex ComputationGraph::add_const_lookup(LookupParameters* p, ...
    function VariableIndex (line 172) | VariableIndex ComputationGraph::add_const_lookup(LookupParameters* p, ...
    function VariableIndex (line 180) | VariableIndex ComputationGraph::add_const_lookup(LookupParameters* p, ...
    function VariableIndex (line 188) | VariableIndex ComputationGraph::add_const_lookup(LookupParameters* p, ...
    function Tensor (line 209) | const Tensor& ComputationGraph::incremental_forward() { return ee->inc...
    function Tensor (line 210) | const Tensor& ComputationGraph::forward() { return ee->forward(); }
    function Tensor (line 211) | const Tensor& ComputationGraph::get_value(VariableIndex i) { return ee...
    function Tensor (line 212) | const Tensor& ComputationGraph::get_value(const expr::Expression& e) {...

FILE: cnn/cnn/cnn.h
  function namespace (line 26) | namespace cnn {
  function VariableIndex (line 197) | VariableIndex ComputationGraph::add_function(const std::initializer_list...
  function VariableIndex (line 206) | VariableIndex ComputationGraph::add_function(const std::initializer_list...
  function VariableIndex (line 215) | VariableIndex ComputationGraph::add_function(const T& arguments) {

FILE: cnn/cnn/conv.cc
  type cnn (line 16) | namespace cnn {
    function string (line 18) | string AddVectorToAllColumns::as_string(const vector<string>& arg_name...
    function Dim (line 24) | Dim AddVectorToAllColumns::dim_forward(const vector<Dim>& xs) const {
    function string (line 56) | string FoldRows::as_string(const vector<string>& arg_names) const {
    function Dim (line 62) | Dim FoldRows::dim_forward(const vector<Dim>& xs) const {
    function string (line 106) | string Conv1DNarrow::as_string(const vector<string>& arg_names) const {
    function Dim (line 112) | Dim Conv1DNarrow::dim_forward(const vector<Dim>& xs) const {
    function string (line 184) | string Conv1DWide::as_string(const vector<string>& arg_names) const {
    function Dim (line 190) | Dim Conv1DWide::dim_forward(const vector<Dim>& xs) const {
    function string (line 260) | string KMaxPooling::as_string(const vector<string>& arg_names) const {
    function Dim (line 266) | Dim KMaxPooling::dim_forward(const vector<Dim>& xs) const {

FILE: cnn/cnn/conv.h
  function Node (line 8) | struct AddVectorToAllColumns : public Node {
  function Node (line 20) | struct KMaxPooling : public Node {

FILE: cnn/cnn/cuda.cc
  type cnn (line 10) | namespace cnn {
    function RemoveArgs (line 14) | static void RemoveArgs(int& argc, char**& argv, int& argi, int n) {
    function Initialize_GPU (line 23) | vector<Device*> Initialize_GPU(int& argc, char**& argv) {

FILE: cnn/cnn/cuda.h
  function namespace (line 33) | namespace cnn {

FILE: cnn/cnn/deep-lstm.cc
  type cnn (line 13) | namespace cnn {
    function Expression (line 91) | Expression DeepLSTMBuilder::add_input_impl(int prev, const Expression&...

FILE: cnn/cnn/deep-lstm.h
  function namespace (line 10) | namespace cnn {

FILE: cnn/cnn/devices.cc
  type cnn (line 9) | namespace cnn {

FILE: cnn/cnn/devices.h
  function DeviceType (line 10) | enum class DeviceType {CPU, GPU};

FILE: cnn/cnn/dict.cc
  type cnn (line 9) | namespace cnn {
    function ReadSentence (line 11) | std::vector<int> ReadSentence(const std::string& line, Dict* sd) {
    function ReadSentencePair (line 23) | void ReadSentencePair(const std::string& line, std::vector<int>* s, Di...

FILE: cnn/cnn/dict.h
  function namespace (line 19) | namespace cnn {

FILE: cnn/cnn/dim.cc
  type cnn (line 7) | namespace cnn {
    function ostream (line 9) | ostream& operator<<(ostream& os, const Dim& d) {
    function ostream (line 19) | ostream& operator<<(ostream& os, const vector<Dim>& ds) {

FILE: cnn/cnn/dim.h
  function namespace (line 14) | namespace boost { namespace serialization { class access; } }
  function namespace (line 16) | namespace cnn {

FILE: cnn/cnn/except.h
  function namespace (line 6) | namespace cnn {

FILE: cnn/cnn/exec.cc
  type cnn (line 7) | namespace cnn {
    function Tensor (line 15) | const Tensor& SimpleExecutionEngine::forward() {
    function Tensor (line 20) | const Tensor& SimpleExecutionEngine::forward(VariableIndex i) {
    function Tensor (line 25) | const Tensor& SimpleExecutionEngine::get_value(VariableIndex i) {
    function Tensor (line 33) | const Tensor& SimpleExecutionEngine::incremental_forward() {
    function Tensor (line 38) | const Tensor& SimpleExecutionEngine::incremental_forward(VariableIndex...

FILE: cnn/cnn/exec.h
  function namespace (line 6) | namespace cnn {

FILE: cnn/cnn/expr.cc
  type cnn (line 8) | namespace cnn { namespace expr {
    type expr (line 8) | namespace expr {
      function Expression (line 12) | Expression input(ComputationGraph& g, real s) { return Expression(&g...
      function Expression (line 13) | Expression input(ComputationGraph& g, const real *ps) { return Expre...
      function Expression (line 14) | Expression input(ComputationGraph& g, const Dim& d, const vector<flo...
      function Expression (line 15) | Expression input(ComputationGraph& g, const Dim& d, const vector<flo...
      function Expression (line 16) | Expression const_parameter(ComputationGraph& g, Parameters* p) { ret...
      function Expression (line 17) | Expression parameter(ComputationGraph& g, Parameters* p) { return Ex...
      function Expression (line 18) | Expression lookup(ComputationGraph& g, LookupParameters* p, unsigned...
      function Expression (line 19) | Expression lookup(ComputationGraph& g, LookupParameters* p, const un...
      function Expression (line 20) | Expression lookup(ComputationGraph& g, LookupParameters* p, const ve...
      function Expression (line 21) | Expression lookup(ComputationGraph& g, LookupParameters* p, const ve...
      function Expression (line 22) | Expression const_lookup(ComputationGraph& g, LookupParameters* p, un...
      function Expression (line 23) | Expression const_lookup(ComputationGraph& g, LookupParameters* p, co...
      function Expression (line 24) | Expression const_lookup(ComputationGraph& g, LookupParameters* p, co...
      function Expression (line 25) | Expression const_lookup(ComputationGraph& g, LookupParameters* p, co...
      function Expression (line 26) | Expression zeroes(ComputationGraph& g, const Dim& d) { return Expres...
      function Expression (line 29) | Expression nobackprop(const Expression& x) { return Expression(x.pg,...
      function Expression (line 31) | Expression operator-(const Expression& x) { return Expression(x.pg, ...
      function Expression (line 32) | Expression operator+(const Expression& x, const Expression& y) { ret...
      function Expression (line 33) | Expression operator+(real x, const Expression& y) { return Expressio...
      function Expression (line 34) | Expression operator+(const Expression& x, real y) { return y+x; }
      function Expression (line 35) | Expression operator-(const Expression& x, const Expression& y) { ret...
      function Expression (line 36) | Expression operator-(real x, const Expression& y) { return Expressio...
      function Expression (line 37) | Expression operator-(const Expression& x, real y) { return -(y-x); }
      function Expression (line 38) | Expression operator*(const Expression& x, const Expression& y) { ret...
      function Expression (line 39) | Expression operator*(const Expression& x, float y) { return Expressi...
      function Expression (line 40) | Expression addmv(const Expression& x, const Expression& y) { return ...
      function Expression (line 41) | Expression cdiv(const Expression& x, const Expression& y) { return E...
      function Expression (line 42) | Expression colwise_add(const Expression& x, const Expression& bias) ...
      function Expression (line 43) | Expression contract3d_1d_1d(const Expression& x, const Expression& y...
      function Expression (line 44) | Expression contract3d_1d_1d(const Expression& x, const Expression& y...
      function Expression (line 45) | Expression contract3d_1d(const Expression& x, const Expression& y) {...
      function Expression (line 46) | Expression contract3d_1d(const Expression& x, const Expression& y, c...
      function Expression (line 48) | Expression sqrt(const Expression& x) { return Expression(x.pg, x.pg-...
      function Expression (line 49) | Expression erf(const Expression& x) { return Expression(x.pg, x.pg->...
      function Expression (line 50) | Expression tanh(const Expression& x) { return Expression(x.pg, x.pg-...
      function Expression (line 51) | Expression lgamma(const Expression& x) { return Expression(x.pg, x.p...
      function Expression (line 52) | Expression log(const Expression& x) { return Expression(x.pg, x.pg->...
      function Expression (line 53) | Expression exp(const Expression& x) { return Expression(x.pg, x.pg->...
      function Expression (line 54) | Expression square(const Expression& x) { return Expression(x.pg, x.p...
      function Expression (line 55) | Expression cube(const Expression& x) { return Expression(x.pg, x.pg-...
      function Expression (line 56) | Expression logistic(const Expression& x) { return Expression(x.pg, x...
      function Expression (line 57) | Expression rectify(const Expression& x) { return Expression(x.pg, x....
      function Expression (line 58) | Expression hinge(const Expression& x, unsigned index, float m) { ret...
      function Expression (line 59) | Expression hinge(const Expression& x, const unsigned* pindex, float ...
      function Expression (line 60) | Expression log_softmax(const Expression& x) { return Expression(x.pg...
      function Expression (line 61) | Expression log_softmax(const Expression& x, const vector<unsigned>& ...
      function Expression (line 62) | Expression sparsemax(const Expression& x) { return Expression(x.pg, ...
      function Expression (line 63) | Expression sparsemax_loss(const Expression& x, const vector<unsigned...
      function Expression (line 64) | Expression sparsemax_loss(const Expression& x, const vector<unsigned...
      function Expression (line 65) | Expression softmax(const Expression& x) { return Expression(x.pg, x....
      function Expression (line 66) | Expression softsign(const Expression& x) { return Expression(x.pg, x...
      function Expression (line 67) | Expression pow(const Expression& x, const Expression& y) { return Ex...
      function Expression (line 68) | Expression min(const Expression& x, const Expression& y) { return Ex...
      function Expression (line 69) | Expression max(const Expression& x, const Expression& y) { return Ex...
      function Expression (line 70) | Expression noise(const Expression& x, real stddev) { return Expressi...
      function Expression (line 71) | Expression dropout(const Expression& x, real p) { return Expression(...
      function Expression (line 72) | Expression block_dropout(const Expression& x, real p) { return Expre...
      function Expression (line 74) | Expression reshape(const Expression& x, const Dim& d) { return Expre...
      function Expression (line 75) | Expression transpose(const Expression& x) { return Expression(x.pg, ...
      function Expression (line 76) | Expression select_rows(const Expression& x, const vector<unsigned>& ...
      function Expression (line 77) | Expression select_rows(const Expression& x, const vector<unsigned>* ...
      function Expression (line 78) | Expression select_cols(const Expression& x, const vector<unsigned>& ...
      function Expression (line 79) | Expression select_cols(const Expression& x, const vector<unsigned>* ...
      function Expression (line 80) | Expression inverse(const Expression& x) { return Expression(x.pg, x....
      function Expression (line 81) | Expression logdet(const Expression& x) { return Expression(x.pg, x.p...
      function Expression (line 83) | Expression trace_of_product(const Expression& x, const Expression& y...
      function Expression (line 84) | Expression cwise_multiply(const Expression& x, const Expression& y) ...
      function Expression (line 86) | Expression squared_norm(const Expression& x) { return Expression(x.p...
      function Expression (line 88) | Expression dot_product(const Expression& x, const Expression& y) { r...
      function Expression (line 89) | Expression squared_distance(const Expression& x, const Expression& y...
      function Expression (line 90) | Expression huber_distance(const Expression& x, const Expression& y, ...
      function Expression (line 91) | Expression l1_distance(const Expression& x, const Expression& y) { r...
      function Expression (line 92) | Expression binary_log_loss(const Expression& x, const Expression& y)...
      function Expression (line 93) | Expression pairwise_rank_loss(const Expression& x, const Expression&...
      function Expression (line 94) | Expression poisson_loss(const Expression& x, unsigned y) { return Ex...
      function Expression (line 95) | Expression poisson_loss(const Expression& x, const unsigned* py) { r...
      function Expression (line 97) | Expression conv1d_narrow(const Expression& x, const Expression& f) {...
      function Expression (line 98) | Expression conv1d_wide(const Expression& x, const Expression& f) { r...
      function Expression (line 99) | Expression kmax_pooling(const Expression& x, unsigned k) { return Ex...
      function Expression (line 100) | Expression fold_rows(const Expression& x, unsigned nrows) { return E...
      function Expression (line 102) | Expression pick(const Expression& x, unsigned v) { return Expression...
      function Expression (line 103) | Expression pick(const Expression& x, const vector<unsigned> & v) { r...
      function Expression (line 104) | Expression pick(const Expression& x, unsigned* pv) { return Expressi...
      function Expression (line 105) | Expression pick(const Expression& x, const vector<unsigned> * pv) { ...
      function Expression (line 107) | Expression pickrange(const Expression& x, unsigned v, unsigned u) { ...
      function Expression (line 109) | Expression pickneglogsoftmax(const Expression& x, unsigned v) { retu...
      function Expression (line 110) | Expression pickneglogsoftmax(const Expression& x, const vector<unsig...
      function Expression (line 111) | Expression pickneglogsoftmax(const Expression& x, unsigned* pv) { re...
      function Expression (line 112) | Expression pickneglogsoftmax(const Expression& x, const vector<unsig...
      function Expression (line 114) | Expression sum_cols(const Expression& x) { return Expression(x.pg, x...
      function Expression (line 116) | Expression sum_batches(const Expression& x) { return Expression(x.pg...
      function Expression (line 118) | Expression kmh_ngram(const Expression& x, unsigned n) { return Expre...

