repo_name stringlengths 8 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
jaryaman/ML_demos | [
"df270b58d35d1248079e4651988ded4074237bfc"
] | [
"Notebooks/utls.py"
] | [
"import matplotlib.pyplot as plt\nimport matplotlib as mpl\nimport numpy as np\nimport matplotlib.ticker\nfrom matplotlib.ticker import FormatStrFormatter\n\ndef reset_plots():\n plt.close('all')\n fontsize = 20\n legsize = 15\n plt.rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})\n pl... | [
[
"matplotlib.pyplot.rc",
"numpy.einsum",
"numpy.linalg.inv",
"numpy.linalg.det",
"matplotlib.ticker.FormatStrFormatter",
"matplotlib.rc",
"numpy.exp",
"matplotlib.pyplot.rcParams.update",
"matplotlib.rcParams.update",
"matplotlib.pyplot.close",
"numpy.sqrt"
]
] |
emtpb/dsch | [
"ed31b72a95e59335f338ae48bc0c7c0d011e889c"
] | [
"dsch/backends/inmem.py"
] | [
"\"\"\"dsch backend for in-memory data storage.\n\nThis backend stores all data in memory and cannot directly save to disk.\nFor temporary data that does not have to be stored, the in-memory backend\nprovides a clean way of data with dsch, without littering the workspace with\ntemporary files. Also, it can be used ... | [
[
"numpy.dtype"
]
] |
legaultmarc/pytorch-genotypes-dataloader | [
"0cb99f28cbfc5a2787d1d51f1c27e7e31dc23d05"
] | [
"pytorch_genotypes/vcf.py"
] | [
"from dataclasses import dataclass\nimport collections\nimport typing\nimport sqlite3\nimport os\n\nimport cyvcf2\nimport numpy as np\nimport torch\n\n\nVERBOSE = True\n\n\ndef set_verbose(b: bool):\n global VERBOSE\n VERBOSE = b\n\n\n@dataclass\nclass VCFChunk:\n chunk_id: int\n chrom: str\n start: ... | [
[
"torch.from_numpy",
"pandas.DataFrame",
"numpy.empty"
]
] |
rivinduw/ntf_estimation | [
"1c4bc7015971081dd880f00940c79776ad1ea63d"
] | [
"validate.py"
] | [
"#!/usr/bin/env python3 -u\n#!/usr/bin/env python3 -u\n# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport torch\n\nfrom fairseq import checkpoint_utils, options, progress_bar, u... | [
[
"torch.cuda.is_available"
]
] |
piotlinski/ssdir | [
"907b4f00a0747b7e774dc0a342d5a40c4d296fb6"
] | [
"pytorch_ssdir/modeling/encoder.py"
] | [
"\"\"\"SSDIR encoder.\"\"\"\nfrom copy import deepcopy\nfrom typing import List, Optional, Tuple\n\nimport torch\nimport torch.nn as nn\nfrom pytorch_ssd.modeling.model import SSD\n\nfrom pytorch_ssdir.modeling.depth import DepthEncoder\nfrom pytorch_ssdir.modeling.present import PresentEncoder\nfrom pytorch_ssdir.... | [
[
"torch.tensor",
"torch.full",
"torch.where",
"torch.cat",
"torch.gt"
]
] |
ZwEin27/digoie-annotation | [
"edf01770e26a78267045bba33a54aef3376fa63f"
] | [
"digoie/core/ml/classifier/mla/decision_tree.py"
] | [
"\nfrom sklearn import tree\n\n\nfrom digoie.core.ml.classifier.mla.base import MLAlgorithm\n\n\nclass MLDecisionTree(MLAlgorithm):\n\n # ML_NAME = DECISION_TREE\n\n def __init__(self, training_dataset, training_label):\n super(MLDecisionTree, self).__init__(training_dataset, training_label)\n\n def... | [
[
"sklearn.tree.DecisionTreeClassifier"
]
] |
sujitmandal/Sales-Forecasting | [
"9052a30f2e3a386eafe36de3e5f1b1205bc1fdf1"
] | [
"LoadModel.py"
] | [
"#Import required libraries\nimport os\nimport pandas as pd\nfrom tensorflow import keras\nimport matplotlib.pyplot as plt\n\n#Github: https://github.com/sujitmandal\n#This programe is create by Sujit Mandal\n\"\"\"\nGithub: https://github.com/sujitmandal\nPypi : https://pypi.org/user/sujitmandal/\nLinkedIn : https... | [
[
"matplotlib.pyplot.legend",
"tensorflow.keras.models.load_model",
"pandas.read_csv",
"matplotlib.pyplot.title",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel"
]
] |
dangilman/LenstronomyWrapper | [
"7c3bb68ab1f982432cd16d570854df50466491e9"
] | [
"lenstronomywrapper/LensData/lensed_quasar.py"
] | [
"import numpy as np\nfrom lenstronomy.PointSource.point_source import PointSource\nimport itertools\nfrom copy import deepcopy\n\nclass LensedQuasar(object):\n\n def __init__(self, x_image, y_image, mag, t_arrival=None):\n\n \"\"\"\n Data class for a quadruply-imaged quasar\n\n :param x_imag... | [
[
"numpy.array",
"numpy.argmin",
"numpy.ones_like"
]
] |
fangchao111/tensorpack | [
"87059de51331e540ca35eb295953ee16e3f59cee"
] | [
"examples/basics/cifar-convnet.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# File: cifar-convnet.py\n# Author: Yuxin Wu\nimport tensorflow as tf\nimport argparse\nimport os\n\nfrom tensorpack import *\nfrom tensorpack.tfutils.summary import *\nfrom tensorpack.dataflow import dataset\nfrom tensorpack.utils.gpu import get_num_gpu\n\n\"\"\"\nA... | [
[
"tensorflow.summary.scalar",
"tensorflow.placeholder",
"tensorflow.add_n",
"tensorflow.summary.image",
"tensorflow.nn.in_top_k",
"tensorflow.train.AdamOptimizer",
"tensorflow.reduce_mean",
"tensorflow.Graph",
"tensorflow.nn.sparse_softmax_cross_entropy_with_logits",
"tensor... |
zamlz/dlcampjeju2018-I2A-cube | [
"85ae7a2084ca490ea685ff3d30e82720fb58c0ea"
] | [
"misc/cube_gif_test.py"
] | [
"\nimport gym\nimport sys\nimport cube_gym\nimport time\nfrom common.multiprocessing_env import SubprocVecEnv\nimport tensorflow as tf\nimport matplotlib.pyplot as plt\nimport matplotlib.animation as animation\n\nfrom a2c import ActorCritic\nfrom policy import *\n\ndef env_fn():\n env = gym.make('cube-x3-v0')\n ... | [
[
"matplotlib.pyplot.figure",
"matplotlib.animation.ArtistAnimation",
"tensorflow.Session"
]
] |
sanzgiri/covid19_india | [
"3a530fb107446bdba54dc6581c45f15f590b0a1e"
] | [
"covid19_model.py"
] | [
"\nimport pandas as pd\nimport numpy as np\nfrom fbprophet import Prophet\nimport pickle\nimport math\nimport scipy.optimize as optim\nimport matplotlib.pyplot as plt\nfrom datetime import datetime, timedelta\n \nimport covid19_prepare_data as prepare_data\n\nimport logging\nlogging.getLogger('fbprophet').setLevel(... | [
[
"pandas.date_range",
"scipy.optimize.curve_fit",
"numpy.append",
"pandas.read_csv",
"pandas.DataFrame",
"numpy.exp",
"numpy.power",
"numpy.log",
"numpy.random.exponential",
"numpy.array"
]
] |
makart19/daal4py | [
"8264fe81c772478c5530f38077a129f027f3677d"
] | [
"daal4py/sklearn/decomposition/_pca_0_23.py"
] | [
"#\n#*******************************************************************************\n# Copyright 2014-2020 Intel Corporation\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# ... | [
[
"sklearn.utils.extmath.stable_cumsum",
"sklearn.utils.validation.check_is_fitted",
"numpy.empty",
"sklearn.decomposition._pca.svd_flip",
"numpy.searchsorted",
"scipy.sparse.issparse",
"sklearn.utils.check_array",
"numpy.linalg.svd",
"numpy.ravel",
"numpy.sqrt",
"sklearn... |
HenryDayHall/awkward-1.0 | [
