SYMBOL INDEX (1145 symbols across 171 files)

FILE: youtube-8m-ensemble/all_ensemble_models/attention_linear_model.py
  class AttentionLinearModel (line 9) | class AttentionLinearModel(models.BaseModel):
    method create_model (line 11) | def create_model(self,

FILE: youtube-8m-ensemble/all_ensemble_models/attention_linmatrix_model.py
  class AttentionLinmatrixModel (line 9) | class AttentionLinmatrixModel(models.BaseModel):
    method create_model (line 11) | def create_model(self,

FILE: youtube-8m-ensemble/all_ensemble_models/attention_matrix_model.py
  class AttentionMatrixModel (line 9) | class AttentionMatrixModel(models.BaseModel):
    method create_model (line 11) | def create_model(self,

FILE: youtube-8m-ensemble/all_ensemble_models/attention_moe_matrix_model.py
  class AttentionMoeMatrixModel (line 9) | class AttentionMoeMatrixModel(models.BaseModel):
    method create_model (line 11) | def create_model(self,
    method relu (line 68) | def relu(self, model_input, relu_cells,

FILE: youtube-8m-ensemble/all_ensemble_models/attention_moe_model.py
  class AttentionMoeModel (line 9) | class AttentionMoeModel(models.BaseModel):
    method create_model (line 11) | def create_model(self,
    method relu (line 44) | def relu(self, model_input, relu_cells,

FILE: youtube-8m-ensemble/all_ensemble_models/attention_rectified_linear_model.py
  class AttentionRectifiedLinearModel (line 9) | class AttentionRectifiedLinearModel(models.BaseModel):
    method create_model (line 11) | def create_model(self,

FILE: youtube-8m-ensemble/all_ensemble_models/deep_combine_chain_model.py
  class DeepCombineChainModel (line 9) | class DeepCombineChainModel(models.BaseModel):
    method create_model (line 11) | def create_model(self,
    method sub_moe (line 72) | def sub_moe(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-ensemble/all_ensemble_models/input_moe_model.py
  class InputMoeModel (line 9) | class InputMoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self,

FILE: youtube-8m-ensemble/all_ensemble_models/linear_regression_model.py
  class LinearRegressionModel (line 9) | class LinearRegressionModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, origi...

FILE: youtube-8m-ensemble/all_ensemble_models/logistic_model.py
  class LogisticModel (line 9) | class LogisticModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, origi...

FILE: youtube-8m-ensemble/all_ensemble_models/matrix_regression_model.py
  class MatrixRegressionModel (line 9) | class MatrixRegressionModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, origi...

FILE: youtube-8m-ensemble/all_ensemble_models/mean_model.py
  class MeanModel (line 9) | class MeanModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, **unused_params):

FILE: youtube-8m-ensemble/all_ensemble_models/moe_model.py
  class MoeModel (line 9) | class MoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self,

FILE: youtube-8m-ensemble/all_ensemble_models/nonunit_matrix_regression_model.py
  class NonunitMatrixRegressionModel (line 9) | class NonunitMatrixRegressionModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, origi...

FILE: youtube-8m-ensemble/average_precision_calculator.py
  class AveragePrecisionCalculator (line 61) | class AveragePrecisionCalculator(object):
    method __init__ (line 64) | def __init__(self, top_n=None):
    method heap_size (line 84) | def heap_size(self):
    method num_accumulated_positives (line 89) | def num_accumulated_positives(self):
    method accumulate (line 93) | def accumulate(self, predictions, actuals, num_positives=None):
    method clear (line 134) | def clear(self):
    method peek_ap_at_n (line 139) | def peek_ap_at_n(self):
    method ap (line 158) | def ap(predictions, actuals):
    method ap_at_n (line 180) | def ap_at_n(predictions, actuals, n=20, total_num_positives=None):
    method _shuffle (line 248) | def _shuffle(predictions, actuals):
    method _zero_one_normalize (line 256) | def _zero_one_normalize(predictions, epsilon=1e-7):

FILE: youtube-8m-ensemble/check_distillation.py
  function find_class_by_name (line 48) | def find_class_by_name(name, modules):
  function get_input_evaluation_tensors (line 54) | def get_input_evaluation_tensors(reader,
  function build_graph (line 76) | def build_graph(all_readers,
  function check_loop (line 121) | def check_loop(model_input, video_id_equal, input_distance, label_distan...
  function check_video_id (line 168) | def check_video_id():
  function main (line 212) | def main(unused_argv):

FILE: youtube-8m-ensemble/check_video_id.py
  function find_class_by_name (line 61) | def find_class_by_name(name, modules):
  function get_input_evaluation_tensors (line 67) | def get_input_evaluation_tensors(reader,
  function build_graph (line 89) | def build_graph(all_readers,
  function check_loop (line 122) | def check_loop(video_id_equal, input_distance, all_patterns):
  function check_video_id (line 166) | def check_video_id():
  function main (line 208) | def main(unused_argv):

FILE: youtube-8m-ensemble/check_video_id_match.py
  function find_class_by_name (line 61) | def find_class_by_name(name, modules):
  function get_input_evaluation_tensors (line 67) | def get_input_evaluation_tensors(reader,
  function build_graph (line 89) | def build_graph(all_readers,
  function check_loop (line 124) | def check_loop(video_id_mismatch, input_distance, actual_batch_size, all...
  function check_video_id (line 184) | def check_video_id():
  function main (line 229) | def main(unused_argv):

FILE: youtube-8m-ensemble/eval.py
  function find_class_by_name (line 61) | def find_class_by_name(name, modules):
  function get_input_evaluation_tensors (line 67) | def get_input_evaluation_tensors(reader,
  function build_graph (line 89) | def build_graph(all_readers,
  function evaluation_loop (line 158) | def evaluation_loop(video_id_batch, prediction_batch, label_batch, loss,
  function evaluate (line 258) | def evaluate():
  function main (line 318) | def main(unused_argv):

FILE: youtube-8m-ensemble/eval_util.py
  function flatten (line 24) | def flatten(l):
  function calculate_hit_at_one (line 28) | def calculate_hit_at_one(predictions, actuals):
  function calculate_recall_at_n (line 45) | def calculate_recall_at_n(predictions, actuals, n):
  function calculate_precision_at_equal_recall_rate (line 74) | def calculate_precision_at_equal_recall_rate(predictions, actuals):
  function calculate_gap (line 102) | def calculate_gap(predictions, actuals, top_k=20):
  function top_k_by_class (line 123) | def top_k_by_class(predictions, labels, k=20):
  function top_k_triplets (line 159) | def top_k_triplets(predictions, labels, k=20):
  class EvaluationMetrics (line 167) | class EvaluationMetrics(object):
    method __init__ (line 170) | def __init__(self, num_class, top_k):
    method accumulate (line 189) | def accumulate(self, predictions, labels, loss):
    method get (line 223) | def get(self):
    method clear (line 247) | def clear(self):

FILE: youtube-8m-ensemble/inference-combine-tfrecords-frame.py
  function find_class_by_name (line 59) | def find_class_by_name(name, modules):
  function get_input_data_tensors (line 64) | def get_input_data_tensors(reader,
  function build_graph (line 84) | def build_graph(input_reader, input_data_pattern,
  function inference_loop (line 118) | def inference_loop(video_ids_batch, labels_batch, rgbs_batch, audios_bat...
  function write_to_record (line 236) | def write_to_record(video_ids, video_labels, video_rgbs, video_audios, v...
  function get_output_feature (line 250) | def get_output_feature(video_id, video_label, video_rgb, video_audio, vi...
  function main (line 265) | def main(unused_argv):

FILE: youtube-8m-ensemble/inference-combine-tfrecords-video.py
  function find_class_by_name (line 56) | def find_class_by_name(name, modules):
  function get_input_data_tensors (line 61) | def get_input_data_tensors(reader,
  function build_graph (line 81) | def build_graph(input_reader, input_data_pattern,
  function inference_loop (line 118) | def inference_loop(video_ids_batch, labels_batch, inputs_batch, predicti...
  function write_to_record (line 219) | def write_to_record(video_ids, video_labels, video_inputs, video_predict...
  function get_output_feature (line 231) | def get_output_feature(video_id, video_label, video_input, video_predict...
  function main (line 262) | def main(unused_argv):

FILE: youtube-8m-ensemble/inference-pre-ensemble.py
  function find_class_by_name (line 64) | def find_class_by_name(name, modules):
  function get_input_data_tensors (line 69) | def get_input_data_tensors(reader,
  function build_graph (line 89) | def build_graph(all_readers,
  function inference_loop (line 155) | def inference_loop(video_id_batch, prediction_batch,
  function write_to_record (line 255) | def write_to_record(video_ids, video_labels, video_features, filenum, nu...
  function get_output_feature (line 265) | def get_output_feature(video_id, video_label, video_feature, feature_nam...
  function main (line 274) | def main(unused_argv):

FILE: youtube-8m-ensemble/inference.py
  function format_lines (line 58) | def format_lines(video_ids, predictions, top_k):
  function find_class_by_name (line 69) | def find_class_by_name(name, modules):
  function get_input_data_tensors (line 75) | def get_input_data_tensors(reader,
  function build_graph (line 96) | def build_graph(all_readers,
  function inference_loop (line 155) | def inference_loop(video_id_batch, prediction_batch, label_batch,
  function inference (line 209) | def inference():
  function main (line 257) | def main(unused_argv):

FILE: youtube-8m-ensemble/losses.py
  function smoothing (line 46) | def smoothing(labels):
  class BaseLoss (line 56) | class BaseLoss(object):
    method calculate_loss (line 59) | def calculate_loss(self, unused_predictions, unused_labels, **unused_p...
  class CrossEntropyLoss (line 76) | class CrossEntropyLoss(BaseLoss):
    method calculate_loss (line 80) | def calculate_loss(self, predictions, labels, weights=None, **unused_p...
  class HingeLoss (line 98) | class HingeLoss(BaseLoss):
    method calculate_loss (line 106) | def calculate_loss(self, predictions, labels, b=1.0, **unused_params):
  class SoftmaxLoss (line 116) | class SoftmaxLoss(BaseLoss):
    method calculate_loss (line 128) | def calculate_loss(self, predictions, labels, **unused_params):
  class MultiTaskLoss (line 142) | class MultiTaskLoss(BaseLoss):
    method calculate_loss (line 145) | def calculate_loss(self, unused_predictions, unused_labels, **unused_p...
    method get_support (line 148) | def get_support(self, labels, support_type=None):
  class MultiTaskCrossEntropyLoss (line 185) | class MultiTaskCrossEntropyLoss(MultiTaskLoss):
    method calculate_loss (line 188) | def calculate_loss(self, predictions, support_predictions, labels, **u...

