repo_id stringclasses 400
values | commit_sha stringclasses 400
values | commit_index int32 0 951 | in_repo_split stringclasses 1
value | cross_repo_split stringclasses 1
value | test_file stringlengths 7 121 | test_function stringlengths 1 108 | assertion_type stringclasses 32
values | difficulty stringclasses 8
values | context_lines int32 3 600 | prefix large_stringlengths 44 113k | target large_stringlengths 1 498 | anchor_sha stringclasses 400
values | anchor_index int32 0 951 | qna_source stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_knn_embed.py | test_get_embeddings | pytest.raises | variable | 65 | import sys
import pytest
from libreco.algorithms import ALS, LightGCN, RNN4Rec
from tests.utils_data import set_ranking_labels
def ptest_knn(model, pd_data):
assert model.get_user_embedding().shape[0] == model.n_users
assert model.get_user_embedding().shape[1] == model.embed_size
assert model.get_item_em... | ValueError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_multi_sparse_processing.py | test_multi_sparse_processing | assert | variable | 49 | import os
import pandas as pd
import pytest
from libreco.data import split_multi_value
def test_multi_sparse_processing():
data_path = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
"sample_data",
"sample_movielens_genre.csv",
)
data = pd.read_csv(data_path, sep=",", h... | all_columns | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_multiprocessing_seeds.py | test_multiprocessing_seeds | assert | variable | 50 | import multiprocessing
import random
import numpy as np
import pytest
import torch
from torch.utils.data import DataLoader
def get_data(request):
data_size = 20
same_seed = request.param["same_seed"]
batch_size = request.param["batch_size"]
num_workers = request.param["num_workers"]
batch_data = B... | num_workers | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_similarities.py | test_similarities | pytest.raises | variable | 55 | import functools
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from scipy.sparse import csr_matrix
from libreco.data import DatasetPure
from libreco.utils.similarities import (
_choose_blocks,
cosine_sim,
jaccard_sim,
pearson_sim,
)
raw_data = """
user,item,label
1,8,2
... | ValueError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_tf_layers.py | test_config | pytest.raises | variable | 31 | import sys
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from libreco.layers import (
conv_nn,
dense_nn,
layer_normalization,
max_pool,
multi_head_attention,
shared_dense,
tf_dense,
tf_rnn,
transformer_decoder_layer,
transformer_... | ValueError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/utils_reco.py | ptest_recommends | pytest.raises | variable | 15 | import numpy as np
import pytest
from libreco.utils.constants import FeatModels, SequenceModels
def recommend_in_former_consumed(data_info, reco, user):
user_id = data_info.user2id[user]
user_consumed = data_info.user_consumed[user_id]
user_consumed_id = [data_info.id2item[i] for i in user_consumed]
r... | ValueError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | test_knn_serialization | assert | variable | 43 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | k_sims_redis | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_autoint.py | test_autoint_multi_sparse | pytest.raises | variable | 26 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import AutoInt
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from tests.utils_pred import ptest_preds
from tests.utils_reco import pt... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_bpr.py | test_bpr | pytest.raises | variable | 111 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import BPR
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import remove_path
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from test... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_deepwalk.py | test_deepwalk | pytest.raises | variable | 57 | import pytest
import tensorflow as tf
from libreco.algorithms import DeepWalk
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import save_load_model... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_din.py | test_din_multi_sparse | pytest.raises | variable | 35 | import os
import sys
from pathlib import Path
import pandas as pd
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import DIN
from libreco.data import DatasetFeat, split_by_ratio_chrono
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_item2vec.py | test_item2vec | pytest.raises | variable | 50 | import pytest
import tensorflow as tf
from libreco.algorithms import Item2Vec
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import save_load_model... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_lightgcn.py | test_lightgcn | pytest.raises | variable | 117 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import LightGCN