"4a860e775502f9adb953524c35c5a2de8f7a3181"
] | [
"tests/test_0056b-partitioned-array-numba.py"
] | [
"# BSD 3-Clause License; see https://github.com/scikit-hep/awkward-1.0/blob/main/LICENSE\n\nfrom __future__ import absolute_import\n\nimport sys\n\nimport pytest # noqa: F401\nimport numpy as np # noqa: F401\nimport awkward as ak # noqa: F401\n\nnumba = pytest.importorskip(\"numba\")\n\nak_numba = pytest.importo... | [
[
"numpy.array"
]
] |
georgezywang/BFT-RLForensics | [
"014be0b57f4edf44ed9d933d23df836cb46d8714"
] | [
"src/utils/logging.py"
] | [
"\"\"\"\nCode adapted from https://github.com/TonghanWang/ROMA\n\"\"\"\n\nfrom collections import defaultdict\nimport logging\nimport numpy as np\nimport torch\n\n\nclass Logger:\n def __init__(self, console_logger):\n self.console_logger = console_logger\n\n self.use_tb = False\n self.use_s... | [
[
"numpy.mean"
]
] |
RickyMexx/DeepRL-LTLf | [
"24cb3ac49e5bb9e07c37644d7226201ccb2b59a4"
] | [
"ra-gym/ra_gym/envs/ra_env.py"
] | [
"import numpy as np\nimport gym\nfrom gym import spaces\nimport time\nclass RAEnv(gym.Env):\n\tmetadata = {\n\t\t'render.modes': ['rgb_array'],\n\t\t'video.frames_per_second': 50\n\t}\n\tdef __init__(self):\n\t\tself.action_space = spaces.Box(low=np.array([-1., -1.]), high=np.array([1., 1.]), dtype=np.float32)\n\t\... | [
[
"numpy.array",
"numpy.clip"
]
] |
ladsantos/blastoise | [
"30458f41c5432c97f71a54a73a89fa1193e28b38"
] | [
"sunburn/test_hst_observation.py"
] | [
"import numpy as np\nfrom . import hst_observation, spectroscopy\n\ndatasets = ['ld9m10ujq', 'ld9m10uyq']\nvisit1 = hst_observation.Visit(datasets, 'cos', prefix='data/')\n\nline_list = spectroscopy.COSFUVLineList(wavelength_shift=.0,\n range_factor=1.0).lines\n\ntr = 'Si III'... | [
[
"numpy.array"
]
] |
eltrompetero/coniii | [
"d698696c11e12a62fe3340eb2f4d3344145a96dd"
] | [
"coniii/ising_eqn/ising_eqn_2_sym.py"
] | [
"# MIT License\n# \n# Copyright (c) 2019 Edward D. Lee, Bryan C. Daniels\n# \n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitation the rig... | [
[
"numpy.array",
"numpy.exp",
"numpy.zeros",
"numpy.isnan"
]
] |
yashtailor/preprocessy | [
"015b4653ef064e3c4db5884aa1b6d1b098383055"
] | [
"tests/test_encode.py"
] | [
"from collections import Counter\n\nimport pandas as pd\nimport pytest\nfrom preprocessy.encoding import Encoder\n\nord_dict = {\"Profession\": {\"Student\": 1, \"Teacher\": 2, \"HOD\": 3}}\n\n\n# test for empty input\ndef test_empty_df():\n params = {\"target_label\": \"Price\", \"ord_dict\": ord_dict}\n wit... | [
[
"pandas.read_csv"
]
] |
hxri/mars | [
"f7864f00911883b94800b63856f0e57648d3d9b4"
] | [
"mars/tensor/arithmetic/tests/test_arithmetic.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# Copyright 1999-2021 Alibaba Group Holding Ltd.\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/li... | [
[
"scipy.sparse.random",
"numpy.empty",
"numpy.timedelta64",
"numpy.dtype",
"numpy.random.randn",
"numpy.arange",
"numpy.frexp",
"numpy.random.rand",
"numpy.negative",
"numpy.datetime64",
"numpy.array"
]
] |
kuke/models | [
"5d25e00c94943e50e64780a244136f88f13c0a88"
] | [
"fluid/PaddleCV/video/metrics/metrics_util.py"
] | [
"# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.\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 require... | [
[
"numpy.array"
]
] |
snap-stanford/GIB | [
"a5b625c38f65feda0413eba81b2ccf5dac8f1a98"
] | [
"experiments/GIB_node_exp.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\n\"\"\"Script for experiments with standard learning with GNNs (including GIB-GAT, GAT, GCN and other baselines.)\"\"\"\nimport argparse\nfrom copy import deepcopy\nimport datetime\nimport matplotlib.pylab as plt\nimport numpy as np\nimport pickle\nimport torc... | [
[
"numpy.ones",
"torch.manual_seed",
"numpy.linspace",
"numpy.random.seed"
]
] |
tdaylan/pcat | [
"b5ed1b88cd87baf8af8ab0f4f75d93dfe28cdbb9"
] | [
"pcat/main.py"
] | [
"# plotting\nimport matplotlib\nmatplotlib.use('agg')\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n# numpy\nimport numpy as np\n\n# scipy\nimport scipy as sp\nimport scipy.interpolate\nfrom scipy.special import erfinv, erf\nfrom scipy.stats import poisson as pss\nimport scipy.fftpack\nimport scipy.spa... | [
[
"numpy.ones",
"scipy.interpolate.interp1d",
"numpy.diff",
"numpy.arctanh",
"matplotlib.pyplot.subplots_adjust",
"numpy.stack",
"matplotlib.pyplot.xkcd",
"numpy.histogramdd",
"matplotlib.pyplot.figtext",
"matplotlib.pyplot.savefig",
"numpy.arccos",
"numpy.histogram2d... |
dataprofessor/st-write | [
"5cbd8608824a9c16560c8746393292c17ce6a792"
] | [
"streamlit_app.py"
] | [
"import numpy as np\nimport altair as alt\nimport pandas as pd\nimport streamlit as st\n\nst.header('st.write')\n\n# Example 1\nst.subheader('Display text')\nst.write('Hello, *World!* :sunglasses:')\n\n# Example 2\nst.subheader('Display numbers')\nst.write(1234)\n\n# Example 3\nst.subheader('Display DataFrame')\ndf... | [
[
"pandas.DataFrame",
"numpy.random.randn"
]
] |
wangwei2009/speechbrain | [
"ebbac4561a9c9101786e0ab0b1105017eb655fc8"
] | [
"recipes/windnoise/model/CRN.py"
] | [
"\"\"\"\nsingle channel speech enhancement for wind noise reduction.\n\nrefer to\n \"A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement\" .\n\nAuthors\n * Wang Wei 2021\n\"\"\"\nimport torch\nimport torch.nn as nn\n\nclass CNN_Block(torch.nn.Module):\n def __init__(self,\n in_cha... | [
[
"torch.nn.BatchNorm2d",
"torch.rand",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.RNN",
"torch.zeros",
"torch.nn.ELU",
"torch.cat",
"torch.nn.ConvTranspose2d"
]
] |
ajavadia/qiskit-sdk-py | [
"a59e8e6be1793197e19998c1f7dcfc45e6f2f3af"
] | [
"qiskit/quantum_info/states/densitymatrix.py"
] | [
"# This code is part of Qiskit.\n#\n# (C) Copyright IBM 2017, 2019.\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.\n#\n# Any modificatio... | [
[
"numpy.allclose",
"numpy.zeros",
"numpy.array2string",
"numpy.dot",
"numpy.conj",
"numpy.reshape",
"numpy.isclose",
"numpy.asarray",
"numpy.argmax",
"numpy.trace",
"numpy.product",
"numpy.kron",
"numpy.linalg.eig"
]
] |
alanhdu/metrics | [
"b168272eaf1ff08b9447e75338753f9c2abf0859"
] | [
"tests/classification/test_inputs.py"
] | [
"# Copyright The PyTorch Lightning team.\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... | [
[
"torch.manual_seed",
"torch.rand",
"torch.tensor",
"torch.randint"
]
] |
Naouali/holbertonschool-machine_learning | [
"60b7d50cd385bdf9c1372b6004308eec408d2670"
] | [
