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unit: def __init__()
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unit: def evaluate()
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unit: def __init__()
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unit: def train()
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id: 5
unit: def __init__()
file: research/gam/gam/trainer/trainer_agreement.py
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id: 6
unit: def __init__()
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id: 7
unit: def train()
file: research/gam/gam/trainer/trainer_agreement.py
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id: 8
unit: def main()
file: research/gam/gam/experiments/run_train_gam_graph.py
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unit: def main()
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id: 10
unit: def train()
file: research/gam/gam/trainer/trainer_classification.py
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id: 11
unit: def embed_single_feature()
file: research/carls/models/caml/sparse_features.py
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id: 12
unit: def main()
file: research/kg_hyp_emb/train.py
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id: 13
unit: def train()
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id: 14
unit: def featurize_each_example()
file: research/a2n/dataset.py
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id: 15
unit: std::string DebugString()
file: research/carls/base/input_context_helper.cc
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id: 16
unit: def _get_agreement_reg_loss()
file: research/gam/gam/trainer/trainer_classification.py
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id: 17
unit: def train()
file: research/a2n/train.py
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id: 18
unit: def _get_agreement_reg_loss()
file: research/gam/gam/trainer/trainer_classification_gcn.py
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size: 80 LOC
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id: 19
unit: def train()
file: research/multi_representation_adversary/multi_representation_adversary/trainer.py
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id: 20
unit: def _get_encoding()
file: research/gam/gam/models/wide_resnet.py
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size: 79 LOC
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number of parameters: 5

id: 21
unit: Status KnowledgeBankGrpcServiceImpl::Update()
file: research/carls/knowledge_bank_grpc_service.cc
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size: 77 LOC
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number of parameters: 3

id: 22
unit: def attention_kbc_model()
file: research/a2n/models.py
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size: 76 LOC
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number of parameters: 4

id: 23
unit: absl::Status DynamicEmbeddingManager::NegativeSampling()
file: research/carls/dynamic_embedding_manager.cc
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size: 72 LOC
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number of parameters: 9

id: 24
unit: def read_graph()
file: research/a2n/graph.py
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size: 70 LOC
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number of parameters: 2

id: 25
unit: def _construct_layers()
file: research/gam/gam/models/cnn.py
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size: 69 LOC
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number of parameters: 2

id: 26
unit: def add_graph_regularization()
file: neural_structured_learning/estimator/graph_regularization.py
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size: 65 LOC
McCabe index: 18
number of parameters: 4

id: 27
unit: absl::Status DynamicEmbeddingManager::Lookup()
file: research/carls/dynamic_embedding_manager.cc
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size: 64 LOC
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number of parameters: 3

id: 28
unit: def evaluate()
file: research/multi_representation_adversary/multi_representation_adversary/evaluator.py
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size: 64 LOC
McCabe index: 17
number of parameters: 11

id: 29
unit: absl::Status BruteForceTopkSampler::SampleInternal()
file: research/carls/candidate_sampling/brute_force_topk_sampler.cc
start line: 91
end line: 155
size: 62 LOC
McCabe index: 11
number of parameters: 4

id: 30
unit: absl::Status NegativeSampler::SampleUnique()
file: research/carls/candidate_sampling/negative_sampler.cc
start line: 155
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size: 62 LOC
McCabe index: 9
number of parameters: 5

id: 31
unit: def load_from_planetoid_files()
file: research/gam/gam/data/loaders.py
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size: 58 LOC
McCabe index: 4
number of parameters: 2

id: 32
unit: Status KnowledgeBankGrpcServiceImpl::StartSessionIfNecessary()
file: research/carls/knowledge_bank_grpc_service.cc
start line: 353
end line: 409
size: 56 LOC
McCabe index: 17
number of parameters: 3

id: 33
unit: absl::Status Prune()
file: research/carls/base/input_context_helper.cc
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size: 54 LOC
McCabe index: 21
number of parameters: 3

id: 34
unit: def _construct_feed_dict()
file: research/gam/gam/trainer/trainer_classification.py
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size: 53 LOC
McCabe index: 9
number of parameters: 7

id: 35
unit: def _construct_feed_dict()
file: research/gam/gam/trainer/trainer_classification_gcn.py
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size: 52 LOC
McCabe index: 8
number of parameters: 7

id: 36
unit: def get_model_cls()
file: research/gam/gam/experiments/helper.py
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size: 52 LOC
McCabe index: 9
number of parameters: 6

id: 37
unit: def add_adversarial_regularization()
file: neural_structured_learning/estimator/adversarial_regularization.py
start line: 0
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size: 51 LOC
McCabe index: 15
number of parameters: 3

id: 38
unit: def gen_neighbor()
file: neural_structured_learning/lib/adversarial_neighbor.py
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size: 51 LOC
McCabe index: 10
number of parameters: 3

id: 39
unit: bool IsPortAvailable()
file: research/carls/kbs_server_helper.cc
start line: 34
end line: 92
size: 51 LOC
McCabe index: 12
number of parameters: 2

id: 40
unit: def copy()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 51 LOC
McCabe index: 14
number of parameters: 14

id: 41
unit: def add_noisy_edges()
file: research/gam/gam/data/robustness.py
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size: 51 LOC
McCabe index: 14
number of parameters: 3

id: 42
unit: def _get_train_edge_iterator()
file: research/gam/gam/trainer/trainer_agreement.py
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size: 50 LOC
McCabe index: 13
number of parameters: 6

id: 43
unit: def compute_dataset_statistics()
file: research/gam/gam/data/dataset.py
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size: 49 LOC
McCabe index: 9
number of parameters: 4

id: 44
unit: def get_model_agr()
file: research/gam/gam/experiments/helper.py
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size: 49 LOC
McCabe index: 8
number of parameters: 6

id: 45
unit: def build_resnet_v1()
file: research/multi_representation_adversary/multi_representation_adversary/resnet.py
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size: 49 LOC
McCabe index: 9
number of parameters: 6

id: 46
unit: def create_model()
file: research/a2n/train.py
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size: 48 LOC
McCabe index: 14
number of parameters: 2

id: 47
unit: def _select_samples_to_label()
file: research/gam/gam/trainer/trainer_cotrain.py
start line: 0
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size: 48 LOC
McCabe index: 14
number of parameters: 4

id: 48
unit: grpc::Status KnowledgeBankGrpcServiceImpl::Sample()
file: research/carls/knowledge_bank_grpc_service.cc
start line: 186
end line: 234
size: 47 LOC
McCabe index: 12
number of parameters: 3

id: 49
unit: grpc::Status KnowledgeBankGrpcServiceImpl::MemoryLookup()
file: research/carls/knowledge_bank_grpc_service.cc
start line: 236
end line: 282
size: 47 LOC
McCabe index: 11
number of parameters: 3

id: 50
unit: void Compute()
file: research/carls/kernels/dynamic_embedding_ops.cc
start line: 192
end line: 245
size: 47 LOC
McCabe index: 7
number of parameters: 1

id: 51
unit: absl::Status Merge()
file: research/carls/base/input_context_helper.cc
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size: 46 LOC
McCabe index: 14
number of parameters: 4

id: 52
unit: absl::Status DynamicEmbeddingManager::LookupGaussianCluster()
file: research/carls/dynamic_embedding_manager.cc
start line: 296
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size: 46 LOC
McCabe index: 5
number of parameters: 6

id: 53
unit: def build_from_adjacency_matrix()
file: research/gam/gam/data/dataset.py
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size: 46 LOC
McCabe index: 6
number of parameters: 8

id: 54
unit: def pack_nodes_and_edges()
file: neural_structured_learning/experimental/gnn.py
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size: 45 LOC
McCabe index: 9
number of parameters: 5

id: 55
unit: def predict_label_by_agreement()
file: research/gam/gam/trainer/trainer_agreement.py
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size: 45 LOC
McCabe index: 9
number of parameters: 4

id: 56
unit: std::unique_ptr DynamicEmbeddingManager::Create()
file: research/carls/dynamic_embedding_manager.cc
start line: 55
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size: 44 LOC
McCabe index: 8
number of parameters: 4

id: 57
unit: def make_cora_dataset()
file: neural_structured_learning/experimental/gnn.py
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size: 42 LOC
McCabe index: 3
number of parameters: 6

id: 58
unit: def pairwise_distance_wrapper()
file: neural_structured_learning/lib/distances.py
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size: 42 LOC
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number of parameters: 4

id: 59
unit: def _join_examples()
file: neural_structured_learning/tools/pack_nbrs.py
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size: 42 LOC
McCabe index: 13
number of parameters: 4

id: 60
unit: absl::Status LeveldbKnowledgeBank::LoadDataFromLevelDb()
file: research/carls/knowledge_bank/leveldb_knowledge_bank.cc
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size: 42 LOC
McCabe index: 7
number of parameters: 2

id: 61
unit: def lookup()
file: research/carls/models/caml/sparse_features.py
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size: 42 LOC
McCabe index: 12
number of parameters: 2

id: 62
unit: void Compute()
file: research/carls/kernels/sampled_logits_ops.cc
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end line: 155
size: 41 LOC
McCabe index: 2
number of parameters: 1

id: 63
unit: absl::Status DynamicEmbeddingManager::TopK()
file: research/carls/dynamic_embedding_manager.cc
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size: 41 LOC
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number of parameters: 4

id: 64
unit: def get_output_shapes()
file: research/a2n/dataset.py
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size: 40 LOC
McCabe index: 8
number of parameters: 1

id: 65
unit: def batch_iterator()
file: research/gam/gam/trainer/trainer_base.py
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size: 40 LOC
McCabe index: 15
number of parameters: 6

id: 66
unit: std::vector GradientDescentOptimizer::Apply()
file: research/carls/gradient_descent/gradient_descent_optimizer.cc
start line: 73
end line: 113
size: 39 LOC
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number of parameters: 3