FILE: cnn/cnn/expr.h
  function namespace (line 7) | namespace cnn { namespace expr {

FILE: cnn/cnn/fast-lstm.cc
  type cnn (line 13) | namespace cnn {
    function Expression (line 96) | Expression FastLSTMBuilder::add_input_impl(int prev, const Expression&...

FILE: cnn/cnn/fast-lstm.h
  function namespace (line 10) | namespace cnn {

FILE: cnn/cnn/functors.h
  function namespace (line 25) | namespace cnn {
  type FL1Backward (line 40) | struct FL1Backward {
  type FHuberBackward (line 48) | struct FHuberBackward {
  type FProduct (line 58) | struct FProduct {
  type FQuotient (line 64) | struct FQuotient {
  type FConstantPlus (line 70) | struct FConstantPlus {
  type FConstantMinus (line 78) | struct FConstantMinus {
  type FNegate (line 86) | struct FNegate {
  type FErf (line 92) | struct FErf {
  type FTanh (line 98) | struct FTanh {
  type FLog (line 111) | struct FLog {
  type FMaxBackwardInv (line 117) | struct FMaxBackwardInv {
  type FSqrtBackward (line 123) | struct FSqrtBackward {
  type FErfBackward (line 129) | struct FErfBackward {
  type FTanhBackward (line 135) | struct FTanhBackward {
  type FLogBackward (line 141) | struct FLogBackward {
  type FPairwiseRankLoss (line 147) | struct FPairwiseRankLoss {
  type FRectifyBackward (line 156) | struct FRectifyBackward {
  type FRectifyNegateBackward (line 162) | struct FRectifyNegateBackward {
  type FSoftmaxNormalize (line 168) | struct FSoftmaxNormalize {
  type FSoftmaxBackward (line 176) | struct FSoftmaxBackward {
  type FLogGammaBackward (line 184) | struct FLogGammaBackward {
  type FNegLogSoftmaxBackward (line 195) | struct FNegLogSoftmaxBackward {
  type FPtrNegLogSoftmaxBackward (line 204) | struct FPtrNegLogSoftmaxBackward {
  type FLogSoftmaxNormalize (line 213) | struct FLogSoftmaxNormalize {
  type FWeightedError (line 221) | struct FWeightedError {
  type FLogSoftmaxBackward (line 227) | struct FLogSoftmaxBackward {
  type FRectify (line 236) | struct FRectify {
  type FSoftSign (line 242) | struct FSoftSign {
  type FSoftSignBackward (line 248) | struct FSoftSignBackward {
  type FLogisticSigmoid (line 255) | struct FLogisticSigmoid {
  type FLogisticSigmoidBackward (line 261) | struct FLogisticSigmoidBackward {
  type FSqDist (line 267) | struct FSqDist {
  type FEuclideanBackward (line 274) | struct FEuclideanBackward {
  type FL2SGDUpdate (line 283) | struct FL2SGDUpdate {
  type FBinaryLogLoss (line 292) | struct FBinaryLogLoss {
  type FBinaryLogLossBackward (line 310) | struct FBinaryLogLossBackward {

FILE: cnn/cnn/gpu-kernels.h
  function namespace (line 6) | namespace cnn {

FILE: cnn/cnn/gpu-ops.h
  function namespace (line 4) | namespace cnn {

FILE: cnn/cnn/grad-check.cc
  type cnn (line 12) | namespace cnn {
    function CheckGrad (line 14) | bool CheckGrad(Model& m, ComputationGraph& g, int verbosity) {

FILE: cnn/cnn/grad-check.h
  function namespace (line 4) | namespace cnn {

FILE: cnn/cnn/graph.cc
  type cnn (line 8) | namespace cnn {
    function GraphOptimize (line 10) | void GraphOptimize(ComputationGraph* cg) {

FILE: cnn/cnn/graph.h
  function namespace (line 4) | namespace cnn {

FILE: cnn/cnn/gru.cc
  type cnn (line 13) | namespace cnn {
    function Expression (line 77) | Expression GRUBuilder::add_input_impl(int prev, const Expression& x) {

FILE: cnn/cnn/gru.h
  function namespace (line 7) | namespace cnn {

FILE: cnn/cnn/hsm-builder.cc
  type cnn (line 13) | namespace cnn {
    function Cluster (line 26) | Cluster* Cluster::add_child(unsigned sym) {
    function Cluster (line 80) | const Cluster* Cluster::get_child(unsigned i) const {
    function Expression (line 90) | Expression Cluster::predict(Expression h, ComputationGraph& cg) const {
    function Expression (line 101) | Expression Cluster::neg_log_softmax(Expression h, unsigned r, Computat...
    function Expression (line 150) | Expression Cluster::get_weights(ComputationGraph& cg) const {
    function Expression (line 157) | Expression Cluster::get_bias(ComputationGraph& cg) const {
    function string (line 164) | string Cluster::toString() const {
    function Expression (line 191) | Expression HierarchicalSoftmaxBuilder::neg_log_softmax(const Expressio...
    function is_ws (line 232) | inline bool is_ws(char x) { return (x == ' ' || x == '\t'); }
    function not_ws (line 233) | inline bool not_ws(char x) { return (x != ' ' && x != '\t'); }
    function Cluster (line 235) | Cluster* HierarchicalSoftmaxBuilder::ReadClusterFile(const std::string...

FILE: cnn/cnn/hsm-builder.h
  function namespace (line 12) | namespace cnn {

FILE: cnn/cnn/init.cc
  type cnn (line 16) | namespace cnn {
    function RemoveArgs (line 26) | static void RemoveArgs(int& argc, char**& argv, int& argi, int n) {
    function Initialize (line 33) | void Initialize(int& argc, char**& argv, unsigned random_seed, bool sh...
    function Cleanup (line 93) | void Cleanup() {

FILE: cnn/cnn/init.h
  function namespace (line 4) | namespace cnn {

FILE: cnn/cnn/lstm.cc
  type cnn (line 13) | namespace cnn {
    function Expression (line 92) | Expression LSTMBuilder::add_input_impl(int prev, const Expression& x) {

FILE: cnn/cnn/lstm.h
  function namespace (line 10) | namespace cnn {

FILE: cnn/cnn/mem.cc
  type cnn (line 19) | namespace cnn {

FILE: cnn/cnn/mem.h
  function namespace (line 6) | namespace cnn {
  function MemAllocator (line 26) | struct CPUAllocator : public MemAllocator {
  function MemAllocator (line 33) | struct SharedAllocator : public MemAllocator {
  function MemAllocator (line 41) | struct GPUAllocator : public MemAllocator {

FILE: cnn/cnn/model.cc
  type cnn (line 21) | namespace cnn {
    function Parameters (line 201) | Parameters* Model::add_parameters(const Dim& d, float scale) {
    function LookupParameters (line 208) | LookupParameters* Model::add_lookup_parameters(unsigned n, const Dim& ...
    function save_cnn_model (line 220) | void save_cnn_model(std::string filename, Model* model) {
    function load_cnn_model (line 226) | void load_cnn_model(std::string filename, Model* model) {

FILE: cnn/cnn/model.h
  function namespace (line 14) | namespace cnn {
  function ParametersBase (line 58) | struct LookupParameters : public ParametersBase {
  function gradient_l2_norm (line 107) | float gradient_l2_norm() const;

FILE: cnn/cnn/mp.cc
  type cnn (line 5) | namespace cnn {
    type mp (line 6) | namespace mp {
      function GenerateQueueName (line 14) | std::string GenerateQueueName() {
      function GenerateSharedMemoryName (line 21) | std::string GenerateSharedMemoryName() {
      function SumValues (line 28) | cnn::real SumValues(const std::vector<cnn::real>& values) {
      function Mean (line 32) | cnn::real Mean(const std::vector<cnn::real>& values) {
      function ElapsedTimeString (line 36) | std::string ElapsedTimeString(const timespec& start, const timespec&...
      function SpawnChildren (line 44) | unsigned SpawnChildren(std::vector<Workload>& workloads) {
      function CreateWorkloads (line 64) | std::vector<Workload> CreateWorkloads(unsigned num_children) {