"supervised_learning/0x05-regularization/3-l2_reg_create_layer.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\nL2 regularization layer\n\"\"\"\n\n\nimport tensorflow as tf\n\n\ndef l2_reg_create_layer(prev, n, activation, lambtha):\n \"\"\"\n l2 regularization layer\n \"\"\"\n reg = tf.contrib.layers.l2_regularizer(scale=lambtha)\n w = tf.contrib.layers.variance_scaling_initia... | [
[
"tensorflow.layers.Dense",
"tensorflow.contrib.layers.l2_regularizer",
"tensorflow.contrib.layers.variance_scaling_initializer"
]
] |
d-v-b/napari | [
"f0ab04af8bf3854325af1e44b5214c4710cab980"
] | [
"napari/layers/shapes/_shapes_models/rectangle.py"
] | [
"import numpy as np\nfrom .shape import Shape\nfrom .._shapes_utils import find_corners, rectangle_to_box\n\n\nclass Rectangle(Shape):\n \"\"\"Class for a single rectangle\n\n Parameters\n ----------\n data : (4, D) or (2, 2) array\n Either a (2, 2) array specifying the two corners of an axis ali... | [
[
"numpy.array",
"numpy.max",
"numpy.min"
]
] |
banayoyo/yoolact | [
"9dd0ee01ce5d5d238f89fa0886e24627ec3ffbe6"
] | [
"eval.py"
] | [
"from data import COCODetection, get_label_map, MEANS, COLORS\nfrom yolact import Yolact\nfrom utils.augmentations import BaseTransform, FastBaseTransform, Resize\nfrom utils.functions import MovingAverage, ProgressBar\nfrom layers.box_utils import jaccard, center_size\nfrom utils import timer\nfrom utils.functions... | [
[
"torch.sum",
"numpy.save",
"torch.stack",
"numpy.searchsorted",
"torch.no_grad",
"matplotlib.pyplot.title",
"torch.set_default_tensor_type",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.show",
"torch.from_numpy",
"numpy.array",
"torch.Tensor"
]
] |
devinllu/dataprep | [
"d56861e5bed3c608cace74983f797dc729072d0a"
] | [
"dataprep/clean/clean_text.py"
] | [
"\"\"\"\nClean a DataFrame column containing text data.\n\"\"\"\nimport re\nimport string\nfrom functools import partial, update_wrapper\nfrom typing import Any, Callable, Dict, List, Optional, Set, Union\nfrom unicodedata import normalize\n\nimport dask.dataframe as dd\nimport numpy as np\nimport pandas as pd\n\nf... | [
[
"pandas.notna",
"pandas.isna"
]
] |
xiye17/transformers | [
"924989e70d9425e3276ca76f148a0fcd4bbd58cf"
] | [
"src/transformers/training_args.py"
] | [
"import dataclasses\nimport json\nimport os\nimport warnings\nfrom dataclasses import dataclass, field\nfrom enum import Enum\nfrom typing import Any, Dict, List, Optional, Tuple\n\nfrom .file_utils import cached_property, is_torch_available, is_torch_tpu_available, torch_required\nfrom .trainer_utils import Evalua... | [
[
"torch.distributed.init_process_group",
"torch.cuda.device_count",
"torch.cuda.is_available",
"torch.device",
"torch.cuda.set_device"
]
] |
LB0828/EmbedKGQA_Learning | [
"db4bb5a91f99db8a36efdf3ae4f668d60ba018d3"
] | [
"KGQA/RoBERTa/pruning_model.py"
] | [
"import torch\nimport torch\nimport torch.nn as nn\nimport torch.nn.utils\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\nfrom torch.nn.utils.rnn import pad_packed_sequence, pack_padded_sequence\nimport torch.nn.functional as F\nimport numpy as np\nfrom torch.nn.init import xavier_normal_\nfr... | [
[
"torch.nn.LogSoftmax",
"torch.nn.BCELoss",
"torch.sigmoid",
"torch.nn.Dropout"
]
] |
Labyrinthine-Unreal/lbrys_sub | [
"c1a5b7d168d107b4820d5c40fbcfc895bf124f86"
] | [
"model.py"
] | [
"# Importing the libraries\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport pickle\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.preprocessing import MinMaxScaler as mini\nfrom sklearn.model_selection import train_test_split\n# Importing the libraries\nimport nump... | [
[
"pandas.read_csv",
"sklearn.linear_model.LinearRegression",
"sklearn.model_selection.train_test_split"
]
] |
uncle-ben-z/cloudutils | [
"c1b5a751af3f9c322963be40f5a77dd282ef4257"
] | [
"projection.py"
] | [
"import os\nimport cv2\nimport numpy as np\nimport xml.etree.ElementTree as ET\nimport matplotlib\n\nmatplotlib.use(\"TkAgg\")\nfrom matplotlib import pyplot as plt\n\n\n# cf. nas/repos/cloud-colorizer/projection/... and repos/projection_utils/...\n\nclass View:\n \"\"\" View class representing the extrinsics an... | [
[
"numpy.sqrt",
"numpy.eye",
"numpy.append",
"numpy.array",
"numpy.linalg.inv",
"numpy.arccos",
"numpy.int32",
"matplotlib.use",
"numpy.dot",
"numpy.linalg.norm"
]
] |
sagarpahwa/qiskit-aer | [
"77e40c8d99fd0490d85285e96f87e4905017b646"
] | [
"qiskit/providers/aer/pulse/controllers/unitary_controller.py"
] | [
"# -*- coding: utf-8 -*-\n\n# This code is part of Qiskit.\n#\n# (C) Copyright IBM 2018, 2019, 2020.\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apache.org/licenses/L... | [
[
"numpy.zeros",
"numpy.exp",
"numpy.random.RandomState",
"scipy.linalg.blas.get_blas_funcs",
"numpy.iinfo",
"numpy.array"
]
] |
luqidndx/PyWake | [
"3d046eb14c4597de49ac2fee3771b8e0e68820ad"
] | [
"py_wake/tests/test_blockage_models/test_selfsimilarity.py"
] | [
"import pytest\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom py_wake.deficit_models import SelfSimilarityDeficit\nfrom py_wake.deficit_models.no_wake import NoWakeDeficit\nfrom py_wake.deficit_models.noj import NOJDeficit\nfrom py_wake.examples.data import hornsrev1\nfrom py_wake.examples.data.hornsr... | [
[
"numpy.sqrt",
"numpy.interp",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.title",
"numpy.arange",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"numpy.array",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.contourf",
"numpy.round",
"matplotlib.pyplot.xlabel... |
NikolaySokolov152/Unet_multiclass | [
"d07f6809b422519097560b07f67d0f139e718381"
] | [
"splitImages.py"
] | [
"import skimage.io as io\nimport numpy as np\nimport os\n\ndef to_0_255_format_img(in_img):\n max_val = in_img[:,:].max()\n if max_val <= 1:\n out_img = np.round(in_img * 255)\n return out_img.astype(np.uint8)\n else:\n return in_img\n\ndef to_0_1_format_img(in_img):\n max_val = in_im... | [
[
"numpy.round",
"numpy.ones",
"numpy.zeros"
]
] |
llv22/baal_tf2.4_mac | [
"6eed225f8b57e61d8d16b1868ea655384c566700"
] | [
"experiments/vgg_mcdropout_cifar10.py"
] | [
"import argparse\nimport random\nfrom copy import deepcopy\n\nimport torch\nimport torch.backends\nfrom torch import optim\nfrom torch.hub import load_state_dict_from_url\nfrom torch.nn import CrossEntropyLoss\nfrom torchvision import datasets\nfrom torchvision.models import vgg16\nfrom torchvision.transforms impor... | [
[
"torch.manual_seed",
"torch.cuda.is_available",
"torch.hub.load_state_dict_from_url",
"torch.nn.CrossEntropyLoss"
]
] |
KristianHolsheimer/keras-gym | [
"0296ddcc8685e1ce732c3173caaa0fd25af9ef58"
] | [
"keras_gym/policies/value_based.py"
] | [
