repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
zhooda/learn-ml | [
"e35765fdc3b27fd923cff89cc086d5093eeee25b"
] | [
"src/derivatives.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\n\ndef f(x):\n return 2*x**2\n\nx = np.arange(0, 5, 0.001)\ny = f(x)\n\nplt.plot(x, y)\n\ncolors = ['k', 'g', 'r', 'b', 'c']\n\ndef approximate_tangent_line(x, approximate_derivative):\n return (approximate_derivative*x) + b\n\nfor i in range(5):\n p2_de... | [
[
"matplotlib.pyplot.plot",
"numpy.arange",
"matplotlib.pyplot.show",
"matplotlib.pyplot.scatter"
]
] |
dumpmemory/Uneven_training_data | [
"63350037744b761619d4d8bc7d2122d2bffa2c95"
] | [
"cartography/classification/run_glue.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.\n# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may... | [
[
"scipy.stats.entropy.size",
"torch.max",
"torch.load",
"numpy.squeeze",
"torch.utils.data.DataLoader",
"numpy.mean",
"torch.no_grad",
"torch.cuda.manual_seed_all",
"torch.cuda.is_available",
"torch.device",
"torch.distributed.get_rank",
"numpy.zeros_like",
"torc... |
ajd98/shap | [
"922fa0fe9f198011edd875289fc68b906ff9f2b8"
] | [
"shap/explainers/kernel.py"
] | [
"from iml.common import convert_to_instance, convert_to_model, match_instance_to_data, match_model_to_data, convert_to_instance_with_index\nfrom iml.explanations import AdditiveExplanation\nfrom iml.links import convert_to_link, IdentityLink\nfrom iml.datatypes import convert_to_data, DenseData\nfrom scipy.special ... | [
[
"numpy.sqrt",
"sklearn.cluster.KMeans",
"numpy.squeeze",
"pandas.DataFrame",
"numpy.hstack",
"numpy.reshape",
"numpy.arange",
"sklearn.linear_model.Lasso",
"numpy.ceil",
"numpy.zeros",
"pandas.concat",
"numpy.nonzero",
"numpy.random.choice",
"scipy.special.b... |
brendanjmeade/dmd_gps | [
"bddc401e7a2e8d0fb44fa830d58197f1319b11c9"
] | [
"dmd_japan.py"
] | [
"import json\nimport datetime\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pydmd as dmd\n\nplt.close(\"all\")\n\n\nwith open('GeonetTimeSeries.json') as json_file: \n data = json.load(json_file)\n\nn_stations = len(data)\nstation_idx = 1\nstation_data = data[station_idx]\n\n# Loop over all time ... | [
[
"matplotlib.pyplot.matshow",
"matplotlib.pyplot.show",
"numpy.zeros",
"matplotlib.pyplot.close"
]
] |
zhfeing/deep-learning-lib-PyTorch | [
"f96e3a71ae2dbeb44696725ec127ff8f37d4c6e9"
] | [
"cv_lib/classification/models/cifar_large_resnet.py"
] | [
"import torch.nn as nn\r\nimport torch.nn.functional as F\r\n\r\n\r\n__all__ = [\r\n \"ResNet_CL\",\r\n \"resnet18_cl\",\r\n \"resnet34_cl\",\r\n \"resnet50_cl\",\r\n \"resnet101_cl\",\r\n \"resnet152_cl\"\r\n]\r\n\r\n\r\nclass BasicBlock(nn.Module):\r\n expansion = 1\r\n\r\n def __init__(se... | [
[
"torch.nn.Sequential",
"torch.nn.init.constant_",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.functional.relu",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_"
]
] |
photoszzt/pytorch | [
"f2857883c4c148ced4f920431b38532fe8081b73"
] | [
"test/distributed/test_c10d_gloo.py"
] | [
"import copy\nimport logging\nimport math\nimport operator\nimport os\nimport random\nimport sys\nimport tempfile\nimport unittest\nfrom functools import reduce\nfrom itertools import groupby\n\nimport torch\nimport torch.distributed as c10d\n\nif not c10d.is_available():\n print(\"c10d not available, skipping t... | [
[
"torch.nn.functional.softmax",
"torch.randint",
"torch.testing._internal.common_utils.find_free_port",
"torch.zeros",
"torch.load",
"torch.testing._internal.common_distributed.verify_ddp_error_logged",
"torch.distributed.PrefixStore",
"torch.sparse_coo_tensor",
"torch.FloatTens... |
zhangyingying94/models | [
"bf46247b4207698bbeb315d9086eb81662015359"
] | [
"adversarial_text/data/data_utils.py"
] | [
"# Copyright 2017 Google, Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by app... | [
[
"tensorflow.gfile.MakeDirs",
"tensorflow.train.SequenceExample",
"tensorflow.python_io.TFRecordWriter"
]
] |
mrdon/manim | [
"d023c76cdef915226bb9a1e41c20168959a02881"
] | [
"manim/scene/scene.py"
] | [
"\"\"\"Basic canvas for animations.\"\"\"\n\n\n__all__ = [\"Scene\"]\n\n\nimport inspect\nimport random\nimport warnings\nimport platform\nimport copy\n\nfrom tqdm import tqdm as ProgressDisplay\nimport numpy as np\n\nfrom .. import config, logger\nfrom ..animation.animation import Animation, Wait\nfrom ..animation... | [
[
"numpy.max",
"numpy.arange",
"numpy.random.seed"
]
] |
AutoDash/AutoDash | [
"3924795a04159f80ea3b65b2172747babd15f35f"
] | [
"src/executor/SegmentSplitter.py"
] | [
"from ..data.VideoItem import VideoItem\nfrom ..data.VideoFile import VideoFile\nfrom .iExecutor import iExecutor\nfrom ..signals.SkipSignal import SkipSignal\nimport re\nimport numpy as np\n\nclass SegmentSplitter(iExecutor):\n def __init__(self, *parents, clip_length='5s', length_threshold='3s'):\n supe... | [
[
"numpy.searchsorted",
"numpy.array",
"numpy.sort",
"numpy.unique"
]
] |
Joao16am/si | [
"813ca373022fc5ee35eac69147b5567275718b46"
] | [
"src/si/util/im2col.py"
] | [
"import numpy as np\n\n\ndef calc_pad_dims_2D(X_shape, out_dim, kernel_shape, stride):\n if not isinstance(X_shape, tuple):\n raise ValueError(\"`X_shape` must be of type tuple\")\n\n if not isinstance(out_dim, tuple):\n raise ValueError(\"`out_dim` must be of type tuple\")\n\n if not isinsta... | [
[
"numpy.pad",
"numpy.arange",
"numpy.tile",
"numpy.array",
"numpy.zeros"
]
] |
SWang848/DCRAC | [
"695d83063cf484cd54d7744c8c719fde94c3cde5"
] | [
"history.py"
] | [
"import numpy as np\nimport time\nimport cv2\ntry:\n from PIL import Image\nexcept:\n import Image\n\nfrom utils import *\n\n\nclass History():\n \"\"\"\n Manages frame history\n \"\"\"\n\n def __init__(self, length, im_shape, nb_action):\n \"\"\"\n Args:\n len... | [
[
"numpy.zeros",
"numpy.roll",
"numpy.ones"
]
] |
Wendy-Xiao/ext_summ_disco_tree_attn | [
"5ff99c8260350c677e140b02521c75ac03d16673"
] | [
"utils.py"
] | [
"from collections import Counter\nfrom pathlib import Path\nfrom random import random\nimport rouge_papier_v2\nimport pandas as pd\nimport re\nimport numpy as np\nimport os\nimport json \nimport torch\nimport os\nimport subprocess\n# import matplotlib.pyplot as plt\n\n# Utility functions\ndef get_posweight(inputs_d... | [
[
"numpy.asarray",
"numpy.array",
"torch.load"
]
] |
mrshu/onnxruntime | [
"a7a2a16edddc283b53d7737f897b4bbda5e86209"
] | [
"orttraining/orttraining/test/python/orttraining_test_ortmodule_poc.py"
] | [
"import argparse\nimport logging\nimport os\nimport torch\nimport time\nfrom torchvision import datasets, transforms\n\nimport onnxruntime\nfrom onnxruntime.training import ORTModule\n\n\nclass NeuralNet(torch.nn.Module):\n def __init__(self, input_size, hidden_size, num_classes):\n super(NeuralNet, self)... | [
[
"torch.nn.CrossEntropyLoss",
"torch.manual_seed",
"torch.nn.Linear",
"torch.no_grad",
"torch.cuda.is_available",
"torch.nn.ReLU"
]
] |
