repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
jpolchlo/rasterframes | [
"1ec7e9e65a4ac7f8f17863d64a4884c35cd24403"
] | [
"pyrasterframes/src/main/python/pyrasterframes/__init__.py"
] | [
"#\n# This software is licensed under the Apache 2 license, quoted below.\n#\n# Copyright 2019 Astraea, Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may not\n# use this file except in compliance with the License. You may obtain a copy of\n# the License at\n#\n# [http://www.apache... | [
[
"pandas.DataFrame"
]
] |
ajmarcus/tfx | [
"28ac2be5ace31ca733f6292495f8be83484a1730",
"28ac2be5ace31ca733f6292495f8be83484a1730"
] | [
"tfx/components/trainer/fn_args_utils_test.py",
"tfx/examples/penguin/penguin_pipeline_kubeflow_e2e_test.py"
] | [
"# Lint as: python2, python3\n# Copyright 2019 Google LLC. 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\... | [
[
"tensorflow.test.main"
],
[
"tensorflow.test.main"
]
] |
congw112358/RAL2022_Code | [
"5e275cb8b389be745fee1285f58732456146f7af"
] | [
"train_realMulti-DA-Loss_classification.py"
] | [
"import os\nimport sys\nimport torch\nimport numpy as np\n\nimport datetime\nimport logging\nimport provider\nimport importlib\nimport shutil\nimport argparse\n\nfrom pathlib import Path\nfrom tqdm import tqdm\nfrom data_utils.PCDLoader import *\n\n\nBASE_DIR = os.path.dirname(os.path.abspath(__file__))\nROOT_DIR =... | [
[
"torch.optim.lr_scheduler.StepLR",
"numpy.zeros",
"torch.no_grad",
"torch.save",
"numpy.mean",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.Tensor"
]
] |
Richoor/HEFT | [
"8422bfc5e9abf132c409a0ae299cbde29eb6e5fc"
] | [
"venv/Lib/site-packages/networkx/linalg/algebraicconnectivity.py"
] | [
"# -*- coding: utf-8 -*-\n# Copyright (C) 2014 ysitu <ysitu@users.noreply.github.com>\n# All rights reserved.\n# BSD license.\n#\n# Author: ysitu <ysitu@users.noreply.github.com>\n\"\"\"\nAlgebraic connectivity and Fiedler vectors of undirected graphs.\n\"\"\"\nfrom functools import partial\nimport networkx as nx\n... | [
[
"numpy.random.normal",
"numpy.array",
"numpy.linalg.norm",
"numpy.dot",
"numpy.asarray",
"numpy.zeros",
"scipy.sparse.spdiags",
"scipy.linalg.eigh",
"scipy.linalg.blas.daxpy",
"scipy.sparse.csc_matrix",
"numpy.ones",
"scipy.linalg.blas.ddot",
"numpy.linalg.qr",
... |
mschart/prednet_FORK | [
"6baebee177e0047edfc66fe9cfbf8f8efca52422"
] | [
"kitti_evaluate.py"
] | [
"'''\nEvaluate trained PredNet on KITTI sequences.\nCalculates mean-squared error and plots predictions.\n'''\n\nimport os\nimport numpy as np\nfrom six.moves import cPickle\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\nimport matplotlib.gridspec as gridspec\n\nfrom keras import backen... | [
[
"matplotlib.use",
"numpy.random.permutation",
"numpy.mean",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.tick_params",
"numpy.transpose",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.imshow",
"matplotlib.gridspec.GridSpec",
"matplotlib.pyplo... |
filemaster/qiskit-terra | [
"8672c407a5a0e34405315f82d5ad5847916e857e"
] | [
"qiskit/tools/qcvv/tomography.py"
] | [
"# -*- coding: utf-8 -*-\n\n# Copyright 2017, IBM.\n#\n# This source code is licensed under the Apache License, Version 2.0 found in\n# the LICENSE.txt file in the root directory of this source tree.\n\n# pylint: disable=invalid-name\n\n\"\"\"\nQuantum Tomography Module\n\nDescription:\n This module contains fun... | [
[
"numpy.array",
"numpy.dot",
"numpy.trace",
"numpy.zeros",
"numpy.sum",
"numpy.linalg.eigh",
"numpy.exp",
"numpy.sqrt",
"numpy.diag",
"numpy.kron"
]
] |
Sanduoo/OpenCV-Python | [
"8356782f65918a5193b0d2d2618d0bcb32e831d2"
] | [
"11_ Histogram3.py"
] | [
"import cv2 as cv\nimport numpy as np\nfrom matplotlib import pyplot as plt\n\n#直方图反向投影\n\ndef bitwise_and():\n small = cv.imread(\"C:/1/image/small.jpg\")\n big = cv.imread(\"C:/1/image/big.jpg\")\n small_hsv = cv.cvtColor(small, cv.COLOR_BGR2HSV)\n big_hsv = cv.cvtColor(big, cv.COLOR_BGR2HSV)\n\n \... | [
[
"matplotlib.pyplot.show",
"numpy.array",
"matplotlib.pyplot.title",
"matplotlib.pyplot.imshow"
]
] |
xxg1413/oneflow | [
"f2e3c85a25b8aecfb6c0c0af1737833b1a77e135",
"f2e3c85a25b8aecfb6c0c0af1737833b1a77e135"
] | [
"oneflow/python/test/ops/test_reduce_mean.py",
"oneflow/python/test/ops/test_mod_int.py"
] | [
"\"\"\"\nCopyright 2020 The OneFlow Authors. All rights reserved.\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 ap... | [
[
"tensorflow.config.experimental.list_physical_devices",
"tensorflow.config.experimental.set_memory_growth",
"tensorflow.GradientTape",
"tensorflow.math.reduce_mean"
],
[
"numpy.array_equal",
"numpy.random.rand"
]
] |
kougou/end2end_dialog | [
"bd70fcca8faec0ded37b74997fa9d2b507a6f07b"
] | [
"SlotTaggingModel_multitask.py"
] | [
"''' Natural language understanding model based on multi-task learning.\n This model is trained on two tasks: slot tagging and user intent prediction. \n\n Inputs: user utterance, e.g. BOS w1 w2 ... EOS\n Outputs: slot tags and user intents, e.g. O O B-moviename ... O\\tinform+moviename\n \n Author ... | [
[
"numpy.zeros_like",
"numpy.random.seed",
"numpy.load",
"numpy.savez_compressed",
"numpy.int32"
]
] |
mlexample/gcspytorchimagenet | [
"b864886ba39869c1c1d601979a80b347f0cc179a"
] | [
"test_train_mp_wds_local.py"
] | [
"import torch_xla.test.test_utils as test_utils\nimport torch_xla.distributed.xla_multiprocessing as xmp\nimport torch_xla.core.xla_model as xm\nimport torch_xla.utils.utils as xu\nimport torch_xla.distributed.parallel_loader as pl\nimport torch_xla.debug.metrics as met\nimport torch_xla\nimport torchvision.transfo... | [
[
"torch.utils.data.get_worker_info",
"torch.set_default_tensor_type",
"torch.manual_seed",
"torch.utils.data.DataLoader",
"torch.nn.CrossEntropyLoss"
]
] |
ebezzam/frius | [
"c3acc98288c949085b7dea08ef3708581f86ce25"
] | [
"report_results/fig1p6_pulse_shape.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport os, sys\n\nsys.path.append(os.path.join(os.path.dirname(__file__)))\nimport plot_settings\nfrom test_utilities import gausspuls_coeff, gausspulse, gauss_ft\n\n# time domain plot\nfc = 5e6\nbandwidth = 2/3\nbwr = -6\nt_vals = np.linspace(-3/fc, 3/fc, 200)\... | [
[
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.autoscale",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.figure",
... |
cbymar/clv-modeling | [
"0ad130b9a1e116afc4df32d307c1e542da0b19aa"
] | [
"clvscript00.py"
] | [
"import datetime as dt\nimport matplotlib.pyplot as plt\nimport lifetimes\nimport numpy as np\nimport os\nimport pandas as pd\nimport seaborn as sns\n\ndef numcard(x):\n return x.nunique(), len(x)\ndef todateclean(x):\n return pd.to_datetime(x, errors='coerce').dt.date.astype('datetime64')\n\n\"\"\"\n- info, ... | [
[
"pandas.to_datetime",
"pandas.merge",
"pandas.concat",
"numpy.random.gamma",
"pandas.DataFrame",
"matplotlib.pyplot.figure",
"numpy.timedelta64",
"numpy.sqrt",
"numpy.argsort",
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"pandas.Series"
]
] |
kapilepatel/pandas | [
"3e652ac565e054b763ccbe23006c02704f6cd1b1"
