repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
aniketkt/TomoEncoders | [
"88fa8ba5ef4a950362fbce69f9963250a02f5f4d"
] | [
"tomo_encoders/labeling/detect_voids.py"
] | [
"#!/usr/bin/env python3 \n# -*- coding: utf-8 -*- \n\"\"\" \n\"\"\" \n\nfrom scipy.ndimage import label as label_np\nfrom scipy.ndimage import find_objects\nfrom cupyx.scipy.ndimage import zoom as zoom_cp\nimport cupy as cp\nfrom scipy.ndimage import zoom as zoom_np\n# from tensorflow.keras.layers import UpSampling... | [
[
"numpy.asarray",
"numpy.zeros",
"numpy.round",
"scipy.ndimage.label",
"scipy.ndimage.find_objects",
"numpy.sum"
]
] |
deephyper/NASBigData | [
"18f083a402b80b1d006eada00db7287ff1802592"
] | [
"nas_big_data/attn/load_data.py"
] | [
"import os\nimport gzip\nimport numpy as np\nimport h5py\n\nfrom nas_big_data.data_utils import cache_load_data_h5\n\nHERE = os.path.dirname(os.path.abspath(__file__))\n\n\ndef load_data_h5(split=\"train\"):\n\n h5f_path = os.path.join(HERE, \"training_attn.h5\")\n h5f = h5py.File(h5f_path, \"r\")\n\n if s... | [
[
"numpy.concatenate"
]
] |
keithgroup/sGDML | [
"459b61602b4aa73e5a38357e0a28adf470388790"
] | [
"scripts/sgdml_dataset_from_aims.py"
] | [
"#!/usr/bin/python\n\n# MIT License\n#\n# Copyright (c) 2018 Stefan Chmiela\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 r... | [
[
"numpy.array",
"numpy.savez_compressed"
]
] |
michaeljneely/google-research | [
"eb2b142f26e39aac1dcbb768417465ae9d4e5af6"
] | [
"isolating_factors/pose_estimation/run_pose_estimation.py"
] | [
"# coding=utf-8\n# Copyright 2021 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... | [
[
"numpy.median",
"tensorflow.io.read_file",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.clip_by_value",
"tensorflow.stack",
"tensorflow.linalg.trace",
"tensorflow.cast",
"numpy.concatenate",
"numpy.sin",
"tensorflow.shape",
"tensorflow.concat",
"tensor... |
CINPLA/python-neo | [
"0cb572304d7687ba70949a14f93c780dac51c79a"
] | [
"neo/io/elphyio.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nREADME\n=====================================================================================\nThis is the implementation of the NEO IO for Elphy files.\n\nIO dependencies:\n- NEO\n- types\n- numpy\n- quantities\n\n\nQuick reference:\n===============================================... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.empty",
"numpy.zeros",
"numpy.putmask",
"numpy.sum",
"numpy.ones",
"numpy.diff",
"numpy.flipud",
"numpy.where",
"numpy.arange",
"numpy.frombuffer",
"numpy.repeat",
"numpy.hstack",
"numpy.dtype"
]
] |
githuboop/faiss-web-service | [
"a82496179c1beb4b6c9524361513519ff473cc07"
] | [
"src/utils/read_array_from_java.py"
] | [
"import numpy as np\n\n\ndef read_array(input, dimensions):\n array = np.fromfile(input, dtype='>f4')\n return reshape_array(array, dimensions)\n\n\ndef reshape_array(array, dimensions):\n size = array.shape[0]\n cols = dimensions\n rows = size / dimensions\n array = array.reshape((rows, cols))\n ... | [
[
"numpy.matrix",
"numpy.fromfile"
]
] |
CSBUnlimited/Machine-Learning | [
"6f22ba02032507d0ec1620586aacf4d645e5f670"
] | [
"ML in Python & R/Part 2 - Regression/Section 9 - Random Forest Regression/data_preprocessing_template.py"
] | [
"# Data Preprocessing template\n\n# Importing the libraries\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# Importing the dataset\ndataset = pd.read_csv('Data.csv')\nX = dataset.iloc[:, :-1].values\ny = dataset.iloc[:, 3].values\n\n# Splitting the dataset into the Training set and Tes... | [
[
"pandas.read_csv",
"sklearn.cross_validation.train_test_split"
]
] |
bgailleton/TVD_Condat2013 | [
"4bf3ce46f2e973427a4552bb5286126db092f67f"
] | [
"setup.py"
] | [
"from setuptools import setup, Extension\r\nfrom setuptools.command.build_ext import build_ext\r\nimport sys\r\nimport os\r\nimport setuptools\r\n\r\n__version__ = '0.0.1'\r\n\r\n\r\nclass get_pybind_include(object):\r\n \"\"\"Helper class to determine the pybind11 include path\r\n\r\n The purpose of this cla... | [
[
"numpy.get_include"
]
] |
mluessi/mne-python | [
"44a5ef5241a748b2f77c62fdcda6334220c6af45"
] | [
"mne/fiff/tests/test_proj.py"
] | [
"import os.path as op\nfrom nose.tools import assert_true\n\nimport numpy as np\nfrom numpy.testing import assert_array_almost_equal\n\nfrom .. import Raw, pick_types, compute_spatial_vectors\nfrom ..proj import make_projector, read_proj\nfrom ..open import fiff_open\nfrom ... import read_events, Epochs\n\nraw_fnam... | [
[
"numpy.testing.assert_array_almost_equal",
"numpy.sign",
"numpy.ones",
"numpy.corrcoef"
]
] |
StocksandVagabonds/CS122-Booling4Soup | [
"dc9f08853c81ccd65e58b89781b9a2d07ff428de"
] | [
"python/process_constituent_tweets.py"
] | [
"import pandas as pd\nimport json\nimport geopandas as gp\nfrom shapely.geometry import Point, Polygon\nimport numpy as np\nimport util\n\n# Load locations of files\nCD_SHP_PATH = '../static_data/congressional_districts/cb_2019_us_cd116_500k.shp'\nCSV_PATH = '../generated_data/twitter_constituent_data.csv'\nTWEET_U... | [
[
"pandas.json_normalize",
"pandas.concat"
]
] |
RodrigoNeves95/DeepLearningTimeSeries | [
"71fedd962f77ca0fe06f2b494af7c3cb8a3be648"
] | [
"mypackage/MyPackage/models/RNN/TCN.py"
] | [
"import torch.nn as nn\nfrom torch.nn.utils import weight_norm\n\n\nclass Chomp1d(nn.Module):\n def __init__(self, chomp_size):\n super(Chomp1d, self).__init__()\n self.chomp_size = chomp_size\n\n def forward(self, x):\n return x[:, :, :-self.chomp_size].contiguous()\n\n\nclass TemporalBl... | [
[
"torch.nn.ReLU",
"torch.nn.Sequential",
"torch.nn.Dropout2d",
"torch.nn.Conv1d"
]
] |
jordimas/fullstop-deep-punctuation-prediction | [
"b776dc91fee52fe35d4ee4b098678144eea3078c"
] | [
"augmentation.py"
] | [
"import os\r\nimport re\r\nimport codecs\r\nimport pandas as pd\r\n\r\nclass Token(object):\r\n \r\n def __init__(self, literal, output, first_task, second_task):\r\n #Original im Text\r\n self.literal = literal\r\n #lowercased\r\n self.output = output\r\n #daten für satzseg... | [
[
"pandas.isnull"
]
] |
MaxenceLarose/ProstateCancerNomograms | [
"4ff15dccd1f2dbde58d3a21a2e680e909e2e408a"
] | [
"prostate_cancer_nomograms/statistical_analysis/base/logistic_regression.py"
] | [
"from typing import Union\nfrom sklearn.linear_model import LogisticRegression\nimport numpy as np\nimport pandas as pd\n\n\nclass CustomLogisticRegression:\n\n def __init__(self, x: pd.DataFrame, y: pd.DataFrame, positive_label: Union[str, int]):\n self.x = x\n self.y = y\n self.positive_la... | [
[
"sklearn.linear_model.LogisticRegression",
"numpy.array"
]
] |
ratnania/python_games | [
"3e145d0bbf6c29413e126bfaab096ac7f7daf525"
] | [
"src/ex2/main.py"
] | [
"import sys, pygame\nimport numpy as np\nfrom numpy.random import random\n\npygame.init()\n\nsize = width, height = 1000, 800\n\namplitude_max = 4.\namplitude = amplitude_max * random()\nspeed = [amplitude*random(), amplitude*random()]\nblack = 0, 0, 0\n\nscreen = pygame.display.set_mode(size)\ndone = False\nis_blu... | [