haochenucr/scdiff2 | [
"ebc4149851399b2f15ed5b5874d44764b5f130fb"
] | [
"scdiff2/prerun.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n# Author: Jun Ding\n# Email: junding (at) cs (dot) cmu (dot) edu\n# Date: June. 29th, 2020\n# \n# This scdiff software suite is desinged to infer the clusters, trajectories, and regulatory\n# networks underlying dynamic biological process (e.g., cell differntiation, disease ... | [
[
"matplotlib.use"
]
] |
IQcollaboratory/galpopFM | [
"1b30abc1cc2fd1119d0f34a237b0c1112d7afc9d"
] | [
"galpopfm/dust_infer.py"
] | [
"'''\n\n\n\n'''\nimport os \nimport sys \nimport h5py \nimport numpy as np \nfrom scipy.stats import chi2 \nnp.seterr(divide='ignore', invalid='ignore')\n# -- abcpmc -- \nimport abcpmc\nfrom abcpmc import mpi_util\n# -- galpopfm --\nfrom . import dustfm as dustFM\nfrom . import measure_obs as measureObs\n\ndat_dir ... | [
[
"scipy.stats.chi2.rvs",
"numpy.abs",
"numpy.isfinite",
"numpy.random.seed",
"numpy.arange",
"numpy.median",
"numpy.cumsum",
"numpy.histogramdd",
"numpy.concatenate",
"numpy.seterr",
"numpy.random.normal",
"numpy.random.rand",
"numpy.array",
"numpy.sum",
... |
PedrV/stfX | [
"017436cd4ade7f0ea95185d82408697c43ac6ce6"
] | [
"validation/utils/m1.py"
] | [
"import unittest\nimport os\nfrom matplotlib import pyplot as plt\nfrom shapely import geometry, affinity\n\nX_COORDINATE = 0\nY_COORDINATE = 1\n\n\ndef extract_x_y(polygon: list) -> (list, list):\n \"\"\"Extract the x and y coordinates as two separate lists\"\"\"\n x_list = []\n y_list = []\n\n for ver... | [
[
"matplotlib.pyplot.figure",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.fill",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylabel"
]
] |
rostyboost/cvxpy | [
"95e728b01b6bb442c924812c7eac631019c5cbc6"
] | [
"cvxpy/tests/test_examples.py"
] | [
"\"\"\"\nCopyright 2013 Steven Diamond\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to i... | [
[
"numpy.random.random",
"numpy.random.seed",
"numpy.logspace",
"scipy.sparse.eye",
"numpy.eye",
"scipy.sparse.rand",
"numpy.linalg.norm",
"numpy.ones",
"numpy.random.normal",
"numpy.random.randn",
"numpy.array",
"numpy.zeros",
"numpy.random.randint"
]
] |
nids2001/UncertainSCI | [
"b3105bddc064575477589d7a930c71fa3149ef36"
] | [
"demos/anisotropic_distribution.py"
] | [
"# Demonstrates generation of anisotropic distributions. Example is similar to\n# quantiles.py demo.\n\nimport numpy as np\nfrom matplotlib import pyplot as plt\n\nfrom UncertainSCI.distributions import BetaDistribution\nfrom UncertainSCI.model_examples import sine_modulation\nfrom UncertainSCI.indexing import Tota... | [
[
"matplotlib.pyplot.legend",
"numpy.linspace",
"numpy.arange",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.fill_between",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"numpy.zeros"
]
] |
ZohrehShams/IntegrativeRuleExtractionMethodology | [
"fd7b569d11de540ffe94e0cc588e78305e45689e"
] | [
"code/src/functionality_helpers.py"
] | [
"import numpy as np\nimport pickle\nimport dnn_re\nfrom evaluate_rules.predict_explain import predict_explain, print_explanation\nfrom evaluate_rules.overlapping_features import features_recurrence_in_explanation\nfrom src import *\nfrom evaluate_rules.predict_explain import predict_explain, print_explanation\nfrom... | [
[
"numpy.load",
"numpy.random.uniform",
"numpy.random.seed",
"numpy.random.randint"
]
] |
Justin-A/PyTorch-tutorials-kr | [
"0d8e407523e5e75de0081becf800b82b37eb912f"
] | [
"intermediate_source/pruning_tutorial.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n가지치기 기법(Pruning) 튜토리얼\n=====================================\n**저자**: `Michela Paganini <https://github.com/mickypaganini>`_\n**번역** : `안상준 <https://github.com/Justin-A>`_\n\n최첨단 딥러닝 모델들은 굉장히 많은 수의 파라미터값들로 구성되기 때문에, 쉽게 배포되기 어렵습니다.\n이와 반대로, 생물학적 신경망들은 효율적으로 희소하게 연결된 것으로 알려져 있습니다.\n모... | [
[
"torch.nn.utils.prune.ln_structured",
"torch.nn.utils.prune.remove",
"torch.nn.Conv2d",
"torch.sum",
"torch.nn.Linear",
"torch.nn.utils.prune.l1_unstructured",
"torch.cuda.is_available",
"torch.nn.utils.prune.global_unstructured",
"torch.nn.utils.prune.random_unstructured"
]
... |
CWSmith022/yigit-lab | [
"8ec1f7d0242d36351ef92bc6698358c9431f4c34"
] | [
"AGONS/AGONS/test.py"
] | [
"# %%\n\"\"\"Test how custom functions work with sklearn package.\"\"\"\nimport numpy as np\nfrom sklearn.preprocessing import FunctionTransformer\nfrom sklearn.preprocessing import StandardScaler, MinMaxScaler\nx = np.array([[1,2,3], [6,5,4], [8,7,9]])\nprint(x)\ndef SSRow(X):\n X_ = X.copy()\n X_t = Standar... | [
[
"sklearn.preprocessing.StandardScaler",
"numpy.array",
"sklearn.preprocessing.MinMaxScaler",
"sklearn.preprocessing.FunctionTransformer"
]
] |
hoaaoh/Audio2Vec | [
"96711c2300646ce10878113fa0d506d703db96d7"
] | [
"src/plot_perfomance.py"
] | [
"#!/usr/bin/env python3\n\nimport argparse\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom scipy.interpolate import spline\ndef main():\n AE_small_list = [ 0.730, 0.685, 0.737, 0.693, 0.881, 0.713 ]\n AE_large_list = [ 0.234, 0.307, 0.400, 0.323, 0.317, 0.233 ]\n ### m = [ 3, 6, 10, 15, 21, 26 ]... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
Boltuzamaki/Monk_Object_Detection | [
"baf113ef6db8b531d0ef6413538e49d422163a20"
] | [
"12_tf_obj_1/lib/calculate_map.py"
] | [
"# Code from - https://github.com/Cartucho/mAP\n\nimport glob\nimport json\nimport os\nimport shutil\nimport operator\nimport sys\nimport argparse\nimport math\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\n\n\ndef log_average_miss_rate(prec, rec, num_images):\n \"\"\"\n log-average miss rate:\... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.gca",
"numpy.maximum",
"matplotlib.pyplot.title",
"numpy.logspace",
"matplotlib.pyplot.gcf",
"numpy.insert",
"matplotlib.pyplot.close",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.text",
"matplotlib.pyplot.show",
"nu... |
USEPA/sensortoolkit | [
"a9da32fd4df492154c6e4cc570011d14e933ee83"
] | [
"sensortoolkit/evaluation_objs/_sensor_eval.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nTop-level analysis module for the ``sensortoolkit`` library.\n\nContains the front-facing ``SensorEvaluation`` class for conducting analysis\nof sensor data.\n\n===============================================================================\n\n@Author:\n | Samuel Frederick, NSSC... | [
[
"pandas.to_datetime",
"matplotlib.pyplot.subplots",
"pandas.Timedelta",
"pandas.DataFrame",
"pandas.to_timedelta"
]
] |
markyong97/retinafacetest | [
"b72317d682c9e17492f5418073073e63c4ce2ce2"
] | [
"retinaface/inference.py"
] | [
"import argparse\nimport json\nfrom pathlib import Path\nfrom typing import Any, Dict, List, Optional, Tuple, Union\n\nimport albumentations as albu\nimport cv2\nimport numpy as np\nimport torch\nimport torch.nn.parallel\nimport torch.utils.data\nimport torch.utils.data.distributed\nimport yaml\nfrom albumentations... | [
[
"torch.nn.functional.softmax",