FILE: youtube-8m-ensemble/mean_average_precision_calculator.py
  class MeanAveragePrecisionCalculator (line 44) | class MeanAveragePrecisionCalculator(object):
    method __init__ (line 48) | def __init__(self, num_class):
    method accumulate (line 71) | def accumulate(self, predictions, actuals, num_positives=None):
    method clear (line 95) | def clear(self):
    method is_empty (line 99) | def is_empty(self):
    method peek_map_at_n (line 103) | def peek_map_at_n(self):

FILE: youtube-8m-ensemble/model_utils.py
  function SampleRandomSequence (line 23) | def SampleRandomSequence(model_input, num_frames, num_samples):
  function SampleRandomFrames (line 51) | def SampleRandomFrames(model_input, num_frames, num_samples):
  function FramePooling (line 72) | def FramePooling(frames, method, **unused_params):

FILE: youtube-8m-ensemble/models.py
  class BaseModel (line 17) | class BaseModel(object):
    method create_model (line 20) | def create_model(self, unused_model_input, **unused_params):

FILE: youtube-8m-ensemble/readers.py
  function resize_axis (line 23) | def resize_axis(tensor, axis, new_size, fill_value=0):
  class BaseReader (line 44) | class BaseReader(object):
    method prepare_reader (line 47) | def prepare_reader(self, unused_filename_queue):
  class EnsembleReader (line 52) | class EnsembleReader(BaseReader):
    method __init__ (line 54) | def __init__(self,
    method prepare_reader (line 67) | def prepare_reader(self, filename_queue, batch_size=1024):
  class EnsembleFrameReader (line 93) | class EnsembleFrameReader(BaseReader):
    method __init__ (line 95) | def __init__(self,
    method get_video_matrix (line 110) | def get_video_matrix(self,
    method prepare_reader (line 120) | def prepare_reader(self, filename_queue):

FILE: youtube-8m-ensemble/train.py
  function get_input_data_tensors (line 113) | def get_input_data_tensors(reader,
  function find_class_by_name (line 137) | def find_class_by_name(name, modules):
  function get_video_weights_array (line 142) | def get_video_weights_array():
  function optional_assign_weights (line 148) | def optional_assign_weights(sess, weights_input, weights_assignment):
  function get_video_weights (line 156) | def get_video_weights(video_id_batch):
  function build_graph (line 175) | def build_graph(all_readers,
  class Trainer (line 353) | class Trainer(object):
    method __init__ (line 356) | def __init__(self, cluster, task, train_dir, log_device_placement=True):
    method run (line 375) | def run(self, start_new_model=False):
    method start_server_if_distributed (line 488) | def start_server_if_distributed(self):
    method remove_training_directory (line 505) | def remove_training_directory(self, train_dir):
    method get_meta_filename (line 518) | def get_meta_filename(self, start_new_model, train_dir):
    method recover_model (line 538) | def recover_model(self, meta_filename):
    method build_model (line 543) | def build_model(self):
  class ParameterServer (line 591) | class ParameterServer(object):
    method __init__ (line 594) | def __init__(self, cluster, task):
    method run (line 606) | def run(self):
  function start_server (line 615) | def start_server(cluster, task):
  function task_as_string (line 638) | def task_as_string(task):
  function main (line 641) | def main(unused_argv):

FILE: youtube-8m-ensemble/utils.py
  function Dequantize (line 23) | def Dequantize(feat_vector, max_quantized_value=2, min_quantized_value=-2):
  function MakeSummary (line 41) | def MakeSummary(name, value):
  function AddGlobalStepSummary (line 50) | def AddGlobalStepSummary(summary_writer,
  function AddEpochSummary (line 94) | def AddEpochSummary(summary_writer,
  function GetListOfFeatureNamesAndSizes (line 140) | def GetListOfFeatureNamesAndSizes(feature_names, feature_sizes):
  function clip_gradient_norms (line 164) | def clip_gradient_norms(gradients_to_variables, max_norm):

FILE: youtube-8m-wangheda/all_data_augmentation/clipping_augmenter.py
  class ClippingAugmenter (line 6) | class ClippingAugmenter:
    method augment (line 8) | def augment(self, model_input_raw, num_frames, labels_batch, **unused_...

FILE: youtube-8m-wangheda/all_data_augmentation/default_augmenter.py
  class DefaultAugmenter (line 6) | class DefaultAugmenter:
    method augment (line 8) | def augment(self, model_input_raw, num_frames, labels_batch, **unused_...

FILE: youtube-8m-wangheda/all_data_augmentation/half_augmenter.py
  class HalfAugmenter (line 6) | class HalfAugmenter:
    method augment (line 8) | def augment(self, model_input_raw, num_frames, labels_batch, **unused_...

FILE: youtube-8m-wangheda/all_data_augmentation/half_video_augmenter.py
  class HalfVideoAugmenter (line 6) | class HalfVideoAugmenter:
    method augment (line 8) | def augment(self, model_input_raw, num_frames, labels_batch, **unused_...
    method frame_augment (line 19) | def frame_augment(self, model_input_raw, num_frames, labels_batch, **u...

FILE: youtube-8m-wangheda/all_data_augmentation/noise_augmenter.py
  class NoiseAugmenter (line 6) | class NoiseAugmenter:
    method augment (line 8) | def augment(self, model_input_raw, num_frames, labels_batch, **unused_...

FILE: youtube-8m-wangheda/all_feature_transform/avg_transformer.py
  class AvgTransformer (line 3) | class AvgTransformer:
    method transform (line 4) | def transform(self, model_input_raw, num_frames, **unused_params):

FILE: youtube-8m-wangheda/all_feature_transform/default_transformer.py
  class DefaultTransformer (line 4) | class DefaultTransformer:
    method transform (line 5) | def transform(self, model_input_raw, num_frames, **unused_params):

FILE: youtube-8m-wangheda/all_feature_transform/engineer_transformer.py
  class EngineerTransformer (line 7) | class EngineerTransformer:
    method transform (line 9) | def transform(self, model_input_raw, num_frames, **unused_params):
    method mask (line 26) | def mask(self, model_input_raw, num_frames):
    method avg (line 41) | def avg(self, model_input_raw, num_frames, mask):
    method std (line 51) | def std(self, model_input_raw, num_frames, mask):
    method diff (line 56) | def diff(self, model_input_raw, num_frames, mask):

FILE: youtube-8m-wangheda/all_feature_transform/identical_transformer.py
  class IdenticalTransformer (line 4) | class IdenticalTransformer:
    method transform (line 5) | def transform(self, model_input_raw, num_frames, **unused_params):

FILE: youtube-8m-wangheda/all_feature_transform/resolution_transformer.py
  class ResolutionTransformer (line 6) | class ResolutionTransformer:
    method resolution (line 7) | def resolution(self, model_input_raw, num_frames):
    method transform (line 25) | def transform(self, model_input_raw, num_frames, **unused_params):

FILE: youtube-8m-wangheda/all_frame_models/bilstm_model.py
  class BiLstmModel (line 13) | class BiLstmModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/biunilstm_model.py
  class BiUniLstmModel (line 13) | class BiUniLstmModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/cnn_deep_combine_chain_model.py
  class CnnDeepCombineChainModel (line 10) | class CnnDeepCombineChainModel(models.BaseModel):
    method cnn (line 13) | def cnn(self,
    method create_model (line 42) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method sub_model (line 90) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_mask (line 121) | def get_mask(self, max_frames, num_frames):

FILE: youtube-8m-wangheda/all_frame_models/cnn_kmax_model.py
  class CnnKmaxModel (line 13) | class CnnKmaxModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...

FILE: youtube-8m-wangheda/all_frame_models/cnn_lstm_memory_model.py
  class CnnLstmMemoryModel (line 13) | class CnnLstmMemoryModel(models.BaseModel):
    method cnn (line 15) | def cnn(self,
    method create_model (line 42) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/cnn_lstm_memory_multitask_model.py
  class CnnLstmMemoryMultiTaskModel (line 13) | class CnnLstmMemoryMultiTaskModel(models.BaseModel):
    method cnn (line 15) | def cnn(self,
    method create_model (line 42) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
    method get_mask (line 105) | def get_mask(self, max_frames, num_frames):

FILE: youtube-8m-wangheda/all_frame_models/cnn_lstm_memory_normalization_model.py
  class CnnLstmMemoryNormalizationModel (line 13) | class CnnLstmMemoryNormalizationModel(models.BaseModel):
    method cnn (line 15) | def cnn(self,
    method create_model (line 43) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
    method layer_normalize (line 85) | def layer_normalize(self, input_raw, epsilon=1e-8):
    method l2_normalize (line 93) | def l2_normalize(self, input_raw, epsilon=1e-8):
    method identical (line 98) | def identical(self, input_raw, epsilon=1e-8):

FILE: youtube-8m-wangheda/all_frame_models/cnn_model.py
  class CnnModel (line 10) | class CnnModel(models.BaseModel):
    method cnn (line 13) | def cnn(self,
    method create_model (line 42) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method sub_model (line 54) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_frame_models/dbof_model.py
  class DbofModel (line 13) | class DbofModel(models.BaseModel):
    method create_model (line 36) | def create_model(self,

FILE: youtube-8m-wangheda/all_frame_models/deep_cnn_deep_combine_chain_model.py
  class DeepCnnDeepCombineChainModel (line 10) | class DeepCnnDeepCombineChainModel(models.BaseModel):
    method cnn (line 13) | def cnn(self,
    method deep_cnn (line 42) | def deep_cnn(self,
    method create_model (line 65) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method sub_model (line 124) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_mask (line 160) | def get_mask(self, max_frames, num_frames):

FILE: youtube-8m-wangheda/all_frame_models/deep_lstm_model.py
  class DeepLstmModel (line 13) | class DeepLstmModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/distillchain_cnn_deep_combine_chain_model.py
  class DistillchainCnnDeepCombineChainModel (line 10) | class DistillchainCnnDeepCombineChainModel(models.BaseModel):
    method cnn (line 13) | def cnn(self,
    method create_model (line 42) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method sub_model (line 105) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_mask (line 136) | def get_mask(self, max_frames, num_frames):

FILE: youtube-8m-wangheda/all_frame_models/distillchain_lstm_attention_max_pooling_model.py
  class DistillchainLstmAttentionMaxPoolingModel (line 10) | class DistillchainLstmAttentionMaxPoolingModel(models.BaseModel):
    method create_model (line 13) | def create_model(self, model_input, vocab_size, num_frames,
    method sub_moe (line 87) | def sub_moe(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_frame_models/distillchain_lstm_cnn_deep_combine_chain_model.py
  class DistillchainLstmCnnDeepCombineChainModel (line 10) | class DistillchainLstmCnnDeepCombineChainModel(models.BaseModel):
    method cnn (line 13) | def cnn(self,
    method create_model (line 42) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method sub_model (line 110) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_mask (line 141) | def get_mask(self, max_frames, num_frames):
    method lstmoutput (line 156) | def lstmoutput(self, model_input, vocab_size, num_frames):

FILE: youtube-8m-wangheda/all_frame_models/distillchain_lstm_memory_deep_combine_chain_model.py
  class DistillchainLstmMemoryDeepCombineChainModel (line 13) | class DistillchainLstmMemoryDeepCombineChainModel(models.BaseModel):
    method create_model (line 16) | def create_model(self, model_input, vocab_size, num_frames,
    method sub_lstm (line 82) | def sub_lstm(self, model_input, num_frames, lstm_size, number_of_layer...
    method sub_moe (line 100) | def sub_moe(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_frame_models/distillchain_lstm_parallel_finaloutput_model.py
  class DistillchainLstmParallelFinaloutputModel (line 13) | class DistillchainLstmParallelFinaloutputModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames,

FILE: youtube-8m-wangheda/all_frame_models/distillchain_multiscale_cnn_lstm_model.py
  class DistillchainMultiscaleCnnLstmModel (line 10) | class DistillchainMultiscaleCnnLstmModel(models.BaseModel):
    method cnn (line 12) | def cnn(self,
    method moe (line 47) | def moe(self,model_input,
    method rnn (line 86) | def rnn(self, model_input, lstm_size, num_frames,
    method create_model (line 99) | def create_model(self, model_input, vocab_size, num_frames,

FILE: youtube-8m-wangheda/all_frame_models/frame_seg_model.py
  class FrameSegModel (line 13) | class FrameSegModel(models.BaseModel):
    method create_model (line 15) | def create_model(self,
    method frame_mean (line 49) | def frame_mean(self, model_input, frame_start,

FILE: youtube-8m-wangheda/all_frame_models/framehop_lstm_memory_deep_combine_chain_model.py
  class FramehopLstmMemoryDeepCombineChainModel (line 13) | class FramehopLstmMemoryDeepCombineChainModel(models.BaseModel):
    method lstm (line 16) | def lstm(self, model_input, vocab_size, num_frames, sub_scope="",
    method create_model (line 59) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 114) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_length_code (line 151) | def get_length_code(self, num_frames):
    method resolution (line 161) | def resolution(self, model_input_raw, num_frames, resolution, method="...

