SYMBOL INDEX (463 symbols across 98 files) FILE: deepctr/contrib/rnn.py function _like_rnncell_ (line 56) | def _like_rnncell_(cell): function _transpose_batch_time (line 78) | def _transpose_batch_time(x): function _best_effort_input_batch_size (line 117) | def _best_effort_input_batch_size(flat_input): function _infer_state_dtype (line 150) | def _infer_state_dtype(explicit_dtype, state): function _rnn_step (line 191) | def _rnn_step( function _reverse_seq (line 367) | def _reverse_seq(input_seq, lengths): function dynamic_rnn (line 678) | def dynamic_rnn(cell, inputs, att_scores=None, sequence_length=None, ini... function _dynamic_rnn_loop (line 893) | def _dynamic_rnn_loop(cell, FILE: deepctr/contrib/rnn_v2.py function _like_rnncell_ (line 67) | def _like_rnncell_(cell): function _transpose_batch_time (line 89) | def _transpose_batch_time(x): function _best_effort_input_batch_size (line 144) | def _best_effort_input_batch_size(flat_input): function _infer_state_dtype (line 191) | def _infer_state_dtype(explicit_dtype, state): function _rnn_step (line 247) | def _rnn_step( function _reverse_seq (line 478) | def _reverse_seq(input_seq, lengths): function dynamic_rnn (line 802) | def dynamic_rnn(cell, inputs, att_scores=None, sequence_length=None, ini... function _dynamic_rnn_loop (line 1149) | def _dynamic_rnn_loop(cell, FILE: deepctr/contrib/utils.py class _Linear_ (line 14) | class _Linear_(object): method __init__ (line 43) | def __init__(self, method __call__ (line 124) | def __call__(self, args): class QAAttGRUCell (line 149) | class QAAttGRUCell(RNNCell): method __init__ (line 172) | def __init__(self, method state_size (line 199) | def state_size(self): method output_size (line 204) | def output_size(self): method __call__ (line 208) | def __call__(self, inputs, state, att_score): method call (line 212) | def call(self, inputs, state, att_score=None): class VecAttGRUCell (line 264) | class VecAttGRUCell(RNNCell): method __init__ (line 287) | def __init__(self, method state_size (line 314) | def state_size(self): method output_size (line 319) | def output_size(self): method __call__ (line 323) | def __call__(self, inputs, state, att_score): method call (line 327) | def call(self, inputs, state, att_score=None): FILE: deepctr/estimator/feature_column.py function linear_model (line 7) | def linear_model(features, linear_feature_columns): function get_linear_logit (line 15) | def get_linear_logit(features, linear_feature_columns, l2_reg_linear=0): function input_from_feature_columns (line 30) | def input_from_feature_columns(features, feature_columns, l2_reg_embeddi... function is_embedding (line 47) | def is_embedding(feature_column): FILE: deepctr/estimator/inputs.py function input_fn_pandas (line 4) | def input_fn_pandas(df, features, label=None, batch_size=256, num_epochs... function input_fn_tfrecord (line 22) | def input_fn_tfrecord(filenames, feature_description, label=None, batch_... FILE: deepctr/estimator/models/afm.py function AFMEstimator (line 20) | def AFMEstimator(linear_feature_columns, dnn_feature_columns, use_attent... FILE: deepctr/estimator/models/autoint.py function AutoIntEstimator (line 21) | def AutoIntEstimator(linear_feature_columns, dnn_feature_columns, att_la... FILE: deepctr/estimator/models/ccpm.py function CCPMEstimator (line 21) | def CCPMEstimator(linear_feature_columns, dnn_feature_columns, conv_kern... FILE: deepctr/estimator/models/dcn.py function DCNEstimator (line 18) | def DCNEstimator(linear_feature_columns, dnn_feature_columns, cross_num=... FILE: deepctr/estimator/models/deepfefm.py function DeepFEFMEstimator (line 21) | def DeepFEFMEstimator(linear_feature_columns, dnn_feature_columns, FILE: deepctr/estimator/models/deepfm.py function DeepFMEstimator (line 20) | def DeepFMEstimator(linear_feature_columns, dnn_feature_columns, dnn_hid... FILE: deepctr/estimator/models/fibinet.py function FiBiNETEstimator (line 20) | def FiBiNETEstimator(linear_feature_columns, dnn_feature_columns, biline... FILE: deepctr/estimator/models/fnn.py function FNNEstimator (line 17) | def FNNEstimator(linear_feature_columns, dnn_feature_columns, dnn_hidden... FILE: deepctr/estimator/models/fwfm.py function FwFMEstimator (line 22) | def FwFMEstimator(linear_feature_columns, dnn_feature_columns, dnn_hidde... FILE: deepctr/estimator/models/nfm.py function NFMEstimator (line 18) | def NFMEstimator(linear_feature_columns, dnn_feature_columns, dnn_hidden... FILE: deepctr/estimator/models/pnn.py function PNNEstimator (line 19) | def PNNEstimator(dnn_feature_columns, dnn_hidden_units=(256, 128, 64), l... FILE: deepctr/estimator/models/wdl.py function WDLEstimator (line 18) | def WDLEstimator(linear_feature_columns, dnn_feature_columns, dnn_hidden... FILE: deepctr/estimator/models/xdeepfm.py function xDeepFMEstimator (line 18) | def