"import numpy as np\n\nfrom ..base.mixins import RandomStateMixin\nfrom ..policies.base import BasePolicy\nfrom ..utils import argmax\n\n\n__all__ = (\n 'EpsilonGreedy',\n # 'BoltzmannPolicy', #TODO: implement\n)\n\n\nclass EpsilonGreedy(BasePolicy, RandomStateMixin):\n \"\"\"\n Value-based policy to s... | [
[
"numpy.ones"
]
] |
Lab41/attalos | [
"43b5b61f6b2a2b5f4a49ef1286b4577f1bf4e140"
] | [
"attalos/evaluation/evaluation.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport math\nimport numpy as np\nimport scipy as sp\n\nfrom sklearn import metrics\n\nclass Evaluation(object):\n \"\"\"\n Assumes:\n predicted: matrix of label prediction confidence [tria... | [
[
"sklearn.metrics.coverage_error",
"numpy.empty",
"numpy.zeros",
"numpy.argsort",
"numpy.abs",
"numpy.copy",
"numpy.count_nonzero",
"sklearn.metrics.f1_score",
"sklearn.metrics.roc_auc_score",
"sklearn.metrics.precision_score",
"sklearn.metrics.label_ranking_average_prec... |
syang1993/OpenNMT-tf | [
"eaeb2970c14dd6a6e1b9d261e15a645b589852e8"
] | [
"opennmt/decoders/rnn_decoder.py"
] | [
"\"\"\"Define RNN-based decoders.\"\"\"\n\nimport inspect\n\nimport tensorflow as tf\n\nfrom tensorflow.python.estimator.util import fn_args\n\nfrom opennmt.decoders.decoder import Decoder, logits_to_cum_log_probs, build_output_layer\nfrom opennmt.utils.cell import build_cell\n\n\nclass RNNDecoder(Decoder):\n \"\"... | [
[
"tensorflow.summary.scalar",
"tensorflow.logging.warn",
"tensorflow.shape",
"tensorflow.contrib.seq2seq.BasicDecoder",
"tensorflow.contrib.seq2seq.tile_batch",
"tensorflow.contrib.seq2seq.TrainingHelper",
"tensorflow.contrib.seq2seq.GreedyEmbeddingHelper",
"tensorflow.expand_dims",... |
alexfmsu/pyquantum | [
"78b09987cbfecf549e67b919bb5cb2046b21ad44"
] | [
"plot_M_diff.py"
] | [
"from PyQuantum.Tools.CSV import *\nimport plotly.graph_objs as go\nimport numpy as np\nfrom PyQuantum.Tools.PlotBuilder2D import *\n\n# data = []\n\n# data.append(go.Scatter(\n# x=[1, 2, 3],\n# y=[4, 5, 6],\n# name=\"w_0['title']\",\n# ))\n\n# plot_builder = PlotBuilder2D({\n# 'title': 'M[p<sub>sin... | [
[
"numpy.array",
"numpy.sum",
"numpy.arange",
"numpy.round"
]
] |
lucaslehnert/rewardpredictive | [
"273da5a2566a263678159ed81dfb202b180a45a1"
] | [
"rewardpredictive/mdp.py"
] | [
"#\n# Copyright (c) 2020 Lucas Lehnert <lucas_lehnert@brown.edu>\n#\n# This source code is licensed under an MIT license found in the LICENSE file in the root directory of this project.\n#\nfrom itertools import product, combinations\n\nimport numpy as np\nimport rlutils as rl\nfrom rlutils.environment.gridworld im... | [
[
"numpy.random.uniform",
"numpy.sum",
"numpy.matmul",
"numpy.zeros",
"numpy.exp",
"numpy.arange",
"numpy.where",
"numpy.max",
"numpy.shape",
"numpy.min",
"numpy.isnan",
"numpy.linalg.pinv",
"numpy.concatenate"
]
] |
keithyipkw/InSync | [
"3744b45f31f713de2dfc8c30507e67db96915e07"
] | [
"benchmark/overhead.py"
] | [
"import sys\nimport numpy as np\nimport pandas as pd\n\ndef main():\n df = pd.read_csv(sys.argv[1], names=[\"Method\", \"Time\"])\n print(df.groupby(\"Method\").describe().to_csv())\n\n\nif __name__ == \"__main__\":\n main()"
] | [
[
"pandas.read_csv"
]
] |
ProjectBlackFalcon/DatBot | [
"8b2cc64af78757b832d8bc6a1373fb74b7a4316f"
] | [
"ModelTests/test_Pathfinder.py"
] | [
"from Pathfinder import PathFinder\nimport numpy as np\nimport winsound\n\n\ndef generate_map_collage():\n maps_coords = pf.get_maps_coords()\n maps = []\n shape = (abs(end[1] - start[1]) + 1, abs(end[0] - start[0]) + 1)\n counter = 0\n for coord in maps_coords:\n map_infos = pf.llf.coord_fetc... | [
[
"numpy.array"
]
] |
krunt/lean_transformer | [
"90abdb87bb08566eaba0a45bc29ec6a3220333ac"
] | [
"tests/test_utils.py"
] | [
"import pytest\nimport torch\nimport torch.nn.functional as F\nfrom lean_transformer.utils import pad_to_multiple, GELU\nimport numpy as np\n\n\n@pytest.mark.forked\ndef test_pad_to_multiple():\n x = torch.randn(3, 3)\n\n assert pad_to_multiple(x, multiple=3, dims=0) is x\n assert pad_to_multiple(x, multip... | [
[
"torch.randn",
"torch.linspace"
]
] |
cvxgrp/sccf | [
"3c5f65e1a6df1a1b9cf58b60dd2b41f5c46be42e"
] | [
"test.py"
] | [
"import unittest\n\nimport sccf\nimport cvxpy as cp\nimport numpy as np\n\n\nclass TestMinExpression(unittest.TestCase):\n def test(self):\n x = cp.Variable(10)\n x.value = np.zeros(10)\n expr = cp.sum_squares(x)\n with self.assertRaises(AssertionError):\n sccf.minimum(-exp... | [
[
"numpy.ones",
"numpy.zeros"
]
] |
YuliusDennyPrabowo/pandas | [
"b74e2ce0f63f616474edc310897a67d501a9e32d"
] | [
"pandas/tests/arrays/test_datetimelike.py"
] | [
"# -*- coding: utf-8 -*-\nimport numpy as np\nimport pytest\n\nimport pandas.compat as compat\n\nimport pandas as pd\nfrom pandas.core.arrays import DatetimeArray, PeriodArray, TimedeltaArray\nimport pandas.util.testing as tm\n\n\n# TODO: more freq variants\n@pytest.fixture(params=['D', 'B', 'W', 'M', 'Q', 'Y'])\nd... | [
[
"numpy.random.shuffle",
"pandas.date_range",
"pandas.util.testing.assert_numpy_array_equal",
"pandas.Period",
"pandas.core.arrays.DatetimeArray",
"pandas.Timestamp.now",
"pandas.core.arrays.TimedeltaArray",
"pandas.core.arrays.PeriodArray",
"pandas.TimedeltaIndex",
"pandas.... |
zhanzheng8585/biprop | [
"ce6a364c8323f102bd41ebb332e1e841ec78c79d"
] | [
"models/resnet_BinAct.py"
] | [
"import torch.nn as nn\n\nfrom utils.builder import get_builder\nfrom args import args\n\n\nfrom collections import OrderedDict\n\n# Binary activation function with gradient estimator\nimport torch\nclass F_BinAct(torch.autograd.Function):\n @staticmethod\n def forward(ctx, inp):\n # Save input for backward\n ... | [
[
"torch.nn.MaxPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.Linear",
"torch.nn.AdaptiveAvgPool2d",
"torch.sign",
"torch.nn.Conv2d",
"torch.abs",
"torch.nn.Sequential",
"torch.clamp"
]
] |
lioncorpo/sfm.lion-judge-corporation | [
"95fb11bff263c3faab62269cc907eec18b527e22"
] | [
"opensfm/pairs_selection.py"
] | [
"import logging\nfrom collections import defaultdict\n\nimport numpy as np\nimport scipy.spatial as spatial\nfrom opensfm import bow, context, feature_loader, vlad\nfrom opensfm.dataset import DataSetBase\n\n\nlogger = logging.getLogger(__name__)\n\n\ndef has_gps_info(exif):\n return (\n exif\n and... | [
[
"numpy.fabs",
"scipy.spatial.cKDTree",
"numpy.argsort"
]
] |
NickKaparinos/Kaggle-Dogs-vs.-Cats-Redux | [
"8bc0296648f7e376c97dba3eeadf5872e7499656"
] | [
"main_pytorch.py"
] | [
"\"\"\"\nNick Kaparinos\nDogs vs. Cats\nKaggle Competition\nGrid Search using pytorch\n\"\"\"\n\nimport pandas as pd\nfrom random import seed\nfrom utilities import *\nfrom torch.utils.data import DataLoader\nfrom torchvision.models import vgg16\nfrom torch.utils.tensorboard import SummaryWriter\nimport torch\nimpo... | [
