python_code stringlengths 0 187k | repo_name stringlengths 8 46 | file_path stringlengths 6 135 |
|---|---|---|
# pylint: disable=no-self-use,invalid-name
from allennlp_models.rc.tools.squad import normalize_answer as _normalize_answer_squad
from allennlp_models.rc.tools.orb_utils import get_metric_squad, get_metric_drop
from allennlp_models.rc.tools.narrativeqa import get_metric_score as get_metric_narrativeqa
from tests impor... | allennlp-models-main | tests/rc/evaluations/orb_test.py |
import pytest
from allennlp_models.rc.dataset_readers.utils import char_span_to_token_span
@pytest.mark.parametrize(
"token_offsets, character_span, expected_result",
[
([(0, 3), (4, 4), (5, 8)], (5, 8), ((2, 2), False)),
([(0, 3), (4, 4), (5, 8)], (4, 8), ((1, 2), False)),
([(0, 3), ... | allennlp-models-main | tests/rc/dataset_readers/utils_test.py |
from allennlp.common.params import Params
from allennlp.common.util import ensure_list
from allennlp.data import DatasetReader
import pytest
from allennlp_models.rc import TransformerSquadReader
from tests import FIXTURES_ROOT
class TestTransformerSquadReader:
def test_from_params(self):
with pytest.warn... | allennlp-models-main | tests/rc/dataset_readers/transformer_squad_test.py |
allennlp-models-main | tests/rc/dataset_readers/__init__.py | |
import pytest
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp_models.rc import DropReader
from tests import FIXTURES_ROOT
class TestDropReader:
def test_read_from_file(self):
reader = DropReader()
instances = ensure_list(reader.read(FIXTURES_ROOT / "... | allennlp-models-main | tests/rc/dataset_readers/drop_test.py |
import pytest
from allennlp.data.tokenizers import WhitespaceTokenizer
from allennlp.data.token_indexers import SingleIdTokenIndexer
from tests import FIXTURES_ROOT
import re
from typing import List
from allennlp_models.rc.dataset_readers.record_reader import RecordTaskReader
"""
Tests for the ReCoRD reader from Supe... | allennlp-models-main | tests/rc/dataset_readers/record_reader_test.py |
import pytest
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp_models.rc import QangarooReader
from tests import FIXTURES_ROOT
class TestQangarooReader:
def test_read_from_file(self):
reader = QangarooReader()
instances = ensure_list(reader.read(FIXTU... | allennlp-models-main | tests/rc/dataset_readers/qangaroo_test.py |
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp.data import DatasetReader
import pytest
from allennlp_models.rc import SquadReader
from allennlp_models.rc.dataset_readers.squad import SQUAD2_NO_ANSWER_TOKEN
from tests import FIXTURES_ROOT
class TestSquadReader:
def t... | allennlp-models-main | tests/rc/dataset_readers/squad_test.py |
from pytest import approx
from allennlp.common.testing import AllenNlpTestCase
from allennlp.models.archival import load_archive
from allennlp.predictors import Predictor
from allennlp_models.rc import ReadingComprehensionPredictor
from tests import FIXTURES_ROOT
class TestBidafPredictor(AllenNlpTestCase):
def... | allennlp-models-main | tests/rc/predictors/bidaf_test.py |
allennlp-models-main | tests/rc/predictors/__init__.py | |
from allennlp.common.testing import AllenNlpTestCase
from allennlp.data import Vocabulary
from allennlp_models.rc import TransformerSquadReader
from allennlp_models.rc import TransformerQA
from allennlp_models.rc import TransformerQAPredictor
class TestTransformerQAPredictor(AllenNlpTestCase):
def setup_method(s... | allennlp-models-main | tests/rc/predictors/transformer_qa_test.py |
from allennlp.models.archival import load_archive
from allennlp.predictors import Predictor
from tests import FIXTURES_ROOT
class TestDialogQAPredictor:
def test_uses_named_inputs(self):
inputs = {
"paragraphs": [
{
"qas": [
{
... | allennlp-models-main | tests/rc/predictors/dialog_qa_test.py |
from flaky import flaky
import pytest
import numpy
from numpy.testing import assert_almost_equal
import torch
from allennlp.commands.train import train_model_from_file
from allennlp.common import Params
from allennlp.common.checks import ConfigurationError
from allennlp.common.testing import AllenNlpTestCase, ModelTes... | allennlp-models-main | tests/rc/models/bidaf_test.py |
