python_code stringlengths 0 187k | repo_name stringlengths 8 46 | file_path stringlengths 6 135 |
|---|---|---|
import logging
from typing import List
import sqlite3
import multiprocessing
from multiprocessing import Process
from allennlp.common.file_utils import cached_path
logger = logging.getLogger(__name__)
MULTIPROCESSING_LOGGER = multiprocessing.get_logger()
class SqlExecutor:
"""
This class evaluates SQL queri... | allennlp-semparse-master | allennlp_semparse/parsimonious_languages/executors/sql_executor.py |
"""
Executors are classes that deterministically transform programs in domain specific languages
into denotations. We have one executor defined for each language-domain pair that we handle.
"""
from allennlp_semparse.parsimonious_languages.executors.sql_executor import SqlExecutor
| allennlp-semparse-master | allennlp_semparse/parsimonious_languages/executors/__init__.py |
import torch
from allennlp.common.util import JsonDict
from allennlp.data import Instance
from allennlp.predictors.predictor import Predictor
@Predictor.register("wikitables-parser")
class WikiTablesParserPredictor(Predictor):
"""
Wrapper for the
:class:`~allennlp.models.encoder_decoders.wikitables_seman... | allennlp-semparse-master | allennlp_semparse/predictors/wikitables_parser.py |
from allennlp_semparse.predictors.atis_parser import AtisParserPredictor
from allennlp_semparse.predictors.nlvr_parser import NlvrParserPredictor
from allennlp_semparse.predictors.wikitables_parser import WikiTablesParserPredictor
| allennlp-semparse-master | allennlp_semparse/predictors/__init__.py |
from allennlp.common.util import JsonDict
from allennlp.data import Instance
from allennlp.predictors.predictor import Predictor
@Predictor.register("atis-parser")
class AtisParserPredictor(Predictor):
"""
Predictor for the :class:`~allennlp_semparse.models.atis.AtisSemanticParser` model.
"""
def _js... | allennlp-semparse-master | allennlp_semparse/predictors/atis_parser.py |
import json
from allennlp.common.util import JsonDict
from allennlp.data import Instance
from allennlp.predictors.predictor import Predictor
@Predictor.register("nlvr-parser")
class NlvrParserPredictor(Predictor):
def _json_to_instance(self, json_dict: JsonDict) -> Instance:
sentence = json_dict["senten... | allennlp-semparse-master | allennlp_semparse/predictors/nlvr_parser.py |
from allennlp_semparse.models.atis.atis_semantic_parser import AtisSemanticParser
from allennlp_semparse.models.nlvr.nlvr_coverage_semantic_parser import NlvrCoverageSemanticParser
from allennlp_semparse.models.nlvr.nlvr_direct_semantic_parser import NlvrDirectSemanticParser
from allennlp_semparse.models.text2sql_parse... | allennlp-semparse-master | allennlp_semparse/models/__init__.py |
import logging
from typing import Any, Dict, List, Tuple, Optional
from collections import defaultdict
import difflib
import sqlparse
import torch
from allennlp.data import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import Attention, Seq2SeqEncoder, TextFieldEmbedder, Embedding
from all... | allennlp-semparse-master | allennlp_semparse/models/text2sql_parser.py |
from typing import Any, Dict, List, Mapping, Sequence, Tuple
import torch
from allennlp.common.checks import check_dimensions_match
from allennlp.common.util import pad_sequence_to_length
from allennlp.data import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import (
Embedding,
Se... | allennlp-semparse-master | allennlp_semparse/models/wikitables/wikitables_semantic_parser.py |
allennlp-semparse-master | allennlp_semparse/models/wikitables/__init__.py | |
from typing import Any, Dict, List
import torch
from allennlp.data import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import (
Attention,
FeedForward,
Seq2SeqEncoder,
Seq2VecEncoder,
TextFieldEmbedder,
)
from allennlp_semparse.domain_languages import WikiTablesLangua... | allennlp-semparse-master | allennlp_semparse/models/wikitables/wikitables_mml_semantic_parser.py |
import logging
import os
from functools import partial
from typing import Dict, List, Tuple, Set, Any
import torch
from allennlp.data import Vocabulary
from allennlp.models.archival import load_archive, Archive
from allennlp.models.model import Model
from allennlp.modules import (
Attention,
FeedForward,
... | allennlp-semparse-master | allennlp_semparse/models/wikitables/wikitables_erm_semantic_parser.py |
import logging
import os
from functools import partial
