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Functions1,219 in github.com/KareemYousrii/SPL

⨍ Functions 1,219◇ Types & classes 137↳ Endpoints 4
↓ 1 callersMethodentropy_kld
(self)
C-HMCNN/hmc-utils/compute_mpe.py:105
↓ 1 callersMethodenumerate_mpe
Enumerate the top-k MPE's of a PSDD AC: TODO evidence.
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:263
↓ 1 callersMethodenumerate_mpe
Enumerate the top-k MPE's of a PSDD AC: TODO evidence.
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:263
↓ 1 callersMethodenumerate_mpe
Enumerate the top-k MPE's of a PSDD AC: TODO evidence.
grids/pypsdd/sdd/psdd.py:263
↓ 1 callersMethodenumerate_mpe
Enumerate the top-k MPE's of a PSDD AC: TODO evidence.
grids/pypsdd/pypsdd/psdd.py:263
↓ 1 callersFunctionevaluate_circuit
(model, gate, cmpe, epoch, data_loader, data_split, prefix)
C-HMCNN/test.py:313
↓ 1 callersMethodff_cross_entropy
(self, target, litleaves, log_space=True)
grids/compute_mpe.py:114
↓ 1 callersMethodff_ll
Generates a torch arithmetic circuit according to the weighted model counting procedure for this SDD. We populate both the weighted m
grids/pypsdd/pypsdd/sdd.py:716
↓ 1 callersFunctionflatten_nested_string_dict
(nested_dict, prepend='')
WarcraftShortestPath/utils.py:259
↓ 1 callersMethodforward_pass
(self, input, label, train, i)
WarcraftShortestPath/warcraft_shortest_path/trainers.py:302
↓ 1 callersFunctionfrom_perm_matrix
Takes a flattened perm matrix, returns a ranking (numbers 1-n)
grids/sushi_data.py:108
↓ 1 callersFunctiongen_grid
Generate nxn grid
grids/generate_graph_data.py:128
↓ 1 callersFunctiongen_grid_removed
Generate a nxn grid, with the listed edge indices removed. The edges are ordered from left to right, then top to bottom, then the same thing sidew
grids/generate_graph_data.py:115
↓ 1 callersMethodgenerate_normalized_ac
Generates a torch arithmetic circuit according to the weighted model counting procedure for this SDD. We populate both the weighted m
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:925
↓ 1 callersMethodgenerate_normalized_ac
Generates a torch arithmetic circuit according to the weighted model counting procedure for this SDD. We populate both the weighted m
grids/pypsdd/pypsdd/sdd.py:1049
↓ 1 callersMethodgenerate_normalized_torch_ac
Generates a torch arithmetic circuit according to the weighted model counting procedure for this SDD. We populate both the weighted m
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:1074
↓ 1 callersMethodgenerate_normalized_torch_ac
Generates a torch arithmetic circuit according to the weighted model counting procedure for this SDD. We populate both the weighted m
grids/pypsdd/pypsdd/sdd.py:1227
↓ 1 callersMethodgenerate_normalized_torch_ac_stable
Generates a torch arithmetic circuit according to the weighted model counting procedure for this SDD. We populate both the weighted m
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:980
↓ 1 callersMethodgenerate_normalized_torch_ac_stable
Generates a torch arithmetic circuit according to the weighted model counting procedure for this SDD. We populate both the weighted m
grids/pypsdd/pypsdd/sdd.py:1104
↓ 1 callersMethodgenerate_tf_ac
Generates a tensorflow arithmetic circuit according to the weighted model counting procedure for this SDD. Assumes the SDD is normalized.
C-HMCNN/hmc-utils/pypsdd/sdd/sdd.py:456
↓ 1 callersFunctionget_im
()
WarcraftShortestPath/utils.py:91
↓ 1 callersMethodget_mpe
Compute the MPE instation given weights associated with literals. Assumes the SDD is normalized.
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:647
↓ 1 callersMethodget_mpe
Compute the MPE instation given weights associated with literals. Assumes the SDD is normalized.
grids/pypsdd/pypsdd/sdd.py:648
↓ 1 callersFunctionget_neighbors
(i,j,dim, dim2=None)
WarcraftShortestPath/warcraft_shortest_path/metrics.py:47
↓ 1 callersFunctionget_neighbourhood_func
(neighbourhood_fn)
WarcraftShortestPath/data/utils.py:26
↓ 1 callersMethodget_norm_ac
(self, litleaves)
C-HMCNN/hmc-utils/compute_mpe.py:89
↓ 1 callersFunctionget_solver
(neighbourhood_fn)
WarcraftShortestPath/comb_modules/dijkstra.py:66
↓ 1 callersMethodget_weighted_mpe
Compute the MPE instation given weights associated with literals. Assumes the SDD is normalized.