FILE: cnn/cnn/mp.h
  function namespace (line 28) | namespace cnn {

FILE: cnn/cnn/nodes-common.cc
  type cnn (line 9) | namespace cnn {
    function LooksLikeVector (line 11) | inline bool LooksLikeVector(const Dim& d) {
    function string (line 20) | string SparsemaxLoss::as_string(const vector<string>& arg_names) const {
    function Dim (line 26) | Dim SparsemaxLoss::dim_forward(const vector<Dim>& xs) const {
    function string (line 34) | string Sparsemax::as_string(const vector<string>& arg_names) const {
    function Dim (line 40) | Dim Sparsemax::dim_forward(const vector<Dim>& xs) const {
    function string (line 48) | string MatrixInverse::as_string(const vector<string>& arg_names) const {
    function Dim (line 54) | Dim MatrixInverse::dim_forward(const vector<Dim>& xs) const {
    function Dim (line 58) | Dim LogDet::dim_forward(const vector<Dim>& xs) const {
    function string (line 66) | string LogDet::as_string(const vector<string>& arg_names) const {
    function string (line 72) | string AddMv::as_string(const vector<string>& arg_names) const {
    function Dim (line 78) | Dim AddMv::dim_forward(const vector<Dim>& xs) const {
    function string (line 89) | string SelectRows::as_string(const vector<string>& arg_names) const {
    function Dim (line 95) | Dim SelectRows::dim_forward(const vector<Dim>& xs) const {
    function string (line 105) | string SelectCols::as_string(const vector<string>& arg_names) const {
    function Dim (line 111) | Dim SelectCols::dim_forward(const vector<Dim>& xs) const {
    function string (line 120) | string Min::as_string(const vector<string>& arg_names) const {
    function Dim (line 126) | Dim Min::dim_forward(const vector<Dim>& xs) const {
    function string (line 134) | string Max::as_string(const vector<string>& arg_names) const {
    function Dim (line 140) | Dim Max::dim_forward(const vector<Dim>& xs) const {
    function string (line 148) | string TraceOfProduct::as_string(const vector<string>& arg_names) const {
    function Dim (line 154) | Dim TraceOfProduct::dim_forward(const vector<Dim>& xs) const {
    function string (line 162) | string ConstScalarMultiply::as_string(const vector<string>& arg_names)...
    function Dim (line 168) | Dim ConstScalarMultiply::dim_forward(const vector<Dim>& xs) const {
    function string (line 176) | string DotProduct::as_string(const vector<string>& arg_names) const {
    function Dim (line 182) | Dim DotProduct::dim_forward(const vector<Dim>& xs) const {
    function string (line 193) | string Transpose::as_string(const vector<string>& arg_names) const {
    function Dim (line 199) | Dim Transpose::dim_forward(const vector<Dim>& xs) const {
    function string (line 207) | string Reshape::as_string(const vector<string>& arg_names) const {
    function Dim (line 213) | Dim Reshape::dim_forward(const vector<Dim>& xs) const {
    function string (line 219) | string SumColumns::as_string(const vector<string>& arg_names) const {
    function Dim (line 227) | Dim SumColumns::dim_forward(const vector<Dim>& xs) const {
    function string (line 233) | string KMHNGram::as_string(const vector<string>& arg_names) const {
    function Dim (line 239) | Dim KMHNGram::dim_forward(const vector<Dim>& xs) const {
    function string (line 249) | string InnerProduct3D_1D::as_string(const vector<string>& arg_names) c...
    function Dim (line 256) | Dim InnerProduct3D_1D::dim_forward(const vector<Dim>& xs) const {
    function string (line 274) | string InnerProduct3D_1D_1D::as_string(const vector<string>& arg_names...
    function Dim (line 281) | Dim InnerProduct3D_1D_1D::dim_forward(const vector<Dim>& xs) const {
    function string (line 300) | string GaussianNoise::as_string(const vector<string>& arg_names) const {
    function Dim (line 306) | Dim GaussianNoise::dim_forward(const vector<Dim>& xs) const {
    function string (line 311) | string Dropout::as_string(const vector<string>& arg_names) const {
    function Dim (line 317) | Dim Dropout::dim_forward(const vector<Dim>& xs) const {
    function string (line 322) | string BlockDropout::as_string(const vector<string>& arg_names) const {
    function Dim (line 328) | Dim BlockDropout::dim_forward(const vector<Dim>& xs) const {
    function string (line 333) | string ConstantPlusX::as_string(const vector<string>& arg_names) const {
    function Dim (line 339) | Dim ConstantPlusX::dim_forward(const vector<Dim>& xs) const {
    function string (line 344) | string ConstantMinusX::as_string(const vector<string>& arg_names) const {
    function Dim (line 350) | Dim ConstantMinusX::dim_forward(const vector<Dim>& xs) const {
    function string (line 355) | string LogSumExp::as_string(const vector<string>& arg_names) const {
    function Dim (line 364) | Dim LogSumExp::dim_forward(const vector<Dim>& xs) const {
    function string (line 375) | string Sum::as_string(const vector<string>& arg_names) const {
    function Dim (line 383) | Dim Sum::dim_forward(const vector<Dim>& xs) const {
    function string (line 395) | string SumBatches::as_string(const vector<string>& arg_names) const {
    function Dim (line 401) | Dim SumBatches::dim_forward(const vector<Dim>& xs) const {
    function string (line 406) | string Average::as_string(const vector<string>& arg_names) const {
    function Dim (line 415) | Dim Average::dim_forward(const vector<Dim>& xs) const {
    function string (line 427) | string Sqrt::as_string(const vector<string>& arg_names) const {
    function Dim (line 433) | Dim Sqrt::dim_forward(const vector<Dim>& xs) const {
    function string (line 438) | string Erf::as_string(const vector<string>& arg_names) const {
    function Dim (line 444) | Dim Erf::dim_forward(const vector<Dim>& xs) const {
    function string (line 449) | string Tanh::as_string(const vector<string>& arg_names) const {
    function Dim (line 455) | Dim Tanh::dim_forward(const vector<Dim>& xs) const {
    function string (line 460) | string Square::as_string(const vector<string>& arg_names) const {
    function Dim (line 466) | Dim Square::dim_forward(const vector<Dim>& xs) const {
    function string (line 471) | string Cube::as_string(const vector<string>& arg_names) const {
    function Dim (line 477) | Dim Cube::dim_forward(const vector<Dim>& xs) const {
    function string (line 482) | string Exp::as_string(const vector<string>& arg_names) const {
    function Dim (line 488) | Dim Exp::dim_forward(const vector<Dim>& xs) const {
    function string (line 493) | string LogGamma::as_string(const vector<string>& arg_names) const {
    function Dim (line 499) | Dim LogGamma::dim_forward(const vector<Dim>& xs) const {
    function string (line 504) | string Log::as_string(const vector<string>& arg_names) const {
    function Dim (line 510) | Dim Log::dim_forward(const vector<Dim>& xs) const {
    function string (line 515) | string Concatenate::as_string(const vector<string>& arg_names) const {
    function Dim (line 525) | Dim Concatenate::dim_forward(const vector<Dim>& xs) const {
    function string (line 543) | string ConcatenateColumns::as_string(const vector<string>& arg_names) ...
    function Dim (line 553) | Dim ConcatenateColumns::dim_forward(const vector<Dim>& xs) const {
    function string (line 569) | string PairwiseRankLoss::as_string(const vector<string>& arg_names) co...
    function Dim (line 575) | Dim PairwiseRankLoss::dim_forward(const vector<Dim>& xs) const {
    function string (line 586) | string Hinge::as_string(const vector<string>& arg_names) const {
    function Dim (line 592) | Dim Hinge::dim_forward(const vector<Dim>& xs) const {
    function string (line 600) | string Identity::as_string(const vector<string>& arg_names) const {
    function Dim (line 604) | Dim Identity::dim_forward(const vector<Dim>& xs) const {
    function string (line 609) | string NoBackprop::as_string(const vector<string>& arg_names) const {
    function Dim (line 615) | Dim NoBackprop::dim_forward(const vector<Dim>& xs) const {
    function string (line 620) | string Softmax::as_string(const vector<string>& arg_names) const {
    function Dim (line 626) | Dim Softmax::dim_forward(const vector<Dim>& xs) const {
    function string (line 635) | string SoftSign::as_string(const vector<string>& arg_names) const {
    function Dim (line 641) | Dim SoftSign::dim_forward(const vector<Dim>& xs) const {
    function string (line 650) | string PickNegLogSoftmax::as_string(const vector<string>& arg_names) c...
    function Dim (line 663) | Dim PickNegLogSoftmax::dim_forward(const vector<Dim>& xs) const {
    function string (line 672) | string LogSoftmax::as_string(const vector<string>& arg_names) const {
    function Dim (line 678) | Dim LogSoftmax::dim_forward(const vector<Dim>& xs) const {
    function string (line 687) | string RestrictedLogSoftmax::as_string(const vector<string>& arg_names...
    function Dim (line 693) | Dim RestrictedLogSoftmax::dim_forward(const vector<Dim>& xs) const {
    function string (line 702) | string PickElement::as_string(const vector<string>& arg_names) const {
    function Dim (line 708) | Dim PickElement::dim_forward(const vector<Dim>& xs) const {
    function string (line 719) | string PickRange::as_string(const vector<string>& arg_names) const {
    function Dim (line 725) | Dim PickRange::dim_forward(const vector<Dim>& xs) const {
    function string (line 735) | string MatrixMultiply::as_string(const vector<string>& arg_names) const {
    function Dim (line 741) | Dim MatrixMultiply::dim_forward(const vector<Dim>& xs) const {
    function string (line 751) | string CwiseMultiply::as_string(const vector<string>& arg_names) const {
    function Dim (line 757) | Dim CwiseMultiply::dim_forward(const vector<Dim>& xs) const {
    function string (line 768) | string Pow::as_string(const vector<string>& arg_names) const {
    function Dim (line 774) | Dim Pow::dim_forward(const vector<Dim>& xs) const {
    function string (line 784) | string CwiseQuotient::as_string(const vector<string>& arg_names) const {
    function Dim (line 790) | Dim CwiseQuotient::dim_forward(const vector<Dim>& xs) const {
    function string (line 801) | string AffineTransform::as_string(const vector<string>& arg_names) con...
    function Dim (line 809) | Dim AffineTransform::dim_forward(const vector<Dim>& xs) const {
    function string (line 827) | string Negate::as_string(const vector<string>& arg_names) const {
    function Dim (line 833) | Dim Negate::dim_forward(const vector<Dim>& xs) const {
    function string (line 838) | string Rectify::as_string(const vector<string>& arg_names) const {
    function Dim (line 844) | Dim Rectify::dim_forward(const vector<Dim>& xs) const {
    function string (line 849) | string HuberDistance::as_string(const vector<string>& arg_names) const {
    function Dim (line 855) | Dim HuberDistance::dim_forward(const vector<Dim>& xs) const {
    function string (line 864) | string L1Distance::as_string(const vector<string>& arg_names) const {
    function Dim (line 870) | Dim L1Distance::dim_forward(const vector<Dim>& xs) const {
    function string (line 879) | string PoissonRegressionLoss::as_string(const vector<string>& arg_name...
    function Dim (line 885) | Dim PoissonRegressionLoss::dim_forward(const vector<Dim>& xs) const {
    function string (line 893) | string SquaredNorm::as_string(const vector<string>& arg_names) const {
    function Dim (line 899) | Dim SquaredNorm::dim_forward(const vector<Dim>& xs) const {
    function string (line 904) | string SquaredEuclideanDistance::as_string(const vector<string>& arg_n...
    function Dim (line 910) | Dim SquaredEuclideanDistance::dim_forward(const vector<Dim>& xs) const {
    function string (line 919) | string LogisticSigmoid::as_string(const vector<string>& arg_names) con...
    function Dim (line 925) | Dim LogisticSigmoid::dim_forward(const vector<Dim>& xs) const {
    function string (line 930) | string BinaryLogLoss::as_string(const vector<string>& arg_names) const {
    function Dim (line 936) | Dim BinaryLogLoss::dim_forward(const vector<Dim>& xs) const {

