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evaluate
evaluate-main/metrics/bertscore/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("bertscore") launch_gradio_widget(module)
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evaluate
evaluate-main/metrics/bertscore/bertscore.py
# Copyright 2020 The HuggingFace Evaluate Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ...
7,950
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evaluate
evaluate-main/metrics/exact_match/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("exact_match") launch_gradio_widget(module)
133
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evaluate
evaluate-main/metrics/exact_match/exact_match.py
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
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evaluate
evaluate-main/metrics/rl_reliability/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("rl_reliability", "online") launch_gradio_widget(module)
146
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py
evaluate
evaluate-main/metrics/rl_reliability/rl_reliability.py
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
7,052
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evaluate
evaluate-main/metrics/comet/app.py
import sys import evaluate from evaluate.utils import launch_gradio_widget sys.path = [p for p in sys.path if p != "/home/user/app"] module = evaluate.load("comet") sys.path = ["/home/user/app"] + sys.path launch_gradio_widget(module)
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evaluate
evaluate-main/metrics/comet/comet.py
# Copyright 2020 The HuggingFace Evaluate Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ...
6,967
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evaluate
evaluate-main/metrics/matthews_correlation/matthews_correlation.py
# Copyright 2021 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
6,601
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evaluate
evaluate-main/metrics/matthews_correlation/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("matthews_correlation") launch_gradio_widget(module)
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evaluate
evaluate-main/metrics/wiki_split/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("wiki_split") launch_gradio_widget(module)
132
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evaluate
evaluate-main/metrics/wiki_split/wiki_split.py
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
14,638
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evaluate
evaluate-main/metrics/squad/squad.py
# Copyright 2020 The HuggingFace Evaluate Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ...
4,525
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evaluate
evaluate-main/metrics/squad/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("squad") launch_gradio_widget(module)
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evaluate
evaluate-main/metrics/squad/compute_score.py
""" Official evaluation script for v1.1 of the SQuAD dataset. """ import argparse import json import re import string import sys from collections import Counter def normalize_answer(s): """Lower text and remove punctuation, articles and extra whitespace.""" def remove_articles(text): return re.sub(r...
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evaluate
evaluate-main/tests/test_evaluation_suite.py
from unittest import TestCase from evaluate import EvaluationSuite from tests.test_evaluator import DummyTextClassificationPipeline class TestEvaluationSuite(TestCase): def setUp(self): # Check that the EvaluationSuite loads successfully self.evaluation_suite = EvaluationSuite.load("evaluate/eval...
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evaluate
evaluate-main/tests/test_hub.py
import glob from unittest import TestCase from unittest.mock import patch import pytest import requests import yaml from evaluate.hub import push_to_hub from tests.test_metric import DummyMetric minimum_metadata = { "model-index": [ { "results": [ { "task"...
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evaluate
evaluate-main/tests/conftest.py
import csv import json import lzma import os import tarfile import textwrap import datasets import pyarrow as pa import pyarrow.parquet as pq import pytest from datasets import config from datasets.arrow_dataset import Dataset from datasets.features import ClassLabel, Features, Sequence, Value @pytest.fixture(autous...
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evaluate
evaluate-main/tests/test_evaluator.py
# Copyright 2022 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # U...
41,784
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evaluate
evaluate-main/tests/test_load.py
import importlib import os import tempfile from unittest import TestCase import pytest from datasets import DownloadConfig import evaluate from evaluate.loading import ( CachedEvaluationModuleFactory, HubEvaluationModuleFactory, LocalEvaluationModuleFactory, evaluation_module_factory, ) from .utils i...
5,516
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evaluate
evaluate-main/tests/utils.py
import os import tempfile import unittest from contextlib import contextmanager from copy import deepcopy from distutils.util import strtobool from enum import Enum from pathlib import Path from unittest.mock import patch from evaluate import config def parse_flag_from_env(key, default=False): try: value...
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evaluate
evaluate-main/tests/test_metric_common.py
# Copyright 2020 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
8,676
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evaluate
evaluate-main/tests/test_file_utils.py
import os from pathlib import Path from unittest.mock import patch import pytest from evaluate.utils.file_utils import OfflineModeIsEnabled, cached_path, ftp_get, ftp_head, http_get, http_head FILE_CONTENT = """\ Text data. Second line of data.""" def test_cached_path_local(text_file): # absolute path...
