python_code stringlengths 0 187k | repo_name stringlengths 8 46 | file_path stringlengths 6 135 |
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# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_array_almost_equal
from keras.layers import Input, Lambda
from keras.models import Model
from deep_qa.layers.wrappers import TimeDistributed
from deep_qa.testing.test_case import DeepQaTestCase
class TestTimeDistributed(DeepQaTes... | deep_qa-master | tests/layers/wrappers/time_distributed_test.py |
deep_qa-master | tests/layers/wrappers/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import numpy
from deep_qa.layers.encoders import BOWEncoder
from deep_qa.layers.wrappers import EncoderWrapper, OutputMask
from deep_qa.testing.test_case import DeepQaTestCase
from deep_qa.training.models import DeepQaModel
from keras.layers import Embedding, Input
class Tes... | deep_qa-master | tests/layers/wrappers/encoder_wrapper_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from keras import backend as K
from keras.layers import Input
from keras.models import Model
from deep_qa.layers.attention.masked_softmax import MaskedSoftmax
class TestMaskedSoftmaxLayer:
def test_call_works_with_no_mask(self):
batch_size = 1
... | deep_qa-master | tests/layers/attention/masked_softmax_test.py |
deep_qa-master | tests/layers/attention/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_almost_equal
import keras.backend as K
from keras.layers import Input
from keras.models import Model
from deep_qa.layers.attention import GatedAttention
class TestGatedAttentionLayer:
def test_multiplication(self):
d... | deep_qa-master | tests/layers/attention/gated_attention_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from keras.layers import Embedding, Input
from keras.models import Model
from deep_qa.layers.attention import WeightedSum
class TestWeightedSumLayer:
def test_call_works_on_simple_input(self):
batch_size = 1
sentence_length = 5
embed... | deep_qa-master | tests/layers/attention/weighted_sum_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_allclose
from keras.layers import Dense, Embedding, Input
from keras.models import Model, load_model
from deep_qa.layers.attention import MatrixAttention
from deep_qa.layers.wrappers import OutputMask
from deep_qa.testing.test_case... | deep_qa-master | tests/layers/attention/matrix_attention_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_almost_equal
from keras.layers import Embedding, Input
from keras.models import Model
import keras.backend as K
from deep_qa.layers.attention import Attention
from deep_qa.layers.wrappers import OutputMask
class TestAttentionLa... | deep_qa-master | tests/layers/attention/attention_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_allclose
from keras.layers import Input, Dense
from keras.models import Model
from deep_qa.layers.backend import CollapseToBatch, ExpandFromBatch, AddMask
class TestCollapseAndExpand:
# We need to test CollapseToBatch and E... | deep_qa-master | tests/layers/backend/collapse_and_expand_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_almost_equal
from keras.layers import Input
from keras.models import Model
from deep_qa.layers.backend import AddMask, ReplaceMaskedValues
class TestReplaceMaskedValues:
def test_call_works_on_simple_input(self):
inp... | deep_qa-master | tests/layers/backend/replace_masked_values_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from keras.layers import Input
from keras.models import Model
from deep_qa.layers.backend.add_mask import AddMask
from deep_qa.layers.backend.multiply import Multiply
from deep_qa.layers.wrappers import OutputMask
class TestMultiply:
def test_call_works_on_... | deep_qa-master | tests/layers/backend/multiply_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from keras.layers import Input
from keras.models import Model
from deep_qa.layers.backend import Permute
class TestPermuteLayer:
def test_call_works_on_simple_input(self):
batch_size = 2
input_length_1 = 2
input_length_2 = 1
... | deep_qa-master | tests/layers/backend/permute_test.py |
deep_qa-master | tests/layers/backend/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import numpy
from keras.layers import Input
from keras.models import Model
from deep_qa.layers.backend import Max