id: 67
unit: Status KnowledgeBankGrpcServiceImpl::Lookup()
file: research/carls/knowledge_bank_grpc_service.cc
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size: 39 LOC
McCabe index: 8
number of parameters: 3

id: 68
unit: def call()
file: research/carls/dynamic_normalization.py
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size: 39 LOC
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number of parameters: 3

id: 69
unit: def split_train_val_unlabeled()
file: research/gam/gam/data/preprocessing.py
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size: 39 LOC
McCabe index: 5
number of parameters: 5

id: 70
unit: def build_from_splits()
file: research/gam/gam/data/dataset.py
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size: 38 LOC
McCabe index: 2
number of parameters: 11

id: 71
unit: def copy()
file: research/gam/gam/data/dataset.py
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size: 38 LOC
McCabe index: 11
number of parameters: 11

id: 72
unit: def edge_iterator()
file: research/gam/gam/trainer/trainer_classification.py
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size: 38 LOC
McCabe index: 9
number of parameters: 4

id: 73
unit: def edge_iterator()
file: research/gam/gam/trainer/trainer_classification_gcn.py
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size: 38 LOC
McCabe index: 9
number of parameters: 4

id: 74
unit: EmbeddingVectorProto InitializeEmbeddingWithSeed()
file: research/carls/knowledge_bank/initializer_helper.cc
start line: 92
end line: 129
size: 37 LOC
McCabe index: 8
number of parameters: 4

id: 75
unit: def random_in_norm_ball()
file: neural_structured_learning/lib/utils.py
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size: 36 LOC
McCabe index: 17
number of parameters: 3

id: 76
unit: def attack()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
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size: 36 LOC
McCabe index: 4
number of parameters: 6

id: 77
unit: def __init__()
file: research/kg_hyp_emb/models/base.py
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size: 36 LOC
McCabe index: 1
number of parameters: 3

id: 78
unit: def load_dataset()
file: research/gnn-survey/utils.py
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size: 36 LOC
McCabe index: 7
number of parameters: 3

id: 79
unit: def generate_by_partitions()
file: research/neural_clustering/data_generators/mog.py
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size: 35 LOC
McCabe index: 10
number of parameters: 3

id: 80
unit: int PickUnusedPortOrDie()
file: research/carls/kbs_server_helper.cc
start line: 98
end line: 135
size: 35 LOC
McCabe index: 7
number of parameters: 0

id: 81
unit: def copy()
file: research/gam/gam/data/dataset.py
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size: 35 LOC
McCabe index: 10
number of parameters: 10

id: 82
unit: def train()
file: research/gnn-survey/train.py
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size: 35 LOC
McCabe index: 8
number of parameters: 7

id: 83
unit: def maximize_within_unit_norm()
file: neural_structured_learning/lib/utils.py
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size: 34 LOC
McCabe index: 15
number of parameters: 3

id: 84
unit: def adversarial_loss()
file: neural_structured_learning/keras/adversarial_regularization.py
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end line: 0
size: 34 LOC
McCabe index: 10
number of parameters: 10

id: 85
unit: void GaussianMemory::AddInputToCluster()
file: research/carls/memory_store/gaussian_memory.cc
start line: 330
end line: 367
size: 34 LOC
McCabe index: 7
number of parameters: 2

id: 86
unit: def load_data_tf_datasets()
file: research/gam/gam/data/loaders.py
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size: 34 LOC
McCabe index: 1
number of parameters: 4

id: 87
unit: def load_data_realistic_ssl()
file: research/gam/gam/data/loaders.py
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end line: 0
size: 34 LOC
McCabe index: 4
number of parameters: 3

id: 88
unit: EmbeddingVectorProto InitializeEmbedding()
file: research/carls/knowledge_bank/initializer_helper.cc
start line: 57
end line: 90
size: 33 LOC
McCabe index: 8
number of parameters: 2

id: 89
unit: def __init__()
file: research/carls/dynamic_normalization.py
start line: 0
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size: 33 LOC
McCabe index: 2
number of parameters: 16

id: 90
unit: def build()
file: research/carls/dynamic_normalization.py
start line: 0
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size: 33 LOC
McCabe index: 17
number of parameters: 2

id: 91
unit: def get_graph_nbrhd_paths_randwalk()
file: research/a2n/dataset.py
start line: 0
end line: 0
size: 33 LOC
McCabe index: 9
number of parameters: 8

id: 92
unit: def build_from_adjacency_matrix()
file: research/gam/gam/data/dataset.py
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size: 33 LOC
McCabe index: 3
number of parameters: 8

id: 93
unit: def _resnet_layer()
file: research/multi_representation_adversary/multi_representation_adversary/resnet.py
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size: 33 LOC
McCabe index: 4
number of parameters: 8

id: 94
unit: absl::Status NegativeSampler::LogUniformSampleWithReplacement()
file: research/carls/candidate_sampling/negative_sampler.cc
start line: 231
end line: 266
size: 32 LOC
McCabe index: 3
number of parameters: 5

id: 95
unit: absl::Status NegativeSampler::UniformSampleWithReplacement()
file: research/carls/candidate_sampling/negative_sampler.cc
start line: 268
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size: 32 LOC
McCabe index: 4
number of parameters: 5

id: 96
unit: def embed()
file: research/a2n/encoders.py
start line: 0
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size: 32 LOC
McCabe index: 3
number of parameters: 3

id: 97
unit: def attack()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
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end line: 0
size: 32 LOC
McCabe index: 2
number of parameters: 6

id: 98
unit: def unpack_neighbor_features()
file: neural_structured_learning/lib/utils.py
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size: 31 LOC
McCabe index: 10
number of parameters: 3

id: 99
unit: absl::Status KnowledgeBank::Export()
file: research/carls/knowledge_bank/knowledge_bank.cc
start line: 98
end line: 131
size: 31 LOC
McCabe index: 6
number of parameters: 3

id: 100
unit: Status KnowledgeBankGrpcServiceImpl::Export()
file: research/carls/knowledge_bank_grpc_service.cc
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end line: 314
size: 31 LOC
McCabe index: 6
number of parameters: 3

id: 101
unit: Status KnowledgeBankGrpcServiceImpl::Import()
file: research/carls/knowledge_bank_grpc_service.cc
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size: 31 LOC
McCabe index: 7
number of parameters: 3

id: 102
unit: void Compute()
file: research/carls/kernels/dynamic_embedding_ops.cc
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size: 31 LOC
McCabe index: 3
number of parameters: 1

id: 103
unit: def __init__()
file: research/a2n/dataset.py
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size: 31 LOC
McCabe index: 7
number of parameters: 12

id: 104
unit: def generate_virtual_adversarial_perturbation()
file: research/gam/gam/trainer/adversarial_sparse.py
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size: 31 LOC
McCabe index: 3
number of parameters: 7

id: 105
unit: def eval()
file: research/kg_hyp_emb/models/base.py
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size: 31 LOC
McCabe index: 8
number of parameters: 4

id: 106
unit: def _read_tfrecord_examples()
file: neural_structured_learning/tools/build_graph.py
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size: 30 LOC
McCabe index: 6
number of parameters: 3

id: 107
unit: def perturb_on_batch()
file: neural_structured_learning/keras/adversarial_regularization.py
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size: 30 LOC
McCabe index: 9
number of parameters: 3

id: 108
unit: absl::Status ValidateInitializer()
file: research/carls/knowledge_bank/initializer_helper.cc
start line: 26
end line: 55
size: 30 LOC
McCabe index: 8
number of parameters: 2

id: 109
unit: bool FindFeatureWeights()
file: research/carls/base/input_context_helper.cc
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size: 30 LOC
McCabe index: 12
number of parameters: 2

id: 110
unit: absl::Status DynamicEmbeddingManager::UpdateGradients()
file: research/carls/dynamic_embedding_manager.cc
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size: 30 LOC
McCabe index: 5
number of parameters: 2

id: 111
unit: def __init__()
file: research/a2n/encoders.py
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size: 30 LOC
McCabe index: 5
number of parameters: 9

id: 112
unit: def build_model()
file: research/gnn-survey/utils.py
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size: 30 LOC
McCabe index: 6
number of parameters: 9

id: 113
unit: absl::Status GaussianMemory::BatchLookupWithGrowInternal()
file: research/carls/memory_store/gaussian_memory.cc
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end line: 242
size: 29 LOC
McCabe index: 6
number of parameters: 2

id: 114
unit: def _partitioned_dynamic_embedding_lookup()
file: research/carls/models/caml/sparse_features.py
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size: 29 LOC
McCabe index: 5
number of parameters: 7

id: 115
unit: def __init__()
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size: 29 LOC
McCabe index: 4
number of parameters: 11

id: 116
unit: void TopN::PushInternal()
file: research/carls/base/top_n.h
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size: 28 LOC
McCabe index: 12
number of parameters: 2

id: 117
unit: absl::Status WriteFileString()
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size: 28 LOC
McCabe index: 6
number of parameters: 3

id: 118
unit: inline std::string CurrentStackTrace()
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McCabe index: 5
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id: 119
unit: absl::Status FindFeatureValuesAndWeights()
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size: 28 LOC
McCabe index: 7
number of parameters: 3

id: 120
unit: void Compute()
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McCabe index: 1
number of parameters: 1

id: 121
unit: absl::Status DynamicEmbeddingManager::UpdateValues()
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size: 28 LOC
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number of parameters: 2