FILE: youtube-8m-wangheda/all_frame_models/framehop_lstm_memory_model.py
  class FramehopLstmMemoryModel (line 13) | class FramehopLstmMemoryModel(models.BaseModel):
    method lstm (line 16) | def lstm(self, model_input, vocab_size, num_frames, sub_scope="",
    method create_model (line 59) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method get_length_code (line 96) | def get_length_code(self, num_frames):
    method resolution (line 106) | def resolution(self, model_input_raw, num_frames, resolution, method="...

FILE: youtube-8m-wangheda/all_frame_models/gru_pooling_model.py
  class GruPoolingModel (line 13) | class GruPoolingModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/gru_with_pooling_model.py
  class GruWithPoolingModel (line 13) | class GruWithPoolingModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/layernorm_lstm_memory_model.py
  class LayerNormLstmMemoryModel (line 13) | class LayerNormLstmMemoryModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames,

FILE: youtube-8m-wangheda/all_frame_models/logistic_model.py
  class FrameLevelLogisticModel (line 13) | class FrameLevelLogisticModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_advanced_model.py
  class LstmAdvancedModel (line 13) | class LstmAdvancedModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_attention_lstm_model.py
  class LstmAttentionLstmModel (line 13) | class LstmAttentionLstmModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_attention_max_pooling_model.py
  class LstmAttentionMaxPoolingModel (line 10) | class LstmAttentionMaxPoolingModel(models.BaseModel):
    method create_model (line 13) | def create_model(self, model_input, vocab_size, num_frames,
    method sub_moe (line 70) | def sub_moe(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_frame_models/lstm_attention_model.py
  class LstmAttentionModel (line 13) | class LstmAttentionModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_auxloss_deep_combine_chain_model.py
  class LstmAuxlossDeepCombineChainModel (line 13) | class LstmAuxlossDeepCombineChainModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method sub_model (line 100) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_frame_models/lstm_cnn_deep_combine_chain_model.py
  class LstmCnnDeepCombineChainModel (line 10) | class LstmCnnDeepCombineChainModel(models.BaseModel):
    method cnn (line 13) | def cnn(self,
    method create_model (line 42) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method sub_model (line 94) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_mask (line 125) | def get_mask(self, max_frames, num_frames):
    method lstmoutput (line 140) | def lstmoutput(self, model_input, vocab_size, num_frames):

FILE: youtube-8m-wangheda/all_frame_models/lstm_divided_model.py
  class LstmDividedModel (line 13) | class LstmDividedModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_look_back_model.py
  class LstmLookBackModel (line 13) | class LstmLookBackModel(models.BaseModel):
    method shift (line 15) | def shift(self,
    method create_model (line 32) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_memory_chain_model.py
  class LstmMemoryChainModel (line 13) | class LstmMemoryChainModel(models.BaseModel):
    method create_model (line 16) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_memory_deep_chain_model.py
  class LstmMemoryDeepChainModel (line 13) | class LstmMemoryDeepChainModel(models.BaseModel):
    method create_model (line 16) | def create_model(self, model_input, vocab_size, num_frames,
    method sub_lstm (line 57) | def sub_lstm(self, model_input, num_frames, lstm_size, number_of_layer...
    method sub_moe (line 75) | def sub_moe(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_frame_models/lstm_memory_input_chain_model.py
  class LstmMemoryInputChainModel (line 13) | class LstmMemoryInputChainModel(models.BaseModel):
    method create_model (line 16) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...

FILE: youtube-8m-wangheda/all_frame_models/lstm_memory_model.py
  class LstmMemoryModel (line 13) | class LstmMemoryModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames,

FILE: youtube-8m-wangheda/all_frame_models/lstm_memory_multitask_model.py
  class LstmMemoryMultitaskModel (line 13) | class LstmMemoryMultitaskModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_memory_normalization_model.py
  class LstmMemoryNormalizationModel (line 13) | class LstmMemoryNormalizationModel(models.BaseModel):
    method create_model (line 16) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
    method layer_normalize (line 57) | def layer_normalize(self, input_raw, epsilon=1e-8):
    method l2_normalize (line 65) | def l2_normalize(self, input_raw, epsilon=1e-8):
    method identical (line 70) | def identical(self, input_raw, epsilon=1e-8):

FILE: youtube-8m-wangheda/all_frame_models/lstm_memory_parallel_chain_model.py
  class LstmMemoryParallelChainModel (line 13) | class LstmMemoryParallelChainModel(models.BaseModel):
    method create_model (line 16) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_model.py
  class LstmModel (line 13) | class LstmModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_multi_attention_model.py
  class LstmMultiAttentionModel (line 13) | class LstmMultiAttentionModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_multi_pooling_model.py
  class LstmMultiPoolingModel (line 13) | class LstmMultiPoolingModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_parallel_finaloutput_model.py
  class LstmParallelFinaloutputModel (line 13) | class LstmParallelFinaloutputModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_parallel_memory_model.py
  class LstmParallelMemoryModel (line 13) | class LstmParallelMemoryModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_parallel_model.py
  class LstmParallelModel (line 13) | class LstmParallelModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_pooling_model.py
  class LstmPoolingModel (line 13) | class LstmPoolingModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_positional_attention_max_pooling_model.py
  class LstmPositionalAttentionMaxPoolingModel (line 10) | class LstmPositionalAttentionMaxPoolingModel(models.BaseModel):
    method create_model (line 13) | def create_model(self, model_input, vocab_size, num_frames,
    method get_positional_embedding (line 73) | def get_positional_embedding(self, model_input, num_frames, l2_penalty...
    method get_mean_input (line 82) | def get_mean_input(self, model_input, num_frames):
    method sub_moe (line 89) | def sub_moe(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_frame_models/lstm_with_mean_input_model.py
  class LstmWithMeanInputModel (line 13) | class LstmWithMeanInputModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/lstm_with_pooling_model.py
  class LstmWithPoolingModel (line 13) | class LstmWithPoolingModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/mm_lstm_memory_model.py
  class MatchingMatrixLstmMemoryModel (line 13) | class MatchingMatrixLstmMemoryModel(models.BaseModel):
    method matching_matrix (line 15) | def matching_matrix(self,
    method create_model (line 50) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/multi_view_cnn_deep_combine_chain_model.py
  class MultiViewCnnDeepCombineChainModel (line 10) | class MultiViewCnnDeepCombineChainModel(models.BaseModel):
    method cnn (line 12) | def cnn(self,
    method create_model (line 41) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method multiview (line 89) | def multiview(self, cnn_output, axis=1):
    method sub_model (line 96) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_mask (line 127) | def get_mask(self, max_frames, num_frames):

FILE: youtube-8m-wangheda/all_frame_models/multires_lstm_memory_deep_combine_chain_model.py
  class MultiresLstmMemoryDeepCombineChainModel (line 13) | class MultiresLstmMemoryDeepCombineChainModel(models.BaseModel):
    method lstm (line 16) | def lstm(self, model_input, vocab_size, num_frames, sub_scope="", **un...
    method create_model (line 48) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 102) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_length_code (line 139) | def get_length_code(self, num_frames):
    method resolution (line 149) | def resolution(self, model_input_raw, num_frames, resolution):

FILE: youtube-8m-wangheda/all_frame_models/multiscale_cnn_lstm_model.py
  class MultiscaleCnnLstmModel (line 10) | class MultiscaleCnnLstmModel(models.BaseModel):
    method cnn (line 12) | def cnn(self,
    method moe (line 47) | def moe(self,model_input,
    method rnn (line 86) | def rnn(self, model_input, lstm_size, num_frames,
    method create_model (line 99) | def create_model(self, model_input, vocab_size, num_frames,

FILE: youtube-8m-wangheda/all_frame_models/positional_cnn_deep_combine_chain_model.py
  class PositionalCnnDeepCombineChainModel (line 10) | class PositionalCnnDeepCombineChainModel(models.BaseModel):
    method cnn (line 13) | def cnn(self,
    method add_positional_embedding (line 42) | def add_positional_embedding(self, model_input, num_frames, l2_penalty...
    method gated_linear_unit (line 52) | def gated_linear_unit(self, input1, input2):
    method create_model (line 55) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method sub_model (line 112) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_mask (line 143) | def get_mask(self, max_frames, num_frames):

FILE: youtube-8m-wangheda/all_frame_models/progressive_attention_lstm_model.py
  class ProgressiveAttentionLstmModel (line 13) | class ProgressiveAttentionLstmModel(models.BaseModel):
    method create_model (line 15) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...

FILE: youtube-8m-wangheda/all_frame_models/wide_and_deep_model.py
  class WideAndDeepModel (line 14) | class WideAndDeepModel(models.BaseModel):
    method create_model (line 16) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...

FILE: youtube-8m-wangheda/all_video_models/chain_main_relu_moe_model.py
  class ChainMainReluMoeModel (line 9) | class ChainMainReluMoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 27) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/chain_moe_model.py
  class ChainMoeModel (line 9) | class ChainMoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 20) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/chain_support_relu_moe_model.py
  class ChainSupportReluMoeModel (line 9) | class ChainSupportReluMoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 27) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/deep_chain_model.py
  class DeepChainModel (line 9) | class DeepChainModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 40) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_length_code (line 71) | def get_length_code(self, num_frames):

FILE: youtube-8m-wangheda/all_video_models/deep_combine_chain_model.py
  class DeepCombineChainModel (line 9) | class DeepCombineChainModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 51) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/distillchain_deep_combine_chain_model.py
  class DistillchainDeepCombineChainModel (line 9) | class DistillchainDeepCombineChainModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 62) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/hidden_chain_model.py
  class HiddenChainModel (line 9) | class HiddenChainModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 35) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/hidden_combine_chain_model.py
  class HiddenCombineChainModel (line 9) | class HiddenCombineChainModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 35) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/logistic_model.py
  class LogisticModel (line 9) | class LogisticModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, origi...

FILE: youtube-8m-wangheda/all_video_models/mlp_moe_model.py
  class MlpMoeModel (line 9) | class MlpMoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self,

FILE: youtube-8m-wangheda/all_video_models/moe_model.py
  class MoeModel (line 9) | class MoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self,

FILE: youtube-8m-wangheda/all_video_models/multitask_divergence_deep_combine_chain_model.py
  class MultiTaskDivergenceDeepCombineChainModel (line 9) | class MultiTaskDivergenceDeepCombineChainModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_chain_model (line 29) | def sub_chain_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 82) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/multitask_divergence_moe_model.py
  class MultiTaskDivergenceMoeModel (line 9) | class MultiTaskDivergenceMoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 29) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/multitask_moe_model.py
  class MultiTaskMoeModel (line 9) | class MultiTaskMoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 19) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/shortcut_chain_support_relu_moe_model.py
  class ShortcutChainSupportReluMoeModel (line 9) | class ShortcutChainSupportReluMoeModel(models.BaseModel):
    method create_model (line 12) | def create_model(self, model_input, vocab_size, num_mixtures=None,
    method sub_model (line 28) | def sub_model(self, model_input, vocab_size, num_mixtures=None,

FILE: youtube-8m-wangheda/all_video_models/stage2_logistic_model.py
  class Stage2LogisticModel (line 9) | class Stage2LogisticModel(models.BaseModel):
    method create_model (line 10) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, origi...