"torch.distributed.init_process_group",
"torch.utils.data.distributed.DistributedSampler",
"torch.utils.data.DataLoader",
"numpy.tile",
"torch.no_grad",
"torch.where",
"torch.device",
"numpy.array",
"torch.nn.parallel.DistributedDataParallel"
... |
pentschev/xarray | [
"de6144c0e8c8fc316cfc412a2057af4d1a04edfd"
] | [
"xarray/tests/test_dataset.py"
] | [
"import pickle\nimport sys\nimport warnings\nfrom copy import copy, deepcopy\nfrom io import StringIO\nfrom textwrap import dedent\n\nimport numpy as np\nimport pandas as pd\nimport pytest\nfrom pandas.core.computation.ops import UndefinedVariableError\nfrom pandas.core.indexes.datetimes import DatetimeIndex\nfrom ... | [
[
"pandas.tseries.frequencies.to_offset",
"pandas.Series",
"numpy.linspace",
"numpy.asarray",
"numpy.issubdtype",
"pandas.MultiIndex.from_tuples",
"pandas.DataFrame",
"numpy.dtype",
"numpy.random.randn",
"numpy.mean",
"scipy.integrate.cumtrapz",
"numpy.trapz",
"nu... |
vfcosta/coegan-trained | [
"44174e68909d9c03bf2e4b7e4c7a48237a560183"
] | [
"evolution/evaluator.py"
] | [
"import util.tools as tools\nfrom util import config\nimport torch\nimport logging\nimport numpy as np\nfrom evolution.population import Population\n\nlogger = logging.getLogger(__name__)\n\n\nclass Evaluator:\n\n def __init__(self, train_loader, validation_loader):\n self.train_loader = train_loader\n ... | [
[
"numpy.random.choice",
"torch.cat",
"torch.cuda.empty_cache",
"torch.no_grad",
"numpy.array"
]
] |
ReneeYe/XSTNet | [
"c5e508aed878d13fea790caee71db1ce77619465",
"c5e508aed878d13fea790caee71db1ce77619465"
] | [
"neurst/tasks/cross_modal_translation.py",
"neurst/tasks/seq2seq.py"
] | [
"# Copyright 2020 ByteDance Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agre... | [
[
"tensorflow.data.experimental.group_by_window",
"tensorflow.cond",
"tensorflow.TensorShape",
"tensorflow.constant",
"tensorflow.concat",
"tensorflow.shape",
"tensorflow.less",
"tensorflow.reshape",
"tensorflow.cast",
"tensorflow.expand_dims",
"tensorflow.where",
"te... |
Albert0147/G-SFDA | [
"6ded750224266cd4cdb100a7fcedfa95688d22da"
] | [
"train_tar_visda.py"
] | [
"import argparse\nimport os, sys\nimport os.path as osp\nimport torchvision\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torchvision import transforms\nimport network, loss\nfrom torch.utils.data import DataLoader\nfrom data_list import ImageList, ImageList_idx\nimport... | [
[
"torch.nn.functional.normalize",
"torch.nn.Softmax",
"torch.mean",
"torch.max",
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.load",
"torch.randn",
"torch.manual_seed",
"torch.utils.data.DataLoader",
"numpy.round",
"torch.utils.data.random_split",
"torch... |
maxburke/arrow | [
"344ed4bed675c4913db5cc7b17d0e6cc57ea55c4"
] | [
"python/pyarrow/tests/test_parquet.py"
] | [
"# -*- coding: utf-8 -*-\n# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.... | [
[
"pandas.Categorical.from_codes",
"pandas.concat",
"pandas.to_datetime",
"pandas.Series",
"numpy.random.seed",
"pandas.Timestamp",
"numpy.arange",
"pandas.Categorical",
"pandas.DataFrame",
"pandas.MultiIndex.from_arrays",
"pandas.util.testing.assert_frame_equal",
"nu... |
dddd1007/mne-python | [
"844d53c866bbea932dd6c89ab444bb7f882f0b6f"
] | [
"mne/viz/_brain/_brain.py"
] | [
"# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>\n# Eric Larson <larson.eric.d@gmail.com>\n# Oleh Kozynets <ok7mailbox@gmail.com>\n# Guillaume Favelier <guillaume.favelier@gmail.com>\n# jona-sassenhagen <jona.sassenhagen@gmail.com>\n# Joan Massich <mailsik@gm... | [
[
"numpy.diag",
"numpy.dot",
"numpy.asarray",
"numpy.in1d",
"numpy.round",
"numpy.max",
"numpy.concatenate",
"matplotlib.image.imread",
"numpy.mean",
"numpy.any",
"numpy.searchsorted",
"numpy.cross",
"numpy.where",
"numpy.clip",
"numpy.unique",
"numpy.... |
tuq820/efficientdet_with_landmark | [
"438d92168e5bb91d9ea9bd4b5c743ef41f936fde"
] | [
"train.py"
] | [
"import os\nimport argparse\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import DataLoader\nfrom torchvision import transforms\nfrom src.dataset import CocoDataset, Resizer, Normalizer, Augmenter, collater, MaJiaDataset\nfrom src.model import EfficientDet\nfrom tensorboardX import SummaryWriter\nimpo... | [
[
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"torch.cuda.manual_seed",
"torch.load",
"torch.manual_seed",
"torch.utils.data.DataLoader",
"torch.nn.DataParallel",
"numpy.mean",
"torch.rand",
"torch.cuda.is_available",
"torch.no_grad",
"torch.cuda.device_count"
]
] |
maneeshdisodia/skills-ml | [
"194b262aa5bad1af381d1f63f8b327cf96523950"
] | [
"skills_ml/algorithms/sampling/methods.py"
] | [
"\"\"\"Generic sampling methods\"\"\"\nimport numpy as np\nimport heapq as hq\nimport random\n\ndef reservoir(it, k):\n \"\"\"Reservoir sampling with Random Sort from a job posting iterator\n\n Randomly choosing a sample of k items from a streaming iterator. Using random sort to implement the algorithm.\n ... | [
[
"numpy.random.uniform"
]
] |
bird-house/blackswan | [
"5f1f20423874315f5e8eea2cf7302f9d0c05adae"
] | [
"blackswan/pythonanattribution.py"
] | [
"# import logging\n# LOGGER = logging.getLogger(\"PYWPS\")\n\nimport pandas\nimport random\nimport numpy as np\n\n\ndef analogs_generator(anafile, yfile, nsim=20):\n \"\"\"\n Simulates nsim values of the variable y using analogues for all the dates present in the file anafile\n \n :param anafile: path t... | [
[
"pandas.read_table",
"pandas.concat",
"numpy.repeat",
"pandas.DataFrame"
]
] |
PrateekMunjal/TorchAL | [
"ec60b093333c66e4c8862d128d81680060fddf36",
"ec60b093333c66e4c8862d128d81680060fddf36"
] | [
"al_utils/vae_sampling.py",
"pycls/models/resnet_style/shake_shake_function.py"
] | [
"import torch\nimport os\nimport math\nimport numpy as np\nfrom copy import deepcopy\nfrom pycls.core.config import cfg\nimport pycls.utils.distributed as du\nfrom tqdm import tqdm\n\n\nclass AdversarySampler:\n def __init__(self, budget):\n self.budget = budget\n self.cuda_id = torch.cuda.current_... | [
[
"numpy.dot",
"torch.transpose",
"torch.mm",
"torch.cuda.current_device",
"numpy.min",
"numpy.arange",
"torch.reshape",
"torch.min",
"torch.cat",
"torch.from_numpy",
"numpy.concatenate",
"numpy.argmax",
"torch.no_grad",
"torch.stack",
"numpy.argsort",
... |
SchernHe/FairML | [
"ebd32df6dec1d5232e05e18c88e89179a420659e"
] | [
"fairml/metrics/utils.py"
] | [
"\"\"\"Provides useful functions to calculate fairness metrics\"\"\"\nfrom sklearn.metrics import confusion_matrix, accuracy_score, precision_score\nimport numpy as np\nimport pandas as pd\n\n\ndef calculate_precision(df, target_variable, prediction_variable):\n \"\"\"Calculate precision / positive predictive va... | [
[
"numpy.arange",
"sklearn.metrics.precision_score",
"sklearn.metrics.confusion_matrix",
"numpy.array",
"sklearn.metrics.accuracy_score"
]
] |
mpiecka/metalcode | [
"b0306dc9d8de53d797c946254fa63fa8b3fbf093"
] | [
"metalcode_v1_0.py"