xDeepFMEstimator(linear_feature_columns, dnn_feature_columns, dnn_hi... FILE: deepctr/estimator/utils.py function _summary_key (line 9) | def _summary_key(head_name, val): class Head (line 13) | class Head(_Head): method __init__ (line 15) | def __init__(self, task, method name (line 21) | def name(self): method logits_dimension (line 25) | def logits_dimension(self): method _eval_metric_ops (line 28) | def _eval_metric_ops(self, method create_loss (line 73) | def create_loss(self, features, mode, logits, labels): method create_estimator_spec (line 82) | def create_estimator_spec( function deepctr_model_fn (line 121) | def deepctr_model_fn(features, mode, logits, labels, task, linear_optimi... function get_train_op_fn (line 134) | def get_train_op_fn(linear_optimizer, dnn_optimizer): function variable_scope (line 165) | def variable_scope(name_or_scope): function get_collection (line 171) | def get_collection(key, scope=None): function get_GraphKeys (line 178) | def get_GraphKeys(): function get_losses (line 185) | def get_losses(): function input_layer (line 192) | def input_layer(features, feature_columns): function get_metrics (line 199) | def get_metrics(): function to_float (line 206) | def to_float(x, name="ToFloat"): function summary_scalar (line 213) | def summary_scalar(name, data): FILE: deepctr/feature_column.py class SparseFeat (line 17) | class SparseFeat(namedtuple('SparseFeat', method __new__ (line 23) | def __new__(cls, name, vocabulary_size, embedding_dim=4, use_hash=Fals... method __hash__ (line 39) | def __hash__(self): class VarLenSparseFeat (line 43) | class VarLenSparseFeat(namedtuple('VarLenSparseFeat', method __new__ (line 47) | def __new__(cls, sparsefeat, maxlen, combiner="mean", length_name=None... method name (line 52) | def name(self): method vocabulary_size (line 56) | def vocabulary_size(self): method embedding_dim (line 60) | def embedding_dim(self): method use_hash (line 64) | def use_hash(self): method vocabulary_path (line 68) | def vocabulary_path(self): method dtype (line 72) | def dtype(self): method embeddings_initializer (line 76) | def embeddings_initializer(self): method embedding_name (line 80) | def embedding_name(self): method group_name (line 84) | def group_name(self): method trainable (line 88) | def trainable(self): method __hash__ (line 91) | def __hash__(self): class DenseFeat (line 95) | class DenseFeat(namedtuple('DenseFeat', ['name', 'dimension', 'dtype', '... method __new__ (line 108) | def __new__(cls, name, dimension=1, dtype="float32", transform_fn=None): method __hash__ (line 111) | def __hash__(self): function get_feature_names (line 123) | def get_feature_names(feature_columns): function build_input_features (line 128) | def build_input_features(feature_columns, prefix=''): function get_linear_logit (line 152) | def get_linear_logit(features, feature_columns, units=1, use_bias=False,... function input_from_feature_columns (line 194) | def input_from_feature_columns(features, feature_columns, l2_reg, seed, ... FILE: deepctr/inputs.py function get_inputs_list (line 19) | def get_inputs_list(inputs): function create_embedding_dict (line 23) | def create_embedding_dict(sparse_feature_columns, varlen_sparse_feature_... function get_embedding_vec_list (line 48) | def get_embedding_vec_list(embedding_dict, input_dict, sparse_feature_co... function create_embedding_matrix (line 63) | def create_embedding_matrix(feature_columns, l2_reg, seed, prefix="", se... function embedding_lookup (line 75) | def embedding_lookup(sparse_embedding_dict, sparse_input_dict, sparse_fe... function varlen_embedding_lookup (line 94) | def varlen_embedding_lookup(embedding_dict, sequence_input_dict, varlen_... function get_varlen_pooling_list (line 107) | def get_varlen_pooling_list(embedding_dict, features, varlen_sparse_feat... function get_dense_input (line 135) | def get_dense_input(features, feature_columns): function mergeDict (line 149) | def mergeDict(a, b): FILE: deepctr/layers/activation.py class Dice (line 28) | class Dice(Layer): method __init__ (line 46) | def __init__(self, axis=-1, epsilon=1e-9, **kwargs): method build (line 51) | def build(self, input_shape): method call (line 59) | def call(self, inputs, training=None, **kwargs): method compute_output_shape (line 66) | def compute_output_shape(self, input_shape): method get_config (line 69) | def get_config(self, ): function activation_layer (line 75) | def activation_layer(activation): FILE: deepctr/layers/core.py class LocalActivationUnit (line 28) | class LocalActivationUnit(Layer): method __init__ (line 55) | def __init__(self, hidden_units=(64, 32), activation='sigmoid', l2_reg... method build (line 66) | def build(self, input_shape): method call (line 94) | def call(self, inputs, training=None, **kwargs): method compute_output_shape (line 110) | def