import numpy
import torch
from flaky import flaky
from allennlp.common.testing import ModelTestCase
from allennlp.data import Batch
from allennlp_models.rc import BidafEnsemble
from tests import FIXTURES_ROOT
class BidafEnsembleTest(ModelTestCase):
def setup_method(self):
super().setup_method()
... | allennlp-models-main | tests/rc/models/bidaf_ensemble_test.py |
from numpy.testing import assert_almost_equal
import torch
from allennlp.common.testing import AllenNlpTestCase
from allennlp_models.rc.models.utils import get_best_span
class TestRcUtil(AllenNlpTestCase):
def test_get_best_span(self):
span_begin_probs = torch.FloatTensor([[0.1, 0.3, 0.05, 0.3, 0.25]]).l... | allennlp-models-main | tests/rc/models/utils_test.py |
from allennlp.common.testing import ModelTestCase
from tests import FIXTURES_ROOT
from allennlp_models.rc import NumericallyAugmentedQaNet
class NumericallyAugmentedQaNetTest(ModelTestCase):
def setup_method(self):
super().setup_method()
self.set_up_model(
FIXTURES_ROOT / "rc" / "naq... | allennlp-models-main | tests/rc/models/naqanet_test.py |
from flaky import flaky
import numpy
from numpy.testing import assert_almost_equal
from allennlp.common import Params
from allennlp.common.testing import ModelTestCase
from allennlp.data import DatasetReader, Vocabulary
from allennlp.data import Batch
from allennlp.models import Model
from allennlp_models import rc ... | allennlp-models-main | tests/rc/models/qanet_test.py |
allennlp-models-main | tests/rc/models/__init__.py | |
import numpy
from numpy.testing import assert_almost_equal
from allennlp.commands.train import train_model_from_file
from allennlp.common.testing import ModelTestCase, AllenNlpTestCase, requires_gpu
from allennlp.data import Batch
from tests import FIXTURES_ROOT
import pytest
import torch
import allennlp_models.rc
c... | allennlp-models-main | tests/rc/models/transformer_qa_test.py |
from allennlp.common.testing import ModelTestCase
from allennlp.data import Batch
import torch
import allennlp_models.rc
from tests import FIXTURES_ROOT
class DialogQATest(ModelTestCase):
def setup_method(self):
super().setup_method()
self.set_up_model(
FIXTURES_ROOT / "rc" / "dialog_... | allennlp-models-main | tests/rc/models/dialog_qa_test.py |
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp_models.rc import QuACReader
from tests import FIXTURES_ROOT
class TestQuACReader:
def test_read(self):
params = Params({"num_context_answers": 2})
reader = QuACReader.from_params(params)
instance... | allennlp-models-main | tests/rc/models/quac_test.py |
from allennlp.interpret.attackers import Hotflip
from allennlp.interpret.attackers.hotflip import DEFAULT_IGNORE_TOKENS
from allennlp.models import load_archive
from allennlp.predictors import Predictor
import allennlp_models.rc
from tests import FIXTURES_ROOT
class TestHotflip:
def test_using_squad_model(self):... | allennlp-models-main | tests/rc/interpret/bidaf_hotflip_test.py |
allennlp-models-main | tests/rc/interpret/__init__.py | |
allennlp-models-main | tests/rc/modules/__init__.py | |
import torch
from torch.nn.parallel.data_parallel import DataParallel
from allennlp.common.testing import AllenNlpTestCase, requires_multi_gpu
from allennlp_models.rc.modules.seq2seq_encoders.stacked_self_attention import (
StackedSelfAttentionEncoder,
)
class TestStackedSelfAttention(AllenNlpTestCase):
def... | allennlp-models-main | tests/rc/modules/seq2seq_encoders/stacked_self_attention_test.py |
import torch
from allennlp.common.testing import AllenNlpTestCase
from allennlp.common.params import Params
from allennlp_models.rc import QaNetEncoder
class QaNetEncoderTest(AllenNlpTestCase):
def test_qanet_encoder_can_build_from_params(self):
params = Params(
{
"input_dim"... | allennlp-models-main | tests/rc/modules/seq2seq_encoders/qanet_encoder_test.py |
allennlp-models-main | tests/rc/modules/seq2seq_encoders/__init__.py | |
import numpy
import torch
from allennlp.common.testing import AllenNlpTestCase
from allennlp.common.params import Params
from allennlp_models.rc.modules.seq2seq_encoders.multi_head_self_attention import (