[
"numpy.random.random"
]
] |
joshim5/mogwai | [
"917fe5b2dea9c3adc3a3d1dfe41ae33c3ae86f55",
"917fe5b2dea9c3adc3a3d1dfe41ae33c3ae86f55"
] | [
"mogwai/data_loading/msa_datamodule.py",
"mogwai/data/trrosetta_dataset.py"
] | [
"from argparse import ArgumentParser, Namespace\n\nfrom typing import Union\nfrom pathlib import Path\nimport torch\nimport pytorch_lightning as pl\nfrom ..data.msa_dataset import MSADataset, MSAStats\nfrom ..data.trrosetta_dataset import TRRosetta_MSADataset\nfrom ..data.repeat_dataset import RepeatDataset\nfrom .... | [
[
"torch.utils.data.DataLoader"
],
[
"numpy.load",
"torch.stack",
"torch.tensor"
]
] |
cllamb0/dosenet-raspberrypi | [
"ba48aa86fbf8df90093f8c59bc3b16446a98207c"
] | [
"rt_waterfall_D3S.py"
] | [
"from auxiliaries import set_verbosity\nimport time\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nclass Rt_Waterfall_D3S(object):\n \"\"\"\n Class for running the D3S in real-time waterfall mode\n \"\"\"\n \n def __init__(self, \n manager=None, \n verbosity... | [
[
"matplotlib.pyplot.colorbar",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.close",
"numpy.shape",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.draw",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.ylabel",
"numpy.transpose",
"numpy.ndarray.flatten"
]... |
enriczhang/optbinning | [
"918b4b0e0f417edfaf9dd5fc80b3021a355fc3dd",
"918b4b0e0f417edfaf9dd5fc80b3021a355fc3dd"
] | [
"optbinning/scorecard/scorecard.py",
"optbinning/binning/continuous_binning.py"
] | [
"\"\"\"\nScorecard development.\n\"\"\"\n\n# Guillermo Navas-Palencia <g.navas.palencia@gmail.com>\n# Copyright (C) 2020\n\nimport numbers\nimport pickle\nimport time\n\nimport numpy as np\nimport pandas as pd\n\nfrom sklearn.base import BaseEstimator\nfrom sklearn.base import clone\nfrom sklearn.exceptions import ... | [
[
"numpy.max",
"numpy.count_nonzero",
"numpy.zeros",
"numpy.log",
"numpy.rint",
"numpy.min",
"sklearn.utils.multiclass.type_of_target",
"pandas.concat",
"sklearn.base.clone"
],
[
"numpy.max",
"numpy.full",
"numpy.count_nonzero",
"numpy.array",
"numpy.empty... |
entn-at/Parakeet | [
"8505805dadecd12a7047574bc1970bcdb21440ab"
] | [
"parakeet/models/deepvoice3/position_embedding.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.array",
"numpy.arange",
"numpy.power"
]
] |
mkm99/TeamProject_StatsCalculator | [
"81085c1af47f38d3e49b43d667e312016c44ad10"
] | [
"StatisticsFunctions/variance.py"
] | [
"import numpy as np\n\nclass Variance():\n @staticmethod\n def variance(data):\n return np.var(data)"
] | [
[
"numpy.var"
]
] |
tabayashi0117/Score-CAM | [
"ed433453f77808a1169270a79175c6025bd89867"
] | [
"gradcamutils.py"
] | [
"import numpy as np\nimport cv2\nimport matplotlib.pyplot as plt\n\nimport tensorflow as tf\nfrom tensorflow.keras import backend as K\nfrom tensorflow.keras.models import Model\nimport gc\n\ntf.compat.v1.disable_eager_execution()\n\ndef normalize(x):\n \"\"\"Utility function to normalize a tensor by its L2 ... | [
[
"numpy.dot",
"tensorflow.keras.preprocessing.image.load_img",
"numpy.minimum",
"tensorflow.compat.v1.get_default_graph",
"numpy.copy",
"numpy.exp",
"numpy.mean",
"tensorflow.gradients",
"numpy.min",
"tensorflow.keras.applications.vgg16.preprocess_input",
"tensorflow.cas... |
eabarnes1010/controlled_abstention_networks | [
"4519ff710d2562a25045d0a2bdd26b3b6a98fa32"
] | [
"manuscript_code/regression_JAMES/network.py"
] | [
"\"\"\"Regression with abstention network architecture.\"\"\"\n\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.keras.layers import Dense\nfrom tensorflow.keras import regularizers\nfrom tensorflow.keras.models import Sequential\n\n__author__ = \"Elizabeth A. Barnes and Randal J. Barnes\"\n__date__ = ... | [
[
"numpy.warnings.filterwarnings",
"tensorflow.keras.models.Model",
"tensorflow.keras.initializers.RandomNormal",
"tensorflow.keras.initializers.RandomUniform",
"tensorflow.keras.regularizers.l1_l2",
"tensorflow.keras.Input",
"tensorflow.keras.layers.concatenate"
]
] |
kavanase/effmass | [
"835310e69304d98d0ebfbc3724ea96c5b202485d"
] | [
"effmass/analysis.py"
] | [
"#! /usr/bin/env python3\n\"\"\"\nA module for analysing the data contained in a :class:`Segment` object.\n\nContains the :class:`Segment` class and methods for calculating various definitions of the effective mass.\n\"\"\"\n\nimport warnings\nimport numpy as np\nfrom scipy import integrate\nfrom effmass import ext... | [
[
"numpy.dot",
"numpy.exp",
"numpy.multiply",
"numpy.sign",
"numpy.where",
"numpy.linalg.lstsq",
"numpy.divide",
"numpy.concatenate",
"numpy.linalg.norm",
"numpy.arange",
"numpy.polyfit",
"numpy.sqrt",
"numpy.poly1d",
"numpy.append",
"numpy.vstack",
"n... |
Duseong/my_packages | [
"b60d57d882746fff81f2bbe2d2b298d9dbd11170"
] | [
"dsj/plot/Plot_2D.py"
] | [
"'''\nPlot_2D.py\nthis code is designed for plotting CESM output \ncan be used for either finite volume or spectral element (+ regional refinement)\n(1) 2D map plotting (class Plot_2D)\n\nMODIFICATION HISTORY:\n Duseong Jo, 19, JAN, 2021: VERSION 1.00\n - Initial version\n Duseong Jo, 20, JAN, 2021: VERSIO... | [
[
"numpy.copy",
"numpy.min",
"numpy.mean",
"numpy.where",
"numpy.sign",
"numpy.concatenate",
"numpy.max",
"numpy.nanmin",
"numpy.arange",
"numpy.ndim",
"numpy.sqrt",
"numpy.around",
"numpy.log10",
"numpy.nanmax",
"numpy.array",
"numpy.int",
"numpy.... |
khlaifiabilel/torchgeo | [
"33efc2c0ca6ad7a5af9e29ddcedf67265fa8721f"
] | [
"tests/datasets/test_vaihingen.py"
] | [
"# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License.\n\nimport os\nimport shutil\nfrom pathlib import Path\nfrom typing import Generator\n\nimport matplotlib.pyplot as plt\nimport pytest\nimport torch\nimport torch.nn as nn\nfrom _pytest.fixtures import SubRequest\nfrom _p... | [
[
"torch.nn.Identity",
"matplotlib.pyplot.close"
]
] |
13952522076/diffvg | [
"2c5af9ecf470b1c7071e821583e5ba09cb2c4622"
] | [
"pair/realimage/main.py"
] | [
"\"\"\"\npython main.py --learning_rate 0.001 --model ResNetAE --loss l2 --optimizer adam --msg demo1\npython main.py --learning_rate 0.001 --model ViTAE --loss l2 --optimizer adam --msg demo1 --paths 197 --zdim 384\n\"\"\"\nimport argparse\nimport os\nimport logging\nimport datetime\nimport torch\nimport torch.nn ... | [
[
"torch.nn.MSELoss",
"torch.optim.lr_scheduler.CosineAnnealingLR",
"torch.no_grad",
"torch.nn.L1Loss",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.load",
"torch.nn.DataParallel"
]
] |
hritik5102/Awesome-Computer-Vision-Guide | [
"005cd96f6d6c7dacdf1b9b5f5bf56cae3d6cea18"
] | [
"src/20 - Contour/05-Contours Hierarchy.py"
] | [