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evaluate
evaluate-main/tests/__init__.py
0
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evaluate
evaluate-main/tests/test_trainer_evaluator_parity.py
import json import os import shutil import subprocess import tempfile import unittest import numpy as np import torch import transformers from datasets import load_dataset from transformers import AutoFeatureExtractor, AutoModelForImageClassification, Trainer, TrainingArguments, pipeline from evaluate import evaluato...
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evaluate
evaluate-main/tests/test_metric.py
import os import pickle import tempfile import time from multiprocessing import Pool from unittest import TestCase, mock import pytest from datasets.features import Features, Sequence, Value from evaluate.module import EvaluationModule, EvaluationModuleInfo, combine from .utils import require_tf, require_torch cla...
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evaluate
evaluate-main/tests/test_viz.py
from unittest import TestCase import matplotlib.pyplot as plt from evaluate.visualization import radar_plot class TestViz(TestCase): def test_invert_range(self): data = [{"accuracy": 0.9, "precision": 0.8}, {"accuracy": 0.7, "precision": 0.6}] model_names = ["model1", "model2"] wrong_inv...
909
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evaluate
evaluate-main/tests/test_save.py
import json import shutil import tempfile from pathlib import Path from unittest import TestCase import evaluate result_dict = {"metric": 1.0, "model_name": "x"} SAVE_EXTRA_KEYS = ["_timestamp", "_git_commit_hash", "_evaluate_version", "_python_version", "_interpreter_path"] class TestSave(TestCase): def setU...
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evaluate
evaluate-main/measurements/honest/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("honest", "en") launch_gradio_widget(module)
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evaluate
evaluate-main/measurements/honest/honest.py
# Source: https://github.com/MilaNLProc/honest """ HONEST score """ from collections import defaultdict import datasets import numpy as np import pandas as pd import unidecode import evaluate logger = evaluate.logging.get_logger(__name__) _CITATION = """ @inproceedings{nozza-etal-2021-honest, title = {"{HON...
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evaluate
evaluate-main/measurements/word_length/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("word_length", module_type="measurement") launch_gradio_widget(module)
160
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evaluate
evaluate-main/measurements/word_length/word_length.py
# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
2,865
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evaluate
evaluate-main/measurements/label_distribution/label_distribution.py
# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
3,876
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evaluate
evaluate-main/measurements/label_distribution/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("label_distribution", module_type="measurement") launch_gradio_widget(module)
167
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evaluate
evaluate-main/measurements/word_count/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("word_count") launch_gradio_widget(module)
132
18
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evaluate
evaluate-main/measurements/word_count/word_count.py
# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
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evaluate
evaluate-main/measurements/perplexity/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("perplexity", module_type="measurement") launch_gradio_widget(module)
159
21.857143
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py
evaluate
evaluate-main/measurements/perplexity/perplexity.py
# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
8,604
43.35567
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py
evaluate
evaluate-main/measurements/text_duplicates/text_duplicates.py
# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
3,347
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evaluate
evaluate-main/measurements/text_duplicates/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("text_duplicates") launch_gradio_widget(module)
137
18.714286
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py
evaluate
evaluate-main/measurements/toxicity/toxicity.py
# Copyright 2020 The HuggingFace Evaluate Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ...
6,077
41.802817
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py
evaluate
evaluate-main/measurements/toxicity/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("toxicity") launch_gradio_widget(module)
130
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py
evaluate
evaluate-main/measurements/regard/app.py
import evaluate from evaluate.utils import launch_gradio_widget module = evaluate.load("regard") launch_gradio_widget(module)
128
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py
evaluate
evaluate-main/measurements/regard/regard.py
# Copyright 2020 The HuggingFace Evaluate Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ...
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airloc
airloc-master/plot_results.py
#!/bin/env python3 import os import time import sys import math import glob from dateutil.parser import parse import numpy as np from config import CONFIG import json import argparse from utils.utils import find_latest_log MA_SMOOTH = 0.02 START_ITER_PLOT = 50 # Metrics with shared y_axis metricsWithSharedY = dic...