from typing import Any, Callable, Dict, List, Tuple, Union
import torch
from allennlp.data.vocabulary import Vocabulary
from allennlp.models.archival import Archive, load_archive
from allennlp.models.model import Model
from allennlp.modules import Attention, Seq2S... | allennlp-semparse-master | allennlp_semparse/models/nlvr/nlvr_coverage_semantic_parser.py |
allennlp-semparse-master | allennlp_semparse/models/nlvr/__init__.py | |
import logging
from typing import Any, Dict, List
import torch
from allennlp.data.vocabulary import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import Attention, Seq2SeqEncoder, TextFieldEmbedder
from allennlp.nn import Activation, util
from allennlp_semparse.domain_languages import NlvrL... | allennlp-semparse-master | allennlp_semparse/models/nlvr/nlvr_direct_semantic_parser.py |
import logging
from typing import Dict, List, Tuple
import torch
from allennlp.data.vocabulary import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import TextFieldEmbedder, Seq2SeqEncoder, Embedding
from allennlp.nn import util
from allennlp.training.metrics import Average
from allennlp_... | allennlp-semparse-master | allennlp_semparse/models/nlvr/nlvr_semantic_parser.py |
allennlp-semparse-master | allennlp_semparse/models/atis/__init__.py | |
import logging
from typing import Any, Dict, Iterable, List, Tuple
import difflib
import sqlparse
import torch
from allennlp.common.util import pad_sequence_to_length
from allennlp.data import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import Attention, Seq2SeqEncoder, TextFieldEmbedder... | allennlp-semparse-master | allennlp_semparse/models/atis/atis_semantic_parser.py |
from collections import defaultdict
from typing import Dict, List, Optional, Set, Tuple, Union
import torch
def construct_prefix_tree(
targets: Union[torch.Tensor, List[List[List[int]]]],
target_mask: Optional[Union[torch.Tensor, List[List[List[int]]]]] = None,
) -> List[Dict[Tuple[int, ...], Set[int]]]:
... | allennlp-semparse-master | allennlp_semparse/state_machines/util.py |
"""
This module contains code for using state machines in a model to do transition-based decoding.
"Transition-based decoding" is where you start in some state, iteratively transition between
states, and have some kind of supervision signal that tells you which end states, or which
transition sequences, are "good".
Ty... | allennlp-semparse-master | allennlp_semparse/state_machines/__init__.py |
from collections import defaultdict
from typing import Dict, Generic, List, TypeVar, Tuple
import torch
from allennlp.common.registrable import FromParams
from allennlp_semparse.state_machines import util
from allennlp_semparse.state_machines.states import State
from allennlp_semparse.state_machines.transition_funct... | allennlp-semparse-master | allennlp_semparse/state_machines/beam_search.py |
from collections import defaultdict
from typing import Dict, List, Optional
import torch
from allennlp_semparse.state_machines import util
from allennlp_semparse.state_machines.states import State
from allennlp_semparse.state_machines.transition_functions import TransitionFunction
class ConstrainedBeamSearch:
"... | allennlp-semparse-master | allennlp_semparse/state_machines/constrained_beam_search.py |
from typing import Callable, Dict, List, TypeVar
from collections import defaultdict
import torch
from allennlp.nn import util as nn_util
from allennlp_semparse.state_machines.states import State
from allennlp_semparse.state_machines.trainers.decoder_trainer import DecoderTrainer
from allennlp_semparse.state_machine... | allennlp-semparse-master | allennlp_semparse/state_machines/trainers/expected_risk_minimization.py |
from typing import Dict, Generic, TypeVar
import torch
from allennlp_semparse.state_machines.states import State
from allennlp_semparse.state_machines.transition_functions import TransitionFunction
SupervisionType = TypeVar("SupervisionType")
class DecoderTrainer(Generic[SupervisionType]):
"""
``DecoderTra... | allennlp-semparse-master | allennlp_semparse/state_machines/trainers/decoder_trainer.py |
from allennlp_semparse.state_machines.trainers.decoder_trainer import DecoderTrainer
from allennlp_semparse.state_machines.trainers.expected_risk_minimization import (
ExpectedRiskMinimization,
)
from allennlp_semparse.state_machines.trainers.maximum_marginal_likelihood import (
MaximumMarginalLikelihood,
)
| allennlp-semparse-master | allennlp_semparse/state_machines/trainers/__init__.py |
