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import fastai from neptune.new.integrations.fastai import NeptuneCallback from fastai.vision.all import * import neptune.new as neptune run = neptune.init( project="common/fastai-integration", api_token="<PASSWORD>", tags="basic" ) path = untar_data(URLs.MNIST_TINY) dls = ImageDataLoaders.from_csv(path) # Log al...
[ "neptune.new.integrations.fastai.NeptuneCallback", "neptune.new.init" ]
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import neptune from tensorflow.keras.callbacks import BaseLogger class NeptuneMonitor(BaseLogger): def __init__(self, name, api_token, prj_name, params: tuple = None): assert api_token is not None assert prj_name is not None super(BaseLogger, self).__init__() self.my_name = name ...
[ "neptune.create_experiment", "neptune.init" ]
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'''Train DCENet with PyTorch''' # from __future__ import print_function import torch import torch.nn as nn import torch.optim as optim from torch.utils.data import DataLoader import os import json import neptune import argparse import numpy as np from loader import * from utils.plots import * from utils.utils impor...
[ "neptune.init", "neptune.log_metric", "neptune.create_experiment", "neptune.append_tag" ]
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import gym, torch, random, copy import torch.nn as nn import torch.optim as optim import numpy as np import torch.nn.functional as F import neptune.new as neptune # initialize policy & value network class PolicyNetwork(nn.Module): def __init__(self, beta): super().__init__() self.model = nn.Sequen...
[ "neptune.new.init" ]
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.exceptions.ProjectNotFound", "neptune.new.sync.get_project", "neptune.new.sync.sync_all_runs", "neptune.new.internal.utils.sync_offset_file.SyncOffsetFile", "neptune.new.sync.get_qualified_name", "neptune.new.sync.sync_selected_runs", "neptune.new.sync.synchronization_status" ]
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import neptune # The init() function called this way assumes that # NEPTUNE_API_TOKEN environment variable is defined. neptune.init('zackpashkin/sandbox') PARAMS = {'decay_factor' : 0.5, 'n_iterations' : 117} neptune.create_experiment(name='minimal_example',params=PARAMS) # log some metrics for i in ran...
[ "neptune.create_experiment", "neptune.init", "neptune.log_metric" ]
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import requests import pytest from neptune.neptune_api import NeptuneService from neptune.tests.conftest import get_server_addr @pytest.mark.fpgas(1) def test_coco(request): """ Check the coco service from Neptune with a known image Args: request (fixture): get the cmdline options """ ser...
[ "neptune.neptune_api.NeptuneService", "neptune.tests.conftest.get_server_addr" ]
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""" Script by <NAME>, November 2020 Used to finetune models trained on pathology images (pre-chunked) on External Images """ import numpy as np import tables import pickle import neptune from neptunecontrib.monitoring.keras import NeptuneMonitor import collections from sklearn.utils import class_weight import cv2 fr...
[ "neptune.init" ]
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import warnings from typing import Callable, Sequence, Union import joblib import neptune.new as neptune import neptune.new.integrations.optuna as optuna_utils import optuna import pandas as pd from optuna.samplers import TPESampler from optuna.study import Study from optuna.trial import FrozenTrial, Trial from sklear...
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import neptune def _update_keys(d, prefix): keys = list(d.keys()) for k in keys: d['{}_{}'.format(prefix, k)] = d.pop(k) class NeptuneWriter: def __init__(self, proj_name): self.project = neptune.init(proj_name) self.has_started = False def start(self, args, **kwargs): ...
[ "neptune.init" ]
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import neptune.new as neptune import os import torch.nn as nn import torch import torch.nn.functional as F from torch.optim import SGD, Adam from torch.utils.data import DataLoader, random_split from torch.optim.lr_scheduler import CyclicLR import torch.multiprocessing as mp import numpy as np import random import math...
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# -*- coding: utf-8 -*- # # Copyright (c) 2017, deepsense.io # # 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 applicab...
[ "neptune.internal.cli.storage.upload_storage_utils.upload_to_storage", "neptune.internal.cli.commands.enqueue_utils.EnqueueUtils", "neptune.internal.common.config.neptune_config.load_global_config", "neptune.internal.cli.storage.populate_storage_utils.CopyProgressBar", "neptune.internal.common.NeptuneExcept...