id: 122
unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def call()
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unit: absl::Status GaussianMemory::ImportInternal()
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id: 129
unit: static void LogError()
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id: 130
unit: void Compute()
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id: 131
unit: void Compute()
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id: 132
unit: void Compute()
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id: 133
unit: def distmult_kbc_model()
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id: 134
unit: def _evaluate()
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id: 135
unit: def encode_onehot()
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unit: def jensen_shannon_divergence()
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id: 137
unit: def make_missing_neighbor_inputs()
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id: 138
unit: InputContext ToInputContext()
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id: 139
unit: def get_loss_vat()
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id: 140
unit: def __init__()
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unit: def _virtual_adv_regularizer()
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id: 142
unit: def call()
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id: 143
unit: absl::Status NegativeSampler::SampleInternal()
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id: 144
unit: def compute_sampled_logits()
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id: 145
unit: def create_tuple_store()
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unit: def attend()
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unit: def build_from_features()
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id: 148
unit: def _create_weight_decay_var()
file: research/gam/gam/trainer/trainer_agreement.py
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size: 25 LOC
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id: 149
unit: def _select_val_set()
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size: 25 LOC
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id: 150
unit: def predict_label_by_agreement()
file: research/gam/gam/trainer/trainer_agreement.py
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size: 25 LOC
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id: 151
unit: def build()
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unit: def __init__()
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unit: def __init__()
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id: 154
unit: def kl_divergence()
file: neural_structured_learning/lib/distances.py
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size: 24 LOC
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id: 155
unit: std::unique_ptr GradientDescentOptimizer::Create()
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size: 24 LOC
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id: 156
unit: std::string JoinPathImpl()
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id: 157
unit: def get_graph_nbrhd_embd_text()
file: research/a2n/dataset.py
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size: 24 LOC
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id: 158
unit: def sample_or_pad()
file: research/a2n/dataset.py
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size: 24 LOC
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id: 159
unit: def create_dataset_iterator()
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size: 24 LOC
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id: 160
unit: def __init__()
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id: 161
unit: def __init__()
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id: 162
unit: def check_convergence()
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id: 163
unit: def _generate_edges()
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size: 23 LOC
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id: 164
unit: def update_states_by_cluster_assignment()
file: research/neural_clustering/models/ncp_base.py
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size: 23 LOC
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id: 165
unit: absl::Status ReadBinaryProto()
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unit: iterator find()
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id: 167
unit: void Compute()
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number of parameters: 1

id: 168
unit: def build()
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unit: def attend()
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id: 170
unit: def generate_virtual_adversarial_perturbation()
file: research/gam/gam/trainer/adversarial_dense.py
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size: 23 LOC
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id: 171
unit: def get_predictions_and_params()
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size: 23 LOC
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id: 172
unit: def load_and_aggregate()
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size: 23 LOC
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id: 173
unit: def __init__()
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id: 174
unit: def pack_nbrs()
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id: 175
unit: def _compute_loss_and_metrics()
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id: 176
unit: GaussianMemory::DistanceToNearestCluster GaussianMemory::FindNearestCluster()
file: research/carls/memory_store/gaussian_memory.cc
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size: 22 LOC
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id: 177
unit: absl::Status LeveldbKnowledgeBank::LookupWithUpdate()
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id: 178
unit: Status SetInputShape()
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unit: def __init__()
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id: 180
unit: def _pair_iterator()
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id: 181
unit: def __init__()
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id: 182
unit: def get_predictions_and_params()
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size: 22 LOC
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id: 183
unit: def get_loss()
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id: 184
unit: def __init__()
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id: 185
unit: def __init__()
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id: 186
unit: def normalize()
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id: 187
unit: def make_adv_reg_config()
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id: 188
unit: def make_graph_reg_config()
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id: 189
unit: def _prepare_metric_fns()
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id: 190
unit: def compile()
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unit: absl::Status MakeErrorStream::Impl::GetStatus()
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unit: def __init__()
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unit: def get_predictions_and_params()
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id: 194
unit: def get_encoding_and_params()
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id: 195
unit: def project_to_ball()
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id: 196
unit: def generate_batch()
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id: 197
unit: def call()
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id: 198
unit: absl::Status GaussianMemory::ProcessResults()
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id: 199
unit: void KnowledgeBank::BatchLookup()
file: research/carls/knowledge_bank/knowledge_bank.cc
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size: 20 LOC
McCabe index: 4
number of parameters: 2

id: 200
unit: void KnowledgeBank::BatchLookupWithUpdate()
file: research/carls/knowledge_bank/knowledge_bank.cc
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McCabe index: 4
number of parameters: 2

id: 201
unit: def attend()
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id: 202
unit: def __init__()
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id: 203
unit: def restore_state_from_file()
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id: 204
unit: def _create_weight_decay_var()
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id: 205
unit: def _create_weight_decay_var()
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id: 206
unit: def _project()
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unit: def call()
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unit: def call()
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id: 209
unit: def sampled_sigmoid_loss()
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id: 210
unit: std::string GetExtensionType()
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unit: absl::Status WriteTextProto()
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id: 212
unit: std::pair insert_or_assign_impl()
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number of parameters: 2

id: 213
unit: def pair_iterator()
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id: 214
unit: def predict()
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id: 215
unit: def pair_iterator()
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id: 216
unit: def get_loss()
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id: 217
unit: def get_loss()
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id: 218
unit: def _construct_layers()
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id: 219
unit: def get_loss()
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id: 220
unit: def __init__()
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id: 221
unit: def _compute_perturbations()
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id: 222
unit: def gen_adv_neighbor()
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id: 223
unit: def get_target_indices()
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id: 224
unit: def build()
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id: 225
unit: def __init__()
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id: 226
unit: def dynamic_embedding_lookup()
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id: 227
unit: absl::Status MemoryStore::Export()
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id: 228
unit: def dynamic_gaussian_memory_lookup()
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id: 229
unit: def sampled_softmax_loss()
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id: 230
unit: EmbeddingVectorProto GradientDescentOptimizer::ApplyAdagrad()
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number of parameters: 2

id: 231
unit: absl::Status InProtoKnowledgeBank::LookupWithUpdate()
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number of parameters: 2

id: 232
unit: absl::Status BuildInputFeatureWithWeights()
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id: 233
unit: absl::Status BuildInputFeatureWithWeights()
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id: 234
unit: absl::Status BuildInputFeatureWithWeights()
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id: 235
unit: absl::Status BuildInputFeatureWithWeights()
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id: 236
unit: absl::Status BuildInputFeatureWithWeights()
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id: 237
unit: absl::Status BuildInputFeatureWithWeightsAndDebugInfo()
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id: 238
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id: 239
unit: absl::Status BuildInputFeatureWithWeightsAndDebugInfo()
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id: 240
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id: 241
unit: absl::Status DynamicEmbeddingManager::LookupInternal()
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id: 242
unit: absl::Status DynamicEmbeddingManager::Export()
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id: 243
unit: def __init__()
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id: 244
unit: def get_train_op()
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unit: def load_data_planetoid()
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id: 246
unit: def _eval_train()
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unit: def get_encoding_and_params()
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id: 248
unit: def _evaluate_dataset()
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unit: def _compute_gradient()
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unit: def _interleave_and_merge()
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unit: def build_graph()
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unit: def _read_tfrecord_examples()
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unit: def call()
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unit: absl::Status GaussianMemory::BatchLookupWithUpdateInternal()
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unit: absl::Status LeveldbKnowledgeBank::ExportInternal()
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unit: def save_knowledge_bank()
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unit: def get_graph_nbrhd_paths()
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unit: def save_embedding_vocabs()
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unit: def create_agreement_prediction()
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id: 262
unit: def _eval_random_pairs()
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id: 263
unit: def get_examples()
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id: 264
unit: def __init__()
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unit: def get_queries()
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unit: def build()
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unit: def main()
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unit: def __init__()
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unit: def graph_call()
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unit: def _main()
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unit: def _prepare_loss_weights()
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id: 272
unit: SampledResult BuildSampledResult()
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unit: float GaussianMemory::ComputeDistance()
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unit: GaussianMemoryCheckpointMetaData GaussianMemory::ConvertToCheckpointMetaData()
file: research/carls/memory_store/gaussian_memory.cc
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id: 275
unit: absl::Status LeveldbKnowledgeBank::Update()
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id: 276
unit: Status KnowledgeBankGrpcServiceImpl::StartSession()
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unit: absl::Status ReadTextProto()
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unit: explicit DynamicEmbeddingManagerResourceOp()
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unit: def _max_neighbors()
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unit: def store_paths()
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unit: def embed()
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id: 282
unit: def _get_neighbors()
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id: 283
unit: def __init__()
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unit: def _construct_encoding()
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unit: def __init__()
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id: 286
unit: def get_encoding_and_params()
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id: 287
unit: def _aggregate()
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id: 288
unit: def hyp_distance()
file: research/kg_hyp_emb/utils/hyperbolic.py
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id: 289
unit: def call()
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unit: def __init__()
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unit: def graph_call()
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unit: def _replicate_index()
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unit: def __init__()
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unit: def _prepare_loss_fns()
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id: 295
unit: def _build_labeled_losses()
file: neural_structured_learning/keras/adversarial_regularization.py
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id: 296
unit: static std::unique_ptr Make()
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unit: std::string GetExtensionType()
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unit: bool ComputeCosineSimilarity()
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id: 299
unit: def read_entity_name_mapping()
file: research/a2n/utils.py
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id: 300
unit: def get_edges()
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id: 301
unit: def _call()
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id: 302
unit: def get_queries()
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id: 303
unit: def call()
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id: 304
unit: def _main()
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id: 305
unit: def __init__()
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id: 306
unit: def _build_labeled_metrics()
file: neural_structured_learning/keras/adversarial_regularization.py
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id: 307
unit: def add_to_collection()
file: research/carls/context.py
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id: 308
unit: def top_k()
file: research/carls/candidate_sampling_ops.py
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id: 309
unit: absl::Status InProtoKnowledgeBank::Update()
file: research/carls/knowledge_bank/in_proto_knowledge_bank.cc
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id: 310
unit: std::vector KnowledgeBank::BatchUpdate()
file: research/carls/knowledge_bank/knowledge_bank.cc
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id: 311
unit: absl::Status KnowledgeBank::Import()
file: research/carls/knowledge_bank/knowledge_bank.cc
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id: 312
unit: static absl::Status MakeError()
file: research/carls/base/status_helper.cc
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id: 313
unit: def get_graph_nbrhd_text()
file: research/a2n/dataset.py
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id: 314
unit: def attend()
file: research/a2n/encoders.py
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id: 315
unit: def mrr()
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id: 316
unit: def sparse_to_tuple()
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id: 317
unit: def get_loss_vat()
file: research/gam/gam/trainer/adversarial_dense.py
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id: 318
unit: def _construct_feed_dict()
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id: 319
unit: def build_attack_fn()
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size: 14 LOC
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id: 320
unit: def build_train_step_fn()
file: research/multi_representation_adversary/multi_representation_adversary/helper.py
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id: 321
unit: def __init__()
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id: 322
unit: def __init__()
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id: 323
unit: def _select_distance_fn()
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id: 324
unit: def replicate_embeddings()
file: neural_structured_learning/lib/utils.py
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id: 325
unit: def add_undirected_edges()
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id: 326
unit: def read_tsv_graph()
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unit: def __call__()
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id: 328
unit: def __init__()
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id: 329
unit: def _make_metric_name()
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id: 330
unit: def initialize_states()
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unit: def dynamic_embedding_update()
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unit: def negative_sampler()
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unit: absl::Status CandidateSampler::Sample()
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unit: absl::Status GaussianMemory::BatchLookupInternal()
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id: 335
unit: GaussianCluster GaussianMemory::ConvertToGaussianCluster()
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id: 336
unit: absl::Status InProtoKnowledgeBank::Lookup()
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id: 337
unit: absl::Status InProtoKnowledgeBank::ImportInternal()
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unit: absl::Status ReadFileString()
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unit: def dynamic_normalization()
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id: 345
unit: def _eval_validation()
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id: 346
unit: def predict()
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id: 347
unit: def load_data()
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id: 348
unit: def get_predictions_and_params()
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id: 349
unit: def get_filters()
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unit: def train_step()
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unit: def build()
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unit: def main()
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unit: def __call__()
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unit: def _call_base_model()
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id: 360
unit: void ThreadBundle::Add()
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id: 361
unit: void Compute()
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id: 362
unit: def get_graph_nbrhd()
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unit: def lookup()
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unit: def predict()
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unit: def dct()
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id: 368
unit: def attack()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 12 LOC
McCabe index: 3
number of parameters: 6