FILE: youtube-8m-wangheda/average_precision_calculator.py
  class AveragePrecisionCalculator (line 61) | class AveragePrecisionCalculator(object):
    method __init__ (line 64) | def __init__(self, top_n=None):
    method heap_size (line 84) | def heap_size(self):
    method num_accumulated_positives (line 89) | def num_accumulated_positives(self):
    method accumulate (line 93) | def accumulate(self, predictions, actuals, num_positives=None):
    method clear (line 134) | def clear(self):
    method peek_ap_at_n (line 139) | def peek_ap_at_n(self):
    method ap (line 158) | def ap(predictions, actuals):
    method ap_at_n (line 180) | def ap_at_n(predictions, actuals, n=20, total_num_positives=None):
    method _shuffle (line 248) | def _shuffle(predictions, actuals):
    method _zero_one_normalize (line 256) | def _zero_one_normalize(predictions, epsilon=1e-7):

FILE: youtube-8m-wangheda/eval.py
  function find_class_by_name (line 87) | def find_class_by_name(name, modules):
  function get_input_evaluation_tensors (line 93) | def get_input_evaluation_tensors(reader,
  function build_graph (line 115) | def build_graph(reader,
  function evaluation_loop (line 208) | def evaluation_loop(video_id_batch, prediction_batch, label_batch, loss,
  function evaluate (line 325) | def evaluate():
  function main (line 387) | def main(unused_argv):

FILE: youtube-8m-wangheda/eval_util.py
  function flatten (line 24) | def flatten(l):
  function calculate_hit_at_one (line 28) | def calculate_hit_at_one(predictions, actuals):
  function calculate_recall_at_n (line 45) | def calculate_recall_at_n(predictions, actuals, n):
  function calculate_precision_at_equal_recall_rate (line 74) | def calculate_precision_at_equal_recall_rate(predictions, actuals):
  function calculate_gap (line 102) | def calculate_gap(predictions, actuals, top_k=20):
  function top_k_by_class (line 123) | def top_k_by_class(predictions, labels, k=20):
  function top_k_triplets (line 159) | def top_k_triplets(predictions, labels, k=20):
  class EvaluationMetrics (line 167) | class EvaluationMetrics(object):
    method __init__ (line 170) | def __init__(self, num_class, top_k):
    method accumulate (line 189) | def accumulate(self, predictions, labels, loss):
    method get (line 223) | def get(self):
    method clear (line 247) | def clear(self):

FILE: youtube-8m-wangheda/inference-layer.py
  function format_lines (line 74) | def format_lines(video_ids, predictions, top_k):
  function get_input_data_tensors (line 88) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function get_output_feature (line 123) | def get_output_feature(video_id, labels, feature_dict):
  function write_to_record (line 132) | def write_to_record(id_batch, label_batch, feature_dict, filenum, num_ex...
  function inference (line 143) | def inference(reader, train_dir, data_pattern, out_file_location, batch_...
  function main (line 225) | def main(unused_argv):

FILE: youtube-8m-wangheda/inference-pre-ensemble-get-input.py
  function get_input_data_tensors (line 134) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function inference (line 170) | def inference(reader, model_checkpoint_path, data_pattern, out_file_loca...
  function write_to_record (line 242) | def write_to_record(id_batch, label_batch, input_batch, filenum, num_exa...
  function get_output_feature (line 252) | def get_output_feature(video_id, labels, features, feature_names):
  function main (line 261) | def main(unused_argv):

FILE: youtube-8m-wangheda/inference-pre-ensemble-with-predictions.py
  function find_class_by_name (line 91) | def find_class_by_name(name, modules):
  function get_input_data_tensors (line 96) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function build_graph (line 132) | def build_graph(reader,
  function inference (line 212) | def inference(saver, model_checkpoint_path, out_file_location, batch_siz...
  function write_to_record (line 300) | def write_to_record(id_batch, label_batch, predictions, filenum, num_exa...
  function get_output_feature (line 310) | def get_output_feature(video_id, labels, features, feature_names):
  function main (line 319) | def main(unused_argv):

FILE: youtube-8m-wangheda/inference-pre-ensemble.py
  function find_class_by_name (line 91) | def find_class_by_name(name, modules):
  function get_input_data_tensors (line 96) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function build_graph (line 132) | def build_graph(reader,
  function inference (line 203) | def inference(saver, model_checkpoint_path, out_file_location, batch_siz...
  function write_to_record (line 291) | def write_to_record(id_batch, label_batch, predictions, filenum, num_exa...
  function get_output_feature (line 301) | def get_output_feature(video_id, labels, features, feature_names):
  function main (line 310) | def main(unused_argv):

FILE: youtube-8m-wangheda/inference-sample-error-analysis.py
  function format_lines (line 74) | def format_lines(video_ids, predictions, labels, top_k):
  function get_input_data_tensors (line 99) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function inference (line 134) | def inference(reader, train_dir, data_pattern, out_file_location, batch_...
  function main (line 199) | def main(unused_argv):

FILE: youtube-8m-wangheda/inference-sample-error.py
  function find_class_by_name (line 85) | def find_class_by_name(name, modules):
  function format_lines (line 90) | def format_lines(video_ids, predictions, labels):
  function get_input_data_tensors (line 100) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function build_graph (line 137) | def build_graph(reader,
  function inference (line 193) | def inference(saver, train_dir, out_file_location, batch_size, top_k):
  function main (line 258) | def main(unused_argv):

FILE: youtube-8m-wangheda/inference-stage1.py
  function format_lines (line 72) | def format_lines(video_ids, predictions, top_k):
  function get_input_data_tensors (line 86) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function get_output_feature (line 121) | def get_output_feature(video_id, labels, feature_dict):
  function write_to_record (line 130) | def write_to_record(id_batch, label_batch, feature_dict, filenum, num_ex...
  function inference (line 141) | def inference(reader, train_dir, data_pattern, out_file_location, batch_...
  function main (line 222) | def main(unused_argv):

FILE: youtube-8m-wangheda/inference.py
  function format_lines (line 76) | def format_lines(video_ids, predictions, top_k):
  function get_input_data_tensors (line 90) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function inference (line 125) | def inference(reader, train_dir, data_pattern, out_file_location, batch_...
  function main (line 190) | def main(unused_argv):

FILE: youtube-8m-wangheda/losses.py
  function smoothing (line 46) | def smoothing(labels):
  class BaseLoss (line 56) | class BaseLoss(object):
    method calculate_loss (line 59) | def calculate_loss(self, unused_predictions, unused_labels, **unused_p...
  class WeightedCrossEntropyLoss (line 76) | class WeightedCrossEntropyLoss(BaseLoss):
    method calculate_loss (line 81) | def calculate_loss(self, predictions, labels, **unused_params):
  class MeanSquareErrorLoss (line 96) | class MeanSquareErrorLoss(BaseLoss):
    method calculate_loss (line 100) | def calculate_loss(self, predictions, labels, **unused_params):
  class CrossEntropyLoss (line 110) | class CrossEntropyLoss(BaseLoss):
    method calculate_loss (line 114) | def calculate_loss(self, predictions, labels, weights=None, **unused_p...
  class HingeLoss (line 132) | class HingeLoss(BaseLoss):
    method calculate_loss (line 140) | def calculate_loss(self, predictions, labels, b=1.0, **unused_params):
  class PairwiseHingeLoss (line 150) | class PairwiseHingeLoss(BaseLoss):
    method calculate_loss (line 151) | def calculate_loss(self, predictions, labels, margin=0.2, adaptive=3.0...
  class MixedLoss (line 182) | class MixedLoss(BaseLoss):
    method calculate_loss (line 183) | def calculate_loss(self, predictions, labels, margin=0.2, adaptive=3, ...
  class SoftmaxLoss (line 190) | class SoftmaxLoss(BaseLoss):
    method calculate_loss (line 202) | def calculate_loss(self, predictions, labels, **unused_params):
  class MultiTaskLoss (line 216) | class MultiTaskLoss(BaseLoss):
    method calculate_loss (line 219) | def calculate_loss(self, unused_predictions, unused_labels, **unused_p...
    method get_support (line 222) | def get_support(self, labels, support_type=None):
  class MultiTaskCrossEntropyAndSoftmaxLoss (line 260) | class MultiTaskCrossEntropyAndSoftmaxLoss(MultiTaskLoss):
    method calculate_loss (line 263) | def calculate_loss(self, predictions, support_predictions, labels, **u...
  class MultiTaskCrossEntropyLoss (line 271) | class MultiTaskCrossEntropyLoss(MultiTaskLoss):
    method calculate_loss (line 274) | def calculate_loss(self, predictions, support_predictions, labels, **u...
  class BatchAgreementCrossEntropyLoss (line 281) | class BatchAgreementCrossEntropyLoss(BaseLoss):
    method calculate_loss (line 284) | def calculate_loss(self, predictions, labels, **unused_params):
  class TopKBatchAgreementCrossEntropyLoss (line 322) | class TopKBatchAgreementCrossEntropyLoss(BaseLoss):
    method calculate_loss (line 325) | def calculate_loss(self, predictions, labels, topk=20, **unused_params):
  class MultiTaskDivergenceCrossEntropyLoss (line 358) | class MultiTaskDivergenceCrossEntropyLoss(MultiTaskLoss):
    method calculate_loss (line 361) | def calculate_loss(self, predictions, support_predictions, labels, **u...
  class MultiTaskDivergenceCrossEntropyAndMSELoss (line 386) | class MultiTaskDivergenceCrossEntropyAndMSELoss(MultiTaskLoss):
    method calculate_loss (line 389) | def calculate_loss(self, predictions, support_predictions, labels, **u...