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import sav... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_rnn4rec.py | test_rnn4rec | pytest.raises | variable | 123 | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import RNN4Rec
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_svdpp.py | test_svdpp | pytest.raises | variable | 104 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import SVDpp
from libreco.data import DatasetPure
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import SAVE_PATH, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_pred... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | check_user_consumed | assert | variable | 71 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | user_consumed | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_data.py | test_dataset_pure | pytest.raises | variable | 85 | import os.path
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from libreco.data import (
DataInfo,
DatasetFeat,
DatasetPure,
TransformedEvalSet,
TransformedSet,
process_data,
)
from l... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_misc.py | test_misc | pytest.raises | variable | 16 | import time
import pytest
from libreco.utils.misc import colorize, time_block, time_func
def long_work():
time.sleep(0.1)
print(colorize("done!", color="red", bold=True, highlight=True))
def test_misc():
long_work()
with time_block("long work2", verbose=0):
time.sleep(0.1)
with pytest.r... | RuntimeError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_pairwise_collator | assert | variable | 116 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | user_dense_len | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_base.py | test_base | pytest.raises | variable | 10 | import pytest
from libreco.bases import Base
def test_base(prepare_pure_data):
_, train_data, _, data_info = prepare_pure_data
with pytest.raises(ValueError):
_ = NCF(task="unknown", data_info=data_info)
with pytest.raises( | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_bpr.py | test_bpr | pytest.raises | variable | 59 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import BPR
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import remove_path
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from test... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_caser.py | test_caser | pytest.raises | variable | 66 | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import Caser
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
f... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_deepfm.py | test_deepfm | pytest.raises | variable | 67 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import DeepFM
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from tests.utils_pred imp... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_deepwalk.py | test_deepwalk | pytest.raises | variable | 28 | import pytest
import tensorflow as tf
from libreco.algorithms import DeepWalk
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import save_load_model... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_din.py | test_din_multi_sparse | assert_* | variable | 34 | import os
import sys
from pathlib import Path
import pandas as pd
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import DIN
from libreco.data import DatasetFeat, split_by_ratio_chrono
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data... | loaded_dyn_rec) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_din.py | test_din | pytest.raises | variable | 70 | import os
import sys
from pathlib import Path
import pandas as pd
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import DIN
from libreco.data import DatasetFeat, split_by_ratio_chrono
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_fm.py | test_fm | pytest.raises | variable | 62 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import FM
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import SAVE_PATH, remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from ... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_item2vec.py | test_item2vec | pytest.raises | variable | 23 | import pytest
import tensorflow as tf
from libreco.algorithms import Item2Vec
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import save_load_model... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_item_cf.py | test_item_cf | pytest.raises | variable | 31 | import numpy as np
import pytest
from libreco.algorithms import ItemCF
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import save_load_model
@pyte... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_lightgcn.py | test_lightgcn | pytest.raises | variable | 75 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import LightGCN
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import sav... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_ncf.py | test_ncf | pytest.raises | variable | 61 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import NCF
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