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.exceptions.MetadataInconsistency", "neptune.new.internal.utils.paths.join_paths", "neptune.new.internal.utils.paths.parse_path" ]
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"""Implements Neptune Logger.""" from abc import ABC from typing import TYPE_CHECKING, List from torchflare.callbacks.callback import Callbacks from torchflare.callbacks.states import CallbackOrder from torchflare.utils.imports_check import module_available _AVAILABLE = module_available("neptune") if _AVAILABLE: ...
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#!/usr/bin/env python # The MIT License (MIT) # Copyright (c) 2020 <NAME> # Paper: "Self-Supervised Relational Reasoning for Representation Learning", <NAME> & <NAME>, NeurIPS 2020 # GitHub: https://github.com/mpatacchiola/self-supervised-relational-reasoning # # Implementation of a standard neural network (no self-su...
[ "neptune.send_metric", "neptune.create_experiment", "neptune.init" ]
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# -*- coding: utf-8 -*- # # Copyright (c) 2017, deepsense.io # # 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 applicab...
[ "neptune.internal.common.api.api_service_factory.create_services", "neptune.internal.common.threads.neptune_future.NeptuneFuture", "neptune.internal.common.NeptuneInternalException", "neptune.internal.common.NeptuneException" ]
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import neptune # The init() function called this way assumes that # NEPTUNE_API_TOKEN environment variable is defined. neptune.init('vanducng/sandbox') neptune.create_experiment(name='minimal_example') # log some metrics for i in range(100): neptune.log_metric('loss', 0.95**i) neptune.log_metric('AUC', 0.96)
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import sys from dataclasses import asdict from pathlib import Path from pprint import pprint from typing import Optional import click import matplotlib.pyplot as plt import neptune import torch import torchaudio from click import Context from torch.nn.functional import mse_loss from tqdm import trange, tqdm from refo...
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import itertools import json import logging import os import tempfile from typing import List, Any, Dict, Tuple import gin import numpy as np import pandas as pd from experiments.src.gin import get_default_experiment_name, parse_gin_str from experiments.src.training.training_utils import get_metric_cls GridResultDic...
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# # Copyright (c) 2022, Neptune Labs Sp. z o.o. # # 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 agr...
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import logging import os as os import tempfile import datetime as dt from matplotlib import pyplot as plt import neptune as npt from neptunecontrib import api as npta from neptunecontrib import hpo as npth from neptunecontrib.monitoring import optuna as nmo from neptunecontrib.monitoring import keras as nmk class E...
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import random import neptune import numpy as np import tensorflow as tf import neptune_tensorboard as neptune_tb from absl import flags from absl import app from data_processor import read_data from tensorflow.keras import callbacks, Sequential from tensorflow.keras.layers import LSTM, Dense, Dropout, BatchNormalizati...
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
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import neptune from config import EnvConfig import pandas as pd import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import pickle comet_cfg = EnvConfig() session = neptune.Session(api_token=comet_cfg.neptune_token) project = session.get_project(project_qualified_name=comet_cfg.ne...
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# importing neptune import neptune # File data version from neptunecontrib.versioning.data import log_data_version # File Loader from data_loader import data_loader # Hyperparameter Tuner from hyperparameter_optimizer import create_objective # Model from model.lightgbm_0.model import learning # set UserName/Experiment...
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from functools import partial import os from datetime import datetime, timedelta import numpy as np import torch from PIL import Image import neptune from torch.autograd import Variable from torch.optim.lr_scheduler import ExponentialLR from tempfile import TemporaryDirectory from steppy.base import Step, IdentityOpe...
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# # Copyright (c) 2021, Neptune Labs Sp. z o.o. # # 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 agr...
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import neptune.new as neptune import os from GTApack.GTA_hotloader import GTA_hotloader from GTApack.GTA_Unet import GTA_Unet from GTApack.GTA_tester import GTA_tester from torchvision import datasets, transforms from torch.optim import SGD, Adam from torch.optim.lr_scheduler import (ReduceLROnPlateau, CyclicLR, ...