compute_output_shape(self, input_shape): method compute_mask (line 113) | def compute_mask(self, inputs, mask): method get_config (line 116) | def get_config(self, ): class DNN (line 123) | class DNN(Layer): method __init__ (line 148) | def __init__(self, hidden_units, activation='relu', l2_reg=0, dropout_... method build (line 160) | def build(self, input_shape): method call (line 189) | def call(self, inputs, training=None, **kwargs): method compute_output_shape (line 210) | def compute_output_shape(self, input_shape): method get_config (line 218) | def get_config(self, ): class PredictionLayer (line 226) | class PredictionLayer(Layer): method __init__ (line 234) | def __init__(self, task='binary', use_bias=True, **kwargs): method build (line 241) | def build(self, input_shape): method call (line 250) | def call(self, inputs, **kwargs): method compute_output_shape (line 261) | def compute_output_shape(self, input_shape): method get_config (line 264) | def get_config(self, ): class RegulationModule (line 270) | class RegulationModule(Layer): method __init__ (line 287) | def __init__(self, tau=1.0, **kwargs): method build (line 293) | def build(self, input_shape): method call (line 304) | def call(self, inputs, **kwargs): method compute_output_shape (line 314) | def compute_output_shape(self, input_shape): method get_config (line 317) | def get_config(self): FILE: deepctr/layers/interaction.py class AFMLayer (line 33) | class AFMLayer(Layer): method __init__ (line 59) | def __init__(self, attention_factor=4, l2_reg_w=0, dropout_rate=0, see... method build (line 66) | def build(self, input_shape): method call (line 110) | def call(self, inputs, training=None, **kwargs): method compute_output_shape (line 142) | def compute_output_shape(self, input_shape): method get_config (line 149) | def get_config(self, ): class BiInteractionPooling (line 157) | class BiInteractionPooling(Layer): method __init__ (line 171) | def __init__(self, **kwargs): method build (line 175) | def build(self, input_shape): method call (line 184) | def call(self, inputs, **kwargs): method compute_output_shape (line 199) | def compute_output_shape(self, input_shape): class CIN (line 203) | class CIN(Layer): method __init__ (line 226) | def __init__(self, layer_size=(128, 128), activation='relu', split_hal... method build (line 237) | def build(self, input_shape): method call (line 271) | def call(self, inputs, **kwargs): method compute_output_shape (line 321) | def compute_output_shape(self, input_shape): method get_config (line 329) | def get_config(self, ): class CrossNet (line 338) | class CrossNet(Layer): method __init__ (line 361) | def __init__(self, layer_num=2, parameterization='vector', l2_reg=0, s... method build (line 369) | def build(self, input_shape): method call (line 399) | def call(self, inputs, **kwargs): method get_config (line 420) | def get_config(self, ): method compute_output_shape (line 428) | def compute_output_shape(self, input_shape): class CrossNetMix (line 432) | class CrossNetMix(Layer): method __init__ (line 458) | def __init__(self, low_rank=32, num_experts=4, layer_num=2, l2_reg=0, ... method build (line 466) | def build(self, input_shape): method call (line 505) | def call(self, inputs, **kwargs): method get_config (line 545) | def get_config(self, ): method compute_output_shape (line 553) | def compute_output_shape(self, input_shape): class FM (line 557) | class FM(Layer): method __init__ (line 571) | def __init__(self, **kwargs): method build (line 575) | def build(self, input_shape): method call (line 582) | def call(self, inputs, **kwargs): method compute_output_shape (line 600) | def compute_output_shape(self, input_shape): class InnerProductLayer (line 604) | class InnerProductLayer(Layer): method __init__ (line 621) | def __init__(self, reduce_sum=True, **kwargs): method build (line 625) | def build(self, input_shape): method call (line 649) | def call(self, inputs, **kwargs): method compute_output_shape (line 674) | def compute_output_shape(self, input_shape): method get_config (line 684) | def get_config(self, ): class InteractingLayer (line 691) | class InteractingLayer(Layer): method __init__ (line 711) | def __init__(self, att_embedding_size=8, head_num=2, use_res=True, sca... method build (line 721) | def build(self, input_shape): method call (line 743) | def call(self, inputs, **kwargs): method compute_output_shape (line 775) | def compute_output_shape(self, input_shape): method get_config (line 779) | def get_config(self, ): class OutterProductLayer (line 787) | class OutterProductLayer(Layer): method __init__ (line 806) | def __init__(self, kernel_type='mat', seed=1024, **kwargs): method build (line 813) | def build(self, input_shape): method call (line 855) | def call(self, inputs, **kwargs): method compute_output_shape (line 919) | def