repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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AOE-Net | AOE-Net-main/evaluation_anet/utils.py | import json
import urllib2
import numpy as np
API = 'http://ec2-52-11-11-89.us-west-2.compute.amazonaws.com/challenge16/api.py'
def get_blocked_videos(api=API):
api_url = '{}?action=get_blocked'.format(api)
req = urllib2.Request(api_url)
response = urllib2.urlopen(req)
return json.loads(response.rea... | 2,652 | 32.1625 | 81 | py |
AOE-Net | AOE-Net-main/evaluation_thumos/prop_eval.py | import io
import requests
import sys
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pickle
import json
import os
def pkl2dataframe(frm_nums, movie_fps_file, result_file):
data_frame = []
movie_fps = pickle.load(open(movie_fps_file, 'rb'))
... | 22,153 | 42.269531 | 108 | py |
advectionDiffusion | advectionDiffusion-main/Simulator.py | """
Forward model in the advection diffusion example.
Ms spatio-temporal model we separate it into the underlying grid
and the actual model propagation.
"""
import numpy as np
import os
from matplotlib import pyplot as plt
from scipy.linalg.special_matrices import toeplitz
import Sampler
class Grid:
"""Grid ... | 8,003 | 30.888446 | 122 | py |
advectionDiffusion | advectionDiffusion-main/Statistics.py | """
Mean and Variance for the advection diffusion example
(eventually in ensemble representation)
"""
import Ensemble
import Sampler
import numpy as np
import linecache
from matplotlib import pyplot as plt
from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
import copy
class Statistics:
def __... | 8,629 | 39.327103 | 167 | py |
advectionDiffusion | advectionDiffusion-main/Comparer.py | import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
from mpl_toolkits.axes_grid1 import AxesGrid
import scipy.stats
from statsmodels.distributions.empirical_distribution import ECDF
class Comparer:
def __init__(self, statistics_kf, stati... | 24,976 | 50.605372 | 167 | py |
advectionDiffusion | advectionDiffusion-main/RunningWriter.py | import numpy as np
import os
import datetime
class RunningWriter:
def __init__(self, trials, N_poi, N_corr_poi):
self.trials = trials
self.N_poi = N_poi
self.N_corr_poi = N_corr_poi
self.mean_rmse_etkfs = np.zeros(trials)
self.mean_rmse_letkfs = np.zeros(trials)
... | 8,360 | 45.709497 | 146 | py |
advectionDiffusion | advectionDiffusion-main/IEWParticleFilter.py | """
Kalman filter update for advection diffusion example.
"""
import numpy as np
from scipy.special import gammainc
from scipy.special import lambertw
from scipy.optimize import fsolve
from scipy.linalg import sqrtm
import sys
class IEWParticle:
def __init__(self, statistics, observation, beta=None, alpha=None... | 3,123 | 30.877551 | 172 | py |
advectionDiffusion | advectionDiffusion-main/TruthGenerator.py | import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
import Sampler
def plot_kernel(grid, prior_args):
"""Plotting 1D Matern kernel for given phi on the half x domain of the grid"""
matern_phi = prior_args["matern_phi"]
# Plot kernel... | 2,674 | 33.294872 | 106 | py |
advectionDiffusion | advectionDiffusion-main/Ensemble.py |
import numpy as np
class Ensemble:
def __init__(self, simulator, N_e):
self.simulator = simulator
self.N_e = N_e
# Allocation
self.ensemble = np.zeros((self.simulator.grid.N_x, self.N_e))
def initialize(self, prior_sampler):
self.ensemble = prior_... | 409 | 19.5 | 69 | py |
advectionDiffusion | advectionDiffusion-main/SLETKalmanFilter.py | """
Kalman filter update for advection diffusion example.
"""
import numpy as np
class SLETKalman:
def __init__(self, statistics, observation, scale_r, scale_w=1.0):
self.statistics = statistics
# Observation and obs error cov matrices
self.H = observation.H
self.R = obser... | 14,065 | 39.188571 | 168 | py |
advectionDiffusion | advectionDiffusion-main/ETKalmanFilter.py | """
Kalman filter update for advection diffusion example.
"""
import numpy as np
class ETKalman:
def __init__(self, statistics, observation):
self.statistics = statistics
# Observation and obs error cov matrices
self.H = observation.H
self.R = observation.R
def filter... | 1,324 | 29.113636 | 101 | py |
advectionDiffusion | advectionDiffusion-main/run_FilteringComparisonLocalisation.py | # %%
"""
Example:
python run_FilteringComparison.py -m ensemble_size
"""
# %%
import numpy as np
# %%
import Sampler
import Simulator
import Observation
import Statistics
import KalmanFilter
import ETKalmanFilter
import SLETKalmanFilter
import IEWParticleFilter
import Comparer
import RunningWriter
# %%
# Initia... | 5,114 | 31.169811 | 140 | py |
advectionDiffusion | advectionDiffusion-main/run_FilteringComparison.py | """
Example:
python run_FilteringComparison.py -m ensemble_size
"""
import Simulator
import Observation
import Statistics
import KalmanFilter
import ETKalmanFilter
import SLETKalmanFilter
import IEWParticleFilter
import Comparer
import RunningWriter
# Initialisation
print("Initialising...")