[
"torch.utils.data.DataLoader",
"torch.manual_seed",
"pandas.set_option",
"torch.cuda.is_available",
"torch.utils.tensorboard.SummaryWriter",
"torch.nn.BCELoss",
"torch.Tensor"
]
] |
Alexzsh/chinese_short_text_classification | [
"de16359b4c83cc18c0478c33e211cc3f85b8e36b"
] | [
"data/pre_process.py"
] | [
"# coding: utf-8\n\nimport sys\nfrom collections import Counter\nimport gc\nimport numpy as np\nimport tensorflow.contrib.keras as kr\nimport jieba\nimport pandas as pd\nimport re\nif sys.version_info[0] > 2:\n is_py3 = True\nelse:\n #reload(sys)\n sys.setdefaultencoding(\"utf-8\")\n is_py3 = False\ndef... | [
[
"pandas.read_csv",
"tensorflow.contrib.keras.utils.to_categorical",
"numpy.arange",
"tensorflow.contrib.keras.preprocessing.sequence.pad_sequences"
]
] |
mosaic-group/PyLibAPR | [
"4b5af50c26b4770c460460f9491bd840af2537da"
] | [
"demo/apr_iteration_demo.py"
] | [
"import pyapr\nimport numpy as np\nfrom time import time\n\n\ndef main():\n \"\"\"\n This demo implements a piecewise constant reconstruction using the wrapped PyLinearIterator. The Python reconstruction\n is timed and compared to the internal C++ version.\n\n Note: The current Python reconstruction is ... | [
[
"numpy.array",
"numpy.allclose",
"numpy.empty"
]
] |
khanfarhan10/gvae | [
"a14fa36c5249373235c7cf339e26328791c6c8c4"
] | [
"ops.py"
] | [
"import math\nimport numpy as np\nimport tensorflow as tf\n\nfrom tensorflow.python.framework import ops\nfrom tensorflow.contrib import slim\nfrom tensorflow.contrib import layers as tflayers\n\n@slim.add_arg_scope\ndef conv2d_transpose(\n inputs,\n out_shape,\n kernel_size=(5, 5),\n st... | [
[
"tensorflow.reduce_logsumexp",
"tensorflow.summary.scalar",
"tensorflow.reshape",
"tensorflow.contrib.slim.conv2d",
"tensorflow.variable_scope",
"tensorflow.matmul",
"tensorflow.name_scope",
"numpy.log",
"tensorflow.reduce_sum",
"tensorflow.summary.histogram",
"numpy.ey... |
pranav-dahiya/Twitter | [
"f38d546d2dda69acb03abb2347e316578fc28a38"
] | [
"supervised.py"
] | [
"import pandas as pd\nimport numpy as np\nfrom sklearn.svm import SVC, SVR\nfrom sklearn.model_selection import cross_validate\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.metrics import make_scorer\n\n\ndef cf_matrix_00(y_true, y_pred):\n ... | [
[
"numpy.sum",
"sklearn.svm.SVC",
"sklearn.svm.SVR",
"sklearn.feature_extraction.text.TfidfVectorizer",
"pandas.read_json",
"sklearn.metrics.confusion_matrix",
"sklearn.metrics.make_scorer",
"numpy.std",
"sklearn.model_selection.cross_validate",
"numpy.mean"
]
] |
demokratiefabrik/fabrikApi | [
"a56bb57d59a5e7cbbeeb77889c02d82f2a04c682"
] | [
"fabrikApi/plugins/CIR/views/plots/ARCHIV/beeplot.py"
] | [
"from io import StringIO\nimport matplotlib.pyplot as p\nimport numpy as np\nimport pandas as pd\nimport seaborn as s\nimport mplcursors\nimport matplotlib.collections\nfrom mpld3 import plugins\n\n# %matplotlib widget\n\nf = StringIO()\n\n# pip install matplotlib seaborn\n\ndef beeplot():\n\n # dataset\n # i... | [
[
"numpy.random.exponential",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots"
]
] |
sina-moammar/2021-neuroscience-project | [
"6e7fa52e0496361d20253945633edaab79734e0b"
] | [
"tests/test_cortex_model.py"
] | [
"import numpy as np\nimport networkit as nk\nfrom collections import defaultdict\nfrom typing import Dict\nimport pytest\n\nfrom cortex_model import cortex_model\n\n\ndef default_params() -> Dict[str, any]:\n size = 4\n graph = nk.graph.Graph(size, directed=True)\n graph.addEdge(0, 1)\n graph.addEdge(0,... | [
[
"numpy.sqrt",
"numpy.array_equiv",
"numpy.zeros",
"numpy.float32",
"numpy.uint16",
"numpy.exp",
"numpy.arange",
"numpy.all",
"numpy.random.rand",
"numpy.array_equal",
"numpy.array",
"numpy.random.randint"
]
] |
andresgreen-byte/Laboratorio-1--Inversion-de-Capital | [
"8a4707301d19c3826c31026c4077930bcd6a8182"
] | [
"env/Lib/site-packages/pandas/tests/series/methods/test_isin.py"
] | [
"import numpy as np\nimport pytest\n\nimport pandas as pd\nfrom pandas import (\n Series,\n date_range,\n)\nimport pandas._testing as tm\nfrom pandas.core.arrays import PeriodArray\n\n\nclass TestSeriesIsIn:\n def test_isin(self):\n s = Series([\"A\", \"B\", \"C\", \"a\", \"B\", \"B\", \"A\", \"C\"]... | [
[
"pandas._testing.assert_numpy_array_equal",
"pandas.Series",
"pandas.date_range",
"pandas.core.arrays.PeriodArray._simple_new",
"numpy.asarray",
"pandas._testing.assert_series_equal",
"pandas.core.algorithms.isin",
"numpy.datetime64",
"numpy.array"
]
] |
Ynakatsuka/birdclef-2021 | [
"d7cf7b39e3164a75547ee50cc9a29bd5ed4c29bd"
] | [
"src/kvt/models/layers/pooling.py"
] | [
"import torch\nfrom torch import nn\nfrom torch.nn import functional as F\nfrom torch.nn.parameter import Parameter\n\nAdaptiveAvgPool2d = nn.AdaptiveAvgPool2d\n\n\nclass AdaptiveConcatPool2d(nn.Module):\n def __init__(self, sz=None):\n super().__init__()\n sz = sz or (1, 1)\n self.ap = nn.A... | [
[
"torch.nn.AdaptiveAvgPool2d",
"torch.ones",
"torch.nn.AdaptiveMaxPool2d"
]
] |
FudanYuan/faultLocalization | [
"5133ee5af48f7d4c8ba05ef9a545139a38f417da"
] | [
"hotspot/code/localization.py"
] | [
"## coding: utf-8\nimport pandas as pd\nimport numpy as np\nimport time\nimport math\nfrom tqdm import tqdm\nimport matplotlib.pyplot as plt\n\nfrom package.utils import KPIPoint\nfrom package.utils import KPISet\nfrom package.utils import Transformer\nfrom package.HotSpot import HotSpot\n\ndef valid():\n #### 加... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
SerafinH/triplet_loss_kws | [
"a203f6063517fd5236c9df9ce28318fec7afb141"
] | [
"loss/triplet.py"
] | [
"import torch\nimport torch.nn.functional as F\nfrom nemo.backends.pytorch.nm import LossNM\nfrom nemo.core.neural_types import *\nfrom nemo.utils.decorators import add_port_docs\n\n\nclass OnlineTripletLoss(LossNM):\n \"\"\"\n Online Triplet loss\n Takes a batch of embeddings and corresponding labels.\n ... | [
[
"torch.flatten",
"torch.nn.functional.relu"
]
] |
jardinier/phlox | [
"f312569ec983b5f27c75846b34debc04fe7bdf98"
] | [
"PhloxAR/dc1394/dc_cam.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom __future__ import division, print_function\nfrom __future__ import absolute_import, unicode_literals\nfrom ctypes import byref, POINTER, c_char, c_uint32, c_float, c_int\nfrom numpy import fromstring, ndarray\nfrom threading import Thread, Lock, Condition\nfrom Queue import Queue\n\... | [
[
"numpy.fromstring"
]
] |
cdrhim/KoELECTRA | [
"19fd5f2b698b297a8cf1e2c0c3995c93509298f3"
