repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
timgates42/kapre | [
"e0fffbbd2f9a8d1bcc4d337d15389d059646b2a8"
] | [
"tests/test_time_frequency.py"
] | [
"import pytest\nimport numpy as np\nimport tensorflow as tf\nimport tensorflow.keras\nimport librosa\nfrom kapre import STFT, Magnitude, Phase, Delta, InverseSTFT, ApplyFilterbank\nfrom kapre.composed import (\n get_melspectrogram_layer,\n get_log_frequency_spectrogram_layer,\n get_stft_mag_phase,\n get... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.sin",
"numpy.angle",
"numpy.reshape",
"numpy.testing.assert_equal",
"numpy.tile",
"numpy.real",
"numpy.shape",
"numpy.take",
"numpy.transpose",
"tensorflow.keras.models.Sequential",
"numpy.cos",
"numpy.a... |
jiaxx/temporal_learning_paper | [
"abffd5bfb36aaad7139485a9b8bd29f3858389e8"
] | [
"code/learningutil.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Oct 4 16:39:50 2013\n\n@author: Xiaoxuan Jia\n\"\"\"\n\nimport json\nimport csv\nimport re\nimport scipy.io\nimport scipy.stats\nimport random\nimport numpy as np\nimport os\nimport itertools\nimport cPickle as pk\nimport pymongo\nimport scipy\nfrom scipy.stats impor... | [
[
"scipy.stats.norm.ppf",
"numpy.zeros",
"numpy.sum",
"matplotlib.pyplot.plot",
"scipy.stats.spearmanr",
"numpy.ma.masked_invalid",
"numpy.shape",
"numpy.random.shuffle",
"numpy.eye",
"scipy.stats.pearsonr",
"scipy.delete",
"numpy.unique"
]
] |
hsmohammed/rudaux | [
"673b2bb2d6b08f9d9c34a2ed6e284d9def1a0fc7"
] | [
"scripts/canvas.py"
] | [
"import requests\nimport urllib.parse\nimport posixpath\nimport pandas as pd\n\ndef get_enrollment_dates(course):\n '''Takes a course object and returns student dates of enrollment.\n Useful for handling late registrations and modified deadlines.\n\n Example:\n course.get_enrollment_date()'''\n url_p... | [
[
"pandas.DataFrame.from_dict"
]
] |
danielkrause/DCASE2022-data-generator | [
"b0ff595e7cf7e5581d9a0ee4d3292a41117db8e5"
] | [
"audio_synthesizer.py"
] | [
"import numpy as np\r\nimport scipy.io\r\nimport utils\r\nimport os\r\nimport mat73\r\nimport scipy.signal as signal\r\nimport soundfile\r\n\r\nclass AudioSynthesizer(object):\r\n def __init__(\r\n self, params, mixtures, mixture_setup, db_config, audio_format\r\n ):\r\n self._mixtur... | [
[
"numpy.zeros",
"numpy.round",
"numpy.sum",
"numpy.shape",
"numpy.stack",
"numpy.arange",
"numpy.sqrt",
"numpy.abs",
"scipy.signal.resample_poly",
"numpy.squeeze"
]
] |
Superhzf/PaperImplementation | [
"a800a9e2fb52fb70766bf91b52871621e0e1dd55"
] | [
"NLP/The_Bottom_up_Evolution_of_Representations_in_the_Transformer/analytics.py"
] | [
"from sklearn.cluster import MiniBatchKMeans\nimport numpy as np\n\nimport torch\nfrom models import TransformerModel, Seq2SeqTransformer, generate_square_subsequent_mask\nfrom models import LM_NAME, MLM_NAME, MT_NAME, NLAYERS, NUM2WORD\nimport os\nfrom data_preprocessing import DATA_DIR_DEV, SAVE_DATA_MT_TRAIN\nfr... | [
[
"torch.rand",
"torch.cuda.is_available"
]
] |
samokhinv/deep_pipe | [
"9461b02f5f32c3e9f24490619ebccf417979cffc"
] | [
"dpipe/batch_iter/utils.py"
] | [
