repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
anthonyhu/tumblr-sentiment | [
"33607d3662842815e6ae8d4a981b782ec3c485e8"
] | [
"datasets/dataset_utils.py"
] | [
"# Copyright 2016 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.train.Int64List",
"tensorflow.train.BytesList",
"tensorflow.gfile.Open"
]
] |
BiolabHHU/Image-denoising-with-MRFNet | [
"79420d707058de0ac04522d499adef79b5f6fc6e"
] | [
"MRFNETgray/utils.py"
] | [
"import math\nimport torch.nn as nn\nimport numpy as np\nfrom skimage.metrics import peak_signal_noise_ratio, structural_similarity\n\n\ndef weights_init_kaiming(m):\n classname = m.__class__.__name__\n if classname.find('Conv') != -1:\n nn.init.kaiming_normal(m.weight.data, a=0, mode='fan_in')\n el... | [
[
"torch.nn.init.kaiming_normal",
"numpy.rot90",
"numpy.flipud",
"numpy.transpose",
"torch.nn.init.constant"
]
] |
dadepo/spark | [
"8dbb7cb5cc0b6dd6639badedc69310ba4078542b"
] | [
"python/pyspark/sql/pandas/conversion.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.DataFrame.from_records",
"pandas.api.types.is_datetime64tz_dtype",
"pandas.api.types.is_datetime64_dtype",
"numpy.dtype"
]
] |
prise6/smart-iss-posts | [
"fc913078e7fbe6343fd36ec6ca9852322247da5d"
] | [
"iss/clustering/ClassicalClustering.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport os\nimport numpy as np\nfrom iss.clustering import AbstractClustering\nfrom sklearn.decomposition import PCA\nfrom sklearn.cluster import KMeans\nfrom sklearn.cluster import AgglomerativeClustering\nfrom sklearn.metrics import silhouette_samples\nfrom iss.tools import Tools\nfrom ... | [
[
"sklearn.cluster.KMeans",
"sklearn.metrics.silhouette_samples",
"numpy.unique",
"sklearn.manifold.TSNE",
"numpy.mean",
"sklearn.cluster.AgglomerativeClustering",
"numpy.array",
"numpy.where",
"sklearn.decomposition.PCA"
]
] |
mark-rtb/TensorflowTTS | [
"9999bbc39de6e5b7e5ef9aac25c5256c2bf77051"
] | [
"utils/config_manager.py"
] | [
"import subprocess\nimport shutil\nfrom pathlib import Path\n\nimport numpy as np\nimport tensorflow as tf\nimport ruamel.yaml\n\nfrom model.models import AutoregressiveTransformer, ForwardTransformer\nfrom utils.scheduling import piecewise_linear_schedule, reduction_schedule\n\n\nclass ConfigManager:\n \n de... | [
[
"tensorflow.train.Checkpoint",
"numpy.array",
"tensorflow.keras.optimizers.Adam",
"tensorflow.train.CheckpointManager"
]
] |
jaymedina/notebooks | [
"48b982081dfc6df83cb8d9170568149a2dd021cc"
] | [
"notebooks/COS/AsnFile/test_asn.py"
] | [
"#!/usr/bin/env python\n#%%[markdown]\n### From here, you can run the `calcos` pipeline on your new association file.\n##### Running `calcos` is explained in *much* more detail in our [Notebook on running the pipeline](https://github.com/spacetelescope/notebooks/blob/master/notebooks/COS/CalCOS/CalCOS.ipynb)\n\n###... | [
[
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylabel"
]
] |
TheNeuralBit/google-cloud-python | [
"226cdf12f5dd69afb0ef665bb9e897d32d56f4b6"
] | [
"bigquery/tests/unit/test__pandas_helpers.py"
] | [
"# Copyright 2019 Google LLC\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 agreed t... | [
[
"pandas.Series",
"pandas.DataFrame"
]
] |
connesy/hep_ml | [
"41e97d598e621ce323a92a607625213ef9d45a36"
] | [
"hep_ml/losses.py"
] | [
"\"\"\"\n**hep_ml.losses** contains different loss functions to use in gradient boosting.\n\nApart from standard classification losses, **hep_ml** contains losses for uniform classification\n(see :class:`BinFlatnessLossFunction`, :class:`KnnFlatnessLossFunction`, :class:`KnnAdaLossFunction`)\nand for ranking (see :... | [
[
"numpy.take",
"numpy.linspace",
"numpy.sqrt",
"numpy.in1d",
"numpy.cumsum",
"pandas.DataFrame",
"numpy.concatenate",
"numpy.max",
"numpy.mean",
"scipy.sparse.vstack",
"numpy.exp",
"numpy.where",
"numpy.unique",
"numpy.clip",
"numpy.arange",
"numpy.co... |
egivental/resetInterpretability | [
"cb1d62bb89512c3469c641f2082f24c813ab2b26"
] | [
"model/CORELS/CORELS.py"
] | [
"import os\nimport subprocess\nimport sys\nimport numpy as np\nimport pandas as pd\nimport string\nfrom .dataMaker import CorelsDataMake\nimport copy\n\n\n#This method accepts a string which contains a definition of a dictionary \n#it returns a dictionary, which contains certain inputs that correspond to an output\... | [
[
"pandas.DataFrame"
]
] |
gitvicky/tf-pde | [
"9ff131192aa21babc4238bd5d123fedefbf48d9e"
] | [
"Examples/Burgers_test.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Jun 18 16:04:32 2020\n\n@author: Vicky\n\nNeural PDE - Tensorflow 2.X\nTesting with Burgers Equation\n\nPDE: u_t + u*u_x - 0.1*u_xx\nIC: u(0, x) = -sin(pi.x/8)\nBC: Periodic \nDomain: t ∈ [0,10], x ∈ [-8,8]\n\"\"\"\nimport os \nimport numpy a... | [
[
"numpy.hstack",
"numpy.random.choice",
"numpy.sin",
"numpy.real",
"numpy.shape",
"numpy.meshgrid",
"numpy.vstack"
]
] |
suokunlong/spyder | [
"2d5d450fdcef232fb7f38e7fefc27f0e7f704c9a"
] | [
"spyder/plugins/variableexplorer/widgets/arrayeditor.py"
] | [
"# -*- coding: utf-8 -*-\r\n#\r\n# Copyright © Spyder Project Contributors\r\n# Licensed under the terms of the MIT License\r\n# (see spyder/__init__.py for details)\r\n\r\n\"\"\"\r\nNumPy Array Editor Dialog based on Qt\r\n\"\"\"\r\n\r\n# pylint: disable=C0103\r\n# pylint: disable=R0903\r\n# pylint: disable=R0911\... | [
[
"numpy.array",
"numpy.abs"
]
] |
SX-Aurora/mpi4py-ve | [
"aa6b1f97933196f8a485d5d808e89d5a29b58b1c"
] | [
"demo/osu_latency.py"
] | [
"# http://mvapich.cse.ohio-state.edu/benchmarks/\n\nfrom mpi4pyve import MPI\n\ndef osu_latency(\n BENCHMARH = \"MPI Latency Test\",\n skip = 1000,\n loop = 10000,\n skip_large = 10,\n loop_large = 100,\n large_message_size = 8192,\n MAX_MSG_SIZE = 1<<22,\n ):\n\n comm = MPI.COMM_WORLD\n ... | [
[
"numpy.zeros"
]
] |
TheoBuchwald/UCPH-KVM | [
"bf77ad06bc1d7077e3cbcd81854f0fbfcd7323f7"
] | [
"KurtGroup/Kurt/output_processing.py"
] | [
"\nimport subprocess\nimport numpy as np\nfrom typing import List\nfrom chemical_information import AtomicInformation\n\ndef Forward_search_last(file: str, text: str, error: str, quiet: bool = False) -> int:\n \"\"\"Searches from the beggining of the file given to the end where it returns the linenumber of the l... | [
[
"numpy.log",
"numpy.linalg.eigh",
"numpy.prod",
"numpy.array",
"numpy.exp"
]
] |
AdmitHub/cloud | [
"e9e116d462ea5603c3ccac22b22be33d9452ed1a"
] | [
"src/python/tensorflow_cloud/tuner/optimizer_client.py"