import logging
from typing import Dict, List, Tuple
import torch
from allennlp.nn import util
from allennlp_semparse.state_machines.constrained_beam_search import ConstrainedBeamSearch
from allennlp_semparse.state_machines.states import State
from allennlp_semparse.state_machines.trainers.decoder_trainer import Deco... | allennlp-semparse-master | allennlp_semparse/state_machines/trainers/maximum_marginal_likelihood.py |
from collections import defaultdict
from typing import Any, Dict, List, Tuple
import torch
from allennlp.common.checks import check_dimensions_match
from allennlp.modules import Attention, FeedForward
from allennlp.nn import Activation
from allennlp_semparse.state_machines.states import GrammarBasedState
from allen... | allennlp-semparse-master | allennlp_semparse/state_machines/transition_functions/linking_transition_function.py |
"""
This module contains ``TransitionFunctions`` for state-machine-based decoders. The
``TransitionFunction`` parameterizes transitions between ``States``. These ``TransitionFunctions``
are all pytorch `Modules`` that have trainable parameters. The :class:`BasicTransitionFunction` is
simply an LSTM decoder with atte... | allennlp-semparse-master | allennlp_semparse/state_machines/transition_functions/__init__.py |
from typing import Generic, List, Set, TypeVar
import torch
from allennlp_semparse.state_machines.states import State
StateType = TypeVar("StateType", bound=State)
class TransitionFunction(torch.nn.Module, Generic[StateType]):
"""
A ``TransitionFunction`` is a module that assigns scores to state transition... | allennlp-semparse-master | allennlp_semparse/state_machines/transition_functions/transition_function.py |
from collections import defaultdict
from typing import Any, Dict, List, Set, Tuple
import torch
from torch.nn.modules.rnn import LSTM, LSTMCell
from torch.nn.modules.linear import Linear
from allennlp.modules import Attention
from allennlp.nn import util, Activation
from allennlp_semparse.state_machines.states impo... | allennlp-semparse-master | allennlp_semparse/state_machines/transition_functions/basic_transition_function.py |
from collections import defaultdict
from typing import Any, Dict, List, Tuple
import torch
from torch.nn import Parameter
from allennlp.common.checks import check_dimensions_match
from allennlp.modules import Attention, FeedForward
from allennlp.nn import Activation
from allennlp_semparse.state_machines.states impo... | allennlp-semparse-master | allennlp_semparse/state_machines/transition_functions/linking_coverage_transition_function.py |
from collections import defaultdict
from typing import Any, Dict, List, Tuple
import torch
from torch.nn import Parameter
from allennlp.modules import Attention
from allennlp.nn import Activation
from allennlp_semparse.state_machines.states import CoverageState, ChecklistStatelet
from allennlp_semparse.state_machin... | allennlp-semparse-master | allennlp_semparse/state_machines/transition_functions/coverage_transition_function.py |
from typing import Any, List, Sequence
import torch
from allennlp.nn import util
from allennlp_semparse.fields.production_rule_field import ProductionRule
from allennlp_semparse.state_machines.states.checklist_statelet import ChecklistStatelet
from allennlp_semparse.state_machines.states.grammar_based_state import G... | allennlp-semparse-master | allennlp_semparse/state_machines/states/coverage_state.py |
from typing import Callable, Dict, Generic, List, TypeVar
from allennlp.nn import util
ActionRepresentation = TypeVar("ActionRepresentation")
class GrammarStatelet(Generic[ActionRepresentation]):
"""
A ``GrammarStatelet`` keeps track of the currently valid actions at every step of decoding.
This class ... | allennlp-semparse-master | allennlp_semparse/state_machines/states/grammar_statelet.py |
"""
This module contains the ``State`` abstraction for defining state-machine-based decoders, and some
pre-built concrete ``State`` classes for various kinds of decoding (e.g., a ``GrammarBasedState``
for doing grammar-based decoding, where the output is a sequence of production rules from a
grammar).
The module also ... | allennlp-semparse-master | allennlp_semparse/state_machines/states/__init__.py |
from typing import List
import torch
from allennlp.nn import util
class RnnStatelet:
"""
This class keeps track of all of decoder-RNN-related variables that you need during decoding.