compute_output_shape(self, input_shape): method get_config (line 924) | def get_config(self, ): class FGCNNLayer (line 931) | class FGCNNLayer(Layer): method __init__ (line 945) | def __init__(self, filters=(14, 16,), kernel_width=(7, 7,), new_maps=(... method build (line 956) | def build(self, input_shape): method call (line 988) | def call(self, inputs, **kwargs): method compute_output_shape (line 1016) | def compute_output_shape(self, input_shape): method get_config (line 1028) | def get_config(self, ): method _conv_output_shape (line 1035) | def _conv_output_shape(self, input_shape, kernel_size): method _pooling_output_shape (line 1049) | def _pooling_output_shape(self, input_shape, pool_size): class SENETLayer (line 1061) | class SENETLayer(Layer): method __init__ (line 1080) | def __init__(self, reduction_ratio=3, seed=1024, **kwargs): method build (line 1086) | def build(self, input_shape): method call (line 1107) | def call(self, inputs, training=None, **kwargs): method compute_output_shape (line 1122) | def compute_output_shape(self, input_shape): method compute_mask (line 1126) | def compute_mask(self, inputs, mask=None): method get_config (line 1129) | def get_config(self, ): class BilinearInteraction (line 1136) | class BilinearInteraction(Layer): method __init__ (line 1155) | def __init__(self, bilinear_type="interaction", seed=1024, **kwargs): method build (line 1161) | def build(self, input_shape): method call (line 1184) | def call(self, inputs, **kwargs): method compute_output_shape (line 1205) | def compute_output_shape(self, input_shape): method get_config (line 1211) | def get_config(self, ): class FieldWiseBiInteraction (line 1218) | class FieldWiseBiInteraction(Layer): method __init__ (line 1237) | def __init__(self, use_bias=True, seed=1024, **kwargs): method build (line 1243) | def build(self, input_shape): method call (line 1277) | def call(self, inputs, **kwargs): method compute_output_shape (line 1335) | def compute_output_shape(self, input_shape): method get_config (line 1338) | def get_config(self, ): class FwFMLayer (line 1345) | class FwFMLayer(Layer): method __init__ (line 1363) | def __init__(self, num_fields=4, regularizer=0.000001, **kwargs): method build (line 1368) | def build(self, input_shape): method call (line 1385) | def call(self, inputs, **kwargs): method compute_output_shape (line 1410) | def compute_output_shape(self, input_shape): method get_config (line 1413) | def get_config(self): class FEFMLayer (line 1422) | class FEFMLayer(Layer): method __init__ (line 1440) | def __init__(self, regularizer, **kwargs): method build (line 1444) | def build(self, input_shape): method call (line 1463) | def call(self, inputs, **kwargs): method compute_output_shape (line 1484) | def compute_output_shape(self, input_shape): method get_config (line 1488) | def get_config(self): class BridgeModule (line 1496) | class BridgeModule(Layer): method __init__ (line 1515) | def __init__(self, bridge_type='hadamard_product', activation='relu', ... method build (line 1521) | def build(self, input_shape): method call (line 1536) | def call(self, inputs, **kwargs): method compute_output_shape (line 1549) | def compute_output_shape(self, input_shape): method get_config (line 1552) | def get_config(self): FILE: deepctr/layers/normalization.py class LayerNormalization (line 18) | class LayerNormalization(Layer): method __init__ (line 19) | def __init__(self, axis=-1, eps=1e-9, center=True, method build (line 27) | def build(self, input_shape): method call (line 34) | def call(self, inputs): method compute_output_shape (line 45) | def compute_output_shape(self, input_shape): method get_config (line 48) | def get_config(self, ): FILE: deepctr/layers/sequence.py class SequencePoolingLayer (line 31) | class SequencePoolingLayer(Layer): method __init__ (line 50) | def __init__(self, mode='mean', supports_masking=False, **kwargs): method build (line 60) | def build(self, input_shape): method call (line 66) | def call(self, seq_value_len_list, mask=None, **kwargs): method compute_output_shape (line 98) | def compute_output_shape(self, input_shape): method compute_mask (line 104) | def compute_mask(self, inputs, mask): method get_config (line 107) | def get_config(self, ): class WeightedSequenceLayer (line 113) | class WeightedSequenceLayer(Layer): method __init__ (line 134) | def __init__(self, weight_normalization=True, supports_masking=False, ... method build (line 139) | def build(self, input_shape): method call (line 145) | def call(self, input_list, mask=None, **kwargs): method compute_output_shape (line 175) | def compute_output_shape(self, input_shape): method compute_mask (line 178) | def compute_mask(self, inputs, mask): method get_config (line 184) | def get_config(self, ): class AttentionSequencePoolingLayer (line 190) | class