FILE: youtube-8m-wangheda/mean_average_precision_calculator.py
  class MeanAveragePrecisionCalculator (line 44) | class MeanAveragePrecisionCalculator(object):
    method __init__ (line 48) | def __init__(self, num_class):
    method accumulate (line 71) | def accumulate(self, predictions, actuals, num_positives=None):
    method clear (line 95) | def clear(self):
    method is_empty (line 99) | def is_empty(self):
    method peek_map_at_n (line 103) | def peek_map_at_n(self):

FILE: youtube-8m-wangheda/model_utils.py
  function SampleRandomSequence (line 23) | def SampleRandomSequence(model_input, num_frames, num_samples):
  function SampleRandomFrames (line 51) | def SampleRandomFrames(model_input, num_frames, num_samples):
  function FramePooling (line 72) | def FramePooling(frames, method, **unused_params):

FILE: youtube-8m-wangheda/models.py
  class BaseModel (line 17) | class BaseModel(object):
    method create_model (line 20) | def create_model(self, unused_model_input, **unused_params):

FILE: youtube-8m-wangheda/readers.py
  function resize_axis (line 21) | def resize_axis(tensor, axis, new_size, fill_value=0):
  class BaseReader (line 58) | class BaseReader(object):
    method prepare_reader (line 61) | def prepare_reader(self, unused_filename_queue):
  class YT8MAggregatedFeatureReader (line 66) | class YT8MAggregatedFeatureReader(BaseReader):
    method __init__ (line 74) | def __init__(self,
    method prepare_reader (line 94) | def prepare_reader(self, filename_queue, batch_size=1024):
  class YT8MFrameFeatureReader (line 127) | class YT8MFrameFeatureReader(BaseReader):
    method __init__ (line 136) | def __init__(self,
    method get_video_matrix (line 159) | def get_video_matrix(self,
    method prepare_reader (line 189) | def prepare_reader(self,
  class YT8MAggregatedDistillationFeatureReader (line 261) | class YT8MAggregatedDistillationFeatureReader(BaseReader):
    method __init__ (line 269) | def __init__(self,
    method prepare_reader (line 289) | def prepare_reader(self, filename_queue, batch_size=1024):
  class YT8MFrameDistillationFeatureReader (line 323) | class YT8MFrameDistillationFeatureReader(BaseReader):
    method __init__ (line 332) | def __init__(self,
    method get_video_matrix (line 355) | def get_video_matrix(self,
    method prepare_reader (line 385) | def prepare_reader(self,

FILE: youtube-8m-wangheda/train-with-predictions.py
  function validate_class_name (line 138) | def validate_class_name(flag_value, category, modules, expected_supercla...
  function get_input_data_tensors (line 166) | def get_input_data_tensors(reader,
  function find_class_by_name (line 208) | def find_class_by_name(name, modules):
  function get_video_weights_array (line 213) | def get_video_weights_array():
  function optional_assign_weights (line 219) | def optional_assign_weights(sess, weights_input, weights_assignment):
  function get_video_weights (line 227) | def get_video_weights(video_id_batch):
  function build_graph (line 246) | def build_graph(reader,
  class Trainer (line 480) | class Trainer(object):
    method __init__ (line 483) | def __init__(self, cluster, task, train_dir, log_device_placement=True):
    method run (line 502) | def run(self, start_new_model=False):
    method start_server_if_distributed (line 622) | def start_server_if_distributed(self):
    method remove_training_directory (line 639) | def remove_training_directory(self, train_dir):
    method get_meta_filename (line 652) | def get_meta_filename(self, start_new_model, train_dir):
    method recover_model (line 672) | def recover_model(self, meta_filename):
    method build_model (line 677) | def build_model(self):
  class ParameterServer (line 739) | class ParameterServer(object):
    method __init__ (line 742) | def __init__(self, cluster, task):
    method run (line 754) | def run(self):
  function start_server (line 763) | def start_server(cluster, task):
  function task_as_string (line 786) | def task_as_string(task):
  function main (line 789) | def main(unused_argv):

FILE: youtube-8m-wangheda/train-with-rebuild.py
  function validate_class_name (line 133) | def validate_class_name(flag_value, category, modules, expected_supercla...
  function get_input_data_tensors (line 161) | def get_input_data_tensors(reader,
  function find_class_by_name (line 206) | def find_class_by_name(name, modules):
  function get_video_weights_array (line 211) | def get_video_weights_array():
  function optional_assign_weights (line 217) | def optional_assign_weights(sess, weights_input, weights_assignment):
  function get_video_weights (line 225) | def get_video_weights(video_id_batch):
  function build_graph (line 244) | def build_graph(reader,
  class Trainer (line 451) | class Trainer(object):
    method __init__ (line 454) | def __init__(self, cluster, task, train_dir, log_device_placement=True):
    method run (line 473) | def run(self, start_new_model=False):
    method start_server_if_distributed (line 592) | def start_server_if_distributed(self):
    method remove_training_directory (line 609) | def remove_training_directory(self, train_dir):
    method get_latest_checkpoint (line 622) | def get_latest_checkpoint(self, start_new_model, train_dir):
    method build_model (line 636) | def build_model(self):
  class ParameterServer (line 687) | class ParameterServer(object):
    method __init__ (line 690) | def __init__(self, cluster, task):
    method run (line 702) | def run(self):
  function start_server (line 711) | def start_server(cluster, task):
  function task_as_string (line 734) | def task_as_string(task):
  function main (line 737) | def main(unused_argv):

FILE: youtube-8m-wangheda/train.py
  function validate_class_name (line 139) | def validate_class_name(flag_value, category, modules, expected_supercla...
  function get_input_data_tensors (line 167) | def get_input_data_tensors(reader,
  function find_class_by_name (line 212) | def find_class_by_name(name, modules):
  function get_video_weights_array (line 217) | def get_video_weights_array():
  function optional_assign_weights (line 223) | def optional_assign_weights(sess, weights_input, weights_assignment):
  function get_video_weights (line 231) | def get_video_weights(video_id_batch):
  function get_weights_by_predictions (line 250) | def get_weights_by_predictions(labels_batch, predictions):
  function build_graph (line 262) | def build_graph(reader,
  class Trainer (line 482) | class Trainer(object):
    method __init__ (line 485) | def __init__(self, cluster, task, train_dir, log_device_placement=True):
    method run (line 504) | def run(self, start_new_model=False):
    method start_server_if_distributed (line 624) | def start_server_if_distributed(self):
    method remove_training_directory (line 641) | def remove_training_directory(self, train_dir):
    method get_meta_filename (line 654) | def get_meta_filename(self, start_new_model, train_dir):
    method recover_model (line 674) | def recover_model(self, meta_filename):
    method build_model (line 679) | def build_model(self):
  class ParameterServer (line 731) | class ParameterServer(object):
    method __init__ (line 734) | def __init__(self, cluster, task):
    method run (line 746) | def run(self):
  function start_server (line 755) | def start_server(cluster, task):
  function task_as_string (line 778) | def task_as_string(task):
  function main (line 781) | def main(unused_argv):

FILE: youtube-8m-wangheda/training_utils/human_readable_error_analysis.py
  function csv_line (line 13) | def csv_line(str_list):

FILE: youtube-8m-wangheda/utils.py
  function Dequantize (line 23) | def Dequantize(feat_vector, max_quantized_value=2, min_quantized_value=-2):
  function MakeSummary (line 41) | def MakeSummary(name, value):
  function AddGlobalStepSummary (line 50) | def AddGlobalStepSummary(summary_writer,
  function AddEpochSummary (line 94) | def AddEpochSummary(summary_writer,
  function GetListOfFeatureNamesAndSizes (line 140) | def GetListOfFeatureNamesAndSizes(feature_names, feature_sizes):
  function clip_gradient_norms (line 164) | def clip_gradient_norms(gradients_to_variables, max_norm):

FILE: youtube-8m-zhangteng/YM_framemean.py
  function get_frame_input_feature (line 15) | def get_frame_input_feature(input_file):
  function get_video_input_feature (line 42) | def get_video_input_feature(input_file):
  function get_output_files (line 59) | def get_output_files(features, feature_names):
  function get_output_feature (line 67) | def get_output_feature(video_id, labels, features, feature_names):
  function read_batch_files (line 76) | def read_batch_files(q,files):
  class myThread (line 123) | class myThread(threading.Thread):
    method __init__ (line 124) | def __init__(self, threadID, name, files, q):
    method run (line 130) | def run(self):
  function main (line 135) | def main():

FILE: youtube-8m-zhangteng/YM_labels_matrix.py
  function get_frame_input_feature (line 12) | def get_frame_input_feature(input_file):
  function get_video_input_feature (line 39) | def get_video_input_feature(input_file):
  function get_output_feature (line 57) | def get_output_feature(video_id, labels, features, feature_names):
  function main (line 66) | def main():

FILE: youtube-8m-zhangteng/YM_labels_model.py
  function main (line 10) | def main():

FILE: youtube-8m-zhangteng/YM_labels_vocab.py
  function main (line 10) | def main():

FILE: youtube-8m-zhangteng/YM_readframefeature.py
  function get_frame_input_feature (line 12) | def get_frame_input_feature(input_file):
  function get_video_input_feature (line 40) | def get_video_input_feature(input_file):
  function get_output_feature (line 57) | def get_output_feature(video_id, labels, features, feature_names):
  function main (line 66) | def main():

FILE: youtube-8m-zhangteng/average_precision_calculator.py
  class AveragePrecisionCalculator (line 61) | class AveragePrecisionCalculator(object):
    method __init__ (line 64) | def __init__(self, top_n=None):
    method heap_size (line 84) | def heap_size(self):
    method num_accumulated_positives (line 89) | def num_accumulated_positives(self):
    method accumulate (line 93) | def accumulate(self, predictions, actuals, num_positives=None):
    method clear (line 134) | def clear(self):
    method peek_ap_at_n (line 139) | def peek_ap_at_n(self):
    method ap (line 158) | def ap(predictions, actuals):
    method ap_at_n (line 180) | def ap_at_n(predictions, actuals, n=20, total_num_positives=None):
    method _shuffle (line 248) | def _shuffle(predictions, actuals):
    method _zero_one_normalize (line 256) | def _zero_one_normalize(predictions, epsilon=1e-7):

FILE: youtube-8m-zhangteng/eval.py
  function find_class_by_name (line 80) | def find_class_by_name(name, modules):
  function get_input_evaluation_tensors (line 86) | def get_input_evaluation_tensors(reader,
  function build_graph (line 125) | def build_graph(reader,
  function evaluation_loop (line 183) | def evaluation_loop(video_id_batch, prediction_batch, label_batch, loss,
  function evaluate (line 289) | def evaluate():
  function main (line 341) | def main(unused_argv):

FILE: youtube-8m-zhangteng/eval_autoencoder.py
  function find_class_by_name (line 74) | def find_class_by_name(name, modules):
  function get_input_evaluation_tensors (line 80) | def get_input_evaluation_tensors(reader,
  function build_graph (line 119) | def build_graph(reader,
  function evaluation_loop (line 168) | def evaluation_loop(video_id_batch, prediction_batch, label_batch, loss,
  function evaluate (line 273) | def evaluate():
  function main (line 325) | def main(unused_argv):

FILE: youtube-8m-zhangteng/eval_distill.py
  function find_class_by_name (line 90) | def find_class_by_name(name, modules):
  function get_input_evaluation_tensors (line 96) | def get_input_evaluation_tensors(reader,
  function build_graph (line 134) | def build_graph(reader1,
  function evaluation_loop (line 202) | def evaluation_loop(video_id_batch, unused_id_batch, prediction_batch, l...
  function evaluate (line 326) | def evaluate():
  function main (line 385) | def main(unused_argv):

FILE: youtube-8m-zhangteng/eval_embedding.py
  function find_class_by_name (line 75) | def find_class_by_name(name, modules):
  function get_input_evaluation_tensors (line 81) | def get_input_evaluation_tensors(reader,
  function build_graph (line 120) | def build_graph(reader,
  function evaluation_loop (line 169) | def evaluation_loop(video_id_batch, prediction_batch, label_batch, loss,
  function evaluate (line 274) | def evaluate():
  function main (line 326) | def main(unused_argv):

FILE: youtube-8m-zhangteng/eval_util.py
  function flatten (line 24) | def flatten(l):
  function calculate_hit_at_one (line 28) | def calculate_hit_at_one(predictions, actuals):
  function calculate_precision_at_equal_recall_rate (line 45) | def calculate_precision_at_equal_recall_rate(predictions, actuals):
  function calculate_gap (line 72) | def calculate_gap(predictions, actuals, top_k=20):
  function top_k_by_class (line 93) | def top_k_by_class(predictions, labels, k=20):
  function top_k_triplets (line 129) | def top_k_triplets(predictions, labels, k=20):
  class EvaluationMetrics (line 137) | class EvaluationMetrics(object):
    method __init__ (line 140) | def __init__(self, num_class, top_k):
    method accumulate (line 159) | def accumulate(self, predictions, labels, loss):
    method get (line 193) | def get(self):
    method clear (line 217) | def clear(self):