fr... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_ngcf.py | test_ngcf | pytest.raises | variable | 81 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import NGCF
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import save_lo... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_rnn4rec.py | test_rnn4rec | pytest.raises | variable | 67 | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import RNN4Rec
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_svd.py | test_svd | pytest.raises | variable | 54 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import SVD
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
fr... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_two_tower.py | test_two_tower | pytest.raises | variable | 76 | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import TwoTower
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_pred... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_user_cf.py | test_user_cf | pytest.raises | variable | 31 | import numpy as np
import pytest
from libreco.algorithms import UserCF
from tests.utils_data import remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest_recommends
from tests.utils_save_load import save_load_model
@pyte... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_wave_net.py | test_wave_net | pytest.raises | variable | 67 | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import WaveNet
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pred import ptest_preds... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_wide_deep.py | test_wide_deep | pytest.raises | variable | 64 | import sys
import pytest
import tensorflow as tf
from libreco.algorithms import WideDeep
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_models import fit_multi_sparse
from tests.utils_pred i... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_youtube_ranking.py | test_youtube_ranking_multi_sparse | assert_* | variable | 30 | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import YouTubeRanking
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_mod... | loaded_dyn_rec) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_youtube_ranking.py | test_youtube_ranking | pytest.raises | variable | 64 | import sys
import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import YouTubeRanking
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_multi_sparse_mod... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_youtube_retrieval.py | test_youtube_retrieval_multi_sparse | assert_* | variable | 63 | import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import YouTubeRetrieval
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import SAVE_PATH, remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pr... | loaded_seq_rec) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_youtube_retrieval.py | test_youtube_retrieval | pytest.raises | variable | 66 | import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import YouTubeRetrieval
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import SAVE_PATH, remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pr... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/models/test_youtube_retrieval.py | test_youtube_retrieval | assert_* | variable | 118 | import pytest
import tensorflow as tf
from numpy.testing import assert_array_equal
from libreco.algorithms import YouTubeRetrieval
from tests.models.utils_tf import ptest_tf_variables
from tests.utils_data import SAVE_PATH, remove_path, set_ranking_labels
from tests.utils_metrics import get_metrics
from tests.utils_pr... | loaded_dyn_rec) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_data.py | test_dataset_pure | pytest.raises | variable | 78 | import os.path
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from libreco.data import (
DataInfo,
DatasetFeat,
DatasetPure,
TransformedEvalSet,
TransformedSet,
process_data,
)
from l... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_multi_sparse_processing.py | test_multi_sparse_processing | pytest.raises | variable | 17 | import os
import pandas as pd
import pytest
from libreco.data import split_multi_value
def test_multi_sparse_processing():
data_path = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
"sample_data",
"sample_movielens_genre.csv",
)
data = pd.read_csv(data_path, sep=",", h... | AssertionError) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_rank_reco.py | test_rank_random | assert | complex_expr | 60 | import numpy as np
import pytest
from libreco.recommendation import rank_recommendations
def test_rank_random():
user_ids = [1, 2]
# fmt: off
preds = np.array([-0.1, -1e8, 0, 0.1, 0.01, 1e8, -0.01, 1e7, 0.1, 0.01]) # inf probs
n_rec = 2
n_items = 5
consumed = {1: [3, 4], 2: [4]}
rec_item... | score[i] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_rank_reco.py | test_rank_random | assert | complex_expr | 27 | import numpy as np
import pytest