[ "neptune.new.init", "neptune.new.types.File" ]
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# # Copyright (c) 2021, Neptune Labs Sp. z o.o. # # 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 agr...
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#!/usr/bin/env python # coding: utf-8 # In[1]: #hide get_ipython().run_line_magic('load_ext', 'autoreload') get_ipython().run_line_magic('autoreload', '2') # In[2]: # default_exp core # In[3]: #export from nbdev.export import check_re,read_nb from pathlib import Path import re import os import platform # #...
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from typing import Dict import neptune.new as neptune import numpy as np import pytorch_lightning as pl import torch import torch.nn as nn from config import NEPTUNE_API_TOKEN, NEPTUNE_PROJECT_NAME from sklearn.metrics import classification_report, f1_score from utils.summary_loss import SummaryLoss from math import c...
[ "neptune.new.init" ]
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import argparse import shutil import sys import time import torch.nn.parallel import torch.optim import torch.utils.data from plot_functions_cw import * from helper_functions import * from PIL import ImageFile import neptune.new as neptune from access_keys import neptune_key run = neptune.init(project='irmavdbrandt/In...
[ "neptune.new.init" ]
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# # Copyright (c) 2021, Neptune Labs Sp. z o.o. # # 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 agr...
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import images as images import numpy as np import pandas as pd import xgboost as xgb from sklearn.metrics import r2_score from sklearn.metrics import mean_squared_error as mse from sklearn.model_selection import train_test_split from sklearn.multioutput import MultiOutputRegressor import pickle import neptune import os...
[ "neptune.stop", "neptune.create_experiment", "neptune.log_artifact" ]
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import json import pandas as pd import lightgbm as lgb from loguru import logger from matplotlib import pyplot as plt from sklearn.model_selection import train_test_split import neptune from neptunecontrib.monitoring.lightgbm import neptune_monitor from src.utils.read_params import read_params if __name__ == '__main...
[ "neptune.stop", "neptune.init" ]
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# -*- coding: utf-8 -*- import argparse import sys import time from datetime import datetime import neptune import torch import numpy as np from torch.utils.data import SequentialSampler, RandomSampler import pandas as pd sys.path.insert(0, '.') from configs import CONFIGS # noqa from src.dataset import DatasetRetr...
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# -*- coding: utf-8 -*- # # Copyright (c) 2016, deepsense.io # # 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 applicab...
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import argparse import os import os.path as osp import torch.nn.functional as F import numpy as np import torch import torch.nn as nn import torch.optim as optim import network import loss from torch.utils.data import DataLoader import lr_schedule import data_list from data_list import ImageList, split_train_test from...
[ "neptune.log_metric", "neptune.create_experiment", "neptune.init", "neptune.append_tag" ]
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import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt from collections import defaultdict from neptune import Session import numpy as np import pandas as pd session = Session() project = session.get_projects('csadrian')['csadrian/global-sinkhorn'] def check_crit(params, crit): for k, v in crit.it...
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from functools import partial import hydra import neptune.new as neptune from omegaconf import DictConfig from data.dataset import load_train_dataset from tuning.bayesian import BayesianSearch, xgb_objective @hydra.main(config_path="../config/tuning/", config_name="xgb.yaml") def _main(cfg: DictConfig): print("...
[ "neptune.new.init" ]
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import neptune.new as neptune import pandas as pd from sklearn.ensemble import RandomForestClassifier TRAIN_DATASET_PATH = '../datasets/tables/train.csv' TEST_DATASET_PATH = '../datasets/tables/test.csv' PARAMS = {'n_estimators': 7, 'max_depth': 2, 'max_features': 2, } def train_model(...
[ "neptune.new.init" ]
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#!/usr/bin/env python # coding: utf-8 """investigate the effect of data augmentation with Adam optimizer without lr scheduler on model performance""" # NOTE: 000_004 is not improving score much. # TODO: perform the Learning Rate Range test and plot the result # TODO: add model parameters to Neptune # NOTE: Params: eff...
