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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_distillation.py | test_distill_removal_pattern | pytest.raises | variable | 64 | from __future__ import annotations
import json
from importlib import import_module
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from pytest import LogCaptureFixture
from transformers import AutoModel, BertTokenizerFast
from model2vec.distill.distillation import (
clean_and_create_v... | ValueError) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_distillation.py | test__post_process_embeddings | assert | variable | 46 | from __future__ import annotations
import json
from importlib import import_module
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from pytest import LogCaptureFixture
from transformers import AutoModel, BertTokenizerFast
from model2vec.distill.distillation import (
clean_and_create_v... | expected_shape | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_distillation.py | test_clean_and_create_vocabulary | assert | variable | 47 | from __future__ import annotations
import json
from importlib import import_module
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from pytest import LogCaptureFixture
from transformers import AutoModel, BertTokenizerFast
from model2vec.distill.distillation import (
clean_and_create_v... | expected_output | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_distillation.py | test_distill_removal_pattern | assert | variable | 50 | from __future__ import annotations
import json
from importlib import import_module
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from pytest import LogCaptureFixture
from transformers import AutoModel, BertTokenizerFast
from model2vec.distill.distillation import (
clean_and_create_v... | expected_vocab_size | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_distillation.py | test_distill_from_model | assert | complex_expr | 74 | from __future__ import annotations
import json
from importlib import import_module
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from pytest import LogCaptureFixture
from transformers import AutoModel, BertTokenizerFast
from model2vec.distill.distillation import (
clean_and_create_v... | static_model2.config | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_distillation.py | test_distill_from_model | assert | complex_expr | 73 | from __future__ import annotations
import json
from importlib import import_module
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from pytest import LogCaptureFixture
from transformers import AutoModel, BertTokenizerFast
from model2vec.distill.distillation import (
clean_and_create_v... | static_model2.embedding.shape | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_distillation.py | test_distill_from_model | assert | complex_expr | 76 | from __future__ import annotations
import json
from importlib import import_module
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from pytest import LogCaptureFixture
from transformers import AutoModel, BertTokenizerFast
from model2vec.distill.distillation import (
clean_and_create_v... | static_model2.base_model_name | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_distillation.py | test_distill | assert | complex_expr | 90 | from __future__ import annotations
import json
from importlib import import_module
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from pytest import LogCaptureFixture
from transformers import AutoModel, BertTokenizerFast
from model2vec.distill.distillation import (
clean_and_create_v... | static_model.config["tokenizer_name"] | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_distillation.py | test_distill_from_model | assert | func_call | 75 | from __future__ import annotations
import json
from importlib import import_module
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from pytest import LogCaptureFixture
from transformers import AutoModel, BertTokenizerFast
from model2vec.distill.distillation import (
clean_and_create_v... | json.loads(static_model2.tokenizer.to_str()) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_inference.py | test_init_predict_proba | assert | numeric_literal | 13 | import os
import re
from tempfile import TemporaryDirectory
from unittest.mock import patch
import pytest
from model2vec.inference import StaticModelPipeline
def test_init_predict_proba(mock_inference_pipeline: StaticModelPipeline) -> None:
"""Test successful init and predict_proba with StaticModelPipeline."""
... | 1 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_inference.py | test_init_predict_proba | assert | collection | 14 | import os
import re
from tempfile import TemporaryDirectory
from unittest.mock import patch
import pytest
from model2vec.inference import StaticModelPipeline
def test_init_predict_proba(mock_inference_pipeline: StaticModelPipeline) -> None:
"""Test successful init and predict_proba with StaticModelPipeline."""
... | [1] | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_inference.py | test_init_predict | assert | variable | 24 | import os
import re
from tempfile import TemporaryDirectory
from unittest.mock import patch
import pytest
from model2vec.inference import StaticModelPipeline
def test_init_predict(mock_inference_pipeline: StaticModelPipeline) -> None:
"""Test successful init and predict with StaticModelPipeline."""
