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unit: def compute_time_decay()
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unit: def _take_sample()
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unit: def to_vw_cmd()
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unit: def predict_ratings()
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id: 385
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id: 386
unit: def _download_reviews()
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id: 387
unit: def get_spark_schema()
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id: 392
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unit: def python_stratified_split()
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id: 395
unit: def read_linked_entities()
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unit: def _get_cosine_similarity()
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id: 397
unit: def __init__()
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unit: def _get_relevant_items_by_timestamp()
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unit: def distributional_coverage()
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unit: def download_deeprec_resources()
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id: 401
unit: def _convert_data()
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unit: def load_model()
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id: 403
unit: def _build_cnn()
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id: 405
unit: def _check_supported_dtypes()
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id: 406
unit: def hide_fastai_progress_bar()
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id: 407
unit: def __init__()
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id: 408
unit: def normalize()
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id: 409
unit: def _predict()
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id: 410
unit: def _convert_user_data()
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unit: def _get_loss()
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id: 412
unit: def fit()
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id: 413
unit: def _get_input_label_from_iter()
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id: 414
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id: 415
unit: def time()
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id: 416
unit: def multinomial_distribution()
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id: 417
unit: def display_metrics()
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id: 418
unit: def recommend_top_k_items()
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id: 419
unit: def __init__()
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id: 420
unit: def __init__()
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unit: def __init__()
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unit: def _build_wide_columns()
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id: 423
unit: def is_databricks()
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id: 424
unit: def start_or_get_spark()
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id: 425
unit: def begin()
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id: 426
unit: def recommend_k_items()
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id: 427
unit: def recommend_k_items_slow()
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id: 428
unit: override def shortName()
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id: 429
unit: override def prepareWrite()
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id: 430
unit: def load_spark_df()
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id: 431
unit: def load_pandas_df()
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id: 432
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id: 433
unit: def get_df()
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unit: def has_columns()
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id: 435
unit: def __hash__()
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id: 436
unit: def _get_column_name()
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id: 437
unit: def get_session()
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id: 438
unit: def merge_rating_true_pred()
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id: 439
unit: def rmse()
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id: 440
unit: def mae()
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id: 441
unit: def rsquared()
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id: 442
unit: def exp_var()
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id: 443
unit: def auc()
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id: 444
unit: def logloss()
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id: 445
unit: def _get_top_k_items()
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id: 446
unit: def _get_relevant_items_by_threshold()
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id: 447
unit: def diversity()
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id: 448
unit: def serendipity()
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id: 449
unit: def catalog_coverage()
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id: 450
unit: def predict_ranking()
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id: 451
unit: def flat_config()
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id: 452
unit: def hit_score()
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id: 453
unit: def dcg_score()
file: recommenders/models/deeprec/deeprec_utils.py
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id: 454
unit: def _build_graph()
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id: 455
unit: def _build_pair_attention()
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id: 456
unit: def eval()
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id: 457
unit: def load()
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id: 458
unit: def __init__()
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id: 459
unit: def cartesian_product()
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id: 460
unit: def score()
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id: 461
unit: def predict()
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id: 462
unit: def _convert_news_data()
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id: 463
unit: def _convert_data()
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id: 464
unit: def __init__()
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id: 466
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id: 467
unit: def _cost()
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unit: def __init__()
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id: 469
unit: def compute_ranking_predictions()
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id: 470
unit: def _update_metrics()
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id: 471
unit: def get_number_processors()
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id: 472
unit: def clear_memory_all_gpus()
file: recommenders/utils/gpu_utils.py
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id: 473
unit: def jaccard()
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id: 474
unit: def lift()
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id: 475
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id: 476
unit: def dbfs_file_exists()
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id: 477
unit: def remove_duplicates()
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id: 478
unit: def clean_dataframe()
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id: 479
unit: def load_pandas_df()
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id: 480
unit: def unzip_file()
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id: 481
unit: def extract_mind()
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id: 482
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id: 483
unit: def word_tokenize()
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id: 484
unit: def download_movielens()
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id: 485
unit: def extract_movielens()
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id: 486
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id: 487
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id: 489
unit: def spark_random_split()
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id: 490
unit: def spark_timestamp_split()
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id: 491
unit: def min_rating_filter_pandas()
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id: 492
unit: def min_rating_filter_spark()
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id: 493
unit: def _get_item_feature_similarity()
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id: 494
unit: def exp_var()
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id: 495
unit: def predict()
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id: 496
unit: def _add_summaries()
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id: 497
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unit: def retrieve_text()
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id: 526
unit: def _newsample()
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id: 527
unit: def _get_cooccurrence_similarity()
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id: 528
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id: 529
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id: 530
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unit: def reduce_dims()
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unit: def save()
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id: 536
unit: def _convert_user_data()
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id: 537
unit: def __init__()
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id: 538
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id: 539
unit: def user()
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id: 540
unit: def news()
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id: 541
unit: def __init__()
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unit: def newsample()
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id: 543
unit: def init_gpu()
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unit: def compute_affinity_matrix()
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id: 546
unit: def __init__()
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unit: def __init__()
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id: 548
unit: def combine_metrics_dicts()
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id: 549
unit: def stop_nni()
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id: 550
unit: def get_number_gpus()
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id: 551
unit: def interval()
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id: 552
unit: def joblib_loader()
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id: 553
unit: override def equals()
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id: 554
unit: def __init__()
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id: 555
unit: def _get_pairwise_items()
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id: 556
unit: def ndcg_score()
file: recommenders/models/deeprec/deeprec_utils.py
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id: 557
unit: def load_dict()
file: recommenders/models/deeprec/deeprec_utils.py
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id: 559
unit: def eval()
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id: 560
unit: def infer()
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id: 561
unit: def infer_embedding()
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id: 562
unit: def _compute_data_loss()
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id: 563
unit: def _convert_sp_mat_to_sp_tensor()
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id: 564
unit: def reset()
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id: 565
unit: def get_data()
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unit: def __init__()
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unit: def __init__()
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id: 568
unit: def length_normalize()
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id: 569
unit: def reduce_dims()
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id: 570
unit: def _convert_news_data()
file: recommenders/models/newsrec/io/mind_iterator.py
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id: 573
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id: 575
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id: 576
unit: def losses()
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id: 577
unit: def init_metrics()
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id: 579
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id: 580
unit: def rescale()
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id: 583
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id: 586
unit: def macroTransform()
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id: 587
unit: override def getFileExtension()
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id: 588
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id: 589
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id: 590
unit: def precision_at_k()
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id: 594
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id: 623
unit: def recommend_items()
file: contrib/azureml_designer_modules/entries/score_sar_entry.py
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size: 2 LOC
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id: 624
unit: def predict()
file: contrib/sarplus/python/pysarplus/SARModel.py
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size: 2 LOC
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number of parameters: 5