from libreco.recommendation import rank_recommendations
def test_rank_random():
user_ids = [1, 2]
# fmt: off
preds = np.array([-0.1, -1e8, 0, 0.1, 0.01, 1e8, -0.01, 1e7, 0.1, 0.01]) # inf probs
n_rec = 2
n_items = 5
consumed = {1: [3, 4], 2: [4]}
rec_item... | rec_items[0] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_online_serving.py | test_online_serving | assert | complex_expr | 77 | import subprocess
import pytest
from libserving.serialization import online2redis, save_online
from tests.utils_data import SAVE_PATH
@pytest.mark.parametrize(
"online_model",
["pure", "user_feat", "separate", "multi_sparse", "item_feat", "all"],
indirect=True,
)
def test_online_serving(online_model, ses... | response.text | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | test_knn_serialization | assert | complex_expr | 41 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | model_num - 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | check_id_mapping | assert | complex_expr | 39 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | model.n_users | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_knn_embed.py | test_get_embeddings | assert | complex_expr | 48 | import sys
import pytest
from libreco.algorithms import ALS, LightGCN, RNN4Rec
from tests.utils_data import set_ranking_labels
def ptest_knn(model, pd_data):
assert model.get_user_embedding().shape[0] == model.n_users
assert model.get_user_embedding().shape[1] == model.embed_size
assert model.get_item_em... | model.n_users | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_knn_embed.py | test_get_embeddings | assert | complex_expr | 55 | import sys
import pytest
from libreco.algorithms import ALS, LightGCN, RNN4Rec
from tests.utils_data import set_ranking_labels
def ptest_knn(model, pd_data):
assert model.get_user_embedding().shape[0] == model.n_users
assert model.get_user_embedding().shape[1] == model.embed_size
assert model.get_item_em... | model.n_items | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | check_model_name | assert | complex_expr | 28 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | m["model_name"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_knn_embed.py | test_get_embeddings | assert | complex_expr | 64 | import sys
import pytest
from libreco.algorithms import ALS, LightGCN, RNN4Rec
from tests.utils_data import set_ranking_labels
def ptest_knn(model, pd_data):
assert model.get_user_embedding().shape[0] == model.n_users
assert model.get_user_embedding().shape[1] == model.embed_size
assert model.get_item_em... | dyn_embed.shape | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_negatives_exceed_sampling_tolerance | assert | complex_expr | 70 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | negatives[0][:4] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_negatives_exceed_sampling_tolerance | assert | complex_expr | 71 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | negatives[1][:4] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_knn_embed.py | test_get_embeddings | assert | complex_expr | 49 | import sys
import pytest
from libreco.algorithms import ALS, LightGCN, RNN4Rec
from tests.utils_data import set_ranking_labels
def ptest_knn(model, pd_data):
assert model.get_user_embedding().shape[0] == model.n_users
assert model.get_user_embedding().shape[1] == model.embed_size
assert model.get_item_em... | model.embed_size | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_similarities.py | test_similarities | assert | complex_expr | 60 | import functools
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from scipy.sparse import csr_matrix
from libreco.data import DatasetPure
from libreco.utils.similarities import (
_choose_blocks,
cosine_sim,
jaccard_sim,
pearson_sim,
)
raw_data = """
user,item,label
1,8,2
... | invert_sim.shape | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | check_user_consumed | assert | complex_expr | 66 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | model.n_users - 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | check_features | assert | complex_expr | 79 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | data_info.n_users | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | check_features | assert | complex_expr | 80 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | data_info.n_items | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | check_features | assert | complex_expr | 85 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | model.max_seq_len | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/utils_pred.py | ptest_preds | assert | complex_expr | 17 | from libreco.prediction import predict_data_with_feats
def ptest_preds(model, task, pd_data, with_feats):
user = pd_data.user.iloc[0]
item = pd_data.item.iloc[0]
pred = model.predict(user=user, item=item)
# prediction in range
if task == "rating":
assert 1 <= pred <= 5
else:
ass... | model.default_pred | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_faiss_index.py | test_faiss_index | assert | complex_expr | 17 | import os
import pytest
from libreco.algorithms import BPR
from libserving.serialization import save_faiss_index
from tests.utils_data import SAVE_PATH
def test_faiss_index(embed_model):
import faiss
save_faiss_index(SAVE_PATH, embed_model, 80, 10)
index = faiss.read_index(os.path.join(SAVE_PATH, "faiss... | embed_model.n_items | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_data.py | test_transformed_evalset | assert_* | complex_expr | 73 | import os.path
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from libreco.data import (
DataInfo,
DatasetFeat,
DatasetPure,
TransformedEvalSet,
TransformedSet,
process_data,
)
from l... | data2.item_indices) | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/retrain/test_als_retrain.py | test_als_retrain | assert | complex_expr | 124 | from pathlib import Path
import pandas as pd
import tensorflow as tf
from libreco.algorithms import ALS
from libreco.data import DataInfo, DatasetPure, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_preds
from tests.... | eval_result["roc_auc"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/retrain/test_gensim_model_retrain.py | retrain | assert | complex_expr | 132 | from pathlib import Path
import pandas as pd
from libreco.algorithms import DeepWalk, Item2Vec
from libreco.data import DataInfo, DatasetPure, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_preds
from tests.utils_rec... | eval_result["roc_auc"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/retrain/test_tfmodel_retrain_feat.py | test_tfmodel_retrain_feat | assert | complex_expr | 159 | from pathlib import Path
import pandas as pd
import pytest
import tensorflow as tf
from libreco.algorithms import DIN
from libreco.data import DataInfo, DatasetFeat, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_pre... | eval_result["roc_auc"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/retrain/test_tfmodel_retrain_pure.py | test_tfmodel_retrain_pure | assert | complex_expr | 135 | from pathlib import Path
import pandas as pd
import tensorflow as tf
from libreco.algorithms import WaveNet
from libreco.data import DataInfo, DatasetPure, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_preds
from te... | eval_result["roc_auc"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/retrain/test_thmodel_retrain_feat.py | test_torchmodel_retrain_feat | assert | complex_expr | 173 | from pathlib import Path
import pandas as pd
import tensorflow as tf
from libreco.algorithms import GraphSage
from libreco.data import DataInfo, DatasetFeat, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_preds
from ... | eval_result["roc_auc"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/retrain/test_thmodel_retrain_feat_dgl.py | test_torchmodel_retrain_feat_dgl | assert | complex_expr | 177 | from pathlib import Path
import pandas as pd
import tensorflow as tf
from libreco.algorithms import PinSageDGL
from libreco.data import DataInfo, DatasetFeat, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_preds
from... | eval_result["roc_auc"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/retrain/test_thmodel_retrain_pure.py | test_torchmodel_retrain_pure | assert | complex_expr | 134 | from pathlib import Path
import pandas as pd
from libreco.algorithms import NGCF
from libreco.data import DataInfo, DatasetPure, split_by_ratio_chrono
from libreco.evaluation import evaluate
from tests.utils_data import SAVE_PATH, remove_path
from tests.utils_pred import ptest_preds
from tests.utils_reco import ptest... | eval_result["roc_auc"] | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_faiss_index.py | test_faiss_index | assert | complex_expr | 18 | import os
import pytest
from libreco.algorithms import BPR
from libserving.serialization import save_faiss_index
from tests.utils_data import SAVE_PATH
def test_faiss_index(embed_model):
import faiss
save_faiss_index(SAVE_PATH, embed_model, 80, 10)
index = faiss.read_index(os.path.join(SAVE_PATH, "faiss... | embed_model.embed_size + 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_data.py | test_data_info | assert | complex_expr | 80 | import os.path
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from libreco.data import (
DataInfo,
DatasetFeat,
DatasetPure,
TransformedEvalSet,
TransformedSet,
process_data,
)
from l... | data_info2.col_name_mapping | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/utils_reco.py | ptest_dyn_recommends | pytest.raises | complex_expr | 94 | import numpy as np
import pytest
from libreco.utils.constants import FeatModels, SequenceModels
def recommend_in_former_consumed(data_info, reco, user):
user_id = data_info.user2id[user]
user_consumed = data_info.user_consumed[user_id]
user_consumed_id = [data_info.id2item[i] for i in user_consumed]
r... | ValueError, match=".*doesn't support arbitrary seq inference.") | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_embed_serving.py | test_embed_serving | assert | numeric_literal | 26 | import subprocess