timestamp = "2022_03_02... | 8,317 | 39.183575 | 239 | py |
advectionDiffusion | advectionDiffusion-main/run_FilteringComparisonSpectrum.py | # %%
"""
Example:
python run_FilteringComparison.py -m ensemble_size
"""
# %%
import numpy as np
# %%
import Sampler
import Simulator
import Observation
import Statistics
import KalmanFilter
import ETKalmanFilter
import SLETKalmanFilter
import IEWParticleFilter
import Comparer
import RunningWriter
# %%
# Initia... | 5,977 | 36.130435 | 120 | py |
advectionDiffusion | advectionDiffusion-main/Sampler.py | import numpy as np
class Sampler:
def __init__(self, grid, args):
self.grid = grid
self.args = args
self.construct()
def construct(self):
# Mean: constant lift
mean_lift = self.args["mean_upshift"]*np.ones(self.grid.N_x)
if "bell_scaling" in self.args.keys(... | 3,320 | 33.957895 | 111 | py |
advectionDiffusion | advectionDiffusion-main/Observation.py | import numpy as np
import linecache
from matplotlib import pyplot as plt
class Observation:
"""Observations in the advection diffusion example.
Handling observation values and construction observation operator"""
def __init__(self, grid, noise_stddev=0.1):
self.grid = grid
self.noise_stddev... | 3,648 | 30.188034 | 114 | py |
advectionDiffusion | advectionDiffusion-main/KalmanFilter.py | """
Kalman filter update for advection diffusion example.
"""
import numpy as np
class Kalman:
def __init__(self, statistics, observation):
self.statistics = statistics
# Observation and obs error cov matrices
self.H = observation.H
self.R = observation.R
def filter(self, for... | 724 | 29.208333 | 103 | py |
advectionDiffusion | advectionDiffusion-main/run_FilteringComparisonLocalisationSingle.py | # %%
"""
Example:
python run_FilteringComparison.py -m ensemble_size
"""
# %%
import numpy as np
# %%
import Sampler
import Simulator
import Observation
import Statistics
import KalmanFilter
import ETKalmanFilter
import SLETKalmanFilter
import IEWParticleFilter
import Comparer
import RunningWriter
# %%
# Initia... | 5,166 | 31.29375 | 140 | py |
flair | flair-master/setup.py | from pathlib import Path
from setuptools import find_packages, setup
required = Path("requirements.txt").read_text(encoding="utf-8").split("\n")
setup(
name="flair",
version="0.12.2",
description="A very simple framework for state-of-the-art NLP",
long_description=Path("README.md").read_text(encoding... | 666 | 29.318182 | 75 | py |
flair | flair-master/collect_env.py | import torch
import transformers
import flair
def main():
print("#### Versions:")
print(f"##### Flair\n{flair.__version__}")
print(f"##### Pytorch\n{torch.__version__}")
print(f"##### Transformers\n{transformers.__version__}")
print(f"#### GPU\n{torch.cuda.is_available()}")
if __name__ == "__ma... | 338 | 18.941176 | 60 | py |
flair | flair-master/examples/ner/run_ner.py | import inspect
import json
import logging
import os
import sys
from dataclasses import dataclass, field
import torch
from transformers import HfArgumentParser
import flair
from flair import set_seed
from flair.embeddings import TransformerWordEmbeddings
from flair.models import SequenceTagger
from flair.trainers impo... | 5,261 | 32.303797 | 112 | py |
flair | flair-master/examples/ner/__init__.py | 0 | 0 | 0 | py | |
flair | flair-master/flair/optim.py | import logging
import torch
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR, ReduceLROnPlateau, _LRScheduler
from torch.optim.optimizer import required # type: ignore[attr-defined]
log = logging.getLogger("flair")
class SGDW(Optimizer):
r"""Implements stochastic gradient descent... | 11,041 | 38.435714 | 120 | py |
flair | flair-master/flair/tokenization.py | import logging
import sys
from abc import ABC, abstractmethod
from typing import Callable, List
from segtok.segmenter import split_single
from segtok.tokenizer import split_contractions, word_tokenizer
log = logging.getLogger("flair")
class Tokenizer(ABC):
r"""An abstract class representing a :class:`Tokenizer`... | 9,873 | 33.645614 | 133 | py |
flair | flair-master/flair/inference_utils.py | import logging
import pickle
import re
import shutil
import sqlite3
from pathlib import Path
from typing import Union
import numpy as np
import torch
from tqdm import tqdm
import flair
from flair.embeddings import WordEmbeddings
# this is the default init size of a lmdb database for embeddings
DEFAULT_MAP_SIZE = 100... | 12,086 | 39.834459 | 112 | py |
flair | flair-master/flair/data.py | import bisect
import logging
import re
import typing
from abc import ABC, abstractmethod
from collections import Counter, defaultdict, namedtuple
from operator import itemgetter
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Union, cast
import torch
from deprecated import deprecated
from t... | 65,248 | 34.694201 | 138 | py |
flair | flair-master/flair/splitter.py | from abc import ABC, abstractmethod
from typing import Any, List, Optional, Union
from segtok.segmenter import split_multi
from flair.data import Sentence
from flair.tokenization import (
SciSpacyTokenizer,
SegtokTokenizer,
SpacyTokenizer,
Tokenizer,
)
class SentenceSplitter(ABC):
r"""An abstrac... | 7,853 | 29.207692 | 115 | py |
flair | flair-master/flair/training_utils.py | import logging
import random
import sys
from collections import defaultdict
from enum import Enum
from functools import reduce
from math import inf
from pathlib import Path
from typing import Dict, List, Optional, Union
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import mean_absolute_error, mean_s... | 14,157 | 32.709524 | 118 | py |
flair | flair-master/flair/file_utils.py | """Utilities for working with the local dataset cache. Copied from AllenNLP."""
