python_code stringlengths 0 187k | repo_name stringlengths 8 46 | file_path stringlengths 6 135 |
|---|---|---|
"""
This script handles the skimage exif problem.
"""
from PIL import Image
import numpy as np
ORIENTATIONS = { # used in apply_orientation
2: (Image.FLIP_LEFT_RIGHT,),
3: (Image.ROTATE_180,),
4: (Image.FLIP_TOP_BOTTOM,),
5: (Image.FLIP_LEFT_RIGHT, Image.ROTATE_90),
6: (Image.ROTATE_270,),
7... | colorization-master | caffe-colorization/examples/web_demo/exifutil.py |
import os
import time
import cPickle
import datetime
import logging
import flask
import werkzeug
import optparse
import tornado.wsgi
import tornado.httpserver
import numpy as np
import pandas as pd
from PIL import Image
import cStringIO as StringIO
import urllib
import exifutil
import caffe
REPO_DIRNAME = os.path.abs... | colorization-master | caffe-colorization/examples/web_demo/app.py |
#!/usr/bin/env python
"""
Form a subset of the Flickr Style data, download images to dirname, and write
Caffe ImagesDataLayer training file.
"""
import os
import urllib
import hashlib
import argparse
import numpy as np
import pandas as pd
from skimage import io
import multiprocessing
# Flickr returns a special image i... | colorization-master | caffe-colorization/examples/finetune_flickr_style/assemble_data.py |
#!/usr/bin/env python
"""
Takes as arguments:
1. the path to a JSON file (such as an IPython notebook).
2. the path to output file
If 'metadata' dict in the JSON file contains 'include_in_docs': true,
then copies the file to output file, appending the 'metadata' property
as YAML front-matter, adding the field 'categor... | colorization-master | caffe-colorization/scripts/copy_notebook.py |
#!/usr/bin/python2
#
# Copyright (c) 2009 Google Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of... | colorization-master | caffe-colorization/scripts/cpp_lint.py |
#!/usr/bin/env python
import os
import sys
import time
import yaml
import urllib
import hashlib
import argparse
required_keys = ['caffemodel', 'caffemodel_url', 'sha1']
def reporthook(count, block_size, total_size):
"""
From http://blog.moleculea.com/2012/10/04/urlretrieve-progres-indicator/
"""
glob... | colorization-master | caffe-colorization/scripts/download_model_binary.py |
"""
Generate data used in the HDF5DataLayer and GradientBasedSolver tests.
"""
import os
import numpy as np
import h5py
script_dir = os.path.dirname(os.path.abspath(__file__))
# Generate HDF5DataLayer sample_data.h5
num_cols = 8
num_rows = 10
height = 6
width = 5
total_size = num_cols * num_rows * height * width
da... | colorization-master | caffe-colorization/src/caffe/test/test_data/generate_sample_data.py |
import sys
import argparse
import caffe
from caffe import score, surgery # score, surgery function from caffe-fcn
import numpy as np
import os
import warnings
print sys.argv
def parse_args():
parser = argparse.ArgumentParser(description='')
# ***** FLAGS *****
parser.add_argument('--gpu', dest='gpu', he... | colorization-master | feature_learning_tests/segmentation/solve.py |
from __future__ import division
import caffe
import numpy as np
def transplant(new_net, net):
for p in net.params:
if p not in new_net.params:
print 'dropping', p
continue
for i in range(len(net.params[p])):
if net.params[p][i].data.shape != new_net.params[p][i].... | colorization-master | feature_learning_tests/segmentation/caffe/surgery.py |
from __future__ import division
import caffe
import numpy as np
import os
import sys
from datetime import datetime
from PIL import Image
def fast_hist(a, b, n):
k = (a >= 0) & (a < n)
return np.bincount(n * a[k].astype(int) + b[k], minlength=n**2).reshape(n, n)
def compute_hist(net, save_dir, dataset, layer='... | colorization-master | feature_learning_tests/segmentation/caffe/score.py |
import caffe
import os
import string
import numpy as np
import argparse
import matplotlib.pyplot as plt
def parse_args():
parser = argparse.ArgumentParser(description='Convert conv layers into FC layers')