FILE: youtube-8m-zhangteng/frame_level_models.py
  class FrameLevelLogisticModel (line 60) | class FrameLevelLogisticModel(models.BaseModel):
    method create_model (line 62) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class DbofModel (line 96) | class DbofModel(models.BaseModel):
    method create_model (line 119) | def create_model(self,
  class Dbof3mModel (line 208) | class Dbof3mModel(models.BaseModel):
    method sub_moe (line 230) | def sub_moe(self,
    method create_model (line 269) | def create_model(self,
  class batch_norm (line 299) | class batch_norm(object):
    method __init__ (line 301) | def __init__(self, epsilon=1e-5, momentum=0.99, name="batch_norm"):
    method __call__ (line 309) | def __call__(self, x, train=True):
  class LstmVisionModel (line 336) | class LstmVisionModel(models.BaseModel):
    method create_model (line 339) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_recurrent_unit (line 398) | def create_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
  class LstmGluModel (line 466) | class LstmGluModel(models.BaseModel):
    method create_model (line 469) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_recurrent_unit (line 530) | def create_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
  class LstmGlu2Model (line 631) | class LstmGlu2Model(models.BaseModel):
    method create_model (line 634) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_recurrent_unit (line 695) | def create_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
  class LstmGlu2MultilayerModel (line 794) | class LstmGlu2MultilayerModel(models.BaseModel):
    method create_model (line 797) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method rnn_gate (line 826) | def rnn_gate(self, model_input, lstm_size, num_frames, l2_penalty=1e-8...
  class LstmBigluModel (line 887) | class LstmBigluModel(models.BaseModel):
    method create_model (line 890) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_forward_recurrent_unit (line 975) | def create_forward_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
    method create_backward_recurrent_unit (line 1034) | def create_backward_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
    method sub_moe (line 1104) | def sub_moe(self,model_input,
  class LstmBiglu2Model (line 1160) | class LstmBiglu2Model(models.BaseModel):
    method create_model (line 1163) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_forward_recurrent_unit (line 1255) | def create_forward_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
    method create_backward_recurrent_unit (line 1354) | def create_backward_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
    method sub_moe (line 1465) | def sub_moe(self,model_input,
  class LstmGateModel (line 1521) | class LstmGateModel(models.BaseModel):
    method create_model (line 1524) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_recurrent_unit (line 1583) | def create_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
  class LstmGateMultilayerModel (line 1642) | class LstmGateMultilayerModel(models.BaseModel):
    method create_model (line 1645) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method rnn_gate (line 1674) | def rnn_gate(self, model_input, lstm_size, num_frames, l2_penalty=1e-8...
    method create_recurrent_unit (line 1733) | def create_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
  class LstmQuickMemoryModel (line 1792) | class LstmQuickMemoryModel(models.BaseModel):
    method create_model (line 1795) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_recurrent_unit (line 1847) | def create_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
  class LstmLinearOutputModel (line 1948) | class LstmLinearOutputModel(models.BaseModel):
    method create_model (line 1951) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_recurrent_unit (line 2010) | def create_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
  class LstmLinearOutput2Model (line 2069) | class LstmLinearOutput2Model(models.BaseModel):
    method create_model (line 2072) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_recurrent_unit (line 2131) | def create_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
  class LstmNoOutputModel (line 2190) | class LstmNoOutputModel(models.BaseModel):
    method create_model (line 2193) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
    method create_recurrent_unit (line 2252) | def create_recurrent_unit(self,emb_dim,hidden_dim,l2_penalty):
  class LstmModel (line 2299) | class LstmModel(models.BaseModel):
    method create_model (line 2301) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmDiffModel (line 2341) | class LstmDiffModel(models.BaseModel):
    method create_model (line 2343) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmFramesModel (line 2396) | class LstmFramesModel(models.BaseModel):
    method sub_moe (line 2398) | def sub_moe(self,model_input,
    method calculate_loss (line 2455) | def calculate_loss(self, predictions, labels, **unused_params):
    method create_model (line 2465) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmFrames2Model (line 2536) | class LstmFrames2Model(models.BaseModel):
    method sub_moe (line 2538) | def sub_moe(self,model_input,
    method calculate_loss (line 2594) | def calculate_loss(self, predictions, labels, **unused_params):
    method create_model (line 2604) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmFrames3Model (line 2678) | class LstmFrames3Model(models.BaseModel):
    method sub_moe (line 2680) | def sub_moe(self,model_input,
    method create_model (line 2737) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmMultiscaleModel (line 2827) | class LstmMultiscaleModel(models.BaseModel):
    method cnn (line 2829) | def cnn(self,
    method sub_moe (line 2864) | def sub_moe(self,model_input,
    method rnn (line 2920) | def rnn(self, model_input, lstm_size, num_frames,sub_scope="", **unuse...
    method create_model (line 2953) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class LstmMultiscaleDitillChainModel (line 2988) | class LstmMultiscaleDitillChainModel(models.BaseModel):
    method cnn (line 2990) | def cnn(self,
    method sub_moe (line 3025) | def sub_moe(self,model_input,
    method rnn (line 3090) | def rnn(self, model_input, lstm_size, num_frames,sub_scope="", **unuse...
    method create_model (line 3123) | def create_model(self, model_input, vocab_size, num_frames, distill_la...
  class LstmMultiscale2Model (line 3160) | class LstmMultiscale2Model(models.BaseModel):
    method cnn (line 3162) | def cnn(self,
    method sub_moe (line 3197) | def sub_moe(self,model_input,
    method rnn_gate (line 3254) | def rnn_gate(self, model_input, lstm_size, num_frames, l2_penalty=1e-8...
    method rnn_standard (line 3306) | def rnn_standard(self, model_input, lstm_size, num_frames,sub_scope=""...
    method create_model (line 3340) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class LstmMultiscale3Model (line 3375) | class LstmMultiscale3Model(models.BaseModel):
    method cnn (line 3377) | def cnn(self,
    method sub_moe (line 3412) | def sub_moe(self,model_input,
    method rnn_glu (line 3469) | def rnn_glu(self, model_input, lstm_size, num_frames, l2_penalty=1e-8,...
    method rnn_standard (line 3523) | def rnn_standard(self, model_input, lstm_size, num_frames,sub_scope=""...
    method create_model (line 3557) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class LstmMultiscaleRebuildModel (line 3592) | class LstmMultiscaleRebuildModel(models.BaseModel):
    method create_model (line 3594) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class LstmLayerModel (line 3629) | class LstmLayerModel(models.BaseModel):
    method create_model (line 3631) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmDivideModel (line 3685) | class LstmDivideModel(models.BaseModel):
    method create_model (line 3687) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmDivideRebuildModel (line 3756) | class LstmDivideRebuildModel(models.BaseModel):
    method create_model (line 3758) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmDivideRebuild2Model (line 3801) | class LstmDivideRebuild2Model(models.BaseModel):
    method create_model (line 3803) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmResidualModel (line 3878) | class LstmResidualModel(models.BaseModel):
    method create_model (line 3882) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmNoiseModel (line 3925) | class LstmNoiseModel(models.BaseModel):
    method create_model (line 3927) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmConditionModel (line 3971) | class LstmConditionModel(models.BaseModel):
    method create_model (line 3973) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmRandomModel (line 4017) | class LstmRandomModel(models.BaseModel):
    method create_model (line 4019) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class LstmAttentionModel (line 4081) | class LstmAttentionModel(models.BaseModel):
    method create_model (line 4083) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmAutoencoderModel (line 4203) | class LstmAutoencoderModel(models.BaseModel):
    method create_model (line 4205) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmSoftmaxModel (line 4271) | class LstmSoftmaxModel(models.BaseModel):
    method create_model (line 4273) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class AttentionModel (line 4355) | class AttentionModel(models.BaseModel):
    method create_model (line 4357) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class CnnGluModel (line 4407) | class CnnGluModel(models.BaseModel):
    method cnn (line 4408) | def cnn(self,
    method kmax (line 4454) | def kmax(self,
    method sub_moe (line 4486) | def sub_moe(self,
    method create_model (line 4543) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class CnnLstmModel (line 4574) | class CnnLstmModel(models.BaseModel):
    method create_model (line 4576) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class CnnKmaxModel (line 4661) | class CnnKmaxModel(models.BaseModel):
    method cnn (line 4663) | def cnn(self,
    method sub_moe (line 4699) | def sub_moe(self,
    method create_model (line 4756) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class CnnKmaxRebuildModel (line 4789) | class CnnKmaxRebuildModel(models.BaseModel):
    method create_model (line 4791) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class CnnWholeModel (line 4822) | class CnnWholeModel(models.BaseModel):
    method cnn (line 4824) | def cnn(self,
    method sub_moe (line 4872) | def sub_moe(self,
    method create_model (line 4929) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class CnnMultiscaleModel (line 4936) | class CnnMultiscaleModel(models.BaseModel):
    method cnn (line 4938) | def cnn(self,
    method sub_moe (line 4978) | def sub_moe(self,
    method create_model (line 5035) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class DeepCnnModel (line 5068) | class DeepCnnModel(models.BaseModel):
    method highway (line 5070) | def highway(self, input_1, input_2, size_1, size_2, l2_penalty=1e-8, l...
    method conv_block (line 5089) | def conv_block(self, input, out_size, layer, kernalsize=3, l2_penalty=...
    method create_model (line 5113) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class LstmExtendModel (line 5169) | class LstmExtendModel(models.BaseModel):
    method create_model (line 5171) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmExtendStateModel (line 5236) | class LstmExtendStateModel(models.BaseModel):
    method cnn (line 5237) | def cnn(self,
    method create_model (line 5266) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmExtendInputModel (line 5336) | class LstmExtendInputModel(models.BaseModel):
    method create_model (line 5338) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmExtendCNNModel (line 5403) | class LstmExtendCNNModel(models.BaseModel):
    method cnn (line 5405) | def cnn(self,
    method create_model (line 5434) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmExtendOrthoModel (line 5503) | class LstmExtendOrthoModel(models.BaseModel):
    method create_model (line 5505) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmGateExtendModel (line 5574) | class LstmGateExtendModel(models.BaseModel):
    method rnn_gate (line 5576) | def rnn_gate(self, model_input, lstm_size, num_frames, l2_penalty=1e-8...
    method create_model (line 5625) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class LstmGluExtendModel (line 5675) | class LstmGluExtendModel(models.BaseModel):
    method rnn_gate (line 5677) | def rnn_gate(self, model_input, lstm_size, num_frames, l2_penalty=1e-8...
    method create_model (line 5728) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmExtendParallelModel (line 5778) | class LstmExtendParallelModel(models.BaseModel):
    method create_model (line 5780) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmExtendCombineModel (line 5852) | class LstmExtendCombineModel(models.BaseModel):
    method create_model (line 5854) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class LstmMoeModel (line 5926) | class LstmMoeModel(models.BaseModel):
    method create_model (line 5928) | def create_model(self, model_input, vocab_size, num_frames, l2_penalty...
  class InputExtendModel (line 5995) | class InputExtendModel(models.BaseModel):
    method create_model (line 5997) | def create_model(self, model_input, vocab_size, num_frames,l2_penalty=...
  class VideoFrameEvalModel (line 6076) | class VideoFrameEvalModel(models.BaseModel):
    method create_model (line 6078) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class FrameAttentionEvalModel (line 6133) | class FrameAttentionEvalModel(models.BaseModel):
    method create_model (line 6135) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class FrameRandomEvalModel (line 6182) | class FrameRandomEvalModel(models.BaseModel):
    method create_model (line 6184) | def create_model(self, model_input, vocab_size, num_frames, **unused_p...
  class CnnDCCDistillChainModel (line 6249) | class CnnDCCDistillChainModel(models.BaseModel):
    method cnn (line 6252) | def cnn(self,
    method create_model (line 6281) | def create_model(self, model_input, vocab_size, num_frames, num_mixtur...
    method sub_model (line 6331) | def sub_model(self, model_input, vocab_size, num_mixtures=None,
    method get_mask (line 6371) | def get_mask(self, max_frames, num_frames):