id: 369
unit: def l1_config()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
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end line: 0
size: 12 LOC
McCabe index: 1
number of parameters: 5

id: 370
unit: def main()
file: research/multi_representation_adversary/multi_representation_adversary/main.py
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end line: 0
size: 12 LOC
McCabe index: 3
number of parameters: 1

id: 371
unit: def get_idx()
file: research/kg_hyp_emb/datasets/process.py
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end line: 0
size: 12 LOC
McCabe index: 5
number of parameters: 1

id: 372
unit: def similarity_score()
file: research/kg_hyp_emb/models/euclidean.py
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end line: 0
size: 12 LOC
McCabe index: 4
number of parameters: 4

id: 373
unit: def build()
file: research/gnn-survey/layers.py
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size: 12 LOC
McCabe index: 1
number of parameters: 2

id: 374
unit: def _apply_perturbations()
file: neural_structured_learning/lib/adversarial_neighbor.py
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size: 11 LOC
McCabe index: 3
number of parameters: 3

id: 375
unit: def decay_over_time()
file: neural_structured_learning/lib/utils.py
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size: 11 LOC
McCabe index: 1
number of parameters: 3

id: 376
unit: def resolve_metric()
file: neural_structured_learning/keras/adversarial_regularization.py
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size: 11 LOC
McCabe index: 10
number of parameters: 2

id: 377
unit: def brute_force_topk_sampler()
file: research/carls/candidate_sampling/candidate_sampler_config_builder.py
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size: 11 LOC
McCabe index: 4
number of parameters: 1

id: 378
unit: bool IsFurther()
file: research/carls/memory_store/distance_helper.cc
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end line: 55
size: 11 LOC
McCabe index: 3
number of parameters: 3

id: 379
unit: def _sampled_logits_lookup_grad()
file: research/carls/candidate_sampling_ops.py
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size: 11 LOC
McCabe index: 2
number of parameters: 6

id: 380
unit: absl::Status CheckInputInputFeature()
file: research/carls/base/input_context_helper.cc
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size: 11 LOC
McCabe index: 1
number of parameters: 4

id: 381
unit: absl::Status WriteBinaryProto()
file: research/carls/base/proto_helper.cc
start line: 68
end line: 78
size: 11 LOC
McCabe index: 2
number of parameters: 3

id: 382
unit: EmbeddingVectorProto ToEmbeddingVectorProto()
file: research/carls/base/embedding_helper.cc
start line: 29
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size: 11 LOC
McCabe index: 2
number of parameters: 1

id: 383
unit: bool ComputeDotProduct()
file: research/carls/base/embedding_helper.cc
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size: 11 LOC
McCabe index: 4
number of parameters: 3

id: 384
unit: absl::Status DynamicEmbeddingManager::Import()
file: research/carls/dynamic_embedding_manager.cc
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McCabe index: 1
number of parameters: 1

id: 385
unit: def _proc_paths()
file: research/a2n/dataset.py
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McCabe index: 5
number of parameters: 6

id: 386
unit: def add_variable_summaries()
file: research/a2n/utils.py
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size: 11 LOC
McCabe index: 1
number of parameters: 2

id: 387
unit: def variable_summaries()
file: research/gam/gam/trainer/trainer_base.py
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size: 11 LOC
McCabe index: 1
number of parameters: 1

id: 388
unit: def _evaluate()
file: research/gam/gam/trainer/trainer_classification_gcn.py
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size: 11 LOC
McCabe index: 2
number of parameters: 5

id: 389
unit: def process_dataset()
file: research/kg_hyp_emb/datasets/process.py
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size: 11 LOC
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number of parameters: 1

id: 390
unit: def get_factors()
file: research/kg_hyp_emb/models/complex.py
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size: 11 LOC
McCabe index: 1
number of parameters: 2

id: 391
unit: def call()
file: research/kg_hyp_emb/models/base.py
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size: 11 LOC
McCabe index: 2
number of parameters: 3

id: 392
unit: def score()
file: research/kg_hyp_emb/models/base.py
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McCabe index: 4
number of parameters: 6

id: 393
unit: def call()
file: research/gnn-survey/layers.py
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size: 11 LOC
McCabe index: 3
number of parameters: 2

id: 394
unit: def _assert_multinomial_distribution()
file: neural_structured_learning/lib/distances.py
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size: 10 LOC
McCabe index: 1
number of parameters: 2

id: 395
unit: def call()
file: neural_structured_learning/keras/layers/pairwise_distance.py
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size: 10 LOC
McCabe index: 2
number of parameters: 3

id: 396
unit: def get_config()
file: neural_structured_learning/keras/layers/pairwise_distance.py
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size: 10 LOC
McCabe index: 3
number of parameters: 1

id: 397
unit: def __init__()
file: neural_structured_learning/keras/graph_regularization.py
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size: 10 LOC
McCabe index: 2
number of parameters: 3

id: 398
unit: def generate_batch()
file: research/neural_clustering/data_generators/mog.py
start line: 0
end line: 0
size: 10 LOC
McCabe index: 2
number of parameters: 4

id: 399
unit: def remap_label_ids()
file: research/neural_clustering/utils/data_utils.py
start line: 0
end line: 0
size: 10 LOC
McCabe index: 3
number of parameters: 1

id: 400
unit: def build_candidate_sampler_config()
file: research/carls/candidate_sampling/candidate_sampler_config_builder.py
start line: 0
end line: 0
size: 10 LOC
McCabe index: 3
number of parameters: 1

id: 401
unit: def _get_neighbor_logits()
file: research/carls/graph_regularization.py
start line: 0
end line: 0
size: 10 LOC
McCabe index: 3
number of parameters: 4

id: 402
unit: float DistanceUpperBound()
file: research/carls/memory_store/distance_helper.cc
start line: 23
end line: 32
size: 10 LOC
McCabe index: 3
number of parameters: 1

id: 403
unit: float DistanceLowerBound()
file: research/carls/memory_store/distance_helper.cc
start line: 34
end line: 43
size: 10 LOC
McCabe index: 3
number of parameters: 1

id: 404
unit: bool FindFeatureWeightsByName()
file: research/carls/base/input_context_helper.cc
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end line: 491
size: 10 LOC
McCabe index: 2
number of parameters: 3

id: 405
unit: void TopN::ExtractNondestructive()
file: research/carls/base/top_n.h
start line: 305
end line: 314
size: 10 LOC
McCabe index: 2
number of parameters: 1

id: 406
unit: std::pair SplitPath()
file: research/carls/base/file_helper.cc
start line: 118
end line: 132
size: 10 LOC
McCabe index: 3
number of parameters: 1

id: 407
unit: std::vector get_begin_iterators()
file: research/carls/base/async_node_hash_map.h
start line: 351
end line: 360
size: 10 LOC
McCabe index: 2
number of parameters: 0

id: 408
unit: std::vector get_end_iterators()
file: research/carls/base/async_node_hash_map.h
start line: 362
end line: 371
size: 10 LOC
McCabe index: 2
number of parameters: 0

id: 409
unit: bool FindFeatureValuesByName()
file: research/carls/base/input_context_helper.h
start line: 66
end line: 75
size: 10 LOC
McCabe index: 2
number of parameters: 3