parser.add_argument('--gpu', dest='gpu', help='gpu id', type=int, default=0)
parser.add_argument('--p... | colorization-master | resources/conv_into_fc.py |
# **************************************
# ***** Richard Zhang / 2016.08.06 *****
# **************************************
import numpy as np
import warnings
import os
import sklearn.neighbors as nn
import caffe
from skimage import color
# ************************
# ***** CAFFE LAYERS *****
# ************************
... | colorization-master | resources/caffe_traininglayers.py |
# **************************************
# ***** Richard Zhang / 2016.06.04 *****
# **************************************
# Absorb batch norm into convolution layers
# This script only supports the conv-batchnorm configuration
# Currently unsupported:
# - deconv layers
# - fc layers
# - batchnorm before linear la... | colorization-master | resources/batch_norm_absorb.py |
from __future__ import print_function, division
INPUT_LAYERS = ['Data', 'ImageData']
# Layers that only support elwise
ELWISE_LAYERS = ['Deconvolution']
# Layers that support parameters
PARAMETER_LAYERS = ['Convolution', 'InnerProduct']+ELWISE_LAYERS
# All supported layers
SUPPORTED_LAYERS = ['ReLU', 'Sigmoid', 'LRN',... | colorization-master | resources/magic_init/magic_init_mod.py |
from __future__ import print_function
from magic_init import *
class BCOLORS:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
class NOCOLORS:
HEADER = ''
OKBLUE = ''
OKGREEN = ''
WARNING = ''
FAIL... | colorization-master | resources/magic_init/measure_stat.py |
import caffe
def parseProtoString(s):
from google.protobuf import text_format
from caffe.proto import caffe_pb2 as pb
proto_net = pb.NetParameter()
text_format.Merge(s, proto_net)
return proto_net
def get_param(l, exclude=set(['top', 'bottom', 'name', 'type'])):
if not hasattr(l,'ListFields'):
if hasattr(l,'... | colorization-master | resources/magic_init/load.py |
import numpy as np
import os
import skimage.color as color
import matplotlib.pyplot as plt
import scipy.ndimage.interpolation as sni
import caffe
import argparse
def parse_args():
parser = argparse.ArgumentParser(description='iColor: deep interactive colorization')
parser.add_argument('-img_in',dest='img_in',h... | colorization-master | colorization/colorize.py |
#!/usr/bin/python
import os
import sys
import argparse
import numpy as np
from skimage import color, io
import scipy.ndimage.interpolation as sni
import caffe
def parse_args(argv):
parser = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.ArgumentDefault... | colorization-master | colorization/demo/batch_process.py |
import sys
import argparse
import caffe
from caffe import score, surgery # score, surgery function from caffe-fcn
import numpy as np
import os
import warnings
print sys.argv
def parse_args():
parser = argparse.ArgumentParser(description='')
# ***** FLAGS *****
parser.add_argument('--gpu', dest='gpu', he... | colorization-master | colorization/feature_learning_tests/segmentation/solve.py |
from __future__ import division
import caffe
import numpy as np
def transplant(new_net, net):
for p in net.params:
if p not in new_net.params:
print 'dropping', p
continue
for i in range(len(net.params[p])):
if net.params[p][i].data.shape != new_net.params[p][i].... | colorization-master | colorization/feature_learning_tests/segmentation/caffe/surgery.py |
from __future__ import division
import caffe
import numpy as np
import os
import sys
from datetime import datetime
from PIL import Image
def fast_hist(a, b, n):
k = (a >= 0) & (a < n)
return np.bincount(n * a[k].astype(int) + b[k], minlength=n**2).reshape(n, n)
def compute_hist(net, save_dir, dataset, layer='... | colorization-master | colorization/feature_learning_tests/segmentation/caffe/score.py |
import caffe
import os
import string
import numpy as np
import argparse
import matplotlib.pyplot as plt
def parse_args():
parser = argparse.ArgumentParser(description='Convert conv layers into FC layers')
parser.add_argument('--gpu', dest='gpu', help='gpu id', type=int, default=0)