] | [
"from numpy import *\r\nimport matplotlib.pyplot as plt\r\nimport time\r\nimport os\r\nimport warnings\r\nwarnings.filterwarnings(\"ignore\", category=VisibleDeprecationWarning)\r\n\r\n# from metalcode_calib_metal import metal_transf\r\nfrom metalcode_calib_tempe import Teff\r\nfrom metalcode_calib_tempe import Bol... | [
[
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.locator_params",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.close",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.figure"
]
] |
haoyu0831/Covid-Mobility-Network-Analysis | [
"8464b0a25db03585219c1fc6d8e257a9ed826628"
] | [
"model.py"
] | [
"import networkx as nx\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\n'''\nThis function is to generate a graph with data produced by read_file.py\n'''\n\n\ndef generate_d_network(dest_cbgs):\n G = nx.DiGraph()\n # add edges\n for i in dest_cbgs:\n G.add_edge(*i, weight=dest_cbgs[i])\n\n ... | [
[
"numpy.array"
]
] |
cperreault11/scikit-learn | [
"0b78cb00e69109f498c326ad84953954e349d11f"
] | [
"sklearn/dummy.py"
] | [
"# Author: Mathieu Blondel <mathieu@mblondel.org>\n# Arnaud Joly <a.joly@ulg.ac.be>\n# Maheshakya Wijewardena <maheshakya.10@cse.mrt.ac.lk>\n# License: BSD 3 clause\n\nimport warnings\nimport numpy as np\nimport scipy.sparse as sp\n\nfrom .base import BaseEstimator, ClassifierMixin, RegressorMixin\n... | [
[
"numpy.log",
"scipy.sparse.issparse",
"numpy.reshape",
"numpy.asarray",
"numpy.median",
"numpy.tile",
"numpy.percentile",
"numpy.ones",
"numpy.atleast_1d",
"numpy.isscalar",
"numpy.ravel",
"numpy.array",
"numpy.average",
"numpy.zeros",
"numpy.where",
... |
ceausuveronica/OpenCV-projects | [
"fe9a95eead97212de5afeb59b31a8996ce7fb116"
] | [
"colored-led-counter/app.py"
] | [
"# import the necessary packages\nimport argparse\nimport numpy as np\nfrom pprint import pprint\n\n\ntry:\n from cv2 import cv2\n\n ap = argparse.ArgumentParser()\n ap.add_argument(\"-i\", \"--image\", required=True,\n help=\"path to the input image\")\n ap.add_argument(\"-c\", \"--c... | [
[
"numpy.array",
"numpy.zeros"
]
] |
jtmccr1/variant_pipeline | [
"b4a26398a5707814884cbf80a2e22032476e6479"
] | [
"scripts/position_data.py"
] | [
"from __future__ import division\nimport pysam\nimport numpy as np\nimport yaml \nfrom Bio import SeqIO \nfrom Bio.Seq import Seq\nfrom Bio.Alphabet import generic_dna\n#from scripts.seq_classes import locus, segment, tally, allele # %%\nfrom seq_classes import locus, segment, tally, allele\n#from scripts.trim_to_r... | [
[
"numpy.cumsum"
]
] |
willzhang100/diora | [
"40b3533e0a181c23cb3d17a65fca528c72813cfb"
] | [
"pytorch/diora/net/outside_index.py"
] | [
"import torch\nfrom diora.net.offset_cache import get_offset_cache\n\n\nclass OutsideIndex(object):\n def get_pairs(self, level, i, n):\n \"\"\"\n Returns all (parent, sibling) coordinate pairs that\n are used to construct a node at coordinates\n (level, i) where there n leaf nodes.\n... | [
[
"torch.cuda.current_device",
"torch.tensor"
]
] |
Geolem/tensorflow | [
"cfc9d3e1ba3b50dc66f1b81eaea537772ab16024"
] | [
"tensorflow/python/distribute/collective_all_reduce_strategy.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.distribute.distribute_lib.StrategyExtendedV1.__init__",
"tensorflow.python.platform.tf_logging.error",
"tensorflow.python.eager.context.async_wait",
"tensorflow.python.distribute.numpy_dataset.SingleDevice",
"tensorflow.python.framework.ops.executing_eagerly_outside_function... |
a07458666/UncertaintyFlow | [
"cef2512901d4e27bb22fc3997522cd47c03b569c"
] | [
"module/dun_datasets/additional_gap_loader.py"
] | [
"import zipfile\r\nimport pickle\r\ntry:\r\n import urllib\r\n from urllib import urlretrieve\r\nexcept Exception:\r\n import urllib.request as urllib\r\nfrom os import path\r\n\r\nimport numpy as np\r\nfrom numpy.random import uniform, randn\r\nimport matplotlib.pyplot as plt\r\nfrom sklearn.model_selecti... | [
[
"numpy.hstack",
"numpy.abs",
"numpy.random.seed",
"numpy.eye",
"sklearn.model_selection.train_test_split",
"numpy.save",
"numpy.stack",
"numpy.concatenate",
"numpy.random.uniform",
"numpy.sin",
"numpy.cos",
"numpy.random.randn",
"numpy.load",
"numpy.zeros"
... |
sumanbanerjee1/Code-Mixed-Dialog | [
"9df1d4dc800548a883f8bc1a9ce4116c77aebc02"
] | [
"code/train_seq2seq.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport json\nimport pickle\nimport os\nimport subprocess\nimport matplotlib.pyplot as plt\nimport matplotlib.ticker as ticker\n\nfrom tqdm import tqdm\nfrom seq2seq.model import Seq2seqModel\nfrom seq2seq.data_utils import pad, replace_token_no, get_len\n\nflags = tf.ap... | [
[
"tensorflow.train.get_checkpoint_state",
"matplotlib.ticker.MultipleLocator",
"tensorflow.Graph",
"numpy.asarray",
"numpy.squeeze",
"matplotlib.pyplot.savefig",
"tensorflow.global_variables_initializer",
"numpy.delete",
"numpy.mean",
"numpy.row_stack",
"tensorflow.Sessi... |
LaplaceKorea/Data | [
"8c16fc8c4cc29c1dc42d340ba1452c7fbc222bd3"
] | [
"FeaturesSP500.py"
] | [
"\nfrom typing import Any, Dict, List, Tuple\nfrom Config import cfg\nfrom Features import *\nimport numpy as np\n\nDELAYED_BID = 66\nDELAYED_ASK = 67\nDELAYED_LAST = 68\nDELAYED_BID_SIZE = 69\nDELAYED_ASK_SIZE = 70\nDELAYED_LAST_SIZE = 71\nDELAYED_HIGH = 72\nDELAYED_LOW = 73\nDELAYED_VOLUME = 74\nDELAYED_CLOSE = 7... | [
[
"numpy.vstack"
]
] |
Chen-Yifan/weaver | [
"431a1427a185fa6357e40b729b8adcf263c349d2"
] | [
"utils/data/config.py"
] | [
"import numpy as np\nimport yaml\nimport copy\n\nfrom ..logger import _logger\nfrom .tools import _get_variable_names\n\n\ndef _as_list(x):\n if x is None:\n return None\n elif isinstance(x, (list, tuple)):\n return x\n else:\n return [x]\n\n\ndef _md5(fname):\n '''https://stackover... | [
[
"numpy.array"
]
] |
developmentseed/label-maker-dask | [
"700d2fa224ac674171fd8c4f8709a67f862eac36"
] | [
"label_maker_dask/utils.py"
] | [
"# pylint: disable=unused-argument\n\"\"\"Provide utility functions\"\"\"\nimport os\nfrom io import BytesIO\nfrom urllib.parse import parse_qs\n\nimport numpy as np\nimport rasterio\nimport requests # type: ignore\nfrom mercantile import Tile, bounds\nfrom PIL import Image, ImageColor\nfrom rasterio.crs import CR... | [
[
"numpy.count_nonzero",
"numpy.moveaxis"
]
] |
DanielCalimayor/DS-Unit-3-Sprint-3-Productization-and-Cloud | [
"d1479de0badb674daf9cbb8b5f738d214de831ed"
] | [
"Iris_Deploy.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[ ]:\n\n\n#pip install pickle-mixin\n\n\n# In[1]:\n\n\n#import the basics but important libraries\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n#Sklearn Preprocessing\nfrom sklearn.preprocessing import LabelEncoder\... | [
[
"pandas.read_csv",
"sklearn.model_selection.train_test_split",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.preprocessing.LabelEncoder",
"sklearn.metrics.classification_report",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.show",