] | [
"pretrain/build_pretraining_dataset.py"
] | [
"# coding=utf-8\n# Copyright 2020 The Google Research 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 requ... | [
[
"tensorflow.compat.v1.io.TFRecordWriter",
"tensorflow.compat.v1.io.gfile.listdir",
"tensorflow.compat.v1.io.gfile.GFile"
]
] |
crisdeodates/AI-depthai-experiments | [
"dd8a24db648338b8e4d7c9ec6c860985f9aeb56d"
] | [
"gen2-blur-faces/main.py"
] | [
"import blobconverter\nimport cv2\nimport depthai as dai\nimport numpy as np\n\nclass HostSync:\n def __init__(self):\n self.arrays = {}\n def add_msg(self, name, msg):\n if not name in self.arrays:\n self.arrays[name] = []\n self.arrays[name].append(msg)\n def get_msgs(self... | [
[
"numpy.zeros"
]
] |
vbgupta/DS440-Transfer-Learning-Address-Sustainability-Issues | [
"b6ef51fa1e4253e92b8179b1953c43e6b983b944"
] | [
"models/src/modeling/main.py"
] | [
"#-----Main Model File----#\n\nclass Model:\n\n def __init__(self, data):\n\n self.data = data\n\n def preprocess(self):\n\n self.data['License_Class'] = self.data['License_Class'].astype('category').cat.codes\n train = self.data[self.data['year'] != 2021]\n test = self.data[self.d... | [
[
"sklearn.ensemble.RandomForestRegressor",
"tensorflow.keras.optimizers.SGD",
"tensorflow.keras.layers.Dense",
"tensorflow.random.set_seed",
"sklearn.decomposition.PCA"
]
] |
notadamking/ta-modin | [
"e0c2e3b36d21b05798f5ffbb4d30d1898573a375"
] | [
"dev/generate_image_bb.py"
] | [
"import numpy as np\nimport platform\n\nif platform.system() == 'Windows':\n import pandas as pd\nelse:\n import modin.pandas as pd\n\nimport matplotlib.pyplot as plt\n\nimport sys\nsys.path.append(\"..\") # Adds higher directory to python modules path.\nfrom ta import *\n\n# Load data\ndf = pd.read_csv('../... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.savefig"
]
] |
RicoFio/5294BIDA6Y_tech_tutorial | [
"a9f966d6022f5d7941100a377d7f9c5face71f00"
] | [
"api/api.py"
] | [
"### IMPORTS ###\nimport os\nimport time\nfrom typing import (\n List,\n Dict,\n Union,\n)\nimport threading\nimport uuid\n\nimport numpy as np\nfrom pydantic import (\n BaseModel,\n validator,\n Field,\n)\n\nfrom fastapi import (\n FastAPI,\n Response,\n status,\n)\nfrom fastapi.middlewa... | [
[
"numpy.array",
"numpy.linalg.lstsq"
]
] |
Fortuz/MARG_project | [
"a83aa84ac001ff7cad93934a3ea8bbd05901d992"
] | [
"modules/UR_module/src/scheduler.py"
] | [
"#encoding: utf-8\r\nimport numpy as np\r\nfrom RTDEhandler import RTDEhandler\r\nfrom URconnect import URCom\r\nimport socket\r\nfrom threading import Thread\r\nimport time\r\nfrom queue import Queue\r\n\r\nclass scheduler:\r\n def __init__(self, robotip):\r\n self.robot=URCom(robotip,30002)\r\n s... | [
[
"numpy.round",
"numpy.array"
]
] |
oslokommune/dataplatform-batch-jobs | [
"c6f2a31d86676dae62bbdcd8822c6f9320c9aec2"
] | [
"tests/s3_access_log_aggregator/test_aggregate_to_db.py"
] | [
"from io import BytesIO\nfrom unittest.mock import Mock\n\nimport pandas as pd\nfrom fastparquet import write as pq_write\n\nfrom batch.models import DatasetRetrievals\nfrom batch.s3_access_log_aggregator.aggregate_to_db import (\n count_get_requests,\n aggregate_to_db,\n read_parquet,\n)\n\n\ndef test_rea... | [
[
"pandas.read_csv",
"pandas.DataFrame",
"pandas.read_parquet"
]
] |
tkon3/pytorch-optimizer | [
"e5578453b79143331c30fd76b08721b45dce86d3"
] | [
"torch_optimizer/adamod.py"
] | [
"import math\nimport torch\nfrom torch.optim.optimizer import Optimizer\n\nfrom .types import Betas2, OptFloat, OptLossClosure, Params\n\n\n__all__ = ('AdaMod',)\n\n\nclass AdaMod(Optimizer):\n r\"\"\"Implements AccSGD algorithm.\n\n It has been proposed in `Adaptive and Momental Bounds for Adaptive\n Lear... | [
[
"torch.min",
"torch.full_like",
"torch.zeros_like"
]
] |
alienkrieg/peal | [
"66b48c0f3973c7f3bceece64dc6e896c9802e29a"
] | [
"peal/operators/reproduction.py"
] | [
"\"\"\"Module that provides operators that reproduce individuals.\"\"\"\n\nimport numpy as np\n\nfrom peal.community import Community\nfrom peal.operators.iteration import (\n SingleIteration,\n RandomStraightIteration,\n)\nfrom peal.operators.operator import Operator\nfrom peal.population import Population\n... | [
[
"numpy.arange",
"numpy.zeros_like",
"numpy.random.shuffle"
]
] |
ChisenZhang/Curve-Text-Detector | [
"2126a660d3baf3e84a76e77352597576519c35a2"
] | [
"lib/fast_rcnn/config.py"
] | [
"# --------------------------------------------------------\n# Fast R-CNN\n# Copyright (c) 2015 Microsoft\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Ross Girshick\n# --------------------------------------------------------\n\n\"\"\"Fast R-CNN config system.\n\nThis file specifies defa... | [
[
"numpy.array"
]
] |
TayaV60/SimpleHTR | [
"5c9e3488e7a581c3f953270802d8a25d6c5493b9"
] | [
"src/model.py"
] | [
"import os\nimport sys\nfrom typing import List, Tuple\n\nimport numpy as np\nimport tensorflow as tf\n\nfrom dataloader_iam import Batch\n\n# Disable eager mode\ntf.compat.v1.disable_eager_execution()\n\n\nclass DecoderType:\n \"\"\"CTC decoder types.\"\"\"\n BestPath = 0\n BeamSearch = 1\n WordBeamSea... | [
[
"tensorflow.random.truncated_normal",
"tensorflow.compat.v1.train.AdamOptimizer",
"tensorflow.squeeze",
"tensorflow.compat.v1.nn.rnn_cell.MultiRNNCell",
"tensorflow.concat",
"tensorflow.compat.v1.layers.batch_normalization",
"tensorflow.nn.softmax",
"tensorflow.nn.ctc_greedy_decode... |
zilishen/gala | [
"5415c817a7cc5e1a5086217332466ffc7af16ab3"
] | [
"gala/dynamics/tests/test_actionangle_staeckel.py"
] | [
"# Third-party\nfrom astropy.constants import G\nimport astropy.units as u\nimport numpy as np\nimport pytest\n\n# gala\nfrom gala.dynamics import get_staeckel_fudge_delta, PhaseSpacePosition\nimport gala.potential as gp\nfrom gala.units import galactic\nfrom .helpers import HAS_GALPY\n\n\n@pytest.mark.skipif(not H... | [
[
"numpy.allclose",
"numpy.random.default_rng"
]
] |
choltz95/SMPyBandits | [
"04bc2b2bf10f8043afa5cac6589c191745735d9c"
] | [
"SMPyBandits/Experiment/Seznec19a_Fig2/main.py"
] | [
"\"\"\"\nauthor : Julien SEZNEC\nProduce the experiment and record the relevant data to reproduce Figure 2 of [Seznec et al., 2019a]\nReference: [Seznec et al., 2019a]\nRotting bandits are not harder than stochastic ones;\nJulien Seznec, Andrea Locatelli, Alexandra Carpentier, Alessandro Lazaric, Michal Valko ;\n... | [
[
"numpy.sqrt",
"numpy.save",
"numpy.abs"
]
] |
linghtiin/test | [
"4718dfbe33768fa6e623e27933199cbb21d440ae"
] | [