import base64
import functools
import io
import logging
import mmap
import os
import re
import shutil
import tempfile
import typing
import warnings
import zipfile
from pathlib import Path
from typing import Optional, Sequence, Tuple, Union,... | 12,566 | 34.600567 | 109 | py |
flair | flair-master/flair/__init__.py | import logging.config
import os
from pathlib import Path
import torch
from transformers import set_seed as hf_set_seed
# global variable: cache_root
from .file_utils import set_proxies
cache_root = Path(os.getenv("FLAIR_CACHE_ROOT", Path(Path.home(), ".flair")))
device: torch.device
"""Flair is using a single devic... | 1,705 | 20.871795 | 106 | py |
flair | flair-master/flair/samplers.py | import logging
import random
from collections import defaultdict
from typing import Dict
import torch
from torch.utils.data.sampler import Sampler
log = logging.getLogger("flair")
class FlairSampler(Sampler):
def set_dataset(self, data_source):
"""Initialize the data source for the FlairSampler.
... | 3,688 | 30 | 116 | py |
flair | flair-master/flair/nn/model.py | import inspect
import itertools
import logging
import typing
from abc import ABC, abstractmethod
from collections import Counter
from pathlib import Path
from typing import Any, Dict, List, Optional, Set, Tuple, Union
import torch.nn
from torch.nn.modules.loss import _Loss
from torch.utils.data.dataset import Dataset
... | 41,127 | 41.443756 | 267 | py |
flair | flair-master/flair/nn/multitask.py | from typing import Iterable, Tuple, Union
from flair.data import Corpus, MultiCorpus
from flair.models import MultitaskModel
from flair.nn import Classifier, Model
def make_multitask_model_and_corpus(
mapping: Iterable[Union[Tuple[Classifier, Corpus], Tuple[Classifier, Corpus, float]]]
) -> Tuple[Model, Corpus]:... | 836 | 30 | 114 | py |
flair | flair-master/flair/nn/dropout.py | import torch
class LockedDropout(torch.nn.Module):
"""Implementation of locked (or variational) dropout.
Randomly drops out entire parameters in embedding space.
"""
def __init__(self, dropout_rate=0.5, batch_first=True, inplace=False) -> None:
super().__init__()
self.dropout_rate = ... | 1,747 | 29.666667 | 88 | py |
flair | flair-master/flair/nn/recurrent.py | from torch import nn
rnn_layers = {"lstm": (nn.LSTM, 2), "gru": (nn.GRU, 1)}
def create_recurrent_layer(layer_type, initial_size, hidden_size, nlayers, dropout=0, **kwargs):
layer_type = layer_type.lower()
assert layer_type in rnn_layers
module, hidden_count = rnn_layers[layer_type]
if nlayers == 1:... | 437 | 28.2 | 96 | py |
flair | flair-master/flair/nn/decoder.py | import logging
from typing import List, Optional
import torch
import flair
from flair.data import Dictionary, Sentence
from flair.embeddings import Embeddings
from flair.nn.distance import (
CosineDistance,
EuclideanDistance,
HyperbolicDistance,
LogitCosineDistance,
NegativeScaledDotProduct,
)
fro... | 8,375 | 38.140187 | 140 | py |
flair | flair-master/flair/nn/__init__.py | from .decoder import LabelVerbalizerDecoder, PrototypicalDecoder
from .dropout import LockedDropout, WordDropout
from .model import Classifier, DefaultClassifier, Model
__all__ = [
"LockedDropout",
"WordDropout",
"Classifier",
"DefaultClassifier",
"Model",
"PrototypicalDecoder",
"LabelVerba... | 337 | 23.142857 | 64 | py |
flair | flair-master/flair/nn/distance/hyperbolic.py | """Hyperbolic distances implemented in pytorch.