id: 625
unit: def f()
file: contrib/sarplus/python/pysarplus/SARPlus.py
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size: 2 LOC
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number of parameters: 3

id: 626
unit: def __init__()
file: contrib/sarplus/python/setup.py
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size: 2 LOC
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number of parameters: 2

id: 627
unit: bool operator()
file: contrib/sarplus/python/src/pysarplus.cpp
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end line: 66
size: 2 LOC
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id: 628
unit: bool operator()
file: contrib/sarplus/python/src/pysarplus.cpp
start line: 70
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size: 2 LOC
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id: 629
unit: def _negative_sampling_offline()
file: recommenders/datasets/amazon_reviews.py
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size: 2 LOC
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id: 630
unit: def _data_generating_no_history_expanding()
file: recommenders/datasets/amazon_reviews.py
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size: 2 LOC
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id: 631
unit: def separator()
file: recommenders/datasets/movielens.py
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size: 2 LOC
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id: 632
unit: def path()
file: recommenders/datasets/movielens.py
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size: 2 LOC
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id: 633
unit: def has_header()
file: recommenders/datasets/movielens.py
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size: 2 LOC
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id: 634
unit: def item_separator()
file: recommenders/datasets/movielens.py
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size: 2 LOC
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id: 635
unit: def item_path()
file: recommenders/datasets/movielens.py
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size: 2 LOC
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id: 636
unit: def item_has_header()
file: recommenders/datasets/movielens.py
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size: 2 LOC
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id: 637
unit: def unique_columns()
file: recommenders/datasets/movielens.py
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size: 2 LOC
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number of parameters: 3

id: 638
unit: def fit_transform()
file: recommenders/datasets/pandas_df_utils.py
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size: 2 LOC
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number of parameters: 3

id: 639
unit: def __eq__()
file: recommenders/datasets/pandas_df_utils.py
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size: 2 LOC
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number of parameters: 2

id: 640
unit: def get_top_k_items()
file: recommenders/evaluation/python_evaluation.py
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size: 2 LOC
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id: 641
unit: def catalog_coverage()
file: recommenders/evaluation/python_evaluation.py
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size: 2 LOC
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id: 642
unit: def distributional_coverage()
file: recommenders/evaluation/python_evaluation.py
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size: 2 LOC
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id: 643
unit: def rmse()
file: recommenders/evaluation/spark_evaluation.py
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size: 2 LOC
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id: 644
unit: def mae()
file: recommenders/evaluation/spark_evaluation.py
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size: 2 LOC
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id: 645
unit: def rsquared()
file: recommenders/evaluation/spark_evaluation.py
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id: 646
unit: def __repr__()
file: recommenders/models/deeprec/deeprec_utils.py
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id: 647
unit: def values()
file: recommenders/models/deeprec/deeprec_utils.py
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id: 648
unit: def _convert_infer_data()
file: recommenders/models/deeprec/io/dkn_iterator.py
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size: 2 LOC
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id: 649
unit: def parser_one_line()
file: recommenders/models/deeprec/io/iterator.py
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id: 650
unit: def load_data_from_file()
file: recommenders/models/deeprec/io/iterator.py
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id: 651
unit: def _convert_data()
file: recommenders/models/deeprec/io/iterator.py
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size: 2 LOC
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number of parameters: 3