] | [
"# Lint as: python3\n# Copyright 2020 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\n#\n# Unl... | [
[
"tensorflow.get_logger"
]
] |
lrgr/imuse-server | [
"b80e1626ad645f63e66efead8f00bbc5af50ac5a"
] | [
"server/scale_exposures.py"
] | [
"import pandas as pd\nimport numpy as np\n\nfrom web_constants import *\nfrom signatures import Signatures, get_signatures_by_mut_type\nfrom project_data import ProjectData, get_selected_project_data\n\nfrom compute_exposures import compute_exposures\n\ndef scale_exposures(chosen_sigs, projects, mut_type, single_sa... | [
[
"pandas.notnull"
]
] |
Apucs/Name-Entity-Recognition | [
"6eadc81871ad615726c82f7a4506baca5b7facee"
] | [
"src/inference.py"
] | [
"import torch\r\nfrom spacy.lang.en import English\r\nfrom build_dataloader import corpus\r\nfrom data import config\r\n\r\n\r\n\r\ndef infer(checkpoint_path, sentence, true_tags=None):\r\n\r\n model = torch.jit.load(checkpoint_path)\r\n model.eval()\r\n # tokenize sentence\r\n nlp = English()\r\n to... | [
[
"torch.LongTensor",
"torch.jit.load"
]
] |
leifdenby/convorg | [
"1a1279c3438fa5283578c30b15bb71686a83f846"
] | [
"convorg/cloudstatistics.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Statistical functions for binary cloud masks. \"\"\"\nimport numpy as np\nimport scipy as sc\n\nfrom skimage import measure\nfrom scipy.spatial.distance import pdist\n\n\n__all__ = [\n 'get_cloudproperties',\n 'neighbor_distance',\n 'iorg',\n 'scai',\n]\n\n\ndef get_cloud... | [
[
"numpy.sum",
"numpy.sqrt",
"numpy.asarray",
"scipy.integrate.trapz",
"numpy.reshape",
"numpy.isnan",
"numpy.arange",
"numpy.sort",
"numpy.ones",
"scipy.stats.mstats.gmean",
"scipy.spatial.distance.pdist",
"numpy.nansum",
"numpy.exp",
"scipy.spatial.cKDTree"
... |
matteonicolo/Forex | [
"efc2ba94417a3c0f9c034cd002242eb37c235cf8"
] | [
"bk_data.py"
] | [
"import sys\r\nsys.path.append(\"C:/Users/GiovanniRocco/Anaconda3/envs/forex\")\r\n\r\nimport time\r\nimport pandas as pd\r\nimport numpy as np\r\nimport json\r\nimport oandapyV20.endpoints.instruments as instruments\r\nfrom oandapyV20 import API\r\nfrom setup import account_id, key, api\r\nimport datetime\r\nfrom ... | [
[
"pandas.DataFrame"
]
] |
AliJahan/examples | [
"ae625ca94ff5b82d7743d4555ddebeb728cc1430"
] | [
"imagenet/main.py"
] | [
"import argparse\nimport os\nimport random\nimport shutil\nimport time\nimport warnings\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.parallel\nimport torch.backends.cudnn as cudnn\nimport torch.distributed as dist\nimport torch.optim\nimport torch.multiprocessing as mp\nimport torch.utils.data\nimport to... | [
[
"torch.nn.CrossEntropyLoss",
"torch.distributed.init_process_group",
"torch.multiprocessing.spawn",
"torch.cuda.set_device",
"torch.load",
"torch.manual_seed",
"torch.nn.DataParallel",
"torch.no_grad",
"torch.cuda.is_available",
"torch.cuda.device_count",
"torch.nn.para... |
yogurfrul/tensorpack | [
"af5864439e22bb63a55eb2349164087e89a2ae6e"
] | [
"tensorpack/dataflow/dataset/cifar.py"
] | [
"# -*- coding: utf-8 -*-\n# File: cifar.py\n\n# Yukun Chen <cykustc@gmail.com>\n\nimport os\nimport pickle\nimport numpy as np\nimport tarfile\nimport six\nfrom six.moves import range\n\nfrom ...utils import logger\nfrom ...utils.fs import download, get_dataset_path\nfrom ..base import RNGDataFlow\n\n__all_... | [
[
"numpy.array",
"numpy.mean",
"numpy.transpose"
]
] |
fcdl94/ICL | [
"9e79abf8b3d45334302c4716ebc1fa9b3119d986"
] | [
"methods/icarl_revgrad.py"
] | [
"from .icarl_da import ICarlDA\nimport torch\nimport torch.nn as nn\nimport numpy as np\nimport logging\n\n\nclass ICarlRG(ICarlDA):\n\n def __init__(self, *args, **kwargs):\n super().__init__(*args, **kwargs)\n self.domain_criterion = nn.BCEWithLogitsLoss()\n self.lam = 0\n self.coun... | [
[
"torch.LongTensor",
"torch.ones",
"torch.zeros",
"torch.tensor",
"torch.nn.BCEWithLogitsLoss",
"numpy.exp",
"numpy.zeros"
]
] |
tjhlp/tests | [
"7407df7dbfdf12a5f69ba7bc8bf8d14131534ac2"
] | [
"numpytest/matplotlib/matplotlib_tjh_02.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\n\nx = np.linspace(-1, 1, 50)\nprint(x)\ny1 = 2 * x + 1\ny2 = x ** 2\nplt.figure(num=1)\n# image\nplt.plot(x, y1, label='linear')\nplt.plot(x, y2, color='red', label='cubic',linestyle='--')\n# limit\nplt.xlim(-1, 2)\nplt.ylim(-2, 3)\nticks = ... | [
[
"matplotlib.pyplot.gca",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.legend",
"numpy.linspace",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
Hhhhhhhhhhao/image-cartoonization | [
"073b51656b96b069496917d212119caad7bf4728"
] | [
"utils/wb_utils.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom skimage import segmentation, color\nfrom joblib import Parallel, delayed\n\n\ndef box_filter(x, r):\n ch = list(x.size())[1]\n \n weight = 1 / ((2*r+1) ** 2)\n\n box_kernel = weight * np.ones((ch, 1, 2*r+1, 2*r+1))\n box_kernel ... | [
[
"torch.normal",
"torch.ones",
"numpy.asarray",
"torch.nn.functional.conv2d",
"torch.from_numpy",
"numpy.ones",
"numpy.shape",
"torch.rand",
"numpy.array"
]
] |
DCMLab/pitchplots | [
"ce29631380bc93e267d6bf62e342d377a9e75f18"
] | [
"static.py"
] | [
"\"\"\"\r\nFunctions for none moving charts\r\n\"\"\"\r\nimport math\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport matplotlib.patches as patches\r\nimport matplotlib\r\n\r\nfrom pitchplots.reader import get_df_short\r\nfrom pitchplots.functions import get_acc, get_ste... | [
[
"pandas.concat",
"matplotlib.colors.LogNorm",
"pandas.Series",
"pandas.isnull",
"matplotlib.patches.RegularPolygon",
"pandas.DataFrame",
"matplotlib.colors.Normalize",
"matplotlib.colorbar.ColorbarBase",
"matplotlib.pyplot.close",
"matplotlib.cm.get_cmap",
"matplotlib.p... |
calum-chamberlain/generalized-phase-detection | [
"9a7ff77fe292c0be6d9dcaaca41f158736f22b73"
] | [
"gpd/helpers/numpy.py"
] | [
"import numpy as np\n\n\ndef sliding_window(data, size, stepsize=1, padded=False, axis=-1, copy=True):\n \"\"\"\n Calculate a sliding window over a signal\n Parameters\n ----------\n data : numpy array\n The array to be slided over.\n size : int\n The sliding window size\n stepsiz... | [
[
"numpy.lib.stride_tricks.as_strided",
"numpy.floor"
]
] |
ryankshah/kymatio | [
"38cead012d1b134843a1dd0d5ea160042037c7da"
] | [
"tests/scattering1d/test_torch_scattering1d.py"
] | [