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# # Copyright (c) 2019, Neptune Labs Sp. z o.o. # # 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 agr...
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from keras.backend import clear_session from keras.layers import Conv1D from keras.layers import Dense from keras.layers import Flatten import optuna import neptune import numpy as np import tensorflow as tf import neptunecontrib.monitoring.optuna as opt_utils from tensorflow.keras.layers import Input, Con...
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# coding=utf-8 # Copyright 2018 <NAME>. # # 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 i...
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.attributes.atoms.datetime.DatetimeVal", "neptune.new.attributes.atoms.datetime.Datetime", "neptune.new.internal.operation.AssignDatetime" ]
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import random import neptune import numpy as np import tensorflow as tf import neptune_tensorboard as neptune_tb from absl import flags from absl import app from data_processor import read_data from tensorflow.keras import callbacks, Sequential from tensorflow.keras.layers import SimpleRNN, Dense, Dropout, BatchNormal...
[ "neptune.create_experiment", "neptune.init" ]
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
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import gym import neptune import tensorflow as tf from spinup import ppo_tf1 as ppo def env_fn(): return gym.make('LunarLander-v2') ac_kwargs = dict(hidden_sizes=[64, 64], activation=tf.nn.relu) neptune.init(project_qualified_name='<namespace/project_name>') experiment = neptune.create_experiment(name='Spinning U...
[ "neptune.create_experiment", "neptune.init" ]
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# -*- coding: utf-8 -*- # @Time : 5/27/2020 5:45 PM # @Author : <NAME> # @Email : <EMAIL> # @File : logger.py # from pathlib import Path # import pandas as pd # import yaml from abc import ABCMeta, abstractmethod # from collections import defaultdict from typing import Any, Optional, Union, Sequence import wan...
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import lightgbm import matplotlib.pyplot as plt import neptune from neptunecontrib.monitoring.utils import pickle_and_send_artifact from neptunecontrib.monitoring.metrics import log_binary_classification_metrics from neptunecontrib.versioning.data import log_data_version import pandas as pd plt.rcParams.update({'font....
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from functools import partial import os import shutil from attrdict import AttrDict import neptune import numpy as np import pandas as pd from sklearn.externals import joblib from steppy.base import Step, IdentityOperation from steppy.adapter import Adapter, E from common_blocks import augmentation as aug from common...
[ "neptune.Context" ]
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
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# # Copyright (c) 2021, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.management.create_project", "neptune.management.add_project_member", "neptune.management.internal.utils.normalize_project_name" ]
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from __future__ import print_function import yaml import easydict import os import argparse import numpy as np import torch from torch import nn from torch.autograd import Variable from apex import amp, optimizers from data_loader.get_loader import get_dataloaders from utils.utils import get_models, get_optimizers, lo...
[ "neptune.log_metric", "neptune.create_experiment", "neptune.init", "neptune.append_tag" ]
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from collections import OrderedDict from hyperopt import hp, tpe, fmin, Trials import neptune import neptunecontrib.hpo.utils as hpo_utils import neptunecontrib.monitoring.skopt as sk_utils import numpy as np import pandas as pd from sklearn.externals import joblib from utils import train_evaluate, axes2fig neptune....
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import random import json import argparse import os import torch from torch.utils.data import DataLoader from torch.optim import Adam from runner.gegl_trainer import GeneticExpertGuidedLearningTrainer from runner.guacamol_generator import GeneticExpertGuidedLearningGenerator from model.neural_apprentice import Smiles...
[ "neptune.set_property", "neptune.append_tag", "neptune.init" ]
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import math from typing import Any, Dict from neptune import new as neptune import pandas as pd from kedro.pipeline import Pipeline, node # ------ Looking for furthest planet ------- def distances(planets: pd.DataFrame) -> Any: planets['Distance from Sun'] = planets['Distance from Sun (106 km)'].apply(lambda ro...
[ "neptune.new.init" ]
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import hashlib import neptune import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from sklearn.metrics import accuracy_score from torchvision import datasets, transforms class Net(nn.Module): def __init__(self, fc_out_features): super(Net, self).__init__() ...