parser.add_argument('--p... | colorization-master | colorization/resources/conv_into_fc.py |
# **************************************
# ***** Richard Zhang / 2016.08.06 *****
# **************************************
import numpy as np
import warnings
import os
import sklearn.neighbors as nn
import caffe
from skimage import color
# ************************
# ***** CAFFE LAYERS *****
# ************************
... | colorization-master | colorization/resources/caffe_traininglayers.py |
# **************************************
# ***** Richard Zhang / 2016.06.04 *****
# **************************************
# Absorb batch norm into convolution layers
# This script only supports the conv-batchnorm configuration
# Currently unsupported:
# - deconv layers
# - fc layers
# - batchnorm before linear la... | colorization-master | colorization/resources/batch_norm_absorb.py |
from __future__ import print_function, division
INPUT_LAYERS = ['Data', 'ImageData']
# Layers that only support elwise
ELWISE_LAYERS = ['Deconvolution']
# Layers that support parameters
PARAMETER_LAYERS = ['Convolution', 'InnerProduct']+ELWISE_LAYERS
# All supported layers
SUPPORTED_LAYERS = ['ReLU', 'Sigmoid', 'LRN',... | colorization-master | colorization/resources/magic_init/magic_init_mod.py |
from __future__ import print_function
from magic_init import *
class BCOLORS:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
class NOCOLORS:
HEADER = ''
OKBLUE = ''
OKGREEN = ''
WARNING = ''
FAIL... | colorization-master | colorization/resources/magic_init/measure_stat.py |
import caffe
def parseProtoString(s):
from google.protobuf import text_format
from caffe.proto import caffe_pb2 as pb
proto_net = pb.NetParameter()
text_format.Merge(s, proto_net)
return proto_net
def get_param(l, exclude=set(['top', 'bottom', 'name', 'type'])):
if not hasattr(l,'ListFields'):
if hasattr(l,'... | colorization-master | colorization/resources/magic_init/load.py |
from __future__ import print_function
import platform
import sys
import argparse
import qdarkstyle
from PyQt4.QtGui import QApplication, QIcon
from PyQt4.QtCore import Qt
from ui import gui_design
from data import colorize_image as CI
sys.path.append('./caffe_files')
def parse_args():
parser = argparse.ArgumentP... | colorization-master | interactive-deep-colorization/ideepcolor.py |
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import cv2
import numpy as np
class GUI_VIS(QWidget):
def __init__(self, win_size=256, scale=2.0):
QWidget.__init__(self)
self.result = None
self.win_width = win_size
self.win_height = win_size
self.scale = scale
... | colorization-master | interactive-deep-colorization/ui/gui_vis.py |
colorization-master | interactive-deep-colorization/ui/__init__.py | |
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import numpy as np
class GUIPalette(QWidget):
def __init__(self, grid_sz=(6, 3)):
QWidget.__init__(self)
self.color_width = 25
self.border = 6
self.win_width = grid_sz[0] * self.color_width + (grid_sz[0]+1) * self.border
... | colorization-master | interactive-deep-colorization/ui/gui_palette.py |
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from . import gui_draw
from . import gui_vis
from . import gui_gamut
from . import gui_palette
import time
class GUIDesign(QWidget):
def __init__(self, color_model, dist_model=None, img_file=None, load_size=256,
win_size=256, save_all=True):
... | colorization-master | interactive-deep-colorization/ui/gui_design.py |
import numpy as np
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import cv2
class UserEdit(object):
def __init__(self, mode, win_size, load_size, img_size):
self.mode = mode
self.win_size = win_size
self.img_size = img_size
self.load_size = load_size
print('image_siz... | colorization-master | interactive-deep-colorization/ui/ui_control.py |
from __future__ import print_function
import inspect, re
import numpy as np
import cv2
import os
import collections
try:
import pickle as pickle
except ImportError:
import pickle
def debug_trace():
from PyQt4.QtCore import pyqtRemoveInputHook
from pdb import set_trace
pyqtRemoveInputHook()
se... | colorization-master | interactive-deep-colorization/ui/utils.py |
import numpy as np
import time
import cv2
from PyQt4.QtCore import *
from PyQt4.QtGui import *
try:
from PyQt4.QtCore import QString
except ImportError:
QString = str
from .ui_control import UIControl
from data import lab_gamut
from skimage import color
import os
import datetime
import glob
import sys
import m... | colorization-master | interactive-deep-colorization/ui/gui_draw.py |
import cv2
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from data import lab_gamut
import numpy as np
class GUIGamut(QWidget):
def __init__(self, gamut_size=110):
QWidget.__init__(self)
self.gamut_size = gamut_size
self.win_size = gamut_size * 2 # divided by 4
self.setFixe... | colorization-master | interactive-deep-colorization/ui/gui_gamut.py |
import numpy as np
import itertools
import time
import datetime
def check_value(inds, val):
# Check to see if an array is a single element equaling a particular value
# Good for pre-processing inputs in a function
if(np.array(inds).size==1):
if(inds==val):
return True
return False
def flatten_nd_array(pts_... | colorization-master | interactive-deep-colorization/caffe_files/util.py |
colorization-master | interactive-deep-colorization/caffe_files/__init__.py | |
import numpy as np
import warnings
import os
import sklearn.neighbors as nn
import caffe
from skimage import color
import matplotlib.pyplot as plt
import color_quantization as cq
# ***************************************
# ***** LAYERS FOR GLOBAL HISTOGRAM *****
# ***************************************
class Spatial... | colorization-master | interactive-deep-colorization/caffe_files/caffe_traininglayers.py |
import numpy as np
from IPython.core.debugger import Pdb as pdb
import sklearn.neighbors as nn
import util
import caffe
class NNEncode():
# Encode points as a linear combination of unordered points
# using NN search and RBF kernel
def __init__(self,NN,sigma,km_filepath='./data/color_bins/pts_in_hull.npy',cc=-1):
... | colorization-master | interactive-deep-colorization/caffe_files/color_quantization.py |
import numpy as np
import scipy as sp
import cv2
import matplotlib.pyplot as plt
from skimage import color
import caffe
from sklearn.cluster import KMeans
from skimage.io import imread
from skimage.io import imsave
from skimage import color
import os
import sys
import ntpath
import datetime
from scipy.ndimage.interpola... | colorization-master | interactive-deep-colorization/data/colorize_image.py |
colorization-master | interactive-deep-colorization/data/__init__.py | |
import numpy as np
import scipy as sp
from skimage import color
from pdb import set_trace as st
import warnings
def qcolor2lab_1d(qc):
# take 1d numpy array and do color conversion
c = np.array([qc.red(), qc.green(), qc.blue()], np.uint8)
return rgb2lab_1d(c)
def rgb2lab_1d(in_rgb):
# take 1d numpy... | colorization-master | interactive-deep-colorization/data/lab_gamut.py |
from setuptools import setup, find_packages
import sys
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 ... | allennlp-reading-comprehension-master | setup.py |
_MAJOR = "0"
_MINOR = "0"
_REVISION = "1-unreleased"
VERSION_SHORT = "{0}.{1}".format(_MAJOR, _MINOR)
VERSION = "{0}.{1}.{2}".format(_MAJOR, _MINOR, _REVISION)
| allennlp-reading-comprehension-master | allennlp_rc/version.py |
import allennlp_rc.dataset_readers
import allennlp_rc.models
import allennlp_rc.predictors
| allennlp-reading-comprehension-master | allennlp_rc/__init__.py |
import json
import logging
from typing import Dict, List
from overrides import overrides
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.instance import Instance
from allennlp.data.fields import Field, TextField, ListField, M... | allennlp-reading-comprehension-master | allennlp_rc/dataset_readers/qangaroo.py |
"""
Utilities for reading comprehension dataset readers.