"Python/Courese/Linear Regression/Logistic Regression.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Mon Feb 18 02:43:27 2019\r\n\r\n@author: z\r\n\"\"\"\r\n\r\nimport numpy as np\r\nimport scipy.stats as ss\r\nimport matplotlib.pyplot as plt\r\n\r\nfrom sklearn.linear_model import LogisticRegression\r\nfrom sklearn.model_selection import train_test_split\r\n\r\nh =... | [
[
"numpy.vstack",
"scipy.stats.norm.rvs",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.xlabel",
"numpy.repeat",
"matplotlib.pyplot.title",
"numpy.arange",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.colorbar",
"sklearn.linear_model.Logist... |
mxz96102/ray | [
"02768ad707f615a47a4a5f28ae333c25012baaa1"
] | [
"python/ray/tests/test_advanced_3.py"
] | [
"# coding: utf-8\nimport glob\nimport logging\nimport os\nimport json\nimport sys\nimport socket\nimport time\n\nimport numpy as np\nimport pickle\nimport pytest\n\nimport ray\nimport ray.ray_constants as ray_constants\nimport ray.cluster_utils\nimport ray.test_utils\nfrom ray import resource_spec\nimport setprocti... | [
[
"numpy.ones",
"numpy.zeros"
]
] |
majdabd/nilearn | [
"55e3f26dbd9fc6e89516e5f37e8aae23ec6086a9"
] | [
"nilearn/tests/test_signal.py"
] | [
"\"\"\"\nTest the signals module\n\"\"\"\n# Author: Gael Varoquaux, Alexandre Abraham\n# License: simplified BSD\n\nimport os.path\nimport warnings\nfrom distutils.version import LooseVersion\n\nimport numpy as np\nimport pytest\n\n# Use nisignal here to avoid name collisions (using nilearn.signal is\n# not possibl... | [
[
"numpy.ones",
"numpy.sum",
"numpy.isclose",
"numpy.copy",
"numpy.random.RandomState",
"numpy.dstack",
"numpy.isfinite",
"numpy.testing.assert_almost_equal",
"numpy.vstack",
"numpy.ndarray",
"numpy.isnan",
"numpy.identity",
"numpy.linspace",
"numpy.mean",
... |
Nickwasused/DNoiSe | [
"40cb7129ee4a9a5d74cb0f673144d5302bf8ef27"
] | [
"dnoise.py"
] | [
"#!/usr/bin/python3\n# -*- coding: utf-8 -*-\n\nimport datetime\nimport json\nimport os\nimport random\nimport sqlite3\nimport sys\nimport time\nimport urllib\nfrom importlib import reload\n\nimport dns.resolver\nimport pandas\nimport requests\n\nreload(sys)\n\n######################################################... | [
[
"pandas.read_csv"
]
] |
ptarau/pypro | [
"9e542ed7d70454f75ce531c918a912aa85a4cd6e"
] | [
"bak/ndb.py"
] | [
"from .db import *\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.neural_network import MLPClassifier\n\n#from answerer import tsv2mat\nimport numpy as np\nfrom sklearn.preprocessing import OneHotEncoder\n\n# it might work better for larger databases\ndef_learner=MLPClassifier(\n hidden_layer_s... | [
[
"numpy.array",
"sklearn.neural_network.MLPClassifier"
]
] |
sahithyaravi1493/modAL | [
"39336f21cd872974cf2f34c1c79012ca30a96819"
] | [
"tests/example_tests/shape_learning.py"
] | [
"\"\"\"\nLearning the shape of an object using uncertainty based sampling.\n\nIn this example, we will demonstrate the use of ActiveLearner with\nthe scikit-learn implementation of the kNN classifier algorithm.\n\"\"\"\n\nimport numpy as np\nfrom copy import deepcopy\nfrom sklearn.ensemble import RandomForestClassi... | [
[
"numpy.zeros",
"numpy.random.seed",
"numpy.asarray",
"numpy.delete",
"sklearn.ensemble.RandomForestClassifier"
]
] |
abhishreeshetty/IDL-CrossViz | [
"729baabd146980839544e274387bd5adb4640d03"
] | [
"datasets/prepare_thing_sem_from_lvis.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\nimport functools\nimport multiprocessing as mp\nimport os\nimport time\n\nimport numpy as np\nfrom lvis import LVIS\nfrom pycocotools import mask as maskUtils\n\n\ndef annToRLE(ann, img_size):\n h, w = img_size\n segm = ann['segmentati... | [
[
"numpy.zeros",
"numpy.savez_compressed"
]
] |
BierOne/VQA-AttReg | [
"dc160fcc54b0a18cf321dfcff133761b5a8f5975"
] | [
"visuals/visual.py"
] | [
"import sys\n# from visualize.visual import *\nimport h5py\nimport json\nimport random\nimport cv2\nimport numpy as np\nimport os\nfrom skimage.transform import resize\nfrom skimage.filters import gaussian\nimport matplotlib.pyplot as plt\nfrom scipy import misc\n\n\nfont=cv2.FONT_HERSHEY_SIMPLEX\nfalse_results_dir... | [
[
"numpy.sum",
"matplotlib.pyplot.get_cmap",
"numpy.delete"
]
] |
hermannbene/BeamTomography | [
"39eae19c54128f27eb90a2717b1876768d730f29"
] | [
"model2D.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom loadData import gauss, loadAndPrepareInput\nfrom scipy import signal\nfrom generateTestData import loadTestData\nfrom plot import plotProjections2D, plotError2D\nfrom scipy.optimize import curve_fit\n\ndef growthRate(X, x, bins, y... | [
[
"numpy.save",
"numpy.sum",
"numpy.array",
"numpy.interp",
"numpy.argwhere",
"numpy.histogram",
"numpy.diff",
"scipy.optimize.curve_fit",
"numpy.cos",
"numpy.argmax",
"scipy.signal.convolve",
"numpy.hstack",
"numpy.max",
"numpy.min",
"numpy.random.normal"... |
ROUASAAD/PCOS | [
"21bc2698f9893484eb6ee9af5f108134948465c6"
] | [
"run.py"
] | [
"import flask\nimport pandas as pd\nimport io\nfrom flask import request, jsonify, render_template, send_from_directory\nimport warnings\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.svm import SVC\n####################################################\n# Flask Config\napp ... | [
[
"pandas.read_csv",
"sklearn.svm.SVC",
"sklearn.model_selection.train_test_split"
]
] |
Dieblitzen/SAMAR-Project | [
"8b3655a3d3ef17c61eb5e0acf411c8b191bd917e"
] | [
"pixor/smooth_L1.py"
] | [
"import tensorflow as tf\nimport numpy as np\n\nTILE_SIZE = 224\n\"\"\" Implements smooth L1 on each dimension. Erases loss for negative pixel locations. \"\"\"\ndef smooth_L1(box_labels, box_preds, class_labels):\n\tdifference = tf.subtract(box_preds, box_labels)\n\tresult = tf.where(tf.abs(difference) < 1, tf.mul... | [
[
"tensorflow.reshape",
"tensorflow.subtract",
"tensorflow.multiply",
"tensorflow.reduce_mean",
"tensorflow.InteractiveSession",
"tensorflow.abs",
"tensorflow.convert_to_tensor",
"tensorflow.clip_by_value",
"tensorflow.square"
]
] |
Roxbili/kws-demo | [
"7e0674f1407572fc8f148293b23fa20a5164bc5e"
] | [
"zynq/tkinter_kws.py"
] | [
"#-*- encoding: utf-8 -*-\n\nimport time\nimport argparse\nimport numpy as np\nimport tkinter as tk \nfrom tkinter.ttk import Label\nfrom kws_ps_pl import BRAM, PSPLTalk, InputDataToBram\nfrom multiprocessing import Process\n\nclass timeRecorder(object):\n def __init__(self):\n self.total_time = 0.\n s... | [
[
"numpy.load",
"numpy.argmax"
]
] |
AmaljithCf/RacingRobot | [
"6885ddb37407dff15845d29f641bc7c39279b216"
] | [
"ros_nodes/serial_adapter.py"
] | [