FILE: cnn/cnn/nodes.cc
  type cnn (line 36) | namespace cnn {
    function EIGEN_STRONG_INLINE (line 770) | EIGEN_STRONG_INLINE float logsumexp(const T& x) {
    function logdet (line 788) | inline typename MatrixType::Scalar logdet(const MatrixType& M, bool us...
    function EIGEN_STRONG_INLINE (line 1495) | EIGEN_STRONG_INLINE real logsumexp(const T& x, const vector<unsigned>&...
    function CUDAMatrixMultiply (line 1622) | inline void CUDAMatrixMultiply(const Tensor& l, const Tensor& r, Tenso...
    function string (line 2151) | string Zeroes::as_string(const vector<string>& arg_names) const {
    function Dim (line 2157) | Dim Zeroes::dim_forward(const vector<Dim>& xs) const {

FILE: cnn/cnn/nodes.h
  function Node (line 11) | struct SparsemaxLoss : public Node {
  function Node (line 106) | struct Pow : public Node {
  function Node (line 119) | struct Min : public Node {
  function Node (line 268) | struct InnerProduct3D_1D_1D : public Node {
  function Node (line 282) | struct GaussianNoise : public Node {
  type BlockDropout (line 314) | struct BlockDropout
  function explicit (line 315) | explicit BlockDropout(const std::initializer_list<VariableIndex>& a, rea...
  function aux_storage_size (line 318) | size_t aux_storage_size() const override;
  function Node (line 346) | struct ConstantMinusX : public Node {
  function Node (line 361) | struct Sqrt : public Node {
  function Node (line 375) | struct Erf : public Node {
  function Node (line 389) | struct Tanh : public Node {
  function Node (line 403) | struct Square : public Node {
  function Node (line 417) | struct Cube : public Node {
  function Node (line 431) | struct Exp : public Node {
  function Node (line 445) | struct LogGamma : public Node {
  function Node (line 459) | struct Log : public Node {
  function Node (line 473) | struct Concatenate : public Node {
  function Node (line 490) | struct ConcatenateColumns : public Node {
  function Node (line 506) | struct PairwiseRankLoss : public Node {
  function Node (line 522) | struct Hinge : public Node {
  function Node (line 554) | struct Identity : public Node {
  function Node (line 571) | struct MaxPooling1D : public Node {
  function Node (line 586) | struct MatrixMultiply : public Node {
  function Node (line 600) | struct CwiseMultiply : public Node {
  function Node (line 614) | struct CwiseQuotient : public Node {
  function Node (line 628) | struct AffineTransform : public Node {
  function Node (line 642) | struct Negate : public Node {
  function Node (line 656) | struct Rectify : public Node {
  function Node (line 674) | struct BinaryLogLoss : public Node {
  function Node (line 688) | struct LogSumExp : public Node {

FILE: cnn/cnn/param-nodes.cc
  type cnn (line 8) | namespace cnn {
    function string (line 10) | string ConstParameterNode::as_string(const vector<string>& arg_names) ...
    function Dim (line 16) | Dim ConstParameterNode::dim_forward(const vector<Dim>& xs) const {
    function string (line 35) | string ParameterNode::as_string(const vector<string>& arg_names) const {
    function Dim (line 41) | Dim ParameterNode::dim_forward(const vector<Dim>& xs) const {
    function string (line 64) | string InputNode::as_string(const vector<string>& arg_names) const {
    function Dim (line 70) | Dim InputNode::dim_forward(const vector<Dim>& xs) const {
    function string (line 99) | string ScalarInputNode::as_string(const vector<string>& arg_names) con...
    function Dim (line 105) | Dim ScalarInputNode::dim_forward(const vector<Dim>& xs) const {
    function string (line 127) | string LookupNode::as_string(const vector<string>& arg_names) const {
    function Dim (line 133) | Dim LookupNode::dim_forward(const vector<Dim>& xs) const {

FILE: cnn/cnn/param-nodes.h
  function namespace (line 7) | namespace cnn {

FILE: cnn/cnn/random.h
  function namespace (line 6) | namespace cnn {

FILE: cnn/cnn/rnn-state-machine.cc
  type cnn (line 8) | namespace cnn {

FILE: cnn/cnn/rnn-state-machine.h
  function namespace (line 4) | namespace cnn {

FILE: cnn/cnn/rnn.cc
  type cnn (line 15) | namespace cnn {
    function Expression (line 66) | Expression SimpleRNNBuilder::add_input_impl(int prev, const Expression...
    function Expression (line 90) | Expression SimpleRNNBuilder::add_auxiliary_input(const Expression &in,...

FILE: cnn/cnn/rnn.h
  function namespace (line 10) | namespace cnn {

FILE: cnn/cnn/saxe-init.cc
  type cnn (line 11) | namespace cnn {
    function OrthonormalRandom (line 13) | void OrthonormalRandom(unsigned dd, float g, Tensor& x) {

FILE: cnn/cnn/saxe-init.h
  function namespace (line 4) | namespace cnn {

FILE: cnn/cnn/shadow-params.cc
  type cnn (line 9) | namespace cnn {
    function AllocateShadowParameters (line 23) | vector<ShadowParameters> AllocateShadowParameters(const Model& m) {
    function AllocateShadowLookupParameters (line 31) | vector<ShadowLookupParameters> AllocateShadowLookupParameters(const Mo...

FILE: cnn/cnn/shadow-params.h
  function namespace (line 11) | namespace cnn {

FILE: cnn/cnn/simd-functors.h
  function namespace (line 21) | namespace cnn {
  function namespace (line 36) | namespace Eigen { namespace internal {
  function namespace (line 46) | namespace cnn {
  function namespace (line 61) | namespace Eigen { namespace internal {
  function namespace (line 71) | namespace cnn {
  function namespace (line 88) | namespace Eigen { namespace internal {
  function namespace (line 99) | namespace cnn {
  function namespace (line 116) | namespace Eigen { namespace internal {
  function namespace (line 126) | namespace cnn {
  function namespace (line 142) | namespace Eigen { namespace internal {
  function namespace (line 152) | namespace cnn {
  function namespace (line 161) | namespace Eigen { namespace internal {
  function namespace (line 171) | namespace cnn {
  function namespace (line 184) | namespace Eigen { namespace internal {
  function namespace (line 194) | namespace cnn {
  function namespace (line 215) | namespace Eigen { namespace internal {

FILE: cnn/cnn/tensor.cc
  type cnn (line 13) | namespace cnn {
    function ostream (line 15) | ostream& operator<<(ostream& os, const Tensor& t) {
    function real (line 26) | real as_scalar(const Tensor& t) {
    function as_vector (line 37) | vector<real> as_vector(const Tensor& v) {
    function real (line 152) | real rand01() {
    function rand0n (line 157) | int rand0n(int n) {
    function real (line 164) | real rand_normal() {

FILE: cnn/cnn/tensor.h
  function namespace (line 24) | namespace cnn {
  type TensorTools (line 209) | struct TensorTools {

FILE: cnn/cnn/tests/test_edges.cc
  function Dim (line 17) | Dim size(const Tensor& t) {
  function BOOST_AUTO_TEST_CASE (line 23) | BOOST_AUTO_TEST_CASE(ESqrL2)
  function BOOST_AUTO_TEST_CASE (line 45) | BOOST_AUTO_TEST_CASE(EMatrixMultiply) {
  function BOOST_AUTO_TEST_CASE (line 76) | BOOST_AUTO_TEST_CASE(EColumnConcat)
  function BOOST_AUTO_TEST_CASE (line 114) | BOOST_AUTO_TEST_CASE(ERowConcat)
  function BOOST_AUTO_TEST_CASE (line 150) | BOOST_AUTO_TEST_CASE(EMultilinear) {
  function BOOST_AUTO_TEST_CASE (line 198) | BOOST_AUTO_TEST_CASE(ELogisticSigmoid) {
  function BOOST_AUTO_TEST_CASE (line 220) | BOOST_AUTO_TEST_CASE(ETanh) {
  function BOOST_AUTO_TEST_CASE (line 240) | BOOST_AUTO_TEST_CASE(MatrixVector) {
  function BOOST_AUTO_TEST_CASE (line 266) | BOOST_AUTO_TEST_CASE(EConstantMinus) {
  function BOOST_AUTO_TEST_CASE (line 283) | BOOST_AUTO_TEST_CASE(ESoftmaxUnif) {
  function BOOST_AUTO_TEST_CASE (line 315) | BOOST_AUTO_TEST_CASE(TensorInner3D_1D) {

FILE: cnn/cnn/tests/test_init.cc
  function BOOST_AUTO_TEST_CASE (line 16) | BOOST_AUTO_TEST_CASE(EOrthonormalRandom)
  function BOOST_AUTO_TEST_CASE (line 45) | BOOST_AUTO_TEST_CASE(BernoulliInit) {
  function BOOST_AUTO_TEST_CASE (line 55) | BOOST_AUTO_TEST_CASE(Rand01) {

FILE: cnn/cnn/tests/test_utils.h
  function namespace (line 6) | namespace cnn {

FILE: cnn/cnn/timing.h
  function namespace (line 8) | namespace cnn {

FILE: cnn/cnn/training.cc
  type cnn (line 5) | namespace cnn {
    function is_valid (line 10) | bool is_valid(const Eigen::MatrixBase<Derived>& x) {

FILE: cnn/cnn/training.h
  function namespace (line 8) | namespace cnn {
  function Trainer (line 47) | struct SimpleSGDTrainer : public Trainer {
  function Trainer (line 53) | struct MomentumSGDTrainer : public Trainer {
  function Trainer (line 69) | struct AdagradTrainer : public Trainer {
  function Trainer (line 80) | struct AdadeltaTrainer : public Trainer {
  function Trainer (line 94) | struct RmsPropTrainer : public Trainer {
  function Trainer (line 106) | struct AdamTrainer : public Trainer {

FILE: cnn/examples/embed-cl.cc
  type Encoder (line 27) | struct Encoder {
    method Encoder (line 31) | explicit Encoder(Model& model) {
    method Expression (line 36) | Expression EmbedSource(const vector<int>& sent, ComputationGraph& cg) {
    method Expression (line 51) | Expression EmbedTarget(const vector<int>& sent, ComputationGraph& cg) {
  function main (line 66) | int main(int argc, char** argv) {

FILE: cnn/examples/encdec.cc
  type EncoderDecoder (line 33) | struct EncoderDecoder {
    method EncoderDecoder (line 45) | explicit EncoderDecoder(Model& model) :
    method Expression (line 62) | Expression BuildGraph(const vector<int>& insent, const vector<int>& os...
  function main (line 122) | int main(int argc, char** argv) {