"""
from collections import Counter, defaultdict
import logging
import string
from typing import Any, Dict, List, Tuple, Optional
from allennlp.data.fields import (
Field,
TextField,
IndexField,
MetadataField,
LabelField,
ListField,
... | allennlp-reading-comprehension-master | allennlp_rc/dataset_readers/util.py |
import json
import logging
from typing import Any, Dict, List, Tuple, Optional, Iterable
from allennlp.common.util import sanitize_wordpiece
from allennlp.data.fields import MetadataField, TextField, SpanField
from overrides import overrides
from allennlp.common.file_utils import cached_path, open_compressed
from all... | allennlp-reading-comprehension-master | allennlp_rc/dataset_readers/transformer_squad.py |
from allennlp_rc.dataset_readers.drop import DropReader
from allennlp_rc.dataset_readers.qangaroo import QangarooReader
from allennlp_rc.dataset_readers.quac import QuACReader
from allennlp_rc.dataset_readers.squad import SquadReader
from allennlp_rc.dataset_readers.triviaqa import TriviaQaReader
from allennlp_rc.datas... | allennlp-reading-comprehension-master | allennlp_rc/dataset_readers/__init__.py |
import json
import logging
from typing import Any, Dict, List, Tuple, Optional
from overrides import overrides
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.instance import Instance
from allennlp.data.token_indexers import ... | allennlp-reading-comprehension-master | allennlp_rc/dataset_readers/squad.py |
import json
import logging
from typing import Any, Dict, List, Tuple
from overrides import overrides
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.instance import Instance
from allennlp.data.token_indexers import SingleIdTo... | allennlp-reading-comprehension-master | allennlp_rc/dataset_readers/quac.py |
import itertools
import json
import logging
import string
from collections import defaultdict
from typing import Dict, List, Union, Tuple, Any
from overrides import overrides
from word2number.w2n import word_to_num
from allennlp.common.file_utils import cached_path
from allennlp.data.fields import (
Field,
Te... | allennlp-reading-comprehension-master | allennlp_rc/dataset_readers/drop.py |
import json
import logging
import os
import tarfile
from typing import Dict, List, Tuple
from overrides import overrides
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.instance import Instance
from allennlp.data.token_indexe... | allennlp-reading-comprehension-master | allennlp_rc/dataset_readers/triviaqa.py |
import json
from overrides import overrides
from allennlp.common.util import JsonDict
from allennlp.data import DatasetReader, Instance
from allennlp.data.tokenizers.spacy_tokenizer import SpacyTokenizer
from allennlp.predictors.predictor import Predictor
from allennlp.models import Model
@Predictor.register("dialog... | allennlp-reading-comprehension-master | allennlp_rc/predictors/dialog_qa.py |
from allennlp_rc.predictors.reading_comprehension import ReadingComprehensionPredictor
from allennlp_rc.predictors.dialog_qa import DialogQAPredictor
from allennlp_rc.predictors.transformer_qa import TransformerQAPredictor
| allennlp-reading-comprehension-master | allennlp_rc/predictors/__init__.py |
from copy import deepcopy
from typing import Dict, List
from overrides import overrides
import numpy
from allennlp.common.util import JsonDict
from allennlp.data import Instance
from allennlp.predictors.predictor import Predictor
from allennlp.data.fields import (
IndexField,
ListField,
LabelField,
Sp... | allennlp-reading-comprehension-master | allennlp_rc/predictors/reading_comprehension.py |
from typing import List, Dict, Any
from allennlp.models import Model
from overrides import overrides
from allennlp.common.util import JsonDict, sanitize
from allennlp.data import Instance, DatasetReader
from allennlp.predictors.predictor import Predictor
@Predictor.register("transformer_qa")
class TransformerQAPred... | allennlp-reading-comprehension-master | allennlp_rc/predictors/transformer_qa.py |
import logging
from typing import Any, Dict, List, Optional
import numpy as np
from overrides import overrides
import torch
import torch.nn.functional as F
from torch.nn.functional import nll_loss
from allennlp.common.checks import check_dimensions_match
from allennlp.data import Vocabulary
from allennlp.models.model ... | allennlp-reading-comprehension-master | allennlp_rc/models/dialog_qa.py |
import torch
def get_best_span(span_start_logits: torch.Tensor, span_end_logits: torch.Tensor) -> torch.Tensor:
"""
