inputs stringlengths 312 52k | targets stringlengths 1 3.1k ⌀ | block_type stringclasses 11
values | scenario stringclasses 7
values |
|---|---|---|---|
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | TRY | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | TRY | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | TRY | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | TRY | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | TRY | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | TRY | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | WHILE | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | WHILE | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | WHILE | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | CATCH | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | CATCH | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/utils.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | null | CATCH | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/math.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/l... | null | ANNOTATION | complete_current_header_empty_completion |
<filename>camp_zipnerf/internal/math.py<fim_prefix># coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/l... | null | ANNOTATION | complete_current_header_empty_completion |
<filename>microagents/agents/agent_persistence_manager.py<fim_prefix>from agents.agent_serializer import AgentSerializer
from integrations.memoize import memoize_to_sqlite
from integrations.sqlite_agent_persistence import SQLiteAgentPersistence
class AgentPersistenceManager:
def __init__(self, db_filename="agents... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/integrations/sqlite_agent_persistence.py<fim_prefix>import sqlite3
import json
from integrations.agent_persistence import AbstractAgentPersistence
class SQLiteAgentPersistence(AbstractAgentPersistence):
def __init__(self, filename="agents.db"):
self.filename = filename
self._i... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/agents/agent_lifecycle.py<fim_prefix>import logging
from typing import List
from agents.microagent import MicroAgent
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_similarity import AgentSimilarity
from agents.agent_persistence_manager import AgentPersistenceManager
from... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/agents/agent_lifecycle.py<fim_prefix>import logging
from typing import List
from agents.microagent import MicroAgent
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_similarity import AgentSimilarity
from agents.agent_persistence_manager import AgentPersistenceManager
from... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/integrations/memoize.py<fim_prefix>import sqlite3
import hashlib
import json
import functools
## Originally from https://www.kevinkatz.io/posts/memoize-to-sqlite
def memoize_to_sqlite(func_name: str, filename: str = "cache.db"):
""<fim_suffix>"
Memoization decorator that caches the outpu... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/agents/agent_lifecycle.py<fim_prefix>import logging
from typing import List
from agents.microagent import MicroAgent
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_similarity import AgentSimilarity
from agents.agent_persistence_manager import AgentPersistenceManager
from... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/agents/microagent_manager.py<fim_prefix>import logging
from typing import List, Optional, Any
from agents.agent_lifecycle import AgentLifecycle
from agents.agent_similarity import AgentSimilarity
from agents.agent_persistence_manager import AgentPersistenceManager
from integrations.openaiwrappe... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/agents/microagent_manager.py<fim_prefix>import logging
from typing import List, Optional, Any
from agents.agent_lifecycle import AgentLifecycle
from agents.agent_similarity import AgentSimilarity
from agents.agent_persistence_manager import AgentPersistenceManager
from integrations.openaiwrappe... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | BLOCK_COMMENT | complete_current_header_empty_completion |
<filename>microagents/agents/microagent.py<fim_prefix>import logging
import uuid
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_evaluation import AgentEvaluator
from agents.agent_response import AgentResponse
from agents.agent_similarity import AgentSimilarity
from agents.response_extraction ... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/agents/microagent.py<fim_prefix>import logging
import uuid
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_evaluation import AgentEvaluator
from agents.agent_response import AgentResponse
from agents.agent_similarity import AgentSimilarity
from agents.response_extraction ... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/integrations/memoize.py<fim_prefix>import sqlite3
import hashlib
import json
import functools
## Originally from https://www.kevinkatz.io/posts/memoize-to-sqlite
def memoize_to_sqlite(func_name: str, filename: str = "cache.db"):
"""
Memoization decorator that caches the output of a metho... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/agents/microagent.py<fim_prefix>import logging
import uuid
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_evaluation import AgentEvaluator
from agents.agent_response import AgentResponse
from agents.agent_similarity import AgentSimilarity
from agents.response_extraction ... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/integrations/sqlite_agent_persistence.py<fim_prefix>import sqlite3
import json
from integrations.agent_persistence import AbstractAgentPersistence
class SQLiteAgentPersistence(AbstractAgentPersistence):
def __init__(self, filename="agents.db"):
self.filename = filename
self._i... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/integrations/memoize.py<fim_prefix>import sqlite3
import hashlib