FILE: youtube-8m-zhangteng/inference-pre-ensemble-distill.py
  function find_class_by_name (line 91) | def find_class_by_name(name, modules):
  function get_input_data_tensors (line 96) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function build_graph (line 132) | def build_graph(reader1,
  function inference (line 197) | def inference(video_id_batch, prediction_batch, label_batch, saver, out_...
  function write_to_record (line 286) | def write_to_record(id_batch, label_batch, predictions, filenum, num_exa...
  function get_output_feature (line 296) | def get_output_feature(video_id, labels, features,feature_names):
  function main (line 305) | def main(unused_argv):

FILE: youtube-8m-zhangteng/inference-pre-ensemble.py
  function get_input_data_tensors (line 69) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function inference (line 105) | def inference(reader, model_checkpoint_path, data_pattern, out_file_loca...
  function write_to_record (line 195) | def write_to_record(id_batch, label_batch, input_batch, predictions, fil...
  function get_output_feature (line 205) | def get_output_feature(video_id, labels, features, feature_names):
  function main (line 214) | def main(unused_argv):

FILE: youtube-8m-zhangteng/inference.py
  function format_lines (line 69) | def format_lines(video_ids, predictions, top_k):
  function get_input_data_tensors (line 83) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function inference (line 118) | def inference(reader, train_dir, data_pattern, out_file_location, batch_...
  function main (line 178) | def main(unused_argv):

FILE: youtube-8m-zhangteng/inference_autoencoder.py
  function format_lines (line 71) | def format_lines(video_ids, predictions, top_k):
  function get_input_data_tensors (line 85) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function get_forward_parameters (line 120) | def get_forward_parameters(vocab_size=4716):
  function inference (line 140) | def inference(reader,train_dir, data_pattern, out_file_location, batch_s...
  function main (line 189) | def main(unused_argv):

FILE: youtube-8m-zhangteng/inference_embedding.py
  function find_class_by_name (line 81) | def find_class_by_name(name, modules):
  function get_input_data_tensors (line 86) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function build_graph (line 122) | def build_graph(reader,
  function inference (line 172) | def inference(video_id_batch, prediction_batch, label_batch, saver, out_...
  function main (line 220) | def main(unused_argv):

FILE: youtube-8m-zhangteng/inference_test.py
  function format_lines (line 69) | def format_lines(video_ids, predictions, top_k):
  function get_input_data_tensors (line 83) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function inference (line 123) | def inference(reader, train_dir, data_pattern, out_file_location, batch_...
  function main (line 183) | def main(unused_argv):

FILE: youtube-8m-zhangteng/inference_with_rebuild.py
  function find_class_by_name (line 82) | def find_class_by_name(name, modules):
  function get_input_data_tensors (line 87) | def get_input_data_tensors(reader, data_pattern, batch_size, num_readers...
  function build_graph (line 123) | def build_graph(reader,
  function inference (line 180) | def inference(video_id_batch, prediction_batch, label_batch, saver, out_...
  function write_to_record (line 267) | def write_to_record(id_batch, label_batch, predictions, filenum, num_exa...
  function get_output_feature (line 277) | def get_output_feature(video_id, labels, features,feature_names):
  function main (line 286) | def main(unused_argv):

FILE: youtube-8m-zhangteng/labels_autoencoder.py
  class AutoEncoderSoftmaxModel (line 35) | class AutoEncoderSoftmaxModel(models.BaseModel):
    method create_model (line 38) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, **unu...
  class AutoEncoderModel (line 84) | class AutoEncoderModel(models.BaseModel):
    method create_model (line 87) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, **unu...

FILE: youtube-8m-zhangteng/labels_embedding.py
  class EmbeddingSigmoidModel (line 32) | class EmbeddingSigmoidModel(models.BaseModel):
    method create_model (line 35) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, **unu...

FILE: youtube-8m-zhangteng/labels_rbm.py
  class RbmModel (line 29) | class RbmModel(models.BaseModel):
    method create_model (line 32) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, **unu...
    method propup (line 55) | def propup(self, visible):
    method propdown (line 58) | def propdown(self, hidden):
    method cd1 (line 61) | def cd1(self, visibles, learning_rate=0.1):
    method reconstruction_error (line 72) | def reconstruction_error(self, model_input):
    method sample_prob (line 76) | def sample_prob(self,probs):
    method sample_h_given_v (line 78) | def sample_h_given_v(self, v_sample):
    method sample_v_given_h (line 80) | def sample_v_given_h(self, h_sample):
    method gibbs_hvh (line 82) | def gibbs_hvh(self, h0_sample):
    method gibbs_vhv (line 86) | def gibbs_vhv(self, v0_sample):

FILE: youtube-8m-zhangteng/losses.py
  class BaseLoss (line 42) | class BaseLoss(object):
    method calculate_loss (line 45) | def calculate_loss(self, unused_predictions, unused_labels, **unused_p...
  class CrossEntropyLoss (line 61) | class CrossEntropyLoss(BaseLoss):
    method calculate_loss (line 64) | def calculate_loss(self, predictions, labels, **unused_params):
    method calculate_loss_distill (line 170) | def calculate_loss_distill(self, predictions, labels_distill, labels, ...
    method calculate_loss_distill_boost (line 197) | def calculate_loss_distill_boost(self, predictions, labels_distill, la...
    method calculate_loss_distill_relabel (line 216) | def calculate_loss_distill_relabel(self, predictions, labels_distill, ...
    method calculate_loss_negative (line 234) | def calculate_loss_negative(self, predictions_pos, predictions_neg, la...
    method calculate_mseloss (line 248) | def calculate_mseloss(self, predictions, labels, **unused_params):
    method calculate_loss_postprocess (line 254) | def calculate_loss_postprocess(self, predictions, labels, **unused_par...
    method calculate_loss_max (line 266) | def calculate_loss_max(self, predictions, predictions_experts, labels,...
    method calculate_loss_mix (line 280) | def calculate_loss_mix(self, predictions, predictions_class, labels, *...
    method calculate_loss_mix2 (line 315) | def calculate_loss_mix2(self, predictions, predictions_class, predicti...
  class CrossEntropyLoss_weight (line 336) | class CrossEntropyLoss_weight(BaseLoss):
    method calculate_loss (line 340) | def calculate_loss(self, predictions, labels, **unused_params):
  class HingeLoss_cos (line 359) | class HingeLoss_cos(BaseLoss):
    method calculate_loss (line 366) | def calculate_loss(self, predictions, labels, b1=1.6, b2=-0.4, **unuse...
  class SoftmaxLoss (line 412) | class SoftmaxLoss(BaseLoss):
    method calculate_loss (line 424) | def calculate_loss(self, predictions, labels, **unused_params):
    method calculate_loss_mix (line 448) | def calculate_loss_mix(self, predictions, predictions_class, labels, *...

FILE: youtube-8m-zhangteng/losses_embedding.py
  class BaseLoss (line 42) | class BaseLoss(object):
    method calculate_loss (line 45) | def calculate_loss(self, unused_predictions, unused_labels, **unused_p...
  class CrossEntropyLoss (line 61) | class CrossEntropyLoss(BaseLoss):
    method calculate_loss (line 64) | def calculate_loss(self, predictions, labels, **unused_params):
  class SoftmaxLoss (line 81) | class SoftmaxLoss(BaseLoss):
    method calculate_loss (line 93) | def calculate_loss(self, predictions, labels, **unused_params):
    method calculate_loss_mix (line 117) | def calculate_loss_mix(self, predictions, predictions_class, labels, *...

FILE: youtube-8m-zhangteng/mean_average_precision_calculator.py
  class MeanAveragePrecisionCalculator (line 44) | class MeanAveragePrecisionCalculator(object):
    method __init__ (line 48) | def __init__(self, num_class):
    method accumulate (line 71) | def accumulate(self, predictions, actuals, num_positives=None):
    method clear (line 95) | def clear(self):
    method is_empty (line 99) | def is_empty(self):
    method peek_map_at_n (line 103) | def peek_map_at_n(self):

FILE: youtube-8m-zhangteng/model_utils.py
  function SampleRandomSequence (line 23) | def SampleRandomSequence(model_input, num_frames, num_samples):
  function SampleRandomFrames (line 51) | def SampleRandomFrames(model_input, num_frames, num_samples):
  function FramePooling (line 72) | def FramePooling(frames, method, **unused_params):

FILE: youtube-8m-zhangteng/models.py
  class BaseModel (line 17) | class BaseModel(object):
    method create_model (line 20) | def create_model(self, unused_model_input, **unused_params):

FILE: youtube-8m-zhangteng/readers.py
  function resize_axis (line 21) | def resize_axis(tensor, axis, new_size, fill_value=0):
  class BaseReader (line 58) | class BaseReader(object):
    method prepare_reader (line 61) | def prepare_reader(self, unused_filename_queue):
  class YT8MAggregatedFeatureReader (line 66) | class YT8MAggregatedFeatureReader(BaseReader):
    method __init__ (line 74) | def __init__(self,
    method prepare_reader (line 94) | def prepare_reader(self, filename_queue, batch_size=1024):
  class YT8MFrameFeatureReader (line 127) | class YT8MFrameFeatureReader(BaseReader):
    method __init__ (line 136) | def __init__(self,
    method get_video_matrix (line 159) | def get_video_matrix(self,
    method prepare_reader (line 189) | def prepare_reader(self,
  class YT8MAggregatedDistillationFeatureReader (line 261) | class YT8MAggregatedDistillationFeatureReader(BaseReader):
    method __init__ (line 269) | def __init__(self,
    method prepare_reader (line 289) | def prepare_reader(self, filename_queue, batch_size=1024):
  class YT8MDistillationFeatureReader (line 323) | class YT8MDistillationFeatureReader(BaseReader):
    method __init__ (line 331) | def __init__(self,
    method prepare_reader (line 351) | def prepare_reader(self, filename_queue, batch_size=1024):
  class YT8MFrameDistillationFeatureReader (line 378) | class YT8MFrameDistillationFeatureReader(BaseReader):
    method __init__ (line 387) | def __init__(self,
    method get_video_matrix (line 410) | def get_video_matrix(self,
    method prepare_reader (line 440) | def prepare_reader(self,

FILE: youtube-8m-zhangteng/rnn_residual.py
  function _infer_state_dtype (line 23) | def _infer_state_dtype(explicit_dtype, state):
  function _on_device (line 52) | def _on_device(fn, device):
  function _rnn_step (line 61) | def _rnn_step(
  function dynamic_rnn (line 189) | def dynamic_rnn(cell, inputs, inerval, sequence_length=None, initial_sta...
  function _dynamic_rnn_loop (line 370) | def _dynamic_rnn_loop(cell,