MultiHeadSelfAttention,
)
class MultiHeadSelfAttentionTest(AllenNlpTestCase):
def test_multi_head_self_... | allennlp-models-main | tests/rc/modules/seq2seq_encoders/multi_head_self_attention_test.py |
allennlp-models-main | tests/generation/__init__.py | |
import tempfile
import pytest
from allennlp.common.checks import ConfigurationError
from allennlp.common.util import ensure_list
from allennlp_models.generation import Seq2SeqDatasetReader
from tests import FIXTURES_ROOT
class TestSeq2SeqDatasetReader:
def test_default_format(self):
reader = Seq2SeqData... | allennlp-models-main | tests/generation/dataset_readers/seq2seq_test.py |
allennlp-models-main | tests/generation/dataset_readers/__init__.py | |
import numpy as np
import torch
from allennlp.common import Params
from allennlp.common.testing import AllenNlpTestCase
from allennlp.common.util import ensure_list
from allennlp.data import DatasetReader
from allennlp.data.fields import TensorField
from allennlp.data.vocabulary import Vocabulary, DEFAULT_OOV_TOKEN
f... | allennlp-models-main | tests/generation/dataset_readers/copynet_test.py |
from allennlp.common.testing import AllenNlpTestCase
from allennlp.models.archival import load_archive
from allennlp.predictors import Predictor
from allennlp_models.generation.predictors import Seq2SeqPredictor
from tests import FIXTURES_ROOT
class TestSeq2SeqPredictor(AllenNlpTestCase):
def test_uses_named_inp... | allennlp-models-main | tests/generation/predictors/seq2seq_test.py |
allennlp-models-main | tests/generation/predictors/__init__.py | |
from allennlp.common.testing import ModelTestCase
from tests import FIXTURES_ROOT
from allennlp_models import generation # noqa: F401
class T5Test(ModelTestCase):
def setup_method(self):
super().setup_method()
self.set_up_model(
FIXTURES_ROOT / "generation" / "t5" / "experiment.json... | allennlp-models-main | tests/generation/models/t5_test.py |
allennlp-models-main | tests/generation/models/__init__.py | |
import numpy as np
import pytest
import torch
from _pytest.mark import param
from allennlp.commands.train import train_model_from_file
from allennlp.common import Params
from allennlp.common.testing import ModelTestCase, requires_gpu
from allennlp.data import Batch, DatasetReader
from allennlp.models import Model
from ... | allennlp-models-main | tests/generation/models/copynet_test.py |
import json
import numpy
import pytest
import torch
from allennlp.models import Model
from allennlp.common import Params
from allennlp.commands.train import train_model_from_file
from allennlp.common.testing import ModelTestCase, requires_gpu
from allennlp.nn.beam_search import BeamSearch
from allennlp.nn.util import... | allennlp-models-main | tests/generation/models/simple_seq2seq_test.py |
import pytest
from allennlp.common import Params
from allennlp.common.testing import ModelTestCase
from allennlp.models import Model
from allennlp_models import generation # noqa: F401
from tests import FIXTURES_ROOT
class BartTest(ModelTestCase):
def setup_method(self):
super().setup_method()
se... | allennlp-models-main | tests/generation/models/bart_test.py |
import json
from allennlp.common.testing import ModelTestCase
from tests import FIXTURES_ROOT
class ComposedSeq2SeqTest(ModelTestCase):
def setup_method(self):
super().setup_method()
self.set_up_model(
FIXTURES_ROOT / "generation" / "composed" / "experiment.json",
FIXTURE... | allennlp-models-main | tests/generation/models/composed_seq2seq_test.py |
allennlp-models-main | tests/generation/modules/__init__.py | |
allennlp-models-main | tests/generation/modules/seq_decoders/__init__.py | |
from typing import Any, Iterable, Dict
import pytest
import torch
from allennlp.common import Lazy, Params
from allennlp.common.checks import ConfigurationError
from allennlp.common.testing import AllenNlpTestCase
from allennlp.common.util import END_SYMBOL, prepare_environment, START_SYMBOL
from allennlp.data.vocab... | allennlp-models-main | tests/generation/modules/seq_decoders/auto_regressive_test.py |
import torch
from allennlp.common.testing import AllenNlpTestCase
from allennlp_models.generation import StackedSelfAttentionDecoderNet