import json
import functools
## Originally from https://www.kevinkatz.io/posts/memoize-to-sqlite
def memoize_to_sqlite(func_name: str, filename: str = "cache.db"):
"""
Memoization decorator that caches the output of a metho... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/agents/microagent.py<fim_prefix>import logging
import uuid
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_evaluation import AgentEvaluator
from agents.agent_response import AgentResponse
from agents.agent_similarity import AgentSimilarity
from agents.response_extraction ... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/integrations/memoize.py<fim_prefix>import sqlite3
import hashlib
import json
import functools
## Originally from https://www.kevinkatz.io/posts/memoize-to-sqlite
def memoize_to_sqlite(func_name: str, filename: str = "cache.db"):
"""
Memoization decorator that caches the output of a metho... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/agents/microagent.py<fim_prefix>import logging
import uuid
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_evaluation import AgentEvaluator
from agents.agent_response import AgentResponse
from agents.agent_similarity import AgentSimilarity
from agents.response_extraction ... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microagents/agents/agent_lifecycle.py<fim_prefix>import logging
from typing import List
from agents.microagent import MicroAgent
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_similarity import AgentSimilarity
from agents.agent_persistence_manager import AgentPersistenceManager
from... | null | TRY | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | TRY | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | TRY | complete_current_header_empty_completion |
<filename>microagents/agents/agent_lifecycle.py<fim_prefix>import logging
from typing import List
from agents.microagent import MicroAgent
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_similarity import AgentSimilarity
from agents.agent_persistence_manager import AgentPersistenceManager
from... | null | TRY | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | CATCH | complete_current_header_empty_completion |
<filename>microagents/agents/agent_lifecycle.py<fim_prefix>import logging
from typing import List
from agents.microagent import MicroAgent
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_similarity import AgentSimilarity
from agents.agent_persistence_manager import AgentPersistenceManager
from... | null | CATCH | complete_current_header_empty_completion |
<filename>microagents/agents/agent_lifecycle.py<fim_prefix>import logging
from typing import List
from agents.microagent import MicroAgent
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_similarity import AgentSimilarity
from agents.agent_persistence_manager import AgentPersistenceManager
from... | null | CATCH | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | CATCH | complete_current_header_empty_completion |
<filename>microagents/agents/agent_persistence_manager.py<fim_prefix>from agents.agent_serializer import AgentSerializer
from integrations.memoize import memoize_to_sqlite
from integrations.sqlite_agent_persistence import SQLiteAgentPersistence
class AgentPersistenceManager:
def __init__(self, db_filename="agents... | null | FOR | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | FOR | complete_current_header_empty_completion |
<filename>microagents/agents/microagent.py<fim_prefix>import logging
import uuid
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_evaluation import AgentEvaluator
from agents.agent_response import AgentResponse
from agents.agent_similarity import AgentSimilarity
from agents.response_extraction ... | null | IF | complete_current_header_empty_completion |
<filename>microagents/agents/microagent.py<fim_prefix>import logging
import uuid
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_evaluation import AgentEvaluator
from agents.agent_response import AgentResponse
from agents.agent_similarity import AgentSimilarity
from agents.response_extraction ... | null | IF | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | IF | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | IF | complete_current_header_empty_completion |
<filename>microagents/agents/agent_similarity.py<fim_prefix>import logging
import numpy as np
from typing import List, Tuple, Optional
from sklearn.metrics.pairwise import cosine_similarity
from integrations.openaiwrapper import OpenAIAPIWrapper
logger = logging.getLogger()
class Agent:
def __init__(self, purpos... | null | IF | complete_current_header_empty_completion |
<filename>microagents/integrations/memoize.py<fim_prefix>import sqlite3
import hashlib
import json
import functools
## Originally from https://www.kevinkatz.io/posts/memoize-to-sqlite
def memoize_to_sqlite(func_name: str, filename: str = "cache.db"):
"""
Memoization decorator that caches the output of a metho... | null | IF | complete_current_header_empty_completion |
<filename>microagents/agents/agent_persistence_manager.py<fim_prefix>from agents.agent_serializer import AgentSerializer
from integrations.memoize import memoize_to_sqlite
from integrations.sqlite_agent_persistence import SQLiteAgentPersistence
class AgentPersistenceManager:
def __init__(self, db_filename="agents... | null | IF | complete_current_header_empty_completion |
<filename>microagents/agents/microagent.py<fim_prefix>import logging
import uuid
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_evaluation import AgentEvaluator
from agents.agent_response import AgentResponse
from agents.agent_similarity import AgentSimilarity
from agents.response_extraction ... | null | IF | complete_current_header_empty_completion |
<filename>microagents/integrations/memoize.py<fim_prefix>import sqlite3
import hashlib
import json
import functools