from pathlib import Path
from libserving.serialization import embed2redis, save_embed, save_faiss_index
from tests.utils_data import SAVE_PATH, remove_path
def test_embed_serving(embed_model, session, close_server):
save_embed(SAVE_PATH, embed_model)
embed2redis(SAVE_PATH)
faiss_path = s... | 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_embed_serving.py | test_embed_serving | assert | numeric_literal | 32 | import subprocess
from pathlib import Path
from libserving.serialization import embed2redis, save_embed, save_faiss_index
from tests.utils_data import SAVE_PATH, remove_path
def test_embed_serving(embed_model, session, close_server):
save_embed(SAVE_PATH, embed_model)
embed2redis(SAVE_PATH)
faiss_path = s... | 3 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_knn_serving.py | test_knn_serving | assert | numeric_literal | 26 | import subprocess
import pytest
from libreco.bases import CfBase
from libserving.serialization import knn2redis, save_knn
from tests.utils_data import SAVE_PATH
@pytest.mark.parametrize("knn_model", ["UserCF", "ItemCF"], indirect=True)
def test_knn_serving(knn_model, session, close_server):
assert isinstance(knn... | 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_knn_serving.py | test_knn_serving | assert | numeric_literal | 32 | import subprocess
import pytest
from libreco.bases import CfBase
from libserving.serialization import knn2redis, save_knn
from tests.utils_data import SAVE_PATH
@pytest.mark.parametrize("knn_model", ["UserCF", "ItemCF"], indirect=True)
def test_knn_serving(knn_model, session, close_server):
assert isinstance(knn... | 3 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_online_serving.py | test_online_serving | assert | numeric_literal | 31 | import subprocess
import pytest
from libserving.serialization import online2redis, save_online
from tests.utils_data import SAVE_PATH
@pytest.mark.parametrize(
"online_model",
["pure", "user_feat", "separate", "multi_sparse", "item_feat", "all"],
indirect=True,
)
def test_online_serving(online_model, ses... | 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_online_serving.py | test_online_serving | assert | numeric_literal | 38 | import subprocess
import pytest
from libserving.serialization import online2redis, save_online
from tests.utils_data import SAVE_PATH
@pytest.mark.parametrize(
"online_model",
["pure", "user_feat", "separate", "multi_sparse", "item_feat", "all"],
indirect=True,
)
def test_online_serving(online_model, ses... | 3 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_serialization.py | test_knn_serialization | assert | numeric_literal | 40 | import json
import os
import numpy as np
import pytest
from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef
from libreco.bases import CfBase, TfBase
from libreco.tfops import tf
from libserving.serialization import (
embed2redis,
knn2redis,
online2redis,
save_embed,
save_knn,
save... | 0 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_tf_serving.py | test_tf_serving | assert | numeric_literal | 29 | import subprocess
import pytest
from libreco.bases import TfBase
from libserving.serialization import save_tf, tf2redis
from tests.utils_data import SAVE_PATH
@pytest.mark.parametrize(
"tf_model", ["pure", "feat-all", "feat-user", "feat-item"], indirect=True
)
def test_tf_serving(tf_model, session, close_server)... | 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/serving/test_tf_serving.py | test_tf_serving | assert | numeric_literal | 33 | import subprocess
import pytest
from libreco.bases import TfBase
from libserving.serialization import save_tf, tf2redis
from tests.utils_data import SAVE_PATH
@pytest.mark.parametrize(
"tf_model", ["pure", "feat-all", "feat-user", "feat-item"], indirect=True
)
def test_tf_serving(tf_model, session, close_server)... | 3 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_normal_collator | assert | numeric_literal | 98 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | 3 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_pairwise_collator | assert | numeric_literal | 98 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | 6 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_collators.py | test_pairwise_collator | assert | numeric_literal | 133 | from io import StringIO
import numpy as np
import pandas as pd
import pytest
import torch
from libreco.algorithms import DIN, LightGCN, PinSageDGL, RNN4Rec
from libreco.batch.batch_data import BatchData
from libreco.batch.batch_unit import (
PairFeats,
PairwiseBatch,
PointwiseBatch,
PointwiseSepFeatBa... | 9 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_data.py | test_dataset_feat | assert | numeric_literal | 69 | import os.path
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from libreco.data import (
DataInfo,
DatasetFeat,
DatasetPure,
TransformedEvalSet,
TransformedSet,
process_data,