"sklearn.metrics.accuracy_score"
]
] |
cnheider/MinkowskiEngine | [
"ae6db31203ba012df2f695576e2d3819d49bf2d7"
] | [
"examples/indoor.py"
] | [
"# Copyright (c) Chris Choy (chrischoy@ai.stanford.edu).\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy of\n# this software and associated documentation files (the \"Software\"), to deal in\n# the Software without restriction, including without limitation the rights to\n# use, co... | [
[
"torch.load",
"torch.from_numpy",
"torch.no_grad",
"torch.cuda.is_available",
"numpy.array"
]
] |
AcodeC/video | [
"5d4497621cba764dc51ae22b10e1196c6e9e28bc"
] | [
"dataset/transform.py"
] | [
"import math\nimport re\nimport string\n\nimport numpy as np\nimport torch\n\n\nclass UniformSample:\n def __init__(self, n_sample):\n self.n_sample = n_sample\n\n def __call__(self, frames):\n n_frames = len(frames)\n if n_frames < self.n_sample:\n return frames\n\n sam... | [
[
"numpy.linspace",
"numpy.random.choice",
"numpy.asarray",
"torch.from_numpy",
"numpy.random.normal",
"numpy.zeros_like"
]
] |
isomorphicdude/Highlighted-Text-OCR | [
"07557bf77172b5e411f83352d8c4a6ba1b46fe6a"
] | [
"detect_mask_and_ocr.py"
] | [
"import cv2\r\nimport numpy as np\r\nimport torch\r\nimport easyocr\r\n\r\n# Reading the image\r\n\r\nimg = cv2.imread('image.jpg')\r\n\r\n#define kernel size \r\nkernel = np.ones((7,7),np.uint8)\r\n\r\n\r\n# convert to hsv colorspace \r\nhsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)\r\n\r\n# lower bound and upper bo... | [
[
"numpy.array",
"numpy.ones"
]
] |
OSUmageed/pyHeatTransfer | [
"b1db8ca7594a657826a1ccfb38a4e4eb102cce55"
] | [
"pyHeatTransfer/conduction.py"
] | [
"#I suppose the idea is that it gets these values from somewhere and takes off.\r\n#Regardless of where those values come from.\r\n\r\nimport os\r\nimport os.path as op\r\nimport sys\r\nimport numpy as np\r\nimport matplotlib as mpl\r\nimport matplotlib.pyplot as plt\r\nimport CoolProp.CoolProp as cp\r\nimport coll... | [
[
"matplotlib.pyplot.clabel",
"numpy.meshgrid",
"numpy.arange",
"matplotlib.pyplot.contour",
"numpy.zeros_like",
"matplotlib.pyplot.grid",
"numpy.interp",
"matplotlib.pyplot.xlabel",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
pranavsb/RL_smart_grid | [
"b23b407d3c873171d9a2af6d5a0104a7bcadc6cd"
] | [
"model/DynamicPricing.py"
] | [
"from Environment import Environment\nfrom QTableAgent import QTableAgent\nimport time, os\nimport numpy as np\nimport pickle\nfrom Utils import get_battery_reward_factor\n\nSOURCE_DEMAND_STATE = 'demand'\nSOURCE_SMART_LOADS = True\nSOURCE_LEARNING_RATE = 0.03\nSOURCE_DISCOUNT_FACTOR = 0.95\nSOURCE_NUM_LOADS = 10\n... | [
[
"numpy.mean"
]
] |
ssriblo/ionic-smarthome-test-1 | [
"060bc247e0b8295d6cd869d90b364756515cfc19"
] | [
"python-opcua/timetable_parser.py"
] | [
"import numpy as np\nimport sys\nimport json\n\nclass DataParserTT(object):\n def __init__(self):\n pass\n # Let convert from string to json: \n # \n\n def timetableParser(self, str):\n# ob = self.obj\n a = [None]*16\n print(f\"\\n\\nstr type\", type(str), str) ... | [
[
"numpy.packbits"
]
] |
QuMuLab/PDKB-Planning | [
"61a96c006b606aa051b2c7c9b5bfc9b6473d2a4d"
] | [
"pdkb/test/aamas.py"
] | [
"\nimport sys, random, time\n\nfrom pdkb.kd45 import *\nfrom pdkb.indexed_kd45 import *\nfrom pdkb.pinf import *\nfrom pdkb.rml import *\nfrom pdkb.test.utils import random_pdkb, random_rml, write_file, append_file\n\nTYPE = 'normal'\nNUM_PDKBS = 10\nQUERIES_PER_PDKB = 10\n\nif 'small' == TYPE:\n AGENTS = (2,3)\... | [
[
"numpy.log",
"numpy.arange",
"matplotlib.lines.Line2D",
"matplotlib.ticker.MaxNLocator",
"numpy.ravel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
PKUxxz/simp-detr | [
"c83846b1b6fc0e396e268dcfef278e162cf231c5"
] | [
"models/main.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport argparse\nimport datetime\nimport json\nimport random\nimport sys\nimport time\nfrom pathlib import Path\n\nimport numpy as np\nimport torch\nfrom torch.utils.data import DataLoader, DistributedSampler\n\nsys.path.append(\"../../../lib\... | [
[
"torch.utils.data.DistributedSampler",
"numpy.random.seed",
"torch.load",
"torch.manual_seed",
"torch.utils.data.SequentialSampler",
"torch.utils.data.DataLoader",
"torch.utils.data.RandomSampler",
"torch.optim.AdamW",
"torch.save",
"torch.nn.parallel.DistributedDataParalle... |
goitom/eemeter | [
"bb05d5b776546858f8f3a8d3a95bec202728d9f0"
] | [
"tests/test_segmentation.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\n\n Copyright 2018 Open Energy Efficiency, Inc.\n\n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n\n http://www.apac... | [
[
"numpy.linspace",
"pandas.DataFrame",
"pandas.date_range"
]
] |
Alhassan20/mealpy | [
"7ed365c5c495ad1c1e066662c90159b3d5e9b8e3"
] | [
"mealpy/bio_based/VCS.py"
] | [
"#!/usr/bin/env python\n# ------------------------------------------------------------------------------------------------------%\n# Created by \"Thieu Nguyen\" at 22:07, 11/04/2020 %\n# ... | [
[
"numpy.abs",
"numpy.random.uniform",
"numpy.random.normal",
"numpy.mean",
"numpy.log1p",
"numpy.sum"
]
] |
patrickltobing/shallow-wavenet | [
"a7348805825e47a24e3ad0e759cecfe85284ba9f"
] | [
"src/bin/feature_extract.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n# Copyright 2019 Patrick Lumban Tobing (Nagoya University)\n# based on PyTorch implementation for WaveNet vocoder by Tomoki Hayashi (Nagoya University)\n# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)\n\nfrom __future__ import division\nfrom __future__ ... | [
[
"numpy.log",
"numpy.expand_dims",
"numpy.pad",
"numpy.arange",
"numpy.set_printoptions",
"numpy.concatenate",
"scipy.interpolate.interp1d",
"numpy.float32",
"scipy.signal.lfilter",
"numpy.array",
"numpy.array_split",
"numpy.where",
"scipy.signal.firwin"
]
] |
yfletberliac/ray | [
"a77d9c228a6891b304e789ba2758a4cbfdb75ec0"
] | [
"python/ray/tune/test/trial_scheduler_test.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport random\nimport unittest\nimport numpy as np\n\nimport ray\nfrom ray.tune.schedulers import (HyperBandScheduler, AsyncHyperBandScheduler,\n PopulationBasedTraining... | [
[
"numpy.ceil"
]
] |
cclauss/xmodaler | [
"3e128a816876988c5fb07d842fde4a140e699dde"
] | [
"xmodaler/utils/colormap.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n\n\"\"\"\nAn awesome colormap for really neat visualizations.\nCopied from Detectron, and removed gray colors.\n\"\"\"\n\nimport numpy as np\n\n__all__ = [\"colormap\", \"random_color\"]\n\n# fmt: off\n# RGB:\n_COLORS = np.array(\n [\n 0.000, 0.447, 0.7... | [
[
"numpy.array"
]
] |
Roxot/AEVNMT | [
"5ebc6ec76b2c891ab76a5584a15e735145fdc43b"
] | [
"nmt/joint/csimplejoint.py"
] | [
"\"\"\"\n:Authors: - Bryan Eikema\n\"\"\"\n\nimport tensorflow as tf\n\nimport nmt.utils.misc_utils as utils\n\nfrom . import DSimpleJointModel\nfrom nmt import model_helper\nfrom .utils import language_model\nfrom nmt.utils.gaussianhelper import GaussianHelper\nfrom nmt.utils.amt_utils import enrich_embeddings_wit... | [