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import argparse import copy import os import neptune from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker from hyperopt import Trials, fmin, hp, tpe from purano.clusterer.clusterer import Clusterer from purano.clusterer.metrics import calc_metrics from purano.io import parse_tg_jsonl, parse_cl...
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
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"""Neptune logger.""" import neptune import numpy as np from ray import tune class NeptuneLogger(tune.logger.Logger): """RLlib Neptune logger. Example usage: ``` import ray from ray import tune ray.init() tune.run( "PPO", stop={"episode_reward_mean": 200}, confi...
[ "neptune.stop" ]
[((2525, 2539), 'neptune.stop', 'neptune.stop', ([], {}), '()\n', (2537, 2539), False, 'import neptune\n')]
import neptune neptune.init('shared/onboarding', api_token='<KEY>') with neptune.create_experiment(name='hello-neptune'): neptune.append_tag('introduction-minimal-example') n = 117 for i in range(1, n): neptune.log_metric('iteration', i) neptune.log_metric('loss', 1/i**0.5) neptune.log_text('magi...
[ "neptune.set_property", "neptune.log_metric", "neptune.create_experiment", "neptune.append_tag", "neptune.init" ]
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# # Copyright (c) 2021, Neptune Labs Sp. z o.o. # # 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 agr...
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# # Copyright (c) 2021, Neptune Labs Sp. z o.o. # # 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 agr...
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import os import lightgbm as lgb import neptune from neptunecontrib.monitoring.lightgbm import neptune_monitor from neptunecontrib.versioning.data import log_data_version from neptunecontrib.api.utils import get_filepaths from neptunecontrib.monitoring.reporting import send_binary_classification_report from neptunecon...
[ "neptune.send_metric", "neptune.send_artifact", "neptune.init" ]
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# # Copyright (c) 2021, Neptune Labs Sp. z o.o. # # 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 agr...
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.init_model_version", "neptune.new.internal.backends.api_model.StringAttribute", "neptune.new.internal.backends.api_model.IntAttribute", "neptune.new.internal.backends.api_model.Attribute" ]
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import neptune.new as neptune import os import matplotlib.pyplot as plt # sgd 411, 412, 413 # adam 414, 415, 416 token = os.getenv('Neptune_api') run1 = neptune.init( project="NTLAB/artifact-rej-scalp", api_token=token, run="AR1-439" ) # adam 1 adam1_rate = run1['network_ADAM/learning_rate'].fetch_value...
[ "neptune.new.init" ]
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import hashlib import os import tempfile import matplotlib.pyplot as plt import neptune import numpy as np import optuna import tensorflow as tf from tensorflow import keras def log_data(logs): neptune.log_metric('epoch_accuracy', logs['accuracy']) neptune.log_metric('epoch_loss', logs['loss']) def train_e...
[ "neptune.log_metric", "neptune.create_experiment", "neptune.set_property", "neptune.init", "neptune.log_text", "neptune.stop", "neptune.log_artifact" ]
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import torch import torch.nn as nn from torch.distributions import Categorical import numpy as np import gym import lolgym.envs from pylol.lib import actions, features, point from pylol.lib import point from absl import flags FLAGS = flags.FLAGS _NO_OP = [actions.FUNCTIONS.no_op.id] _MOVE = [actions.FU...
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# # Copyright (c) 2021, Neptune Labs Sp. z o.o. # # 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 agr...
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import os import re import string from typing import Tuple import flytekit from flytekit import task, workflow, Secret, Resources from flytekit.types.directory import FlyteDirectory from flytekitplugins.kftensorflow import TfJob import tensorflow as tf from tensorflow.keras import layers from tensorflow.keras import lo...
[ "neptune.new.integrations.tensorflow_keras.NeptuneCallback" ]
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.types.series.file_series.FileSeries", "neptune.new.internal.operation.ClearImageLog", "neptune.new.internal.utils.base64_encode", "neptune.utils.split_to_chunks", "neptune.new.exceptions.FileNotFound", "neptune.new.internal.operation.LogImages", "neptune.new.exceptions.OperationNotSupported...