"import pytest\nimport torch\nfrom kymatio import Scattering1D\nimport math\nimport os\nimport io\nimport numpy as np\n\n\nbackends = []\nskcuda_available = False\ntry:\n if torch.cuda.is_available():\n from skcuda import cublas\n import cupy\n skcuda_available = True\nexcept:\n Warning('... | [
[
"torch.abs",
"torch.ones",
"numpy.allclose",
"numpy.fft.fft",
"torch.zeros",
"torch.sqrt",
"torch.manual_seed",
"torch.randn",
"numpy.load",
"torch.sum",
"torch.from_numpy",
"numpy.fft.ifft",
"torch.cuda.is_available",
"torch.arange",
"torch.allclose",
... |
tkhe/ssd-family | [
"a797ec36fda59549aff54419c105813c33d8cdd3"
] | [
"ssd/modeling/extra_layers/pelee_extra_layers.py"
] | [
"import torch.nn as nn\n\nfrom ssd.layers import Conv2d\n\n\nclass ResBlock(nn.Module):\n def __init__(self, in_channels):\n super(ResBlock, self).__init__()\n\n self.branch1 = nn.Sequential(\n Conv2d(in_channels, 128, kernel_size=1),\n Conv2d(128, 128, kernel_size=3),\n ... | [
[
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.BatchNorm2d"
]
] |
KshitijKarthick/tvecs | [
"bcec2d09045319472036aa7aa03084ca2569b7bb"
] | [
"tvecs/evaluation/evaluation.py"
] | [
"#!/usr/bin/env python2.7\n# -*- coding: utf-8 -*-\n\"\"\"Module to Evaluate T-Vecs model against Human Semantic Similarity Score.\"\"\"\nimport os\nimport codecs\nfrom scipy.stats import pearsonr\nfrom gensim.models import Word2Vec\n\nfrom tvecs.logger import init_logger as log\nfrom tvecs.bilingual_generator impo... | [
[
"scipy.stats.pearsonr"
]
] |
alxyok/ransplacement | [
"9434dbe458b5d1e31be65c976fc693965997d504"
] | [
"trainer.py"
] | [
"# MIT License\n\n# Copyright (c) 2021 alxyok\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, modify, ... | [
[
"torch.set_default_dtype"
]
] |
offroad-robotics/gpr-lib | [
"a5d61c825f22dd3aae8a1107142356d22907474f"
] | [
"examples/ground_truth_2d_example.py"
] | [
"# Copyright (c) 2021, Jeremy Roy\r\n# All rights reserved.\r\n\r\n# Redistribution and use in source and binary forms, with or without\r\n# modification, are permitted provided that the following conditions are met:\r\n# 1. Redistributions of source code must retain the above copyright\r\n# notice, this list of... | [
[
"numpy.array"
]
] |
arssly/openvqa | [
"f10254a05819f813b71337a2ee45b2be09ab8e5d"
] | [
"openvqa/premodels/resnet/preproc.py"
] | [
"import torch\nfrom PIL import Image\nfrom openvqa.premodels.resnet.resnet_model import model, preproc_transform\n\n\ndef preproc_to_feats(image):\n input_tensor = preproc_transform(image)\n input_batch = input_tensor.unsqueeze(0) # create a mini-batch as expected by the model\n\n if torch.cuda.is_availab... | [
[
"torch.no_grad",
"torch.cuda.is_available"
]
] |
VivianYuan12138/python_matplotlib_learning | [
"c1011b8ed850959f66472e2d81b7d41f0623d06b"
] | [
"example/example1.py"
] | [
"# ① 导入库\nimport matplotlib.pyplot as plt #导入matplotlib库中的pyplot子库\n# ② 新建绘图区\nfig, ax = plt.subplots(figsize=(6,4)) #指定绘图区大小为6*4英寸\nplt.rcParams['font.sans-serif'] = ['SimHei'] #设置显示中文字体（黑体）\n# ③ 准备数据\nseazons=['一季度', '二季度', '三季度','四季度'] #设置分类轴显示文本\nsales=[2780,1950,2680,2120] #设置某产品的销售量数据\nindex=[0,1,2,3] #index控... | [
[
"matplotlib.pyplot.text",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]... |
cikrhazo/FERSNet | [
"a5d9d2e71cf4e4026012f4c2cca7db6a11d162f9"
] | [
"network.py"
] | [
"import torch\nimport torch.nn as nn\nfrom LeakyUnit import LeakyUnit\nfrom net_utlz.blocks import BasicBlock, conv1x1, UNetUp, Transform\n\ncfg = {\n 'VGG13': [(64, 64), (64, 64), 'D1:128, 64',\n (128, 128), (128, 128), 'D:128, 64',\n (256, 128), (256, 256), 'D:256, 128',\n ... | [
[
"torch.nn.ZeroPad2d",
"torch.nn.ConvTranspose2d",
"torch.cat",
"torch.randn",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.LeakyReLU",
"torch.nn.InstanceNorm2d",
"torch.nn.BatchNorm2d",
... |
arekmula/skull_stripping | [
"d03cef81392f8cd243dc1c6d32ffa897af922eb2"
] | [
"tf_implementation/experiments/show_slices_from_generator.py"
] | [
"from argparse import ArgumentParser\nfrom pathlib import Path\nfrom matplotlib import pyplot as plt\n\nfrom segmentation.dataset import scans_generator\n\n\ndef main(args):\n train_path = Path(args.train_dir_path)\n val_path = Path(args.val_dir_path)\n\n train_scans, val_scans, train_samples, val_samples ... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
nng555/fairseq | [
"c9730a125825a85f33042e1b9fd1959b8ca829e5"
] | [
"scripts/wilcox_test.py"
] | [
"import os\nimport argparse\nimport time\nimport copy\nimport numpy as np\nfrom scipy.stats import wilcoxon, mannwhitneyu\n\nimport hydra\nimport omegaconf\nfrom omegaconf import DictConfig\nfrom hydra import slurm_utils\n\n@hydra.main(config_path='/h/nng/conf/robust/config.yaml', strict=False)\ndef display_results... | [
[
"scipy.stats.wilcoxon",
"numpy.average"
]
] |
hgfe/DCSSR | [
"949359eeab248a220834f49ab238dbbf93e656d5"
] | [
"utils.py"
] | [
"from PIL import Image\nimport os\nfrom torch.utils.data.dataset import Dataset\nfrom torchvision.transforms import ToTensor\nimport random\nimport torch\nimport numpy as np\nfrom skimage import measure\nfrom torch.nn import init\n\nclass TrainSetLoader(Dataset):\n def __init__(self, dataset_dir, cfg):\n ... | [
[
"torch.abs",
"numpy.ascontiguousarray",
"numpy.squeeze",
"numpy.array",
"torch.nn.init.xavier_normal"
]
] |
ContinuumIO/chaco | [
"e4a42b91cb25ef7191fd465caaef2c3256fc668e",
"e4a42b91cb25ef7191fd465caaef2c3256fc668e"
] | [
"chaco/tests/create_2d_test_case.py",
"examples/demo/edit_line.py"
] | [
"from __future__ import with_statement\n\nfrom chaco.api import Plot, ArrayPlotData\n\nfrom traits.api import HasTraits, Instance\nfrom enable.component_editor import ComponentEditor\nfrom traitsui.api import Item, View\n\nimport numpy as np\n\nimport nose\nfrom _tools import store_exceptions_on_all_threads, assert... | [
[
"numpy.linspace",
"numpy.arange",
"numpy.ones",
"numpy.meshgrid",
"numpy.zeros"
],
[
"scipy.special.jn",
"numpy.linspace"
]
] |
ph-u/CMEECourseWork_pmH | [
"8d52d4dcc3a643da7d55874e350c18f3bf377138"
] | [
"Week7/Code/LV2.py"
] | [
"#!/bin/env python3\n\n# Author: ph-u\n# Script: LV2.py\n# Desc: Consumer-Resource cycle plotting\n# Input: python3 LV2.py\n# Output: 1. two graphical outputs in `results` subdirectory; 2. final numbers terminal output\n# Arguments: 0\n# Date: Nov 2019\n\n\n\"\"\"Consumer-Resource cycle plotting\"\"\"\n\n__appname_... | [
[
"scipy.linspace",
"matplotlib.pylab.grid",
"matplotlib.pylab.legend",