] | [
"pandas/core/generic.py"
] | [
"# pylint: disable=W0231,E1101\nimport collections\nfrom datetime import timedelta\nimport functools\nimport gc\nimport json\nimport operator\nfrom textwrap import dedent\nimport warnings\nimport weakref\n\nimport numpy as np\n\nfrom pandas._libs import Timestamp, iNaT, properties\nimport pandas.compat as compat\nf... | [
[
"pandas.io.pickle.to_pickle",
"pandas.core.index.RangeIndex",
"pandas.core.missing.clean_reindex_fill_method",
"pandas.compat.lzip",
"pandas.io.formats.excel.ExcelFormatter",
"pandas.core.dtypes.common.is_number",
"pandas.core.window.rolling",
"pandas.compat.iteritems",
"pandas... |
aditzkabitz/pandas | [
"a3702e2207af106939804ceb193bf4fae3e23a31"
] | [
"pandas/core/groupby/ops.py"
] | [
"\"\"\"\nProvide classes to perform the groupby aggregate operations.\n\nThese are not exposed to the user and provide implementations of the grouping\noperations, primarily in cython. These classes (BaseGrouper and BinGrouper)\nare contained *in* the SeriesGroupBy and DataFrameGroupBy objects.\n\"\"\"\nfrom __futu... | [
[
"pandas.core.sorting.get_group_index",
"pandas.core.dtypes.cast.maybe_downcast_to_dtype",
"pandas.core.dtypes.common.is_datetime64_any_dtype",
"pandas.core.indexes.api.ensure_index",
"pandas.core.arrays.integer.Int64Dtype",
"pandas._libs.reduction.extract_result",
"pandas.core.dtypes.c... |
socsol/infsocsol | [
"67038e95e891c1f921974b88b072e1fbe41c8c0f"
] | [
"tests/test_fisheries_det_basic.py"
] | [
"# Copyright 2019 Alastair Pharo\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... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.dot"
]
] |
qphong/BayesOpt-LV | [
"b852a94e9bae8716566e014ca1dd02186bcdf7ca"
] | [
"functions.py"
] | [
"import numpy as np\nimport scipy.stats as scst\nimport scipy.special as scsp\nimport scipy.optimize as scopt\nimport tensorflow as tf\nimport tensorflow_probability as tfp\nimport pickle\nimport os\nimport sys\n\ntry:\n import gpflow\nexcept:\n raise Exception(\"Requires gpflow!\")\n\n\nimport utils\n\n\ndef... | [
[
"tensorflow.exp",
"numpy.random.rand",
"numpy.meshgrid",
"tensorflow.ones_like",
"numpy.tile",
"numpy.exp",
"tensorflow.reshape",
"tensorflow.sqrt",
"numpy.cos",
"tensorflow.cast",
"tensorflow.shape",
"scipy.special.logsumexp",
"numpy.log",
"tensorflow.trans... |
iwillcodeu/KerasGANs | [
"636ec0533df1d1ba2bfe4ec9ae7aa66bd7ee2177"
] | [
"wgan_gp/wgan_gp.py"
] | [
"\n# Large amount of credit goes to:\n# https://github.com/keras-team/keras-contrib/blob/master/examples/improved_wgan.py\n# which I've used as a reference for this implementation\n\nfrom __future__ import print_function, division\n\nfrom keras.datasets import mnist\nfrom keras.layers.merge import _Merge\nfrom kera... | [
[
"numpy.random.normal",
"numpy.zeros",
"numpy.ones",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots",
"numpy.random.randint",
"numpy.expand_dims"
]
] |
claudius-kienle/self-supervised-depth-denoising | [
"4dffb30e8ef5022ef665825d26f45f67bf712cfd"
] | [
"src/evaluate/plot_evaluation.py"
] | [
"from argparse import ArgumentParser\nimport enum\nfrom pathlib import Path\nfrom matplotlib import pyplot as plt\nfrom matplotlib.lines import Line2D\nimport numpy as np\nimport yaml\n\nimport pandas as pd\n\n\nMETRICS = ['total_L1', '0_to10mm_L1', '10_to20mm_L1', 'above20mm_L1']\nMETRICS_TITLE = ['L1Loss', 'L1Los... | [
[
"matplotlib.lines.Line2D",
"matplotlib.pyplot.setp",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.get_cmap",
"pandas.read_json",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.subplots_adjust"
]
] |
junyongk/pytorch-seq2seq | [
"9c60de7825cd0f65050fa958126340607e75057c"
] | [
"seq2seq/models/DecoderRNN.py"
] | [
"import random\n\nimport numpy as np\n\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\nimport torch.nn.functional as F\n\nfrom .attention import Attention\nfrom .baseRNN import BaseRNN\n\nif torch.cuda.is_available():\n import torch.cuda as device\nelse:\n import torch as device\n\n... | [
[
"torch.nn.Linear",
"numpy.array",
"torch.cuda.is_available",
"torch.LongTensor",
"torch.nn.Embedding"
]
] |
neu-szy/BasicSR | [
"dce8d520d79225ba6e2dfa326a76e31b86df4436"
] | [
"basicsr/archs/seanet_arch.py"
] | [
"from . import sean_common as common\nimport torch.nn as nn\nimport torch\nfrom basicsr.utils.registry import ARCH_REGISTRY\n\nclass LFF(nn.Module):\n def __init__(self, scale, n_colors, conv=common.default_conv, n_feats=64):\n super(LFF, self).__init__()\n\n kernel_size = 3\n n_layes = 5\n ... | [
[
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.Sequential",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
Li-kewei/models | [
"d02ba6a87c37ad9d0bc413413b9e9ddc8c60f43c"
] | [
"official/cv/brdnet/preprocess.py"
] | [
"# Copyright 2021 Huawei Technologies Co., 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/licenses/LICENSE-2.0\n#\n# Unless required by applicable l... | [
[
"numpy.random.seed",
"numpy.random.normal"
]
] |
KlrShaK/bayesrace | [
"8fe76f22b2ed57987dd8a57279cd29c100d0b9a6"
] | [
"bayes_race/models/dynamic.py"
] | [
"\"\"\"\tDynamic bicycle model.\n\t\n\tUse Dynamic class to:\n\t1. simulate continuous model\n\t2. linearize continuous model\n\t3. discretize continuous model\n\t4. simulate continuously linearized discrete model\n\t5. compare continuous and discrete models\n\n\"\"\"\n\n__author__ = 'Achin Jain'\n__email__ = 'achi... | [
[
"numpy.array",
"numpy.sin",
"numpy.zeros",
"numpy.arctan",
"numpy.cos",
"numpy.sqrt",
"numpy.linspace"
]
] |
nguyenvanhoang7398/nndl2-project | [
"0da19e3ff0da1de2cb9ad6c9286d9f9204358b91"
] | [
"zero/cli.py"
] | [
"from datetime import datetime\nimport logging\nimport os\nimport subprocess\nimport sys\nfrom argparse import Namespace\n\nlogging.getLogger(\"transformers\").setLevel(logging.WARNING)\n\nimport click\nimport torch\n\nfrom luke.utils.model_utils import ModelArchive\n\nfrom zero.utils.experiment_logger import comme... | [
[
"torch.distributed.init_process_group",
"torch.device",
"torch.cuda.set_device"
]
] |
denisesato/scikit-multiflow | [
"3eb4c7262bb60d7e3f65c0d3395e4572d9a8cb95",
"3eb4c7262bb60d7e3f65c0d3395e4572d9a8cb95",
"3eb4c7262bb60d7e3f65c0d3395e4572d9a8cb95",
"3eb4c7262bb60d7e3f65c0d3395e4572d9a8cb95",
"3eb4c7262bb60d7e3f65c0d3395e4572d9a8cb95",
"3eb4c7262bb60d7e3f65c0d3395e4572d9a8cb95"
] | [
"src/skmultiflow/drift_detection/adwin.py",
"src/skmultiflow/meta/online_under_over_bagging.py",
"tests/meta/test_regressor_chains.py",
"src/skmultiflow/bayes/naive_bayes.py",
"tests/data/test_regression_generator.py",
"src/skmultiflow/data/sea_generator.py"
] | [
"import numpy as np\n\nfrom skmultiflow.drift_detection.base_drift_detector import BaseDriftDetector\n\n\nclass ADWIN(BaseDriftDetector):\n \"\"\" Adaptive Windowing method for concept drift detection.\n\n Parameters\n ----------\n delta : float (default=0.002)\n The delta parameter for the ADWIN... | [
[
"numpy.log",
"numpy.zeros",
"numpy.power",
"numpy.sqrt",
"numpy.absolute"
],
[
"numpy.sum",
"numpy.argmax",
"numpy.asarray",