"import cv2\nimport numpy as np \nimport matplotlib.pyplot as plt \n\n\nimg = cv2.imread('../Images and Videos/contours_hierarchy.png')\ncv2.imshow(\"ori\", img)\ncv2.waitKey(0)\n\nimgray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n\nret1, thresh = cv2.threshold(imgray, 10, 255, cv2.THRESH_BINARY)\n\ncnts, hier = cv2.... | [
[
"numpy.array"
]
] |
skasch/wiremind_ds_test | [
"60080d487ba626a594490f55f38d852efdd8e4d0"
] | [
"wiremind/features.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nThe features module.\n\nExtract useful features for training the model.\n\nCreated by Romain Mondon-Cancel on 2020-09-25 22:26:54\n\"\"\"\n\nimport bisect\nimport functools as ft\nimport logging\nimport random\nimport typing as t\n\nimport pandas as pd\nimport sklearn.model_selecti... | [
[
"pandas.concat"
]
] |
Alexsbuchanan/GmdhPy | [
"770df3815eff87aca360ac39d85a57af63458275"
] | [
"tests/test_neuron.py"
] | [
"# -*- coding: utf-8 -*-\nimport unittest\n\nimport numpy as np\nfrom gmdhpy.neuron import RefFunctionType, CriterionType, PolynomNeuron\n\n\nclass NeuronTestCase(unittest.TestCase):\n\n def test_neuron_ref_function_getter(self):\n try:\n RefFunctionType.get('linear')\n RefFunctionTy... | [
[
"numpy.array"
]
] |
addy1997/python-RRT | [
"93983e17f2e6e93ff79c8f04a86ce28718ba2779"
] | [
"Graph neural network/Plotting_colors.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport itertools\nfrom typing import List\n\nimport matplotlib\nimport matplotlib.colors\nimport matplotlib.pyplot as plt\nimport numpy as np\n\ngreen = \"#2ecc71\"\nblue = \"#3498db\"\npurple = \"#9b59b6\"\nyellow = \"#f1c40f\"\norange = \"#e67e22\"\nred = \... | [
[
"numpy.arange",
"matplotlib.colors.to_rgba",
"matplotlib.colors.to_hex"
]
] |
asakhare/mnist-multi-gpu | [
"3bbd69d852c9029bd3f86ca83786d33b15a54a8d"
] | [
"mnist_multi_gpu_batching_train.py"
] | [
"# Copyright 2017 Norman Heckscher. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the 'License');\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by ... | [
[
"tensorflow.nn.in_top_k",
"tensorflow.train.start_queue_runners",
"tensorflow.constant_initializer",
"tensorflow.nn.conv2d",
"tensorflow.nn.lrn",
"tensorflow.matmul",
"tensorflow.train.get_checkpoint_state",
"tensorflow.reshape",
"tensorflow.local_variables_initializer",
"t... |
daandres/pytorch-lightning | [
"83283fdb208e0f8a3388453e2abd62527cfc493f"
] | [
"pytorch_lightning/accelerators/gpu.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.cuda.set_device",
"torch.cuda.empty_cache",
"torch.cuda.device",
"torch.cuda.device_count"
]
] |
FrankLeeC/MachineLearning | [
"3a927ba35ac9da634ae9334a0d621f8c34d8bac8"
] | [
"gan/mlp/data.py"
] | [
"# -*- coding:utf-8 -*-\n\nfrom PIL import Image\nimport numpy as np\nimport os\n\n'''\n0 black\n255 white\n'''\n\n# shape [1, x*y]\ndef __convert(fname):\n m = np.where(np.array(Image.open(fname))>=50, 255, 0)\n x, y = m.shape\n m = np.reshape(m, (1, x * y))\n return m\n\ndef load(path):\n labels = ... | [
[
"numpy.reshape"
]
] |
devangpatelmks/094_DevangPatel | [
"0da5bf92616284271118db2eab976d8555880f11"
] | [
"LAB3/Lab3_3_Task2.py"
] | [
"# CELL 0\n# Import necessary libraries\n\nimport matplotlib.pyplot as plt\nfrom sklearn.datasets import load_wine\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn import metrics\n\n# CELL 1\n# Load the wine dataset and split the data\n\ndataset = load_wine()\n\nfrom sklearn.model_selection import train_te... | [
[
"sklearn.model_selection.train_test_split",
"sklearn.datasets.load_wine",
"sklearn.naive_bayes.GaussianNB",
"sklearn.metrics.accuracy_score"
]
] |
RishabhSehgal/keras_cv_attention_models | [
"c1e20e45815339d70a987ec7dd9e6f926b4eb21d"
] | [
"keras_cv_attention_models/imagenet/data.py"
] | [
"import tensorflow as tf\nimport tensorflow_datasets as tfds\nfrom tensorflow import keras\nfrom tensorflow.keras.preprocessing.image import img_to_array, array_to_img\n\n\ndef random_crop_fraction(size, scale=(0.08, 1.0), ratio=(0.75, 1.3333333), log_distribute=True, compute_dtype=\"float32\"):\n height, width ... | [
[
"tensorflow.image.central_crop",
"tensorflow.image.random_flip_left_right",
"tensorflow.ones_like",
"tensorflow.reshape",
"tensorflow.image.crop_to_bounding_box",
"tensorflow.sqrt",
"tensorflow.clip_by_value",
"tensorflow.math.sqrt",
"tensorflow.one_hot",
"tensorflow.cast",... |
jiaw-z/DenseMatchingBenchmark | [
"177c56ca1952f54d28e6073afa2c16981113a2af"
] | [
"dmb/modeling/stereo/disp_samplers/utils/patch_match.py"
] | [
"# ---------------------------------------------------------------------------\n# DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch\n#\n# This is a reimplementation of patch match which is written by Shivam Duggal\n#\n# Original code: https://github.com/uber-research/DeepPruner\n# -------... | [
[
"torch.cat",
"torch.arange",
"torch.nn.functional.softmax",
"torch.zeros_like",
"torch.nn.functional.conv3d",
"torch.mean",
"torch.sum"
]
] |
comp-physics/PyCav | [
"d118f64bb318055f751f96f92a52295c3a4edbb5"
] | [
"PyCav/unused/mc.py"
] | [
"import numpy as np\nimport scipy.integrate as sp\nimport matplotlib.pyplot as plt\n\n\nclass integrate:\n def __init__(self):\n pass\n\n\ndef fun(t, y):\n return np.array([y[1] * t, 2 * t * y[0]])\n\n\nif __name__ == \"__main__\":\n t0 = 0.0\n T = 1.0\n y0 = np.array([1.0, 0.0])\n ret = sp... | [
[
"scipy.integrate.solve_ivp",
"numpy.array"
]
] |
jeherr/espaloma | [
"1be88601f7d1307df283b6cd71714c3311e59f74"
] | [
"scripts/perses-benchmark/tyk2/openff-1.2.0/benchmark_analysis.py"
] | [
"\"\"\"\nScript to perform analysis of perses simulations executed using run_benchmarks.py script.\n\nIntended to be used on systems from https://github.com/openforcefield/protein-ligand-benchmark\n\"\"\"\n\nimport argparse\nimport glob\nimport itertools\nimport re\nimport warnings\n\nimport numpy as np\nimport url... | [
[
"numpy.log"
]
] |
tim-learn/ATDOC | [
"857f2c676106b1952333f3f03f42aaff91fa7435"
] | [
"loss.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\nimport math\nimport torch.nn.functional as F\nimport pdb\n\nclass CrossEntropyLabelSmooth(nn.Module):\n \"\"\"Cross entropy loss with label smoothing regularizer.\n Reference:\n Szegedy et al. Rethinking the Ince... | [
[
"torch.nn.LogSoftmax",
"torch.cat",
"numpy.array",
"torch.no_grad",
"torch.pow",
"torch.svd",
"torch.ones",
"torch.cuda.empty_cache",
"torch.ones_like",
"torch.nn.BCELoss",
"torch.log",
"torch.exp",
"torch.mean",
"torch.sum"
]
] |
n8anderson/lux | [
"b971d0ce25d1d64a9641a782d931dbfe0f6c09a0"
] | [
"lux/utils/date_utils.py"
] | [
"# Copyright 2019-2020 The Lux 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 applicabl... | [
[
"pandas.to_datetime",
"pandas.api.types.is_datetime64_any_dtype",
"pandas.api.types.is_period_dtype",
"pandas.DatetimeIndex"
]
] |
PanYicheng/snn_toolbox | [
"79afdc6cf3bc1b31cc57a758754d74c17d5971a6"
] | [