This module was copied from the repository the following repository:
https://github.com/asappresearch/dynamic-classification
It contains the code from the paper "Metric Learning for Dynamic Text
Classification".
https://arxiv.org/abs/1911.01026
In case this file is mo... | 3,718 | 25.949275 | 132 | py |
flair | flair-master/flair/nn/distance/euclidean.py | """Euclidean distances implemented in pytorch.
This module was copied from the repository the following repository:
https://github.com/asappresearch/dynamic-classification
It contains the code from the paper "Metric Learning for Dynamic Text
Classification".
https://arxiv.org/abs/1911.01026
In case this file is mod... | 1,839 | 26.462687 | 131 | py |
flair | flair-master/flair/nn/distance/cosine.py | import torch
# Source: https://github.com/UKPLab/sentence-transformers/blob/master/sentence_transformers/util.py#L23
def dot_product(a: torch.Tensor, b: torch.Tensor, normalize=False):
"""Computes dot product for pairs of vectors.
:param normalize: Vectors are normalized (leads to cosine similarity)
:re... | 1,129 | 27.974359 | 103 | py |
flair | flair-master/flair/nn/distance/__init__.py | from .cosine import CosineDistance, LogitCosineDistance, NegativeScaledDotProduct
from .euclidean import EuclideanDistance, EuclideanMean
from .hyperbolic import HyperbolicDistance, HyperbolicMean
__all__ = [
"EuclideanDistance",
"EuclideanMean",
"HyperbolicDistance",
"HyperbolicMean",
"CosineDista... | 387 | 26.714286 | 81 | py |
flair | flair-master/flair/models/text_regression_model.py | import logging
import typing
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data.dataset import Dataset
from tqdm import tqdm
import flair
import flair.embeddings
from flair.data import Corpus, Dictionary, Sentence, _iter_dataset
... | 9,039 | 36.201646 | 120 | py |
flair | flair-master/flair/models/pairwise_classification_model.py | import typing
from typing import List
import torch
import flair.embeddings
import flair.nn
from flair.data import Corpus, Sentence, TextPair, _iter_dataset
class TextPairClassifier(flair.nn.DefaultClassifier[TextPair, TextPair]):
"""Text Pair Classification Model for tasks such as Recognizing Textual Entailment... | 4,628 | 38.905172 | 118 | py |
flair | flair-master/flair/models/word_tagger_model.py | import logging
from pathlib import Path
from typing import Any, Dict, List, Union
import torch
import flair.nn
from flair.data import Dictionary, Sentence, Span, Token
from flair.embeddings import TokenEmbeddings
log = logging.getLogger("flair")
def WordTagger(embeddings, tag_dictionary, tag_type, **classifierargs... | 9,672 | 40.337607 | 120 | py |
flair | flair-master/flair/models/pairwise_regression_model.py | import typing
from pathlib import Path
from typing import Any, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data.dataset import Dataset
from tqdm import tqdm
import flair.embeddings
import flair.nn
from flair.data import Corpus, Dictionary, Sentence, TextPair, _iter_dataset
from fla... | 12,876 | 36.324638 | 119 | py |
flair | flair-master/flair/models/regexp_tagger.py | import re
import typing
from dataclasses import dataclass, field
from typing import Dict, List, Tuple, Union
from flair.data import Sentence, Span, Token
@dataclass
class TokenCollection:
"""A utility class for RegexpTagger to hold all tokens for a given Sentence and define some functionality.