class TestStackedSelfAttentionDecoderNet(AllenNlpTestCase):
def test_stacked_self_attention_decoder_net_init(self):
decoder_inout_dim = 10
decoder_net = Stacked... | allennlp-models-main | tests/generation/modules/decoder_nets/stacked_self_attention_test.py |
allennlp-models-main | tests/generation/modules/decoder_nets/__init__.py | |
import torch
from allennlp.common.testing import AllenNlpTestCase
from allennlp.modules.attention import DotProductAttention
from allennlp_models.generation.modules.decoder_nets.lstm_cell import LstmCellDecoderNet
class TestLstmCellDecoderNet(AllenNlpTestCase):
def test_lstm_cell_decoder_net_init(self):
... | allennlp-models-main | tests/generation/modules/decoder_nets/lstm_cell_test.py |
allennlp-models-main | tests/coref/__init__.py | |
import torch
from allennlp.common.testing import (
multi_device,
AllenNlpTestCase,
global_distributed_metric,
run_distributed_test,
)
from allennlp_models.coref.metrics.conll_coref_scores import ConllCorefScores
class ConllCorefScoresTest(AllenNlpTestCase):
@multi_device
def test_get_predict... | allennlp-models-main | tests/coref/metrics/conll_coref_scores_test.py |
allennlp-models-main | tests/coref/metrics/__init__.py | |
import torch
from allennlp.common.testing import (
AllenNlpTestCase,
global_distributed_metric,
run_distributed_test,
)
from allennlp_models.coref.metrics.mention_recall import MentionRecall
class MentionRecallTest(AllenNlpTestCase):
def test_mention_recall(self):
metric = MentionRecall()
... | allennlp-models-main | tests/coref/metrics/mention_recall_test.py |
from typing import List, Tuple
from allennlp.common.util import ensure_list
from allennlp.common.testing import AllenNlpTestCase
from allennlp_models.coref import WinobiasReader
from tests import FIXTURES_ROOT
class TestWinobiasReader:
span_width = 5
def test_read_from_file(self):
conll_reader = Wi... | allennlp-models-main | tests/coref/dataset_readers/winobias_test.py |
from typing import List, Tuple
import pytest
from allennlp.common.util import ensure_list
from allennlp.common.testing import AllenNlpTestCase
from allennlp_models.coref import PrecoReader
from tests import FIXTURES_ROOT
class TestPrecoReader:
span_width = 5
@pytest.mark.parametrize("remove_singleton_clus... | allennlp-models-main | tests/coref/dataset_readers/preco_test.py |
allennlp-models-main | tests/coref/dataset_readers/__init__.py | |
from typing import List, Tuple
from allennlp.data.tokenizers import PretrainedTransformerTokenizer
from allennlp.common.util import ensure_list
from allennlp.common.testing import AllenNlpTestCase
from allennlp_models.coref import ConllCorefReader
from tests import FIXTURES_ROOT
class TestCorefReader:
span_widt... | allennlp-models-main | tests/coref/dataset_readers/coref_test.py |
allennlp-models-main | tests/coref/predictors/__init__.py | |
import spacy
from allennlp.common.testing import AllenNlpTestCase
from allennlp.models.archival import load_archive
from allennlp.predictors import Predictor
from allennlp_models.coref import CorefPredictor
from tests import FIXTURES_ROOT
class TestCorefPredictor(AllenNlpTestCase):
def test_uses_named_inputs(s... | allennlp-models-main | tests/coref/predictors/coref_test.py |
allennlp-models-main | tests/coref/models/__init__.py | |
import torch
from allennlp.common.testing import ModelTestCase
from allennlp_models import coref # noqa: F401
from tests import FIXTURES_ROOT
class CorefTest(ModelTestCase):
def setup_method(self):
super().setup_method()
self.set_up_model(
FIXTURES_ROOT / "coref" / "experiment.json"... | allennlp-models-main | tests/coref/models/coref_test.py |
allennlp-models-main | tests/coref/interpret/__init__.py | |
from pytest import approx
from allennlp.common.testing import AllenNlpTestCase
from allennlp.interpret.saliency_interpreters import SimpleGradient
from allennlp.models.archival import load_archive
from allennlp.predictors import Predictor
from tests import FIXTURES_ROOT
class TestInterpret(AllenNlpTestCase):
de... | allennlp-models-main | tests/coref/interpret/interpret_test.py |
#!/usr/bin/env python
"""
Ensures models are automatically found by allennlp.