## Originally from https://www.kevinkatz.io/posts/memoize-to-sqlite
def memoize_to_sqlite(func_name: str, filename: str = "cache.db"):
"""
Memoization decorator that caches the output of a metho... | null | METHOD | complete_current_header_empty_completion |
<filename>microagents/integrations/memoize.py<fim_prefix>import sqlite3
import hashlib
import json
import functools
## Originally from https://www.kevinkatz.io/posts/memoize-to-sqlite
def memoize_to_sqlite(func_name: str, filename: str = "cache.db"):
"""
Memoization decorator that caches the output of a metho... | null | METHOD | complete_current_header_empty_completion |
<filename>microagents/integrations/memoize.py<fim_prefix>import sqlite3
import hashlib
import json
import functools
## Originally from https://www.kevinkatz.io/posts/memoize-to-sqlite
def memoize_to_sqlite(func_name: str, filename: str = "cache.db"):
"""
Memoization decorator that caches the output of a metho... | null | METHOD | complete_current_header_empty_completion |
<filename>microagents/integrations/sqlite_agent_persistence.py<fim_prefix>import sqlite3
import json
from integrations.agent_persistence import AbstractAgentPersistence
class SQLiteAgentPersistence(AbstractAgentPersistence):
def __init__(self, filename="agents.db"):
self.filename = filename
self._i... | null | LINE_COMMENT | complete_current_header_empty_completion |
<filename>microagents/agents/microagent.py<fim_prefix>import logging
import uuid
from integrations.openaiwrapper import OpenAIAPIWrapper
from agents.agent_evaluation import AgentEvaluator
from agents.agent_response import AgentResponse
from agents.agent_similarity import AgentSimilarity
from agents.response_extraction ... | null | LINE_COMMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] <fim_suffix>+= score
else:
... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | STATEMENT | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | FOR | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.<fim_suffix>items():
if url in old:
old[url] += score
else:
... | null | FOR | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | FOR | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | FOR | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in old:
old[url] += score
else:
old[u... | null | FOR | complete_current_header_empty_completion |
<filename>microsearch/src/microsearch/engine.py<fim_prefix>from collections import defaultdict
from math import log
import string
def update_url_scores(old: dict[str, float], new: dict[str, float]):
for url, score in new.items():
if url in ol<fim_suffix>d:
old[url] += score
else:
... | null | IF | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/line_parser.py<fim_prefix>import datetime
import logging
import math
import re
import string
from nltk.corpus import stopwords
from .patterns import abbreviations
from .patterns import states
from .patterns import states_abbreviations
from .styling_utils import mode_of_lis... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/processors.py<fim_prefix>import logging
import re
from collections import Counter
from collections import defaultdict
from . import formatter
from . import line_parser
from . import patterns
from nlm_ingestor.ingestor_utils import spell_utils
from nlm_ingestor.ingestor_util... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/processors.py<fim_prefix>import logging
import re
from collections import Counter
from collections import defaultdict
from . import formatter
from . import line_parser
from . import patterns
from nlm_ingestor.ingestor_utils import spell_utils
from nlm_ingestor.ingestor_util... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/line_parser.py<fim_prefix>import datetime
import logging
import math
import re
import string
from nltk.corpus import stopwords
from .patterns import abbreviations
from .patterns import states
from .patterns import states_abbreviations
from .styling_utils import mode_of_lis... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/line_parser.py<fim_prefix>import datetime
import logging
import math
import re
import string
from nltk.corpus import stopwords
from .patterns import abbreviations
from .patterns import states
from .patterns import states_abbreviations
from .styling_utils import mode_of_lis... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/line_parser.py<fim_prefix>import datetime
import logging
import math
import re
import string
from nltk.corpus import stopwords
from .patterns import abbreviations
from .patterns import states
from .patterns import states_abbreviations
from .styling_utils import mode_of_lis... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/utils.py<fim_prefix>import json
import re
import numpy as np
from nltk import load
from nltk import PunktSentenceTokenizer
nltk_abbs = load("tokenizers/punkt/{}.pickle".format("english"))._params.abbrev_types
class NpEncoder(json.JSONEncoder):
def default(self... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/line_parser.py<fim_prefix>import datetime
import logging
import math
import re
import string
from nltk.corpus import stopwords
from .patterns import abbreviations
from .patterns import states
from .patterns import states_abbreviations
from .styling_utils import mode_of_lis... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/spell_utils.py<fim_prefix>import logging
import os
import string
from symspellpy.symspellpy import SymSpell
from symspellpy.symspellpy import Verbosity
import nlm_ingestor.ingestor as ingestor
from nlm_ingestor.ingestor import patterns
logger = logging.getLogger(__n... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/utils.py<fim_prefix>import json
import re
import numpy as np
from nltk import load
from nltk import PunktSentenceTokenizer
nltk_abbs = load("tokenizers/punkt/{}.pickle".format("english"))._params.abbrev_types
class NpEncoder(json.JSONEncoder):
def default(self... | null | STATEMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/processors.py<fim_prefix>import logging