:param senten... | 4,917 | 38.344 | 117 | py |
flair | flair-master/flair/models/sequence_tagger_model.py | import logging
import tempfile
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple, Union, cast
from urllib.error import HTTPError
import torch
import torch.nn
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
from tqdm import tqdm
import... | 45,746 | 43.500973 | 137 | py |
flair | flair-master/flair/models/clustering.py | import logging
import pickle
from collections import OrderedDict
from pathlib import Path
from typing import Optional, Union
import joblib
from sklearn.base import BaseEstimator, ClusterMixin
from sklearn.metrics import normalized_mutual_info_score
from tqdm import tqdm
from flair.data import Corpus, _iter_dataset
fr... | 4,340 | 36.422414 | 113 | py |
flair | flair-master/flair/models/multitask_model.py | import logging
import random
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
import flair.nn
from flair.data import DT, Dictionary, Sentence
from flair.file_utils import cached_path
from flair.nn import Classifier
from flair.training_utils import Result
log = logging.... | 10,773 | 38.756458 | 115 | py |
flair | flair-master/flair/models/entity_linker_model.py | import logging
import re
from functools import lru_cache
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Set, Union
from unicodedata import category
import torch
import flair.embeddings
import flair.nn
from flair.data import Dictionary, Sentence, Span
from flair.file_utils import cach... | 9,722 | 41.458515 | 188 | py |
flair | flair-master/flair/models/text_classification_model.py | import logging
from pathlib import Path
from typing import Any, Dict, List, Union
import torch
import flair.embeddings
import flair.nn
from flair.data import Sentence
from flair.file_utils import cached_path
log = logging.getLogger("flair")
class TextClassifier(flair.nn.DefaultClassifier[Sentence, Sentence]):
... | 4,864 | 34.510949 | 114 | py |
flair | flair-master/flair/models/relation_extractor_model.py | import logging
from pathlib import Path
from typing import Any, Dict, List, Optional, Set, Tuple, Union
import torch
import flair.embeddings
import flair.nn
from flair.data import Relation, Sentence
from flair.file_utils import cached_path
log = logging.getLogger("flair")
class RelationExtractor(flair.nn.DefaultCl... | 6,828 | 37.801136 | 120 | py |
flair | flair-master/flair/models/tars_model.py | import logging
import typing
from abc import ABC
from collections import OrderedDict
from pathlib import Path
from typing import Any, Dict, List, Optional, Set, Tuple, Union
import numpy as np
import torch
from sklearn.metrics.pairwise import cosine_similarity
from sklearn.preprocessing import minmax_scale
from tqdm i... | 40,613 | 40.956612 | 126 | py |
flair | flair-master/flair/models/lemmatizer_model.py | import logging
from math import inf
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
import flair.embeddings
import flair.nn
from flair.data import Dictionary, Sentence, Token
from flair.datasets import DataLoader, FlairDatapointDataset
from flair.training_utils import Result, store_e... | 34,759 | 48.026798 | 120 | py |
flair | flair-master/flair/models/__init__.py | from .clustering import ClusteringModel
from .entity_linker_model import EntityLinker
from .language_model import LanguageModel
from .lemmatizer_model import Lemmatizer
from .multitask_model import MultitaskModel
from .pairwise_classification_model import TextPairClassifier
from .pairwise_regression_model import TextPa... | 1,180 | 30.918919 | 69 | py |
flair | flair-master/flair/models/language_model.py | import math
from pathlib import Path
from typing import List, Optional, Tuple, Union
import torch
from torch import logsumexp, nn
from torch.optim import Optimizer
import flair
from flair.data import Dictionary
from flair.nn.recurrent import create_recurrent_layer
class LanguageModel(nn.Module):
"""Container mo... | 17,001 | 35.021186 | 117 | py |
flair | flair-master/flair/models/relation_classifier_model.py | import itertools
import logging
import typing
from abc import ABC, abstractmethod
from pathlib import Path
from typing import (
Any,
Dict,
Iterator,
List,
NamedTuple,
Optional,
Sequence,
Set,
Tuple,
Union,
cast,
)
import torch
from torch.utils.data.dataset import Dataset
im... | 34,165 | 45.995873 | 120 | py |
flair | flair-master/flair/models/sequence_tagger_utils/viterbi.py | from typing import Tuple
import numpy as np
import torch
import torch.nn
from torch.nn.functional import softmax
from torch.nn.utils.rnn import pack_padded_sequence
import flair
from flair.data import Dictionary, Label, List, Sentence
START_TAG: str = "<START>"
STOP_TAG: str = "<STOP>"
class ViterbiLoss(torch.nn.M... | 10,765 | 44.046025 | 119 | py |
flair | flair-master/flair/models/sequence_tagger_utils/crf.py | import torch
import flair
START_TAG: str = "<START>"
STOP_TAG: str = "<STOP>"
class CRF(torch.nn.Module):
"""Conditional Random Field.
Conditional Random Field Implementation according to sgrvinod (https://github.com/sgrvinod).