"matplotlib.pylab.text",
"matplotlib.pylab.title",
"scipy.integrate.odeint",
"matplotlib.pylab.figure",
"matplotlib.pylab.ylabel",
"matplotlib.pylab.plot",
"scipy.array",
"matplotlib.pylab.xlabel"
]... |
Zhangzhicheng001/Danim | [
"c45addc3d7679b7adb4a2cfd241c2247ce0a6669"
] | [
"Danim/BubbleChart/bubble_constants.py"
] | [
"# for SPECIFIC_COLORS only\nimport pandas as pd\n\nimport numpy as np\nfrom manimlib.constants import *\n\n\n#-----------data settings 输入数据设置------------#\n#************************************************#\n\nDATA_DIR = \"manim\\\\Danim\\\\DATA\"\nfile_name_list = [\"X.csv\",\"Y.csv\",\"R.csv\"]\nX_file_name = \... | [
[
"numpy.array"
]
] |
FofanovLab/VaST | [
"72670bfc1fed6418eb9bbc7123d864a91fa63173"
] | [
"VaST/Amplicon_Filter.py"
] | [
"import itertools as it\nimport logging\nfrom collections import namedtuple\n\nimport numpy as np\nimport pandas as pd\n\nfrom Pattern import Patterns\nfrom utils import AMBIGUOUS_DICT\n\nAmplicon = namedtuple('Amplicon', ['start', 'stop', 'genome', 'site_ids'])\n\n\nclass AmpliconFilter:\n def __init__(\n ... | [
[
"numpy.unique",
"pandas.DataFrame",
"numpy.setdiff1d",
"numpy.all",
"numpy.any",
"numpy.array",
"numpy.sum"
]
] |
microsoft/AR2 | [
"c8df9379e0f7d50f9f52aa34982908c88b408a24"
] | [
"AR2/wiki/co_training_wiki_train.py"
] | [
"from os.path import join\nimport sys\n\nsys.path += ['../']\nimport argparse\nimport glob\nimport json\nimport logging\nimport os\nimport random\nimport numpy as np\nimport torch\n\nsys.path.append(os.getcwd())\nsys.path.append(os.path.abspath(os.path.dirname(os.getcwd())))\n# \nfrom torch.utils.data import DataL... | [
[
"torch.nn.functional.softmax",
"torch.serialization.default_restore_location",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device",
"torch.distributed.get_rank",
"torch.nn.CrossEntropyLoss",
"torch.distributed.init_process_group",
"torch.utils.data.distributed.Distribute... |
Berkeley-Data/hpt | [
"65bd3cedee83d43fdc8b57646dcd2e2642ddee30"
] | [
"src/utils/plot_basetrain_robust.py"
] | [
"\nimport glob\nimport shutil\nimport sys\nimport json\nimport pandas as pd\nimport argparse \nfrom matplotlib import pyplot as plt\nfrom matplotlib.ticker import NullFormatter # useful for `logit` scale\nimport seaborn as sns\nimport os \n\ndir_path = os.path.dirname(os.path.realpath(__file__))\n\ndef parse_args(... | [
[
"pandas.concat",
"matplotlib.pyplot.axhline"
]
] |
ankycheng/damages-calculator | [
"9ad958cd50911aef83ac92206950d9e29ab6e6a3"
] | [
"charts.py"
] | [
"import calculateTool.legaltechDataProcess as ltp\nimport jieba.analyse\nimport jieba\nimport pandas as pd\nimport numpy as np\nimport nltk\nfrom collections import Counter\nimport re\nimport seaborn as sns\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom matplotlib.font_manager import findfont, FontProper... | [
[
"matplotlib.font_manager.fontManager.ttflist.extend",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.title",
"matplotlib.use",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ylabel",
"matplotlib.font_manager.createF... |
iver56/keras-retinanet | [
"83feca1aa49a8a75ed5d4a2ab43d8c18c6cce3f7"
] | [
"keras_retinanet/bin/evaluate.py"
] | [
"#!/usr/bin/env python\n\n\"\"\"\nCopyright 2017-2018 Fizyr (https://fizyr.com)\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 ... | [
[
"tensorflow.ConfigProto",
"tensorflow.Session"
]
] |
metataro/sc2_imitation_learning | [
"8dca03e9be92e2d8297a4bc34248939af5c7ec3b"
] | [
"tests/test_behaviour_cloning_learner.py"
] | [
"import tensorflow as tf\nimport numpy as np\n\nfrom sc2_imitation_learning.behaviour_cloning.learner import compute_correct_predictions, compute_neg_log_probs\n\n\nclass Test(tf.test.TestCase):\n def test_compute_correct_predictions(self):\n targets = np.asarray([0, -1, 1, -1])\n predictions = np.... | [
[
"numpy.asarray",
"tensorflow.math.log_softmax"
]
] |
bsaleil/lc | [
"ee7867fd2bdbbe88924300e10b14ea717ee6434b"
] | [
"tools/graphs.py"
] | [
"#!/usr/bin/env python3\n#!/usr/bin/python3\n#---------------------------------------------------------------------------\n#\n# Copyright (c) 2015, Baptiste Saleil. All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the follo... | [
[
"matplotlib.backends.backend_pdf.PdfPages"
]
] |
leomi7/flower-recognition | [
"f7fd167aa8000bb9c2ddd2f9dd1f2e120dff1fa8"
] | [
"extract_features.py"
] | [
"# filter warnings\nimport warnings\n\nwarnings.simplefilter(action=\"ignore\", category=FutureWarning)\n\n# keras imports\nfrom keras.applications.vgg16 import VGG16, preprocess_input\nfrom keras.applications.vgg19 import VGG19, preprocess_input\n\nfrom keras.applications.resnet50 import ResNet50, preprocess_input... | [
[
"numpy.array",
"sklearn.preprocessing.LabelEncoder",
"numpy.expand_dims"
]
] |
omersan/LSTM_Nudging | [
"35c8f294708336a28f33b4be93a82d80f2f3d99c"
] | [
"Nudging/plotting_field.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Apr 14 19:17:22 2020\n\n@author: suraj\n\"\"\"\n\nimport numpy as np\nfrom numpy.random import seed\nseed(1)\nfrom scipy import integrate\nfrom scipy import linalg\nimport matplotlib.pyplot as plt \nimport time as tm\nimport matplotlib.ticker ... | [
[
"numpy.random.seed",
"matplotlib.pyplot.rc",
"matplotlib.pyplot.subplots",
"numpy.load",
"matplotlib.pyplot.show",
"matplotlib.pyplot.cm.ScalarMappable"
]
] |
gddickinson/VolumeSlider | [
"bdde0e6e18741f1b11481fe9ae7dba6c0f571acc"
] | [
"volumeSlider/tiffLoader.py"
] | [
"import numpy as np\nfrom qtpy import QtWidgets, QtCore, QtGui\nimport flika\nfrom flika import global_vars as g\nfrom flika.utils.io import tifffile\nfrom flika.process.file_ import get_permutation_tuple\nfrom flika.utils.misc import open_file_gui\nfrom distutils.version import StrictVersion\nfrom flika.window imp... | [
[
"numpy.transpose"
]
] |
MacuXavier/S1_ML_Practices | [
"4cd29c5537c95cfd940e13e741db8d363c57ab1d"
] | [
"CIFAR10/train.py"
] | [
"import os\nimport os.path as osp\n# third-party packages\nimport pyprind\nimport glog as log\n# pytorch related packages\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torchvision.transforms as T\nimport torchvision.datasets as datasets\nimport argparse\n# Model Definition\nfrom mode... | [
[
"torch.nn.CrossEntropyLoss",
"torch.load",
"torch.manual_seed",
"torch.no_grad",
"torch.save"
]
] |
ankeshanand/Rainbow | [
"cb89a0f2794381973daaa9b66cd8924111291b78"
] | [