"numpy.zeros"
],
[
"numpy.array",
"sklearn.linear_model.SGDRegressor",
"sklearn.set_config",
"sklearn.datasets.make_regression"
... |
Bobholamovic/ever | [
"f38060674a40ed53072b9d9be99cc656a830398f"
] | [
"ever/module/_hrnet.py"
] | [
"\"\"\" Modified from offical repo and mmlab's repo of HRNet\nMIT License\nCopyright (c) 2019 Microsoft\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including witho... | [
[
"torch.device",
"torch.nn.init.kaiming_uniform_",
"torch.nn.ModuleList",
"torch.nn.init.constant_",
"torch.nn.Sequential",
"torch.nn.init.kaiming_normal_",
"torch.utils.model_zoo.load_url",
"torch.nn.ReLU",
"torch.nn.Upsample",
"torch.nn.Conv2d"
]
] |
WenmuZhou/crnn.pytorch | [
"bf7a7c62376eee93943ca7c68e88e3d563c09aa8"
] | [
"data_loader/modules/Text_Image_Augmentation_python/augment.py"
] | [
"# -*- coding:utf-8 -*-\n# Author: RubanSeven\n\n# import cv2\nimport numpy as np\n# from transform import get_perspective_transform, warp_perspective\nfrom .warp_mls import WarpMLS\n\n\ndef distort(src, segment):\n img_h, img_w = src.shape[:2]\n\n cut = img_w // segment\n thresh = cut // 3\n # thresh =... | [
[
"numpy.random.randint",
"numpy.arange"
]
] |
1MT3J45/ML-DroughtAnalysisNLP | [
"861b70acaabe9f28b887eef6661b399e7f9ca8d6"
] | [
"freqWordSelection.py"
] | [
"from __future__ import division\nfrom __future__ import print_function\nfrom __future__ import with_statement\n\nfrom replacers import *\nimport pandas as pd\nimport nltk\nimport subprocess\n\n\ndef findFreqWord(fuzzyDF):\n f1 = fuzzyDF # pd.read_csv(\"SubmittedCSV/fuzzy.csv\")\n f2 = pd.DataFrame(columns=[... | [
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
jzlotek/drexel-tms-parser | [
"9d5582a441d490a8099252994f9e41dca36acf81"
] | [
"src/plotter.py"
] | [
"import io\nfrom sdk.db import database\nimport numpy as np\nimport matplotlib.pyplot as plt \nfrom numba import jit\nfrom utils import logger\n\n\nsemester_order = ['FA', 'WI', 'SP', 'SU']\n\ndef get_section(x):\n return (\n x.get('semester'),\n x.get('year')\n )\n\n \ndef filter_function(s... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.close"
]
] |
marshuang80/NucleiSegmentation | [
"aef5196b6fd906bff3866156e205d4f787710bde"
] | [
"process_data/nuclei_create_hdf5.py"
] | [
"import numpy as np\nimport h5py\nimport argparse\nimport imageio\nimport tqdm\nimport os\nfrom glob import glob\n\n\ndef main(args):\n \"\"\"Main function to parse in Nuclei Dataset from Kaggle and store as HDF5\n\n Parameters\n ----------\n args: ArgumentParser()\n input_dir: str\n ... | [
[
"numpy.zeros_like",
"numpy.transpose",
"numpy.expand_dims",
"numpy.vstack",
"numpy.maximum"
]
] |
WuHaobo/Paddle | [
"f430799bc82ee327d14a04c3bb1ea712d39d1cef"
] | [
"python/paddle/fluid/tests/unittests/test_roll_op.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 re... | [
[
"numpy.allclose",
"numpy.array",
"numpy.roll",
"numpy.random.random"
]
] |
willwhitney/sac_dists | [
"d1374caab080d9fb4b8e762f501501843686cf13"
] | [
"distributions/squashed_normal.py"
] | [
"from torch import nn\nimport torch.nn.functional as F\nfrom torch import distributions as pyd\n\n\nclass TanhTransform(pyd.transforms.Transform):\n domain = pyd.constraints.real\n codomain = pyd.constraints.interval(-1.0, 1.0)\n bijective = True\n sign = +1\n\n def __init__(self, cache_size=1):\n ... | [
[
"torch.distributions.Normal",
"torch.nn.functional.softplus",
"torch.distributions.constraints.interval"
]
] |
HotelsDotCom/neaps | [
"4222016d60d27a168f4fb5569d696ec1731f8698"
] | [
"neaps-api/neaps_lib/bootstrap_test.py"
] | [
"#\n# Copyright 2018 Expedia 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 agr... | [
[
"numpy.float64",
"numpy.int64"
]
] |
yasuyuky/pytorch-pfn-extras | [
"febea6ded644d3b7a099ac557f06567a04b3b838"
] | [
"pytorch_pfn_extras/dataset/tabular/tabular_dataset.py"
] | [
"import numpy\nimport torch\n\nimport pytorch_pfn_extras as ppe\nfrom torch.utils.data import Dataset\n\n\nclass TabularDataset(Dataset):\n \"\"\"An abstract class that represents tabular dataset.\n\n This class represents a tabular dataset.\n In a tabular dataset, all examples have the same number of elem... | [
[
"numpy.array"
]
] |
ThatSnail/synth_detune | [
"9540508ae653b390dfea5e3083b05936c53c6d4d"
] | [
"plotter.py"
] | [
"\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nts = np.load(\"ts.npy\")\nts -= ts[0]\nxs = np.load(\"xs.npy\")\n\nprint(\"ts shape: {0}\".format(np.shape(ts)))\nprint(\"xs shape: {0}\".format(np.shape(xs)))\n\nplt.figure()\nplt.scatter(ts, xs)\nplt.show()\n"
] | [
[
"numpy.load",
"numpy.shape",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.pyplot.scatter"
]
] |
BFourcin/rcmodel | [
"160eb2ad7ea60f328abde157baeef7378e28d815"
] | [
"src/rcmodel/optimisation.py"
] | [
"from filelock import FileLock\nimport torch\nimport pandas as pd\nfrom .tools import BuildingTemperatureDataset\nimport os\n\ndef train(model, device, dataloader, optimizer):\n \"\"\"\n Performs one epoch of training.\n Order of rooms in building and in data must match otherwise model will fit wrong rooms... | [
[
"pandas.to_datetime",
"torch.nn.MSELoss",
"pandas.Timedelta",
"torch.no_grad",
"torch.optim.Adam",
"pandas.Timestamp",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"pandas.read_csv"
]
] |
madhukaranand/Which-Bollywood-Celebrity-You-look-like | [
"22d5aac12f88c5f5616008eb981346480cdd1d28"
] | [
"src/testing.py"
] | [
"from keras_vggface.utils import preprocess_input\nfrom keras_vggface.vggface import VGGFace\nimport numpy as np\nimport pickle\nfrom sklearn.metrics.pairwise import cosine_similarity\nimport cv2\nfrom mtcnn import MTCNN\nfrom PIL import Image\n\nfeature_list = np.array(pickle.load(open('artifacts/extracted_feature... | [
[
"numpy.asarray",
"numpy.expand_dims"
]
] |
itsnamgyu/reid-metric | [
"437e02ebad510b482f620a293fd8c7baa4f42ad6"
] | [
"hitl/feedback.py"
] | [
"import torch\n\nfrom utils.distmat import compute_distmat\n\n\ndef init_feedback_indices(q, g, device=None):\n return torch.zeros((q, g), dtype=torch.bool, device=device)\n\n\ndef init_feedback_indices_qg(q, g, positive=False, device=None):\n indices = torch.zeros(q, q + g, dtype=torch.bool, device=device)\n... | [
[
"torch.zeros",
"torch.arange"
]
] |
Mougatine/lectures-labs | [
"0f2bdd326174c92d80816663e2ae49abeb7f8533"
] | [
"labs/10_unsupervised_generative_models/solutions/grl_training.py"
] | [
"import collections\n\nfrom tensorflow.keras.losses import SparseCategoricalCrossentropy, BinaryCrossentropy\nfrom tensorflow.keras.metrics import Mean, Accuracy\n\n\noptimizer = SGD(lr=0.01, momentum=0.9, nesterov=True)\n\ncce = SparseCategoricalCrossentropy()\nbce = BinaryCrossentropy()\n\nmodel.compile(\n opt... | [
[
"tensorflow.keras.losses.SparseCategoricalCrossentropy",
"tensorflow.keras.losses.BinaryCrossentropy"
]
] |
bobvdvelde/polyaxon | [
"90a8cc37143a9ba1dd7eaf040377100d7a33f0d1"
] | [
"src/core/tests/test_tracking/test_run_tracking.py"
] | [
"#!/usr/bin/python\n#\n# Copyright 2018-2021 Polyaxon, 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 requir... | [