id: 410
unit: def _add_offset()
file: research/carls/dynamic_normalization.py
start line: 0
end line: 0
size: 10 LOC
McCabe index: 1
number of parameters: 3

id: 411
unit: def _add_scale()
file: research/carls/dynamic_normalization.py
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end line: 0
size: 10 LOC
McCabe index: 1
number of parameters: 3

id: 412
unit: def get_attention_probs()
file: research/a2n/encoders.py
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end line: 0
size: 10 LOC
McCabe index: 1
number of parameters: 5

id: 413
unit: def _lookup()
file: research/a2n/encoders.py
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size: 10 LOC
McCabe index: 1
number of parameters: 3

id: 414
unit: def save_state_to_file()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 10 LOC
McCabe index: 1
number of parameters: 2

id: 415
unit: def split_train_val()
file: research/gam/gam/data/preprocessing.py
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end line: 0
size: 10 LOC
McCabe index: 3
number of parameters: 4

id: 416
unit: def get_encoding_and_params()
file: research/gam/gam/models/gcn.py
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end line: 0
size: 10 LOC
McCabe index: 3
number of parameters: 6

id: 417
unit: def to_np_array()
file: research/kg_hyp_emb/datasets/process.py
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end line: 0
size: 10 LOC
McCabe index: 3
number of parameters: 3

id: 418
unit: def get_queries()
file: research/kg_hyp_emb/models/complex.py
start line: 0
end line: 0
size: 10 LOC
McCabe index: 1
number of parameters: 2

id: 419
unit: def get_scores_targets()
file: research/kg_hyp_emb/models/base.py
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end line: 0
size: 10 LOC
McCabe index: 1
number of parameters: 2

id: 420
unit: def call()
file: research/gnn-survey/layers.py
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size: 10 LOC
McCabe index: 3
number of parameters: 2

id: 421
unit: def __init__()
file: research/gnn-survey/models.py
start line: 0
end line: 0
size: 10 LOC
McCabe index: 1
number of parameters: 6

id: 422
unit: def _select_decay_fn()
file: neural_structured_learning/lib/utils.py
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end line: 0
size: 9 LOC
McCabe index: 4
number of parameters: 1

id: 423
unit: def virtual_adv_regularizer()
file: neural_structured_learning/lib/regularizer.py
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end line: 0
size: 9 LOC
McCabe index: 2
number of parameters: 4

id: 424
unit: def __init__()
file: neural_structured_learning/tools/build_graph.py
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end line: 0
size: 9 LOC
McCabe index: 9
number of parameters: 2

id: 425
unit: def _generate_lsh_buckets()
file: neural_structured_learning/tools/build_graph.py
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end line: 0
size: 9 LOC
McCabe index: 3
number of parameters: 2

id: 426
unit: def add_edge()
file: neural_structured_learning/tools/graph_utils.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 4
number of parameters: 2

id: 427
unit: def write_tsv_graph()
file: neural_structured_learning/tools/graph_utils.py
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end line: 0
size: 9 LOC
McCabe index: 3
number of parameters: 2

id: 428
unit: def __call__()
file: neural_structured_learning/keras/adversarial_regularization.py
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size: 9 LOC
McCabe index: 3
number of parameters: 3

id: 429
unit: def __init__()
file: research/carls/dynamic_embedding_neighbor_cache.py
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size: 9 LOC
McCabe index: 1
number of parameters: 5

id: 430
unit: def _dynamic_gaussian_memory_lookup_grad()
file: research/carls/dynamic_memory_ops.py
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end line: 0
size: 9 LOC
McCabe index: 5
number of parameters: 5

id: 431
unit: EmbeddingVectorProto InitTensor()
file: research/carls/gradient_descent/gradient_descent_optimizer.cc
start line: 24
end line: 32
size: 9 LOC
McCabe index: 2
number of parameters: 2

id: 432
unit: EmbeddingVectorProto GradientDescentOptimizer::ApplyGradientDescent()
file: research/carls/gradient_descent/gradient_descent_optimizer.cc
start line: 115
end line: 123
size: 9 LOC
McCabe index: 2
number of parameters: 2

id: 433
unit: void ThreadBundle::Init()
file: research/carls/base/thread_bundle.cc
start line: 46
end line: 54
size: 9 LOC
McCabe index: 1
number of parameters: 0

id: 434
unit: tensorflow::Tensor ToTensorFlowTensor()
file: research/carls/base/embedding_helper.cc
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end line: 56
size: 9 LOC
McCabe index: 2
number of parameters: 1

id: 435
unit: bool empty()
file: research/carls/base/async_node_hash_map.h
start line: 188
end line: 196
size: 9 LOC
McCabe index: 3
number of parameters: 0

id: 436
unit: absl::Status FindFeatureValuesAndWeightsByName()
file: research/carls/base/input_context_helper.h
start line: 99
end line: 107
size: 9 LOC
McCabe index: 2
number of parameters: 3

id: 437
unit: Status CreateResource()
file: research/carls/kernels/dynamic_embedding_manager_resource.cc
start line: 91
end line: 99
size: 9 LOC
McCabe index: 2
number of parameters: 1

id: 438
unit: def get_graph_nbrhd_with_rels()
file: research/a2n/dataset.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 13
number of parameters: 3

id: 439
unit: def _tuple_iterator()
file: research/a2n/dataset.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 5
number of parameters: 1

id: 440
unit: def __init__()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 4

id: 441
unit: def generate_graph()
file: research/a2n/generate_random_graph.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 3
number of parameters: 0

id: 442
unit: def __init__()
file: research/gam/gam/trainer/trainer_base.py
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size: 9 LOC
McCabe index: 1
number of parameters: 5

id: 443
unit: def __init__()
file: research/gam/gam/trainer/trainer_agreement.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 2

id: 444
unit: def sparse_dropout()
file: research/gam/gam/models/gcn.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 3

id: 445
unit: def linf_config()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 2

id: 446
unit: def l2_config()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 2

id: 447
unit: def __init__()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 4

id: 448
unit: def update()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 3
number of parameters: 3

id: 449
unit: def _update()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 2
number of parameters: 3

id: 450
unit: def build_eval_step_fn()
file: research/multi_representation_adversary/multi_representation_adversary/helper.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 2
number of parameters: 3

id: 451
unit: def euc_sq_distance()
file: research/kg_hyp_emb/utils/euclidean.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 2
number of parameters: 3

id: 452
unit: def givens_reflection()
file: research/kg_hyp_emb/utils/euclidean.py
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end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 2

id: 453
unit: def __init__()
file: research/kg_hyp_emb/models/euclidean.py
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end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 3

id: 454
unit: def __init__()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 3

id: 455
unit: def __init__()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 3

id: 456
unit: def get_queries()
file: research/kg_hyp_emb/models/hyperbolic.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 1
number of parameters: 2

id: 457
unit: def similarity_score()
file: research/kg_hyp_emb/models/complex.py
start line: 0
end line: 0
size: 9 LOC
McCabe index: 2
number of parameters: 4

id: 458
unit: def _split_dict()
file: neural_structured_learning/lib/adversarial_neighbor.py
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end line: 0
size: 8 LOC
McCabe index: 3
number of parameters: 3

id: 459
unit: def apply_feature_mask()
file: neural_structured_learning/lib/utils.py
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end line: 0
size: 8 LOC
McCabe index: 2
number of parameters: 2

id: 460
unit: def _replicate_sources()
file: neural_structured_learning/keras/layers/pairwise_distance.py
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end line: 0
size: 8 LOC
McCabe index: 6
number of parameters: 3

id: 461
unit: def _extract_labels_and_weights()
file: neural_structured_learning/keras/adversarial_regularization.py
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end line: 0
size: 8 LOC
McCabe index: 3
number of parameters: 2

id: 462
unit: def build()
file: research/carls/dynamic_embedding_ops.py
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end line: 0
size: 8 LOC
McCabe index: 2
number of parameters: 2

id: 463
unit: def lookup()
file: research/carls/dynamic_embedding_neighbor_cache.py
start line: 0
end line: 0
size: 8 LOC
McCabe index: 1
number of parameters: 2

id: 464
unit: void ClearInternalData()
file: research/carls/knowledge_bank/leveldb_knowledge_bank.cc
start line: 104
end line: 113
size: 8 LOC
McCabe index: 1
number of parameters: 0

id: 465
unit: std::vector GetAllFeatureNames()
file: research/carls/base/input_context_helper.cc
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size: 8 LOC
McCabe index: 2
number of parameters: 1

id: 466
unit: size_t size()
file: research/carls/base/async_node_hash_map.h
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size: 8 LOC
McCabe index: 2
number of parameters: 0

id: 467
unit: std::string TimestampedDirname()
file: research/carls/kernels/io_ops.cc
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size: 8 LOC
McCabe index: 1
number of parameters: 0

id: 468
unit: def restore_knowledge_bank()
file: research/carls/io_ops.py
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size: 8 LOC
McCabe index: 1
number of parameters: 5

id: 469
unit: def _compute_label_correctness()
file: research/gam/gam/data/dataset.py
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size: 8 LOC
McCabe index: 2
number of parameters: 2

id: 470
unit: def get_edges()
file: research/gam/gam/data/dataset.py
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end line: 0
size: 8 LOC
McCabe index: 1
number of parameters: 4

id: 471
unit: def _create_counter()
file: research/gam/gam/trainer/trainer_cotrain.py
start line: 0
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size: 8 LOC
McCabe index: 1
number of parameters: 1

id: 472
unit: def _create_counter()
file: research/gam/gam/trainer/trainer_classification.py
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size: 8 LOC
McCabe index: 1
number of parameters: 1

id: 473
unit: def _create_counter()
file: research/gam/gam/trainer/trainer_agreement.py
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size: 8 LOC
McCabe index: 1
number of parameters: 1