"import threading\nimport time\n\nimport numpy as np\nimport rospy\nfrom std_msgs.msg import Int16, Int8\nfrom robust_serial import write_order, Order\nfrom robust_serial.threads import CommandThread, ListenerThread\nfrom robust_serial.utils import open_serial_port, CustomQueue\n\nfrom constants import BAUDRATE, N_... | [
[
"numpy.clip"
]
] |
ESOGU-SRLAB/opendr | [
"f2eb5a6d7a070d3534d470987c3abc69eec53905"
] | [
"projects/data_generation/synthetic_multi_view_facial_image_generation/algorithm/Rotate_and_Render/train.py"
] | [
"import torch.multiprocessing as multiprocessing\nimport sys\nfrom options.train_options import TrainOptions\nimport data\nfrom trainers import create_trainer\nfrom util.iter_counter import IterationCounter\nfrom util.visualizer import Visualizer\nfrom torch.multiprocessing import Queue\nfrom data.data_utils import... | [
[
"torch.multiprocessing.set_start_method",
"torch.multiprocessing.Queue"
]
] |
umautobots/osp | [
"d055f1c846f907445186b9dea7da2d4dca4790a6"
] | [
"misc/social_forces/fieldofview.py"
] | [
"\"\"\"\nhttps://github.com/svenkreiss/socialforce\nField of view computation.\n\"\"\"\nimport numpy as np\n\n\nclass FieldOfView(object):\n \"\"\"Compute field of view prefactors.\n\n The field of view angle twophi is given in degrees.\n out_of_view_factor is C in the paper.\n \"\"\"\n def __init__(... | [
[
"numpy.ones_like",
"numpy.cos",
"numpy.fill_diagonal",
"numpy.einsum",
"numpy.linalg.norm"
]
] |
yanchunyu71/relational-networks-paddle | [
"40fcd55c00d890136f52504d8b73f76ddef6e159"
] | [
"main.py"
] | [
"from __future__ import print_function\nimport argparse\nimport os\nimport pickle\nimport random\nimport numpy as np\nimport csv\n\n\nimport paddle\nfrom model import RN, CNN_MLP\n\n\n# Training settings\nparser = argparse.ArgumentParser(description='Paddle Relational-Network sort-of-CLVR Example')\nparser.add_argu... | [
[
"numpy.swapaxes",
"numpy.asarray"
]
] |
niva83/mocalum | [
"5c387197127a81ecc5cda2e4d79b5a33e9f8e31f"
] | [
"mocalum/persistance.py"
] | [
"\"\"\"This module contains a class which stores data created in the interaction\nwith mocalum.\n\"\"\"\nimport time\nfrom . import metadata\nimport numpy as np\nfrom numpy.linalg import inv as inv\nimport xarray as xr\nfrom tqdm import tqdm\nfrom .utils import sliding_window_slicing, bbox_pts_from_array, bbox_pts_... | [
[
"numpy.ceil",
"numpy.linalg.inv",
"numpy.copy",
"numpy.arange",
"numpy.max",
"numpy.min",
"numpy.array",
"numpy.full"
]
] |
PolSl-PBL-7/DragonEye | [
"13ba314809e62ec1118756a00453a7e175df4329"
] | [
"pipelines/training_pipeline.py"
] | [
"NAME = \"training_pipeline\"\n\n\ndef training_pipeline(\n pipeline_params: dict,\n compile_params: dict,\n model_params: dict,\n source_params: dict,\n training_params: dict,\n data_processing_pipeline_params:\n dict = None,\n versioner_params: dict = None,\n processor_params: dict = No... | [
[
"tensorflow.config.experimental.set_memory_growth",
"tensorflow.config.list_logical_devices",
"tensorflow.keras.callbacks.EarlyStopping",
"tensorflow.data.Dataset.zip",
"tensorflow.config.list_physical_devices"
]
] |
ubiquity6/MVSNet | [
"7dc026acb019d270e79de7be4a5cfcb33863127f"
] | [
"mvsnet/cnn_wrapper/network.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nCopyright 2019, Zixin Luo & Yao Yao, HKUST.\nCNN layer wrapper.\n\nPlease be noted that the center and scale paramter are disabled by default for all BN / GN layers\n\"\"\"\n\nfrom __future__ import print_function\n\nimport os\nimport sys\nimport numpy as np\nimport tensorflow as tf\... | [
[
"tensorflow.layers.conv2d",
"tensorflow.reshape",
"tensorflow.variable_scope",
"tensorflow.squeeze",
"tensorflow.concat",
"tensorflow.layers.average_pooling2d",
"tensorflow.nn.softmax",
"tensorflow.layers.conv3d_transpose",
"tensorflow.layers.flatten",
"tensorflow.ones_init... |
abcxs/polyrnn | [
"92eee689fe62585529deb1c44fbf1c889f414fa2"
] | [
"mmdet/models/utils/vertex_util.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom mmcv.cnn import ConvModule, xavier_init\nfrom mmcv.cnn.bricks import NonLocal2d\nfrom .builder import MODULE_UTIL\n\nclass Bottleneck(nn.Module):\n\n def __init__(self,\n in_channels,\n mid_channels,\n ... | [
[
"torch.randn",
"torch.nn.functional.adaptive_max_pool2d",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.tanh",
"torch.sigmoid",
"torch.cat",
"torch.nn.functional.interpolate"
]
] |
WdBlink/Teacher-Student-Faster-Rcnn | [
"df8085c61e334abb04bab5e8192de8cb4ce2b2af"
] | [
"ubteacher/data/datasets/builtin.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport os\nimport contextlib\nfrom detectron2.data import DatasetCatalog, MetadataCatalog\nfrom fvcore.common.timer import Timer\nfrom fvcore.common.file_io import PathManager\nimport io\nimport logging\nfrom detectron2.data.datasets.cityscape... | [
[
"numpy.loadtxt"
]
] |
mosesnah-shared/adaptive-control | [
"dc9504f1f2531a3ed2d16358f28024c4647a09e4"
] | [
"MuJoCo/run.py"
] | [
"\"\"\"\n\n# ============================================================================= #\n| Project: Adaptive Controller Example\n| Title: Python Controller File for Running the adaptive controller simulation\n| Author: Moses C. Nah\n| Email: [Moses] mosesnah@mit.edu\n| Creation... | [
[
"numpy.set_printoptions"
]
] |
GranScudetto/TensorflowExamples | [
"25e0f0f973febc8997b75eb512c22d2e85b0788a"
] | [
"classification/cifar10/cifar_models.py"
] | [
"\"\"\"\nSeparated File containing all different models implemented\n\nCreation Date: May 2020\nCreator: GranScudetto\n\"\"\"\nfrom tensorflow.keras.layers import Input, Conv2D, BatchNormalization, Activation, Dense\nfrom tensorflow.keras.layers import MaxPool2D, Concatenate, Flatten\nfrom tensorflow.keras import M... | [
[
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Concatenate",
"tensorflow.keras.Model",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.layers.BatchNormalization",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.layers.MaxPoo... |
pengnanchi/CPC_audio | [
"6900d49d441df90679cdd4ba76b266331d98e7be"
] | [
"cpc/train.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\nimport argparse\nimport json\nimport os\nimport numpy as np\nimport torch\nimport time\nfrom copy import deepcopy\nimport random\nimpo... | [
[
"torch.cuda.empty_cache",
"torch.load",
"torch.no_grad",
"torch.cuda.device_count",
"torch.optim.Adam",
"torch.multiprocessing.set_start_method",
"torch.optim.lr_scheduler.StepLR"
]
] |
mfkasim1/pyscf | [
"7be5e015b2b40181755c71d888449db936604660"
] | [
"pyscf/agf2/ragf2_slow.py"
] | [
"# 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/LICENSE-2.0\n#\n# Unless r... | [
[
"numpy.sqrt",
"numpy.sum",
"numpy.zeros"
]
] |
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