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# # Copyright (c) 2021, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.get_project", "neptune.new.init_project", "neptune.new.init_run", "neptune.new.init_model" ]
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import neptune.new as neptune data_version = "5b49383080a7edfe4ef72dc359112d3c" base_namespace = "production" # (neptune) fetch project project = neptune.get_project(name="common/project-tabular-data") # (neptune) find best run for given data version best_run_df = project.fetch_runs_table(tag="best-finetuned").to_pa...
[ "neptune.new.get_project", "neptune.new.init" ]
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import neptune.new as neptune import time from metrics import calculate_counter, calculate_classification, calculate_counter135 from models.shapes_classifier import ShapesClassifier from models.shapes_counter import ShapesCounter, ShapesCounter135 tracked_values = ['train/loss', 'train/acc', ...
[ "neptune.new.init" ]
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import neptune.new as neptune import os from GTApack.GTA_hotloader import GTA_hotloader from GTApack.GTA_antihot import GTA_antihot from GTApack.GTA_Unet import GTA_Unet from GTApack.GTA_prop_to_hot import GTA_prop_to_hot from GTApack.GTA_tester import GTA_tester from torchvision import datasets, transforms from torch...
[ "neptune.new.init", "neptune.new.types.File" ]
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# # Copyright (c) 2016, deepsense.io # # 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 w...
[ "neptune.internal.common.utils.browser.SilentBrowser", "neptune.internal.common.utils.browser.NullBrowser", "neptune.internal.common.config.neptune_config.load_bool_env", "neptune.internal.cli.commands.data.upload.DataUpload", "neptune.internal.cli.commands.data.remove.DataRemove", "neptune.internal.cli.c...
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# -*- coding: utf-8 -*- # # Copyright (c) 2017, deepsense.io # # 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 applicab...
[ "neptune.internal.common.api.exceptions.NeptuneUnprocessableEntityException", "neptune.internal.common.api.exceptions.ServerTimedOutException", "neptune.internal.common.api.exceptions.NeptuneEntityNotFoundException", "neptune.internal.common.api.exceptions.NeptuneServerRequestFailedException", "neptune.inte...
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.internal.utils.verify_collection_type", "neptune.new.internal.utils.paths.parse_path", "neptune.new.internal.utils.is_float_like", "neptune.new.internal.utils.is_float", "neptune.new.types.atoms.file.File.is_convertable", "neptune.new.internal.utils.is_string", "neptune.new.internal.utils.i...
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import neptune.new as neptune # download runs table from Neptune my_project = neptune.get_project(name="common/colab-test-run", api_token="<PASSWORD>") run_df = my_project.fetch_runs_table(tag=["advanced"]).to_pandas() run_df.head() # resume run run = neptune.init(project="common/colab-test-run", api_token="<PASSWORD...
[ "neptune.new.get_project", "neptune.new.init" ]
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# # Copyright (c) 2022, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.internal.backends.api_model.IntAttribute", "neptune.new.get_last_run", "neptune.new.init_run", "neptune.new.internal.backends.api_model.Attribute" ]
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import neptune.new as neptune run = neptune.init(project="common/colab-test-run", api_token="<PASSWORD>") params = {"learning_rate": 0.1} # log params run["parameters"] = params # log name and append tags run["sys/name"] = "basic-colab-example" run["sys/tags"].add(["colab", "intro"]) # log loss during training for...
[ "neptune.new.init" ]
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""" Log using `neptune <https://www.neptune.ml>`_ Neptune logger can be used in the online mode or offline (silent) mode. To log experiment data in online mode, NeptuneLogger requries an API key: .. code-block:: python from pytorch_lightning.logging import NeptuneLogger # arguments made to NeptuneLogger are ...
[ "neptune.OfflineBackend", "neptune.create_experiment", "neptune.init" ]
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"""Implement a callback to log images.""" # ============================================================================= # Copyright 2021 <NAME> # # 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...
[ "neptune.new.types.File.as_image" ]
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from typing import Dict, List import neptune from catalyst.core.callback import ( Callback, CallbackNode, CallbackOrder, CallbackScope, ) from catalyst.core.runner import IRunner class NeptuneLogger(Callback): """Logger callback, translates ``runner.*_metrics`` to Neptune. Read about Neptune...