)
from l... | 5 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_data.py | test_dataset_feat | assert | numeric_literal | 70 | import os.path
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from libreco.data import (
DataInfo,
DatasetFeat,
DatasetPure,
TransformedEvalSet,
TransformedSet,
process_data,
)
from l... | 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_data.py | test_dataset_feat | assert | numeric_literal | 71 | import os.path
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from libreco.data import (
DataInfo,
DatasetFeat,
DatasetPure,
TransformedEvalSet,
TransformedSet,
process_data,
)
from l... | 2 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_data.py | test_dataset_feat | assert | numeric_literal | 73 | import os.path
from io import StringIO
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from scipy.sparse import csr_matrix
from libreco.data import (
DataInfo,
DatasetFeat,
DatasetPure,
TransformedEvalSet,
TransformedSet,
process_data,
)
from l... | 3 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_feature.py | test_multi_sparse_indices | assert | numeric_literal | 149 | import os
from dataclasses import astuple
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from libreco.data import DatasetFeat
from libreco.data.data_info import EmptyFeature, Feature, store_old_info
from libreco.feature.multi_sparse import (
... | 7 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_feature.py | test_assign_features | assert | numeric_literal | 110 | import os
from dataclasses import astuple
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from libreco.data import DatasetFeat
from libreco.data.data_info import EmptyFeature, Feature, store_old_info
from libreco.feature.multi_sparse import (
... | 3 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_knn_embed.py | ptest_knn | assert | numeric_literal | 25 | import sys
import pytest
from libreco.algorithms import ALS, LightGCN, RNN4Rec
from tests.utils_data import set_ranking_labels
def ptest_knn(model, pd_data):
assert model.get_user_embedding().shape[0] == model.n_users
assert model.get_user_embedding().shape[1] == model.embed_size
assert model.get_item_em... | 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_split_data.py | test_random_split | assert | numeric_literal | 36 | from io import StringIO
import pandas as pd
from libreco.data import (
random_split,
split_by_num,
split_by_num_chrono,
split_by_ratio,
split_by_ratio_chrono,
)
raw_data = StringIO(
"""
user,item,label,time
4617,296,2,964138229
4617,296,2,964138221
4617,296,2,964138222
1298,208,4,974849526
45... | 3 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_split_data.py | test_random_split | assert | numeric_literal | 51 | from io import StringIO
import pandas as pd
from libreco.data import (
random_split,
split_by_num,
split_by_num_chrono,
split_by_ratio,
split_by_ratio_chrono,
)
raw_data = StringIO(
"""
user,item,label,time
4617,296,2,964138229
4617,296,2,964138221
4617,296,2,964138222
1298,208,4,974849526
45... | 6 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_split_data.py | test_random_split | assert | numeric_literal | 64 | from io import StringIO
import pandas as pd
from libreco.data import (
random_split,
split_by_num,
split_by_num_chrono,
split_by_ratio,
split_by_ratio_chrono,
)
raw_data = StringIO(
"""
user,item,label,time
4617,296,2,964138229
4617,296,2,964138221
4617,296,2,964138222
1298,208,4,974849526
45... | 0 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_split_data.py | test_split_by_ratio | assert | numeric_literal | 37 | from io import StringIO
import pandas as pd
from libreco.data import (
random_split,
split_by_num,
split_by_num_chrono,
split_by_ratio,
split_by_ratio_chrono,
)
raw_data = StringIO(
"""
user,item,label,time
4617,296,2,964138229
4617,296,2,964138221
4617,296,2,964138222
1298,208,4,974849526
45... | 2 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/test_split_data.py | test_split_by_num | assert | numeric_literal | 37 | from io import StringIO
import pandas as pd
from libreco.data import (
random_split,
split_by_num,
split_by_num_chrono,
split_by_ratio,
split_by_ratio_chrono,
)
raw_data = StringIO(
"""
user,item,label,time
4617,296,2,964138229
4617,296,2,964138221
4617,296,2,964138222
1298,208,4,974849526
45... | 1 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
massquantity/LibRecommender | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | train | train | tests/utils_pred.py | ptest_preds | assert | numeric_literal | 24 | from libreco.prediction import predict_data_with_feats
def ptest_preds(model, task, pd_data, with_feats):
user = pd_data.user.iloc[0]
item = pd_data.item.iloc[0]
pred = model.predict(user=user, item=item)
# prediction in range
if task == "rating":
assert 1 <= pred <= 5
else:
ass... | 5 | b0aef08fabb80738dacf160451dae8f7ea5eef25 | 80 | v2_extractor_at_anchor |
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