[
"tensorflow.cond",
"tensorflow.nn.dynamic_rnn",
"tensorflow.contrib.distributions.matrix_diag_transform",
"tensorflow.contrib.rnn.GRUCell",
"tensorflow.reduce_sum",
"tensorflow.summary.scalar",
"tensorflow.contrib.distributions.MultivariateNormalDiag",
"tensorflow.layers.dense",
... |
asappinc/emergent_comms_negotiation | [
"19ad405dcb83a3a521b6e1752cec075b69aa164b"
] | [
"nets.py"
] | [
"import torch\nfrom torch import nn, autograd\nfrom torch.autograd import Variable\nimport torch.nn.functional as F\n\n\nclass NumberSequenceEncoder(nn.Module):\n def __init__(self, num_values, embedding_size=100):\n \"\"\"\n eg for values 0,1,2,3,4,5, num_values will be: 6\n for 0,1,..,9 nu... | [
[
"torch.nn.functional.softmax",
"torch.cat",
"torch.nn.Embedding",
"torch.multinomial",
"torch.nn.LSTMCell",
"torch.nn.Linear",
"torch.nn.functional.sigmoid",
"torch.nn.functional.relu",
"torch.bernoulli",
"torch.autograd.Variable"
]
] |
varunsingh251/Indian-Sign-Language-Recognition | [
"40604e5c0a2a9b6310e26c0fa31b4f4f1c30de45"
] | [
"Bag of Features/preprocessing_surf.py"
] | [
"import numpy as np\nimport cv2\nimport os\nimport csv\nimport sklearn.metrics as sm\nfrom surf_image_processing import func,func2\nfrom sklearn.cluster import MiniBatchKMeans\nfrom sklearn.svm import SVC\nfrom sklearn.grid_search import GridSearchCV\nimport random\nimport warnings\nimport pickle\nfrom sklearn.naiv... | [
[
"sklearn.neural_network.MLPClassifier",
"sklearn.naive_bayes.GaussianNB",
"sklearn.linear_model.LogisticRegression",
"numpy.random.choice",
"sklearn.metrics.precision_score",
"sklearn.neighbors.KNeighborsClassifier",
"numpy.bincount",
"sklearn.svm.SVC",
"sklearn.metrics.f1_scor... |
davidastephens/zipline | [
"1da206df936bb8125913bae9fc182fd4f611a691"
] | [
"zipline/algorithm.py"
] | [
"#\n# Copyright 2013 Quantopian, Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or... | [
[
"numpy.allclose",
"pandas.DataFrame",
"numpy.datetime64"
]
] |
redhood-97/sms.ai | [
"8b787e3f678003826e36e233d966c7108989354c"
] | [
"spam.py"
] | [
"\nimport os, csv, re, nltk\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\nfrom sklearn import preprocessing\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransformer\... | [
[
"sklearn.model_selection.train_test_split",
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.naive_bayes.BernoulliNB",
"numpy.array",
"sklearn.preprocessing.LabelEncoder"
]
] |
DrFargo/Starship-Simulation | [
"ff1c30cd8227c7041357a1e2da2fcb34ab06a757"
] | [
"src/base.py"
] | [
"## Author DrFargo\r\n## Created: 2021-02-07\r\n## Latest update: 2021-02-12\r\n\r\nimport matplotlib\r\nfrom mpl_toolkits.mplot3d import Axes3D\r\nimport numpy as np\r\nimport scipy.linalg as la\r\nimport matplotlib.pyplot as plt\r\n\r\nclass starshipSimulation:\r\n def parameters(self, g, lox, engines):\r\n ... | [
[
"numpy.max",
"matplotlib.pyplot.show",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure"
]
] |
roshan19041/Causal-Discovery | [
"900cfc94d9fc3ff3d75366b00bda3acd044ed638",
"900cfc94d9fc3ff3d75366b00bda3acd044ed638"
] | [
"src/Loss.py",
"src/OrientationModels.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Jun 23 18:59:20 2019\n\n@author: roshanprakash\n\"\"\"\nimport tensorflow as tf\n\ndef compute_loss(generated_data, observed_data):\n \"\"\"\n Computes the Maximum Mean Discrepancy between generated data and observational data.\n \n ... | [
[
"tensorflow.transpose",
"tensorflow.concat",
"tensorflow.constant",
"tensorflow.shape",
"tensorflow.scalar_mul",
"tensorflow.ones",
"tensorflow.square"
],
[
"numpy.random.get_state",
"tensorflow.concat",
"sklearn.model_selection.ShuffleSplit",
"sklearn.tree.Decision... |
shivammehta007/NLPinEnglishLearning | [
"ae869d868e39df9b1787134ba6e964acd385dd2e"
] | [
"classifier/train.py"
] | [
"\"\"\"\nTraining script for the model\n\"\"\"\nimport argparse\nimport logging\nimport os\nimport time\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom tqdm.auto import tqdm\n\nfrom config.hyperparameters import (\n BATCH_SIZE,\n BIDIRECTION,\n DROPOUT,\n EMBEDDING_DIM,\n EP... | [
[
"torch.nn.CrossEntropyLoss",
"torch.load",
"torch.zeros"
]
] |
JoshMend/prebotc-graph-model | [
"4002e51ab965be366b30c2a6d900ac288fa41245"
] | [
"postprocessing_preBotBot/doPost.py"
] | [
"#!/usr/bin/env python\n'''\nThis file does all the post processing for a given mat file at once. This includes: \n\n1) Deleting Transient\n2)Binning the spikes \n3)Filter spikes using gaussian distribution \n4)Using butterworth filter to remove high frequency signals to smooth \n5)Finds Phase Lag and Population Co... | [
[
"numpy.sqrt",
"numpy.linspace",
"numpy.asarray",
"numpy.isneginf",
"numpy.mean",
"numpy.nanmean",
"numpy.nanstd",
"numpy.where",
"numpy.square",
"numpy.hstack",
"numpy.pad",
"numpy.arange",
"numpy.ceil",
"numpy.std",
"numpy.diff",
"numpy.zeros",
... |
RammySekham/Data-Engineering | [
"eec1020defe9c54403f6a80ba91fc071ed22b727"
] | [
"DataModelling_PostgreSQL/etl.py"
] | [
"import os\nimport glob\nimport psycopg2\nimport pandas as pd\nimport settings\nfrom sql_queries import *\n\n\ndef process_song_file(cur, filepath):\n \"\"\"\n process the json song file to insert song record into SQL table\n \"\"\"\n \n # open song file\n df = pd.read_json(filepath, lines=True)\n... | [
[
"pandas.to_datetime",
"pandas.Timestamp",
"pandas.read_json",
"pandas.DataFrame"
]
] |
dvhg/tvm | [
"288e9ef41d7884cea3d868d6d2bbb672c058757b"
] | [
"python/tvm/testing.py"
] | [
"# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); y... | [
[
"numpy.abs",
"numpy.isfinite",
"numpy.argwhere",
"numpy.all",
"numpy.asanyarray",
"numpy.zeros_like",
"numpy.prod",
"numpy.testing.assert_allclose",
"numpy.unravel_index",
"numpy.sum"
]
] |
kyuhyoung/yolact | [
"98fc78e963264d2ec18cf1b85de7a328abcd6e96"
] | [
"train.py"
] | [
"from data import *\nfrom utils.augmentations import SSDAugmentation, BaseTransform\nfrom utils.functions import MovingAverage, SavePath\nfrom utils.logger import Log\nfrom utils import timer\nfrom layers.modules import MultiBoxLoss\nfrom yolact import Yolact\nimport os\nimport sys\nimport time\nimport math, random... | [
[
"torch.set_default_tensor_type",
"torch.zeros",
"torch.utils.data.DataLoader",
"torch.isfinite",
"torch.no_grad",
"torch.cuda.is_available",
"torch.stack",
"torch.cuda.device_count"
]
] |
HenrikJantti/xFELTOR | [
"321fe73ce28fa590baedabc0aa13c5ba50a32dff"
] | [
"xfeltor/load.py"
] | [
"import xarray as xr\nimport numpy as np\nfrom typing import Union\nimport json\n\n\ndef open_feltordataset(\n datapath: str = \"./*.nc\",\n chunks: Union[int, dict] = None,\n restart_indices: bool = False,\n probes: bool = False,\n **kwargs: dict,\n) -> xr.Dataset:\n \"\"\"Loads FELTOR output int... | [
[
"numpy.reshape",
"numpy.unique"
]
] |
alexchungio/under-water-detect | [