id: 474
unit: def create_agreement_prediction()
file: research/gam/gam/trainer/trainer_agreement.py
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size: 8 LOC
McCabe index: 1
number of parameters: 4

id: 475
unit: def _create_counter()
file: research/gam/gam/trainer/trainer_classification_gcn.py
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size: 8 LOC
McCabe index: 1
number of parameters: 1

id: 476
unit: def kl_divergence_with_logit()
file: research/gam/gam/trainer/adversarial_sparse.py
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size: 8 LOC
McCabe index: 1
number of parameters: 3

id: 477
unit: def fast_flip()
file: research/gam/gam/models/wide_resnet.py
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size: 8 LOC
McCabe index: 1
number of parameters: 2

id: 478
unit: def save_gin_config()
file: research/multi_representation_adversary/multi_representation_adversary/main.py
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size: 8 LOC
McCabe index: 3
number of parameters: 2

id: 479
unit: def __init__()
file: research/kg_hyp_emb/learning/losses.py
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size: 8 LOC
McCabe index: 1
number of parameters: 3

id: 480
unit: def calculate_loss()
file: research/kg_hyp_emb/learning/losses.py
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size: 8 LOC
McCabe index: 4
number of parameters: 3

id: 481
unit: def givens_rotations()
file: research/kg_hyp_emb/utils/euclidean.py
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end line: 0
size: 8 LOC
McCabe index: 1
number of parameters: 2

id: 482
unit: def __init__()
file: research/kg_hyp_emb/models/hyperbolic.py
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size: 8 LOC
McCabe index: 1
number of parameters: 3

id: 483
unit: def get_queries()
file: research/kg_hyp_emb/models/complex.py
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size: 8 LOC
McCabe index: 1
number of parameters: 2

id: 484
unit: def call()
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McCabe index: 2
number of parameters: 2

id: 485
unit: def call()
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McCabe index: 2
number of parameters: 2

id: 486
unit: def call()
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McCabe index: 2
number of parameters: 2

id: 487
unit: def __init__()
file: neural_structured_learning/experimental/gnn.py
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size: 7 LOC
McCabe index: 1
number of parameters: 4

id: 488
unit: def _compose_as_dict()
file: neural_structured_learning/lib/adversarial_neighbor.py
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size: 7 LOC
McCabe index: 4
number of parameters: 2

id: 489
unit: def _decompose_as()
file: neural_structured_learning/lib/adversarial_neighbor.py
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size: 7 LOC
McCabe index: 5
number of parameters: 3

id: 490
unit: def _bucket()
file: neural_structured_learning/tools/build_graph.py
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size: 7 LOC
McCabe index: 3
number of parameters: 3

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unit: def _clone_metrics()
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unit: def __init__()
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unit: def avg_both()
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unit: def _reduce_across_tensors()
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unit: def adv_regularizer()
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unit: def get_config()
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unit: def _is_binary_classification_loss()
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unit: def _get_or_create_base_output_names()
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unit: def increment_last_dim()
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unit: void AddOrUpdateFeature()
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unit: InMemoryEmbeddingVector ToInMemoryEmbeddingVector()
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unit: bool ComputeCosineSimilarity()
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unit: bool ComputeCosineSimilarity()
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unit: void MakeErrorStream::Impl::CheckNotDone()
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unit: def predict()
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McCabe index: 1
number of parameters: 2

id: 614
unit: def count_params()
file: research/kg_hyp_emb/utils/train.py
start line: 0
end line: 0
size: 5 LOC
McCabe index: 2
number of parameters: 1

id: 615
unit: def get_queries()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 5 LOC
McCabe index: 1
number of parameters: 2

id: 616
unit: def get_queries()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 5 LOC
McCabe index: 1
number of parameters: 2

id: 617
unit: def get_queries()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 5 LOC
McCabe index: 1
number of parameters: 2

id: 618
unit: def __init__()
file: research/kg_hyp_emb/models/complex.py
start line: 0
end line: 0
size: 5 LOC
McCabe index: 1
number of parameters: 3

id: 619
unit: def __init__()
file: research/gnn-survey/layers.py
start line: 0
end line: 0
size: 5 LOC
McCabe index: 1
number of parameters: 5

id: 620
unit: def normalize_adj_matrix()
file: research/gnn-survey/utils.py
start line: 0
end line: 0
size: 5 LOC
McCabe index: 1
number of parameters: 1

id: 621
unit: def _kl_divergence_fn()
file: neural_structured_learning/lib/distances.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 622
unit: def _is_axis_required_in_distance_fn()
file: neural_structured_learning/lib/distances.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 623
unit: def is_differentiable_tensor()
file: neural_structured_learning/lib/adversarial_neighbor.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 4
number of parameters: 1

id: 624
unit: def build_graph_from_config()
file: neural_structured_learning/tools/build_graph.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 625
unit: def from_config()
file: neural_structured_learning/keras/layers/pairwise_distance.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 626
unit: def _compute_total_loss()
file: neural_structured_learning/keras/adversarial_regularization.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 4

id: 627
unit: def save()
file: neural_structured_learning/keras/adversarial_regularization.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 628
unit: def __init__()
file: research/neural_clustering/data_generators/partition.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 2

id: 629
unit: def __init__()
file: research/neural_clustering/models/ncp_wrapper.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 630
unit: def loss_function()
file: research/neural_clustering/models/ncp_wrapper.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 631
unit: def call()
file: research/carls/dynamic_embedding_ops.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 632
unit: uint32_t Uniform()
file: research/carls/candidate_sampling/negative_sampler.cc
start line: 78
end line: 81
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 633
unit: float RandFloat()
file: research/carls/candidate_sampling/negative_sampler.cc
start line: 84
end line: 87
size: 4 LOC
McCabe index: 1
number of parameters: 0

id: 634
unit: absl::Status CandidateSampler::InsertOrUpdate()
file: research/carls/candidate_sampling/candidate_sampler.cc
start line: 42
end line: 45
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 635
unit: absl::Status MemoryStore::Import()
file: research/carls/memory_store/memory_store.cc
start line: 73
end line: 76
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 636
unit: size_t Size()
file: research/carls/knowledge_bank/leveldb_knowledge_bank.cc
start line: 85
end line: 88
size: 4 LOC
McCabe index: 1
number of parameters: 0

id: 637
unit: absl::Status LeveldbKnowledgeBank::ImportInternal()
file: research/carls/knowledge_bank/leveldb_knowledge_bank.cc
start line: 250
end line: 253
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 638
unit: size_t InProtoKnowledgeBank::Size()
file: research/carls/knowledge_bank/in_proto_knowledge_bank.cc
start line: 167
end line: 170
size: 4 LOC
McCabe index: 1
number of parameters: 0

id: 639
unit: std::vector InProtoKnowledgeBank::Keys()
file: research/carls/knowledge_bank/in_proto_knowledge_bank.cc
start line: 172
end line: 175
size: 4 LOC
McCabe index: 1
number of parameters: 0

id: 640
unit: size_t KnowledgeBankGrpcServiceImpl::KnowledgeBankSize()
file: research/carls/knowledge_bank_grpc_service.cc
start line: 348
end line: 351
size: 4 LOC
McCabe index: 1
number of parameters: 0

id: 641
unit: bool FeatureExists()
file: research/carls/base/input_context_helper.cc
start line: 49
end line: 52
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 642
unit: void ThreadBundle::Inc()
file: research/carls/base/thread_bundle.cc
start line: 79
end line: 82
size: 4 LOC
McCabe index: 1
number of parameters: 0

id: 643
unit: void ThreadBundle::Dec()
file: research/carls/base/thread_bundle.cc
start line: 84
end line: 87
size: 4 LOC
McCabe index: 2
number of parameters: 0

id: 644
unit: void TopN::Reset()
file: research/carls/base/top_n.h
start line: 334
end line: 337
size: 4 LOC
McCabe index: 1
number of parameters: 0

id: 645
unit: absl::Status IsDirectory()
file: research/carls/base/file_helper.cc
start line: 105
end line: 108
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 646
unit: absl::Status RecursivelyCreateDir()
file: research/carls/base/file_helper.cc
start line: 134
end line: 137
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 647
unit: static absl::Status MakeStatus()
file: research/carls/base/status_helper.cc
start line: 34
end line: 37
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 648
unit: absl::Status ToAbslStatus()
file: research/carls/base/status_helper.cc
start line: 210
end line: 213
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 649
unit: absl::Status ToAbslStatus()
file: research/carls/base/status_helper.cc
start line: 215
end line: 218
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 650
unit: grpc::Status ToGrpcStatus()
file: research/carls/base/status_helper.cc
start line: 220
end line: 223
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 651
unit: def _get_training_value()
file: research/carls/dynamic_normalization.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 2

id: 652
unit: T DieIfNull()
file: research/carls/dynamic_embedding_manager.cc
start line: 45
end line: 48
size: 4 LOC
McCabe index: 2
number of parameters: 4

id: 653
unit: def __init__()
file: research/carls/models/caml/sparse_features.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 654
unit: def call()
file: research/carls/models/caml/sparse_features.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 655
unit: def __init__()
file: research/a2n/graph.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 0

id: 656
unit: def add_embedding_to_projector()
file: research/a2n/train.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 657
unit: def read_graph_data()
file: research/a2n/train.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 0

id: 658
unit: def get_from_collection()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 2

id: 659
unit: def __init__()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 660
unit: def __init__()
file: research/a2n/encoders.py
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end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 8

id: 661
unit: def __init__()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 10

id: 662
unit: def embed()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 663
unit: def combine_dict()
file: research/a2n/utils.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 2

id: 664
unit: def get_features()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 665
unit: def update_labels()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 666
unit: def __init__()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 4