FILE: cnn/examples/mlc.cc
  type TrainingInstance (line 18) | struct TrainingInstance {
    method TrainingInstance (line 19) | TrainingInstance() {}
    method TrainingInstance (line 20) | TrainingInstance(const vector<pair<unsigned,float>>& x, const vector<u...
  function swap (line 25) | void swap(TrainingInstance& a, TrainingInstance& b) {
  function ReadFiles (line 33) | vector<TrainingInstance> ReadFiles(const char* xfname, const char* yfnam...
  type MLCBuilder (line 80) | struct MLCBuilder {
    method MLCBuilder (line 81) | explicit MLCBuilder(Model& m, unsigned nfeats, unsigned labels) {
    method Expression (line 91) | Expression BuildPredictionScores(ComputationGraph& cg, const vector<pa...
  function main (line 109) | int main(int argc, char** argv) {

FILE: cnn/examples/nlm.cc
  function main (line 16) | int main(int argc, char** argv) {

FILE: cnn/examples/poisson-regression.cc
  type RNNLengthPredictor (line 33) | struct RNNLengthPredictor {
    method RNNLengthPredictor (line 38) | explicit RNNLengthPredictor(Model& model) : builder(LAYERS, INPUT_DIM,...
    method Expression (line 45) | Expression BuildLMGraph(const vector<int>& sent, unsigned len, Computa...
  function main (line 66) | int main(int argc, char** argv) {

FILE: cnn/examples/read-write.cc
  class XORModel (line 20) | class XORModel {
    method XORModel (line 30) | XORModel() {}
    method XORModel (line 32) | XORModel(const unsigned& hidden_len, Model *m) {
    method InitParams (line 37) | void InitParams(Model *m) {
    method AddParamsToCG (line 44) | void AddParamsToCG(ComputationGraph *cg) {
    method Train (line 51) | float Train(vector<cnn::real> &input, cnn::real &gold_output,
    method Decode (line 68) | float Decode(vector<cnn::real> &input) {
    method serialize (line 81) | void serialize(Archive& ar, const unsigned int) {
  function WriteToFile (line 89) | void WriteToFile(string& filename, XORModel &model, Model &cnn_model) {
  function ReadFromFile (line 101) | void ReadFromFile(string& filename, XORModel *model, Model *cnn_model) {
  function main (line 119) | int main(int argc, char** argv) {

FILE: cnn/examples/rnnlm-aevb.cc
  type RNNLanguageModel (line 35) | struct RNNLanguageModel {
    method RNNLanguageModel (line 52) | explicit RNNLanguageModel(Model& model) :
    method Expression (line 71) | Expression BuildLMGraph(const vector<int>& sent, ComputationGraph& cg,...
  function main (line 121) | int main(int argc, char** argv) {

FILE: cnn/examples/rnnlm-batch.cc
  type RNNLanguageModel (line 33) | struct RNNLanguageModel {
    method RNNLanguageModel (line 38) | explicit RNNLanguageModel(Model& model) : builder(LAYERS, INPUT_DIM, H...
    method Expression (line 45) | Expression BuildLMGraphs(const vector<vector<int> >& sents,
    method RandomSample (line 75) | void RandomSample(int max_len = 150) {
  type CompareLen (line 113) | struct CompareLen {
  function main (line 119) | int main(int argc, char** argv) {

FILE: cnn/examples/rnnlm-cfsm.cc
  type RNNLanguageModel (line 32) | struct RNNLanguageModel {
    method RNNLanguageModel (line 36) | explicit RNNLanguageModel(Model& model, ClassFactoredSoftmaxBuilder& h) :
    method Expression (line 42) | Expression BuildLMGraph(const vector<int>& sent, ComputationGraph& cg) {
    method RandomSample (line 62) | void RandomSample(int max_len = 150) {
  function main (line 83) | int main(int argc, char** argv) {

FILE: cnn/examples/rnnlm-givenbag.cc
  type RNNLanguageModel (line 32) | struct RNNLanguageModel {
    method RNNLanguageModel (line 37) | explicit RNNLanguageModel(Model& model) : builder(LAYERS, INPUT_DIM, H...
    method Expression (line 44) | Expression BuildLMGraph(const vector<int>& sent, ComputationGraph& cg,...
    method RandomSample (line 69) | void RandomSample(int max_len = 150) {
  function main (line 106) | int main(int argc, char** argv) {

FILE: cnn/examples/rnnlm-mp.cc
  function ReadData (line 27) | vector<Datum> ReadData(string filename) {
  class Learner (line 42) | class Learner : public ILearner<D, cnn::real> {
    method Learner (line 44) | explicit Learner(RNNLanguageModel<T>& rnnlm, unsigned data_size) : rnn...
    method LearnFromDatum (line 47) | cnn::real LearnFromDatum(const D& datum, bool learn) {
    method SaveModel (line 57) | void SaveModel() {}
  function main (line 63) | int main(int argc, char** argv) {

FILE: cnn/examples/rnnlm.cc
  type RNNLanguageModel (line 31) | struct RNNLanguageModel {
    method RNNLanguageModel (line 36) | explicit RNNLanguageModel(Model& model) : builder(LAYERS, INPUT_DIM, H...
    method Expression (line 43) | Expression BuildLMGraph(const vector<int>& sent, ComputationGraph& cg) {
    method RandomSample (line 80) | void RandomSample(int max_len = 150) {
  function main (line 117) | int main(int argc, char** argv) {

FILE: cnn/examples/rnnlm.h
  function explicit (line 27) | explicit RNNLanguageModel(Model& model) : builder(LAYERS, INPUT_DIM, HID...
  function Expression (line 36) | Expression BuildLMGraph(const vector<int>& sent, ComputationGraph& cg) {

FILE: cnn/examples/rnnlm2.cc
  type RNNLanguageModel (line 31) | struct RNNLanguageModel {
    method RNNLanguageModel (line 36) | explicit RNNLanguageModel(Model& model) : builder(LAYERS, INPUT_DIM, H...
    method Expression (line 43) | Expression BuildLMGraph(const vector<int>& sent, ComputationGraph& cg) {
    method RandomSample (line 85) | void RandomSample(int max_len = 150) {
  function main (line 122) | int main(int argc, char** argv) {

FILE: cnn/examples/segrnn-sup.cc
  type PKey (line 30) | struct PKey {
    method PKey (line 31) | PKey(int x1, int x2, unsigned x3)
  type std (line 43) | namespace std {
    type hash<PKey> (line 45) | struct hash<PKey>
  type SymbolEmbedding (line 73) | struct SymbolEmbedding {
    method SymbolEmbedding (line 74) | SymbolEmbedding(Model& m, unsigned n, unsigned dim) {
    method load_embedding (line 77) | void load_embedding(cnn::Dict& d, string pretrain_path){
    method new_graph (line 96) | void new_graph(ComputationGraph& g) { cg = &g; }
    method Expression (line 97) | Expression embed(unsigned label_id) {
  type DurationEmbedding (line 104) | struct DurationEmbedding {
  type MLPDurationEmbedding (line 112) | struct MLPDurationEmbedding : public DurationEmbedding {
    method MLPDurationEmbedding (line 113) | MLPDurationEmbedding(Model& m, unsigned hidden, unsigned dim) {
    method new_graph (line 125) | void new_graph(ComputationGraph& g) override {
    method Expression (line 133) | Expression embed(unsigned dur) override {
  type BinnedDurationEmbedding (line 153) | struct BinnedDurationEmbedding : public DurationEmbedding {
    method BinnedDurationEmbedding (line 154) | BinnedDurationEmbedding(Model& m, unsigned dim, unsigned num_bins = 8)...
    method new_graph (line 157) | void new_graph(ComputationGraph& g) override {
    method Expression (line 160) | Expression embed(unsigned dur) override {
  type BiTrans (line 171) | struct BiTrans {
    method BiTrans (line 178) | explicit BiTrans(Model& model) :
    method transcribe (line 186) | vector<Expression> transcribe(ComputationGraph& cg, const vector<Expre...
  type SegEmbedUni (line 220) | struct SegEmbedUni {
    method SegEmbedUni (line 225) | explicit SegEmbedUni(Model& m) :
    method construct_chart (line 229) | void construct_chart(ComputationGraph& cg, const vector<Expression>& c...
    method Expression (line 255) | const Expression& operator()(int i, int j) const {
  type SegEmbedBi (line 265) | struct SegEmbedBi {
    method SegEmbedBi (line 269) | explicit SegEmbedBi(Model& m) : fwd(m), rev(m) {}
    method construct_chart (line 270) | void construct_chart(ComputationGraph& cg, const vector<Expression>& c...
  type SegmentalRNN (line 301) | struct SegmentalRNN {
    method SegmentalRNN (line 309) | explicit SegmentalRNN(Model& model, cnn::Dict& d_, cnn::Dict& td_) :
    method ConstructInput (line 343) | vector<Expression> ConstructInput(const vector<int>& x,
    method ConstructSegmentMap (line 352) | unordered_map<PKey,Expression> ConstructSegmentMap(vector<Expression>&...
    method Expression (line 410) | Expression SupervisedCRFLoss(vector<Expression>& xins,
    method Expression (line 477) | Expression PartiallySupervisedCRFLoss(vector<Expression>& xins,
    method Expression (line 562) | Expression SumParts(int len,
    method Expression (line 594) | Expression SupervisedHingeLoss(vector<Expression>& xins,
    method PureDecode (line 612) | void PureDecode(int len,
    method ViterbiDecode (line 683) | void ViterbiDecode(vector<Expression>& xins,
  function ParseTrainingInstance (line 708) | pair<vector<int>,vector<pair<int,int>>> ParseTrainingInstance(const std:...
  function check_max_seg (line 744) | bool inline check_max_seg(const vector<pair<int,int>>& yz, int max_seg_l...
  function evaluate (line 756) | double evaluate(vector<vector<pair<int,int>>>& yz_preds,
  function test_only (line 839) | void test_only(SegmentalRNN<LSTMBuilder>& segrnn,
  function read_file (line 861) | void read_file(string file_path,
  function save_models (line 880) | void save_models(string model_file_prefix,
  function load_models (line 906) | void load_models(string model_file_prefix,
  function load_dicts (line 919) | void load_dicts(string model_file_prefix,
  function edit_distance (line 938) | unsigned int edit_distance(const std::string& s1, const std::string& s2)
  function evaluate_partial (line 952) | double evaluate_partial(vector<vector<pair<int,int>>>& yz_preds,
  function predict_and_evaluate (line 986) | double predict_and_evaluate(SegmentalRNN<LSTMBuilder>& segrnn,
  function main (line 1012) | int main(int argc, char** argv) {

FILE: cnn/examples/skiprnnlm.cc
  type RNNSkipLM (line 43) | struct RNNSkipLM {
    method RNNSkipLM (line 48) | explicit RNNSkipLM(Model& model) : builder(LAYERS, INPUT_DIM, HIDDEN_D...
    method Expression (line 55) | Expression BuildLMGraph(const Document& doc, ComputationGraph& cg) {
  function main (line 95) | int main(int argc, char** argv) {
  function read_documents (line 208) | void read_documents(const std::string &filename, Corpus &corpus) {

FILE: cnn/examples/tag-bilstm.cc
  type RNNLanguageModel (line 38) | struct RNNLanguageModel {
    method RNNLanguageModel (line 48) | explicit RNNLanguageModel(Model& model) :
    method Expression (line 61) | Expression BuildTaggingGraph(const vector<int>& sent, const vector<int...
  function main (line 115) | int main(int argc, char** argv) {