This acts the same as the static method ``BidirectionalAttentionFlow.get_best_span()``
in ``allennlp/models/reading_comprehension/bidaf.py``. We keep it here so that users can
directly i... | allennlp-reading-comprehension-master | allennlp_rc/models/util.py |
from typing import Any, Dict, List, Optional
import torch
from torch.nn.functional import nll_loss
from allennlp.data import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import Highway
from allennlp.modules import Seq2SeqEncoder, TextFieldEmbedder
from allennlp.modules.matrix_attention.mat... | allennlp-reading-comprehension-master | allennlp_rc/models/qanet.py |
from allennlp_rc.models.bidaf import BidirectionalAttentionFlow
from allennlp_rc.models.bidaf_ensemble import BidafEnsemble
from allennlp_rc.models.dialog_qa import DialogQA
from allennlp_rc.models.naqanet import NumericallyAugmentedQaNet
from allennlp_rc.models.qanet import QaNet
from allennlp_rc.models.transformer_qa... | allennlp-reading-comprehension-master | allennlp_rc/models/__init__.py |
import logging
from typing import Any, Dict, List, Optional
import torch
from torch.nn.functional import nll_loss
from allennlp.common.checks import check_dimensions_match
from allennlp.data import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import Highway
from allennlp.modules import Seq... | allennlp-reading-comprehension-master | allennlp_rc/models/bidaf.py |
from typing import Dict, List, Any
from overrides import overrides
import torch
from allennlp.common.checks import ConfigurationError
from allennlp.models.ensemble import Ensemble
from allennlp.models.archival import load_archive
from allennlp.models.model import Model
from allennlp.common import Params
from allennlp... | allennlp-reading-comprehension-master | allennlp_rc/models/bidaf_ensemble.py |
from typing import Any, Dict, List, Optional
import logging
import torch
from allennlp.data import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import Highway
from allennlp.nn.activations import Activation
from allennlp.modules.feedforward import FeedForward
from allennlp.modules import Se... | allennlp-reading-comprehension-master | allennlp_rc/models/naqanet.py |
import logging
from typing import Any, Dict, List, Optional
import numpy as np
import torch
from allennlp.common.util import sanitize_wordpiece
from allennlp.modules.text_field_embedders import BasicTextFieldEmbedder
from allennlp.modules.token_embedders import PretrainedTransformerEmbedder
from allennlp.nn.util impor... | allennlp-reading-comprehension-master | allennlp_rc/models/transformer_qa.py |
""" Evaluation script for NarrativeQA dataset. """
import nltk
try:
nltk.data.find("tokenizers/punkt")
except LookupError:
nltk.download("punkt")
nltk.download("wordnet")
import rouge
from nltk.translate.bleu_score import sentence_bleu
from nltk.tokenize import word_tokenize
from nltk.translate.meteor_sc... | allennlp-reading-comprehension-master | allennlp_rc/eval/narrativeqa_eval.py |
""" Official evaluation script for v1.1 of the SQuAD dataset. """
from __future__ import print_function
from collections import Counter
import string
import re
import argparse
import json
import sys
def normalize_answer(s):
"""Lower text and remove punctuation, articles and extra whitespace."""
def remove_ar... | allennlp-reading-comprehension-master | allennlp_rc/eval/squad_eval.py |
from allennlp_rc.eval.drop_em_and_f1 import DropEmAndF1
from allennlp_rc.eval.squad_em_and_f1 import SquadEmAndF1
| allennlp-reading-comprehension-master | allennlp_rc/eval/__init__.py |
"""Official evaluation script for ORB.
Usage:
python evaluation_script.py
--dataset_file <file_path>
--prediction_file <file_path>
--metrics_output_file <file_path>
"""
# pylint: disable=unused-import
from __future__ import absolute_import
from __future__ import division
from __future__ impor... | allennlp-reading-comprehension-master | allennlp_rc/eval/orb_eval.py |
from typing import List, Tuple
from allennlp_rc.eval.squad_eval import exact_match_score, f1_score
from allennlp_rc.eval.drop_eval import get_metrics as drop_metrics
from allennlp_rc.eval.narrativeqa_eval import get_metric_score as get_metric_narrativeqa
from allennlp_rc.eval.squad2_eval import get_metric_score as get_... | allennlp-reading-comprehension-master | allennlp_rc/eval/orb_utils.py |
"""
This evaluation script relies heavily on the one for DROP (``allennlp/tools/drop_eval.py``). We need a separate
script for Quoref only because the data formats are slightly different.