[
"numpy.array",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"numpy.random.randn",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.fignum_exists",
"matplotlib.pyplot.figure",
"numpy.random.randint",
"matplotlib.pyplot.Circle",
"matplotlib.pyplot.tight_layout",
"matplot... |
Jerry-li-uw/privacy | [
"7019bc04c9068772f7412650fac4c56851cdcc23"
] | [
"tutorials/dp_optimizer_adp.py"
] | [
"# Copyright 2020 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.shape",
"tensorflow.GradientTape",
"tensorflow.Variable",
"tensorflow.keras.backend.name_scope",
"tensorflow.reshape",
"tensorflow.nest.map_structure",
"tensorflow.nest.flatten",
"tensorflow.map_fn",
"tensorflow.print",
"tensorflow.gradients",
"tensorflow.tr... |
JustinSGray/blue | [
"49f4edd00eda43f7ce5e10a5121839f2e897d429"
] | [
"openmdao/components/tests/test_meta_model_structured_comp.py"
] | [
"\"\"\"\nUnit tests for the structured metamodel component.\n\"\"\"\nimport unittest\nimport inspect\n\nimport numpy as np\nfrom numpy.testing import assert_almost_equal\n\nimport openmdao.api as om\nfrom openmdao.utils.assert_utils import assert_near_equal, assert_warning, assert_check_partials\nfrom openmdao.util... | [
[
"numpy.array",
"numpy.sin",
"numpy.zeros",
"numpy.random.seed",
"numpy.testing.assert_almost_equal",
"numpy.ones",
"numpy.sqrt",
"numpy.linspace",
"numpy.meshgrid"
]
] |
skylook/mobilestereonet | [
"45b5ce6e9cf96698ac3f274353c64e5c5fc12b5d"
] | [
"datasets/dataset.py"
] | [
"import os\nimport random\nimport numpy as np\nfrom PIL import Image\nfrom torch.utils.data import Dataset\nfrom datasets.data_io import get_transform, read_all_lines, pfm_imread\n\nclass PicoStereoDataset(Dataset):\n def __init__(self, datapath, list_filename, training):\n self.datapath = datapath\n ... | [
[
"numpy.ascontiguousarray",
"numpy.array",
"numpy.lib.pad"
]
] |
akio-kobayashi/lc_lstm | [
"c5367518ebf56d13a29794d90061fdfb06677e3e",
"c5367518ebf56d13a29794d90061fdfb06677e3e"
] | [
"nbest_multi_fixed_generator.py",
"post_multi_fixed_generator.py"
] | [
"import numpy as np\nimport sys, os, re, gzip, struct\nimport random\nimport h5py\nimport copy\nfrom keras import backend as K\nfrom keras.utils import Sequence\nimport keras.utils\nimport tensorflow as tf\nimport multi_utils\nimport mat_utils\n\nclass NbestFixedDataGenerator(Sequence):\n\n def __init__(self, fi... | [
[
"numpy.ceil",
"numpy.expand_dims"
],
[
"numpy.ceil",
"numpy.expand_dims"
]
] |
mathandy/svgtree | [
"884fd0aea780996a263ffe487f5803aec253f56c"
] | [
"noIntersections4rings.py"
] | [
"# External Dependencies\nfrom __future__ import division\nfrom numpy import isclose\nfrom svgpathtools import Path\n\n# Internal Dependencies\nfrom misc4rings import isNear\n\n\nclass ClosedRingsOverlapError(Exception):\n def __init__(self,mes):\n self.mes = mes\n def __str__(self):\n return rep... | [
[
"numpy.isclose"
]
] |
dinga92/neuropredict | [
"8e7a445424f8c649a6583567f5692fdf73d7e1d9"
] | [
"neuropredict/run_workflow.py"
] | [
"\"\"\"\nneuropredict : easy and comprehensive predictive analysis.\n\n\"\"\"\nfrom __future__ import print_function\n\n__all__ = ['run', 'cli', 'get_parser']\n\nimport argparse\nimport os\nimport sys\nimport textwrap\nimport traceback\nimport warnings\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom sys i... | [
[
"numpy.all",
"numpy.int64",
"numpy.float32",
"matplotlib.pyplot.close"
]
] |
Zhiwei-Z/prompzzw | [
"9d109f1a604125411a1e7894c3222cd50a0ec975"
] | [
"meta_policy_search/meta_algos/trpo_maml.py"
] | [
"from meta_policy_search.utils import logger\nfrom meta_policy_search.meta_algos.base import MAMLAlgo\nfrom meta_policy_search.optimizers.conjugate_gradient_optimizer import ConjugateGradientOptimizer\n\nimport tensorflow as tf\nfrom collections import OrderedDict\n\nclass TRPOMAML(MAMLAlgo):\n \"\"\"\n Algor... | [
[
"tensorflow.variable_scope",
"tensorflow.reduce_mean",
"tensorflow.stack"
]
] |
Fennec2000GH/Poly-Finance | [
"33de7a7503f4a4c800ab364f4720104c889cf30f"
] | [
"ml.py"
] | [
"import matplotlib.pyplot as plt, streamlit as st\r\nfrom typing import Iterable, Union\r\n\r\nfrom sklearn.metrics import classification_report\r\nfrom sklearn.metrics import roc_curve, auc, RocCurveDisplay\r\n\r\ndef train(estimator: object, X: Iterable[Union[int, float]], y: Iterable):\r\n \"\"\"\r\n Train... | [
[
"sklearn.metrics.classification_report",
"sklearn.metrics.auc",
"sklearn.metrics.roc_curve"
]
] |
liuyenting/olive-camera-dcamapi | [
"0ac8eeeb2d666561fefd8f6e6a137bfa304f5d3a"
] | [
"setup.py"
] | [
"import os\r\nfrom setuptools import Extension, setup\r\nimport sys\r\n\r\nfrom Cython.Build import build_ext\r\nimport numpy\r\n\r\nNAME = \"olive-camera-dcamapi\"\r\nVERSION = \"0.1\"\r\nDESCRIPTION = \"A small template project that shows how to wrap C/C++ code into python using Cython\"\r\nURL = \"https://github... | [
[
"numpy.get_include"
]
] |
ytakefuji/machine-learning | [
"f0bc65c221ffbf775ad43055f4164abbd3ffee4a"
] | [
"elm_pima.py"
] | [
"import pandas as pd\npima=pd.read_csv('pima-indians-diabetes.csv',encoding=\"shift-jis\")\npima.columns=['pregnant','plasmaGlucose','bloodP','skinThick','serumInsulin','weight','pedigree','age','diabetes']\nfrom sklearn.model_selection import train_test_split\ny = pima['diabetes']\nX=pima.drop(['diabetes'],axis=1)... | [
[
"sklearn.model_selection.train_test_split",
"pandas.read_csv"
]
] |
ecom-research/pytorch_geometric | [
"bca73a6f0808cfcf7133548edfbb5628ad6e49fa"
] | [
"benchmark/recsys/gcn_solver.py"
] | [
"import argparse\nimport torch\nimport os\nimport numpy as np\nimport random as rd\n\nfrom models import GCN\nfrom utils import get_folder_path\nfrom base_solver import BaseSolver\n\n\nMODEL = 'GCN'\n\nparser = argparse.ArgumentParser()\n# Dataset params\nparser.add_argument(\"--dataset\", type=str, default='Moviel... | [
[
"numpy.array",
"numpy.sum",
"torch.from_numpy",
"torch.cuda.is_available",
"numpy.flip"
]
] |
SumanSudhir/Kaggle-SIIM-ISIC-Melanoma-Classification | [
"d22e91f357dd2940f8aac5d254f13d865bcba3bb"
] | [
"src/test.py"
] | [
"import os\nimport sys\n\nimport numpy as np\nimport pandas as pd\nimport random\n\nfrom tqdm import tqdm\n\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nimport torch.nn.functional as F\nimport albumentations as A\nfrom albumentations.pyt... | [
[
"numpy.concatenate",
"torch.device",
"torch.cat",
"torch.cuda.manual_seed",
"torch.stack",
"numpy.random.seed",
"pandas.DataFrame",
"torch.no_grad",
"torch.manual_seed",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"pandas.read_csv",
"torch.mean"
... |
alvisdeng/NLP-Language-Model | [
"84903b344936bc66ccf217e1d74524552049b8f8"
] | [
"lm.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n#\n# Copyright (C) 2019 Zimeng Qiu <zimengq@andrew.cmu.edu>\n\n\"\"\"\nF19 11-411/611 NLP Assignment 3 Task 1\nN-gram Language Model Implementation Script\nZimeng Qiu Sep 2019\n\nThis is a simple implementation of N-gram language model\n\nWrite your own implementatio... | [
[