This includes things like the current decoder hidden state, the memory cell (for LSTM
decoders), the encoder output t... | allennlp-semparse-master | allennlp_semparse/state_machines/states/rnn_statelet.py |
from typing import Any, Dict, List, Sequence, Tuple
import torch
from allennlp_semparse.fields.production_rule_field import ProductionRule
from allennlp_semparse.state_machines.states.grammar_statelet import GrammarStatelet
from allennlp_semparse.state_machines.states.rnn_statelet import RnnStatelet
from allennlp_sem... | allennlp-semparse-master | allennlp_semparse/state_machines/states/grammar_based_state.py |
from typing import Callable, Dict, List, Tuple
import torch
from allennlp.nn import util
# We're not actually inhereting from `GrammarStatelet` here because there's very little logic that
# would actually be shared. Doing that doesn't solve our type problems, anyway, because List isn't
# covariant...
class LambdaG... | allennlp-semparse-master | allennlp_semparse/state_machines/states/lambda_grammar_statelet.py |
from typing import Dict
import torch
from allennlp.nn import util
class ChecklistStatelet:
"""
This class keeps track of checklist related variables that are used while training a coverage
based semantic parser (or any other kind of transition based constrained decoder). This is
intended to be used ... | allennlp-semparse-master | allennlp_semparse/state_machines/states/checklist_statelet.py |
from typing import Generic, List, TypeVar
import torch
# Note that the bound here is `State` itself. This is what lets us have methods that take
# lists of a `State` subclass and output structures with the subclass. Really ugly that we
# have to do this generic typing _for our own class_, but it makes mypy happy an... | allennlp-semparse-master | allennlp_semparse/state_machines/states/state.py |
from typing import List
NUMBER_CHARACTERS = {"0", "1", "2", "3", "4", "5", "6", "7", "8", "9", ".", "-"}
MONTH_NUMBERS = {
"january": 1,
"jan": 1,
"february": 2,
"feb": 2,
"march": 3,
"mar": 3,
"april": 4,
"apr": 4,
"may": 5,
"june": 6,
"jun": 6,
"july": 7,
"jul": 7... | allennlp-semparse-master | allennlp_semparse/common/util.py |
"""
A ``KnowledgeGraph`` is a graphical representation of some structured knowledge source: say a
table, figure or an explicit knowledge base.
"""
from typing import Dict, List, Set
class KnowledgeGraph:
"""
A ``KnowledgeGraph`` represents a collection of entities and their relationships.
The ``Knowledg... | allennlp-semparse-master | allennlp_semparse/common/knowledge_graph.py |
from allennlp_semparse.common.date import Date
from allennlp_semparse.common.errors import ParsingError, ExecutionError
from allennlp_semparse.common.util import (
NUMBER_CHARACTERS,
MONTH_NUMBERS,
ORDER_OF_MAGNITUDE_WORDS,
NUMBER_WORDS,
)
| allennlp-semparse-master | allennlp_semparse/common/__init__.py |
from collections import defaultdict
from typing import List, Dict, Set
import logging
from allennlp.common.util import START_SYMBOL
from allennlp_semparse.domain_languages.domain_language import DomainLanguage
logger = logging.getLogger(__name__)
class ActionSpaceWalker:
"""
``ActionSpaceWalker`` takes a ... | allennlp-semparse-master | allennlp_semparse/common/action_space_walker.py |
class ParsingError(Exception):
"""
This exception gets raised when there is a parsing error during logical form processing. This
might happen because you're not handling the full set of possible logical forms, for instance,
and having this error provides a consistent way to catch those errors and log h... | allennlp-semparse-master | allennlp_semparse/common/errors.py |
from allennlp_semparse.common.errors import ExecutionError
class Date:
def __init__(self, year: int, month: int, day: int) -> None:
self.year = year
self.month = month
self.day = day
def __eq__(self, other) -> bool:
# Note that the logic below renders equality to be non-transi... | allennlp-semparse-master | allennlp_semparse/common/date.py |
import re
import csv
from typing import Union, Dict, List, Tuple, Set
from collections import defaultdict
from unidecode import unidecode
from allennlp.data.tokenizers import Token
from allennlp_semparse.common import Date, NUMBER_CHARACTERS, NUMBER_WORDS, ORDER_OF_MAGNITUDE_WORDS
from allennlp_semparse.common.knowle... | allennlp-semparse-master | allennlp_semparse/common/wikitables/table_question_context.py |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This is the official evaluator taken from the original dataset. I made minimal changes to make it
Python 3 compatible, and conform to our style guidelines.