AttentionSequencePoolingLayer(Layer): method __init__ (line 218) | def __init__(self, att_hidden_units=(80, 40), att_activation='sigmoid'... method build (line 229) | def build(self, input_shape): method call (line 251) | def call(self, inputs, mask=None, training=None, **kwargs): method compute_output_shape (line 290) | def compute_output_shape(self, input_shape): method compute_mask (line 296) | def compute_mask(self, inputs, mask): method get_config (line 299) | def get_config(self, ): class BiLSTM (line 308) | class BiLSTM(Layer): method __init__ (line 331) | def __init__(self, units, layers=2, res_layers=0, dropout_rate=0.2, me... method build (line 347) | def build(self, input_shape): method call (line 365) | def call(self, inputs, mask=None, **kwargs): method compute_output_shape (line 401) | def compute_output_shape(self, input_shape): method compute_mask (line 410) | def compute_mask(self, inputs, mask): method get_config (line 413) | def get_config(self, ): class Transformer (line 421) | class Transformer(Layer): method __init__ (line 451) | def __init__(self, att_embedding_size=1, head_num=8, dropout_rate=0.0,... method build (line 471) | def build(self, input_shape): method call (line 513) | def call(self, inputs, mask=None, training=None, **kwargs): method compute_output_shape (line 627) | def compute_output_shape(self, input_shape): method compute_mask (line 631) | def compute_mask(self, inputs, mask=None): method get_config (line 634) | def get_config(self, ): class PositionEncoding (line 644) | class PositionEncoding(Layer): method __init__ (line 645) | def __init__(self, pos_embedding_trainable=True, method build (line 653) | def build(self, input_shape): method call (line 673) | def call(self, inputs, mask=None): method compute_output_shape (line 681) | def compute_output_shape(self, input_shape): method compute_mask (line 685) | def compute_mask(self, inputs, mask=None): method get_config (line 688) | def get_config(self, ): class BiasEncoding (line 696) | class BiasEncoding(Layer): method __init__ (line 697) | def __init__(self, sess_max_count, seed=1024, **kwargs): method build (line 702) | def build(self, input_shape): method call (line 729) | def call(self, inputs, mask=None): method compute_output_shape (line 740) | def compute_output_shape(self, input_shape): method compute_mask (line 744) | def compute_mask(self, inputs, mask=None): method get_config (line 747) | def get_config(self, ): class DynamicGRU (line 754) | class DynamicGRU(Layer): method __init__ (line 755) | def __init__(self, num_units=None, gru_type='GRU', return_sequence=Tru... method build (line 762) | def build(self, input_shape): method call (line 780) | def call(self, input_list): method compute_output_shape (line 799) | def compute_output_shape(self, input_shape): method get_config (line 806) | def get_config(self, ): class KMaxPooling (line 812) | class KMaxPooling(Layer): method __init__ (line 828) | def __init__(self, k=1, axis=-1, **kwargs): method build (line 834) | def build(self, input_shape): method call (line 847) | def call(self, inputs): method compute_output_shape (line 860) | def compute_output_shape(self, input_shape): method get_config (line 865) | def get_config(self, ): FILE: deepctr/layers/utils.py class NoMask (line 26) | class NoMask(Layer): method __init__ (line 27) | def __init__(self, **kwargs): method build (line 30) | def build(self, input_shape): method call (line 34) | def call(self, x, mask=None, **kwargs): method compute_mask (line 37) | def compute_mask(self, inputs, mask): class Hash (line 41) | class Hash(Layer): method __init__ (line 75) | def __init__(self, num_buckets, mask_zero=False, vocabulary_path=None,... method build (line 85) | def build(self, input_shape): method call (line 89) | def call(self, x, mask=None, **kwargs): method compute_output_shape (line 114) | def compute_output_shape(self, input_shape): method get_config (line 117) | def get_config(self, ): class Linear (line 124) | class Linear(Layer): method __init__ (line 126) | def __init__(self, l2_reg=0.0, mode=0, use_bias=False, seed=1024, **kw... method build (line 137) | def build(self, input_shape): method call (line 160) | def call(self, inputs, **kwargs): method compute_output_shape (line 177) | def compute_output_shape(self, input_shape): method compute_mask (line 180) | def compute_mask(self, inputs, mask): method get_config (line 183) | def get_config(self, ): class Concat (line 189) | class Concat(Layer): method __init__ (line 190) | def __init__(self, axis, supports_masking=True, **kwargs): method call (line 195) | def call(self, inputs): method compute_mask (line 198) | def compute_mask(self, inputs, mask=None): method get_config (line 230) | def get_config(self, ): function concat_func (line 236) | def concat_func(inputs, axis=-1, mask=False): function reduce_mean (line 245) | def reduce_mean(input_tensor, function reduce_sum (line 263) | def reduce_sum(input_tensor, function reduce_max (line 281) | def reduce_max(input_tensor, function div (line 299) | def div(x, y, name=None): function softmax (line 306) | def softmax(logits, dim=-1, name=None): class _Add (line 313) | class _Add(Layer): method __init__ (line 314) | def __init__(self, **kwargs): method build (line 317) | def build(self, input_shape): method call (line 321) | def call(self, inputs, **kwargs): function add_func (line 328) | def add_func(inputs): function combined_dnn_input (line 336) | def combined_dnn_input(sparse_embedding_list, dense_value_list): FILE: deepctr/models/afm.py function AFM (line 19) | def AFM(linear_feature_columns, dnn_feature_columns, fm_group=DEFAULT_GR... FILE: deepctr/models/autoint.py function AutoInt (line 21) | def AutoInt(linear_feature_columns, dnn_feature_columns, att_layer_num=3... FILE: deepctr/models/ccpm.py function CCPM (line 22) | def CCPM(linear_feature_columns, dnn_feature_columns, conv_kernel_width=... FILE: deepctr/models/dcn.py function DCN (line 22) | def DCN(linear_feature_columns, dnn_feature_columns, cross_num=2, cross_... FILE: deepctr/models/dcnmix.py function DCNMix (line 22) | def DCNMix(linear_feature_columns, dnn_feature_columns, cross_num=2, FILE: deepctr/models/deepfefm.py function DeepFEFM (line 25) | def DeepFEFM(linear_feature_columns, dnn_feature_columns, use_fefm=True, FILE: deepctr/models/deepfm.py function DeepFM (line 22) | def DeepFM(linear_feature_columns, dnn_feature_columns, fm_group=(DEFAUL... FILE: deepctr/models/difm.py function DIFM (line 20) | def DIFM(linear_feature_columns, dnn_feature_columns, FILE: deepctr/models/edcn.py function EDCN (line 18) | def EDCN(linear_feature_columns, FILE: deepctr/models/fgcnn.py function unstack (line 22) | def unstack(input_tensor): function FGCNN (line 27) | def FGCNN(linear_feature_columns, dnn_feature_columns, conv_kernel_width... FILE: deepctr/models/fibinet.py function FiBiNET (line 19) | def FiBiNET(linear_feature_columns, dnn_feature_columns, bilinear_type='... FILE: deepctr/models/flen.py function FLEN (line 22) | def FLEN(linear_feature_columns, FILE: deepctr/models/fnn.py function FNN (line 17) | def FNN(linear_feature_columns, dnn_feature_columns, dnn_hidden_units=(2... FILE: deepctr/models/fwfm.py function FwFM (line 23) | def FwFM(linear_feature_columns, dnn_feature_columns, fm_group=(DEFAULT_... FILE: deepctr/models/ifm.py function IFM (line 21) | def IFM(linear_feature_columns, dnn_feature_columns, dnn_hidden_units=(2... FILE: deepctr/models/mlr.py function MLR (line 17) | def MLR(region_feature_columns, base_feature_columns=None, region_num=4, function get_region_score (line 60) | def get_region_score(features, feature_columns, region_number, l2_reg, s... function get_learner_score (line 67) | def get_learner_score(features, feature_columns, region_number, l2_reg, ... FILE: deepctr/models/multitask/esmm.py function ESMM (line 19) | def ESMM(dnn_feature_columns, tower_dnn_hidden_units=(256, 128, 64), l2_... FILE: deepctr/models/multitask/mmoe.py function MMOE (line 20) | def MMOE(dnn_feature_columns, num_experts=3, expert_dnn_hidden_units=(25... FILE: deepctr/models/multitask/ple.py function PLE (line 20) | def PLE(dnn_feature_columns, shared_expert_num=1, specific_expert_num=1,... FILE: deepctr/models/multitask/sharedbottom.py function SharedBottom (line 19) | def SharedBottom(dnn_feature_columns, bottom_dnn_hidden_units=(256, 128)... FILE: deepctr/models/nfm.py function NFM (line 18) | def NFM(linear_feature_columns, dnn_feature_columns, dnn_hidden_units=(2... FILE: deepctr/models/onn.py function ONN (line 32) | def ONN(linear_feature_columns, dnn_feature_columns, dnn_hidden_units=(2... function feature_embedding (line 111) | def feature_embedding(fc_i, fc_j, embedding_dict, input_feature): FILE: deepctr/models/pnn.py function PNN (line 19) | def PNN(dnn_feature_columns, dnn_hidden_units=(256, 128, 64), l2_reg_emb... FILE: deepctr/models/sequence/bst.py function BST (line 21) | def BST(dnn_feature_columns, history_feature_list, transformer_num=1, at... FILE: deepctr/models/sequence/dien.py function auxiliary_loss (line 22) | def auxiliary_loss(h_states, click_seq, noclick_seq, mask, stag=None): function interest_evolution (line 66) | def interest_evolution(concat_behavior, deep_input_item, user_behavior_l... function DIEN (line 112) | def DIEN(dnn_feature_columns, history_feature_list, FILE: deepctr/models/sequence/din.py function DIN (line 20) | def DIN(dnn_feature_columns, history_feature_list, dnn_use_bn=False, FILE: deepctr/models/sequence/dsin.py function DSIN (line 26) | def DSIN(dnn_feature_columns, sess_feature_list, sess_max_count=5, bias_... function sess_interest_division (line 145) | def