"snntoolbox/simulation/backends/inisim/temporal_mean_rate_tensorflow.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"INI temporal mean rate simulator with Tensorflow backend.\n\nThis module defines the layer objects used to create a spiking neural network\nfor our built-in INI simulator\n:py:mod:`~snntoolbox.simulation.target_simulators.INI_temporal_mean_rate_target_sim`.\n\nThe coding scheme under... | [
[
"numpy.true_divide",
"numpy.float32"
]
] |
sjk0709/PaintCode_classification | [
"0663f68592b7685dc1c1008f6433ae1d60f21dc4"
] | [
"PaintCode_classification/PaintCode_CNN_pytorch/networks/cnn0.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Apr 28 16:38:27 2018\n\n@author: song\n\"\"\"\n\n#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Apr 12 20:49:19 2018\n\n@author: song\n\"\"\"\n\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue April 3 10:56:53 2018\n\n... | [
[
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
mx-e/ev_adoption_analysis | [
"192d38975a03c57cafab1892543981a101554193"
] | [
"data/import_charging_points.py"
] | [
"import sqlite3\nimport pandas as pd\n\ncharging_points = pd.read_csv(\"other/charging_points.csv\", delimiter=';', decimal=',', thousands=' ')\n\n\ndef extract_type(str):\n type_descr = str.split(' ')[0]\n return 'STADT' if type_descr == 'Stadtkreis' or type_descr == 'Kreisfreie' else 'LAND'\n\ndef extract_n... | [
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
mkveerapen/hail | [
"1be33e27de2945ddd3f46eed85c11a301c1d40d2"
] | [
"hail/python/hail/methods/statgen.py"
] | [
"import itertools\nimport math\nimport numpy as np\nfrom typing import Dict, Callable\nimport builtins\n\nimport hail\nimport hail as hl\nimport hail.expr.aggregators as agg\nfrom hail.expr import (Expression, ExpressionException, expr_float64, expr_call,\n expr_any, expr_numeric, expr_locus, ... | [
[
"numpy.copy",
"numpy.isfinite"
]
] |
msakarvadia/dlSoftwareTests | [
"30722c2df7863684491ef6068473da515a7bc679"
] | [
"tensorflow/horovod_mnist.py"
] | [
"#!/usr/bin/env python\nimport argparse,logging,time,sys,os,json\nsys.path.append('..')\nos.environ['TF_CPP_MIN_VLOG_LEVEL'] = '3'\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\nlogger = logging.getLogger(__name__)\n\nimport tensorflow as tf\n\nfrom tensorflow.keras.layers import Dense, Flatten, Conv2D\nfrom tensorflow... | [
[
"tensorflow.keras.metrics.Mean",
"tensorflow.keras.datasets.mnist.load_data",
"tensorflow.GradientTape",
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.keras.layers.Flatten",
"tensorflow.config.experimental.set_memory_growth",
"tensorflow.keras.metrics.SparseCategoricalAccur... |
pzzhang/maskrcnn-benchmark | [
"904090992fe5e0dfe2439fb49faf7f4162d6ba41"
] | [
"maskrcnn_benchmark/engine/inference.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\nimport logging\nimport time\nimport os\n\nimport torch\nfrom tqdm import tqdm\n\nfrom maskrcnn_benchmark.data.datasets.evaluation import evaluate\nfrom ..utils.comm import is_main_process, get_world_size\nfrom ..utils.comm import all_gather\n... | [
[
"torch.device",
"torch.no_grad",
"torch.cuda.synchronize"
]
] |
96lives/matrixlstm | [
"18cc93a795ce132e05b886aa34565a102915b1c6"
] | [
"classification/libs/utils.py"
] | [
"import torch\nimport numpy as np\n\nimport re\nimport itertools\nfrom textwrap import wrap\nimport matplotlib.pyplot as plt\n\n\ndef padding_mask(lengths, batch_size, time_size=None):\n \"\"\"\n Computes a [batch_size, time_size] binary mask which selects all and only the\n non padded values in the input ... | [
[
"numpy.nan_to_num",
"torch.arange",
"torch.max",
"matplotlib.pyplot.figure",
"torch.cumsum"
]
] |
AliLotfi92/InfoMax_VAE | [
"c2f7ba15e4bc18f479948b45bd900e236a6528c7"
] | [
"CIFAR-10/PlainVAE_CNN_CIFAR10.py"
] | [
"\n\nimport torch\nfrom torch.autograd import Variable\nimport torch.nn as nn\nfrom torchvision import datasets, transforms\nfrom torch.utils.data import DataLoader\nimport torch.optim as optim\nimport math\nimport numpy as np\nimport os\nimport torch.nn.functional as F\nimport torch.nn.init as init\nimport matplot... | [
[
"torch.nn.Sigmoid",
"torch.nn.ConvTranspose2d",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.randn",
"torch.nn.functional.binary_cross_entropy"
]
] |
Stefi99R/Geographic-Information-System | [
"bd2ee4f43ed39152b152be5b31086326e6d61df7"
] | [
"app/main.py"
] | [
"import math\nfrom tkinter import *\nfrom tkinter import messagebox, filedialog\nfrom tkinter.font import Font\nfrom tkinter.ttk import Progressbar\nimport geopandas as gpd\nimport numpy as np\nimport shapefile\nfrom descartes import PolygonPatch\nfrom geopandas import GeoDataFrame, points_from_xy\nfrom matplotlib.... | [
[
"numpy.array",
"sklearn.neighbors._ball_tree.BallTree",
"matplotlib.pyplot.close",
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg",
"scipy.spatial.qhull.Delaunay",
"scipy.spatial.qhull.ConvexHull",
"matplotlib.figure.Figure",
"pandas.read_csv",
"matplotlib.backends._backe... |
bennihepp/pybh | [
"bbc684d9290a7685bf137a81e3a5d45b7ee24875"
] | [
"pybh/transforms.py"
] | [
"import numpy as np\nfrom .contrib import transformations\nfrom . import math_utils\n\n\ndef translation_matrix(offset):\n mat = np.eye(4, dtype=offset.dtype)\n mat[:3, 3] = offset\n return mat\n\n\ndef apply_translation(mat, offset):\n offset_mat = translation_matrix(offset)\n print(offset, offset_m... | [
[
"numpy.array",
"numpy.dot",
"numpy.asarray",
"numpy.zeros",
"numpy.copy",
"numpy.eye",
"numpy.diag",
"numpy.transpose",
"numpy.linalg.inv"
]
] |
A-kriti/Amazing-Python-Scripts | [
"ebf607fe39e6d9e61f30ec3439fc8d6ab1f736b9",
"e2272048cbe49b4bda5072bbdd8479739bb6c18d"
] | [
"Message_Spam_Detection/Dataset_Cleaning.py",
"Whatsapp_COVID-19_Bot/covid_bot.py"
] | [
"#importing required libraries\nimport pandas as pd\nimport string \nimport nltk\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransformer\nfrom sklearn.ensemble import RandomForestClassifier\nimport pickle\nimport warnings\nimport re\nwarnings.filter... | [
[
"pandas.read_csv"
],
[
"pandas.DataFrame"
]
] |
dowell666/TALE | [
"f4cdb1ff6eb9bcc5303e30f249cbcecc5148f99b"
] | [
"src/Utils/metric.py"
] | [
"import sklearn\nfrom sklearn.metrics import average_precision_score\nfrom sklearn.metrics import precision_recall_curve\nfrom sklearn.metrics import auc\nimport numpy as np\ndef auprc(ytrue, ypred):\n p, r, t = precision_recall_curve(ytrue, ypred)\n #print (r, len(r), p, t)\n return auc(r,p)\n\n\n\ndef main(yt... | [
[
"numpy.array",
"numpy.matmul",
"sklearn.metrics.precision_recall_curve",
"numpy.sum",
"numpy.load",
"numpy.mean",
"numpy.sqrt",
"numpy.greater",
"sklearn.metrics.auc"
]
] |
muneerqu/Cirq | [
"de0c5e855069bba71e55b070fc9b06f58c07a861",
"de0c5e855069bba71e55b070fc9b06f58c07a861"
] | [
"cirq/testing/consistent_decomposition.py",
"cirq/ion/ion_gates_test.py"
] | [
"# Copyright 2018 The Cirq Developers\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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law o... | [