11,151
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airloc
airloc-master/config.py
""" Central configration file for the project. Acts as a storage of global variables and various configuration settings. """ import os import pprint from easydict import EasyDict as edict from datetime import datetime CONFIG = edict() """ Evaluation of RL-agent """ # These settings control the evaluation runs of th...
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airloc
airloc-master/__init__.py
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airloc
airloc-master/networks/rl_agent.py
import torch import torch.nn as nn import torch.nn.init as init import math import random import sys import os import torch.nn.functional as F from config import CONFIG from networks.resnets import ResNet18 from torchvision.models.feature_extraction import get_graph_node_names from torchvision.models.feature_extraction...
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airloc
airloc-master/networks/agent.py
import torch import importlib.util import torch.nn as nn import torch.nn.init as init import math import random import sys import os import torch.nn.functional as F from config import CONFIG from networks.resnets import ResNet18 from torchvision.models.feature_extraction import get_graph_node_names from torchvision.mod...
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airloc
airloc-master/networks/RandomAgent.py
import torch import importlib.util import torch.nn as nn import torch.nn.init as init import math import random import sys import os import torch.nn.functional as F from config import CONFIG from networks.resnets import ResNet18 from torchvision.models.feature_extraction import get_graph_node_names from torchvision.mod...
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airloc
airloc-master/networks/rnn_agents.py
import torch import torch.nn as nn import torchvision.transforms as transforms import torch.nn.functional as F import os import importlib.util import time import json import math from utils.utils import calculate_cnn_output_size, cosine_sim_heatmap from utils.agent_utils import visualize_cnn_filter, get_outside import...
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airloc
airloc-master/networks/__init__.py
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airloc-master/networks/deterministic_agent.py
import torch import importlib.util import torch.nn as nn import torch.nn.init as init import math import random import sys import os import torch.nn.functional as F from config import CONFIG from networks.resnets import ResNet18 from torchvision.models.feature_extraction import get_graph_node_names from torchvision.m...
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airloc
airloc-master/networks/resnets.py
import torch import torch.nn as nn import math import random import sys import os import torch.nn.functional as F import torchvision.models as models from torch.autograd import Variable # During dev #sys.path.append(os.path.abspath('..')) #execfile(os.path.join(__file__, '../config.py')) from config import CONFI...
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airloc
airloc-master/training/train_agent.py
import traceback import pdb from datetime import datetime import random import signal import time import numpy as np import json import os import sys # matplotlib is used for debugging image inputs to networks import matplotlib import matplotlib.pyplot as plt from copy import deepcopy import torch import torch.nn as nn...
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airloc
airloc-master/training/__init__.py
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airloc
airloc-master/training/run_deterministic.py
from datetime import datetime import random import time import numpy as np import json from shutil import copyfile import os import sys # matplotlib is used for debugging image inputs to networks import matplotlib import matplotlib.pyplot as plt #matplotlib.use('TkAgg') from copy import deepcopy import torch from to...
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airloc
airloc-master/eval/eval_agent.py
from datetime import datetime import random import time import numpy as np import json import os import sys import importlib # matplotlib is used for debugging image inputs to networks import matplotlib import matplotlib.pyplot as plt #matplotlib.use('TkAgg') import torch import torchvision.transforms as transforms imp...
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airloc
airloc-master/eval/__init__.py
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0
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airloc
airloc-master/logs/2022-06-23_08-29-00-213310_residual_nosemseg_seed0/config.py
""" Central configration file for the project. Acts as a storage of global variables and various configuration settings. TODO TODO TODO: Remove unnecessary fields below; this is copied from an earlier project """ import os import pprint from easydict import EasyDict as edict from datetime import datetime import socke...
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airloc
airloc-master/logs/2022-09-13_14-07-42-505667_pre_disaster/config.py
""" Central configration file for the project. Acts as a storage of global variables and various configuration settings. TODO TODO TODO: Remove unnecessary fields below; this is copied from an earlier project """ import os import pprint from easydict import EasyDict as edict from datetime import datetime CONFIG = e...
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airloc
airloc-master/logs/2022-06-23_08-30-12-761837_residual_semseg/config.py
""" Central configration file for the project. Acts as a storage of global variables and various configuration settings. TODO TODO TODO: Remove unnecessary fields below; this is copied from an earlier project """ import os import pprint from easydict import EasyDict as edict from datetime import datetime import socke...