id: 667
unit: def convert_image()
file: research/gam/gam/data/preprocessing.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 668
unit: def get_normalized_vector()
file: research/gam/gam/trainer/adversarial_dense.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 669
unit: def get_normalizing_constant()
file: research/gam/gam/trainer/adversarial_dense.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 670
unit: def entropy_y_x()
file: research/gam/gam/trainer/adversarial_dense.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 671
unit: def predict()
file: research/gam/gam/trainer/trainer_agreement.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 6

id: 672
unit: def logsoftmax()
file: research/gam/gam/trainer/adversarial_sparse.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 1

id: 673
unit: def normalize_predictions()
file: research/gam/gam/models/cnn.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 2

id: 674
unit: def normalize_predictions()
file: research/gam/gam/models/gcn.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 2

id: 675
unit: def __call__()
file: research/gam/gam/models/gcn.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 676
unit: def normalize_predictions()
file: research/gam/gam/models/mlp.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 2

id: 677
unit: def save()
file: research/gam/gam/models/models_base.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 4

id: 678
unit: def load()
file: research/gam/gam/models/models_base.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 4

id: 679
unit: def normalize_predictions()
file: research/gam/gam/models/wide_resnet.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 2

id: 680
unit: def __init__()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 681
unit: def _update()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 682
unit: def __init__()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 683
unit: def learning_rate_scheduler()
file: research/multi_representation_adversary/multi_representation_adversary/trainer.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 3
number of parameters: 4

id: 684
unit: def logmap0()
file: research/kg_hyp_emb/utils/hyperbolic.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 685
unit: def get_queries()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 686
unit: def get_queries()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 687
unit: def __init__()
file: research/kg_hyp_emb/models/hyperbolic.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 3

id: 688
unit: def cal_acc()
file: research/gnn-survey/utils.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 689
unit: def call()
file: research/gnn-survey/models.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 690
unit: def call()
file: research/gnn-survey/models.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 2
number of parameters: 2

id: 691
unit: def call()
file: research/gnn-survey/models.py
start line: 0
end line: 0
size: 4 LOC
McCabe index: 1
number of parameters: 2

id: 692
unit: def __init__()
file: neural_structured_learning/experimental/gnn.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 693
unit: def __init__()
file: neural_structured_learning/experimental/gnn.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 694
unit: def _assert_valid_axis()
file: neural_structured_learning/lib/distances.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 4
number of parameters: 2

id: 695
unit: def call()
file: neural_structured_learning/keras/layers/neighbor_features.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 696
unit: def _include_feature()
file: neural_structured_learning/keras/layers/neighbor_features.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 3
number of parameters: 2

id: 697
unit: def from_config()
file: neural_structured_learning/keras/layers/neighbor_features.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 698
unit: def compile()
file: neural_structured_learning/keras/graph_regularization.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 699
unit: def _is_sparse_categorical_loss()
file: neural_structured_learning/keras/adversarial_regularization.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 2
number of parameters: 1

id: 700
unit: def batch_multinomial_sampling()
file: research/neural_clustering/data_generators/partition.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 701
unit: bool operator()
file: research/carls/candidate_sampling/brute_force_topk_sampler.cc
start line: 46
end line: 48
size: 3 LOC
McCabe index: 1
number of parameters: 0

id: 702
unit: float StableExpectedCount()
file: research/carls/candidate_sampling/negative_sampler.cc
start line: 34
end line: 36
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 703
unit: int CandidateSampler::NumOfCandidates()
file: research/carls/candidate_sampling/candidate_sampler.cc
start line: 47
end line: 49
size: 3 LOC
McCabe index: 1
number of parameters: 0

id: 704
unit: def get_all_collection()
file: research/carls/context.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 2
number of parameters: 0

id: 705
unit: def clear_all_collection()
file: research/carls/context.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 0

id: 706
unit: void push()
file: research/carls/base/top_n.h
start line: 116
end line: 118
size: 3 LOC
McCabe index: 2
number of parameters: 1

id: 707
unit: void push()
file: research/carls/base/top_n.h
start line: 119
end line: 121
size: 3 LOC
McCabe index: 2
number of parameters: 2

id: 708
unit: bool IsAbsolutePath()
file: research/carls/base/file_helper.cc
start line: 26
end line: 28
size: 3 LOC
McCabe index: 2
number of parameters: 1

id: 709
unit: absl::string_view Dirname()
file: research/carls/base/file_helper.cc
start line: 110
end line: 112
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 710
unit: absl::string_view Basename()
file: research/carls/base/file_helper.cc
start line: 114
end line: 116
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 711
unit: std::string JoinPath()
file: research/carls/base/file_helper.h
start line: 46
end line: 48
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 712
unit: iterator begin()
file: research/carls/base/async_node_hash_map.h
start line: 180
end line: 182
size: 3 LOC
McCabe index: 1
number of parameters: 0

id: 713
unit: iterator end()
file: research/carls/base/async_node_hash_map.h
start line: 183
end line: 185
size: 3 LOC
McCabe index: 1
number of parameters: 0

id: 714
unit: std::pair insert_or_assign()
file: research/carls/base/async_node_hash_map.h
start line: 224
end line: 226
size: 3 LOC
McCabe index: 3
number of parameters: 2

id: 715
unit: std::pair insert_or_assign()
file: research/carls/base/async_node_hash_map.h
start line: 229
end line: 231
size: 3 LOC
McCabe index: 2
number of parameters: 2

id: 716
unit: std::pair insert_or_assign()
file: research/carls/base/async_node_hash_map.h
start line: 234
end line: 236
size: 3 LOC
McCabe index: 2
number of parameters: 2

id: 717
unit: std::pair insert_or_assign()
file: research/carls/base/async_node_hash_map.h
start line: 239
end line: 241
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 718
unit: unsigned int get_partition()
file: research/carls/base/async_node_hash_map.h
start line: 244
end line: 246
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 719
unit: def get_next_kg_actions()
file: research/a2n/graph.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 0

id: 720
unit: def get_next_kg_actions_sampled()
file: research/a2n/graph.py
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end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 0

id: 721
unit: def add_histogram_summary()
file: research/a2n/utils.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 722
unit: def source_attention_kbc_model()
file: research/a2n/models.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 0

id: 723
unit: def main()
file: research/a2n/generate_random_graph.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 724
unit: def load_from_pickle()
file: research/gam/gam/data/dataset.py
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end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 725
unit: def __init__()
file: research/gam/gam/trainer/trainer_classification.py
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end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 726
unit: def train()
file: research/gam/gam/trainer/trainer_classification.py
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end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 4

id: 727
unit: def __init__()
file: research/gam/gam/trainer/trainer_agreement.py
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end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 728
unit: def create_agreement_prediction()
file: research/gam/gam/trainer/trainer_agreement.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 4

id: 729
unit: def _hash()
file: research/multi_representation_adversary/multi_representation_adversary/evaluator.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 730
unit: def eta_scheduler()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 3
number of parameters: 2

id: 731
unit: def _select()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 732
unit: def normalize_image()
file: research/multi_representation_adversary/multi_representation_adversary/data.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 733
unit: def get_validation_dataset()
file: research/multi_representation_adversary/multi_representation_adversary/data.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 734
unit: def get_test_dataset()
file: research/multi_representation_adversary/multi_representation_adversary/data.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 735
unit: def loss_from_logits()
file: research/kg_hyp_emb/learning/losses.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 4

id: 736
unit: def loss_from_logits()
file: research/kg_hyp_emb/learning/losses.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 4

id: 737
unit: def __init__()
file: research/kg_hyp_emb/learning/regularizers.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 738
unit: def artanh()
file: research/kg_hyp_emb/utils/hyperbolic.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 739
unit: def project()
file: research/kg_hyp_emb/utils/hyperbolic.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 740
unit: def get_rhs()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 741
unit: def get_candidates()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 742
unit: def __init__()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 743
unit: def __init__()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 744
unit: def get_reflection_queries()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 745
unit: def get_rotation_queries()
file: research/kg_hyp_emb/models/euclidean.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 746
unit: def get_rhs()
file: research/kg_hyp_emb/models/hyperbolic.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 2

id: 747
unit: def get_candidates()
file: research/kg_hyp_emb/models/hyperbolic.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 1

id: 748
unit: def similarity_score()
file: research/kg_hyp_emb/models/hyperbolic.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 4

id: 749
unit: def get_reflection_queries()
file: research/kg_hyp_emb/models/hyperbolic.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 750
unit: def get_rotation_queries()
file: research/kg_hyp_emb/models/hyperbolic.py
start line: 0
end line: 0
size: 3 LOC
McCabe index: 1
number of parameters: 3