"312672ccbe5e31ca21dffab26e1438ea190f3e5a"
] | [
"docs/check_and_draw_box.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n#------------------------------------------------------\n# @ File : check_and_draw_box.py\n# @ Description: \n# @ Author : Alex Chung\n# @ Contact : yonganzhong@outlook.com\n# @ License : Copyright (c) 2017-2018\n# @ Time : 2021/1/26 下午2:43\n# ... | [
[
"numpy.array",
"matplotlib.font_manager.FontProperties",
"numpy.floor"
]
] |
UKPLab/tacl2018-preference-convincing | [
"65eb1cd3bf76f8068889880e0f80178e790350ce"
] | [
"python/analysis/habernal_comparison/analyse_features.py"
] | [
"'''\nCreated on 1 Jun 2017\n\nLoad a set of feature lengthscales from a good run with 'both' types of features. \nSort them by lengthscale.\nPlot the distribution.\n\nIdentify which type of feature they are: add colours or markers to the plot.\n\nProvide a zoomed-in variant for the best 25 features.\n\n@author: si... | [
[
"matplotlib.pyplot.title",
"numpy.unique",
"numpy.min",
"numpy.arange",
"matplotlib.pyplot.savefig",
"numpy.argwhere",
"numpy.concatenate",
"numpy.max",
"matplotlib.pyplot.ylabel",
"numpy.fromstring",
"matplotlib.rcParams.update",
"numpy.savetxt",
"numpy.argsort... |
bibekuchiha/dataquest | [
"c7d8a2966fe2eee864442a59d64309033ea9993e"
] | [
"5. Probability and Statistics/statistics-intermediate/The Mode-307.py"
] | [
"## 1. Introduction ##\n\nimport pandas as pd\n\nhouses = pd.read_table('AmesHousing_1.txt')\nprint(houses[['Land Slope','Roof Style','Kitchen AbvGr']])\n\nscale_land = 'ordinal'\n\nscale_roof = 'nominal'\n\nkitchen_variable = 'discrete'\n\n\n## 2. The Mode for Ordinal Variables ##\n\ndef mode(array):\n counts ... | [
[
"pandas.read_table",
"pandas.interval_range",
"pandas.Series",
"matplotlib.pyplot.legend"
]
] |
swkokr/FetchPickAndPlace_HER_DDPG | [
"8378b53dac922cffeff8e2bdabca69cf6fd8bd54"
] | [
"baselines/her/ddpg.py"
] | [
"from collections import OrderedDict\n\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.contrib.staging import StagingArea\n\nfrom baselines import logger\nfrom baselines.her.util import (\n import_function, store_args, flatten_grads, transitions_in_episode_batch, convert_episode_to_batch_major)\nfr... | [
[
"numpy.random.randn",
"tensorflow.boolean_mask",
"numpy.clip",
"tensorflow.get_collection",
"tensorflow.stop_gradient",
"tensorflow.square",
"numpy.load",
"numpy.zeros",
"tensorflow.placeholder",
"numpy.random.binomial",
"numpy.array",
"tensorflow.clip_by_value",
... |
devillove084/CollageDesign | [
"e2a85a8d15f82d1f72b754de04af78126eae9a1c"
] | [
"MLCtr/machineLearning/decision_tree.py"
] | [
"from __future__ import division, print_function\nimport numpy as np\nimport cupy\n\n\nfrom graduateutil import divide_on_feature, train_test_split, standardize, mean_squared_error\nfrom graduateutil import calculate_entropy, accuracy_score, calculate_variance\n\nclass DecisionNode():\n \"\"\"Class that represen... | [
[
"numpy.expand_dims",
"numpy.unique",
"numpy.concatenate",
"numpy.mean",
"numpy.shape"
]
] |
jcboyd/cyclegan-roi | [
"f0c80c6122d17406f5282f58ea09abaf2b70c388"
] | [
"src/utils.py"
] | [
"import numpy as np\nimport torch\nfrom torch.nn import UpsamplingNearest2d, UpsamplingBilinear2d\n\nfrom rectpack import newPacker\n\n\ndef get_mnist_canvas(images, labels, nb_classes=10, dim=128):\n\n canvas = -torch.ones((dim, dim))\n noise_canvas = torch.zeros((nb_classes, dim, dim))\n condition_canvas... | [
[
"torch.randint",
"torch.ones",
"torch.max",
"torch.cat",
"torch.zeros",
"torch.randn",
"torch.Tensor",
"numpy.clip",
"torch.nn.UpsamplingBilinear2d",
"numpy.random.randn",
"torch.nn.UpsamplingNearest2d"
]
] |
ireina7/gzsl-seg | [
"9aad220274b4a58b59f5da430f873b5dfc21e458"
] | [
"src/util/logging.py"
] | [
"import sys\nimport matplotlib.pyplot as plt\n\nfrom util.typing.basic import *\nfrom src.config import *\n\n\ndef show_figure_nonblocking() -> None:\n plt.show(block = False)\n plt.pause(0.001)\n #end show_figure_nonblocking\n\ndef show_figure_blocking() -> None:\n plt.show()\n #end show_figure_blocking\n\nde... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.show",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.figure"
]
] |
plenoi/EvoloPy | [
"7c943925b9a73ad671735493ce281b67d178dc7c"
] | [
"PSO.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun May 15 22:37:00 2016\n\n@author: Hossam Faris\n\"\"\"\n\nimport random\nimport numpy\nfrom colorama import Fore, Back, Style\nfrom solution import solution\nimport time\n\n\n\n\n\n\ndef PSO(objf,lb,ub,dim,PopSize,iters):\n\n # PSO parameters\n \n# dim=30\n# ... | [
[
"numpy.random.uniform",
"numpy.zeros",
"numpy.clip"
]
] |
esowc/DAAQS | [
"141b4d97edb319ab67d9f42a1aa54a4555829de2"
] | [
"DAAQS/utils/preprocess.py"
] | [
"import numpy as np\n\nfrom DAAQS.utils.misc import index_to_center\n\ndef temporal_average(c_data, o_data, index_lat, index_lon):\n\n ## Ideally CAMS data is time_step x 3 x 3\n ## And openaq_data is list of all stations in that 3x3 grid \n\n ## CAMS Data\n c_grid = c_data[:,index_lat-1:index_lat+2,ind... | [
[
"numpy.ravel",
"numpy.mean",
"numpy.stack"
]
] |
HolmesShuan/Location-aware-Upsampling-for-Semantic-Segmentation | [
"83822e86570bbff4ca721d80089b5d82f1958852"
] | [
"LaU-reg/experiments/segmentation/option.py"
] | [
"###########################################################################\n# Created by: Hang Zhang \n# Email: zhang.hang@rutgers.edu \n# Copyright (c) 2017\n###########################################################################\nimport argparse\n\nimport torch\n\nclass Options():\n def __init__(self):\n... | [
[
"torch.cuda.is_available"
]
] |
andreea-zaharia/flower | [
"c576f0118e5c3d7a7d774dc156fb4b6db194655d",
"c576f0118e5c3d7a7d774dc156fb4b6db194655d"
] | [
"examples/dp-sgd-mnist/server.py",
"baselines/flwr_baselines/publications/fedbn/convergence_rate/client.py"
] | [
"import argparse\nimport os\n\nimport tensorflow as tf\n\nimport flwr as fl\n\nimport common\n\n# Make TensorFlow logs less verbose\nos.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\"\n\n\ndef get_eval_fn(model):\n \"\"\"Return an evaluation function for server-side evaluation.\"\"\"\n\n # Load test data here to av... | [
[
"tensorflow.keras.losses.CategoricalCrossentropy",
"tensorflow.keras.datasets.mnist.load_data"
],
[
"torch.nn.CrossEntropyLoss",
"torch.max",
"torch.utils.data.DataLoader",
"torch.tensor",
"torch.no_grad",
"torch.cuda.is_available"
]
] |
RPGroup-PBoC/mwc_mutants | [
"35581602c35793fc8ec42c8aff37b8305c5e54e1"
] | [
"mut/flow.py"
] | [
"import numpy as np\nimport fcsparser\nimport pandas as pd\nfrom ._fit_bivariate_normal_AstroML import fit_bivariate_normal\nimport scipy.stats\n\n# #######################\n# Automated Gating\n# #######################\ndef fit_2D_gaussian(df, x_val='FSC-H', y_val='SSC-H', log=False):\n '''\n This function h... | [
[
"numpy.dot",
"numpy.linalg.inv",
"numpy.cos",