"numpy.log2",
"numpy.power",
"numpy.zeros"
]
] |
LottieWang/mindspore | [
"d16e9bc3f689cf0b52c15a4566f5aad2c54a236e",
"d16e9bc3f689cf0b52c15a4566f5aad2c54a236e",
"1331c7e432fb691d1cfa625ab7cc7451dcfc7ce0"
] | [
"tests/st/fl/mobile/test_mobile_lenet.py",
"model_zoo/official/cv/centerface/dependency/evaluate/eval.py",
"tests/ut/python/dataset/test_save_op.py"
] | [
"# Copyright 2021 Huawei Technologies Co., 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/licenses/LICENSE-2.0\n#\n# Unless required by applicable l... | [
[
"numpy.random.seed",
"numpy.random.randint",
"numpy.random.rand"
],
[
"numpy.concatenate",
"numpy.max",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.ones",
"numpy.min",
"numpy.where",
"numpy.maximum"
],
[
"numpy.array",
"numpy.arange",
"nump... |
mmtechslv/PhyloMAF | [
"bab43dd4a4d2812951b1fdf4f1abb83edb79ea88",
"bab43dd4a4d2812951b1fdf4f1abb83edb79ea88"
] | [
"pmaf/biome/essentials/_taxonomy.py",
"pmaf/sequence/_multiple/_stream.py"
] | [
"import warnings\n\nwarnings.simplefilter(\"ignore\", category=FutureWarning)\nfrom pmaf.biome.essentials._metakit import EssentialFeatureMetabase\nfrom pmaf.biome.essentials._base import EssentialBackboneBase\nfrom pmaf.internal._constants import (\n AVAIL_TAXONOMY_NOTATIONS,\n jRegexGG,\n jRegexQIIME,\n ... | [
[
"pandas.DataFrame.from_records",
"numpy.asarray",
"pandas.DataFrame",
"pandas.notna",
"pandas.Series",
"pandas.read_csv",
"numpy.unique"
],
[
"pandas.Series"
]
] |
avigna/COMPAS-1 | [
"63e1aeef4ed37ff661b8118842ef73a4e9bea1fd"
] | [
"utils/example_plots/methods_paper_plots/fig_5_HR_diagram/pythonSubmit.py"
] | [
"import numpy as np\nimport sys\nimport os\nimport re\nimport ntpath\nfrom subprocess import call\n\n#### DISCLAIMER: This script uses the `pythonSubmit.py` format\n#### that has been replaced by the `runSubmit.py` and \n#### `compasConfigDefault.yaml` combo as of v02.25.10.\n#### The `pythonSubmit.py` format will ... | [
[
"numpy.loadtxt"
]
] |
brianjstroh/BrawlStars | [
"1d4700ee9e1a7f595bf76bb205cbe1f65f6b635f"
] | [
"Capstone_Tables&Figures_Results_Graphs.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Apr 25 21:37:26 2021\n\n@author: brian\n\"\"\"\nimport os\nos.chdir('C:/Users/brian/Desktop/All/UWEC/DS785_Capstone/Project')\nimport brawl_data as bd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport pandas as pd\nfrom statsmodels.stats.proportion impo... | [
[
"matplotlib.pyplot.title"
]
] |
STASYA00/CityMorph | [
"18b8273a1ae0a4e8f234850d0c98640a2483ab04"
] | [
"scripts/writer.py"
] | [
"import json\nimport os\nimport pandas as pd\nimport sys\n\nsys.path.append('scripts/')\nfrom polygon import Collection, Footprint\n\n\nclass Writer:\n\t\"\"\"\n\tClass that stores smart label values per instance\n\t\"\"\"\n\tdef __init__(self, filename):\n\t\t\"\"\"\n\t\tClass initialization.\n\t\t:param filename:... | [
[
"pandas.DataFrame.from_dict",
"pandas.DataFrame",
"pandas.read_csv"
]
] |
MengwenHe-CMU/17S_10701_MachineLearning | [
"613a3087a57a206b83d79855cec359e04cb440f7"
] | [
"Homeworks/HW2/Python/hw2_B.py"
] | [
"from sklearn.ensemble import AdaBoostClassifier\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.naive_bayes import BernoulliNB\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn import svm\nfrom sklearn import metrics\nfrom matplotlib import pyplot\nfrom matplotlib import gridspec\ni... | [
[
"numpy.random.rand",
"numpy.zeros",
"sklearn.metrics.zero_one_loss",
"numpy.ones",
"matplotlib.pyplot.figure",
"sklearn.svm.SVC",
"sklearn.linear_model.LogisticRegression",
"sklearn.naive_bayes.BernoulliNB",
"numpy.arange",
"sklearn.tree.DecisionTreeClassifier",
"matplo... |
fabianrost84/pymc | [
"f514a8a42475ca12f2b0c2c9592c8c2f890d9f02"
] | [
"pymc/StepMethods.py"
] | [
"from __future__ import division\n\nimport numpy as np\nfrom .utils import msqrt, check_type, round_array, float_dtypes, integer_dtypes, bool_dtypes, safe_len, find_generations, logp_of_set, symmetrize, logp_gradient_of_set\nfrom numpy import ndim, ones, zeros, log, shape, cov, ndarray, inner, reshape, sqrt, any, a... | [
[
"numpy.dot",
"numpy.random.exponential",
"numpy.exp",
"numpy.where",
"numpy.cumsum",
"numpy.outer",
"numpy.random.random",
"numpy.concatenate",
"numpy.random.normal",
"numpy.empty",
"numpy.log",
"numpy.random.poisson",
"numpy.eye",
"numpy.ndim",
"numpy.l... |
haamoon/finding_common_object | [
"2b670facce4e22d669101b0628724d994255dd61"
] | [
"utils.py"
] | [
"import tensorflow as tf\nfrom dataflow.generator_cls import GeneratorCLS\nimport json\nimport logging\nfrom easydict import EasyDict\nfrom dataflow.utils import fix_rng_seed\nfrom model.util import batched_gather\nimport os\nimport pickle\n\ndef get_lr_schedule(lr_schedule):\n boundaries = lr_schedule.boundaries\... | [
[
"tensorflow.shape",
"tensorflow.keras.optimizers.schedules.PiecewiseConstantDecay",
"tensorflow.reshape",
"tensorflow.data.Dataset.from_generator",
"tensorflow.reduce_sum"
]
] |
floscha/keras-io | [
"fb064c551eda7aea631ceaa548c4411b9a1193cb"
] | [
"examples/rl/ppo_cartpole.py"
] | [
"\"\"\"\nTitle: Proximal Policy Optimization\nAuthor: [Ilias Chrysovergis](https://twitter.com/iliachry)\nDate created: 2021/06/24\nLast modified: 2021/06/24\nDescription: Implementation of a Proximal Policy Optimization agent for the CartPole-v0 environment.\n\"\"\"\n\n\"\"\"\n## Introduction\n\nThis code example ... | [
[
"tensorflow.random.categorical",
"tensorflow.minimum",
"tensorflow.GradientTape",
"numpy.zeros",
"tensorflow.where",
"tensorflow.one_hot",
"numpy.mean",
"tensorflow.keras.layers.Dense",
"numpy.std",
"tensorflow.keras.Model",
"tensorflow.nn.log_softmax",
"tensorflow.... |
mikobski/Robot-Inspekcyjny | [
"925491fc43b71bdaa54dccf60d38da59d244181d"
] | [
"robot/src/vision_to_mavros/scripts/calibrate_extrinsics.py"
] | [
"#!/usr/bin/env python3\n######################################################\n## Calibrating the extrinsics between T265 and D4xx ##\n## Based on this example: https://github.com/IntelRealSense/librealsense/pull/4355\n## with changes and modifications.\n######################################################\n\n#... | [
[
"numpy.array",
"numpy.savetxt",
"numpy.reshape",
"numpy.asarray",
"numpy.zeros",
"numpy.set_printoptions",
"numpy.eye",
"numpy.linalg.inv"
]
] |
Hammer7/Flowers-TF-Lite | [
"e98f1ce1c354ce4e09a2c045364fa518702619c5"
] | [
"flowers_tf_lite.py"
] | [
"#@title Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n#\r\n# https://www.apache.org/licenses/LICENSE-2.0\r\n#\r\n# Unless required by applicable law or agreed to in writing, sof... | [
[
"tensorflow.keras.utils.get_file",
"tensorflow.lite.TFLiteConverter.from_saved_model",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.applications.MobileNetV2",
"tensorflow.keras.layers.GlobalAveragePooling2D",
"tensorflow.saved_model.save",
"matplotlib.pyplot.savefig",
"tensor... |
FightingSrain/tianshou | [
"bd9c3c7f8d144448c44a350828b2c5222298bd8e"
] | [
"tianshou/utils/net/discrete.py"
] | [