[
"numpy.testing.assert_allclose"
],
[
"numpy.array",
"numpy.diag",
"numpy.sqrt"
]
] |
bilisun/Vanilla_NER | [
"d7692b0aa12b2640a785b336c6ffdcb1d4fc2cd0"
] | [
"model_seq/TFBase.py"
] | [
"\"\"\"\nAdaptive Asynchronous Temporal Fields Base model\n\"\"\"\n\nimport torch.nn as nn\nimport torch\nfrom torch.autograd import Variable\n\n\nclass BasicModule(nn.Module):\n def __init__(self, in_dim, a_classes, b_classes, mask=None, _type=2, hidden_dim=1000, droprate=0.3):\n super(BasicModule, self)... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.ones",
"torch.nn.ReLU",
"torch.Tensor"
]
] |
mohd-faizy/DataScience-With-Python | [
"13ebb10cf9083343056d5b782957241de1d595f9",
"13ebb10cf9083343056d5b782957241de1d595f9",
"13ebb10cf9083343056d5b782957241de1d595f9"
] | [
"02_Intermediate Python/5-case-study-hacker-statistics/03_determine-your-next-move.py",
"11_python-data-science-toolbox-(part-2)/3-bringing-it-all-together!/04_turning-this-all-into-a-dataframe.py",
"25_Supervised Learning with scikit-learn/03_Fine-tuning-your-model/03-plotting-an-roc-curve.py"
] | [
"'''\n03 - Determine your next move\n\nIn the Empire State Building bet, your next move depends on the number of eyes you\nthrow with the dice. We can perfectly code this with an if-elif-else construct!\n\nThe sample code assumes that you're currently at step 50. Can you fill in the\nmissing pieces to finish the sc... | [
[
"numpy.random.seed",
"numpy.random.randint"
],
[
"pandas.DataFrame"
],
[
"sklearn.metrics.roc_curve"
]
] |
Nihar-21/CTA200 | [
"055851a7d9a55e9bb53e308f79f3d63124016e6c"
] | [
"SURP INTRO PROJECT/myfunctions/Plotting0.py"
] | [
"\nimport matplotlib.pyplot as plt\nfrom matplotlib import ticker\nfrom matplotlib.colors import LogNorm\nimport matplotlib\nimport numpy as np\nget_ipython().run_line_magic('matplotlib', 'inline')\n\n\ndef Plotting0(ebs,aps,Na,stime,i):\n \n t,ax = plt.subplots(1,1,figsize=(7,5))\n extent=[ebs.min(), ebs.m... | [
[
"matplotlib.pyplot.colorbar",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
fanyongkang87/ykfan_utils | [
"de4d27218ddeaaa2dcf5b2434bdc8fb2646ba431"
] | [
"src/ykfan_utils/tflite/tflite_convert.py"
] | [
"import tensorflow as tf\nimport tensorflow.contrib.lite as lite\nfrom tensorflow.python.framework import graph_util\n# from train_models.mtcnn_model_v3 import P_Net_V3, R_Net_V3\n\n\ndef net_freeze(net_factory, model_path, net_name, output_array, tflite_name):\n image_size = 48\n if net_name == \"P_Net\":\n ... | [
[
"tensorflow.get_default_graph",
"tensorflow.Graph",
"tensorflow.Session",
"tensorflow.train.Saver",
"tensorflow.train.get_checkpoint_state",
"tensorflow.gfile.GFile",
"tensorflow.placeholder"
]
] |
iggy12345/emerson_seed_object_detection | [
"121c6fe55fb4c903cb2c05f12077c3940973eadc"
] | [
"pmd_implementation/pauls_files/pmd_implementation/pmd_depth.py"
] | [
"# -*- coding: utf-8 -*-\r\n# pylint: disable=C0103\r\n# pylint: disable=E1101\r\n\r\nprint('Importing libraries')\r\nimport sys\r\nimport time\r\nimport numpy as np\r\nimport tensorflow as tf\r\nimport cv2\r\nfrom random import *\r\nimport argparse\r\n\r\nfrom utils import label_map_util\r\nfrom utils import visua... | [
[
"numpy.hstack",
"numpy.stack",
"numpy.squeeze"
]
] |
MMyheart/euler | [
"d5910cec735daa7b2f94dc7675a376ffc649b128"
] | [
"tf_euler/python/euler_ops/type_ops.py"
] | [
"# Copyright 2020 Alibaba Group Holding Limited. 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# Unle... | [
[
"tensorflow.convert_to_tensor"
]
] |
shrey-bansal/pytorch_geometric | [
"17108a08066b0a73530544d01719b186f2625ef2"
] | [
"torch_geometric/datasets/zinc.py"
] | [
"import os\nimport os.path as osp\nimport shutil\nimport pickle\n\nimport torch\nfrom tqdm import tqdm\nfrom torch_geometric.data import (InMemoryDataset, Data, download_url,\n extract_zip)\n\n\nclass ZINC(InMemoryDataset):\n r\"\"\"The ZINC dataset from the `\"Grammar Variationa... | [
[
"torch.load"
]
] |
wonbeomjang/mobile-hair-segmentation-pytorch | [
"75aa6bee45c5c6034013a51b59df2a5027432260"
] | [
"webcam.py"
] | [
"import cv2\nimport torch\nfrom model.model import MobileHairNet\nfrom config.config import get_config\nimport os\nimport numpy as np\nfrom glob import glob\n\ndef get_mask(image, net, size=224):\n image_h, image_w = image.shape[0], image.shape[1]\n\n down_size_image = cv2.resize(image, (size, size))\n dow... | [
[
"numpy.zeros",
"torch.from_numpy",
"numpy.where",
"torch.cuda.is_available",
"numpy.transpose",
"torch.load"
]
] |
arahosu/edward2 | [
"6fd50d4b9351616c3cd8b5e9224d118ba48c935f"
] | [
"baselines/cifar10/ensemble.py"
] | [
"# coding=utf-8\n# Copyright 2019 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.reduce_logsumexp",
"tensorflow.compat.v2.concat",
"tensorflow.compat.v2.shape",
"tensorflow.compat.v2.enable_v2_behavior",
"tensorflow.compat.v2.math.log",
"tensorflow.compat.v2.nn.softmax",
"tensorflow.compat.v2.convert_to_tensor",
"tensorflow.compat.v2.reduc... |
wrist/streamlit-dsp | [
"c9030dcb04362a062f06809b01351f24ec8ffe25"
] | [
"streamlit_dsp/st_util.py"
] | [
"#!/usr/bin/env python\n\nimport streamlit as st\nimport altair as alt\nimport numpy as np\nimport pandas as pd\n\nimport os\nimport base64\n\ndef st_my_line_chart(xs, ys, columns, xlabel, ylabel, xlim=None, ylim=None, category_name=None):\n df = pd.DataFrame(data=np.array(ys).T,\n index=xs,... | [
[
"numpy.array"
]
] |
Pandinosaurus/imageSeg-3D_topo | [
"86ca52e53f838309132a67f2a3e58cf69d314770"
] | [
"TopologyForceV1/Code/TDFPython/TDFMain_0.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport math\nfrom scipy import misc\n# from mogutda import SimplicialComplex\n\nimport sys\nimport matplotlib.image as mpimg\nimport os\nimport ext_libs.Gudhi as gdh\nimport pd\nimport histo_image as hi\n\n\ndef compute_persistence_2DImg_1DHom(f):\n \"\"\"\n ... | [
[
"matplotlib.pyplot.arrow",
"numpy.where",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.axis",
"numpy.pad",
"numpy.reshape",
"numpy.zeros",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"scipy.misc.imread",
"numpy.random.... |
xu-song/transformers | [
"bf3b555d407585144fcdd08a26bc151e8c8f05ff"
] | [
"examples/pytorch/translation/run_translation.py"
] | [
"#!/usr/bin/env python\n# coding=utf-8\n# Copyright The HuggingFace Team and The 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# ... | [
[
"numpy.where",
"numpy.count_nonzero",
"numpy.mean"
]
] |
jbhangoo/jbhangoo.github.io | [
"dd9ae5238cd493388145f2fd33b8e848295d426a"
] | [
"src/Classify/NaiveBayes.py"
] | [
"from src.Classify.Classifier import Classifier\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.naive_bayes import GaussianNB\nimport joblib\n\nSCALERFILE = \"models/nb_scaler.J\"\nMODELFILE = \"models/nb_model.J\"\n\nclass NaiveBayes(Classifier):\n def __init__(self, X_train, y_train, scaling_f... | [
[
"sklearn.naive_bayes.GaussianNB"