"pandas.DataFrame",
"numpy.sin",
"numpy.linalg.det",
"numpy.log10",
"numpy.array",
"numpy.sum"
]
] |
fkopsaf/OpenAeroStruct | [
"414bd76a7f14f1bd52d6dacc6694382d52e5fabc"
] | [
"openaerostruct/geometry/utils.py"
] | [
"from __future__ import print_function, division\r\nimport warnings\r\nimport numpy as np\r\nfrom numpy import cos, sin, tan\r\n\r\nfrom openaerostruct.geometry.CRM_definitions import get_crm_points\r\n\r\n\r\ndef rotate(mesh, theta_y, symmetry, rotate_x=True):\r\n \"\"\"\r\n Compute rotation matrices given m... | [
[
"numpy.linspace",
"numpy.einsum",
"numpy.arctan",
"numpy.vstack",
"numpy.concatenate",
"numpy.hstack",
"matplotlib.pyplot.tight_layout",
"numpy.sin",
"numpy.interp",
"matplotlib.pyplot.subplots_adjust",
"numpy.zeros",
"matplotlib.pyplot.figure",
"numpy.tan",
... |
keforres/PreREISE | [
"fcc111fdccc0626d3d34f1749a14035e47991043"
] | [
"prereise/gather/demanddata/eia/tests/test_get_eia_data.py"
] | [
"import getpass\nimport os\nfrom datetime import datetime\n\nimport pandas as pd\nimport pytest\n\nfrom prereise.gather.demanddata.eia import get_eia_data\n\n\n@pytest.mark.skip(reason=\"Need API key\")\ndef test_eia_download():\n \"\"\"Check data frame assembled from data download by API call from EIA. Test\n ... | [
[
"pandas.to_datetime"
]
] |
zegerk/gym-micropolis | [
"554bf41e9c4001140cdba90c5bbb3cc6bacf4c65"
] | [
"arguments.py"
] | [
"import argparse\n\nimport torch\n\n\ndef get_args():\n parser = argparse.ArgumentParser(description='RL')\n parser.add_argument('--algo', default='a2c',\n help='algorithm to use: a2c | ppo | acktr')\n parser.add_argument('--lr', type=float, default=7e-4,\n hel... | [
[
"torch.cuda.is_available"
]
] |
abecker99/Interpolation | [
"0527e6296c98b1c7f6cf512e614090f61754705d"
] | [
"TestingBisection.py"
] | [
"import numpy as np\n\n\ndef find_sign_change(f, step, a, b):\n x = a\n pairs = []\n while (x + step < b):\n if (f(x + step)/f(x) < 0):\n pairs.append([x, x+step])\n x += step\n return pairs\n\ndef bisect(f, pairs, tolerance):\n zeros = []\n for pair in pairs:\n mid... | [
[
"numpy.sin"
]
] |
wangxinxin08/Paddle | [
"1b0c5ef264b52a9d75f971216618ebbbbc7e5931"
] | [
"python/paddle/tensor/manipulation.py"
] | [
"# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless ... | [
[
"numpy.asscalar"
]
] |
BillyGareth/pyod | [
"7aeefcf65ceb0196434b7adb4fd706bfb404e4e2"
] | [
"pyod/test/test_xgbod.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport os\nimport sys\nfrom os import path\n\nimport unittest\n# noinspection PyProtectedMember\nfrom numpy.testing import assert_allclose\nfrom numpy.testing import assert_array_less\nfrom numpy.testing import ass... | [
[
"numpy.testing.assert_equal",
"sklearn.metrics.roc_auc_score",
"scipy.stats.rankdata",
"sklearn.model_selection.train_test_split",
"numpy.testing.assert_array_less",
"sklearn.base.clone",
"numpy.testing.assert_raises",
"sklearn.utils.validation.check_X_y"
]
] |
Asjidkalam/analytics-zoo | [
"0afa8437abc3e5cf5289d2cfde68b237a45f9d0d"
] | [
"pyzoo/zoo/tfpark/tf_optimizer.py"
] | [
"#\n# Copyright 2018 Analytics Zoo Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable ... | [
[
"tensorflow.shape",
"tensorflow.get_collection",
"tensorflow.keras.backend.get_session",
"tensorflow.keras.backend.learning_phase",
"tensorflow.assign",
"tensorflow.is_numeric_tensor",
"tensorflow.placeholder",
"tensorflow.identity",
"tensorflow.global_variables_initializer",
... |
tunbehaun273/crabmeyerpy | [
"d36fe3ed9b8591bb92bd9915996dd21d79fc4dad"
] | [
"crabmeyerpy/ssc.py"
] | [
"import yaml\nfrom scipy.special import kv # Bessel function\nfrom scipy.integrate import simps\nfrom scipy.interpolate import interp1d\n\n# imports to speed up integrations:\nfrom numpy import meshgrid, linspace, ones, zeros\nfrom numpy import log, exp, pi, sqrt, power, tan\n\n# import functions for photon fields... | [
[
"numpy.log",
"numpy.sqrt",
"numpy.meshgrid",
"numpy.linspace",
"numpy.power",
"numpy.tan",
"scipy.integrate.simps",
"numpy.exp",
"numpy.zeros"
]
] |
cvlab-stonybrook/BodyHands | [
"dcfe470f6fd31a048d4d17d4ae9a2a524538b380"
] | [
"bodyhands/utils/extend_utils_boxes.py"
] | [
"import torch\nfrom detectron2.structures import Boxes\n\ndef pairwise_intersection(boxes1: Boxes, boxes2: Boxes) -> torch.Tensor:\n\n boxes1, boxes2 = boxes1.tensor, boxes2.tensor\n width_height = torch.min(boxes1[:, None, 2:], boxes2[:, 2:]) - torch.max(\n boxes1[:, None, :2], boxes2[:, :2]\n ) #... | [
[
"torch.min",
"torch.max",
"torch.zeros"
]
] |
maxscheurer/pyscf | [
"162c37942289c0aec70e70ba1ea98ade3ec34da5"
] | [
"pyscf/lo/orth.py"
] | [
"#!/usr/bin/env python\n# Copyright 2014-2020 The PySCF Developers. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LIC... | [
[
"numpy.hstack",
"numpy.sqrt",
"numpy.einsum",
"numpy.eye",
"numpy.ones",
"numpy.linalg.det",
"numpy.linalg.cholesky",
"numpy.linalg.qr",
"numpy.argsort",
"numpy.zeros",
"numpy.where"
]
] |
diegoolano/biomedical_interpretable_entity_representations | [
"3c35f02ee8dd7ee0f2a23b0014e4b112beab6461"
] | [
"ier_model/run_et.py"
] | [
"#!/usr/bin/env python3\nimport argparse\nimport gc\nimport json\nimport numpy as np\nimport pickle\nimport random\nimport time\nimport torch\nimport torch.nn as nn\nfrom tqdm import tqdm\nfrom transformers import AdamW, get_linear_schedule_with_warmup\n\nimport transformer_constant\nimport transformer_data_utils\n... | [
[
"torch.distributed.init_process_group",
"numpy.random.seed",
"torch.load",
"torch.cuda.set_device",
"torch.manual_seed",
"torch.cuda.device_count",
"torch.distributed.barrier",
"torch.nn.Sigmoid",
"numpy.argmax",
"torch.cuda.is_available",
"torch.cuda.manual_seed_all",
... |
drewhayward/DFOL-VQA | [
"8c7d403bac560588ab3ac45774a3e4f71fbe9c90"
] | [
"src/nsvqa/nn/interpreter/batch_base_interpreter.py"
] | [
"# Copyright (c) Microsoft. All rights reserved.\n# Licensed under the MIT license. See LICENSE.md file\n# in the project root for full license information.\n\nimport torch\nimport torch.nn as nn\nimport os\n\nfrom operator import itemgetter\nfrom nsvqa.nn.interpreter import util\nfrom nsvqa.nn.interpreter.batch_ba... | [
[
"torch.cat",
"torch.tensor"
]
] |
weecology/albumentations | [
"cc8fbb6e2fcc4f6a4c87a29b6b0784391b0e2db4"
] | [
"tests/test_transforms.py"
] | [
"from functools import partial\n\nimport cv2\nimport numpy as np\nimport pytest\nimport random\n\nimport albumentations as A\nimport albumentations.augmentations.functional as F\nimport albumentations.augmentations.geometric.functional as FGeometric\n\nfrom torchvision.transforms import ColorJitter\nfrom PIL import... | [
[
"numpy.random.random",
"numpy.allclose",
"numpy.array_equal",
"numpy.random.seed",
"numpy.abs",
"numpy.unique",
"numpy.eye",
"numpy.arange",
"numpy.ones",
"numpy.all",
"numpy.testing.assert_almost_equal",
"numpy.testing.assert_array_equal",
"numpy.random.rand",
... |
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