"""
import json
from typing import Dict, Tuple, List, Any, Optional
import argparse
import numpy as np
from allennlp_rc.eval impor... | allennlp-reading-comprehension-master | allennlp_rc/eval/quoref_eval.py |
"""Official evaluation script for SQuAD version 2.0.
"""
import collections
import re
import string
def make_qid_to_has_ans(dataset):
qid_to_has_ans = {}
for article in dataset:
for p in article["paragraphs"]:
for qa in p["qas"]:
qid_to_has_ans[qa["id"]] = bool(qa["answers... | allennlp-reading-comprehension-master | allennlp_rc/eval/squad2_eval.py |
from typing import Tuple
from allennlp.training.metrics.metric import Metric
from overrides import overrides
from allennlp_rc.eval import squad_eval
@Metric.register("squad")
class SquadEmAndF1(Metric):
"""
This :class:`Metric` takes the best span string computed by a model, along with the answer
string... | allennlp-reading-comprehension-master | allennlp_rc/eval/squad_em_and_f1.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 numpy as np
from scipy.optimize import linear_sum_assignment
# From here through _normalize_answer was originally copied from:
# https://wo... | allennlp-reading-comprehension-master | allennlp_rc/eval/drop_eval.py |
from typing import Tuple, List, Union
from allennlp.training.metrics.metric import Metric
from overrides import overrides
from allennlp_rc.eval.drop_eval import get_metrics as drop_em_and_f1, answer_json_to_strings
from allennlp_rc.eval.squad_eval import metric_max_over_ground_truths
@Metric.register("drop")
class ... | allennlp-reading-comprehension-master | allennlp_rc/eval/drop_em_and_f1.py |
import pathlib
PROJECT_ROOT = (pathlib.Path(__file__).parent / "..").resolve() # pylint: disable=no-member
TESTS_ROOT = PROJECT_ROOT / "tests"
FIXTURES_ROOT = PROJECT_ROOT / "test_fixtures"
| allennlp-reading-comprehension-master | tests/__init__.py |
from allennlp_rc import version
class TestVersion:
def test_version_exists(self):
assert version.VERSION.startswith(version.VERSION_SHORT)
| allennlp-reading-comprehension-master | tests/version_test.py |
import pytest
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp_rc.dataset_readers import TriviaQaReader
from tests import FIXTURES_ROOT
class TestTriviaQaReader:
@pytest.mark.parametrize("lazy", (True, False))
def test_read(self, lazy):
params = Params(
... | allennlp-reading-comprehension-master | tests/dataset_readers/triviaqa_test.py |
import pytest
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp_rc.dataset_readers import TransformerSquadReader
from tests import FIXTURES_ROOT
class TestTransformerSquadReader:
def test_read_from_file(self):
reader = TransformerSquadReader()
instance... | allennlp-reading-comprehension-master | tests/dataset_readers/transformer_squad_test.py |
allennlp-reading-comprehension-master | tests/dataset_readers/__init__.py | |
import pytest
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp_rc.dataset_readers import DropReader
from tests import FIXTURES_ROOT
class TestDropReader:
@pytest.mark.parametrize("lazy", (True, False))
def test_read_from_file(self, lazy):
reader = DropRea... | allennlp-reading-comprehension-master | tests/dataset_readers/drop_test.py |
import pytest
from allennlp.common.testing import AllenNlpTestCase
from allennlp.data.tokenizers import SpacyTokenizer
from allennlp_rc.dataset_readers import util
class TestReadingComprehensionUtil(AllenNlpTestCase):
def test_char_span_to_token_span_handles_easy_cases(self):
# These are _inclusive_ span... | allennlp-reading-comprehension-master | tests/dataset_readers/util_test.py |
import pytest
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp_rc.dataset_readers import QuACReader
from tests import FIXTURES_ROOT
class TestQuACReader:
@pytest.mark.parametrize("lazy", (True, False))
def test_read(self, lazy):
params = Params({"lazy": l... | allennlp-reading-comprehension-master | tests/dataset_readers/quac_test.py |
import pytest
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp_rc.dataset_readers import QangarooReader
from tests import FIXTURES_ROOT
class TestQangarooReader:
@pytest.mark.parametrize("lazy", (True, False))
def test_read_from_file(self, lazy):