import re
from collections import Counter
from collections import defaultdict
from . import formatter
from . import line_parser
from . import patterns
from nlm_ingestor.ingestor_utils import spell_utils
from nlm_ingestor.ingestor_util... | null | IF | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/processors.py<fim_prefix>import logging
import re
from collections import Counter
from collections import defaultdict
from . import formatter
from . import line_parser
from . import patterns
from nlm_ingestor.ingestor_utils import spell_utils
from nlm_ingestor.ingestor_util... | null | IF | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/spell_utils.py<fim_prefix>import logging
import os
import string
from symspellpy.symspellpy import SymSpell
from symspellpy.symspellpy import Verbosity
import nlm_ingestor.ingestor as ingestor
from nlm_ingestor.ingestor import patterns
logger = logging.getLogger(__n... | null | IF | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/line_parser.py<fim_prefix>import datetime
import logging
import math
import re
import string
from nltk.corpus import stopwords
from .patterns import abbreviations
from .patterns import states
from .patterns import states_abbreviations
from .styling_utils import mode_of_lis... | null | IF | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/processors.py<fim_prefix>import logging
import re
from collections import Counter
from collections import defaultdict
from . import formatter
from . import line_parser
from . import patterns
from nlm_ingestor.ingestor_utils import spell_utils
from nlm_ingestor.ingestor_util... | null | IF | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/line_parser.py<fim_prefix>import datetime
import logging
import math
import re
import string
from nltk.corpus import stopwords
from .patterns import abbreviations
from .patterns import states
from .patterns import states_abbreviations
from .styling_utils import mode_of_lis... | null | IF | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/line_parser.py<fim_prefix>import datetime
import logging
import math
import re
import string
from nltk.corpus import stopwords
from .patterns import abbreviations
from .patterns import states
from .patterns import states_abbreviations
from .styling_utils import mode_of_lis... | null | IF | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/utils.py<fim_prefix>import json
import re
import numpy as np
from nltk import load
from nltk import PunktSentenceTokenizer
nltk_abbs = load("tokenizers/punkt/{}.pickle".format("english"))._params.abbrev_types
class NpEncoder(json.JSONEncoder):
def default(self... | null | FOR | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/utils.py<fim_prefix>import json
import re
import numpy as np
from nltk import load
from nltk import PunktSentenceTokenizer
nltk_abbs = load("tokenizers/punkt/{}.pickle".format("english"))._params.abbrev_types
class NpEncoder(json.JSONEncoder):
def default(self... | null | FOR | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/processors.py<fim_prefix>import logging
import re
from collections import Counter
from collections import defaultdict
from . import formatter
from . import line_parser
from . import patterns
from nlm_ingestor.ingestor_utils import spell_utils
from nlm_ingestor.ingestor_util... | null | FOR | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/processors.py<fim_prefix>import logging
import re
from collections import Counter
from collections import defaultdict
from . import formatter
from . import line_parser
from . import patterns
from nlm_ingestor.ingestor_utils import spell_utils
from nlm_ingestor.ingestor_util... | null | LINE_COMMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/utils.py<fim_prefix>import json
import re
import numpy as np
from nltk import load
from nltk import PunktSentenceTokenizer
nltk_abbs = load("tokenizers/punkt/{}.pickle".format("english"))._params.abbrev_types
class NpEncoder(json.JSONEncoder):
def default(self... | null | LINE_COMMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/line_parser.py<fim_prefix>import datetime
import logging
import math
import re
import string
from nltk.corpus import stopwords
from .patterns import abbreviations
from .patterns import states
from .patterns import states_abbreviations
from .styling_utils import mode_of_lis... | null | LINE_COMMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/utils.py<fim_prefix>import json
import re
import numpy as np
from nltk import load
from nltk import PunktSentenceTokenizer
nltk_abbs = load("tokenizers/punkt/{}.pickle".format("english"))._params.abbrev_types
class NpEncoder(json.JSONEncoder):
def default(self... | null | LINE_COMMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/utils.py<fim_prefix>import json
import re
import numpy as np
from nltk import load
from nltk import PunktSentenceTokenizer
nltk_abbs = load("tokenizers/punkt/{}.pickle".format("english"))._params.abbrev_types
class NpEncoder(json.JSONEncoder):
def default(self... | null | LINE_COMMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor/processors.py<fim_prefix>import logging
import re
from collections import Counter
from collections import defaultdict
from . import formatter
from . import line_parser
from . import patterns
from nlm_ingestor.ingestor_utils import spell_utils
from nlm_ingestor.ingestor_util... | null | LINE_COMMENT | complete_current_header_empty_completion |
<filename>nlm-ingestor/nlm_ingestor/ingestor_utils/utils.py<fim_prefix>import json
import re
import numpy as np
from nltk import load
from nltk import PunktSentenceTokenizer
nltk_abbs = load("tokenizers/punkt/{}.pickle".format("english"))._params.abbrev_types
class NpEncoder(json.JSONEncoder):
def default(self... | null | LINE_COMMENT | complete_current_header_empty_completion |
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