FILE: cnn/examples/textcat.cc
  type NeuralBagOfWords (line 31) | struct NeuralBagOfWords {
    method NeuralBagOfWords (line 38) | explicit NeuralBagOfWords(Model& m) :
    method Expression (line 45) | Expression BuildClassifier(const vector<int>& x, ComputationGraph& cg) {
  type ConvLayer (line 61) | struct ConvLayer {
    method ConvLayer (line 67) | ConvLayer(Model&m, int in_rows, int k_fold_rows, int filter_width, int...
    method apply (line 87) | vector<Expression> apply(ComputationGraph& cg, const vector<Expression...
  type ConvNet (line 116) | struct ConvNet {
    method ConvNet (line 123) | explicit ConvNet(Model& m) :
    method Expression (line 132) | Expression BuildClassifier(const vector<int>& x, ComputationGraph& cg,...
  function IsCurrentPredictionCorrection (line 156) | bool IsCurrentPredictionCorrection(ComputationGraph& cg, int y_true) {
  function Expression (line 166) | Expression CrossEntropyLoss(const Expression& y_pred, int y_true) {
  function Expression (line 172) | Expression HingeLoss(const Expression& y_pred, int y_true) {
  function main (line 177) | int main(int argc, char** argv) {

FILE: cnn/examples/tok-embed.cc
  function UTF8Len (line 43) | inline unsigned int UTF8Len(unsigned char x) {
  type PrefixNode (line 53) | struct PrefixNode {
    method PrefixNode (line 54) | PrefixNode() :
  type PrefixCode (line 76) | struct PrefixCode {
    method PrefixCode (line 77) | PrefixCode() : params_allocated(false) {}
    method PrefixNode (line 79) | PrefixNode* add(const string& pfc) {
    method AllocateParameters_rec (line 96) | void AllocateParameters_rec(Model& m, unsigned dim, PrefixNode* n) {
    method AllocateParameters (line 111) | void AllocateParameters(Model& m, unsigned dim) {
  type SymbolEmbedding (line 121) | struct SymbolEmbedding {
    method SymbolEmbedding (line 122) | SymbolEmbedding(Model& m, unsigned n, unsigned dim) {
    method new_graph (line 125) | void new_graph(ComputationGraph& g) { cg = &g; }
    method Expression (line 126) | Expression embed(unsigned label_id) {
  type PrefixCodeDecoder (line 133) | struct PrefixCodeDecoder {
    method PrefixCodeDecoder (line 137) | explicit PrefixCodeDecoder(Model& model, PrefixCode* pc) :
    method Expression (line 141) | Expression loss(ComputationGraph& cg, const Expression& v, const strin...
  type BiCharLSTM (line 171) | struct BiCharLSTM {
    method BiCharLSTM (line 181) | explicit BiCharLSTM(Model& model) :
    method Expression (line 192) | Expression embed(ComputationGraph& cg, const vector<unsigned>& x) {
  function main (line 221) | int main(int argc, char** argv) {

FILE: cnn/examples/xor-batch-lookup.cc
  function main (line 16) | int main(int argc, char** argv) {

FILE: cnn/examples/xor-batch.cc
  function main (line 16) | int main(int argc, char** argv) {

FILE: cnn/examples/xor-xent.cc
  function main (line 16) | int main(int argc, char** argv) {

FILE: cnn/examples/xor.cc
  function main (line 16) | int main(int argc, char** argv) {