class TestMaxLayer:
def test_call_works_on_simple_input(self):
batch_size = 2
input_length = 5
input_layer = Input(shape=(input_leng... | deep_qa-master | tests/layers/backend/max_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_almost_equal
import keras.backend as K
from keras.layers import Input, Masking
from keras.models import Model
from deep_qa.layers.backend import BatchDot
from deep_qa.layers.wrappers import OutputMask
from deep_qa.testing.test_case... | deep_qa-master | tests/layers/backend/batch_dot_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from keras.layers import Input
from keras.models import Model
from deep_qa.layers.backend import Envelope
class TestEnvelopeLayer:
def test_call_works_on_simple_input(self):
batch_size = 1
sequence_length = 5
span_begin_input = Input... | deep_qa-master | tests/layers/backend/envelope_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from keras.layers import Input
from keras.models import Model
from deep_qa.layers.backend import Repeat
class TestRepeatLayer:
def test_call_works_on_simple_input(self):
batch_size = 2
input_length = 3
repetitions = 4
input_l... | deep_qa-master | tests/layers/backend/repeat_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from keras.layers import Input
from keras.models import Model
from deep_qa.layers.backend import RepeatLike
class TestRepeatLikeLayer:
def test_call_works_on_simple_input(self):
batch_size = 2
input_length = 3
repetitions = 4
... | deep_qa-master | tests/layers/backend/repeat_like_test.py |
deep_qa-master | tests/layers/encoders/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import numpy
from keras.layers import Input, Embedding
from keras.models import Model
from deep_qa.layers.encoders import BOWEncoder
class TestBOWEncoder:
def test_on_unmasked_input(self):
sentence_length = 5
embedding_dim = 10
vocabulary_size = 1... | deep_qa-master | tests/layers/encoders/bow_encoder_test.py |
deep_qa-master | tests/training/__init__.py | |
# pylint: disable=no-self-use,invalid-name
from copy import deepcopy
import keras.backend as K
from deep_qa.common.params import Params
from deep_qa.models.text_classification import ClassificationModel
from deep_qa.testing.test_case import DeepQaTestCase
class TestMultiGpu(DeepQaTestCase):
def setUp(self):
... | deep_qa-master | tests/training/multi_gpu_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
import tensorflow
from deep_qa.common.params import Params
from deep_qa.testing.test_case import DeepQaTestCase
from deep_qa.training.train_utils import _get_dense_gradient_average, _get_sparse_gradient_average
from deep_qa.training.train_utils import pin_variable... | deep_qa-master | tests/training/train_utils_test.py |
# pylint: disable=invalid-name,no-self-use
import numpy
from numpy.testing import assert_almost_equal
from keras import backend as K
from deep_qa.testing.test_case import DeepQaTestCase
from deep_qa.training.losses import ranking_loss, ranking_loss_with_margin
class TestLosses(DeepQaTestCase):
def test_ranking_lo... | deep_qa-master | tests/training/losses_test.py |
# pylint: disable=no-self-use,invalid-name
from unittest import mock
from deep_qa.common.params import Params, pop_choice
from deep_qa.data.datasets import Dataset, SnliDataset
from deep_qa.layers.encoders import encoders
from deep_qa.models.text_classification import ClassificationModel
from deep_qa.testing.test_case... | deep_qa-master | tests/training/text_trainer_test.py |
deep_qa-master | tests/tensors/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_almost_equal, assert_array_almost_equal
import keras.backend as K
from deep_qa.tensors.backend import l1_normalize
from deep_qa.tensors.masked_operations import masked_batch_dot, masked_softmax
class TestMaskedOperations:
d... | deep_qa-master | tests/tensors/masked_operations_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from deep_qa.tensors.backend import hardmax
from deep_qa.testing.test_case import DeepQaTestCase
from keras import backend as K
class TestBackendTensorFunctions(DeepQaTestCase):
def test_hardmax(self):
batch_size = 3
knowledge_length = 5
... | deep_qa-master | tests/tensors/backend_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_almost_equal
import keras.backend as K