"""
# Official Evaluator for WikiTableQuestions Dataset
#
# There are 3 value types
# 1. String (unicode)
# 2. N... | allennlp-semparse-master | allennlp_semparse/common/wikitables/wikitables_evaluator.py |
from allennlp_semparse.common.wikitables.table_question_context import (
TableQuestionContext,
CellValueType,
)
| allennlp-semparse-master | allennlp_semparse/common/wikitables/__init__.py |
"""
Utility functions for reading the standardised text2sql datasets presented in
`"Improving Text to SQL Evaluation Methodology" <https://arxiv.org/abs/1806.09029>`_
"""
from typing import List, Dict, NamedTuple, Iterable, Tuple, Set
from collections import defaultdict
from allennlp.common import JsonDict
class Sql... | allennlp-semparse-master | allennlp_semparse/common/sql/text2sql_utils.py |
allennlp-semparse-master | allennlp_semparse/common/sql/__init__.py | |
from collections import defaultdict
from typing import Any, Callable, Dict, List, Optional, Sequence, Set, Tuple, Type, Union
import inspect
import logging
import sys
import traceback
import types
from nltk import Tree
from allennlp.common.util import START_SYMBOL
from allennlp_semparse.common import util, ParsingEr... | allennlp-semparse-master | allennlp_semparse/domain_languages/domain_language.py |
from collections import defaultdict
# We use "Number" in a bunch of places throughout to try to generalize ints and floats.
# Unfortunately, mypy doesn't like this very much, so we have to "type: ignore" a bunch of things.
# But it makes for a nicer induced grammar, so it's worth it.
from numbers import Number
from ty... | allennlp-semparse-master | allennlp_semparse/domain_languages/wikitables_language.py |
from allennlp_semparse.domain_languages.domain_language import (
DomainLanguage,
START_SYMBOL,
predicate,
predicate_with_side_args,
)
from allennlp_semparse.domain_languages.nlvr_language import NlvrLanguage
from allennlp_semparse.domain_languages.wikitables_language import WikiTablesLanguage
| allennlp-semparse-master | allennlp_semparse/domain_languages/__init__.py |
from collections import defaultdict
from typing import Callable, Dict, List, NamedTuple, Set
from allennlp.common.util import JsonDict
from allennlp_semparse.domain_languages.domain_language import DomainLanguage, predicate
class Object:
"""
``Objects`` are the geometric shapes in the NLVR domain. They have... | allennlp-semparse-master | allennlp_semparse/domain_languages/nlvr_language.py |
from typing import Dict, List, Optional, NamedTuple
import torch
from allennlp.data.fields.field import Field
from allennlp.data.vocabulary import Vocabulary
class ProductionRule(NamedTuple):
rule: str
is_global_rule: bool
rule_id: Optional[torch.LongTensor] = None
nonterminal: Optional[str] = None... | allennlp-semparse-master | allennlp_semparse/fields/production_rule_field.py |
from allennlp_semparse.fields.knowledge_graph_field import KnowledgeGraphField
from allennlp_semparse.fields.production_rule_field import ProductionRuleField
| allennlp-semparse-master | allennlp_semparse/fields/__init__.py |
"""
``KnowledgeGraphField`` is a ``Field`` which stores a knowledge graph representation.