id: 652
unit: def gen_feed_dict()
file: recommenders/models/deeprec/io/iterator.py
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size: 2 LOC
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number of parameters: 2

id: 653
unit: def _build_graph()
file: recommenders/models/deeprec/models/base_model.py
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size: 2 LOC
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number of parameters: 1

id: 654
unit: def _dropout()
file: recommenders/models/deeprec/models/base_model.py
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size: 2 LOC
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number of parameters: 3

id: 655
unit: def _init_embedding()
file: recommenders/models/deeprec/models/dkn.py
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size: 2 LOC
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number of parameters: 2

id: 656
unit: def _get_pred()
file: recommenders/models/deeprec/models/dkn_item2item.py
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size: 2 LOC
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number of parameters: 3

id: 657
unit: def recommend_k_items()
file: recommenders/models/deeprec/models/graphrec/lightgcn.py
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size: 2 LOC
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number of parameters: 0

id: 658
unit: def state_size()
file: recommenders/models/deeprec/models/sequential/rnn_cell_implement.py
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size: 2 LOC
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number of parameters: 1

id: 659
unit: def output_size()
file: recommenders/models/deeprec/models/sequential/rnn_cell_implement.py
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size: 2 LOC
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number of parameters: 1

id: 660
unit: def state_size()
file: recommenders/models/deeprec/models/sequential/rnn_cell_implement.py
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size: 2 LOC
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number of parameters: 1

id: 661
unit: def output_size()
file: recommenders/models/deeprec/models/sequential/rnn_cell_implement.py
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size: 2 LOC
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number of parameters: 1

id: 662
unit: def _build_seq_graph()
file: recommenders/models/deeprec/models/sequential/sequential_base_model.py
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size: 2 LOC
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number of parameters: 1

id: 663
unit: def state_size()
file: recommenders/models/deeprec/models/sequential/sum_cells.py
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size: 2 LOC
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id: 664
unit: def output_size()
file: recommenders/models/deeprec/models/sequential/sum_cells.py
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size: 2 LOC
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number of parameters: 1

id: 665
unit: def _build_CIN()
file: recommenders/models/deeprec/models/xDeepFM.py
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size: 2 LOC
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number of parameters: 0

id: 666
unit: def _loadTarget()
file: recommenders/models/geoimc/geoimc_algorithm.py
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size: 2 LOC
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number of parameters: 0

id: 667
unit: def _create_model()
file: recommenders/models/ncf/ncf_singlenode.py
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size: 2 LOC
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number of parameters: 0

id: 668
unit: def _init_embedding()
file: recommenders/models/newsrec/models/base_model.py
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size: 2 LOC
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number of parameters: 2

id: 669
unit: def _build_graph()
file: recommenders/models/newsrec/models/base_model.py
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size: 2 LOC
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number of parameters: 1

id: 670
unit: def _get_input_label_from_iter()
file: recommenders/models/newsrec/models/base_model.py
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size: 2 LOC
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number of parameters: 2

id: 671
unit: def compute_mask()
file: recommenders/models/newsrec/models/layers.py
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size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 672
unit: def compute_output_shape()
file: recommenders/models/newsrec/models/layers.py
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size: 2 LOC
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number of parameters: 2

id: 673
unit: def compute_output_shape()
file: recommenders/models/newsrec/models/layers.py
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size: 2 LOC
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id: 674
unit: def __init__()
file: recommenders/models/newsrec/models/layers.py
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number of parameters: 2

id: 675
unit: def compute_output_shape()
file: recommenders/models/newsrec/models/layers.py
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size: 2 LOC
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id: 676
unit: def __init__()
file: recommenders/models/newsrec/models/layers.py
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size: 2 LOC
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id: 677
unit: def build()
file: recommenders/models/newsrec/models/layers.py
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size: 2 LOC
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id: 678
unit: def call()
file: recommenders/models/newsrec/models/layers.py
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size: 2 LOC
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number of parameters: 3

id: 679
unit: def compute_output_shape()
file: recommenders/models/newsrec/models/layers.py
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size: 2 LOC
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number of parameters: 2