"""
import logging
from allennlp.common.plugins import import_plugins
from allennlp.models import Model
logging.basicConfig(level=logging.INFO)
import_plugins()
Model.by_name("copynet_seq2seq")
| allennlp-models-main | scripts/ensure_models_found.py |
"""
Run this script to update the list of pre-trained models in the README based on the current model cards.
"""
from typing import List
import json
import glob
AUTO_GENERATED_SECTION_START = "<!-- This section is automatically generated"
AUTO_GENERATED_SECTION_END = "<!-- End automatically generated section -->"
... | allennlp-models-main | scripts/update_readme_model_list.py |
#!/usr/bin/env python
"""
This script is used to populate the table of contents for the API in the mkdocs config file.
"""
import argparse
from pathlib import Path
from typing import Any, List
from ruamel.yaml import YAML
from allennlp_models.version import VERSION
API_TOC_KEY = "Models"
def parse_args():
p... | allennlp-models-main | scripts/build_docs_config.py |
#!/usr/bin/env python
"""
Ensures allennlp and models versions are the same.
"""
from allennlp.version import VERSION as CORE_VERSION
from allennlp_models.version import VERSION as MODELS_VERSION
assert CORE_VERSION == MODELS_VERSION, f"core: {CORE_VERSION}, models: {MODELS_VERSION}"
| allennlp-models-main | scripts/ensure_versions_match.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)
parser.add_argument("--as-range", actio... | allennlp-models-main | scripts/get_version.py |
import argparse
import random
from utils import read_csv, write_array2tsv, head_based_split, count_relation
def load_conceptnet(args):
random.seed(args.random_seed)
cn_train_file = args.data_folder + args.data_file
cn_train_data = read_csv(cn_train_file, delimiter="\t")
train_data = [[l[1], l[0], l[... | comet-atomic-2020-master | split/split_conceptnet.py |
from utils import read_csv, write_tsv
def tuple_key(d):
return d[0] + d[1] + d[2]
def main():
folder = "./data/transomcs/"
file = folder + "TransOMCS_full.txt"
data = read_csv(file, delimiter="\t")
confidences = {}
for d in data:
key = tuple_key(d)
confidences[key] = float(... | comet-atomic-2020-master | split/filter_human_eval_tuples_with_updated_transomcs.py |
import argparse
import random
from utils import read_csv, write_array2tsv
def load_atomic(args):
random.seed(args.random_seed)
atomic_split_folder = args.data_folder + "original_split/"
atomic_file = args.data_folder + args.data_file
atomic_data = read_csv(atomic_file, delimiter="\t", skip_header=T... | comet-atomic-2020-master | split/split_atomic.py |
comet-atomic-2020-master | split/__init__.py | |
import argparse
import random
from utils import read_csv, write_array2tsv, head_based_split
def load_transomcs(args):
import matplotlib.pyplot as plt
random.seed(args.random_seed)
data_file = args.data_folder + args.data_file
data = read_csv(data_file, delimiter="\t")
selection = [[l[0], l[1],... | comet-atomic-2020-master | split/split_transomcs.py |
import json
import sys
import csv
import operator
import random
def read_csv(input_file, quotechar='"', delimiter=",", skip_header=False):
"""Reads a tab separated value file."""