]
] |
georgeliu233/DRLFD_Urban | [
"08e448d50ba0def1f968ba51d5a24053f37a0791"
] | [
"sac.py"
] | [
"import sys\nimport time\nimport warnings\n\nimport numpy as np\nimport tensorflow as tf\nfrom collections import deque\nfrom stable_baselines.common import tf_util, OffPolicyRLModel, SetVerbosity, TensorboardWriter\nfrom stable_baselines.common.vec_env import VecEnv\nfrom stable_baselines.common.math_util import s... | [
[
"tensorflow.exp",
"numpy.ones_like",
"numpy.random.rand",
"numpy.mean",
"tensorflow.control_dependencies",
"tensorflow.global_variables_initializer",
"tensorflow.cast",
"tensorflow.square",
"tensorflow.trainable_variables",
"numpy.log",
"tensorflow.variable_scope",
... |
sebastientourbier/nipype | [
"99c5904176481520c5bf42a501aae1a12184e672",
"99c5904176481520c5bf42a501aae1a12184e672"
] | [
"nipype/interfaces/dipy/simulate.py",
"nipype/utils/matlabtools.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Change directory to provide relative paths for doctests\n >>> import os\n >>> filepath = os.path.dirname( os.path.realpath( __file__ ) )\n >>> datadir = os.path.realpath(os.path.join(filepath, '../../testing/data'))\n >>> os.chdir(datadir)\n\"\"\"\nfrom __future__ import prin... | [
[
"numpy.concatenate",
"numpy.zeros_like",
"numpy.linalg.norm",
"numpy.random.rand",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.ones",
"numpy.random.randn",
"numpy.shape",
"numpy.any",
"numpy.finfo",
"numpy.loadtxt",
"numpy.atleast_1d",
"numpy.clip"... |
pwuertz/openvino | [
"c2e2fdf3fa09c8bcee9041abce0822e1b51c3018",
"c2e2fdf3fa09c8bcee9041abce0822e1b51c3018"
] | [
"inference-engine/ie_bridges/python/sample/style_transfer_sample/style_transfer_sample.py",
"inference-engine/ie_bridges/python/sample/hello_classification/hello_classification.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n# Copyright (C) 2018-2021 Intel Corporation\n# SPDX-License-Identifier: Apache-2.0\nimport argparse\nimport logging as log\nimport sys\n\nimport cv2\nimport numpy as np\nfrom openvino.inference_engine import IECore\n\n\ndef parse_args() -> argparse.Namespace:\n '... | [
[
"numpy.ndarray",
"numpy.clip"
],
[
"numpy.argsort",
"numpy.expand_dims"
]
] |
WangWenhao0716/DomainMix | [
"d4957c6ad06bf90faea44b0091669984ad7fe049"
] | [
"train.py"
] | [
"from __future__ import print_function, absolute_import\nimport argparse\nimport os.path as osp\nimport random\nimport numpy as np\nimport sys\nimport collections\nimport copy\nimport time\nfrom datetime import timedelta\nimport gc\nfrom sklearn.cluster import DBSCAN\n\nimport torch\nfrom torch import nn\nfrom torc... | [
[
"torch.nn.functional.normalize",
"torch.cat",
"torch.cuda.manual_seed_all",
"torch.min",
"torch.max",
"numpy.random.seed",
"torch.optim.Adam",
"torch.manual_seed",
"sklearn.cluster.DBSCAN",
"numpy.sort",
"torch.Tensor",
"torch.nn.DataParallel"
]
] |
JohnlNguyen/multihead-siamese-nets | [
"0cede14601ce1a62bd58abf92a04ad3d7cc3be99"
] | [
"tests/test_recurrent.py"
] | [
"import tensorflow as tf\n\nfrom layers.recurrent import rnn_layer\n\n\nclass TestRNN(tf.test.TestCase):\n\n def testRNNUnidirectionalNetwork(self):\n with self.test_session():\n embedded_x = tf.random_normal([1, 2, 5]) # batch x sentence length x embedding size\n hidden_size = 10\n... | [
[
"tensorflow.random_normal"
]
] |
mikigom/mmgeneration | [
"699c4156141bee0573d67d5385c214ab0398b7ff",
"699c4156141bee0573d67d5385c214ab0398b7ff"
] | [
"mmgen/core/hooks/visualize_training_samples.py",
"mmgen/models/architectures/fid_inception.py"
] | [
"import os.path as osp\n\nimport mmcv\nimport torch\nfrom mmcv.runner import HOOKS, Hook\nfrom mmcv.runner.dist_utils import master_only\nfrom torchvision.utils import save_image\n\n\n@HOOKS.register_module()\nclass VisualizeUnconditionalSamples(Hook):\n \"\"\"Visualization hook for unconditional GANs.\n\n In... | [
[
"torch.no_grad",
"torch.cat"
],
[
"torch.cat",
"torch.nn.functional.avg_pool2d",
"torch.nn.ModuleList",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.functional.interpolate",
"torch.utils.model_zoo.load_url",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.function... |
Bazzaware/AI-Crash-Course | [
"066e4bf62cf76c5ced7b08b249ac4f1379cb11dc"
] | [
"Chapter 06/thompson_sampling.py"
] | [
"# AI for Sales & Advertizing - Sell like the Wolf of AI Street\n\n# Importing the libraries\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport random\n\n# Setting the parameters\nN = 10000\nd = 9\n\n# Building the environment inside a simulation\nconversion_rates = [0.05,0.13,0.09,0.16,0.11,0.04,0.20,0.0... | [
[
"numpy.random.rand",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
jbcdnr/x-transformers | [
"01b8db99d2cb6eba5622de6ebb168a1f8aeeb758"
] | [
"x_transformers/x_transformers.py"
] | [
"import math\nimport torch\nfrom torch import nn, einsum\nimport torch.nn.functional as F\nfrom functools import partial\nfrom inspect import isfunction\nfrom collections import namedtuple\n\nfrom einops import rearrange, repeat, reduce\nfrom einops.layers.torch import Rearrange\n\nfrom entmax import entmax15\n\nfr... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.einsum",
"torch.nn.ModuleList",
"torch.finfo",
"torch.ones",
"torch.nn.functional.pad",
"torch.where",
"torch.nn.LayerNorm",
"torch.nn.Conv1d",
"torch.norm",
"torch.nn.functional.gelu",
"torch.abs",
"torch.nn.init.norma... |
ppapalampidi/HERO_Video_Feature_Extractor | [
"49535050b272251da230d34e5dcb3fbd307a1671"
] | [
"slowfast/extract_feature/extract.py"
] | [
"import torch as th\nimport numpy as np\nfrom video_loader import (\n VideoLoader, clip_iterator, pack_pathway_output)\nfrom video_dataflow import VideoDataFlow, ReadVideo\nfrom dataflow import MultiProcessMapDataZMQ\nfrom torch.utils.data import DataLoader\nimport argparse\nfrom model import build_model\nfrom p... | [
[
"torch.cuda.synchronize",
"numpy.random.seed",
"torch.no_grad",
"torch.manual_seed",
"torch.cuda.HalfTensor",
"numpy.savez",
"torch.utils.data.DataLoader"
]
] |
lucas-ventura/convolutional_occupancy_networks | [
"4f4613d4f27cd88b4b9287eb0b20c43fe3b3efb9"
] | [
"src/data/transforms.py"
] | [
"import numpy as np\nimport open3d as o3d\nimport torch\nimport json\nfrom scipy import spatial\n\n\n# Transforms\nclass PointcloudNoise(object):\n ''' Point cloud noise transformation class.\n\n It adds noise to point cloud data.\n\n Args:\n stddev (int): standard deviation\n '''\n\n def __in... | [
[
"numpy.concatenate",
"torch.rand",
"numpy.array",
"numpy.asarray",
"numpy.zeros",
"numpy.ones",
"numpy.random.randn",
"numpy.nonzero",
"torch.ones",
"scipy.spatial.KDTree",
"torch.randint",
"numpy.random.randint"
]
] |
xiaozw1994/TimeSeries | [
"1d233b0ae61a8eed2fa6876160b5f29b69abdc5f"
] | [
"Examples/capsStrew.py"
] | [