from deep_qa.tensors.similarity_functions.dot_product import DotProduct
class TestDotProductSimilarityFunction:
dot_product = DotProduct(name='dot_product')
def test_initialize_weig... | deep_qa-master | tests/tensors/similarity_functions/dot_product_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_almost_equal
import keras.backend as K
from deep_qa.tensors.similarity_functions.linear import Linear
class TestLinearSimilarityFunction:
def test_initialize_weights_returns_correct_weight_sizes(self):
linear = Linea... | deep_qa-master | tests/tensors/similarity_functions/linear_test.py |
deep_qa-master | tests/tensors/similarity_functions/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_almost_equal
import keras.backend as K
from deep_qa.tensors.similarity_functions.cosine_similarity import CosineSimilarity
from deep_qa.tensors.similarity_functions.dot_product import DotProduct
class TestCosineSimilarityFunctio... | deep_qa-master | tests/tensors/similarity_functions/cosine_similarity_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from numpy.testing import assert_almost_equal
import keras.backend as K
from deep_qa.tensors.similarity_functions.bilinear import Bilinear
class TestBilinearSimilarityFunction:
def test_initialize_weights_returns_correct_weight_sizes(self):
bilinear... | deep_qa-master | tests/tensors/similarity_functions/bilinear_test.py |
deep_qa-master | tests/models/__init__.py | |
deep_qa-master | tests/models/sequence_tagging/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import numpy
from deep_qa.common.params import Params
from deep_qa.models.sequence_tagging import SimpleTagger
from deep_qa.testing.test_case import DeepQaTestCase
class TestSimpleTagger(DeepQaTestCase):
def test_trains_and_loads_correctly(self):
self.write_seque... | deep_qa-master | tests/models/sequence_tagging/simple_tagger_test.py |
deep_qa-master | tests/models/entailment/__init__.py | |
# pylint: disable=no-self-use,invalid-name
from deep_qa.common.params import Params
from deep_qa.models.entailment import DecomposableAttention
from deep_qa.testing.test_case import DeepQaTestCase
class TestDecomposableAttentionModel(DeepQaTestCase):
def test_trains_and_loads_correctly(self):
self.write_... | deep_qa-master | tests/models/entailment/decomposable_attention_test.py |
deep_qa-master | tests/models/reading_comprehension/__init__.py | |
# pylint: disable=no-self-use,invalid-name
from deep_qa.common.params import Params
from deep_qa.models.reading_comprehension import AttentionSumReader
from deep_qa.testing.test_case import DeepQaTestCase
class TestAttentionSumReader(DeepQaTestCase):
def test_train_does_not_crash_and_load_works(self):
se... | deep_qa-master | tests/models/reading_comprehension/attention_sum_reader_test.py |
# pylint: disable=no-self-use,invalid-name
from deep_qa.common.params import Params
from deep_qa.models.reading_comprehension import GatedAttentionReader
from deep_qa.testing.test_case import DeepQaTestCase
class TestGatedAttention(DeepQaTestCase):
def test_cloze_train_does_not_crash(self):
self.write_wh... | deep_qa-master | tests/models/reading_comprehension/gated_attention_reader_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from deep_qa.common.params import Params
from deep_qa.models.reading_comprehension import BidirectionalAttentionFlow
from deep_qa.testing.test_case import DeepQaTestCase
from flaky import flaky
class TestBidirectionalAttentionFlow(DeepQaTestCase):
@flaky
... | deep_qa-master | tests/models/reading_comprehension/bidirectional_attention_test.py |
deep_qa-master | tests/common/__init__.py | |
from deep_qa.common.checks import ensure_pythonhashseed_set
def test_pythonhashseed():
ensure_pythonhashseed_set()
| deep_qa-master | tests/common/pythonhashseed_test.py |
# pylint: disable=no-self-use,invalid-name
from deep_qa.common import util
from deep_qa.testing.test_case import DeepQaTestCase
class TestCommonUtils(DeepQaTestCase):
def test_group_by_count(self):
assert util.group_by_count([1, 2, 3, 4, 5, 6, 7], 3, 20) == [[1, 2, 3], [4, 5, 6], [7, 20, 20]]
| deep_qa-master | tests/common/test_util.py |
# pylint: disable=no-self-use,invalid-name
import gzip
import numpy
import pytest
from deep_qa.common.checks import ConfigurationError
from deep_qa.data.data_indexer import DataIndexer