"import torch\nimport numpy as np\nfrom torch import nn\nimport torch.nn.functional as F\n\n\nclass Actor(nn.Module):\n \"\"\"For advanced usage (how to customize the network), please refer to\n :ref:`build_the_network`.\n \"\"\"\n\n def __init__(self, preprocess_net, action_shape, hidden_layer_size=128... | [
[
"torch.nn.Linear",
"torch.nn.BatchNorm2d",
"torch.nn.Conv2d",
"numpy.prod",
"torch.tensor"
]
] |
pjamesjoyce/brightway2-io | [
"142fc26e2ffc47d8ec474386ee93ab2737a089ce"
] | [
"bw2io/strategies/generic.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import print_function, unicode_literals\nfrom eight import *\n\nfrom bw2data import mapping, Database, databases\nfrom ..units import normalize_units as normalize_units_function\nfrom ..errors import StrategyError\nfrom ..utils import activity_hash, DEFAULT_FIELDS\nfrom cop... | [
[
"numpy.isnan"
]
] |
zabop/astropy | [
"9f77b9a0ffe18e4c767e36f00e2e8728135c0e11"
] | [
"astropy/modeling/powerlaws.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\n\"\"\"\nPower law model variants\n\"\"\"\n# pylint: disable=invalid-name\nimport numpy as np\n\nfrom astropy.units import Quantity\n\nfrom .core import Fittable1DModel\nfrom .parameters import InputParameterError, Parameter\n\n__all__ = ['PowerLaw1D'... | [
[
"numpy.zeros_like",
"numpy.log",
"numpy.exp",
"numpy.any",
"numpy.where",
"numpy.abs"
]
] |
yweweler/single-speaker-tts | [
"04aa714e0ba79c932179cc45a0bbfaa28e768cc7"
] | [
"tacotron/attention.py"
] | [
"import tensorflow as tf\nfrom tensorflow.contrib.seq2seq.python.ops.attention_wrapper import LuongAttention, \\\n AttentionWrapper, AttentionWrapperState\n\n\nclass AttentionMode:\n \"\"\"\n Enumerator for the Luong style local attention modes.\n\n - See [1]: Effective Approaches to Attention-based Neu... | [
[
"tensorflow.exp",
"tensorflow.tensordot",
"tensorflow.matmul",
"tensorflow.stack",
"tensorflow.tanh",
"tensorflow.identity",
"tensorflow.cast",
"tensorflow.shape",
"tensorflow.concat",
"tensorflow.sigmoid",
"tensorflow.variable_scope",
"tensorflow.squeeze",
"ten... |
Yard1/ludwig | [
"510455f8d4fcd6b66e76d2c906d2c600fe724093"
] | [
"ludwig/features/image_feature.py"
] | [
"#! /usr/bin/env python\n# coding=utf-8\n# Copyright (c) 2019 Uber Technologies, 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/LICENS... | [
[
"tensorflow.image.per_image_standardization",
"numpy.arange",
"numpy.zeros",
"tensorflow.cast"
]
] |
caiodearaujo/streamlit-awesome-table | [
"18a7ad7372aba1163f17134191d784056649bbd8"
] | [
"samples/with_search/__init__.py"
] | [
"import pandas as pd\nimport streamlit as st\nfrom awesome_table import AwesomeTable\nfrom awesome_table.column import (Column, ColumnDType)\nfrom sample import data as sample_data\n\nst.set_page_config(page_title='AwesomeTable by @caiofaar', page_icon='📊', layout='wide')\nst.title('AwesomeTable with Search')\n\nA... | [
[
"pandas.json_normalize"
]
] |
aharley/track_check_repeat | [
"564c3065a758deea11acdcaeea7a187ce376d564"
] | [
"nets/raft_core/backraft.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nimport sys\nsys.path.append('./')\n\nfrom update import BasicUpdateBlock, SmallUpdateBlock\nfrom extractor import BasicEncoder, SmallEncoder\nfrom corr import CorrBlock, AlternateCorrBlock\nfrom util import bilinear_sampler... | [
[
"torch.nn.functional.unfold",
"torch.relu",
"torch.split",
"torch.softmax",
"torch.tanh",
"torch.sum"
]
] |
MGHComputationalPathology/CalicoML | [
"e296f1cc0a78c4bf05e719aae96d8ea2e9d6c03c"
] | [
"tests/test_metrics.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"\\\nCopyright (c) 2015-2018, MGH Computational Pathology\n\n\"\"\"\n\nfrom __future__ import print_function\n\nfrom calicoml.core.metrics import ppv, npv, ROC\nfrom calicoml.core.metrics import compute_averaged_metrics, accuracy_from_confusion_matrix, ConditionalMeansSelector\nfrom... | [
[
"numpy.testing.assert_allclose",
"sklearn.metrics.confusion_matrix",
"numpy.random.normal",
"numpy.random.choice",
"numpy.asarray",
"numpy.random.seed"
]
] |
edwardoughton/e3nb | [
"d03701ba24aad8a723e3e9c138f7f636f7c67573"
] | [
"scripts/los.py"
] | [
"\"\"\"\nExtract CLOS / NLOS lookup.\n\nWritten by Ed Oughton.\n\nMarch 2021\n\n\"\"\"\nimport os\nimport configparser\nimport json\nimport math\nimport glob\nimport random\nimport numpy as np\nimport pandas as pd\nimport geopandas as gpd\nimport pyproj\nfrom shapely.geometry import Point, Polygon, box, LineString\... | [
[
"numpy.ceil",
"numpy.isnan",
"numpy.random.seed",
"numpy.percentile",
"pandas.DataFrame",
"pandas.qcut",
"pandas.read_csv",
"numpy.floor"
]
] |
AroMorin/DNNOP | [
"271e65811fe7cadcffc8155049e256fa78c0c5c6"
] | [
"environments/nao/pose_assumption.py"
] | [
"\"\"\"NAO robot class\"\"\"\n\nfrom .robot import Robot\nimport torch\n\nclass Pose_Assumption(Robot):\n def __init__(self, env_params):\n super(Pose_Assumption, self).__init__(env_params)\n env_params = self.ingest_params2(env_params)\n self.target = env_params[\"target error\"]\n s... | [
[
"torch.tensor"
]
] |
ankitsrao/aws-unused-resources | [
"f155f6f327235b6ceae541b02381f4083369b132"
] | [
"unused_aws_resources.py"
] | [
"\"\"\"\r\nSYNOPSIS\r\n--------\r\n Get the details of unused resources present across regions in the AWS account\r\n\r\nDESCRIPTION\r\n-----------\r\n This script provides a detailed overview of the number of unused resources present in the AWS account. \r\n\tIt provides service-wise details of unused resour... | [
[
"pandas.read_csv",
"pandas.ExcelWriter"
]
] |
doneva593/wifisystem | [
"209c3ca8783f967221fe821993e0368ab96f4398"
] | [
"server/ai/src/naive_bayes.py"
] | [
"import sqlite3\nimport mmap\nimport os\nimport sys\nimport copy\nimport math\nimport tempfile\n\nfrom tqdm import tqdm\nfrom scipy.stats import norm\nfrom expiringdict import ExpiringDict\n\ncache = ExpiringDict(max_len=100000,max_age_seconds=600)\n\ndef get_num_lines(file_path):\n fp = open(file_path, \"r+\")\... | [
[
"scipy.stats.norm.pdf"
]
] |
mvdoc/mne-python | [
"bac50dd08361b10d0a65c614ea2de06308750411",
"bac50dd08361b10d0a65c614ea2de06308750411",
"bac50dd08361b10d0a65c614ea2de06308750411"
] | [
"mne/io/artemis123/artemis123.py",
"examples/decoding/plot_linear_model_patterns.py",
"mne/chpi.py"
] | [
"# Author: Luke Bloy <bloyl@chop.edu>\n#\n# License: BSD (3-clause)\n\nimport numpy as np\nimport os.path as op\nimport datetime\nimport calendar\n\nfrom .utils import _load_mne_locs\nfrom ...utils import logger, warn\nfrom ..utils import _read_segments_file\nfrom ..base import BaseRaw\nfrom ..meas_info import _emp... | [
[
"numpy.zeros"
],
[
"sklearn.linear_model.LogisticRegression",
"sklearn.preprocessing.StandardScaler"
],
[
"numpy.dot",
"scipy.linalg.svd",
"numpy.mean",
"scipy.linalg.pinv",
"numpy.where",
"numpy.cos",
"scipy.optimize.fmin_cobyla",
"numpy.concatenate",
"nump... |
GEM7318/Snowmobile | [
"23631a47e510dfd15bce0e8708f95ebf5734349e"
] | [
"docs/snippets/configuration.py"
] | [