target: l... | target | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_inference.py | test_roundtrip_save_mock_trust_pattern | pytest.raises | variable | 16 | import os
import re
from tempfile import TemporaryDirectory
from unittest.mock import patch
import pytest
from model2vec.inference import StaticModelPipeline
@patch("model2vec.inference.model._DEFAULT_TRUST_PATTERN", re.compile("torch"))
def test_roundtrip_save_mock_trust_pattern(mock_inference_pipeline: StaticModel... | ValueError) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_inference.py | test_roundtrip_save_file_gone | pytest.raises | variable | 17 | import os
import re
from tempfile import TemporaryDirectory
from unittest.mock import patch
import pytest
from model2vec.inference import StaticModelPipeline
def test_roundtrip_save_file_gone(mock_inference_pipeline: StaticModelPipeline) -> None:
"""Test saving and loading the pipeline."""
with TemporaryDire... | FileNotFoundError) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_initialization | assert | numeric_literal | 16 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_initialization(mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]) -> None:
"""Test succes... | 5 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_encode_as_sequence | assert | numeric_literal | 19 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_encode_as_sequence(mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]) -> None:
"""Test en... | 2 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_encode_single_sentence | assert | collection | 18 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_encode_single_sentence(
mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]
) -> None:
... | (2,) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_initialization | assert | collection | 15 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_initialization(mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]) -> None:
"""Test succes... | (5, 2) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_encode_multiple_sentences | assert | collection | 18 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_encode_multiple_sentences(
mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]
) -> None:
... | (2, 2) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_encode_as_sequence_multiprocessing | assert | numeric_literal | 20 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_encode_as_sequence_multiprocessing(
mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]
) -... | 15_000 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_load_pretrained_quantized | assert | complex_expr | 25 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_load_pretrained_quantized(
tmp_path: Path, mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, s... | np.int8 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_local_load_from_model | assert | complex_expr | 21 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_local_load_from_model(mock_tokenizer: Tokenizer) -> None:
"""Test local load from a model."""
x = np.ones((mock_toke... | x.shape | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_normalize | assert_* | variable | 22 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_normalize(mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]) -> None:
"""Test normalizati... | expected) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_encode_multiprocessing | assert | collection | 20 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_encode_multiprocessing(
mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]
) -> None:
... | (15000, 2) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_load_pretrained_quantized | assert | complex_expr | 32 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_load_pretrained_quantized(
tmp_path: Path, mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, s... | np.float16 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_load_pretrained_quantized | assert | complex_expr | 38 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_load_pretrained_quantized(
tmp_path: Path, mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, s... | np.float32 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_initialization | assert | variable | 18 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_initialization(mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]) -> None:
"""Test succes... | mock_config | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_tokenize | assert | variable | 20 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_tokenize(mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]) -> None:
"""Test tokenization... | tokens_slow | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_model.py | test_load_pretrained_dim | pytest.raises | variable | 37 | from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pytest
import safetensors
from tokenizers import Tokenizer
from model2vec import StaticModel
def test_load_pretrained_dim(
tmp_path: Path, mock_vectors: np.ndarray, mock_tokenizer: Tokenizer, mock_config: dict[str, str]
) ... | ValueError) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_quantization.py | test_quantize_embeddings | assert | variable | 24 | import numpy as np
import pytest
from model2vec.quantization import DType, quantize_embeddings
@pytest.mark.parametrize(
"input_dtype,target_dtype,expected_dtype",
[
(np.float32, DType.Float16, np.float16),
(np.float16, DType.Float32, np.float32),
(np.float32, DType.Float64, np.float64... | expected_dtype | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_process_tokenizer | assert | numeric_literal | 19 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | 5 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_process_tokenizer | assert | numeric_literal | 20 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | 6 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_process_tokenizer | assert | variable | 23 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | y | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_process_unigram | assert | numeric_literal | 26 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | 0 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_replace_pretokenizer | assert | string_literal | 17 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | "▁" | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_fix_single_pretokenizer | assert | none_literal | 19 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | None | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_replace_pretokenizer | assert | bool_literal | 27 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | False | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_create_tokenizer | assert | numeric_literal | 15 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | 29525 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_calculate_token_weight_for_unigram | assert | variable | 26 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | weight | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_create_tokenizer | assert | collection | 16 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | [29524] | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_process_tokenizer | assert | string_literal | 18 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | "Unigram" | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_tokenizer.py | test_replace_normalizer | assert | string_literal | 16 | import json