[ "neptune.create_experiment", "neptune.init", "neptune.OfflineBackend" ]
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# # Copyright (c) 2019, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.internal.utils.images.get_image_content", "neptune.new.internal.utils.images.get_html_content" ]
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import os import neptune import pandas as pd from src.features.utils import md5_hash, get_filepaths APPLICATION_FEATURES_PATH = 'data/interim/application_features.csv' BUREAU_FEATURES_PATH = 'data/interim/bureau_features.csv' PROCESSED_FEATURES_FILEPATH = 'data/processed/features_joined_v1.csv' NROWS=None def main...
[ "neptune.set_property" ]
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import os import pandas as pd import models import data import generator as gen import json from tensorflow.keras.optimizers import Adam from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau, ModelCheckpoint import multiprocessing from _common import utils from _common import callbacks as cbs impo...
[ "neptune.send_artifact", "neptune.init" ]
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import torch.nn as nn import torch.utils import torch.nn.functional as F import torchvision.datasets as dset import torch.backends.cudnn as cudnn import numpy as np import pandas as pd from tqdm import tqdm import neptune import random import os import glob import torch import utils import logging from model_meta...
[ "neptune.init", "neptune.send_metric", "neptune.set_property", "neptune.create_experiment" ]
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""" Train a model on miniImageNet. """ import random import neptune import tensorflow as tf from supervised_reptile.args import model_kwargs, train_kwargs, evaluate_kwargs, neptune_args from supervised_reptile.eval import evaluate from supervised_reptile.models import ProgressiveMiniImageNetModel from supervised_rep...
[ "neptune.Context" ]
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import neptune.new as neptune import os import torch.nn as nn import torch import torch.nn.functional as F from torch.optim import SGD, Adam from torch.utils.data import DataLoader, random_split from torch.optim.lr_scheduler import CyclicLR import torch.multiprocessing as mp import numpy as np import random import sys...
[ "neptune.new.init" ]
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import argparse import os import random import torch from torch.optim import Adam from runner.pretrain_trainer import PreTrainer from model.neural_apprentice import SmilesGenerator, SmilesGeneratorHandler from util.smiles.dataset import load_dataset from util.smiles.char_dict import SmilesCharDictionary import neptu...
[ "neptune.append_tag", "neptune.init" ]
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""" Script to train model for next sentence prediction """ import os, sys import logging import json import collections import itertools import argparse from typing import * import numpy as np from sklearn import metrics from scipy.special import softmax import torch import torch.nn as nn import skorch import skorc...
[ "neptune.init", "neptune.create_experiment" ]
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import copy import neptune import numpy as np import pommerman import torch from torch import nn from pommerman.dqn import utils, utility from pommerman.dqn.experience_replay import Memory, RecurrentMemory from pommerman.dqn.nets.vdn import VDNMixer class Arena: """Parent abstract Arena.""" def __init__(...
[ "neptune.send_metric" ]
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.internal.threading.daemon.Daemon.ConnectionRetryWrapper" ]
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.attributes.series.string_series.StringSeries" ]
[((820, 866), 'mock.patch', 'patch', (['"""time.time"""'], {'new': 'TestAttributeBase._now'}), "('time.time', new=TestAttributeBase._now)\n", (825, 866), False, 'from mock import patch, MagicMock\n'), ((1230, 1253), 'neptune.new.attributes.series.string_series.StringSeries', 'StringSeries', (['exp', 'path'], {}), '(exp...
# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # 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 agr...
[ "neptune.new.types.File.as_html", "neptune.new.types.File.as_pickle", "neptune.new.internal.utils.images._get_pil_image_data", "neptune.new.types.File.from_stream", "neptune.new.types.File.from_content", "neptune.new.types.File.as_image", "neptune.new.types.File" ]
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# -*- coding: utf-8 -*- import json import os import random import click import neptune import numpy as np import regex import torch from loguru import logger from neptune.exceptions import NoExperimentContext from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset from tqdm import tqd...
[ "neptune.stop", "neptune.send_metric" ]
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