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airloc
airloc-master/doerchnet/plot_results.py
#!/bin/env python3 import os import time import sys import math from dateutil.parser import parse import numpy as np from config import CONFIG import json import argparse from utils.utils import find_latest_log MA_SMOOTH = 0.01 START_ITER_PLOT = 30 # For some, inxplicable reason, need to run this here?? # What a...
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airloc
airloc-master/doerchnet/share_net.py
import torch import torch.nn as nn from config import CONFIG class ShareNet(nn.Module): def __init__(self , num_out_classes = 8): super(ShareNet, self).__init__() # Check wether to include segmentation channel if CONFIG.RL_priv_use_seg or CONFIG.RL_predict_seg_mask: self...
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airloc
airloc-master/doerchnet/utils.py
import torch import numpy as np import torchvision.transforms as transforms import os import gc import matplotlib.patches as patches import matplotlib.pyplot as plt import urllib import matplotlib import random from torch.nn.functional import one_hot from config import CONFIG from utils.utils import get_deterministic...
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airloc
airloc-master/doerchnet/networks.py
import torch import torch.nn as nn import torch.nn.functional as F from config import CONFIG class AJNet(nn.Module): def __init__(self,net_type,mode = 'train', unit_size = 128,num_classes =8 , both_branches = True): super(AJNet,self).__init__() # Allow for pretraining network with ground t...
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airloc
airloc-master/doerchnet/train.py
import os import torch import random import torch.nn.functional as F import torchvision.transforms as transforms import torch.nn as nn import json import numpy as np import matplotlib import matplotlib.pyplot as plt from shutil import copyfile from utils.utils import get_random_crops, get_deterministic_crops, load_...
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airloc
airloc-master/doerchnet/logs/with-sem-seg/share_net.py
import torch import torch.nn as nn from config import CONFIG class ShareNet(nn.Module): def __init__(self , num_out_classes = 8): super(ShareNet, self).__init__() # Check wether to include segmentation channel if CONFIG.RL_priv_use_seg or CONFIG.RL_predict_seg_mask: self...
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airloc
airloc-master/doerchnet/logs/without-sem-seg/share_net.py
import torch import torch.nn as nn from config import CONFIG class ShareNet(nn.Module): def __init__(self , num_out_classes = 8): super(ShareNet, self).__init__() # Check wether to include segmentation channel if CONFIG.RL_priv_use_seg: self.seg_chan = 1 else: ...
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airloc
airloc-master/doerchnet/logs/without-sem-seg-pre-michael/share_net.py
import torch import torch.nn as nn from config import CONFIG class ShareNet(nn.Module): def __init__(self , num_out_classes = 8): super(ShareNet, self).__init__() # Check wether to include segmentation channel if CONFIG.RL_priv_use_seg or CONFIG.RL_predict_seg_mask: self...
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airloc
airloc-master/doerchnet/logs/without-sem-seg-pre-michael/networks.py
import torch import torch.nn as nn import torch.nn.functional as F from config import CONFIG class AJNet(nn.Module): def __init__(self,net_type,mode = 'train', unit_size = 128,num_classes =8 , both_branches = True): super(AJNet,self).__init__() # Allow for pretraining network with ground t...
4,630
27.763975
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airloc
airloc-master/doerchnet/logs/without-sem-seg-pre-michael/config.py
""" Central configration file for the project. Acts as a storage of global variables and various configuration settings. TODO TODO TODO: Remove unnecessary fields below; this is copied from an earlier project """ import os import pprint from easydict import EasyDict as edict from datetime import datetime import socke...
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airloc
airloc-master/doerchnet/logs/without-sem-seg-pre-michael/train.py
import os import torch import random import torch.nn.functional as F import torchvision.transforms as transforms import torch.nn as nn import json import numpy as np import matplotlib import matplotlib.pyplot as plt from shutil import copyfile from utils.utils import get_random_crops, get_deterministic_crops, load_...
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airloc
airloc-master/segmentations/plot_results.py
#!/bin/env python3 import os import time import sys import math from dateutil.parser import parse import numpy as np from config import CONFIG import json import argparse from utils.utils import find_latest_log MA_SMOOTH = 0.0025 START_ITER_PLOT = 30 # What are the customs_mas ? def _custom_ma(data, ma_smooth=MA_S...