sess_interest_division(sparse_embedding_dict, user_behavior_input_di... function sess_interest_extractor (line 161) | def sess_interest_extractor(tr_input, sess_max_count, TR): FILE: deepctr/models/wdl.py function WDL (line 18) | def WDL(linear_feature_columns, dnn_feature_columns, dnn_hidden_units=(2... FILE: deepctr/models/xdeepfm.py function xDeepFM (line 18) | def xDeepFM(linear_feature_columns, dnn_feature_columns, dnn_hidden_unit... FILE: deepctr/utils.py function check_version (line 21) | def check_version(version): FILE: examples/gen_tfrecords.py function make_example (line 3) | def make_example(line, sparse_feature_name, dense_feature_name, label_na... function write_tfrecord (line 12) | def write_tfrecord(filename, df, sparse_feature_names, dense_feature_nam... FILE: examples/run_dien.py function get_xy_fd (line 8) | def get_xy_fd(use_neg=False, hash_flag=False): FILE: examples/run_din.py function get_xy_fd (line 7) | def get_xy_fd(): FILE: examples/run_dsin.py function get_xy_fd (line 8) | def get_xy_fd(hash_flag=False): FILE: examples/run_multivalue_movielens.py function split (line 10) | def split(x): FILE: tests/feature_test.py function test_long_dense_vector (line 6) | def test_long_dense_vector(): function test_feature_column_sparsefeat_vocabulary_path (line 23) | def test_feature_column_sparsefeat_vocabulary_path(): FILE: tests/layers/activations_test.py function test_dice (line 10) | def test_dice(): FILE: tests/layers/core_test.py function test_LocalActivationUnit (line 22) | def test_LocalActivationUnit(hidden_units, activation): function test_DNN (line 39) | def test_DNN(hidden_units, use_bn): function test_PredictionLayer (line 53) | def test_PredictionLayer(task, use_bias): function test_test_PredictionLayer_invalid (line 60) | def test_test_PredictionLayer_invalid(): FILE: tests/layers/interaction_test.py function test_FEFMLayer (line 17) | def test_FEFMLayer(): function test_FwFM (line 27) | def test_FwFM(reg_strength): function test_CrossNet (line 40) | def test_CrossNet(layer_num, ): function test_InnerProductLayer (line 59) | def test_InnerProductLayer(reduce_sum): function test_OutterProductLayer (line 71) | def test_OutterProductLayer(kernel_type): function test_BiInteractionPooling (line 77) | def test_BiInteractionPooling(): function test_FM (line 83) | def test_FM(): function test_AFMLayer (line 89) | def test_AFMLayer(): function test_CIN (line 100) | def test_CIN(layer_size, split_half): function test_InteractingLayer (line 122) | def test_InteractingLayer(head_num, use_res, ): function test_FGCNNLayer (line 129) | def test_FGCNNLayer(): function test_BilinearInteraction (line 146) | def test_BilinearInteraction(bilinear_type): FILE: tests/layers/normalization_test.py function test_LayerNormalization (line 17) | def test_LayerNormalization(axis): FILE: tests/layers/sequence_test.py function test_AttentionSequencePoolingLayer (line 30) | def test_AttentionSequencePoolingLayer(weight_normalization): function test_SequencePoolingLayer (line 46) | def test_SequencePoolingLayer(mode, supports_masking, input_shape): function test_BiLSTM (line 77) | def test_BiLSTM(merge_mode): function test_Transformer (line 88) | def test_Transformer(attention_type): function test_KMaxPooling (line 97) | def test_KMaxPooling(): function test_PositionEncoding (line 109) | def test_PositionEncoding(pos_embedding_trainable, zero_pad): FILE: tests/layers/utils_test.py function test_Hash (line 25) | def test_Hash(num_buckets, mask_zero, vocabulary_path, input_data, expec... function test_Linear (line 36) | def test_Linear(): FILE: tests/models/AFM_test.py function test_AFM (line 13) | def test_AFM(use_attention, sparse_feature_num, dense_feature_num): function test_AFMEstimator (line 29) | def test_AFMEstimator(use_attention, sparse_feature_num, dense_feature_n... FILE: tests/models/AutoInt_test.py function test_AutoInt (line 14) | def test_AutoInt(att_layer_num, dnn_hidden_units, sparse_feature_num): function test_AutoIntEstimator (line 31) | def test_AutoIntEstimator(att_layer_num, dnn_hidden_units, sparse_featur... FILE: tests/models/BST_test.py function test_BST (line 6) | def test_BST(): FILE: tests/models/CCPM_test.py function test_CCPM (line 13) | def test_CCPM(sparse_feature_num, dense_feature_num): function test_CCPM_without_seq (line 32) | def test_CCPM_without_seq(sparse_feature_num, dense_feature_num): function test_CCPMEstimator_without_seq (line 51) | def test_CCPMEstimator_without_seq(sparse_feature_num, dense_feature_num): FILE: tests/models/DCNMix_test.py function test_DCNMix (line 12) | def test_DCNMix(cross_num, hidden_size, sparse_feature_num): FILE: tests/models/DCN_test.py function test_DCN (line 13) | def test_DCN(cross_num, hidden_size, sparse_feature_num, cross_parameter... function test_DCN_2 (line 25) | def test_DCN_2(): function test_DCNEstimator (line 