with open(input_file, "r") as f:
reader = csv.reader(f, delimiter=delimiter, quotechar=quotechar, quoting=csv.QUOTE_ALL, sk... | comet-atomic-2020-master | split/utils.py |
import argparse
import random
from utils import read_csv, write_jsonl
def sample_kg(args):
random.seed(args.random_seed)
data_file = args.input_file
data = read_csv(data_file, delimiter="\t")
prefixes = {}
for l in data:
prefix = l[0] + " " + l[1]
if prefix not in prefixes.keys... | comet-atomic-2020-master | split/sample_prefixes.py |
import argparse
import random
from utils import read_csv, write_array2tsv, head_based_split, get_head_set
def load_atomic2020(args):
random.seed(args.random_seed)
atomic2020_v1_file = args.data_folder + "atomic_original_tuples.tsv"
atomic2020_addl_file = args.data_folder + "atomic_additional_tuples.tsv"... | comet-atomic-2020-master | split/split_atomic2020.py |
comet-atomic-2020-master | mosaic/__init__.py | |
# Importing stock libraries
import numpy as np
import pandas as pd
import torch
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader, RandomSampler, SequentialSampler
# Importing the T5 modules from huggingface/transformers
from transformers import T5Tokenizer, T5ForConditionalGeneration
#... | comet-atomic-2020-master | mosaic/infra/logging.py |
# Importing stock libraries
import numpy as np
import pandas as pd
import torch
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader, RandomSampler, SequentialSampler
# Importing the T5 modules from huggingface/transformers
from transformers import T5Tokenizer, T5ForConditionalGeneration
#... | comet-atomic-2020-master | mosaic/infra/modeling.py |
# Importing stock libraries
import numpy as np
import pandas as pd
import torch
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader, RandomSampler, SequentialSampler
# Importing the T5 modules from huggingface/transformers
from transformers import T5Tokenizer, T5ForConditionalGeneration
#... | comet-atomic-2020-master | mosaic/datasets/KGDataset.py |
comet-atomic-2020-master | mosaic/datasets/__init__.py | |
from nltk import pos_tag, word_tokenize
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
import csv
import argparse
import os
exact2tokenized = {}
tokenized2pos = {}
pos2content = {}
def main():
print('\n#######################')
print('Preprocess Part 2')
print('################... | comet-atomic-2020-master | human_eval/coverage/preprocess_kb_triples_part2.py |
import pandas as pd
from collections import OrderedDict
import csv
import os
import argparse
def main():
print('\n#######################')
print('Calculate Coverage')
print('#######################')
# OUTPUT DIR
output_dir = os.path.join(args.data_dir, 'output-x')
print("Outputting matche... | comet-atomic-2020-master | human_eval/coverage/calculate_coverage.py |
import pandas as pd
import string
import argparse
import os
str2exact = {}
def main():
print('\n#######################')
print('Preprocess Part 1')
print('#######################')
data_dir = [(os.path.join(args.data_dir,'atomic2020.tsv'),'atomic2020'),
(os.path.join(args.data_dir,'c... | comet-atomic-2020-master | human_eval/coverage/preprocess_kb_triples_part1.py |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelForQuestionAnswering,
... | comet-atomic-2020-master | models/comet_atomic2020_bart/lightning_base.py |
import itertools
import json
import linecache
import os
import pickle
import warnings
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import numpy as np
import torch
from rouge_score import rouge_scorer, scoring
from sacrebleu import corpus_bleu
from ... | comet-atomic-2020-master | models/comet_atomic2020_bart/utils.py |
import logging
import os
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
def count_trainable_parameters(model):
model_parameters = filter(lambda p: p.requires_gra... | comet-atomic-2020-master | models/comet_atomic2020_bart/callbacks.py |
import json
import torch
import argparse
from tqdm import tqdm
from pathlib import Path
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
from utils import calculate_rouge, use_task_specific_params, calculate_bleu_score, trim_batch
def chunks(lst, n):
"""Yield successive n-sized chunks from lst."""