"""
from typing import Callable, Dict, List, Set
import editdistance
import torch
from allennlp.common import util
from allennlp.common.checks import ConfigurationError
from allennlp.data.fields import Field, ListField, TextFie... | allennlp-semparse-master | allennlp_semparse/fields/knowledge_graph_field.py |
allennlp-semparse-master | allennlp_semparse/nltk_languages/__init__.py | |
allennlp-semparse-master | allennlp_semparse/nltk_languages/contexts/__init__.py | |
from typing import List, Dict, Set, Tuple
from collections import defaultdict
import logging
import re
from nltk import Tree
from nltk.sem.logic import ApplicationExpression, Expression, LambdaExpression, BasicType, Type
from allennlp_semparse.common import util
from allennlp_semparse.common.errors import ParsingErro... | allennlp-semparse-master | allennlp_semparse/nltk_languages/worlds/world.py |
allennlp-semparse-master | allennlp_semparse/nltk_languages/worlds/__init__.py | |
allennlp-semparse-master | allennlp_semparse/nltk_languages/type_declarations/__init__.py | |
"""
This module defines some classes that are generally useful for defining a type system for a new
domain. We inherit the type logic in ``nltk.sem.logic`` and add some functionality on top of it
here. There are two main improvements:
1) Firstly, we allow defining multiple basic types with their own names (see ``NamedB... | allennlp-semparse-master | allennlp_semparse/nltk_languages/type_declarations/type_declaration.py |
import json
import os
import sys
from collections import defaultdict
from typing import Dict, Any, Iterable, Tuple
import glob
import argparse
sys.path.insert(0, os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
JsonDict = Dict[str, Any]
def process_dataset(data: JsonDict, split_type: str) -> Ite... | allennlp-semparse-master | scripts/reformat_text2sql_data.py |
import json
import os
import sys
import argparse
sys.path.insert(0, os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
from allennlp.data.dataset_readers.dataset_utils.text2sql_utils import process_sql_data
from allennlp.semparse.contexts.sql_context_utils import SqlVisitor, format_grammar_string
fr... | allennlp-semparse-master | scripts/examine_sql_coverage.py |
#!/usr/bin/env python3
import argparse
from typing import Dict
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("version_type", choices=["stable", "latest", "current"])
parser.add_argument("--minimal", action="store_true", default=False)
return parser.parse_args()
def post_p... | allennlp-semparse-master | scripts/get_version.py |
import json
import logging
import os
import sys
sys.path.insert(0, os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", level=logging.DEBUG
)
from allennlp.commands.train import datasets_from_params
from allennlp.co... | allennlp-semparse-master | scripts/wikitables/preprocess_data.py |
#! /usr/bin/env python
import sys
import os
import argparse
import gzip
import logging
import math
from multiprocessing import Process
sys.path.insert(
0, os.path.dirname(os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
)
from allennlp.common.util import JsonDict
from allennlp.data.tokenizers... | allennlp-semparse-master | scripts/wikitables/search_for_logical_forms.py |
#! /usr/bin/env python
import sys
import os
import gzip
import argparse
sys.path.insert(
0, os.path.dirname(os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
)
from allennlp.data.dataset_readers import WikiTablesDatasetReader
from allennlp.data.dataset_readers.semantic_parsing.wikitables impo... | allennlp-semparse-master | scripts/wikitables/generate_data_from_erm_model.py |
#! /usr/bin/env python
"""
NLVR dataset has at most four worlds corresponding to each sentence (with 93% of the sentences
appearing with four worlds), identified by the prefixes in identifiers. This script groups the
worlds and corresponding labels together to enable training a parser with this information.
"""
impor... | allennlp-semparse-master | scripts/nlvr/group_nlvr_worlds.py |
#! /usr/bin/env python
import json
import argparse
from typing import Tuple, List
import os
import sys
sys.path.insert(
0, os.path.dirname(os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
)
from allennlp.common.util import JsonDict
from allennlp.semparse.domain_languages import NlvrLanguage
fr... | allennlp-semparse-master | scripts/nlvr/get_nlvr_logical_forms.py |
#! /usr/bin/env python
import sys
import os
import json
import argparse
sys.path.insert(
0, os.path.dirname(os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
)
from allennlp.data.dataset_readers import NlvrDatasetReader
from allennlp.models import NlvrCoverageSemanticParser
from allennlp.mode... | allennlp-semparse-master | scripts/nlvr/generate_data_from_erm_model.py |
import torch
from transformers import BertTokenizer
from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
from transformers import BertForSequenceClassification, AdamW, BertConfig, BertModel, AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained('allenai/scibert_scivocab... | covid-sim-master | demo-env/download_bert_model.py |
# -*- coding: utf-8 -*-
import requests
import time
import math
import signal
def is_ok(url: str) -> bool:
"""
Returns True if the provided URL responds with a 2XX when fetched via
a HTTP GET request.