"\"\"\"\n\"\"\"\nimport snowmobile\n\nsn = snowmobile.connect(delay=True)\n\nsn.alive # > False\ntype(sn.con) # > NoneType\n\ntype(sn.cfg) # > snowmobile.core.configuration.Configuration\nstr(sn.cfg) # > snowmobile.Configuration('snowmobile.toml')\n\nprint(sn.cfg.location) # > /path/to/your/snowmobile.toml\n\n... | [
[
"pandas.read_sql"
]
] |
nnassar98/pyleecan | [
"c4fdc6362fdeba3d0766d5d1df3ff9c97c3f9fa3",
"3a6ffe14ab46e90dc0b2855386623833c622b95e"
] | [
"Tests/Plot/test_plots.py",
"Tests/Functions/test_dqh_transformation_freq.py"
] | [
"from os.path import isfile\nfrom os.path import join\n\nimport matplotlib.pyplot as plt\nimport pytest\nfrom SciDataTool import DataTime, Data1D, DataLinspace, VectorField, Norm_ref\nfrom numpy import linspace, sin, squeeze\n\nfrom Tests import TEST_DATA_DIR\nfrom Tests import save_plot_path as save_path\nfrom pyl... | [
[
"numpy.linspace",
"numpy.sin",
"matplotlib.pyplot.close"
],
[
"numpy.array",
"numpy.angle",
"numpy.zeros",
"numpy.exp",
"numpy.abs",
"numpy.linspace"
]
] |
iamacityzen/ga-learner-dsmp-repo | [
"a4c091f4e95504938270906b04426839b63814c3"
] | [
"Making-first-prediction-using-linear-regression/code.py"
] | [
"# --------------\nimport pandas as pd\nimport numpy as np\nfrom sklearn.cross_validation import train_test_split\n# code starts here\ndf = pd.read_csv(path)\ndf.head()\nX = df[['ages','num_reviews','piece_count','play_star_rating','review_difficulty','star_rating','theme_name','val_star_rating','country']]\ny = df... | [
[
"sklearn.metrics.mean_squared_error",
"sklearn.linear_model.LinearRegression",
"matplotlib.pyplot.hist",
"sklearn.metrics.r2_score",
"pandas.read_csv",
"sklearn.cross_validation.train_test_split"
]
] |
OmoooJ/gluon-facex | [
"c5606fc9e2223c6d6dce2aaf2858d83f5eac1d54",
"c5606fc9e2223c6d6dce2aaf2858d83f5eac1d54"
] | [
"examples/mnist/train_mnist_arcloss.py",
"gluonfr/metrics/verification.py"
] | [
"# MIT License\n#\n# Copyright (c) 2018 Haoxintong\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 rights\n# to use, copy, mo... | [
[
"numpy.hstack",
"numpy.vstack"
],
[
"numpy.logical_not",
"numpy.max",
"numpy.array",
"numpy.less",
"scipy.interpolate.interp1d",
"numpy.asarray",
"numpy.zeros",
"numpy.square",
"numpy.linalg.norm",
"numpy.sum",
"numpy.mean",
"numpy.logical_and",
"num... |
jatinchowdhury18/BBDDelay | [
"eb219742ff53b15e11efbaf9bc38b002610cf9b9"
] | [
"sim/filter_design.py"
] | [
"import numpy as np\nimport scipy.signal as signal\nimport matplotlib.pyplot as plt\n\nFS = 48000.0\nFREQ = 9000\nomega = 2 * np.pi * FREQ\n\nr = np.array([251589, -130428 - 4165j, -130428 + 4165j, 4634 - 22873j, 4634 + 22873j])\np = np.array([-46580, -55482 + 25082j, -55482 - 25082j, -26292 - 59437j, -26292 + 5943... | [
[
"numpy.array",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"scipy.signal.freqs_zpk",
"scipy.signal.butter",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"numpy.logspace"
]
] |
ofgulban/meso-MRI | [
"15ef8e19aae6218833a06bf01418d3d83eafd8c7",
"15ef8e19aae6218833a06bf01418d3d83eafd8c7"
] | [
"scripts/wip/anim-test_camera.py",
"scripts/wip/wip-patch_flatten_filtered.py"
] | [
"\"\"\"Test Pyvista camera parameters.\"\"\"\n\nimport os\nimport numpy as np\nimport pyvista as pv\nimport nibabel as nb\n\nFILE = \"/home/faruk/data2/DATA_MRI_NIFTI/derived/sub-04/flattening/sub-04_ses-T2s_segm_rim_CS_LH_v02_borderized_multilaterate_perimeter_chunk_T2star_flat_400x400_voronoi.nii.gz\"\n\nOUTDIR =... | [
[
"numpy.ones"
],
[
"numpy.eye"
]
] |
carlylagrotta/MSI | [
"e958beb5df2a2d1018bbb2f96382b5c99b08c3ef"
] | [
"tests/shock_tube_optimization_shell_six_paramter_fit_test_modified.py"
] | [
"import sys, os\nsys.path.append('../../') #get rid of this at some point with central test script or when package is built\nos.chdir('../../')\n\nimport MSI.simulations.instruments.shock_tube as st\nimport MSI.cti_core.cti_processor as pr\nimport MSI.optimization.matrix_loader as ml\nimport MSI.optimization.opt_ru... | [
[
"numpy.array",
"pandas.read_csv",
"numpy.diag"
]
] |
herupraptono/kevmurphyML | [
"d8e08dbe268d2da9712ef915893984dc830fabea",
"d8e08dbe268d2da9712ef915893984dc830fabea",
"d8e08dbe268d2da9712ef915893984dc830fabea"
] | [
"figureCode/daft/mlpXor.py",
"figureCode/contoursSSEDemo.py",
"figureCode/logregBinarydemo.py"
] | [
"from matplotlib import rc\nrc(\"font\", family=\"serif\", size=12)\nrc(\"text\", usetex=True)\nrc(\"text.latex\", preamble=open(\"macros.tex\").read())\n\n#import daft\n\t\nimport imp\ndaft = imp.load_source('daft', '/Users/kpmurphy/github/daft/daft.py')\n \nimport os\n\npgm = daft.PGM([4, 4], origin=[0, 0])\n\npg... | [
[
"matplotlib.rc"
],
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure",
"numpy.linalg.lstsq",
"numpy.arange",
"numpy.ravel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.contour",
"numpy.meshgrid"
],
... |
mhavasi/edward2 | [
"b630fea94386f7a6413f7d33ce75bb1dbe413d2d",
"b630fea94386f7a6413f7d33ce75bb1dbe413d2d"
] | [
"baselines/imagenet/ensemble.py",
"baselines/imagenet/efficientnet_be_model.py"
] | [
"# coding=utf-8\n# Copyright 2020 The Edward2 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 ... | [
[
"tensorflow.compat.v2.io.gfile.makedirs",
"tensorflow.compat.v2.keras.metrics.SparseCategoricalAccuracy",
"tensorflow.compat.v2.train.Checkpoint",
"tensorflow.compat.v2.reduce_logsumexp",
"tensorflow.compat.v2.concat",
"tensorflow.compat.v2.shape",
"tensorflow.compat.v2.cast",
"num... |
awillats/brian2 | [
"e1107ed0cc4a7d6c69c1e2634b675ba09edfd9fc",
"e1107ed0cc4a7d6c69c1e2634b675ba09edfd9fc",
"e1107ed0cc4a7d6c69c1e2634b675ba09edfd9fc",
"e1107ed0cc4a7d6c69c1e2634b675ba09edfd9fc"
] | [
"brian2/core/functions.py",
"brian2/tests/test_subgroup.py",
"brian2/tests/test_morphology.py",
"brian2/tests/features/base.py"
] | [
"from collections.abc import Mapping\nimport inspect\nimport types\nfrom typing import Callable\n\nimport numpy as np\nimport sympy\nfrom sympy.codegen import cfunctions as sympy_cfunctions\nfrom numpy.random import randn, rand\nfrom sympy import Function as sympy_Function\nfrom sympy import S\n\nimport brian2.unit... | [
[
"numpy.array",
"numpy.asarray"
],
[
"numpy.testing.assert_array_equal",
"numpy.testing.assert_equal"
],
[
"numpy.testing.assert_equal"
],
[
"numpy.array",
"numpy.isnan",
"numpy.abs"
]
] |
kjohi/spark | [
"62bbeff24c2c23f52738738ea8b0a7bd4737aa4b"
] | [
"python/pyspark/pandas/frame.py"
] | [
"#\n# Licensed to the Apache Software Foundation (ASF) under one or more\n# contributor license agreements. See the NOTICE file distributed with\n# this work for additional information regarding copyright ownership.\n# The ASF licenses this file to You under the Apache License, Version 2.0\n# (the \"License\"); yo... | [
[
"pandas.concat",
"numpy.dtype",
"pandas.DataFrame.from_records",
"pandas.DataFrame.info",
"pandas.DataFrame",
"pandas.core.dtypes.inference.is_sequence",
"pandas.core.dtypes.common.infer_dtype_from_object",
"pandas.api.types.is_dict_like",
"pandas.api.types.is_list_like",
"... |
takeitbillykyle/EL2805-Reinforcement-Learning- | [
"ba16f1bff7d6676fcafd2ec19e6d2bcd195ebb1f"
] | [