id: 680
unit: def _get_user_feature_from_iter()
file: recommenders/models/newsrec/models/lstur.py
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size: 2 LOC
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number of parameters: 2

id: 681
unit: def _get_news_feature_from_iter()
file: recommenders/models/newsrec/models/lstur.py
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size: 2 LOC
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number of parameters: 2

id: 682
unit: def _get_user_feature_from_iter()
file: recommenders/models/newsrec/models/nrms.py
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size: 2 LOC
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number of parameters: 2

id: 683
unit: def _get_news_feature_from_iter()
file: recommenders/models/newsrec/models/nrms.py
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size: 2 LOC
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number of parameters: 2

id: 684
unit: def placeholder()
file: recommenders/models/rbm/rbm.py
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size: 2 LOC
McCabe index: 1
number of parameters: 1

id: 685
unit: def fit_and_evaluate()
file: recommenders/models/rlrmc/RLRMCalgorithm.py
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size: 2 LOC
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number of parameters: 3

id: 686
unit: def surprise_trainset_to_df()
file: recommenders/models/surprise/surprise_utils.py
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size: 2 LOC
McCabe index: 1
number of parameters: 0

id: 687
unit: def tokenize_text()
file: recommenders/models/tfidf/tfidf_utils.py
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size: 2 LOC
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number of parameters: 5

id: 688
unit: def fit()
file: recommenders/models/tfidf/tfidf_utils.py
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size: 2 LOC
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number of parameters: 3

id: 689
unit: def __make_clickable()
file: recommenders/models/tfidf/tfidf_utils.py
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size: 2 LOC
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number of parameters: 2

id: 690
unit: def get_top_k_recommendations()
file: recommenders/models/tfidf/tfidf_utils.py
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size: 2 LOC
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number of parameters: 0

id: 691
unit: def on_train_begin()
file: recommenders/models/vae/multinomial_vae.py
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id: 692
unit: def get_data()
file: recommenders/models/vae/multinomial_vae.py
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id: 693
unit: def on_train_begin()
file: recommenders/models/vae/multinomial_vae.py
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id: 694
unit: def get_data()
file: recommenders/models/vae/multinomial_vae.py
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id: 695
unit: def ndcg_per_epoch()
file: recommenders/models/vae/multinomial_vae.py
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id: 696
unit: def on_train_begin()
file: recommenders/models/vae/standard_vae.py
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id: 697
unit: def get_data()
file: recommenders/models/vae/standard_vae.py
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id: 698
unit: def on_train_begin()
file: recommenders/models/vae/standard_vae.py
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id: 699
unit: def get_data()
file: recommenders/models/vae/standard_vae.py
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id: 700
unit: def ndcg_per_epoch()
file: recommenders/models/vae/standard_vae.py
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size: 2 LOC
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id: 701
unit: def __del__()
file: recommenders/models/vowpal_wabbit/vw.py
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number of parameters: 1

id: 702
unit: def _build_deep_columns()
file: recommenders/models/wide_deep/wide_deep_utils.py
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id: 703
unit: def compute_test_results()
file: recommenders/tuning/nni/ncf_utils.py
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id: 704
unit: def get_experiment_status()
file: recommenders/tuning/nni/nni_utils.py
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id: 705
unit: def invert_dictionary()
file: recommenders/utils/general_utils.py
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number of parameters: 1

id: 706
unit: def get_physical_memory()
file: recommenders/utils/general_utils.py
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id: 707
unit: def qps_to_replicas()
file: recommenders/utils/k8s_utils.py
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id: 708
unit: def replicas_to_qps()
file: recommenders/utils/k8s_utils.py
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size: 2 LOC
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id: 709
unit: def exponential_decay()
file: recommenders/utils/python_utils.py
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size: 2 LOC
McCabe index: 1
number of parameters: 3

id: 710
unit: def binarize()
file: recommenders/utils/python_utils.py
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size: 2 LOC
McCabe index: 1
number of parameters: 2

id: 711
unit: def pandas_input_fn()
file: recommenders/utils/tf_utils.py
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size: 2 LOC
McCabe index: 1
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id: 712
unit: def __init__()
file: recommenders/utils/tf_utils.py
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id: 713
unit: def get_log()
file: recommenders/utils/tf_utils.py
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number of parameters: 1

id: 714
unit: def __exit__()
file: recommenders/utils/timer.py
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id: 715
unit: def __str__()
file: recommenders/utils/timer.py
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id: 716
unit: def prepare_for_operationalization()
file: tools/databricks_install.py
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number of parameters: 0

id: 717
unit: int get_id()
file: contrib/sarplus/python/src/pysarplus.cpp
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number of parameters: 0

id: 718
unit: float get_score()
file: contrib/sarplus/python/src/pysarplus.cpp
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number of parameters: 0