"memory.py"
] | [
"from collections import namedtuple\nimport numpy as np\nimport torch\n\nTransition = namedtuple('Transition', ('timestep', 'state', 'action', 'reward', 'nonterminal'))\nblank_trans = Transition(0, torch.zeros(84, 84, dtype=torch.uint8), None, 0, False)\n\n\n# Segment tree data structure where parent node values ar... | [
[
"numpy.power",
"torch.zeros",
"torch.cat",
"torch.tensor",
"torch.stack",
"numpy.random.uniform",
"numpy.array",
"numpy.zeros",
"torch.device"
]
] |
jni/useful-histories | [
"0c75003e4fa3a80d4bf7281314cdf6e363d3be56"
] | [
"climate-change-model-test.py"
] | [
"# IPython log file\n\n\nT = pd.read_csv('bundoora-temp.csv')\nT.head()\nT.rename(columns={'Mean maximum temperature (°C)':'Temperature'},\n inplace=True)\n \nT['Date'] = T['Year'] + (T['Month'] - 0.5) / 12\ndates = T['Date']\ntemps = T['Temperature']\ndef predicted_temperature(parameters, time):\n ... | [
[
"scipy.optimize.leastsq",
"scipy.stats.chi2.sf"
]
] |
Oktai15/NeMo | [
"5b6dd3850129898be47cf0d65587897ec45a5b59"
] | [
"nemo/collections/asr/models/ctc_models.py"
] | [
"# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless re... | [
[
"torch.no_grad",
"torch.cuda.is_available"
]
] |
localmonkey/rosalind | [
"dceab11d4938c1325075988be091abd3a5d25824"
] | [
"algorythmic_heights/bf/bf.py"
] | [
"import queue\nimport numpy as np\n\n\nclass myGrph:\n def __init__(self, vertex_quant, edges_quant):\n self.V_quant = vertex_quant\n self.E_quant = edges_quant\n self.edges_list = np.zeros((edges_quant, 3), dtype=np.int64)\n #self.edge_list = []\n\n def fill_connections(self, file... | [
[
"numpy.zeros",
"numpy.full"
]
] |
Fieps1/p3-tennis | [
"29f3dab5810d7cd7f84120416a615956d266c256"
] | [
"deep_rl/component/envs.py"
] | [
"#######################################################################\n# Copyright (C) 2017 Shangtong Zhang(zhangshangtong.cpp@gmail.com) #\n# Permission given to modify the code as long as you keep this #\n# declaration at the top #\n#######################... | [
[
"numpy.clip",
"numpy.asarray",
"numpy.full",
"numpy.concatenate",
"numpy.ones",
"numpy.random.rand",
"numpy.prod",
"numpy.array"
]
] |
YOHNGGG/Deep-Learning-based-Spectrum-Sensing | [
"e3b17ea30020db5ccf753497ce00a0fdf3ffa342"
] | [
"Python/SignalLoader_Test.py"
] | [
"import torch\r\nimport os, glob\r\nimport random\r\nimport csv\r\nfrom torch.utils.data import Dataset,DataLoader\r\nfrom scipy.io import loadmat\r\n\r\nclass LoadSignal(Dataset):\r\n\r\n def __init__(self,root):\r\n super(LoadSignal, self).__init__()\r\n\r\n self.root = root\r\n\r\n self.n... | [
[
"scipy.io.loadmat",
"torch.utils.data.DataLoader",
"torch.unsqueeze",
"torch.tensor"
]
] |
JungeAlexander/cocosco | [
"81ba561f6f16b43cfbd1b6d119e042bb640da23d"
] | [
"tests/ml/feature/test_glove.py"
] | [
"import numpy as np\n\nimport cocoscore.ml.feature.glove as glove\n\n\nclass TestClass(object):\n test_vec_file = 'tests/ml/feature/vectors.txt.gz'\n test_vocab_file = 'tests/ml/feature/vocab.txt.gz'\n\n def test_load_vector_array(self):\n w, w2i, i2w = glove.load_vector_array(self.test_vec_file, se... | [
[
"numpy.array"
]
] |
SamanKhamesian/Music-Genre-Classification-of-Audio-Signals | [
"10b29b91738b25138cc9916ae174e4cd5027c759"
] | [
"Source/Classification.py"
] | [
"import joblib\nimport sklearn\n\nfrom Source.Utilities import *\nfrom config import Test, Model\n\nPATH = librosa.util.find_files(Test.DATA_PATH)\n\n\ndef main():\n songs = []\n\n # Load Test Files\n for p in PATH:\n song, sr = librosa.load(p, sr=SAMPLING_RATE, duration=5.0)\n songs.append(s... | [
[
"sklearn.preprocessing.MinMaxScaler"
]
] |
eliadl/textdistance | [
"bbba2eb9660aa0b360ad54ef7aa5a8348d9a9924"
] | [
"textdistance/algorithms/edit_based.py"
] | [
"# built-in\nfrom collections import defaultdict\n\n# app\nfrom .base import Base as _Base, BaseSimilarity as _BaseSimilarity\n\n\ntry:\n # python3\n from itertools import zip_longest\nexcept ImportError:\n # python2\n from itertools import izip_longest as zip_longest\ntry:\n import numpy\nexcept Imp... | [
[
"numpy.arange",
"numpy.zeros"
]
] |
StanfordASL/sensitivity_torch | [
"0601c30c21f6d3acfb5dea9ae4f98a42d8101cab"
] | [
"sensitivity_torch/utils.py"
] | [
"##^# ops import and utils ######################################################\nimport os, pickle, time as time_module, pdb, math\nfrom pprint import pprint\nfrom collections import OrderedDict as odict\nfrom operator import itemgetter\n\nimport torch, numpy as np\nfrom torch.utils.tensorboard import SummaryWrit... | [
[
"torch.mean",
"torch.norm",
"torch.sum",
"torch.std",
"torch.utils.tensorboard.SummaryWriter",
"numpy.array",
"torch.as_tensor"
]
] |
vdutell/wavelet_stim | [
"5a0026220a9d72365983cd66b796bb1a32f3d326"
] | [
"utils/getstim.py"
] | [
"import numpy as np\n\nimport utils.imtools as imtools\nimport utils.fouriertools as ftools\nimport utils.wavelettools as wtools\nimport utils.imwritetools as imwtools\nimport pathlib\n\ndef step_stim_img(width_px, height_px, loc=0.5, stepdn=False, rescale=True, orient=1, contrast=1):\n '''\n Make a step func... | [
[
"numpy.ones_like",
"numpy.shape",
"numpy.zeros",
"numpy.ones"
]
] |
kourtneyshort/healthcare | [
"7d3d4dc9deb3d31eab99035780ccb9a44f00b687"
] | [
"datathon/datathon_etl_pipelines/mimic_cxr/prepare_mimic_cxr.py"
] | [
"r\"\"\"Load the MIMIC CXR dataset onto GCP.\n\nThe raw MIMIC CXR dataset is originally hosted by Physionet as a collection of\ntar files which contain JPG images, and a gzip'd CSV file of labels.\n\nThe JPG images have paths of the form:\n(train|valid)/p([0-9]+)/s([0-9]+)/view([0-9]+)_(frontal|lateral|other)\\.jpg... | [
[
"tensorflow.io.gfile.GFile",
"tensorflow.io.gfile.glob",
"tensorflow.train.Features"
]
] |
OscarPalominoC/linearRegression | [
"8b601b173bf4785f076aa9f2e4ab9acde738ad24"
] | [
"linearRegression.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\n# Función para hallar b0 y b1\ndef estimate_b0_b1(x, y):\n n = np.size(x)\n \n # Obtenemos los promedios de X y de Y\n m_x, m_y = np.mean(x), np.mean(y)\n \n # Calculando la sumatoria de XY y sumatoria de X*Xprom\n sumatoria_XY = np.sum((x... | [
[
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.plot",
"numpy.size",
"numpy.mean",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"numpy.sum",
"matplotlib.pyplot.ylabel"
]
] |
TimRepke/openTSNE | [
"22c306c3ec087e4b4be364431bc3626190a85c86"
] | [