FILE: youtube-8m-zhangteng/train-with-rebuild.py
  function validate_class_name (line 114) | def validate_class_name(flag_value, category, modules, expected_supercla...
  function get_input_data_tensors (line 142) | def get_input_data_tensors(reader,
  function find_class_by_name (line 187) | def find_class_by_name(name, modules):
  function build_graph (line 193) | def build_graph(reader,
  class Trainer (line 392) | class Trainer(object):
    method __init__ (line 395) | def __init__(self, cluster, task, train_dir, log_device_placement=True):
    method run (line 414) | def run(self, start_new_model=False):
    method start_server_if_distributed (line 496) | def start_server_if_distributed(self):
    method remove_training_directory (line 513) | def remove_training_directory(self, train_dir):
    method get_meta_filename (line 526) | def get_meta_filename(self, start_new_model, train_dir):
    method recover_model (line 546) | def recover_model(self, meta_filename):
    method get_latest_checkpoint (line 551) | def get_latest_checkpoint(self, start_new_model, train_dir):
    method build_model (line 565) | def build_model(self):
  class ParameterServer (line 611) | class ParameterServer(object):
    method __init__ (line 614) | def __init__(self, cluster, task):
    method run (line 626) | def run(self):
  function start_server (line 635) | def start_server(cluster, task):
  function task_as_string (line 658) | def task_as_string(task):
  function main (line 661) | def main(unused_argv):

FILE: youtube-8m-zhangteng/train.py
  function validate_class_name (line 127) | def validate_class_name(flag_value, category, modules, expected_supercla...
  function get_input_data_tensors (line 155) | def get_input_data_tensors(reader,
  function find_class_by_name (line 200) | def find_class_by_name(name, modules):
  function build_graph (line 206) | def build_graph(reader,
  class Trainer (line 445) | class Trainer(object):
    method __init__ (line 448) | def __init__(self, cluster, task, train_dir, log_device_placement=True):
    method run (line 468) | def run(self, start_new_model=False):
    method start_server_if_distributed (line 555) | def start_server_if_distributed(self):
    method remove_training_directory (line 572) | def remove_training_directory(self, train_dir):
    method get_meta_filename (line 585) | def get_meta_filename(self, start_new_model, train_dir):
    method recover_model (line 605) | def recover_model(self, meta_filename):
    method build_model (line 610) | def build_model(self):
  class ParameterServer (line 661) | class ParameterServer(object):
    method __init__ (line 664) | def __init__(self, cluster, task):
    method run (line 676) | def run(self):
  function start_server (line 685) | def start_server(cluster, task):
  function task_as_string (line 708) | def task_as_string(task):
  function main (line 711) | def main(unused_argv):

FILE: youtube-8m-zhangteng/train_autoencoder.py
  function validate_class_name (line 105) | def validate_class_name(flag_value, category, modules, expected_supercla...
  function get_input_data_tensors (line 133) | def get_input_data_tensors(reader,
  function find_class_by_name (line 178) | def find_class_by_name(name, modules):
  function get_forward_parameters (line 183) | def get_forward_parameters(vocab_size=4716):
  function build_graph (line 203) | def build_graph(reader,
  class Trainer (line 341) | class Trainer(object):
    method __init__ (line 344) | def __init__(self, cluster, task, train_dir, log_device_placement=True):
    method run (line 363) | def run(self, start_new_model=False):
    method start_server_if_distributed (line 455) | def start_server_if_distributed(self):
    method remove_training_directory (line 472) | def remove_training_directory(self, train_dir):
    method get_meta_filename (line 485) | def get_meta_filename(self, start_new_model, train_dir):
    method recover_model (line 505) | def recover_model(self, meta_filename):
    method build_model (line 510) | def build_model(self):
  class ParameterServer (line 553) | class ParameterServer(object):
    method __init__ (line 556) | def __init__(self, cluster, task):
    method run (line 568) | def run(self):
  function start_server (line 577) | def start_server(cluster, task):
  function task_as_string (line 600) | def task_as_string(task):
  function main (line 603) | def main(unused_argv):

FILE: youtube-8m-zhangteng/train_embedding.py
  function validate_class_name (line 106) | def validate_class_name(flag_value, category, modules, expected_supercla...
  function get_input_data_tensors (line 134) | def get_input_data_tensors(reader,
  function find_class_by_name (line 179) | def find_class_by_name(name, modules):
  function build_graph (line 185) | def build_graph(reader,
  class Trainer (line 319) | class Trainer(object):
    method __init__ (line 322) | def __init__(self, cluster, task, train_dir, log_device_placement=True):
    method run (line 342) | def run(self, start_new_model=False):
    method start_server_if_distributed (line 430) | def start_server_if_distributed(self):
    method remove_training_directory (line 447) | def remove_training_directory(self, train_dir):
    method get_meta_filename (line 460) | def get_meta_filename(self, start_new_model, train_dir):
    method recover_model (line 480) | def recover_model(self, meta_filename):
    method build_model (line 485) | def build_model(self):
  class ParameterServer (line 528) | class ParameterServer(object):
    method __init__ (line 531) | def __init__(self, cluster, task):
    method run (line 543) | def run(self):
  function start_server (line 552) | def start_server(cluster, task):
  function task_as_string (line 575) | def task_as_string(task):
  function main (line 578) | def main(unused_argv):

FILE: youtube-8m-zhangteng/train_ensemble.py
  function validate_class_name (line 136) | def validate_class_name(flag_value, category, modules, expected_supercla...
  function get_input_data_tensors (line 165) | def get_input_data_tensors(reader,
  function find_class_by_name (line 204) | def find_class_by_name(name, modules):
  function build_graph (line 210) | def build_graph(reader1,
  class Trainer (line 432) | class Trainer(object):
    method __init__ (line 435) | def __init__(self, cluster, task, train_dir, log_device_placement=True):
    method run (line 455) | def run(self, start_new_model=False):
    method start_server_if_distributed (line 542) | def start_server_if_distributed(self):
    method remove_training_directory (line 559) | def remove_training_directory(self, train_dir):
    method get_meta_filename (line 572) | def get_meta_filename(self, start_new_model, train_dir):
    method recover_model (line 592) | def recover_model(self, meta_filename):
    method build_model (line 597) | def build_model(self):
  class ParameterServer (line 641) | class ParameterServer(object):
    method __init__ (line 644) | def __init__(self, cluster, task):
    method run (line 656) | def run(self):
  function start_server (line 665) | def start_server(cluster, task):
  function task_as_string (line 688) | def task_as_string(task):
  function main (line 691) | def main(unused_argv):

FILE: youtube-8m-zhangteng/utils.py
  function Dequantize (line 23) | def Dequantize(feat_vector, max_quantized_value=2, min_quantized_value=-2):
  function MakeSummary (line 41) | def MakeSummary(name, value):
  function AddGlobalStepSummary (line 50) | def AddGlobalStepSummary(summary_writer,
  function AddEpochSummary (line 94) | def AddEpochSummary(summary_writer,
  function GetListOfFeatureNamesAndSizes (line 140) | def GetListOfFeatureNamesAndSizes(feature_names, feature_sizes):

FILE: youtube-8m-zhangteng/video_level_models.py
  class LogisticModel (line 61) | class LogisticModel(models.BaseModel):
    method create_model (line 64) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, **unu...
  class MoeModel (line 80) | class MoeModel(models.BaseModel):
    method create_model (line 83) | def create_model(self,
  class MoeDistillModel (line 157) | class MoeDistillModel(models.BaseModel):
    method create_model (line 160) | def create_model(self,
  class MoeDistillEmbeddingModel (line 233) | class MoeDistillEmbeddingModel(models.BaseModel):
    method create_model (line 236) | def create_model(self,
  class MoeDistillChainModel (line 286) | class MoeDistillChainModel(models.BaseModel):
    method create_model (line 289) | def create_model(self,
  class MoeDistillChainNormModel (line 359) | class MoeDistillChainNormModel(models.BaseModel):
    method create_model (line 362) | def create_model(self,
  class MoeDistillChainNorm2Model (line 434) | class MoeDistillChainNorm2Model(models.BaseModel):
    method create_model (line 437) | def create_model(self,
  class MoeDistillSplitModel (line 509) | class MoeDistillSplitModel(models.BaseModel):
    method create_model (line 512) | def create_model(self,
  class MoeDistillSplit2Model (line 584) | class MoeDistillSplit2Model(models.BaseModel):
    method create_model (line 587) | def create_model(self,
  class MoeDistillSplit3Model (line 661) | class MoeDistillSplit3Model(models.BaseModel):
    method create_model (line 664) | def create_model(self,
  class MoeDistillSplit4Model (line 774) | class MoeDistillSplit4Model(models.BaseModel):
    method create_model (line 777) | def create_model(self,
  class MoeSoftmaxModel (line 877) | class MoeSoftmaxModel(models.BaseModel):
    method sub_model (line 879) | def sub_model(self,
    method create_model (line 962) | def create_model(self,
  class MoeNegativeModel (line 1020) | class MoeNegativeModel(models.BaseModel):
    method create_model (line 1023) | def create_model(self,
  class MoeMaxModel (line 1107) | class MoeMaxModel(models.BaseModel):
    method create_model (line 1110) | def create_model(self,
  class MoeMaxMixModel (line 1208) | class MoeMaxMixModel(models.BaseModel):
    method create_model (line 1211) | def create_model(self,
  class MoeKnowledgeModel (line 1331) | class MoeKnowledgeModel(models.BaseModel):
    method create_model (line 1334) | def create_model(self,
  class MoeMixModel (line 1441) | class MoeMixModel(models.BaseModel):
    method create_model (line 1444) | def create_model(self,
  class MoeMixExtendModel (line 1534) | class MoeMixExtendModel(models.BaseModel):
    method create_model (line 1537) | def create_model(self,
  class MoeMix2Model (line 1632) | class MoeMix2Model(models.BaseModel):
    method create_model (line 1635) | def create_model(self,
  class MoeMix3Model (line 1762) | class MoeMix3Model(models.BaseModel):
    method create_model (line 1765) | def create_model(self,
  class MoeMix4Model (line 1872) | class MoeMix4Model(models.BaseModel):
    method create_model (line 1875) | def create_model(self,
  class MoeNoiseModel (line 2046) | class MoeNoiseModel(models.BaseModel):
    method create_model (line 2049) | def create_model(self,
  class MoeMix5Model (line 2200) | class MoeMix5Model(models.BaseModel):
    method create_model (line 2203) | def create_model(self,
  class MoeExtendModel (line 2272) | class MoeExtendModel(models.BaseModel):
    method create_model (line 2275) | def create_model(self,
  class MoeExtendDistillChainModel (line 2332) | class MoeExtendDistillChainModel(models.BaseModel):
    method create_model (line 2335) | def create_model(self,
  class MoeExtendCombineModel (line 2402) | class MoeExtendCombineModel(models.BaseModel):
    method create_model (line 2405) | def create_model(self,
  class MoeExtendSoftmaxModel (line 2504) | class MoeExtendSoftmaxModel(models.BaseModel):
    method create_model (line 2507) | def create_model(self,
  class MoeSepModel (line 2573) | class MoeSepModel(models.BaseModel):
    method create_model (line 2576) | def create_model(self,
  class SimModel (line 2639) | class SimModel(models.BaseModel):
    method create_model (line 2642) | def create_model(self,
  class AutoEncoderModel (line 2707) | class AutoEncoderModel(models.BaseModel):
    method create_model (line 2710) | def create_model(self, model_input, vocab_size, l2_penalty=1e-8, **unu...

FILE: youtube-8m-zhangteng/writers.py
  class BaseWriter (line 21) | class BaseWriter(object):
    method prepare_writer (line 24) | def prepare_writer(self, unused_filename_queue):
  class YT8MAggregatedFeatureWriter (line 29) | class YT8MAggregatedFeatureWriter(BaseWriter):
    method __init__ (line 37) | def __init__(self,
    method prepare_writer (line 57) | def prepare_writer(self, filename_queue, batch_size=1024):