import pytest
from transformers import PreTrainedTokenizerFast
from model2vec.tokenizer.model import _calculate_token_weight_for_unigram, _process_unigram, process_tokenizer
from model2vec.tokenizer.normalizer import replace_normalizer
from model2vec.tokenizer.pretokenizer import _FORBIDDEN_PRETOKENIZERS,... | "Sequence" | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_init_predict | assert | numeric_literal | 28 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | 2 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_tokenize | assert | numeric_literal | 18 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | 0 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_convert_to_pipeline | assert | variable | 23 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | b | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_predict_proba | assert | collection | 17 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | (2, 2) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_train_test_split | assert | func_call | 19 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | len(a) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_train_test_split | assert | func_call | 20 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | len(b) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_predict | assert | collection | 26 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | [1, 1] | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_encode | assert | collection | 17 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | (2, 12) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_init_predict | assert | complex_expr | 21 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | s.classes_ | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_init_predict | assert | collection | 22 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | ["0", "1"] | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_predict | assert | collection | 24 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | ["b", "b"] | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_textdataset_init_incorrect | pytest.raises | variable | 16 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | ValueError) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_trainable.py | test_predict | assert | collection | 21 | from tempfile import TemporaryDirectory
import numpy as np
import pytest
import torch
from tokenizers import Tokenizer
from transformers import AutoTokenizer
from model2vec.model import StaticModel
from model2vec.train import StaticModelForClassification
from model2vec.train.base import FinetunableStaticModel, TextDa... | [[0, 1], [0, 1]] | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_utils.py | test_local_load_mismatch | assert | numeric_literal | 33 | from __future__ import annotations
import json
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from typing import Any
from unittest.mock import patch
import numpy as np
import pytest
import safetensors
import safetensors.numpy
from tokenizers import Tokenizer
from model2vec.disti... | 1 | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_utils.py | test__get_metadata_from_readme_not_exists | assert | collection | 22 | from __future__ import annotations
import json
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from typing import Any
from unittest.mock import patch
import numpy as np
import pytest
import safetensors
import safetensors.numpy
from tokenizers import Tokenizer
from model2vec.disti... | {} | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_utils.py | test__get_metadata_from_readme_mocked_file_keys | assert | func_call | 25 | from __future__ import annotations
import json
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from typing import Any
from unittest.mock import patch
import numpy as np
import pytest
import safetensors
import safetensors.numpy
from tokenizers import Tokenizer
from model2vec.disti... | set() | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_utils.py | test__get_metadata_from_readme_mocked_file | assert | string_literal | 25 | from __future__ import annotations
import json
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from typing import Any
from unittest.mock import patch
import numpy as np
import pytest
import safetensors
import safetensors.numpy
from tokenizers import Tokenizer
from model2vec.disti... | "value" | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_utils.py | test_local_load | assert | complex_expr | 41 | from __future__ import annotations
import json
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from typing import Any
from unittest.mock import patch
import numpy as np
import pytest
import safetensors
import safetensors.numpy
from tokenizers import Tokenizer
from model2vec.disti... | x.shape | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_utils.py | test_select_optimal_device | assert | variable | 40 | from __future__ import annotations
import json
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from typing import Any
from unittest.mock import patch
import numpy as np
import pytest
import safetensors
import safetensors.numpy
from tokenizers import Tokenizer
from model2vec.disti... | expected | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_utils.py | test_importable | pytest.raises | variable | 22 | from __future__ import annotations
import json
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from typing import Any
from unittest.mock import patch
import numpy as np
import pytest
import safetensors
import safetensors.numpy
from tokenizers import Tokenizer
from model2vec.disti... | ImportError) | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_utils.py | test_local_load | assert | func_call | 40 | from __future__ import annotations
import json
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from typing import Any
from unittest.mock import patch
import numpy as np
import pytest
import safetensors
import safetensors.numpy
from tokenizers import Tokenizer
from model2vec.disti... | mock_tokenizer.to_str() | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/model2vec | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | train | train | tests/test_utils.py | test_get_package_extras | assert | collection | 23 | from __future__ import annotations
import json
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from typing import Any
from unittest.mock import patch
import numpy as np
import pytest
import safetensors
import safetensors.numpy
from tokenizers import Tokenizer
from model2vec.disti... | {"torch", "transformers", "scikit-learn"} | 4867cb86e955e462fe3659b01903f69bbc88180b | 36 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_selected_with_duplicates_dicts | assert | numeric_literal | 22 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_selected_with_duplicates_dicts() -> None:
"""Test selected_with_duplicates for dicts."""