"openTSNE/callbacks.py"
] | [
"import logging\nimport time\nimport warnings\nfrom functools import partial\n\nimport numpy as np\nfrom scipy.sparse import csr_matrix\n\nfrom openTSNE import kl_divergence\nfrom openTSNE.tsne import TSNEEmbedding\n\nlog = logging.getLogger(__name__)\n\n\nclass Callback:\n def optimization_about_to_start(self):... | [
[
"numpy.std",
"numpy.array",
"numpy.mean",
"numpy.sum"
]
] |
georgenemo/Paddledy | [
"cc2d4e869d2bc045bf30cd3494df7e9dd689f0c6"
] | [
"python/paddle/nn/layer/conv.py"
] | [
"# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless ... | [
[
"numpy.prod"
]
] |
Kunind/building-controls-simulator | [
"7d3b74539233cfe5e2983f2f7554afd1bbbacbe9"
] | [
"src/python/BuildingControlsSimulator/DataClients/GCSDYDSource.py"
] | [
"# created by Tom Stesco tom.s@ecobee.com\n\nimport logging\n\nimport attr\nimport pandas as pd\nimport numpy as np\nimport gcsfs\n\nfrom BuildingControlsSimulator.DataClients.GCSDataSource import GCSDataSource\nfrom BuildingControlsSimulator.DataClients.DataSpec import DonateYourDataSpec\n\n\nlogger = logging.getL... | [
[
"pandas.read_csv",
"pandas.to_datetime",
"numpy.any"
]
] |
ah4d1/anoapycore | [
"b530a7fd97e0f97659b3936733db8bc906efaa3e"
] | [
"src/anoapycore/data/__init__.py"
] | [
"from . import column\nfrom . import load\nfrom . import null\nfrom . import row\nfrom . import save\nfrom . import series\nfrom . import stat\nfrom . import value\n\nimport pandas as __pd\nfrom sklearn.preprocessing import MinMaxScaler as __minmax\nfrom sklearn.preprocessing import StandardScaler as __standard\nfr... | [
[
"pandas.merge",
"pandas.concat",
"pandas.DataFrame",
"sklearn.preprocessing.StandardScaler",
"sklearn.preprocessing.MinMaxScaler"
]
] |
lwhluvdemo/PaddleDetection | [
"99c7e3a75a955b4a4cb038679c8f88e170bb3b44"
] | [
"ppdet/modeling/layers.py"
] | [
"# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless ... | [
[
"numpy.hstack",
"numpy.meshgrid",
"numpy.arange",
"numpy.stack",
"numpy.outer",
"numpy.array"
]
] |
foxlf823/NCRFpp | [
"bea99df2951b729fabb96ccdc36edc2272847d50"
] | [
"model/charbigru.py"
] | [
"# -*- coding: utf-8 -*-\n# @Author: Jie Yang\n# @Date: 2017-10-17 16:47:32\n# @Last Modified by: Jie Yang, Contact: jieynlp@gmail.com\n# @Last Modified time: 2018-10-18 11:12:13\nfrom __future__ import print_function\nimport torch\nimport torch.nn as nn\nfrom torch.nn.utils.rnn import pack_padded_sequence,... | [
[
"torch.nn.Dropout",
"numpy.sqrt",
"torch.nn.GRU",
"torch.from_numpy",
"torch.nn.Embedding",
"torch.nn.utils.rnn.pack_padded_sequence",
"torch.nn.utils.rnn.pad_packed_sequence",
"torch.cuda.is_available",
"numpy.random.uniform",
"numpy.empty"
]
] |
Manfred-Hyt/meshpy | [
"9381d91b259dff9fb2404cffe23f27f88ec0ccb4"
] | [
"meshpy/mesh_creation_functions/beam_fibers_in_rectangle.py"
] | [
"# -*- coding: utf-8 -*-\n# -----------------------------------------------------------------------------\n# MeshPy: A beam finite element input generator\n#\n# MIT License\n#\n# Copyright (c) 2021 Ivo Steinbrecher\n# Institute for Mathematics and Computer-Based Simulation\n# U... | [
[
"numpy.dot",
"numpy.linalg.solve",
"numpy.abs",
"numpy.cos",
"numpy.linalg.norm",
"numpy.sin",
"numpy.linalg.det",
"numpy.max",
"numpy.append",
"numpy.array"
]
] |
GeunYoung2/learn | [
"7e4c0e0ac0825d81cf8a2a5ce9aa00cd2e02fdd4"
] | [
"Data_Analysis.py"
] | [
"## 영상 처리 및 데이터 분석 툴\r\nfrom tkinter import *;\r\nimport os.path;\r\nimport math\r\nfrom tkinter.filedialog import *\r\nfrom tkinter.simpledialog import *\r\nimport struct;\r\nimport threading\r\nimport matplotlib.pyplot as plt\r\nimport xlwt\r\nimport xlsxwriter\r\nimport pymysql\r\nimport csv\r\nimport sqlite3\r\... | [
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.show"
]
] |
devforfu/catalyst | [
"0ec665981135b264120cb5c4c04d56034f1c831c"
] | [
"examples/atari/src/atari_wrappers.py"
] | [
"from collections import deque\nimport numpy as np\nimport gym\nfrom gym import spaces\nimport cv2\n\ncv2.ocl.setUseOpenCL(False)\n\n\nclass TimeLimit(gym.Wrapper):\n def __init__(self, env, max_episode_steps=None):\n super().__init__(env)\n self._max_episode_steps = max_episode_steps\n self... | [
[
"numpy.expand_dims",
"numpy.sign",
"numpy.concatenate",
"numpy.array",
"numpy.zeros"
]
] |
jiecaoyu/FBGEMM | [
"2c547924deafa1839483d31096de800078c35711"
] | [
"fbgemm_gpu/bench/bench_utils.py"
] | [
"# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n# This source code is licensed under the BSD-style license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport itertools\nimport logging\nimport statistics\nimport time\nfrom typing import Callable, List, Op... | [
[
"torch.cuda.synchronize",
"torch.cuda.current_device",
"torch.load",
"torch.zeros",
"torch.cat",
"torch.cuda.Event",
"torch.nn.EmbeddingBag",
"numpy.cumsum",
"numpy.random.zipf",
"numpy.ones",
"torch.nn.Embedding",
"torch.sort",
"torch.cuda.is_available",
"t... |
anubhabPanda/TSAI-EVA5 | [
"d16d83c796240632e120ba51cff2d10349ffee34"
] | [
"Week10/Picasso/models/model11.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom models.resnet import BasicBlock\n\n\nclass Residual_Block(nn.Module):\n def __init__(self, in_channels, out_channels, basic_block = None):\n super(Residual_Block, self).__init__()\n self.conv1 = nn.Sequential(\n ... | [
[
"torch.nn.functional.log_softmax",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU"
]
] |
mimacom/whtobu-ml | [
"d17f1ea704d8c347de51aaa385de0e6f381a1f36"
] | [
"api.py"
] | [
"#!whtobu/bin/python\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport numpy as np\nimport os\nimport tensorflow as tf\nimport time\nimport uuid\nfrom flask import Flask, jsonify, make_response, request, abort\nfrom werkzeug.utils import secu... | [
[
"tensorflow.Graph",
"tensorflow.image.resize_bilinear",
"tensorflow.import_graph_def",
"tensorflow.read_file",
"tensorflow.gfile.GFile",
"numpy.squeeze",
"tensorflow.cast",
"tensorflow.image.decode_png",
"tensorflow.expand_dims",
"tensorflow.image.decode_bmp",
"tensorfl... |
233-puchi/mindspore | [
"e9d2684cdb7668eac48169feeff778eeffbfa70e"
] | [
"mindspore/explainer/_image_classification_runner.py"
] | [
"# Copyright 2020-2021 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 applica... | [
[
"numpy.expand_dims",
"numpy.sqrt",
"numpy.isfinite",
"scipy.stats.beta.interval",
"numpy.uint8",
"numpy.errstate",
"numpy.array",