Classifier which predicts single tag / class / label for given word based o... | 2,171 | 41.588235 | 119 | py |
flair | flair-master/flair/models/sequence_tagger_utils/__init__.py | 0 | 0 | 0 | py | |
flair | flair-master/flair/embeddings/document.py | import logging
from typing import Any, Dict, List, Optional, Union, cast
import torch
from sklearn.feature_extraction.text import TfidfVectorizer
from torch.nn import RNNBase
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import flair
from flair.data import Sentence
from flair.embeddings.bas... | 30,169 | 38.080311 | 129 | py |
flair | flair-master/flair/embeddings/base.py | import inspect
import logging
from abc import abstractmethod
from typing import Any, Dict, Generic, List, Sequence, Type, Union
import torch
from torch.nn import Parameter, ParameterList
import flair
from flair.data import DT, Sentence
log = logging.getLogger("flair")
class Embeddings(torch.nn.Module, Generic[DT])... | 7,959 | 33.912281 | 131 | py |
flair | flair-master/flair/embeddings/legacy.py | import logging
import re
from abc import abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Tuple, Union
import torch
from deprecated import deprecated
from transformers import (
AlbertModel,
AlbertTokenizer,
BertModel,
BertTokenizer,
CamembertModel,
CamembertToken... | 63,878 | 39.099812 | 174 | py |
flair | flair-master/flair/embeddings/image.py | import logging
from typing import Any, Dict, List, Optional
import torch
import torch.nn.functional as F
from torch.nn import (
AdaptiveAvgPool2d,
AdaptiveMaxPool2d,
Conv2d,
Dropout2d,
Linear,
MaxPool2d,
Parameter,
ReLU,
Sequential,
TransformerEncoder,
TransformerEncoderLaye... | 10,902 | 37.663121 | 118 | py |
flair | flair-master/flair/embeddings/transformer.py | import inspect
import os
import random
import re
import tempfile
import warnings
import zipfile
from abc import abstractmethod
from io import BytesIO
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple, Type, Union, cast
import torch
from torch.jit import ScriptModule
from transformers import ... | 58,455 | 41.606414 | 146 | py |
flair | flair-master/flair/embeddings/token.py | import hashlib
import logging
import os
import re
import tempfile
from collections import Counter
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
import gensim
import numpy as np
import torch
from bpemb import BPEmb
from gensim.models import KeyedVectors
from gensim.models.fasttext import ... | 64,771 | 40.734536 | 131 | py |
flair | flair-master/flair/embeddings/__init__.py | # Expose base classses
from flair.embeddings.transformer import (
TransformerEmbeddings,
TransformerJitDocumentEmbeddings,
TransformerJitWordEmbeddings,
TransformerOnnxDocumentEmbeddings,
TransformerOnnxWordEmbeddings,
)
from .base import Embeddings, ScalarMix
# Expose document embedding classes
f... | 2,905 | 23.837607 | 44 | py |
flair | flair-master/flair/datasets/text_image.py | import json
import logging
import os
import urllib
from pathlib import Path
from typing import List
import numpy as np
import torch.utils.data.dataloader
from torch.utils.data import Dataset
from tqdm import tqdm
from flair.data import Corpus, DataPair, FlairDataset, Image, Sentence
from flair.file_utils import cache... | 3,092 | 35.821429 | 121 | py |
flair | flair-master/flair/datasets/base.py | import logging
from abc import abstractmethod
from pathlib import Path
from typing import Generic, List, Optional, Union
import torch.utils.data.dataloader
from deprecated import deprecated
from flair.data import DT, FlairDataset, Sentence, Tokenizer
from flair.tokenization import SegtokTokenizer, SpaceTokenizer
log... | 9,549 | 33.854015 | 128 | py |
flair | flair-master/flair/datasets/biomedical.py | import inspect
import json
import logging
import os
import re
import shutil
import sys
from abc import ABC, abstractmethod
from collections import defaultdict, deque
from copy import copy
from operator import attrgetter
from pathlib import Path
from tarfile import (
CompressionError,
ExtractError,
HeaderErr... | 234,560 | 38.608409 | 173 | py |
flair | flair-master/flair/datasets/text_text.py | import logging
import os
from pathlib import Path
from typing import List, Optional, Union
import flair
from flair.data import Corpus, DataPair, FlairDataset, Sentence, TextPair, _iter_dataset
from flair.datasets.base import find_train_dev_test_files
from flair.file_utils import cached_path, unpack_file, unzip_file
l... | 44,055 | 37.342907 | 169 | py |
flair | flair-master/flair/datasets/entity_linking.py | import csv
import logging
import os
from pathlib import Path
from typing import Dict, List, Optional, Union
import requests
import flair
from flair.data import Corpus, MultiCorpus, Sentence
from flair.datasets.sequence_labeling import ColumnCorpus, MultiFileColumnCorpus
from flair.file_utils import cached_path, unpac... | 79,934 | 44.110045 | 181 | py |
flair | flair-master/flair/datasets/treebanks.py | import logging
import re
from pathlib import Path
from typing import List, Optional, Union
import flair
from flair.data import Corpus, FlairDataset, Sentence, Token
from flair.datasets.base import find_train_dev_test_files
from flair.file_utils import cached_path
log = logging.getLogger("flair")
class UniversalDepe... | 65,227 | 39.742036 | 118 | py |
flair | flair-master/flair/datasets/ocr.py | import json
from pathlib import Path
from typing import Dict, Optional, Union
import gdown.download_folder
import PIL
from torch.utils.data import Dataset
import flair
from flair.data import BoundingBox, Corpus, FlairDataset, Sentence, get_spans_from_bio
from flair.datasets.base import find_train_dev_test_files
cla... | 10,117 | 40.130081 | 120 | py |
flair | flair-master/flair/datasets/relation_extraction.py | import bisect
import io
import json
import logging
import os
import re
from collections import defaultdict
from pathlib import Path