"import os \nimport numpy as np\nimport tensorflow as tf\nfrom utils import reduce_sum\nfrom utils import softmax\nfrom utils import get_shape\nimport config as cfg\nimport time\nfrom keras.utils import np_utils\nimport matplotlib.pyplot as plt\nfrom sklearn import metrics\nimport seaborn as sns\nfrom scipy impor... | [
[
"tensorflow.contrib.layers.batch_norm",
"sklearn.metrics.confusion_matrix",
"tensorflow.contrib.layers.fully_connected",
"tensorflow.contrib.layers.conv2d",
"tensorflow.reshape",
"tensorflow.sqrt",
"tensorflow.tile",
"tensorflow.stop_gradient",
"tensorflow.nn.tanh",
"tensor... |
laurencebho/Sketch-R2CNN | [
"6389eec24d1cfba419d8c75e07873285fcba6fd1"
] | [
"models/sketch_r2cnn.py"
] | [
"from __future__ import division\nfrom __future__ import print_function\nfrom .basemodel import BaseModel\nfrom torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence, PackedSequence\nimport os.path\nimport sys\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n_project_folder_ = ... | [
[
"torch.nn.Linear",
"torch.nn.utils.rnn.PackedSequence",
"torch.nn.LSTM",
"torch.nn.utils.rnn.pad_packed_sequence",
"torch.nn.utils.rnn.pack_padded_sequence"
]
] |
sxnxhxrxkx/nonamechan | [
"4830ee9852b790ae46d66bc1ed356b3f1b0a8404"
] | [
"wc.py"
] | [
"# coding:utf-8\nfrom wordcloud import WordCloud\nfrom bs4 import BeautifulSoup\nimport requests\nimport MeCab as mc\nimport numpy as np\nfrom PIL import Image\nimport os\n\ndef mecab_analysis(text):\n print('mecab_analysis_start')\n t = mc.Tagger (\"-Ochasen\") # + r\"C:\\Program Files (x86)\\MeCab\\dic\\ipa... | [
[
"numpy.array"
]
] |
khanhgithead/TensorNetwork | [
"e12580f1749493dbe05f474d2fecdec4eaba73c5"
] | [
"tensornetwork/backends/symmetric/symmetric_backend_test.py"
] | [
"import numpy as np\nimport pytest\nfrom tensornetwork.backends.symmetric import symmetric_backend\nfrom tensornetwork.backends.numpy import numpy_backend\nfrom tensornetwork.block_sparse.charge import (U1Charge, charge_equal,\n BaseCharge, fuse_charges)\nfrom tensornet... | [
[
"numpy.testing.assert_allclose",
"numpy.random.rand",
"numpy.sign",
"numpy.finfo",
"numpy.imag",
"numpy.full",
"numpy.linalg.norm",
"numpy.divmod",
"numpy.random.randint",
"numpy.arange",
"numpy.conj",
"numpy.prod",
"numpy.array",
"numpy.int",
"numpy.res... |
max-brambach/neural_tube_patterning_paper | [
"cb03634511b31b07ae6fc72a0df6cf8c88674891"
] | [
"rostrocaudal/f2d-kd_oex.py"
] | [
"import OdeSolver as ode\nimport numpy as np\nimport pandas as pd\nimport os\nimport glob\nimport matplotlib.pyplot as plt\nimport tqdm\n\ndef ode_neuralisation(x, a):\n \"\"\"\n Set of ODEs of the rostrocaudal model.\n :param x: list, contains the fb, mb, hb, gsk3 and ct levels at t=i\n :param a: list,... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.savetxt",
"matplotlib.pyplot.close",
"numpy.linspace",
"matplotlib.pyplot.subplots",
"numpy.save",
"numpy.loadtxt",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.show",
"pandas.read_csv",
"numpy.m... |
kairess/MUNIT-Tensorflow | [
"8504f00e70cc0c26df7e589455813f5833ca1eae"
] | [
"utils.py"
] | [
"import tensorflow as tf\nfrom tensorflow.contrib import slim\nfrom skimage import io\nimport os, random\nimport numpy as np\n\n# https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/\n# https://people.eecs.berkeley.edu/~tinghuiz/projects/pix2pix/datasets/\n\nclass ImageData:\n\n def __init__(self, i... | [
[
"tensorflow.trainable_variables",
"tensorflow.shape",
"tensorflow.image.random_flip_left_right",
"numpy.zeros",
"tensorflow.read_file",
"tensorflow.cast",
"tensorflow.random_crop",
"tensorflow.contrib.slim.model_analyzer.analyze_vars",
"tensorflow.image.resize_images",
"ten... |
reidcathcart/toxic_comments | [
"ef04670a48c8194eae87df1ef25f811802f691cd"
] | [
"src/models/keras_model.py"
] | [
"import datetime\nimport numpy as np\nnp.random.seed(89)\nimport pandas as pd\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\n\nfrom keras.models import Model\nfrom keras.layers import Input, Dense, Embedding, SpatialDropout1D, concatenate\nfrom keras.layers impor... | [
[
"numpy.asarray",
"numpy.zeros",
"numpy.random.seed",
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"sklearn.metrics.roc_auc_score"
]
] |
mhun1/transformers | [
"06376fabd7ccc15bf7fa5a4a4a142961a8c41e79"
] | [
"transformers/mlp.py"
] | [
"import torch\n\nfrom torch import nn\n\n\nclass MLP(nn.Module):\n\n \"\"\"Docstring for MLP. \"\"\"\n\n def __init__(self, dim, hidden, dropout_rate):\n \"\"\"TODO: to be defined.\n\n :dim: TODO\n :hidden: TODO\n :dropout_rate: TODO\n\n \"\"\"\n nn.Module.__init__(se... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.GELU",
"torch.nn.Module.__init__"
]
] |
maxtcurie/Parallel_programming | [
"512ac4da0e99d4413e34790edcb255f2e145749e"
] | [
"GPU/python/Matrix.py"
] | [
"import numba\nfrom numba import jit, cuda\nimport numpy as np\n# to measure exec time\nfrom timeit import default_timer as timer \n \nn_loop=10000000\n# normal function to run on cpu\ndef func(a): \n for i in range(n_loop):\n a[i]+= 1 \n \n# function optimized to run on... | [
[
"numpy.ones"
]
] |
guedes-joaofelipe/CaseRecommender | [
"5606db93f0296d0b9b5eeaba2bd48787c5ff5625"
] | [
"caserec/recommenders/rating_prediction/itemknn.py"
] | [
"# coding=utf-8\n\"\"\"\n ItemKNN based on Collaborative Filtering Recommender\n [Rating Prediction]\n\n Literature:\n KAggarwal, Charu C.:\n Chapter 2: Neighborhood-Based Collaborative Filtering\n Recommender Systems: The Textbook. 2016\n https://www.springer.com/br/book/978331... | [
[
"numpy.flatnonzero"
]
] |
douya1997/pytorch-cifar | [
"d5c73f6c1eddf3a2e74cb2dbd0eab6cc6dc4d14b"
] | [
"models/resnet.py"
] | [
"'''ResNet in PyTorch.\n\nFor Pre-activation ResNet, see 'preact_resnet.py'.\n\nReference:\n[1] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun\n Deep Residual Learning for Image Recognition. arXiv:1512.03385\n'''\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nclass Self_Attn(nn.Modul... | [
[
"torch.nn.Linear",
"torch.zeros",
"torch.nn.functional.avg_pool2d",
"torch.nn.Softmax",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.bmm",
"torch.nn.Conv2d",
"torch.nn.functional.relu",
"torch.randn"
]
] |
koonn/bunseki | [
"deb397e40a02bb709825c70c9be81f54449ac195"
] | [
"src_archived/model_nn.py"
] | [
"from keras.callbacks import EarlyStopping\nfrom keras.layers.advanced_activations import PReLU\nfrom keras.layers.core import Activation, Dense, Dropout\nfrom keras.layers.normalization import BatchNormalization\nfrom keras.models import Sequential, load_model\nfrom keras.utils import np_utils\nfrom sklearn.prepro... | [
[
"tensorflow.compat.v1.logging.set_verbosity",
"sklearn.preprocessing.StandardScaler"
]
] |
martinlarsalbert/water_depth | [
"454d99031a79a9a589debbc1e1461ab8de52e5a7"
] | [
"src/visualization/period_plot.py"
] | [