id: 751
unit: def _make_ragged()
file: neural_structured_learning/experimental/gnn.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 752
unit: def graph_call()
file: neural_structured_learning/experimental/gnn.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 753
unit: def __init__()
file: neural_structured_learning/lib/abstract_gen_neighbor.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 754
unit: def gen_neighbor()
file: neural_structured_learning/lib/abstract_gen_neighbor.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 755
unit: def _expand_to_rank()
file: neural_structured_learning/lib/utils.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 756
unit: def all()
file: neural_structured_learning/configs/configs.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 757
unit: def all()
file: neural_structured_learning/configs/configs.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 758
unit: def all()
file: neural_structured_learning/configs/configs.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 759
unit: def all()
file: neural_structured_learning/configs/configs.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 760
unit: def all()
file: neural_structured_learning/configs/configs.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 761
unit: def evaluate()
file: neural_structured_learning/keras/graph_regularization.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 762
unit: def predict()
file: neural_structured_learning/keras/graph_regularization.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 763
unit: def call()
file: neural_structured_learning/keras/adversarial_regularization.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 764
unit: def generate_single()
file: research/neural_clustering/data_generators/partition.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 765
unit: def sample()
file: research/neural_clustering/models/ncp_wrapper.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 766
unit: def sample()
file: research/neural_clustering/models/ncp_wrapper.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 767
unit: explicit MakeErrorStreamWithOutput()
file: research/carls/base/status_helper.h
start line: 51
end line: 52
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 768
unit: explicit StatusAdaptorForMacros()
file: research/carls/base/status_helper.h
start line: 159
end line: 160
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 769
unit: explicit SaveKnowledgeBankOp()
file: research/carls/kernels/io_ops.cc
start line: 80
end line: 81
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 770
unit: explicit RestoreKnowledgeBankOp()
file: research/carls/kernels/io_ops.cc
start line: 123
end line: 124
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 771
unit: explicit DynamicGaussianMemoryLookupOp()
file: research/carls/kernels/dynamic_memory_ops.cc
start line: 88
end line: 89
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 772
unit: explicit SampledLogitsLookupOp()
file: research/carls/kernels/sampled_logits_ops.cc
start line: 103
end line: 104
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 773
unit: explicit SampledLogitsLookupGradOp()
file: research/carls/kernels/sampled_logits_ops.cc
start line: 164
end line: 165
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 774
unit: explicit DynamicEmbeddingLookupOp()
file: research/carls/kernels/dynamic_embedding_ops.cc
start line: 140
end line: 141
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 775
unit: explicit DynamicEmbeddingUpdateOp()
file: research/carls/kernels/dynamic_embedding_ops.cc
start line: 187
end line: 188
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 776
unit: explicit DynamicEmbeddingLookupGradOp()
file: research/carls/kernels/dynamic_embedding_ops.cc
start line: 254
end line: 255
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 777
unit: def __init__()
file: research/carls/neighbor_cache_client.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 778
unit: def lookup()
file: research/carls/neighbor_cache_client.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 2
number of parameters: 2

id: 779
unit: def update()
file: research/carls/neighbor_cache_client.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 780
unit: def key_feature_name()
file: research/carls/neighbor_cache_client.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 781
unit: def trainable()
file: research/carls/dynamic_normalization.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 782
unit: def trainable()
file: research/carls/dynamic_normalization.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 783
unit: def variable_map()
file: research/carls/models/caml/sparse_features.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 784
unit: def __init__()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 2
number of parameters: 1

id: 785
unit: def add_to_collection()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 786
unit: def make_feed_dict()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 787
unit: def make_feed_dict()
file: research/a2n/encoders.py
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end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 788
unit: def make_feed_dict()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 789
unit: def make_feed_dict()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 790
unit: def make_feed_dict()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 791
unit: def make_feed_dict()
file: research/a2n/encoders.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 792
unit: def copy_labels()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 793
unit: def get_labels()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 794
unit: def num_train()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 795
unit: def num_val()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 796
unit: def num_test()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 797
unit: def num_unlabeled()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 798
unit: def get_indices_train()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 799
unit: def get_indices_unlabeled()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 800
unit: def get_indices_val()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 801
unit: def get_indices_test()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 802
unit: def save_to_pickle()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 803
unit: def label_samples()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 804
unit: def get_indices_train()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 805
unit: def get_indices_val()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 806
unit: def get_indices_test()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 807
unit: def get_indices_unlabeled()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 808
unit: def get_features()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 809
unit: def get_labels()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 810
unit: def get_original_labels()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 811
unit: def num_samples()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 812
unit: def num_features()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 813
unit: def features()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 814
unit: def features_shape()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 815
unit: def num_classes()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 816
unit: def num_train()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 817
unit: def num_val()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 818
unit: def num_test()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 819
unit: def num_unlabeled()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 820
unit: def copy_labels()
file: research/gam/gam/data/dataset.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 821
unit: def train()
file: research/gam/gam/trainer/trainer_base.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 822
unit: def train()
file: research/gam/gam/trainer/trainer_agreement.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 4

id: 823
unit: def train()
file: research/gam/gam/trainer/trainer_agreement.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 824
unit: def get_predictions_and_params()
file: research/gam/gam/models/models_base.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 4

id: 825
unit: def get_loss()
file: research/gam/gam/models/models_base.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 5

id: 826
unit: def normalize_predictions()
file: research/gam/gam/models/models_base.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 827
unit: def __call__()
file: research/gam/gam/models/models_base.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 828
unit: def identity()
file: research/multi_representation_adversary/multi_representation_adversary/transforms.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 829
unit: def inverse_identity()
file: research/multi_representation_adversary/multi_representation_adversary/transforms.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 830
unit: def attack()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 6

id: 831
unit: def attack()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 6

id: 832
unit: def attack()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 6

id: 833
unit: def single_rotation_config()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 834
unit: def union_rotation_config()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 835
unit: def construct_attack()
file: research/multi_representation_adversary/multi_representation_adversary/attacks.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 836
unit: def should_update()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 837
unit: def _select()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 838
unit: def _update()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 839
unit: def _select()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 840
unit: def _select()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 841
unit: def _update()
file: research/multi_representation_adversary/multi_representation_adversary/selectors.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 842
unit: def convert_to_tuples()
file: research/multi_representation_adversary/multi_representation_adversary/data.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 843
unit: def get_filters()
file: research/kg_hyp_emb/datasets/datasets.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 844
unit: def get_shape()
file: research/kg_hyp_emb/datasets/datasets.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 845
unit: def loss_from_logits()
file: research/kg_hyp_emb/learning/losses.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 4

id: 846
unit: def compute_norm()
file: research/kg_hyp_emb/learning/regularizers.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 847
unit: def get_config()
file: research/kg_hyp_emb/learning/regularizers.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 848
unit: def __call__()
file: research/kg_hyp_emb/learning/regularizers.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 849
unit: def get_config()
file: research/kg_hyp_emb/learning/regularizers.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 850
unit: def compute_norm()
file: research/kg_hyp_emb/learning/regularizers.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 851
unit: def compute_norm()
file: research/kg_hyp_emb/learning/regularizers.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 852
unit: def compute_norm()
file: research/kg_hyp_emb/learning/regularizers.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 853
unit: def compute_norm()
file: research/kg_hyp_emb/learning/regularizers.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 854
unit: def tanh()
file: research/kg_hyp_emb/utils/hyperbolic.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 855
unit: def get_rhs()
file: research/kg_hyp_emb/models/complex.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 856
unit: def get_candidates()
file: research/kg_hyp_emb/models/complex.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 857
unit: def get_queries()
file: research/kg_hyp_emb/models/base.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 858
unit: def get_rhs()
file: research/kg_hyp_emb/models/base.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 859
unit: def get_candidates()
file: research/kg_hyp_emb/models/base.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 860
unit: def similarity_score()
file: research/kg_hyp_emb/models/base.py
start line: 0
end line: 0
size: 2 LOC
McCabe index: 1
number of parameters: 4

id: 861
unit: std::string address()
file: research/carls/kbs_server_helper.h
start line: 62
end line: 62
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 862
unit: int port()
file: research/carls/kbs_server_helper.h
start line: 65
end line: 65
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 863
unit: void KbsServerHelper::WaitForTermination()
file: research/carls/kbs_server_helper.cc
start line: 155
end line: 155
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 864
unit: void KbsServerHelper::Terminate()
file: research/carls/kbs_server_helper.cc
start line: 157
end line: 157
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 865
unit: int embedding_dimension()
file: research/carls/knowledge_bank/knowledge_bank.h
start line: 86
end line: 86
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 866
unit: constexpr absl::string_view ExtensionName()
file: research/carls/base/proto_factory.h
start line: 33
end line: 33
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 867
unit: void ThreadBundle::JoinAll()
file: research/carls/base/thread_bundle.cc
start line: 69
end line: 69
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 868
unit: operator absl::Status()
file: research/carls/base/status_helper.h
start line: 62
end line: 62
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 869
unit: absl::Status GetStatus()
file: research/carls/base/status_helper.h
start line: 147
end line: 147
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 870
unit: explicit operator bool()
file: research/carls/base/status_helper.h
start line: 165
end line: 165
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 871
unit: explicit TopN()
file: research/carls/base/top_n.h
start line: 90
end line: 90
size: 1 LOC
McCabe index: 1
number of parameters: 1

id: 872
unit: size_t limit()
file: research/carls/base/top_n.h
start line: 93
end line: 93
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 873
unit: size_t size()
file: research/carls/base/top_n.h
start line: 97
end line: 97
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 874
unit: bool empty()
file: research/carls/base/top_n.h
start line: 99
end line: 99
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 875
unit: void reserve()
file: research/carls/base/top_n.h
start line: 104
end line: 104
size: 1 LOC
McCabe index: 1
number of parameters: 1

id: 876
unit: void push()
file: research/carls/base/top_n.h
start line: 111
end line: 111
size: 1 LOC
McCabe index: 1
number of parameters: 1

id: 877
unit: void push()
file: research/carls/base/top_n.h
start line: 112
end line: 112
size: 1 LOC
McCabe index: 1
number of parameters: 2

id: 878
unit: UnsortedIterator unsorted_begin()
file: research/carls/base/top_n.h
start line: 172
end line: 172
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 879
unit: UnsortedIterator unsorted_end()
file: research/carls/base/top_n.h
start line: 173
end line: 173
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 880
unit: void MakeErrorStream::CheckNotDone()
file: research/carls/base/status_helper.cc
start line: 129
end line: 129
size: 1 LOC
McCabe index: 1
number of parameters: 0

id: 881
unit: explicit TopkLookupOp()
file: research/carls/kernels/topk_ops.cc
start line: 68
end line: 68
size: 1 LOC
McCabe index: 1
number of parameters: 1

id: 882
unit: std::string DebugString()
file: research/carls/kernels/dynamic_embedding_manager_resource.h
start line: 35
end line: 35
size: 1 LOC
McCabe index: 1
number of parameters: 0