FILE: cnn/pycnn/pycnn_viz.py
  function new_index (line 7) | def new_index():
  function init (line 12) | def init(random_seed=None): pass
  class SimpleConcreteDim (line 14) | class SimpleConcreteDim(object):
    method __init__ (line 15) | def __init__(self, nrows, ncols, inferred):
    method __getitem__ (line 19) | def __getitem__(self, key): return [self.nrows, self.ncols][key]
    method __iter__ (line 20) | def __iter__(self): return iter([self.nrows, self.ncols])
    method __str__ (line 21) | def __str__(self): return 'Dim(%s,%s)' % (self.nrows, self.ncols)
    method __eq__ (line 22) | def __eq__(self, other): return isinstance(other, SimpleConcreteDim) a...
    method __ne__ (line 23) | def __ne__(self, other): return not self==other
    method __hash__ (line 24) | def __hash__(self): return hash((self.nrows, self.ncols))
    method isvalid (line 25) | def isvalid(self): return True
    method invalid (line 26) | def invalid(self): return False
  class InvalidConcreteDim (line 28) | class InvalidConcreteDim(object):
    method __init__ (line 29) | def __init__(self, a_dim=None, b_dim=None):
    method __getitem__ (line 32) | def __getitem__(self, key): return None
    method __repr__ (line 33) | def __repr__(self):
    method __str__ (line 38) | def __str__(self): return repr(self)
    method isvalid (line 39) | def isvalid(self): return False
    method invalid (line 40) | def invalid(self): return True
  function make_dim (line 44) | def make_dim(a, b=None, inferred=False):
  function ensure_freshness (line 65) | def ensure_freshness(a):
  function copy_dim (line 69) | def copy_dim(a):
  function ensure_same_dim (line 74) | def ensure_same_dim(a,b):
  function ensure_mul_dim (line 81) | def ensure_mul_dim(a,b):
  function ensure_all_same_dim (line 88) | def ensure_all_same_dim(xs):
  function _add (line 99) | def _add(a, b):       return GVExpr('add', [a,b], ensure_same_dim(a,b))
  function _mul (line 100) | def _mul(a, b):       return GVExpr('mul', [a,b], ensure_mul_dim(a,b))
  function _neg (line 101) | def _neg(a):          return GVExpr('neg',       [a],   copy_dim(a))
  function _scalarsub (line 102) | def _scalarsub(a, b): return GVExpr('scalarsub', [a,b], copy_dim(b))
  function _cadd (line 103) | def _cadd(a, b):      return GVExpr('cadd', [a,b], copy_dim(a))
  function _cmul (line 104) | def _cmul(a, b):      return GVExpr('cmul', [a,b], copy_dim(a))
  function _cdiv (line 105) | def _cdiv(a, b):      return GVExpr('cdiv', [a,b], copy_dim(a))
  class Expression (line 107) | class Expression(object): #{{{
    method __init__ (line 108) | def __init__(self, name, args, dim):
    method cg (line 115) | def cg(self): return cg()
    method get_cg_version (line 116) | def get_cg_version(self): return self.cg_version
    method get_vindex (line 117) | def get_vindex(self): return self.vindex
    method __repr__ (line 119) | def __repr__(self): return str(self)
    method __str__ (line 120) | def __str__(self): return '%s([%s], %s, %s/%s)' % (self.name, ', '.joi...
    method __getitem__ (line 121) | def __getitem__(self, i): return None
    method __getslice__ (line 122) | def __getslice__(self, i, j): return None
    method scalar_value (line 123) | def scalar_value(self, recalculate=False): return 0.0
    method vec_value (line 124) | def vec_value(self, recalculate=False): return []
    method npvalue (line 125) | def npvalue(self, recalculate=False): return None
    method value (line 126) | def value(self, recalculate=False): return None
    method forward (line 127) | def forward(self, recalculate=False): return None
    method set (line 128) | def set(self, x): pass
    method backward (line 130) | def backward(self): pass
    method __add__ (line 132) | def __add__(self, other):
    method __mul__ (line 138) | def __mul__(self, other):
    method __div__ (line 144) | def __div__(self, other):
    method __neg__ (line 148) | def __neg__(self):        return _neg(self)
    method __sub__ (line 149) | def __sub__(self, other):
    method init_row (line 157) | def init_row(self, i, row): pass
  function GVExpr (line 160) | def GVExpr(name, args, dim):
  class Model (line 166) | class Model(object):
    method __init__ (line 167) | def __init__(self):
    method add_parameters (line 172) | def add_parameters(self, name, dim, scale=0):
    method add_lookup_parameters (line 179) | def add_lookup_parameters(self, name, dim):
    method __getitem__ (line 187) | def __getitem__(self, name): return self.named_params[name]
    method __contains__ (line 188) | def __contains__(self, name): return name in self.named_params
    method save (line 189) | def save(self, fname): pass
    method load (line 190) | def load(self, fname): pass
  function cg_version (line 196) | def cg_version(): return _cg._cg_version
  function renew_cg (line 197) | def renew_cg(): return _cg.renew()
  function cg (line 199) | def cg():
  class ComputationGraph (line 203) | class ComputationGraph(object):
    method __init__ (line 204) | def __init__(self, guard=0):
    method renew (line 208) | def renew(self):
    method version (line 213) | def version(self): return self._cg_version
    method parameters (line 215) | def parameters(self, params):
    method forward_scalar (line 219) | def forward_scalar(self): return 0.0
    method inc_forward_scalar (line 220) | def inc_forward_scalar(self): return 0.0
    method forward_vec (line 221) | def forward_vec(self): return []
    method inc_forward_vec (line 222) | def inc_forward_vec(self): return []
    method forward (line 223) | def forward(self): return None
    method inc_forward (line 224) | def inc_forward(self): return None
    method backward (line 225) | def backward(self): return None
  function parameter (line 231) | def parameter(p):
  function scalarInput (line 235) | def scalarInput(s): return GVExpr('scalarInput', [s], make_dim(1, inferr...
  function vecInput (line 236) | def vecInput(dim): return GVExpr('vecInput', [dim], make_dim(dim))
  function inputVector (line 237) | def inputVector(v): return GVExpr('inputVector', [v], make_dim(len(v), i...
  function matInput (line 238) | def matInput(d1, d2): return GVExpr('matInput', [d1, d2], make_dim(d1, d2))
  function inputMatrix (line 239) | def inputMatrix(v, d): return GVExpr('inputMatrix', [v, d], make_dim(d, ...
  function lookup (line 240) | def lookup(p, index=0, update=True): return GVExpr('lookup', [p, index, ...
  function lookup_batch (line 241) | def lookup_batch(p, indices, update=True): return GVExpr('lookup_batch',...
  function pick (line 242) | def pick(a, index=0): return GVExpr('pick', [a, index], make_dim(1, infe...
  function pick_batch (line 243) | def pick_batch(a, indices): return GVExpr('pick_batch', [a, indices], ma...
  function hinge (line 244) | def hinge(x, index, m=1.0): return GVExpr('hinge', [x, index, m], copy_d...
  function nobackprop (line 246) | def nobackprop(x): return GVExpr('nobackprop', [x], copy_dim(x))
  function cdiv (line 249) | def cdiv(x, y): return GVExpr('cdiv', [x,y], ensure_same_dim(x,y))
  function colwise_add (line 250) | def colwise_add(x, y):
  function trace_of_product (line 259) | def trace_of_product(x, y): return GVExpr('trace_of_product', [x,y], ens...
  function cwise_multiply (line 260) | def cwise_multiply(x, y): return GVExpr('cwise_multiply', [x,y], ensure_...
  function dot_product (line 261) | def dot_product(x, y): return GVExpr('dot_product', [x,y], ensure_same_d...
  function squared_distance (line 262) | def squared_distance(x, y): return GVExpr('squared_distance', [x,y], ens...
  function l1_distance (line 263) | def l1_distance(x, y): return GVExpr('l1_distance', [x,y], ensure_same_d...
  function binary_log_loss (line 264) | def binary_log_loss(x, y): return GVExpr('binary_log_loss', [x,y], ensur...
  function conv1d_narrow (line 265) | def conv1d_narrow(x, y):
  function conv1d_wide (line 273) | def conv1d_wide(x, y):
  function tanh (line 283) | def tanh(x): return GVExpr('tanh', [x], copy_dim(x))
  function exp (line 284) | def exp(x): return GVExpr('exp', [x], copy_dim(x))
  function square (line 285) | def square(x): return GVExpr('square', [x], copy_dim(x))
  function cube (line 286) | def cube(x): return GVExpr('cube', [x], copy_dim(x))
  function log (line 287) | def log(x): return GVExpr('log', [x], copy_dim(x))
  function logistic (line 288) | def logistic(x): return GVExpr('logistic', [x], copy_dim(x))
  function rectify (line 289) | def rectify(x): return GVExpr('rectify', [x], copy_dim(x))
  function log_softmax (line 290) | def log_softmax(x, restrict=None): return GVExpr('log_softmax', [x,restr...
  function softmax (line 291) | def softmax(x): return GVExpr('softmax', [x], copy_dim(x))
  function softsign (line 292) | def softsign(x): return GVExpr('softsign', [x], copy_dim(x))
  function bmin (line 293) | def bmin(x, y): return GVExpr('bmin', [x,y], ensure_same_dim(x,y))
  function bmax (line 294) | def bmax(x, y): return GVExpr('bmax', [x,y], ensure_same_dim(x,y))
  function transpose (line 295) | def transpose(x): return GVExpr('transpose', [x], x.dim[::-1] if x.dim.i...
  function sum_cols (line 296) | def sum_cols(x): return GVExpr('sum_cols', [x], make_dim(x.dim[0],1) if ...
  function sum_batches (line 298) | def sum_batches(x): return GVExpr('sum_batches', [x], copy_dim(x))
  function fold_rows (line 301) | def fold_rows(x, nrows=2):
  function pairwise_rank_loss (line 309) | def pairwise_rank_loss(x, y, m=1.0): return GVExpr('pairwise_rank_loss',...
  function poisson_loss (line 310) | def poisson_loss(x, y): return GVExpr('poisson_loss', [x,y], copy_dim(x))
  function huber_distance (line 311) | def huber_distance(x, y, c=1.345): return GVExpr('huber_distance', [x,y,...
  function kmax_pooling (line 313) | def kmax_pooling(x, k): return GVExpr('kmax_pooling', [x,k], make_dim(x....
  function pickneglogsoftmax (line 314) | def pickneglogsoftmax(x, v): return GVExpr('pickneglogsoftmax', [x,v], m...
  function pickneglogsoftmax_batch (line 315) | def pickneglogsoftmax_batch(x, vs): return GVExpr('pickneglogsoftmax_bat...
  function kmh_ngram (line 317) | def kmh_ngram(x, n): return GVExpr('kmh_ngram', [x,n], make_dim(x.dim[0]...
  function pickrange (line 318) | def pickrange(x, v, u): return GVExpr('pickrange', [x,v,u], make_dim(u-v...
  function noise (line 320) | def noise(x, stddev): return GVExpr('noise', [x,stddev], copy_dim(x))
  function dropout (line 321) | def dropout(x, p): return GVExpr('dropout', [x,p], copy_dim(x))
  function block_dropout (line 322) | def block_dropout(x, p): return GVExpr('block_dropout', [x,p], copy_dim(x))
  function reshape (line 324) | def reshape(x, d): return GVExpr('reshape', [x,d], make_dim(d))
  function esum (line 325) | def esum(xs): return GVExpr('esum', xs, ensure_all_same_dim(xs))
  function average (line 326) | def average(xs): return GVExpr('average', xs, ensure_all_same_dim(xs))
  function emax (line 327) | def emax(xs): return GVExpr('emax', xs, ensure_all_same_dim(xs))
  function concatenate_cols (line 328) | def concatenate_cols(xs):
  function concatenate (line 339) | def concatenate(xs):
  function affine_transform (line 351) | def affine_transform(xs):
  function new_builder_num (line 370) | def new_builder_num():
  class _RNNBuilder (line 375) | class _RNNBuilder(object):
    method new_graph (line 376) | def new_graph(self):
    method start_new_sequence (line 380) | def start_new_sequence(self, es=None):
    method add_input (line 383) | def add_input(self, e):
    method add_input_to_prev (line 388) | def add_input_to_prev(self, prev, e):
    method rewind_one_step (line 393) | def rewind_one_step(self):
    method back (line 397) | def back(self):
    method final_h (line 401) | def final_h(self):
    method final_s (line 410) | def final_s(self):
    method get_h (line 419) | def get_h(self, i):
    method get_s (line 428) | def get_s(self, i):
    method initial_state (line 437) | def initial_state(self,vecs=None):
    method initial_state_from_raw_vectors (line 447) | def initial_state_from_raw_vectors(self,vecs=None):
  class SimpleRNNBuilder (line 462) | class SimpleRNNBuilder(_RNNBuilder):
    method __init__ (line 463) | def __init__(self, layers, input_dim, hidden_dim, model):
    method whoami (line 471) | def whoami(self): return "SimpleRNNBuilder"
  class LSTMBuilder (line 472) | class LSTMBuilder(_RNNBuilder):
    method __init__ (line 473) | def __init__(self, layers, input_dim, hidden_dim, model):
    method whoami (line 481) | def whoami(self): return "LSTMBuilder"
  class FastLSTMBuilder (line 482) | class FastLSTMBuilder(_RNNBuilder):
    method __init__ (line 483) | def __init__(self, layers, input_dim, hidden_dim, model):
    method whoami (line 491) | def whoami(self): return "FastLSTMBuilder"
  class BiRNNBuilder (line 493) | class BiRNNBuilder(object):
    method __init__ (line 500) | def __init__(self, num_layers, input_dim, hidden_dim, model, rnn_build...
    method whoami (line 519) | def whoami(self): return "BiRNNBuilder"
    method add_inputs (line 521) | def add_inputs(self, es):
    method transduce (line 551) | def transduce(self, es):
  class RNNState (line 579) | class RNNState(object): # {{{
    method __init__ (line 580) | def __init__(self, builder, state_idx=-1, prev_state=None, out=None):
    method add_input (line 586) | def add_input(self, x): # x: Expression
    method add_inputs (line 595) | def add_inputs(self, xs):
    method transduce (line 605) | def transduce(self, xs):
    method output (line 608) | def output(self): return self._out
    method prev (line 610) | def prev(self): return self._prev
    method b (line 611) | def b(self): return self.builder
    method get_state_idx (line 612) | def get_state_idx(self): return self.state_idx
  class StackedRNNState (line 615) | class StackedRNNState(object):
    method __init__ (line 618) | def __init__(self, states, prev=None):
    method add_input (line 622) | def add_input(self, x):
    method output (line 630) | def output(self): return self.states[-1].output()
    method prev (line 632) | def prev(self): return self.prev
    method h (line 633) | def h(self): return [s.h() for s in self.states]
    method s (line 634) | def s(self): return [s.s() for s in self.states]
    method add_inputs (line 636) | def add_inputs(self, xs):
  class Trainer (line 649) | class Trainer(object):
    method update (line 650) | def update(self, s=1.0): pass
    method update_epoch (line 651) | def update_epoch(self, r = 1.0): pass
    method status (line 652) | def status(self): pass
  class SimpleSGDTrainer (line 653) | class SimpleSGDTrainer(Trainer):
    method __init__ (line 654) | def __init__(self, m, lam = 1e-6, e0 = 0.1): pass
  class MomentumSGDTrainer (line 655) | class MomentumSGDTrainer(Trainer):
    method __init__ (line 656) | def __init__(self, m, lam = 1e-6, e0 = 0.01, mom = 0.9): pass
  class AdagradTrainer (line 657) | class AdagradTrainer(Trainer):
    method __init__ (line 658) | def __init__(self, m, lam = 1e-6, e0 = 0.1, eps = 1e-20): pass
  class AdadeltaTrainer (line 659) | class AdadeltaTrainer(Trainer):
    method __init__ (line 660) | def __init__(self, m, lam = 1e-6, eps = 1e-6, rho = 0.95): pass
  class AdamTrainer (line 661) | class AdamTrainer(Trainer):
    method __init__ (line 662) | def __init__(self, m, lam = 1e-6, alpha = 0.001, beta_1 = 0.9, beta_2 ...
  function shape_str (line 680) | def shape_str(e_dim):
  class GVNode (line 695) | class GVNode(object):
    method __init__ (line 696) | def __init__(self, name, input_dim, label, output_dim, children, featu...
    method __iter__ (line 705) | def __iter__(self): return iter([self.name, self.input_dim, self.label...
    method __repr__ (line 706) | def __repr__(self): return 'GVNode(%s)' % ', '.join(map(str, self))
    method __str__ (line 707) | def __str__(self): return repr(self)
  function make_network_graph (line 709) | def make_network_graph(compact, expression_names, lookup_names):
  function parents_of (line 870) | def parents_of(n, nodes):
  function collapse_birnn_states (line 878) | def collapse_birnn_states(nodes, compact):
  function PrintGraphviz (line 929) | def PrintGraphviz(compact=False, show_dims=True, expression_names=None, ...

FILE: cnn/pyexamples/attention.py
  function embedd_sentence (line 33) | def embedd_sentence(model, sentence):
  function run_lstm (line 42) | def run_lstm(model, init_state, input_vecs):
  function encode_sentence (line 53) | def encode_sentence(model, enc_fwd_lstm, enc_bwd_lstm, sentence):
  function attend (line 64) | def attend(model, input_vectors, state):
  function decode (line 79) | def decode(model, dec_lstm, vectors, output):
  function generate (line 100) | def generate(model, input, enc_fwd_lstm, enc_bwd_lstm, dec_lstm):
  function get_loss (line 134) | def get_loss(model, input_sentence, output_sentence, enc_fwd_lstm, enc_b...
  function train (line 141) | def train(model, sentence):

FILE: cnn/pyexamples/bilstmtagger.py
  function read (line 14) | def read(fname):
  function build_tagging_graph (line 66) | def build_tagging_graph(words, tags, model, builders):
  function tag_sent (line 92) | def tag_sent(sent, model, builders):

FILE: cnn/pyexamples/cpu_vs_gpu.py
  function do_cpu (line 11) | def do_cpu():
  function do_gpu (line 19) | def do_gpu():

FILE: cnn/pyexamples/rnnlm.py
  class RNNLanguageModel (line 15) | class RNNLanguageModel:
    method __init__ (line 16) | def __init__(self, model, LAYERS, INPUT_DIM, HIDDEN_DIM, VOCAB_SIZE, b...
    method BuildLMGraph (line 24) | def BuildLMGraph(self, sent):
    method sample (line 44) | def sample(self, first=1, nchars=0, stop=-1):

FILE: cnn/pyexamples/rnnlm_transduce.py
  class RNNLanguageModel (line 16) | class RNNLanguageModel:
    method __init__ (line 17) | def __init__(self, model, LAYERS, INPUT_DIM, HIDDEN_DIM, VOCAB_SIZE, b...
    method BuildLMGraph (line 25) | def BuildLMGraph(self, sent):
    method sample (line 43) | def sample(self, first=1, nchars=0, stop=-1):