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airloc
airloc-master/segmentations/unet_model.py
""" Full assembly of the parts to form the complete network """ from .unet_parts import * class UNet(nn.Module): def __init__(self, n_channels, n_classes, bilinear=False): super(UNet, self).__init__() self.n_channels = n_channels self.n_classes = n_classes self.bilinear = bilinear...
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airloc
airloc-master/segmentations/u_net.py
import torch import torch.nn as nn import torch.nn.functional as F from config import CONFIG class UNet(nn.Module): def __init__(self, n_channels, n_classes, bilinear=False): super(UNet, self).__init__() self.n_channels = n_channels self.n_classes = n_classes self.bilinear ...
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airloc
airloc-master/segmentations/utils.py
from config import CONFIG import math import json import os import time import zipfile import gc import numpy as np import torch import torchvision import torchvision.transforms as transforms from torchvision.datasets import ImageFolder from torch.utils.data import random_split,Subset import matplotlib matplotlib.use(...
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airloc
airloc-master/segmentations/unet_parts.py
""" Parts of the U-Net model """ import torch import torch.nn as nn import torch.nn.functional as F class DoubleConv(nn.Module): """(convolution => [BN] => ReLU) * 2""" def __init__(self, in_channels, out_channels, mid_channels=None): super().__init__() if not mid_channels: mid_c...
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airloc
airloc-master/segmentations/networks.py
import random from config import CONFIG import torch import torchvision.transforms as transforms import torch.nn as nn import torch.nn.functional as F import torch.nn.init as init from utils.utils import calculate_cnn_output_size class BakeNet(nn.Module): def __init__(self, n_out_chan = 2): super(B...
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airloc
airloc-master/segmentations/train.py
import os import torch import random import torchvision import torchvision.transforms as transforms import torch.nn.functional as F import torch.nn as nn import json import numpy as np from torchinfo import summary from shutil import copyfile from utils.utils import get_random_crops, get_deterministic_crops, load_n...
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airloc
airloc-master/segmentations/logs/sem-seg-model/u_net.py
import torch import torch.nn as nn import torch.nn.functional as F from config import CONFIG class UNet(nn.Module): def __init__(self, n_channels, n_classes, bilinear=False): super(UNet, self).__init__() self.n_channels = n_channels self.n_classes = n_classes self.bilinear ...
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airloc
airloc-master/utils/agent_utils.py
import math import os import time import zipfile import warnings import gc import numpy as np import torch import torchvision import torchvision.transforms as transforms from torch.distributions import MultivariateNormal, OneHotCategorical import matplotlib import matplotlib.pyplot as plt from torch.nn import Cross...
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airloc
airloc-master/utils/dataset_utils.py
import os import random import torch from PIL import Image import pandas as pd from torch.utils.data.dataset import Dataset from torchvision import transforms import torchvision.transforms.functional as F import numpy as np import glob from config import CONFIG import argparse import sys import time class DubaiSeven(...
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airloc
airloc-master/utils/utils.py
import math import json import os import time import zipfile import signal import pdb import gc from shutil import copyfile import numpy as np import torch from glob import glob # Might not be available on RISE import seaborn as sns import torchvision import torchvision.transforms as transforms from torchvision.datase...
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airloc
airloc-master/utils/create_split_file.py
import pandas as pd import os import matplotlib import argparse import torch from utils.dataset_utils import * import matplotlib.pyplot as plt import torchvision.transforms as transforms import time import numpy as np from doerchnet.utils import visualize_doerch from utils.utils import sample_grid_games_fixed_distan...
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airloc
airloc-master/utils/create_game_files.py
#!/bin/env python3 import numpy as np import random import pandas as pd from shutil import copyfile import argparse import os, sys from config import CONFIG argparse = argparse.ArgumentParser() argparse.add_argument("--seed" , type = int , default = 0 , help = "Set seed for random number generators") argparse.add...
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airloc
airloc-master/utils/training_utils.py
import torch import sys import numpy as np import torchvision.transforms as transforms from copy import deepcopy import time import math import torchvision.transforms.functional as F from torchvision.transforms import Resize from utils.agent_utils import rewards_to_go, normalize_batch_weights from utils.utils import ...