"""
try:
resp = requests.get(url)
except:
return False
return True if mat... | covid-sim-master | sonar/ping.py |
import torch
from transformers import BertTokenizer
from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
from transformers import BertForSequenceClassification, AdamW, BertConfig, BertModel, AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained('allenai/scibert_scivocab... | covid-sim-master | api/download_bert_model.py |
import argparse
import faiss
import numpy as np
from sklearn.decomposition import PCA
import pandas as pd
import subprocess
import tqdm
import pickle
def file_len(fname):
p = subprocess.Popen(['wc', '-l', fname], stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
res... | covid-sim-master | api/covid-ai2/build_index.py |
import torch
from transformers import BertTokenizer
import csv
from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
from transformers import BertForSequenceClassification, AdamW, BertConfig, BertModel, AutoTokenizer, AutoModel
import time
import datetime
import random
import numpy as... | covid-sim-master | api/covid-ai2/run_bert.py |
import pandas as pd
import tqdm
import pickle
import random
import itertools
import torch
from transformers import BertTokenizer
from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
from transformers import AutoTokenizer, AutoModel, AutoConfig
from transformers import BertForSequenc... | covid-sim-master | api/covid-ai2/alignment_supervised2.py |
#import bert
import numpy as np
from sklearn.metrics.pairwise import cosine_similarity
#import matplotlib.pyplot as plt
#import spike_queries
#from termcolor import colored
#import random
from collections import Counter, defaultdict
#from viterbi_trellis import ViterbiTrellis
import streamlit as st
from annot import a... | covid-sim-master | api/covid-ai2/alignment.py |
import streamlit as st
import pandas as pd
import numpy as np
import pandas as pd
import faiss
import bert
from bert import BertEncoder
import pickle
import spike_queries
import sklearn
import time
from sklearn.cluster import KMeans as Kmeans
@st.cache(allow_output_mutation=True)
def load_sents_and_ids():
with st... | covid-sim-master | api/covid-ai2/clustering-demo.py |
# FROM THE PACKAGE st-annotated-text https://github.com/tvst/st-annotated-text
import streamlit.components.v1
from htbuilder import HtmlElement, div, span, styles
from htbuilder.units import px, rem, em
def annotation(body, label="", background="#ddd", color="#333", **style):
"""Build an HtmlElement span object... | covid-sim-master | api/covid-ai2/annot.py |
import torch
from transformers import BertTokenizer, BertModel, BertForMaskedLM, BertConfig, RobertaModel, RobertaForMaskedLM, \
RobertaTokenizer, RobertaConfig
from transformers import AutoTokenizer, AutoModel, AutoConfig
#from transformers import AlbertTokenizer, AlbertModel, AlbertConfig
#from transformers impor... | covid-sim-master | api/covid-ai2/bert_all_seq.py |
import streamlit as st
import pandas as pd
import numpy as np
import pandas as pd
import faiss
import bert
from bert import BertEncoder
import pickle
import spike_queries
import sklearn
import random
import time
import alignment
import bert_all_seq
#import alignment_supervised2 as alignment_supervised
import alignment_... | covid-sim-master | api/covid-ai2/demo2.py |
import pandas as pd
import tqdm
import pickle
import random
import itertools
import torch
from transformers import BertTokenizer
from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
from transformers import AutoTokenizer, AutoModel, AutoConfig
from transformers import BertForSequen... | covid-sim-master | api/covid-ai2/alignment_model.py |
import torch
from typing import List, Dict
import random
import numpy as np
class Dataset(torch.utils.data.Dataset):
"""Simple torch dataset class"""
def __init__(self, data: List[Dict], device = "cpu", negative_prob = 0.0):
self.data = data
self.device = device
self.negative_prob = n... | covid-sim-master | api/covid-ai2/dataset.py |
import pandas as pd
import numpy as np
import spike_queries
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='download covid dataset',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--num-results', dest=... | covid-sim-master | api/covid-ai2/download_data.py |
"""Hack to add per-session state to Streamlit.