from deep_qa.data.embeddings import PretrainedEmbeddings
from deep_qa.models.text_classification import ClassificationModel
from deep_... | deep_qa-master | tests/data/embeddings_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from deep_qa.common.params import Params
from deep_qa.data import DataGenerator, IndexedDataset
from deep_qa.testing.test_case import DeepQaTestCase
class TestDataGenerator(DeepQaTestCase):
def setUp(self):
super(TestDataGenerator, self).setUp()
... | deep_qa-master | tests/data/data_generator_test.py |
deep_qa-master | tests/data/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import codecs
from deep_qa.data.data_indexer import DataIndexer
from deep_qa.data.datasets import TextDataset
from deep_qa.data.instances.text_classification.text_classification_instance import TextClassificationInstance
from deep_qa.testing.test_case import DeepQaTestCase
c... | deep_qa-master | tests/data/data_indexer_test.py |
# pylint: disable=no-self-use,invalid-name
from deep_qa.data.tokenizers.word_processor import WordProcessor
from deep_qa.common.params import Params
class TestWordProcessor:
def test_passes_through_correctly(self):
word_processor = WordProcessor(Params({}))
sentence = "this (sentence) has 'crazy' ... | deep_qa-master | tests/data/tokenizers/word_processor_test.py |
# pylint: disable=no-self-use,invalid-name
from deep_qa.data.tokenizers.word_tokenizer import WordTokenizer
from deep_qa.common.params import Params
class TestTokenizer:
tokenizer = WordTokenizer(Params({}))
passage = "On January 7, 2012, Beyoncé gave birth to her first child, a daughter, Blue Ivy " +\
... | deep_qa-master | tests/data/tokenizers/tokenizer_test.py |
# pylint: disable=no-self-use,invalid-name
from deep_qa.data.tokenizers.word_splitter import SimpleWordSplitter
from deep_qa.data.tokenizers.word_splitter import SpacyWordSplitter
class TestSimpleWordSplitter:
word_splitter = SimpleWordSplitter()
def test_tokenize_handles_complex_punctuation(self):
s... | deep_qa-master | tests/data/tokenizers/word_splitter_test.py |
deep_qa-master | tests/data/dataset_readers/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import random
from os.path import join
import numpy
from deep_qa.data.dataset_readers.squad_sentence_selection_reader import SquadSentenceSelectionReader
from deep_qa.testing.test_case import DeepQaTestCase
from overrides import overrides
class TestSquadSentenceSelectionRea... | deep_qa-master | tests/data/dataset_readers/squad_sentence_selection_reader_test.py |
# pylint: disable=no-self-use,invalid-name
from deep_qa.data.datasets import SnliDataset
from deep_qa.data.instances.entailment.snli_instance import SnliInstance
from deep_qa.testing.test_case import DeepQaTestCase
class TestSnliDataset(DeepQaTestCase):
def setUp(self):
super(TestSnliDataset, self).setU... | deep_qa-master | tests/data/datasets/snli_dataset_test.py |
deep_qa-master | tests/data/datasets/__init__.py | |
# pylint: disable=no-self-use,invalid-name
from deep_qa.data.datasets.dataset import Dataset, TextDataset
from deep_qa.data.instances.text_classification.text_classification_instance import TextClassificationInstance
from deep_qa.testing.test_case import DeepQaTestCase
class TestDataset:
def test_merge(self):
... | deep_qa-master | tests/data/datasets/dataset_test.py |
# pylint: disable=no-self-use,invalid-name
from deep_qa.common.params import Params
from deep_qa.data.datasets import LanguageModelingDataset
from deep_qa.data.instances.language_modeling.sentence_instance import SentenceInstance
from deep_qa.testing.test_case import DeepQaTestCase
class TestLanguageModellingDataset(... | deep_qa-master | tests/data/datasets/language_modeling_dataset_test.py |
# pylint: disable=no-self-use,invalid-name
from deep_qa.common.params import Params
from deep_qa.data.data_indexer import DataIndexer
from deep_qa.data.instances.instance import TextInstance
from deep_qa.data.instances.text_classification import IndexedTextClassificationInstance
from deep_qa.data.instances.text_classif... | deep_qa-master | tests/data/instances/text_instance_test.py |
deep_qa-master | tests/data/instances/__init__.py | |
deep_qa-master | tests/data/instances/sequence_tagging/__init__.py | |