FILE: cnn/pyexamples/util.py
  class Vocab (line 3) | class Vocab:
    method __init__ (line 4) | def __init__(self, w2i=None):
    method from_corpus (line 9) | def from_corpus(cls, corpus):
    method size (line 15) | def size(self): return len(self.w2i.keys())
  class CorpusReader (line 17) | class CorpusReader:
    method __init__ (line 18) | def __init__(self, fname):
    method __iter__ (line 20) | def __iter__(self):
  class CharsCorpusReader (line 26) | class CharsCorpusReader:
    method __init__ (line 27) | def __init__(self, fname, begin=None):
    method __iter__ (line 30) | def __iter__(self):

FILE: cnn/rnnlm/lm.cc
  function InitCommandLine (line 42) | void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
  type RNNLanguageModel (line 76) | struct RNNLanguageModel {
    method RNNLanguageModel (line 81) | explicit RNNLanguageModel(Model& model) : builder(LAYERS, INPUT_DIM, H...
    method Expression (line 88) | Expression BuildLMGraph(const vector<int>& sent, ComputationGraph& cg,...
    method RandomSample (line 122) | void RandomSample(int max_len = 200) {
  function main (line 157) | int main(int argc, char** argv) {

FILE: cnn/tests/test-cnn.cc
  type ConfigureCNNTest (line 5) | struct ConfigureCNNTest {
    method ConfigureCNNTest (line 6) | ConfigureCNNTest() {
  function BOOST_AUTO_TEST_CASE (line 24) | BOOST_AUTO_TEST_CASE( aligned_allocator ) {

FILE: cnn/tests/test-nodes.cc
  type NodeTest (line 12) | struct NodeTest {
    method NodeTest (line 13) | NodeTest() {
    method print_vec (line 47) | std::string print_vec(const std::vector<T> vec) {
  function BOOST_AUTO_TEST_CASE (line 66) | BOOST_AUTO_TEST_CASE( negate_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 75) | BOOST_AUTO_TEST_CASE( add_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 85) | BOOST_AUTO_TEST_CASE( addscalar_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 94) | BOOST_AUTO_TEST_CASE( scalaradd_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 103) | BOOST_AUTO_TEST_CASE( subtract_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 113) | BOOST_AUTO_TEST_CASE( scalarsubtract_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 122) | BOOST_AUTO_TEST_CASE( subtractscalar_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 131) | BOOST_AUTO_TEST_CASE( multiply_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 142) | BOOST_AUTO_TEST_CASE( multiply_batch_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 153) | BOOST_AUTO_TEST_CASE( affine_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 165) | BOOST_AUTO_TEST_CASE( affine_batch_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 177) | BOOST_AUTO_TEST_CASE( affine_batch2_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 189) | BOOST_AUTO_TEST_CASE( multiplyscalar_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 198) | BOOST_AUTO_TEST_CASE( scalarmultiply_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 207) | BOOST_AUTO_TEST_CASE( dividescalar_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 216) | BOOST_AUTO_TEST_CASE( cdiv_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 226) | BOOST_AUTO_TEST_CASE( colwise_add_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 243) | BOOST_AUTO_TEST_CASE( sqrt_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 252) | BOOST_AUTO_TEST_CASE( erf_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 261) | BOOST_AUTO_TEST_CASE( tanh_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 270) | BOOST_AUTO_TEST_CASE( exp_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 279) | BOOST_AUTO_TEST_CASE( square_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 288) | BOOST_AUTO_TEST_CASE( cube_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 297) | BOOST_AUTO_TEST_CASE( lgamma_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 306) | BOOST_AUTO_TEST_CASE( log_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 315) | BOOST_AUTO_TEST_CASE( logistic_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 324) | BOOST_AUTO_TEST_CASE( rectify_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 333) | BOOST_AUTO_TEST_CASE( hinge_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 342) | BOOST_AUTO_TEST_CASE( hingeptr_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 351) | BOOST_AUTO_TEST_CASE( log_softmax_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 360) | BOOST_AUTO_TEST_CASE( restricted_log_softmax_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 370) | BOOST_AUTO_TEST_CASE( softmax_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 379) | BOOST_AUTO_TEST_CASE( softsign_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 388) | BOOST_AUTO_TEST_CASE( pow_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 398) | BOOST_AUTO_TEST_CASE( min_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 408) | BOOST_AUTO_TEST_CASE( max_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 441) | BOOST_AUTO_TEST_CASE( reshape_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 450) | BOOST_AUTO_TEST_CASE( transpose_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 459) | BOOST_AUTO_TEST_CASE( trace_of_product_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 468) | BOOST_AUTO_TEST_CASE( cwise_multiply_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 478) | BOOST_AUTO_TEST_CASE( dot_product_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 487) | BOOST_AUTO_TEST_CASE( squared_distance_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 496) | BOOST_AUTO_TEST_CASE( huber_distance_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 505) | BOOST_AUTO_TEST_CASE( l1_distance_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 514) | BOOST_AUTO_TEST_CASE( binary_log_loss_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 523) | BOOST_AUTO_TEST_CASE( pairwise_rank_loss_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 545) | BOOST_AUTO_TEST_CASE( pick_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 554) | BOOST_AUTO_TEST_CASE( pickptr_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 563) | BOOST_AUTO_TEST_CASE( pick_batch_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 573) | BOOST_AUTO_TEST_CASE( pickrange_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 582) | BOOST_AUTO_TEST_CASE( pickneglogsoftmax_gradient ) {
  function BOOST_AUTO_TEST_CASE (line 591) | BOOST_AUTO_TEST_CASE( pickneglogsoftmax_batch_gradient ) {

FILE: get_dictionary.py
  function is_next_open_bracket (line 1) | def is_next_open_bracket(line, start_idx):
  function get_between_brackets (line 9) | def get_between_brackets(line, start_idx):
  function get_dict (line 18) | def get_dict(lines):

FILE: get_oracle.py
  function unkify (line 5) | def unkify(tokens, words_dict):
  function is_next_open_bracket (line 72) | def is_next_open_bracket(line, start_idx):
  function get_between_brackets (line 80) | def get_between_brackets(line, start_idx):
  function get_tags_tokens_lowercase (line 98) | def get_tags_tokens_lowercase(line):
  function get_nonterminal (line 120) | def get_nonterminal(line, start_idx):
  function get_actions (line 131) | def get_actions(line):
  function main (line 162) | def main():

FILE: get_oracle_gen.py
  function unkify (line 5) | def unkify(tokens, words_dict):
  function is_next_open_bracket (line 72) | def is_next_open_bracket(line, start_idx):
  function get_between_brackets (line 80) | def get_between_brackets(line, start_idx):
  function get_tags_tokens_lowercase (line 98) | def get_tags_tokens_lowercase(line):
  function get_nonterminal (line 120) | def get_nonterminal(line, start_idx):
  function get_actions (line 131) | def get_actions(line):
  function main (line 162) | def main():

FILE: interpreting-rnng/nt-parser-gen-attention-gated-stack-only.cc
  function InitCommandLine (line 63) | void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
  type ParserBuilder (line 96) | struct ParserBuilder {
    method ParserBuilder (line 132) | explicit ParserBuilder(Model* model, const unordered_map<unsigned, vec...
    method IsActionForbidden_Generative (line 174) | static bool IsActionForbidden_Generative(const string& a, char prev_a,...
    method log_prob_parser (line 194) | vector<unsigned> log_prob_parser(ComputationGraph* hg,
  function signal_callback_handler (line 536) | void signal_callback_handler(int /* signum */) {
  function main (line 545) | int main(int argc, char** argv) {

FILE: nt-parser/compressed-fstream.h
  function namespace (line 12) | namespace cnn {

FILE: nt-parser/eval.cc
  type parser (line 12) | namespace parser {
    function EvalBResults (line 14) | EvalBResults Evaluate(const string& ref_fname, const string& hyp_fname) {

FILE: nt-parser/eval.h
  function namespace (line 7) | namespace parser {

FILE: nt-parser/nt-parser-gen.cc
  function InitCommandLine (line 63) | void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
  type ParserBuilder (line 96) | struct ParserBuilder {
    method ParserBuilder (line 125) | explicit ParserBuilder(Model* model, const unordered_map<unsigned, vec...
    method IsActionForbidden_Generative (line 160) | static bool IsActionForbidden_Generative(const string& a, char prev_a,...
    method log_prob_parser (line 180) | vector<unsigned> log_prob_parser(ComputationGraph* hg,
  function signal_callback_handler (line 440) | void signal_callback_handler(int /* signum */) {
  function main (line 449) | int main(int argc, char** argv) {

FILE: nt-parser/nt-parser.cc
  function InitCommandLine (line 66) | void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
  type ParserBuilder (line 104) | struct ParserBuilder {
    method ParserBuilder (line 135) | explicit ParserBuilder(Model* model, const unordered_map<unsigned, vec...
    method IsActionForbidden_Discriminative (line 181) | static bool IsActionForbidden_Discriminative(const string& a, char pre...
    method log_prob_parser (line 222) | vector<unsigned> log_prob_parser(ComputationGraph* hg,
    type ParserState (line 510) | struct ParserState {
    type ParserStateCompare (line 531) | struct ParserStateCompare {
    method prune (line 537) | static void prune(vector<ParserState>& pq, unsigned k) {
    method all_complete (line 549) | static bool all_complete(const vector<ParserState>& pq) {
    method log_prob_parser_beam (line 561) | vector<unsigned> log_prob_parser_beam(ComputationGraph* hg,
  function signal_callback_handler (line 853) | void signal_callback_handler(int /* signum */) {
  function main (line 862) | int main(int argc, char** argv) {

FILE: nt-parser/oracle.cc
  type parser (line 11) | namespace parser {
    function is_ws (line 16) | inline bool is_ws(char x) { //check whether the character is a space o...
    function is_not_ws (line 20) | inline bool is_not_ws(char x) {

FILE: nt-parser/oracle.h
  function namespace (line 8) | namespace cnn { class Dict; }
  function namespace (line 10) | namespace parser {
  type Oracle (line 21) | struct Oracle {
  function class (line 40) | class TopDownOracle : public Oracle {
  function class (line 57) | class TopDownOracleGen : public Oracle {
  function class (line 65) | class TopDownOracleGen2 : public Oracle {

FILE: nt-parser/pretrained.cc
  type parser (line 10) | namespace parser {
    function ReadEmbeddings_word2vec (line 12) | void ReadEmbeddings_word2vec(const string& fname,

FILE: nt-parser/pretrained.h
  function namespace (line 8) | namespace cnn { struct Dict; }
  function namespace (line 10) | namespace parser {

FILE: remove_dev_unk.py
  function is_next_open_bracket (line 3) | def is_next_open_bracket(line, start_idx):
  function get_between_brackets (line 11) | def get_between_brackets(line, start_idx):
  function get_tags_tokens_lowercase (line 20) | def get_tags_tokens_lowercase(line):
  function main (line 42) | def main():

FILE: utils/remove_dev_unk.py
  function is_next_open_bracket (line 3) | def is_next_open_bracket(line, start_idx):
  function get_between_brackets (line 11) | def get_between_brackets(line, start_idx):
  function get_tags_tokens_lowercase (line 20) | def get_tags_tokens_lowercase(line):
  function main (line 42) | def main():