"numpy.zeros"
]
] |
yewon-lee/Crazyflie_New | [
"500f350f665fb5588a8b522e5894c710cfc51487"
] | [
"rotors_control/src/nodes/position_controller_node_ChihChun_flocking.py"
] | [
"#!/usr/bin/env python2\n\n\"\"\"\nROS interface for controlling up to four Cf2.0's and running the flocking algorithm.\n\nThis ROS node subscribes to the following topics:\n/crazyflie2_id/odometry\n\nThis ROS node publishes to the following topics:\n/crazyflie2_id/command/motor_speed\n/crazyflie2_id/goal\n\nWhere ... | [
[
"numpy.square",
"numpy.asarray",
"numpy.linalg.norm",
"numpy.shape",
"numpy.array"
]
] |
ndalsanto/PDE-DNN | [
"1d4e612660e90546c6d97f4a6c8c1f498e5bfdf9"
] | [
"fem_data_generation.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Jun 5 16:07:28 2019\n\n@author: Niccolo' Dal Santo\n@email : niccolo.dalsanto@epfl.ch\n\"\"\"\n\nimport random\nimport numpy as np\n\n# generate the coordinates randomly or in a tensorial way (if the mesh is structured and the fem dofs are or... | [
[
"numpy.zeros",
"numpy.sort",
"numpy.unique"
]
] |
fabianegli/biopython | [
"132851bb572c0f6a22cde788d3a56e87ee1f48d2"
] | [
"Tests/test_seq.py"
] | [
"# This code is part of the Biopython distribution and governed by its\n# license. Please see the LICENSE file that should have been included\n# as part of this package.\n\n\"\"\"Tests for seq module.\"\"\"\n\nimport array\nimport copy\nimport unittest\nimport warnings\n\ntry:\n import numpy\nexcept ImportError... | [
[
"numpy.array",
"numpy.intc"
]
] |
baregawi/haystack | [
"f70d35279b9b35002012890399b5f20d6d35df8e"
] | [
"test/test_document_store.py"
] | [
"import numpy as np\nimport pandas as pd\nimport pytest\nimport json\nimport responses\nfrom responses import matchers\nfrom unittest.mock import Mock\nfrom elasticsearch import Elasticsearch\nfrom elasticsearch.exceptions import RequestError\n\nfrom conftest import (\n deepset_cloud_fixture,\n get_document_s... | [
[
"pandas.DataFrame",
"numpy.testing.assert_array_equal",
"numpy.random.randn",
"numpy.testing.assert_raises",
"numpy.random.rand",
"numpy.testing.assert_array_almost_equal"
]
] |
msheller/topologies | [
"c6457a677410fb028167f05b4e313dbffcab3d24"
] | [
"3D_UNet/model.py"
] | [
"#!/usr/bin/python\n\n# ----------------------------------------------------------------------------\n# Copyright 2018 Intel\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# ... | [
[
"tensorflow.reduce_sum",
"tensorflow.log",
"tensorflow.reduce_mean"
]
] |
pauljaffe/task-dyva | [
"dbf778635cdb5f1d42149da82ca07ee3919296fa"
] | [
"task_dyva/taskdataset.py"
] | [
"\"\"\"Classes and utility functions for processing game data.\n\nEbbFlowGameData: Container for data from a single game.\nEbbFlowDataset: Subclass of PyTorch Dataset,\n container for data from multiple games.\nEbbFlowStats: Subclass of EbbFlowDataset,\n provides extra functionality for analysis.\n\"\"\"\nimp... | [
[
"numpy.expand_dims",
"torch.load",
"torch.cat",
"numpy.squeeze",
"numpy.cumsum",
"pandas.DataFrame",
"numpy.round",
"numpy.concatenate",
"scipy.stats.gaussian_kde",
"scipy.stats.bernoulli.rvs",
"numpy.mean",
"torch.save",
"matplotlib.pyplot.tight_layout",
"n... |
jihwanlee-alphago/aqt | [
"dfc0761f8db13b10174550979b0a3c8b32fd3d01",
"dfc0761f8db13b10174550979b0a3c8b32fd3d01"
] | [
"aqt/jax_legacy/jax/compute_cost_utils_test.py",
"aqt/jax_legacy/jax/wmt_mlperf/models_test.py"
] | [
"# Copyright 2022 Google LLC\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 agreed ... | [
[
"numpy.testing.assert_array_equal"
],
[
"numpy.array"
]
] |
amathislab/Primer-MotionCapture | [
"ee595bb14ad89d5a6e2b412ce28962f5607cad77"
] | [
"Illustrating-Augmentations-FigurePipelineMouse.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nThis script uses Imgaug to display various augmentation methods\nfor a few labeled images of a mouse (Data in folder mouse_m7s3\nfrom Mathis, A., et al. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning.\nNat Neurosci 21, 1... | [
[
"numpy.hstack",
"numpy.shape",
"numpy.isfinite"
]
] |
Mishiba-Toshihiro/Self-Register | [
"ac9ce28c714db1d1086b3dba23a464d8f686cfd4"
] | [
"self-checkout.py"
] | [
"import argparse\nimport ntpath\nimport picamera\nimport pygame.mixer\nfrom datetime import datetime\nfrom yolo import YOLO\nfrom PIL import Image, ImageOps, ImageTk\nimport tkinter as tk\nfrom time import sleep\nfrom timeit import default_timer as timer\nimport pandas as pd\nimport os\nimport sys\nfrom contextlib ... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
jesserobertson/uncover-ml | [
"22ca6361b25a119dd8fab1f3d50475df70b35170"
] | [
"preprocessing/raster_average.py"
] | [
"import warnings\nfrom subprocess import check_call\nimport shutil\nimport glob\nimport logging\nfrom os.path import abspath, join, basename, isdir, isfile\nimport click\nimport numpy as np\nfrom numpy.lib.stride_tricks import as_strided\nfrom scipy import ndimage\nfrom osgeo import gdal\nfrom uncoverml import mpio... | [
[
"numpy.isnan",
"scipy.ndimage.uniform_filter",
"numpy.lib.stride_tricks.as_strided",
"numpy.zeros_like",
"numpy.array_split",
"numpy.empty"
]
] |
Quansight-Labs/cudf | [
"d05de978f2d1f34b7629bd54ab9485df1f9949ef"
] | [
"python/cudf/cudf/tests/test_binops.py"
] | [
"# Copyright (c) 2018-2021, NVIDIA CORPORATION.\n\nfrom __future__ import division\n\nimport decimal\nimport operator\nimport random\nfrom itertools import product\n\nimport numpy as np\nimport pandas as pd\nimport pytest\n\nimport cudf\nfrom cudf.core import Series\nfrom cudf.core.index import as_index\nfrom cudf.... | [
[
"numpy.true_divide",
"numpy.datetime_data",
"numpy.random.random",
"pandas.Series",
"numpy.random.seed",
"pandas.DateOffset",
"numpy.random.choice",
"numpy.isnan",
"numpy.float16",
"pandas.Index",
"pandas.DataFrame",
"numpy.dtype",
"numpy.testing.assert_array_eq... |
Ina299/prompt2slip | [
"b35489ff4fc4f5d724cfb74c75e5e128da553c70"
] | [
"prompt2slip/loss_transformers.py"
] | [
"from typing import Optional, Dict, Any, Union\n\nimport torch\nfrom torch import nn\nfrom torch.nn import functional as F\nfrom torch import Tensor\nfrom torchtyping import TensorType\nimport transformers\n\nfrom .utils import make_forbit_indicates\n\nKeyValBatchType = Union[transformers.BatchEncoding, Dict[str, T... | [
[
"torch.mean",
"torch.nn.CrossEntropyLoss",
"torch.max",
"torch.nn.functional.log_softmax",
"torch.clamp",
"torch.logical_not"
]
] |