# pylint: disable=no-self-use,invalid-name
from deep_qa.data.instances.sequence_tagging.tagging_instance import IndexedTaggingInstance
from deep_qa.testing.test_case import DeepQaTestCase
from numpy.testing import assert_array_almost_equal
class TestIndexedTaggingInstance(DeepQaTestCase):
def setUp(self):
... | deep_qa-master | tests/data/instances/sequence_tagging/test_tagging_instance.py |
# pylint: disable=no-self-use,invalid-name
from typing import List
from deep_qa.common.params import Params
from deep_qa.data.data_indexer import DataIndexer
from deep_qa.data.instances.instance import TextInstance
from deep_qa.data.instances.sequence_tagging.pretokenized_tagging_instance import PreTokenizedTaggingIns... | deep_qa-master | tests/data/instances/sequence_tagging/pretokenized_tagging_instance_test.py |
deep_qa-master | tests/data/instances/entailment/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import pytest
from deep_qa.data.data_indexer import DataIndexer
from deep_qa.data.instances.entailment.snli_instance import SnliInstance
class TestSnliInstance:
@staticmethod
def instance_to_line(text: str, hypothesis: str, label: str, index=None):
line = ''... | deep_qa-master | tests/data/instances/entailment/snli_instance_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy
from deep_qa.data.instances.entailment.sentence_pair_instance import IndexedSentencePairInstance
from deep_qa.testing.test_case import DeepQaTestCase
class TestIndexedSentencePairInstance(DeepQaTestCase):
def test_get_padding_lengths_returns_max_of_both_sen... | deep_qa-master | tests/data/instances/entailment/sentence_pair_instance_test.py |
# pylint: disable=no-self-use,invalid-name
import numpy as np
from deep_qa.data.data_indexer import DataIndexer
# pylint: disable=line-too-long
from deep_qa.data.instances.reading_comprehension.mc_question_passage_instance import IndexedMcQuestionPassageInstance
from deep_qa.data.instances.reading_comprehension.mc_ques... | deep_qa-master | tests/data/instances/reading_comprehension/mc_question_passage_instance_test.py |
deep_qa-master | tests/data/instances/reading_comprehension/__init__.py | |
# pylint: disable=no-self-use,invalid-name
from typing import Tuple
import numpy
from deep_qa.data.data_indexer import DataIndexer
from deep_qa.data.instances.reading_comprehension.character_span_instance import CharacterSpanInstance
from deep_qa.testing.test_case import DeepQaTestCase
class TestCharacterSpanInstanc... | deep_qa-master | tests/data/instances/reading_comprehension/character_span_instance_test.py |
deep_qa-master | tests/data/instances/text_classification/__init__.py | |
# pylint: disable=no-self-use,invalid-name
import numpy
from deep_qa.data.instances.text_classification import IndexedTextClassificationInstance
from deep_qa.data.instances.text_classification import TextClassificationInstance
from deep_qa.testing.test_case import DeepQaTestCase
class TestTextClassificationInstance:... | deep_qa-master | tests/data/instances/text_classification/text_classification_instance_test.py |
deep_qa-master | tests/data/instances/language_modeling/__init__.py | |
# pylint: disable=no-self-use,invalid-name
from deep_qa.common.params import Params
from deep_qa.data.data_indexer import DataIndexer
from deep_qa.data.instances import TextInstance
from deep_qa.data.instances.language_modeling import IndexedSentenceInstance
from deep_qa.data.instances.language_modeling import Sentence... | deep_qa-master | tests/data/instances/language_modeling/sentence_instance_test.py |
# -*- coding: utf-8 -*-
"""
This script takes as input raw TSV files from the Omnibus dataset and
preprocesses them to be compatible with the deep_qa pipeline.
"""
import logging
import os
import csv
from argparse import ArgumentParser
import pandas
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
... | deep_qa-master | scripts/clean_raw_omnibus.py |
import logging
import os
import sys
# pylint: disable=wrong-import-position
sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
from deep_qa import run_model_from_file, evaluate_model
from deep_qa.common.checks import ensure_pythonhashseed_set
logger = logging.getLogger(__name__) # pylint: disable=invalid... | deep_qa-master | scripts/run_model.py |
# -*- coding: utf-8 -*-
"""
This script takes as input CSV files from the Maluuba NewsQA dataset.