C-HMCNN/hmc-utils/pypsdd/sdd/sdd.py:411
↓ 1 callersMethodget_weighted_mpe
Compute the MPE instation given weights associated with literals. Assumes the SDD is normalized.
grids/pypsdd/sdd/sdd.py:411
↓ 1 callersFunctionglobal_model_count
(alpha,manager)
WarcraftShortestPath/data/zdd2sdd.py:7
↓ 1 callersFunctionhyperparam_dict_product
(hyperparam_dict)
WarcraftShortestPath/utils.py:332
↓ 1 callersFunctionhyperparam_dict_samples
(hyperparam_dict, num_samples)
WarcraftShortestPath/utils.py:323
↓ 1 callersMethodinfer_datatype
(self, data)
WarcraftShortestPath/logger.py:36
↓ 1 callersMethodinit_weights
(self, m)
C-HMCNN/hmc-utils/GatingFunction.py:59
↓ 1 callersMethodinit_weights
(self, m)
grids/GatingFunction.py:59
↓ 1 callersMethodinitialize
(self)
C-HMCNN/hmc-utils/GatingFunction.py:64
↓ 1 callersMethodinitialize
(self)
grids/GatingFunction.py:64
↓ 1 callersMethodinitialize_node
Initialize the parameters of a PSDD node.
C-HMCNN/hmc-utils/pypsdd/sdd/prior.py:69
↓ 1 callersMethodinitialize_node
Initialize the parameters of a PSDD node.
C-HMCNN/hmc-utils/pypsdd/pypsdd/prior.py:69
↓ 1 callersMethodinitialize_node
Initialize the parameters of a PSDD node.
grids/pypsdd/sdd/prior.py:69
↓ 1 callersMethodinitialize_node
Initialize the parameters of a PSDD node.
grids/pypsdd/pypsdd/prior.py:69
↓ 1 callersMethodinitialize_psdd
(self,root)
C-HMCNN/hmc-utils/pypsdd/pypsdd/prior.py:12
↓ 1 callersMethodinitialize_psdd
(self,root)
grids/pypsdd/sdd/prior.py:12
↓ 1 callersMethodinitialize_psdd
(self,root)
grids/pypsdd/pypsdd/prior.py:12
↓ 1 callersMethodinternal_node
Creates new internal Vtree node with children left and right
C-HMCNN/hmc-utils/pypsdd/sdd/vtree.py:22
↓ 1 callersMethodinternal_node
Creates new internal Vtree node with children left and right
C-HMCNN/hmc-utils/pypsdd/pypsdd/vtree.py:22
↓ 1 callersMethodinternal_node
Creates new internal Vtree node with children left and right
grids/pypsdd/sdd/vtree.py:22
↓ 1 callersMethodinternal_node
Creates new internal Vtree node with children left and right
grids/pypsdd/pypsdd/vtree.py:22
↓ 1 callersFunctionis_json_file
(cmd_line)
WarcraftShortestPath/utils.py:463
↓ 1 callersMethodis_model
Returns True if inst (of type Inst or InstMap) is a model of the SDD, and False otherwise.
C-HMCNN/hmc-utils/pypsdd/sdd/sdd.py:253
↓ 1 callersMethodis_model
Returns True if inst (of type Inst or InstMap) is a model of the SDD, and False otherwise.
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:398
↓ 1 callersMethodis_model
Returns True if inst (of type Inst or InstMap) is a model of the SDD, and False otherwise.
grids/pypsdd/sdd/sdd.py:253
↓ 1 callersMethodis_model
Returns True if inst (of type Inst or InstMap) is a model of the SDD, and False otherwise.
grids/pypsdd/pypsdd/sdd.py:398
↓ 1 callersFunctionis_parseable_dict
(cmd_line)
WarcraftShortestPath/utils.py:471
↓ 1 callersFunctionis_valid_label_fn_new
(suggested_path)
WarcraftShortestPath/warcraft_shortest_path/metrics.py:59
↓ 1 callersMethodleaf_node
Creates new leaf Vtree node with variable var
C-HMCNN/hmc-utils/pypsdd/sdd/vtree.py:17
↓ 1 callersMethodleaf_node
Creates new leaf Vtree node with variable var
C-HMCNN/hmc-utils/pypsdd/pypsdd/vtree.py:17
↓ 1 callersMethodleaf_node
Creates new leaf Vtree node with variable var
grids/pypsdd/sdd/vtree.py:17
↓ 1 callersMethodleaf_node
Creates new leaf Vtree node with variable var
grids/pypsdd/pypsdd/vtree.py:17
↓ 1 callersMethodlit_to_value
(lit)
C-HMCNN/hmc-utils/pypsdd/sdd/data.py:409
↓ 1 callersMethodlit_to_value
(lit)
C-HMCNN/hmc-utils/pypsdd/pypsdd/data.py:409
↓ 1 callersMethodlit_to_value
(lit)
grids/pypsdd/sdd/data.py:409
↓ 1 callersMethodlit_to_value
(lit)
grids/pypsdd/pypsdd/data.py:409
↓ 1 callersMethodll
Calculate the probabilty of particular model of the underlying circuit. Assumes that the circuit is normalized.