XC-Li/Deep_Learning_GWU | [
"2dfe0d39ce8f9d981cee545f489f9dde1ffdfa7c"
] | [
"Homework6/2_Tensor_Pytorch_Edited.py"
] | [
"import torch\n#----------------------------------------------------------------------------\ndtype = torch.float\nif torch.cuda.is_available():\n device = torch.device(\"cuda:0\")\nelse:\n device = torch.device(\"cpu\")\n#----------------------------------------------------------------------------\nBatch_siz... | [
[
"torch.device",
"torch.randn",
"torch.cuda.is_available"
]
] |
mynameisvinn/scikit-network | [
"255e99b2f7d5ad8914a8fad3a89d7817764666e0"
] | [
"sknetwork/linalg/sparse_lowrank.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Apr 19 2019\n@author: Nathan de Lara <ndelara@enst.fr>\n\"\"\"\n\nfrom typing import Union, Tuple\n\nimport numpy as np\nfrom scipy import sparse\nfrom scipy.sparse.linalg import LinearOperator\n\n\nclass SparseLR(LinearOperator):\n \"\"\"Class... | [
[
"numpy.dtype",
"scipy.sparse.csr_matrix",
"numpy.ones"
]
] |
DaikiOnodera/kaggle-hpa | [
"3e7888cadaa18403231136800bfd1ac324d6db66"
] | [
"swa.py"
] | [
"import os\nimport argparse\nimport pprint\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\n\nfrom datasets import get_dataloader\nfrom transforms import get_transform\nfrom models import get_model\nimport utils.config\nimport utils.swa as swa\nimport utils.checkpoint\n\n\ndef get_checkpoints(c... | [
[
"torch.no_grad"
]
] |
1751200/Xlab-k8s-gpu | [
"b258f9610d2416a047f8f9545b1d6f66a7e88df3"
] | [
"MatMul/PyTorch&CuPy/pythonTest.py"
] | [
"import torch\r\nimport time\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nimport cupy as cp\r\n# torch.cuda.device_count()\r\n# torch.cuda.get_device_name(0)\r\n\r\n#计算cupy矩阵乘法以及其计算平均时间\r\n#shape:矩阵维度，shape*shape\r\n#times:计算次数，计算时间是取平均时间\r\ndef cupy_test(shape,times):\r\n sumT = 0\r\n for i in... | [
[
"matplotlib.pyplot.legend",
"torch.mm",
"torch.cuda.set_device",
"numpy.einsum",
"matplotlib.pyplot.plot",
"numpy.random.rand",
"torch.rand",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
ykawazura/calliope | [
"343b72a0930d70332172a5d87a579b0f8dcced66"
] | [
"diagnostics/MHD_COMP_ADIAB/energy_dot_avg.py"
] | [
"# -*- coding: utf-8 -*-\n\n#####################################################\n## main program for making plots from AstroGK data ##\n#####################################################\nimport numpy as np\nfrom scipy.integrate import simps, trapz\nfrom scipy import interpolate\n\nfrom numba import jit\n\n@ji... | [
[
"scipy.integrate.trapz",
"numpy.loadtxt"
]
] |
swdev1202/PointRCNN | [
"2557d670e80e813a8af4edf9f7ff7d2e9d94cfb0"
] | [
"lib/utils/object3d.py"
] | [
"import numpy as np\n\n\ndef cls_type_to_id(cls_type):\n type_to_id = {'Car': 1, 'Pedestrian': 2, 'Cyclist': 3, 'Van': 4}\n if cls_type not in type_to_id.keys():\n return -1\n return type_to_id[cls_type]\n\n\nclass Object3d(object):\n def __init__(self, line):\n label = line.strip().split(... | [
[
"numpy.dot",
"numpy.clip",
"numpy.linalg.norm",
"numpy.cos",
"numpy.sin",
"numpy.floor",
"numpy.zeros",
"numpy.vstack"
]
] |
asanoviskhak/Outtalent | [
"8a10b23335d8e9f080e5c39715b38bcc2916ff00"
] | [
"Leetcode/1420. Build Array Where You Can Find The Maximum Exactly K Comparisons/solution1.py"
] | [
"import numpy as np\n\n\nclass Solution:\n def numOfArrays(self, n: int, m: int, k: int) -> int:\n mod = 1e9 + 7\n dp = np.zeros((n, k + 1, m + 1))\n ps = np.zeros((n, k + 1, m + 1))\n for i in range(1, m + 1):\n dp[0, 1, i] = 1\n ps[0, 1, i] = ps[0, 1, i - 1] + ... | [
[
"numpy.zeros"
]
] |
Matheus-IT/lang-python-related | [
"dd2e5d9b9f16d3838ba1670fdfcba1fa3fe305e9"
] | [
"data_analysis/NumPy/03NumPy_estatistica.py"
] | [
"import numpy as np\r\n\r\n# Criando um array\r\nA = np.array([15, 23, 63, 94, 75])\r\n\r\n# Em estatística a média é o valor que aponta para onde mais se concentram os dados de uma distribuição.\r\nprint(np.mean(A))\r\n\r\n# O desvio padrão mostra o quanto de variação ou \"dispersão\" existe em \r\n# relação à méd... | [
[
"numpy.var",
"numpy.std",
"numpy.array",
"numpy.mean"
]
] |
mani-shailesh/lime | [
"3aa9ea9c30bffe73f1bffbe09fe70f6b8bd2c29c"
] | [
"lime/explanation.py"
] | [
"\"\"\"\nExplanation class, with visualization functions.\n\"\"\"\nfrom __future__ import unicode_literals\nfrom io import open\nimport os\nimport os.path\nimport json\nimport string\nimport numpy as np\n\nfrom .exceptions import LimeError\n\nfrom sklearn.utils import check_random_state\n\n\ndef id_generator(size=1... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.barh",
"matplotlib.pyplot.yticks",
"sklearn.utils.check_random_state",
"matplotlib.pyplot.figure"
]
] |
jagadeeshmeesala/data-processing-pipeline | [
"9a3ef1b650c1e5dd7f12a007ff598ba5f70bdb82"
] | [
"producer.py"
] | [
"#####################################################\n## PROGRAM TO IMPLEMENT KINESIS PRODUCER THAT FETCHES WEATHER INFORMATION\n## AND STREAMS THE DATA INTO KINESIS STREAM\n####################################################\n\n# necessary imports\nimport boto3\nimport datetime as dt\nimport pandas as pd\nimpor... | [
[
"pandas.DataFrame"
]
] |
wondar-chan/akshare | [
"16eeed1c42bfd66533a0430c3f086890269fad90"
] | [
"akshare/economic/macro_usa.py"
] | [
"#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n\"\"\"\nDate: 2021/12/24 12:08\nDesc: 金十数据中心-经济指标-美国\nhttps://datacenter.jin10.com/economic\n\"\"\"\nimport json\nimport time\n\nimport pandas as pd\nfrom akshare.utils import demjson\nimport requests\n\nfrom akshare.economic.cons import (\n JS_USA_NON_FARM_URL,\n ... | [
[
"pandas.concat",
"pandas.to_datetime",
"pandas.to_numeric",
"pandas.DataFrame"
]
] |
VikrantKamble/lyaf_optdepth | [
"899048ab73e546513b3713b3818abfab3ce3ab05"
] | [
"lyaf_optdepth/utils.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom scipy.stats import chi2\nfrom matplotlib.patches import Ellipse\nfrom scipy.special import erf\nfrom astroML.plotting.mcmc import convert_to_stdev as cts\nfrom scipy.optimize import curve_fit\n\n\ndef draw_ellipse(pos, cov, nsig=None, ax=None, label=\"temp\... | [
[
"numpy.diag",
"matplotlib.pyplot.legend",
"numpy.dot",
"numpy.sqrt",
"numpy.arctan2",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.plot",
"numpy.exp",
"scipy.optimize.curve_fit",
"matplotlib.pyplot.tight_layout",
"numpy.arange",
"numpy.linalg.det",
"numpy.zeros"... |
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