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airloc
airloc-master/utils/split_images.py
import os import math import glob from PIL import Image import matplotlib import matplotlib.pyplot as plt from matplotlib.colors import rgb2hex,to_rgb from config import CONFIG import cv2 import numpy as np import regex as re matplotlib.use('Agg') data = 'masa' if data == 'dubai': labels = ['#3C1098', '#...
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airloc
airloc-master/utils/normalize_dataset.py
#!/bin/env python3 import os import numpy as np import imageio as iio import time import torch import json import torchvision.transforms as transforms from torchvision.datasets import ImageFolder from torch.utils.data import random_split,Subset from utils.dataset_utils import CustomDataset, Dubai, Masa, MasaFilt, MasaF...
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airloc
airloc-master/utils/__init__.py
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airloc
airloc-master/utils/stat_collector.py
import os import sys import numpy as np from collections import OrderedDict import gc import matplotlib import matplotlib.pyplot as plt import math def replace(string_in, replace_from, replace_to='_'): if not isinstance(replace_from, list): replace_from = [replace_from] string_out = string_in for ...
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aabbcc
aabbcc-master/python/setup.py
#!/usr/bin/env python """ setup.py file for the AABB.cc python interface. """ from distutils.core import setup, Extension aabb_module = Extension('_aabb', sources = ['aabb_wrap.cxx', '../src/AABB.cc'], extra_compile_args = ["-O3", "-std=c++11"], ...
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aabbcc
aabbcc-master/python/hard_disc.py
#!/usr/bin/env python2 # Copyright (c) 2016-2018 Lester Hedges <[email protected]> # # This software is provided 'as-is', without any express or implied # warranty. In no event will the authors be held liable for any damages # arising from the use of this software. # Permission is granted to anyone to us...
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emcee3
emcee3-master/benchmark.py
#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import division, print_function import time import numpy as np import emcee import emcee3 def lnprob(x): return -0.5 * np.sum(x**2) N = 5000 coords = np.random.randn(56, 10) emcee_sampler = emcee.EnsembleSampler(coords.shape[0], coords.shape[1], ...
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emcee3
emcee3-master/setup.py
# -*- coding: utf-8 -*- import os import sys from setuptools import setup from setuptools.command.test import test as TestCommand if "test" in sys.argv: version = "0.0.0" else: # Hackishly inject a constant into builtins to enable importing of the # package even if numpy isn't installed. Only do this if ...
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emcee3
emcee3-master/emcee3/autocorr.py
# -*- coding: utf-8 -*- from __future__ import division, print_function import logging import numpy as np __all__ = ["function", "integrated_time", "AutocorrError"] def function(x, axis=0, fast=False): """Estimate the autocorrelation function of a time series using the FFT. Args: x: The time serie...
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emcee3
emcee3-master/emcee3/state.py
# -*- coding: utf-8 -*- from __future__ import division, print_function import numpy as np __all__ = ["State"] class State(object): """The current state of a walker. This object captures the state of a walker. It will store the coordinates, probabilities, and any other computed metadata. Metadata can ...
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emcee3
emcee3-master/emcee3/model.py
# -*- coding: utf-8 -*- from __future__ import division, print_function import numpy as np from .state import State from .numgrad import numerical_gradient_1, numerical_gradient_2 __all__ = ["is_model", "Model", "SimpleModel"] def is_model(model): return ( hasattr(model, "compute_log_probability") and ...
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emcee3
emcee3-master/emcee3/__init__.py
# -*- coding: utf-8 -*- __version__ = "3.0.0.dev0" try: __EMCEE3_SETUP__ except NameError: __EMCEE3_SETUP__ = False if not __EMCEE3_SETUP__: __all__ = [ "moves", "pools", "autocorr", "Model", "SimpleModel", "Sampler", "Ensemble", "State", ...
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emcee3
emcee3-master/emcee3/ensemble.py
# -*- coding: utf-8 -*- from __future__ import division, print_function import numpy as np from .pools import DefaultPool from .model import is_model, SimpleModel __all__ = ["Ensemble"] class Ensemble(object): """The state of the ensemble of walkers. Args: model (callable or Model): The model spe...
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