The dataset is quite dirty by default, so this script does some preprocessing
and extracts the relevant information we neeed in the deep_qa library.
"""
import json
import logging
import os
import re
from argparse import ... | deep_qa-master | scripts/clean_newsqa.py |
import logging
import os
import sys
# pylint: disable=wrong-import-position
sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
from deep_qa import score_dataset_with_ensemble, compute_accuracy
from deep_qa.common.checks import ensure_pythonhashseed_set
logger = logging.getLogger(__name__) # pylint: disab... | deep_qa-master | scripts/run_ensemble.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# deep_qa documentation build configuration file, created by
# sphinx-quickstart on Wed Jan 25 11:35:07 2017.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# au... | deep_qa-master | doc/conf.py |
import logging
import os
import openai
from diskcache import Cache
logger = logging.getLogger(__name__)
cache = Cache(os.path.expanduser("~/.cache/gpt3calls"))
@cache.memoize()
def cached_openai_call( # kwargs doesn't work with caching.
prompt, engine, temperature, max_tokens, top_p,
frequency_pen... | DecomP-main | src/decomp/models/gpt3generator.py |
import requests
class LLMClientGenerator:
# Instructions to start the LLM Server are in the README here:
# https://github.com/harshTrivedi/llm_server
def __init__(self, model_name, host, port,
max_input=None, max_tokens=100,
min_length=1, do_sample=False, stop=["\n"],
... | DecomP-main | src/decomp/models/llm_client_generator.py |
import json
import re
from decomp.models.gpt3generator import GPT3Generator
from decomp.models.llm_client_generator import LLMClientGenerator
class LLMQAModel:
def __init__(self, prompt_file="", regex_extract=None, add_context=True, gen_model="gpt3",
**kwargs):
if prompt_file:
... | DecomP-main | src/decomp/models/llm_qa_model.py |
import torch
from transformers import AutoConfig, AutoTokenizer, AutoModelWithLMHead
from transformers.generation_utils import SampleEncoderDecoderOutput
import logging
logger = logging.getLogger(__name__)
class LMGenerator:
def __init__(self, model_path, device=None,
generation_args={}, encode... | DecomP-main | src/decomp/models/generator.py |
"""
Script to build dataset for concatenating letters from words.
E.g.
Take the letters at position 3 of the words in "Nestor Geng Duran" and concatenate them.
Sample usage:
python -m decomp.datasets_utils.build_letter_cat_dataset \
--input_first_names configs/letter_datasets/first_names.txt \
--input_last_nam... | DecomP-main | src/decomp/datasets_utils/build_letter_cat_dataset.py |
# Reverse the sequence "card, stamp, book, water, glasses".
import argparse
import logging
import json
import math
import os
import random
import string
log = logging.getLogger(__name__)
questions = {
("reversed", "words"): 'Reverse the sequence "{}".',
("reversed", "letters"): 'Reverse the sequence "{}".',
... | DecomP-main | src/decomp/datasets_utils/build_reverse_dataset.py |
#!/usr/bin/python
from collections import defaultdict
from typing import Any, Dict, List, Set, Tuple, Union, Optional
import json
import argparse
import string
import re
import sys
import numpy as np
from scipy.optimize import linear_sum_assignment
# From here through _normalize_answer was originally copied from:
#... | DecomP-main | src/decomp/datasets_utils/drop_eval.py |
from __future__ import annotations
import json
from dataclasses import dataclass
from typing import Any
class BasicDataInstance(dict):
_REQUIRED_ATTRS = set([])
def __init__(self, input_data):
dict.__init__({})
self.update(input_data)
for item in type(self)._REQUIRED_ATTRS:
... | DecomP-main | src/decomp/inference/data_instances.py |
import json
from datetime import datetime
from dateutil.parser import parse
from decomp.models.llm_qa_model import LLMQAModel
from decomp.inference.data_instances import QuestionAnsweringStep, StructuredDataInstance
from decomp.inference.model_search import ParticipantModel
from decomp.inference.participant_qgen impo... | DecomP-main | src/decomp/inference/participant_qa.py |
import json