"Assignment 2/robbing_banks.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport time\nfrom IPython import display\n\n# Implemented methods\nmethods = ['DynProg', 'ValIter'];\n\n# Some colours\nLIGHT_RED = '#FFC4CC';\nLIGHT_GREEN = '#95FD99';\nBLACK = '#000000';\nWHITE = '#FFFFFF';\nLIGHT_PURPLE = '#E8D0FF';\nLIGHT_O... | [
[
"numpy.max",
"numpy.array",
"numpy.linalg.norm",
"numpy.dot",
"numpy.zeros",
"numpy.sum",
"numpy.copy",
"matplotlib.pyplot.figure",
"numpy.sign",
"numpy.argmax",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.show",
"matplotlib.pyplot.gca",
"matplotlib.pyplot... |
JohnMLarkin/pydap | [
"68650ae51d33cc5ac840b307edcc7b70cbb645a6"
] | [
"src/pydap/responses/das.py"
] | [
"\"\"\"The DAS response.\n\nThe DAS response describes the attributes associated with a dataset and its\nvariables. Together with the DDS the DAS response completely describes the\nmetadata of a dataset, allowing it to be introspected and data to be\ndownloaded.\n\n\"\"\"\n\ntry:\n from functools import singledi... | [
[
"numpy.asarray"
]
] |
fastflair/docarray | [
"0bbdbc816b2f4a3b399779f6816875fbc1dfe862"
] | [
"docarray/array/storage/qdrant/helper.py"
] | [
"from typing import List, TYPE_CHECKING\n\nimport numpy as np\nimport scipy.sparse\nfrom qdrant_openapi_client.models.models import Distance\n\nfrom docarray.math.helper import EPSILON\n\nif TYPE_CHECKING:\n from docarray.types import ArrayType\n\n\nclass QdrantStorageHelper:\n @classmethod\n def embedding... | [
[
"numpy.all",
"numpy.random.rand",
"numpy.asarray"
]
] |
tugrabatin/backdoors101 | [
"af12c08280fe59380f74c05e2737eb2e92a80fdf"
] | [
"utils/min_norm_solvers.py"
] | [
"# Credits to Ozan Sener\n# https://github.com/intel-isl/MultiObjectiveOptimization\n\nimport numpy as np\nimport torch\n\n\nclass MGDASolver:\n MAX_ITER = 250\n STOP_CRIT = 1e-5\n\n @staticmethod\n def _min_norm_element_from2(v1v1, v1v2, v2v2):\n \"\"\"\n Analytical solution for min_{c} |... | [
[
"numpy.dot",
"numpy.zeros",
"numpy.sum",
"numpy.min",
"numpy.sort",
"numpy.abs"
]
] |
keithyin/tensorflow-demos | [
"e716eb1469cf8985018dc913cff91fc07fb073e9"
] | [
"one_hot_demo.py"
] | [
"import tensorflow as tf\nif __name__ == '__main__':\n a = tf.constant([[1], [2], [3]], dtype=tf.int64)\n one_hotted = tf.one_hot(a, depth=4)\n print(one_hotted.shape)\n with tf.Session() as sess:\n print(sess.run(one_hotted))"
] | [
[
"tensorflow.constant",
"tensorflow.one_hot",
"tensorflow.Session"
]
] |
unanan/deep-text-recognition-benchmark-mnn-ncnn | [
"7b68ff66c518869897990e9f5fb00dbb7024d614"
] | [
"train.py"
] | [
"import os\nimport sys\nimport time\nimport random\nimport string\nimport argparse\n\nimport torch\nimport torch.backends.cudnn as cudnn\nimport torch.nn.init as init\nimport torch.optim as optim\nimport torch.utils.data\nimport numpy as np\n\nfrom utils import CTCLabelConverter, AttnLabelConverter, Averager\nfrom ... | [
[
"torch.cuda.manual_seed",
"torch.nn.init.constant_",
"numpy.random.seed",
"torch.no_grad",
"torch.optim.Adam",
"torch.nn.CTCLoss",
"torch.nn.init.kaiming_normal_",
"torch.optim.Adadelta",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.cuda.is_available",
"to... |
ufopcsilab/ECGClassification | [
"e45044e98be45becc04b032713a727eec7fb029a"
] | [
"python/qrs/qrs_net.py"
] | [
"#!/usr/bin/python\n# -*- encoding: utf-8 -*-\n\n\"\"\"\n@ide: PyCharm\n@author: Pedro Silva\n@contact: pedroh21.silva@gmail.com\n@created: out-10 of 2019\n\"\"\"\nimport os\n\nimport numpy as np\nimport tensorflow as tf\nimport tensorflow.keras.backend as kback\n\nfrom tensorflow import keras\n\n\nclass QRSNet(obj... | [
[
"tensorflow.keras.layers.Conv1D",
"tensorflow.keras.utils.to_categorical",
"tensorflow.keras.optimizers.SGD",
"numpy.asarray",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.backend.set_value",
"tensorflow.keras.Sequential",
"tensorfl... |
mmccarty/dask | [
"5602876f3389d039aba0d1a860922777843dbcb9",
"5602876f3389d039aba0d1a860922777843dbcb9",
"5602876f3389d039aba0d1a860922777843dbcb9"
] | [
"dask/dataframe/tests/test_shuffle.py",
"dask/array/overlap.py",
"dask/dataframe/io/tests/test_parquet.py"
] | [
"import itertools\nimport multiprocessing as mp\nimport os\nimport pickle\nimport random\nimport string\nimport tempfile\nfrom concurrent.futures import ProcessPoolExecutor\nfrom copy import copy\nfrom functools import partial\nfrom unittest import mock\n\nimport numpy as np\nimport pandas as pd\nimport pytest\n\ni... | [
[
"pandas.to_datetime",
"numpy.datetime64",
"numpy.array",
"pandas.Index",
"pandas.DatetimeIndex",
"numpy.random.seed",
"pandas.DataFrame",
"pandas.date_range",
"pandas.timedelta_range",
"pandas.Timestamp",
"pandas.Categorical",
"pandas.api.types.CategoricalDtype",
... |
Snarp/nostalgebraist-autoresponder | [
"c22e033d5d091361f7f2d5d8cb609bd95077de6e"
] | [
"src/stable_library_code/transformers/gpt_neo/modeling_gpt_neo.py"
] | [
"# coding=utf-8\n# Copyright 2021 The Eleuther AI and HuggingFace Inc. team. 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/lic... | [
[
"torch.nn.Dropout",
"torch.nn.LayerNorm",
"torch.cat",
"torch.nn.Softmax",
"torch.arange",
"tensorflow.train.load_variable",
"torch.nn.CrossEntropyLoss",
"torch.tril",
"torch.from_numpy",
"tensorflow.train.list_variables",
"torch.ones",
"torch.tensor",
"torch.ma... |
076923/cv2-utils | [
"16919450a690870a80c127b41209e338867d3212"
] | [
"cv2u/core/cluster.py"
] | [
"import cv2\nimport numpy as np\nfrom sklearn.cluster import DBSCAN as skDBSCAN\n\n\ndef DBSCAN(src, eps, min_samples):\n arr = cv2.cvtColor(src, cv2.COLOR_BGR2LAB).reshape(-1, src.shape[2])\n clustering = skDBSCAN(eps=eps, min_samples=min_samples).fit(arr)\n labels = clustering.labels_ + 1\n maps = lab... | [
[
"numpy.where",
"numpy.array",
"sklearn.cluster.DBSCAN",
"numpy.asarray"
]
] |
sinemetu1/confidence | [
"a5c46ce72f4de217708358fb12417c032e08c40e"
] | [
"spotify_confidence/examples.py"
] | [
"# Copyright 2017-2020 Spotify AB\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 agr... | [
[
"pandas.DataFrame",
"pandas.date_range",
"numpy.random.binomial",
"pandas.concat"
]
] |
lluciesmith/DeepHalos | [
"ef97438ffde2872047aff078308b0a45e4107522"
] | [
"paper_plots/plot_likelihood.py"
] | [
"import numpy as np\nfrom plots import plots_for_predictions as pp\nimport sys\nsys.path.append('/Users/lls/Documents/mlhalos_code/')\nfrom mlhalos import distinct_colours as dc\nimport matplotlib.pyplot as plt\nfrom pickle import load\n\nc = dc.get_distinct(6)\n\npath = '/Users/lls/Documents/deep_halos_files/mass_... | [
[
"numpy.load"
]
] |
slowy07/tensor2robot | [
"c32179493e2d22bda44f72206d097c59f173dda0",
"c32179493e2d22bda44f72206d097c59f173dda0"
] | [
"research/vrgripper/mse_decoder.py",
"models/regression_model.py"
] | [
"# coding=utf-8\n# Copyright 2021 The Tensor2Robot 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 require... | [
[
"tensorflow.contrib.slim.fully_connected",
"tensorflow.compat.v1.losses.mean_squared_error"
],
[
"tensorflow.compat.v1.summary.histogram",
"tensorflow.compat.v1.losses.mean_squared_error"
]
] |
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