... | comet-atomic-2020-master | models/comet_atomic2020_bart/generation_example.py |
import argparse
import glob
import logging
import os
import time
import warnings
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from torch.utils.data import DataLoader
from lightning_base import BaseTrans... | comet-atomic-2020-master | models/comet_atomic2020_bart/finetune.py |
import argparse
import gc
import os
from pathlib import Path
from typing import List
import pytorch_lightning as pl
import torch
from torch import nn
from torch.nn import functional as F
from lightning_base import generic_train
from transformers import AdamW, BartConfig, BartForConditionalGeneration, T5Config, T5ForC... | comet-atomic-2020-master | models/comet_atomic2020_bart/distillation.py |
# Importing stock libraries
import json
from typing import List
import numpy as np
import pandas as pd
import torch
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader, RandomSampler, SequentialSampler
# Importing the T5 modules from huggingface/transformers
from transformers import T5Tok... | comet-atomic-2020-master | models/gpt2_zeroshot/gpt2-zeroshot.py |
# Importing stock libraries
import numpy as np
import pandas as pd
import torch
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader, RandomSampler, SequentialSampler
import json
from typing import List
# Importing the GPT2 modules from huggingface/transformers
from transformers import GPT2... | comet-atomic-2020-master | models/comet_atomic2020_gpt2/comet_gpt2.py |
import csv
relations = set()
with open('../old_data/atomic2020_train.tsv') as file:
reader = csv.DictReader(file, delimiter='\t')
for row in reader:
relations.add(row['relation'])
with open('../old_data/atomic_train.tsv') as file:
reader = csv.DictReader(file, delimiter='\t')
for row in reader... | comet-atomic-2020-master | scripts/retrieve_special_tokens.py |
import sys
import csv
writer = csv.DictWriter(open('../data/atomic_test.tsv', 'w'), delimiter='\t', fieldnames=['relation', 'head_event', 'tail_event'])
writer.writeheader()
with open(sys.argv[1]) as file:
reader = csv.DictReader(file, delimiter='\t', fieldnames=['head', 'relation', 'tail', 'id1', 'id2', 'score']... | comet-atomic-2020-master | scripts/convert_atomic.py |
import sys
import csv
writer = csv.DictWriter(open(f'../data/{sys.argv[1].split("/")[-1].split("_")[0]}_{sys.argv[1].split("/")[-1].split("_")[-1].split(".")[0]}.tsv', 'w'), delimiter='\t', fieldnames=['relation', 'head_event', 'tail_event'])
writer.writeheader()
with open(sys.argv[1]) as file:
reader = csv.DictR... | comet-atomic-2020-master | scripts/convert_ronan.py |
import pandas as pd
import transformers
import os
from transformers import T5Tokenizer
train_dataset = pd.read_csv('../data/atomic2020_train.tsv', encoding='latin-1', sep="\t")
train_dataset = train_dataset[['head_event','tail_event','relation']]
train_dataset.head_event = train_dataset.head_event + ' ' + train_datas... | comet-atomic-2020-master | scripts/calculate_max_len.py |
import sys
import csv
writer = csv.DictWriter(open('../data/conceptnet_dev.tsv', 'w'), delimiter='\t', fieldnames=['relation', 'head', 'tail'])
writer.writeheader()
with open(sys.argv[1]) as file:
reader = csv.DictReader(file, delimiter='\t', fieldnames=['relation', 'head', 'tail', 'score'])
for row in reader... | comet-atomic-2020-master | scripts/convert_conceptnet.py |
import json
import sys
import csv
import operator
import random
def read_csv(input_file, quotechar='"', delimiter=",", skip_header=False):
"""Reads a tab separated value file."""
with open(input_file, "r") as f:
reader = csv.reader(f, delimiter=delimiter, quotechar=quotechar, quoting=csv.QUOTE_ALL, sk... | comet-atomic-2020-master | system_eval/utils.py |
import argparse
import numpy as np
from nltk.translate.bleu_score import sentence_bleu
from utils import read_jsonl, remove_prefix, write_jsonl
from evaluation.eval import QGEvalCap
from tabulate import tabulate
import json
import os
from collections import defaultdict
import random
def get_reference_sentences(filenam... | comet-atomic-2020-master | system_eval/automatic_eval.py |
comet-atomic-2020-master | system_eval/evaluation/__init__.py | |
from evaluation.bleu.bleu import Bleu
from evaluation.meteor.meteor_nltk import Meteor
from evaluation.rouge.rouge import Rouge
from evaluation.cider.cider import Cider
from evaluation.bert_score.bert_score import BertScore
from collections import defaultdict
from argparse import ArgumentParser
import sys
import json
... | comet-atomic-2020-master | system_eval/evaluation/eval.py |
# Filename: cider.py
#
# Description: Describes the class to compute the CIDEr (Consensus-Based Image Description Evaluation) Metric
# by Vedantam, Zitnick, and Parikh (http://arxiv.org/abs/1411.5726)
#
# Creation Date: Sun Feb 8 14:16:54 2015
#
# Authors: Ramakrishna Vedantam <vrama91@vt.edu> and Tsung... | comet-atomic-2020-master | system_eval/evaluation/cider/cider.py |
__author__ = 'tylin'
| comet-atomic-2020-master | system_eval/evaluation/cider/__init__.py |
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