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:710
↓ 1 callersMethodll
Calculate the probabilty of particular model of the underlying circuit. Assumes that the circuit is normalized.
grids/pypsdd/pypsdd/sdd.py:934
↓ 1 callersMethodlog_likelihood
Computes the log likelihood log Pr(data | theta)
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:380
↓ 1 callersMethodlog_likelihood
Computes the log likelihood log Pr(data | theta)
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:380
↓ 1 callersMethodlog_likelihood
Computes the log likelihood log Pr(data | theta)
grids/pypsdd/sdd/psdd.py:380
↓ 1 callersMethodlog_likelihood
Computes the log likelihood log Pr(data | theta)
grids/pypsdd/pypsdd/psdd.py:380
↓ 1 callersMethodlog_prior
(self,root)
C-HMCNN/hmc-utils/pypsdd/sdd/prior.py:15
↓ 1 callersMethodlog_prior
Computes log Pr(theta)
C-HMCNN/hmc-utils/pypsdd/sdd/prior.py:147
↓ 1 callersMethodlog_prior
(self,root)
C-HMCNN/hmc-utils/pypsdd/pypsdd/prior.py:15
↓ 1 callersMethodlog_prior
Computes log Pr(theta)
C-HMCNN/hmc-utils/pypsdd/pypsdd/prior.py:147
↓ 1 callersMethodlog_prior
(self,root)
grids/pypsdd/sdd/prior.py:15
↓ 1 callersMethodlog_prior
Computes log Pr(theta)
grids/pypsdd/sdd/prior.py:147
↓ 1 callersMethodlog_prior
(self,root)
grids/pypsdd/pypsdd/prior.py:15
↓ 1 callersMethodlog_prior
Computes log Pr(theta)
grids/pypsdd/pypsdd/prior.py:147
↓ 1 callersMethodlog_prior_brute_force
Brute-force (enumerative) computation of the 'uniform smoothing' parameter prior
C-HMCNN/hmc-utils/pypsdd/sdd/prior.py:172
↓ 1 callersMethodlog_prior_brute_force
Brute-force (enumerative) computation of the 'uniform smoothing' parameter prior
C-HMCNN/hmc-utils/pypsdd/pypsdd/prior.py:172
↓ 1 callersMethodlog_prior_brute_force
Brute-force (enumerative) computation of the 'uniform smoothing' parameter prior
grids/pypsdd/sdd/prior.py:172
↓ 1 callersMethodlog_prior_brute_force
Brute-force (enumerative) computation of the 'uniform smoothing' parameter prior
grids/pypsdd/pypsdd/prior.py:172
↓ 1 callersFunctionlogaddexp
(x: Tensor, y: Tensor)
grids/pypsdd/pypsdd/sdd.py:74
↓ 1 callersFunctionlogsumexp
(tensor: Tensor, dim: int, keepdim: bool = False)
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:12
↓ 1 callersFunctionlogsumexp
(tensor: Tensor, dim: int, keepdim: bool = False)
grids/pypsdd/pypsdd/sdd.py:12
↓ 1 callersFunctionmain
()
C-HMCNN/train.py:82
↓ 1 callersFunctionmain
()
C-HMCNN/test.py:81
↓ 1 callersFunctionmain
()
WarcraftShortestPath/main.py:55
↓ 1 callersFunctionmain
()
grids/grid_net.py:66
↓ 1 callersFunctionmain
(args=sys.argv[1:])
grids/generate_graph_data.py:171
↓ 1 callersFunctionmain
()
grids/sushi_net.py:50
↓ 1 callersMethodmars
Evaluate a PSDD top-down for its marginals.
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:836
↓ 1 callersMethodmpe
Compute the most probable explanation (MPE) given evidence. Returns (un-normalized) MPE value and instantiation. If evidence is incon
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:214
↓ 1 callersMethodmpe
Compute the most probable explanation (MPE) given evidence. Returns (un-normalized) MPE value and instantiation. If evidence is incon
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:214
↓ 1 callersMethodmpe
Compute the most probable explanation (MPE) given evidence. Returns (un-normalized) MPE value and instantiation. If evidence is incon
grids/pypsdd/sdd/psdd.py:214
↓ 1 callersMethodmpe
Compute the most probable explanation (MPE) given evidence. Returns (un-normalized) MPE value and instantiation. If evidence is incon
grids/pypsdd/pypsdd/psdd.py:214
↓ 1 callersMethodmult_weight
(self,weight)
C-HMCNN/hmc-utils/pypsdd/sdd/data.py:440
↓ 1 callersMethodmult_weight
(self,weight)
C-HMCNN/hmc-utils/pypsdd/pypsdd/data.py:440
↓ 1 callersMethodmult_weight
(self,weight)
grids/pypsdd/sdd/data.py:440
↓ 1 callersMethodmult_weight
(self,weight)
grids/pypsdd/pypsdd/data.py:440
↓ 1 callersMethodnegate
Negate a normalized SDD node
C-HMCNN/hmc-utils/pypsdd/sdd/manager.py:110
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