import logging
import re
from json import JSONDecodeError
from decomp.inference.utils import flatten_list, get_answer_indices
from decomp.inference.data_instances import Task, QuestionGenerationStep, AnswerSubOperationStep, \
QuestionAnsweringStep, StructuredDataInstance, QuestionParsingStep
from decom... | DecomP-main | src/decomp/inference/participant_execution_routed.py |
from typing import Dict
from decomp.inference.dataset_readers import HotpotQAReader, DatasetReader, DropReader
from decomp.inference.participant_execution_routed import RoutedExecutionParticipant
from decomp.inference.participant_qa import ExprEvalQAParticipantModel, LLMQAParticipantModel, \
LLMQADecompParticipant... | DecomP-main | src/decomp/inference/constants.py |
DecomP-main | src/decomp/inference/__init__.py | |
import logging
import math
import random
import re
from itertools import product, permutations
from decomp.inference.data_instances import QuestionGenerationStep, Task
from decomp.inference.model_search import ParticipantModel
from decomp.inference.utils import get_sequence_representation, stem_filter_tokenization, BL... | DecomP-main | src/decomp/inference/participant_qgen.py |
import os
import re
from typing import List, Dict
from nltk import word_tokenize
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
stemmer = PorterStemmer()
stop_words_set = set(stopwords.words('english'))
QUESTION_MARKER = " Q: "
COMPQ_MARKER = " QC: "
SIMPQ_MARKER = " QS: "
INTERQ_MARKE... | DecomP-main | src/decomp/inference/utils.py |
import argparse
import json
import logging
import os
import _jsonnet
from decomp.inference.constants import MODEL_NAME_CLASS, READER_NAME_CLASS
from decomp.inference.dataset_readers import DatasetReader
from decomp.inference.model_search import (
ModelController,
BestFirstDecomposer)
from decomp.inference.dat... | DecomP-main | src/decomp/inference/configurable_inference.py |
import copy
import heapq
import json
import logging
from decomp.inference.data_instances import BasicDataInstance
class ParticipantModel(object):
"""Base model in this case for coordinating different models. Provides a general
class to structure all contributing models (in this case, by defining a single
... | DecomP-main | src/decomp/inference/model_search.py |
import re
from decomp.inference.data_instances import QuestionAnsweringStep
from decomp.inference.model_search import ParticipantModel
from decomp.inference.utils import get_sequence_representation
class DumpChainsParticipant(ParticipantModel):
def __init__(self, output_file, next_model="gen"):
self.out... | DecomP-main | src/decomp/inference/participant_util.py |
import json
class DatasetReader:
def __init__(self, add_paras=False, add_gold_paras=False):
self.add_paras = add_paras
self.add_gold_paras = add_gold_paras
def read_examples(self, file):
return NotImplementedError("read_examples not implemented by " + self.__class__.__name__)
class... | DecomP-main | src/decomp/inference/dataset_readers.py |
from setuptools import setup, find_packages
import os
# PEP0440 compatible formatted version, see:
# https://www.python.org/dev/peps/pep-0440/
#
# release markers:
# X.Y
# X.Y.Z # For bugfix releases
#
# pre-release markers:
# X.YaN # Alpha release
# X.YbN # Beta release
# X.YrcN # Release Candidate
#... | allennlp-models-main | setup.py |
import os
import glob
from typing import Dict, Union, Any
from allennlp.common import Params
from allennlp.predictors import Predictor
from allennlp.common.model_card import ModelCard
from allennlp.common.task_card import TaskCard
from allennlp.common.plugins import import_plugins
def get_tasks() -> Dict[str, TaskC... | allennlp-models-main | allennlp_models/pretrained.py |
import os
_MAJOR = "2"
_MINOR = "10"
_PATCH = "1"
# This is mainly for nightly builds which have the suffix ".dev$DATE". See
# https://semver.org/#is-v123-a-semantic-version for the semantics.
_SUFFIX = os.environ.get("ALLENNLP_MODELS_VERSION_SUFFIX", "")
VERSION_SHORT = "{0}.{1}".format(_MAJOR, _MINOR)
VERSION = "{0... | allennlp-models-main | allennlp_models/version.py |
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