Usage
-----
>>> import SessionState
>>>
>>> session_state = SessionState.get(user_name='', favorite_color='black')
>>> session_state.user_name
''
>>> session_state.user_name = 'Mary'
>>> session_state.favorite_color
'black'
Since you set user_name above, next time your scr... | covid-sim-master | api/covid-ai2/SessionState.py |
import torch
from transformers import BertTokenizer
from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
from transformers import BertForSequenceClassification, AdamW, BertConfig, BertModel, AutoTokenizer, AutoModel
import numpy as np
from typing import List
import tqdm
class BertEn... | covid-sim-master | api/covid-ai2/bert.py |
import requests
import pandas as pd
import streamlit as st
COVID_URL = "https://spike.staging.apps.allenai.org/api/3/search/query" #"http://35.242.203.108:5000/api/3/search/query"
COVID_BASE_URL = "https://spike.staging.apps.allenai.org" #"http://35.242.203.108:5000"
PUBMED_URL = "http://34.89.172.235:5000/api/3/sear... | covid-sim-master | api/covid-ai2/spike_queries.py |
import streamlit as st
import pandas as pd
import numpy as np
import pandas as pd
import faiss
import bert
from bert import BertEncoder
import pickle
import spike_queries
import sklearn
import random
import time
import alignment
import bert_all_seq
#import alignment_supervised2 as alignment_supervised
import alignment_... | covid-sim-master | api/covid-ai2/demo.py |
import pandas as pd
import tqdm
import pickle
import random
import itertools
import torch
from transformers import BertTokenizer
from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
from transformers import AutoTokenizer, AutoModel, AutoConfig
from transformers import BertForSequenc... | covid-sim-master | api/covid-ai2/alignment_supervised.py |
import os
from pathlib import Path
ABS_PATH_OF_REARRANGE_TOP_LEVEL_DIR = os.path.abspath(os.path.dirname(Path(__file__)))
IOU_THRESHOLD = 0.5
OPENNESS_THRESHOLD = 0.2
POSITION_DIFF_BARRIER = 2.0
| ai2thor-rearrangement-main | rearrange_constants.py |
"""Inference loop for the AI2-THOR object rearrangement task."""
from allenact.utils.misc_utils import NumpyJSONEncoder
from baseline_configs.one_phase.one_phase_rgb_base import (
OnePhaseRGBBaseExperimentConfig,
)
from baseline_configs.two_phase.two_phase_rgb_base import (
TwoPhaseRGBBaseExperimentConfig,
)
f... | ai2thor-rearrangement-main | example.py |
"""Include the Task and TaskSampler to train on a single unshuffle instance."""
import copy
import itertools
import os
import random
import traceback
from abc import ABC
from typing import Any, Tuple, Optional, Dict, Sequence, List, Union, cast, Set
import canonicaljson
import compress_pickle
import gym.spaces
import ... | ai2thor-rearrangement-main | rearrange/tasks.py |
from typing import Any, Optional, Union
import gym.spaces
import numpy as np
from allenact.base_abstractions.sensor import Sensor
try:
from allenact.embodiedai.sensors.vision_sensors import RGBSensor
except ImportError:
raise ImportError("Please update to allenact>=0.4.0.")
from allenact.utils.misc_utils imp... | ai2thor-rearrangement-main | rearrange/sensors.py |
"""Definitions for a greedy expert for the `Unshuffle` task."""
import copy
import random
from collections import defaultdict
from typing import (
Dict,
Tuple,
Any,
Optional,
Union,
List,
Sequence,
TYPE_CHECKING,
)
import ai2thor.controller
import ai2thor.server
import networkx as nx
i... | ai2thor-rearrangement-main | rearrange/expert.py |
import os
from pathlib import Path
MAX_HAND_METERS = 0.5
FOV = 90
REQUIRED_THOR_VERSION = "5.0.0"
STARTER_DATA_DIR = os.path.join(
os.path.abspath(os.path.dirname(Path(__file__))), "../data", "2023",
)
THOR_COMMIT_ID = "a9ccb07faf771377c9ff1615bfe7e0ad01968663"
STEP_SIZE = 0.25
# fmt: off
REARRANGE_SIM_OBJECTS ... | ai2thor-rearrangement-main | rearrange/constants.py |
ai2thor-rearrangement-main | rearrange/__init__.py | |
from typing import (
Optional,
Tuple,
Sequence,
Union,
Dict,
Any,
)
import gym
import gym.spaces
import numpy as np
import torch
import torch.nn as nn
from torch import Tensor
from allenact.algorithms.onpolicy_sync.policy import (
ActorCriticModel,
DistributionType,
LinearActorCrit... | ai2thor-rearrangement-main | rearrange/baseline_models.py |
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