selected = {"id": 0, "text": "hello"}
d = DeduplicationResult(
... | 1 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_selected_with_duplicates_cache_invalidation_on_rethreshold | assert | numeric_literal | 22 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_selected_with_duplicates_cache_invalidation_on_rethreshold() -> None:
"""Test that rethreshold invalidates the selected_with_duplicates cache."""
d = Dedupli... | 3 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_rethreshold_empty | assert | collection | 12 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_rethreshold_empty() -> None:
"""Test rethresholding the duplicates."""
d = DuplicateRecord("a", False, [])
d._rethreshold(0.85)
assert d.duplicates ... | [] | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_deduplication_scoring | assert | numeric_literal | 15 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_deduplication_scoring() -> None:
"""Test the deduplication scoring."""
d = DeduplicationResult(
["a", "b", "c"],
[DuplicateRecord("a", False,... | 0.4 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_deduplication_scoring_exact | assert | numeric_literal | 15 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_deduplication_scoring_exact() -> None:
"""Test the deduplication scoring."""
d = DeduplicationResult(
["a", "b", "c"],
[DuplicateRecord("a", ... | 0.2 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_deduplication_scoring_exact_empty | assert | numeric_literal | 11 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_deduplication_scoring_exact_empty() -> None:
"""Test the deduplication scoring."""
d = DeduplicationResult([], [], 0.8, columns=["text"])
assert d.exact... | 0.0 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_selected_with_duplicates_dicts | assert | collection | 26 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_selected_with_duplicates_dicts() -> None:
"""Test selected_with_duplicates for dicts."""
selected = {"id": 0, "text": "hello"}
d = DeduplicationResult(
... | {1, 2} | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_selected_with_duplicates_caching | assert | variable | 23 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_selected_with_duplicates_caching() -> None:
"""Test that selected_with_duplicates is properly cached."""
d = DeduplicationResult(
selected=["original... | result2 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_selected_with_duplicates_strings | assert | variable | 25 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_selected_with_duplicates_strings() -> None:
"""Test selected_with_duplicates for strings."""
d = DeduplicationResult(
selected=["original"],
... | expected | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_selected_with_duplicates_dicts | assert | variable | 25 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_selected_with_duplicates_dicts() -> None:
"""Test selected_with_duplicates for dicts."""
selected = {"id": 0, "text": "hello"}
d = DeduplicationResult(
... | selected | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_datamodels.py | test_selected_with_duplicates_removes_internal_duplicates | assert | variable | 32 | import pytest
import semhash
import semhash.version
from semhash.datamodels import DeduplicationResult, DuplicateRecord, SelectedWithDuplicates
def test_selected_with_duplicates_removes_internal_duplicates() -> None:
"""Test that selected_with_duplicates removes internal duplicates that have the same hash."""
... | filtered | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_self_find_representative | assert | numeric_literal | 17 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_self_find_representative(use_ann: bool, model: Encoder, train_texts: list[str]) -> None:
"""Test the self_find_representative method."""
semhash = SemHash.from_re... | 3 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_filter_outliers | assert | numeric_literal | 13 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_filter_outliers(use_ann: bool, model: Encoder, train_texts: list[str], test_texts: list[str]) -> None:
"""Test the filter_outliers method."""
semhash = SemHash.fr... | 2 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_multi_dataset_deduplication | assert | collection | 33 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_multi_dataset_deduplication(use_ann: bool, model: Encoder) -> None:
"""Test deduplication across two datasets."""
# No duplicates
texts1 = [
"It's dan... | [] | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_single_dataset_deduplication | assert | variable | 20 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_single_dataset_deduplication(use_ann: bool, model: Encoder) -> None:
"""Test single dataset deduplication."""
# No duplicates
texts = [
"It's dangerou... | texts | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_multi_dataset_deduplication | assert | variable | 24 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_multi_dataset_deduplication(use_ann: bool, model: Encoder) -> None:
"""Test deduplication across two datasets."""