reader =... | allennlp-reading-comprehension-master | tests/dataset_readers/qangaroo_test.py |
import pytest
from allennlp.common import Params
from allennlp.common.util import ensure_list
from allennlp_rc.dataset_readers import SquadReader
from tests import FIXTURES_ROOT
class TestSquadReader:
@pytest.mark.parametrize("lazy", (True, False))
def test_read_from_file(self, lazy):
reader = Squad... | allennlp-reading-comprehension-master | tests/dataset_readers/squad_test.py |
allennlp-reading-comprehension-master | tests/predictors/__init__.py | |
from allennlp.common.testing import AllenNlpTestCase
from allennlp.data import Vocabulary
from allennlp_rc.dataset_readers import TransformerSquadReader
from allennlp_rc.models import TransformerQA
from allennlp_rc.predictors import TransformerQAPredictor
class TestTransformerQAPredictor(AllenNlpTestCase):
def s... | allennlp-reading-comprehension-master | tests/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-reading-comprehension-master | tests/predictors/dialog_qa_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_rc import predictors
from tests import FIXTURES_ROOT
class TestBidafPredictor(AllenNlpTestCase):
def test_uses_named_inputs(sel... | allennlp-reading-comprehension-master | tests/predictors/reading_comprehension_test.py |
from flaky import flaky
import pytest
import numpy
from numpy.testing import assert_almost_equal
import torch
from allennlp.common import Params
from allennlp.common.checks import ConfigurationError
from allennlp.common.testing import ModelTestCase
from allennlp.data import DatasetReader, Vocabulary
from allennlp.data... | allennlp-reading-comprehension-master | tests/models/bidaf_test.py |
import numpy
import torch
from flaky import flaky
from allennlp.common.testing import ModelTestCase
from allennlp.data.dataset import Batch
from allennlp_rc.models.bidaf_ensemble import BidafEnsemble, ensemble
from tests import FIXTURES_ROOT
class BidafEnsembleTest(ModelTestCase):
def setUp(self):
super... | allennlp-reading-comprehension-master | tests/models/bidaf_ensemble_test.py |
from flaky import flaky
from allennlp.common.testing import ModelTestCase
from tests import FIXTURES_ROOT
import allennlp_rc
class NumericallyAugmentedQaNetTest(ModelTestCase):
def setUp(self):
super().setUp()
self.set_up_model(
FIXTURES_ROOT / "naqanet" / "experiment.json", FIXTURE... | allennlp-reading-comprehension-master | tests/models/naqanet_test.py |
import torch
import pytest
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.dataset import Batch
from allennlp.data import DataLo... | allennlp-reading-comprehension-master | tests/models/qanet_test.py |
allennlp-reading-comprehension-master | tests/models/__init__.py | |
from flaky import flaky
import numpy
from numpy.testing import assert_almost_equal
from allennlp.common.testing import ModelTestCase
from allennlp.data.dataset import Batch
from tests import FIXTURES_ROOT
import allennlp_rc # noqa F401: Needed to register the registrables.
class TransformerQaTest(ModelTestCase):
... | allennlp-reading-comprehension-master | tests/models/transformer_qa_test.py |
from numpy.testing import assert_almost_equal
import torch
from allennlp.common.testing import AllenNlpTestCase
from allennlp_rc.models.util import get_best_span
from tests import FIXTURES_ROOT
class TestRcUtil(AllenNlpTestCase):
def test_get_best_span(self):
span_begin_probs = torch.FloatTensor([[0.1, 0... | allennlp-reading-comprehension-master | tests/models/util_test.py |
from allennlp.common.testing import ModelTestCase
from allennlp.data.dataset import Batch
from tests import FIXTURES_ROOT
import allennlp_rc
class DialogQATest(ModelTestCase):
def setUp(self):
super().setUp()
self.set_up_model(
FIXTURES_ROOT / "dialog_qa" / "experiment.json",
... | allennlp-reading-comprehension-master | tests/models/dialog_qa_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_rc
from tests import FIXTURES_ROOT
class TestHotflip:
def test_using_squad_model(self):
... | allennlp-reading-comprehension-master | tests/interpret/hotflip_test.py |
allennlp-reading-comprehension-master | tests/interpret/__init__.py |
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