41) | def test_DCNEstimator(cross_num, hidden_size, sparse_feature_num): FILE: tests/models/DIEN_test.py function get_xy_fd (line 11) | def get_xy_fd(use_neg=False, hash_flag=False): function test_DIEN (line 63) | def test_DIEN(gru_type): function test_DIEN_neg (line 78) | def test_DIEN_neg(): FILE: tests/models/DIFM_test.py function test_DIFM (line 11) | def test_DIFM(att_head_num, dnn_hidden_units, sparse_feature_num): FILE: tests/models/DIN_test.py function get_xy_fd (line 10) | def get_xy_fd(hash_flag=False): function test_DIN (line 43) | def test_DIN(): FILE: tests/models/DSIN_test.py function get_xy_fd (line 9) | def get_xy_fd(hash_flag=False): function test_DSIN (line 56) | def test_DSIN(bias_encoding): FILE: tests/models/DeepFEFM_test.py function test_DeepFEFM (line 21) | def test_DeepFEFM(hidden_size, sparse_feature_num, use_fefm, use_linear,... function test_DeepFEFMEstimator (line 40) | def test_DeepFEFMEstimator(hidden_size, sparse_feature_num): FILE: tests/models/DeepFM_test.py function test_DeepFM (line 13) | def test_DeepFM(hidden_size, sparse_feature_num): function test_DeepFMEstimator (line 30) | def test_DeepFMEstimator(hidden_size, sparse_feature_num): FILE: tests/models/EDCN_test.py function test_EDCN (line 16) | def test_EDCN(bridge_type, cross_num, cross_parameterization, sparse_fea... FILE: tests/models/FGCNN_test.py function test_FGCNN (line 12) | def test_FGCNN(sparse_feature_num, dense_feature_num): FILE: tests/models/FLEN_test.py function test_FLEN (line 13) | def test_FLEN(hidden_size, sparse_feature_num): FILE: tests/models/FNN_test.py function test_FNN (line 13) | def test_FNN(sparse_feature_num, dense_feature_num): function test_FNNEstimator (line 45) | def test_FNNEstimator(sparse_feature_num, dense_feature_num): FILE: tests/models/FiBiNET_test.py function test_FiBiNET (line 12) | def test_FiBiNET(bilinear_type): function test_FiBiNETEstimator (line 26) | def test_FiBiNETEstimator(bilinear_type): FILE: tests/models/FwFM_test.py function test_FwFM (line 13) | def test_FwFM(hidden_size, sparse_feature_num): function test_FwFMEstimator (line 28) | def test_FwFMEstimator(hidden_size, sparse_feature_num): FILE: tests/models/IFM_test.py function test_IFM (line 13) | def test_IFM(hidden_size, sparse_feature_num): FILE: tests/models/MLR_test.py function test_MLRs (line 17) | def test_MLRs(region_sparse, region_dense, base_sparse, base_dense, bias... function test_MLR (line 32) | def test_MLR(): FILE: tests/models/MTL_test.py function test_SharedBottom (line 8) | def test_SharedBottom(): function test_ESMM (line 19) | def test_ESMM(): function test_MMOE (line 30) | def test_MMOE(): function test_PLE (line 48) | def test_PLE(num_levels, gate_dnn_hidden_units): FILE: tests/models/NFM_test.py function test_NFM (line 11) | def test_NFM(hidden_size, sparse_feature_num): function test_FNNEstimator (line 26) | def test_FNNEstimator(hidden_size, sparse_feature_num): FILE: tests/models/ONN_test.py function test_ONN (line 13) | def test_ONN(sparse_feature_num): FILE: tests/models/PNN_test.py function test_PNN (line 12) | def test_PNN(use_inner, use_outter, sparse_feature_num): function test_PNNEstimator (line 26) | def test_PNNEstimator(use_inner, use_outter, sparse_feature_num): FILE: tests/models/WDL_test.py function test_WDL (line 14) | def test_WDL(sparse_feature_num, dense_feature_num): function test_WDLEstimator (line 32) | def test_WDLEstimator(sparse_feature_num, dense_feature_num): FILE: tests/models/xDeepFM_test.py function test_xDeepFM (line 15) | def test_xDeepFM(dnn_hidden_units, cin_layer_size, cin_split_half, cin_a... function test_xDeepFMEstimator (line 44) | def test_xDeepFMEstimator(dnn_hidden_units, cin_layer_size, cin_split_ha... FILE: tests/utils.py function test_estimator_version (line 22) | def test_estimator_version(tf_version): function gen_sequence (line 33) | def gen_sequence(dim, max_len, sample_size): function get_test_data (line 38) | def get_test_data(sample_size=1000, embedding_size=4, sparse_feature_num... function layer_test (line 108) | def layer_test(layer_cls, kwargs=None, input_shape=None, input_dtype=None, function has_arg (line 279) | def has_arg(fn, name, accept_all=False): function check_model (line 356) | def check_model(model, model_name, x, y, check_model_io=True): function get_test_data_estimator (line 384) | def get_test_data_estimator(sample_size=1000, embedding_size=4, sparse_f... function check_estimator (line 416) | def check_estimator(model, input_fn): FILE: tests/utils_mtl.py function get_mtl_test_data (line 13) | def get_mtl_test_data(sample_size=10, embedding_size=4, sparse_feature_n... function check_mtl_model (line 58) | def check_mtl_model(model, model_name, x, y_list, task_types, check_mode... FILE: tests/utils_test.py function test_check_version (line 4) | def test_check_version():