from typing import Any, Dict, Iterable, List, Optional, Set, Tuple, Union
import conllu
import gdown
from conllu.models import Metadata, Token
import flair
from flair.data import Sentenc... | 29,860 | 37.48067 | 120 | py |
flair | flair-master/flair/datasets/__init__.py | # Expose base classses
from .base import (
DataLoader,
FlairDatapointDataset,
MongoDataset,
SentenceDataset,
StringDataset,
)
# Expose all biomedical data sets used for the evaluation of BioBERT
# -
# -
# -
# -
# Expose all biomedical data sets using the HUNER splits
# Expose all biomedical data se... | 11,771 | 19.58042 | 68 | py |
flair | flair-master/flair/datasets/sequence_labeling.py | import copy
import json
import logging
import os
import re
import shutil
from collections import defaultdict
from pathlib import Path
from typing import (
Any,
DefaultDict,
Dict,
Iterable,
Iterator,
List,
Optional,
Tuple,
Union,
cast,
)
from torch.utils.data import ConcatDataset... | 197,364 | 40.160584 | 192 | py |
flair | flair-master/flair/datasets/document_classification.py | import csv
import json
import logging
import os
from pathlib import Path
from typing import Dict, List, Optional, Union
import flair
from flair.data import (
Corpus,
DataPair,
FlairDataset,
Sentence,
Tokenizer,
_iter_dataset,
)
from flair.datasets.base import find_train_dev_test_files
from flai... | 88,472 | 41.049905 | 134 | py |
flair | flair-master/flair/visual/training_curves.py | import csv
import logging
import math
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Union
import matplotlib.pyplot as plt
import numpy as np
# header for 'weights.txt'
WEIGHT_NAME = 1
WEIGHT_NUMBER = 2
WEIGHT_VALUE = 3
log = logging.getLogger("flair")
class Plotter:
... | 7,518 | 35.323671 | 107 | py |
flair | flair-master/flair/visual/tree_printer.py | from typing import List
from pptree import print_tree
from flair.data import Sentence, Token
class NodeToken:
def __init__(self, token: Token, tag_type: str) -> None:
self.token: Token = token
self.tag_type: str = tag_type
self.children: List[NodeToken] = []
def set_haed(self, paren... | 891 | 26.030303 | 86 | py |
flair | flair-master/flair/visual/activations.py | import numpy
class Highlighter:
def __init__(self) -> None:
self.color_map = [
"#ff0000",
"#ff4000",
"#ff8000",
"#ffbf00",
"#ffff00",
"#bfff00",
"#80ff00",
"#40ff00",
"#00ff00",
"#00ff40... | 1,910 | 25.178082 | 98 | py |
flair | flair-master/flair/visual/manifold.py | import numpy
import tqdm
from sklearn.manifold import TSNE
class _Transform:
def __init__(self) -> None:
pass
def fit(self, X):
return self.transform.fit_transform(X)
class tSNE(_Transform):
def __init__(self) -> None:
super().__init__()
self.transform = TSNE(n_componen... | 3,350 | 26.694215 | 93 | py |
flair | flair-master/flair/visual/__init__.py | from .activations import Highlighter
from .manifold import Visualizer
__all__ = ["Highlighter", "Visualizer"]
| 111 | 21.4 | 39 | py |
flair | flair-master/flair/visual/ner_html.py | import html
from typing import List, Union
from flair.data import Sentence
TAGGED_ENTITY = """
<mark class="entity" style="background: {color}; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 3; border-radius: 0.35em; box-decoration-break: clone; -webkit-box-decoration-break: clone">
{entity}
<span styl... | 3,042 | 32.811111 | 195 | py |
flair | flair-master/flair/trainers/language_model_trainer.py | import datetime
import logging
import math
import random
import time
from pathlib import Path
from typing import Iterable, Optional, Type, Union
import torch
from torch import cuda
from torch.optim import AdamW, Optimizer
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch.optim.sgd import SGD
from torch... | 17,266 | 35.660297 | 142 | py |
flair | flair-master/flair/trainers/__init__.py | from .language_model_trainer import LanguageModelTrainer, TextCorpus
from .trainer import ModelTrainer
__all__ = ["ModelTrainer", "LanguageModelTrainer", "TextCorpus"]
| 169 | 33 | 68 | py |
flair | flair-master/flair/trainers/trainer.py | import inspect
import logging
import os
import random
import time
import warnings
from inspect import signature
from pathlib import Path
from typing import List, Optional, Tuple, Type, Union
import torch
from torch.optim.sgd import SGD
from torch.utils.data.dataset import ConcatDataset
import flair
import flair.nn
fr... | 36,077 | 41.245902 | 124 | py |
flair | flair-master/flair/trainers/plugins/base.py | import logging
from collections import defaultdict
from inspect import isclass, signature
from itertools import count
from queue import Queue
from typing import (
Callable,
Dict,
Iterator,
List,
NewType,
Optional,
Sequence,
Set,
Type,
Union,
cast,
)
log = logging.getLogger("... | 8,348 | 29.694853 | 117 | py |
flair | flair-master/flair/trainers/plugins/__init__.py | from .base import BasePlugin, Pluggable, TrainerPlugin, TrainingInterrupt
from .functional.amp import AmpPlugin
from .functional.anneal_on_plateau import AnnealingPlugin
from .functional.checkpoints import CheckpointPlugin
from .functional.linear_scheduler import LinearSchedulerPlugin
from .functional.weight_extractor ... | 950 | 30.7 | 73 | py |
flair | flair-master/flair/trainers/plugins/metric_records.py | import time
from dataclasses import dataclass
from enum import Enum
from typing import Any, Iterable, Iterator, Optional, Tuple, Union
RecordType = Enum("RecordType", ["scalar", "image", "histogram", "string", "scalar_list"])
class MetricName:
def __init__(self, name) -> None:
self.parts: Tuple[str, ...]... | 4,204 | 30.856061 | 114 | py |
flair | flair-master/flair/trainers/plugins/loggers/tensorboard.py | import logging
import os
from flair.trainers.plugins.base import TrainerPlugin
from flair.training_utils import log_line
log = logging.getLogger("flair")
class TensorboardLogger(TrainerPlugin):
"""Plugin that takes care of tensorboard logging."""