# No duplicates
texts1 = [
"It's dan... | texts2 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test__diversify | assert | collection | 25 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test__diversify(monkeypatch: pytest.MonkeyPatch) -> None:
"""Test the _diversify method."""
from semhash import semhash
semhash_instance = SemHash(index=None, mod... | ["a", "b"] | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_from_records_without_columns | pytest.raises | variable | 15 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_from_records_without_columns(use_ann: bool, model: Encoder) -> None:
"""Test fitting without specifying columns."""
records = [
{"question": "What is the ... | ValueError) | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_self_filter_outliers | assert | collection | 16 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_self_filter_outliers(use_ann: bool, model: Encoder, train_texts: list[str]) -> None:
"""Test the self_filter_outliers method."""
semhash = SemHash.from_records(re... | {"car", "bicycle"} | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_filter_outliers | assert | func_call | 14 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_filter_outliers(use_ann: bool, model: Encoder, train_texts: list[str], test_texts: list[str]) -> None:
"""Test the filter_outliers method."""
semhash = SemHash.fr... | len(test_texts) - 2 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_self_filter_outliers | assert | func_call | 14 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_self_filter_outliers(use_ann: bool, model: Encoder, train_texts: list[str]) -> None:
"""Test the self_filter_outliers method."""
semhash = SemHash.from_records(re... | len(train_texts) - 2 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_from_embeddings | assert | func_call | 28 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_from_embeddings(use_ann: bool, model: Encoder, train_texts: list[str]) -> None:
"""Test from_embeddings constructor with validation and comparison to from_records."""... | len(result2.selected) | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_from_embeddings | assert | func_call | 29 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_from_embeddings(use_ann: bool, model: Encoder, train_texts: list[str]) -> None:
"""Test from_embeddings constructor with validation and comparison to from_records."""... | len(result2.filtered) | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_semhash.py | test_filter_outliers | assert | collection | 16 | import numpy as np
import pytest
from semhash import SemHash
from semhash.datamodels import FilterResult
from semhash.utils import Encoder
def test_filter_outliers(use_ann: bool, model: Encoder, train_texts: list[str], test_texts: list[str]) -> None:
"""Test the filter_outliers method."""
semhash = SemHash.fr... | {"motorcycle", "plane"} | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_remove_exact_duplicates | assert | numeric_literal | 24 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_remove_exact_duplicates() -> None:
"""Test exact duplicate removal."""
records... | 2 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_remove_exact_duplicates | assert | numeric_literal | 25 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_remove_exact_duplicates() -> None:
"""Test exact duplicate removal."""
records... | 1 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_compute_candidate_limit | assert | numeric_literal | 20 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_compute_candidate_limit() -> None:
"""Test candidate limit computation."""
# B... | 50 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_compute_candidate_limit | assert | numeric_literal | 18 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_compute_candidate_limit() -> None:
"""Test candidate limit computation."""
# B... | 100 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_compute_candidate_limit | assert | numeric_literal | 22 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_compute_candidate_limit() -> None:
"""Test candidate limit computation."""
# B... | 1000 | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_prepare_records | assert | bool_literal | 20 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_prepare_records() -> None:
"""Test preparing records."""
# String records
... | True | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_prepare_records | assert | bool_literal | 27 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_prepare_records() -> None:
"""Test preparing records."""
# String records
... | False | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_to_frozendict | assert | variable | 20 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_to_frozendict() -> None:
"""Test converting dict to frozendict."""
record = {"... | result | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_prepare_records | assert | variable | 29 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_prepare_records() -> None:
"""Test preparing records."""
# String records
... | records | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_featurize | assert | collection | 19 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_featurize(model: Encoder) -> None:
"""Test featurizing records."""
records = [... | (2, 128) | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_prepare_records | assert | collection | 21 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_prepare_records() -> None:
"""Test preparing records."""
# String records
... | ["text"] | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
MinishLab/semhash | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | train | train | tests/test_utils.py | test_remove_exact_duplicates | assert | collection | 26 | import numpy as np
import pytest
from frozendict import frozendict
from semhash.utils import (
Encoder,
compute_candidate_limit,
featurize,
prepare_records,
remove_exact_duplicates,
to_frozendict,
)
def test_remove_exact_duplicates() -> None:
"""Test exact duplicate removal."""
records... | {"text": "hello", "id": "3"} | feccbb996fb29193929bcfd98ee6ad24a8855b9d | 15 | v2_extractor_at_anchor |
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