"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nplt.style.use('dark_background')\nimport docs\nimport os.path\n\nimport src.data.water_depth as water_depth\n\ndef plot():\n\n data_depth = water_depth.get()\n \n periods = data_depth[::12]\n df_depth = pd.DataFrame(index=data_de... | [
[
"pandas.DataFrame",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.style.use"
]
] |
Zehui-Lin/DCGAN | [
"94dcb618d034b86c9e91beadb0476c032497a3e7"
] | [
"CelebA/generate_visual_result.py"
] | [
"import os\nimport imageio\nimport glob\ngif_name = 'dcgan.gif'\nfinal_name = 'final.png'\n\ndef creat_gif(result_path, gif_name, duration=0.2):\n filenames = glob.glob(os.path.join(result_path,'image*.png'))\n filenames = sorted(filenames)\n # generate final image\n final_image = filenames[-1]\n fin... | [
[
"tensorflow.data.Dataset.from_tensor_slices",
"matplotlib.pyplot.savefig",
"tensorflow.io.read_file",
"matplotlib.pyplot.figure",
"tensorflow.image.resize",
"matplotlib.pyplot.imshow",
"tensorflow.image.decode_jpeg",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.subplot"
]
] |
duy-maimanh/examples | [
"67ed12fd0adbe22469b6fac916d96e27f02a7330"
] | [
"tensorflow_examples/lite/model_maker/third_party/efficientdet/model_inspect.py"
] | [
"# Copyright 2020 Google Research. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by... | [
[
"numpy.random.rand",
"tensorflow.compat.v1.Graph",
"tensorflow.compat.v1.get_default_graph",
"tensorflow.compat.v1.io.gfile.makedirs",
"tensorflow.compat.v1.RunMetadata",
"tensorflow.compat.v1.reduce_sum",
"tensorflow.compat.v1.placeholder",
"tensorflow.python.client.timeline.Timel... |
oskali/mit_cassandra | [
"522460c29a9bfb6fe16ff85775f52d78d5372233"
] | [
"code/mdp_testing.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nThis file is intended to perform various testing measurements on the output of\n\nthe MDP Clustering Algorithm.\n\nCreated on Sun Apr 26 23:13:09 2020\n\n@author: Amine\n\"\"\"\n#############################################################################\n# Load Libraries\n\n# -*-... | [
[
"pandas.to_datetime",
"numpy.array",
"pandas.isna",
"pandas.DataFrame",
"matplotlib.pyplot.grid",
"sklearn.neighbors.KNeighborsClassifier",
"matplotlib.pyplot.legend",
"numpy.exp",
"matplotlib.pyplot.subplots",
"numpy.arange",
"sklearn.tree.DecisionTreeClassifier",
... |
joshbeal/tensorflow | [
"f67e646bc18caeda4ec722d2922a8ba6daf58bfe"
] | [
"tensorflow/lite/python/util.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.core.protobuf.config_pb2.ConfigProto",
"tensorflow.python.training.saver.export_meta_graph",
"tensorflow.lite.python.op_hint.convert_op_hints_to_stubs",
"tensorflow.python.framework.graph_util.remove_training_nodes",
"tensorflow.lite.python.op_hint.find_all_hinted_output_nodes",
... |
caizhanjin/vnpy | [
"c0886dbd8eba7f506634b1700dfd09b0b098ef26",
"b7c507a90c84a6a3c34831d8daf5f8947b9858d2"
] | [
"vnpy_pro/tools/chart.py",
"vnpy_pro/trader/utility.py"
] | [
"from pyecharts.charts import Line, Grid, Bar, Kline\nimport pyecharts.options as opts\nimport numpy as np\nimport pandas as pd\nimport os\nfrom functools import wraps\n\n\ndef draw_daily_results_chart(daily_df, save_path):\n \"\"\"绘制资金曲线图\"\"\"\n date_list = daily_df.index.values.tolist()\n balance_list =... | [
[
"pandas.DataFrame",
"pandas.read_csv",
"numpy.zeros",
"pandas.concat"
],
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.subplots"
]
] |
llhuii/neptune | [
"36ad049bd5fc0d09c33175b7c1821edf7c18c56a"
] | [
"examples/surface_defect_detection/training_worker/inference.py"
] | [
"import logging\n\nimport numpy as np\n\nfrom neptune.ml_model import load_model\nimport neptune.ml_model\n\nLOG = logging.getLogger(__name__)\n\nif __name__ == '__main__':\n valid_data = neptune.load_test_dataset(data_format=\"txt\")\n\n x_valid = np.array([tup[0] for tup in valid_data])\n y_valid = np.ar... | [
[
"numpy.array"
]
] |
xinyang178/xbot | [
"dad1fc67062dc6fd21802899fd68f7eb91c96569"
] | [
"data/crosswoz/data_process/dst/trade_preprocess.py"
] | [
"import os\nimport bz2\nimport json\nimport random\nimport pickle\nfrom tqdm import tqdm\nfrom functools import partial\n\nimport torch\nfrom torch.utils.data.sampler import Sampler\nfrom torch.utils.data import Dataset, DataLoader\n\nEXPERIMENT_DOMAINS = [\"餐馆\", \"地铁\", \"出租\", \"酒店\", \"景点\"]\n\n\nclass Lang:\n ... | [
[
"torch.multinomial",
"torch.tensor",
"torch.utils.data.DataLoader"
]
] |
UManPychron/pychron | [
"b84c9fd70072f9cbda30abe2c471e64fe3dd75d8"
] | [
"pychron/experiment/automated_run/automated_run.py"
] | [
"# ===============================================================================\n# Copyright 2011 Jake Ross\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.apach... | [
[
"numpy.polyval",
"numpy.linspace",
"numpy.polyfit"
]
] |
akglazer/permute | [
"2ff8f4861fea44ef412ebc6a5304b7570bd6c66c"
] | [
"permute/tests/test_npc.py"
] | [
"from __future__ import (absolute_import, division,\n print_function, unicode_literals)\n\nfrom nose.plugins.attrib import attr\nfrom nose.tools import assert_raises, raises\n\nimport numpy as np\nfrom numpy.random import RandomState\nfrom scipy.stats import norm\n\nfrom ..npc import (fisher,... | [
[
"numpy.concatenate",
"numpy.array",
"scipy.stats.norm.ppf",
"numpy.testing.assert_equal",
"numpy.testing.assert_almost_equal",
"numpy.random.RandomState",
"numpy.linspace"
]
] |
sensorPointCloud/pointCloudFromImage | [
"04ecf793522a5fff86e9f3a9a239f6ac6cd8a7bb"
] | [
"sensor/distance_estimation.py"
] | [
"import numpy as np\nimport mpmath as mp\n\n\ndef rot_z_2d_mpmath(angle_degrees):\n theta = mp.radians(angle_degrees)\n c, s = mp.cos(theta), mp.sin(theta)\n return mp.matrix([[c, -s], [s, c]])\n\n\ndef get_camera_pos_mpmath(config, angle):\n x = config['camera_mount_x']\n y = config['camera_mount_y'... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.sin",
"numpy.degrees",
"numpy.radians",
"numpy.arctan2",
"numpy.cos",
"numpy.deg2rad"
]
] |
shinoyuki222/torch-light | [
"4799805d9bcae82a9f12a574dcf9fdd838c92ee9"
] | [
"seq2seq/data_loader.py"
] | [
"import numpy as np\nimport torch\nfrom torch.autograd import Variable\nimport const\n\nclass DataLoader(object):\n def __init__(self, src_sents, tgt_sents, cuda, batch_size, shuffle=True, evaluation=False):\n self.cuda = cuda\n self.sents_size = len(src_sents)\n self._step = 0\n self... | [
[
"numpy.arange",
"numpy.asarray",
"numpy.random.shuffle",
"torch.from_numpy"
]
] |
MArtinherz/sportsipy | [
"24f4c1d5e3bb8ecc56e21568961588491e9cfd2a"
] | [
"tests/integration/schedule/test_nba_schedule.py"
] | [
"import mock\nimport os\nimport pandas as pd\nimport pytest\nfrom datetime import datetime\nfrom flexmock import flexmock\nfrom sportsipy import utils\nfrom sportsipy.constants import AWAY, WIN\nfrom sportsipy.nba.boxscore import Boxscore\nfrom sportsipy.nba.constants import SCHEDULE_URL\nfrom sportsipy.nba.schedul... | [
[
"pandas.DataFrame",
"pandas.concat"
]
] |
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