def __init__(self, log_dir=None, comment="", tracked_metrics... | 2,065 | 33.433333 | 229 | py |
flair | flair-master/flair/trainers/plugins/loggers/log_file.py | import logging
from pathlib import Path
from flair.trainers.plugins.base import TrainerPlugin
from flair.training_utils import add_file_handler
log = logging.getLogger("flair")
class LogFilePlugin(TrainerPlugin):
"""Plugin for the training.log file."""
def __init__(self, base_path) -> None:
super()... | 599 | 26.272727 | 82 | py |
flair | flair-master/flair/trainers/plugins/loggers/loss_file.py | from datetime import datetime
from typing import Dict, Optional, Tuple, Union
from flair.trainers.plugins.base import TrainerPlugin
from flair.trainers.plugins.metric_records import MetricName
from flair.training_utils import init_output_file
class LossFilePlugin(TrainerPlugin):
"""Plugin that manages the loss.t... | 4,382 | 34.634146 | 116 | py |
flair | flair-master/flair/trainers/plugins/loggers/wandb.py | import logging
from flair.trainers.plugins.base import TrainerPlugin
log = logging.getLogger("flair")
class WandbLoggingHandler(logging.Handler):
def __init__(self, wandb, *args, **kwargs) -> None:
super().__init__(*args, **kwargs)
self.wandb = wandb
def emit(self, record):
try:
... | 2,315 | 30.726027 | 101 | py |
flair | flair-master/flair/trainers/plugins/loggers/metric_history.py | import logging
from typing import Dict, Mapping
from flair.trainers.plugins.base import TrainerPlugin
log = logging.getLogger("flair")
default_metrics_to_collect = {
("train", "loss"): "train_loss_history",
("dev", "score"): "dev_score_history",
("dev", "loss"): "dev_loss_history",
}
class MetricHisto... | 1,132 | 28.051282 | 89 | py |
flair | flair-master/flair/trainers/plugins/loggers/__init__.py | 0 | 0 | 0 | py | |
flair | flair-master/flair/trainers/plugins/functional/weight_extractor.py | from flair.trainers.plugins.base import TrainerPlugin
from flair.training_utils import WeightExtractor
class WeightExtractorPlugin(TrainerPlugin):
"""Simple Plugin for weight extraction."""
def __init__(self, base_path) -> None:
super().__init__()
self.weight_extractor = WeightExtractor(base_... | 851 | 30.555556 | 85 | py |
flair | flair-master/flair/trainers/plugins/functional/checkpoints.py | import logging
from flair.trainers.plugins.base import TrainerPlugin
log = logging.getLogger("flair")
class CheckpointPlugin(TrainerPlugin):
def __init__(
self,
save_model_each_k_epochs,
save_optimizer_state,
base_path,
) -> None:
super().__init__()
self.save_... | 1,073 | 29.685714 | 114 | py |
flair | flair-master/flair/trainers/plugins/functional/linear_scheduler.py | import logging
from flair.optim import LinearSchedulerWithWarmup
from flair.trainers.plugins.base import TrainerPlugin
log = logging.getLogger("flair")
class LinearSchedulerPlugin(TrainerPlugin):
"""Plugin for LinearSchedulerWithWarmup."""
def __init__(self, warmup_fraction: float, **kwargs) -> None:
... | 2,261 | 29.16 | 132 | py |
flair | flair-master/flair/trainers/plugins/functional/amp.py | from flair.trainers.plugins.base import TrainerPlugin
class AmpPlugin(TrainerPlugin):
"""Simple plugin for AMP."""
def __init__(self, opt_level) -> None:
super().__init__()
self.opt_level = opt_level
self.wrapped_backward = None
try:
from apex import amp
... | 1,537 | 25.982456 | 73 | py |
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