"from typing import Callable, Iterable, Sequence\n\nimport numpy as np\n\nfrom dpipe.im.axes import AxesLike, AxesParams\nfrom dpipe.itertools import lmap, squeeze_first\nfrom dpipe.im import pad_to_shape\n\n\ndef pad_batch_equal(batch, padding_values: AxesParams = 0, ratio: AxesParams = 0.5):\n \"\"\"\n Pad ... | [
[
"numpy.array",
"numpy.random.binomial",
"numpy.atleast_1d"
]
] |
zeuseyera/baselines-kr | [
"c9926418d2d8efee21ef20d548366eaaaa193011"
] | [
"baselines/a2c/utils.py"
] | [
"import os\nimport numpy as np\nimport tensorflow as tf\nfrom collections import deque\n\ndef sample(logits):\n noise = tf.random_uniform(tf.shape(logits))\n return tf.argmax(logits - tf.log(-tf.log(noise)), 1)\n\ndef cat_entropy(logits):\n a0 = logits - tf.reduce_max(logits, 1, keepdims=True)\n ea0 = ... | [
[
"tensorflow.exp",
"tensorflow.constant_initializer",
"tensorflow.nn.conv2d",
"tensorflow.matmul",
"tensorflow.nn.moments",
"tensorflow.reshape",
"numpy.mean",
"tensorflow.sqrt",
"tensorflow.stack",
"tensorflow.tanh",
"tensorflow.trainable_variables",
"numpy.random.n... |
samiulshuvo/se_relativisticgan | [
"5501c4d96faa03eb3c1fd776b232b68940183f4d"
] | [
"data_ops.py"
] | [
"\"\"\"\nData processing routines\nDeepak Baby, UGent, June 2018\ndeepak.baby@ugent.be\n\"\"\"\n\nimport numpy as np\n\ndef reconstruct_wav(wavmat, stride_factor=0.5):\n \"\"\"\n Reconstructs the audiofile from sliced matrix wavmat\n \"\"\"\n window_length = wavmat.shape[1]\n window_stride = int(stride_factor ... | [
[
"numpy.concatenate",
"numpy.ceil",
"numpy.zeros",
"numpy.ones",
"numpy.expand_dims"
]
] |
icc2115/dl-selection | [
"e39ef0e73bf631e413bac48db791aed617dd7e32"
] | [
"selection/layers/utils.py"
] | [
"import torch\nimport torch.nn.functional as F\n\n\ndef clamp_probs(probs):\n eps = torch.finfo(probs.dtype).eps\n return torch.clamp(probs, min=eps, max=1-eps)\n\ndef concrete_sample(logits, temperature, shape=torch.Size([])):\n '''\n Sampling for Concrete distribution.\n\n See Eq. 10 of Maddison et... | [
[
"torch.Size",
"torch.rand",
"torch.finfo",
"torch.nn.functional.logsigmoid",
"torch.clamp",
"torch.log"
]
] |
willidert/aux_est_micro | [
"6882794efa609f4171d86a0de1599bb97ac1ff2b"
] | [
"data-clean/clean.py"
] | [
"import pandas as pd\nimport numpy as np\n\n\ndef gloriosafuncao(df):\n\n df = pd.DataFrame([df])\n\n numerico = [\n 11, \"email\", 1, 2, 3, 7,\n 8, 9, 12, 10, 13, 14,\n 15, 16, 17, 18, 19, 20, 21, 4, 5, 6\n ]\n\n df.columns = numerico\n\n labels = [\n 'email',\n 'P... | [
[
"pandas.DataFrame",
"numpy.array",
"pandas.concat"
]
] |
ZXTFINAL/deeplearning | [
"52208b43fc8f9a1ea8508b1c07140c70e1529459",
"52208b43fc8f9a1ea8508b1c07140c70e1529459"
] | [
"1_boston.py",
"1_gradient.py"
] | [
"import numpy as np\nfrom sklearn.datasets import load_boston\nfrom sklearn.model_selection import train_test_split\ndataset = load_boston()\nX = dataset.data\ny = dataset.target\nmean = X.mean(axis=0)\nstd = X.std(axis=0)\nX = (X-mean)/std\n# print(X)\nX_train, X_test, y_train, y_test = train_test_split(X, y, test... | [
[
"sklearn.model_selection.train_test_split",
"numpy.random.rand",
"sklearn.datasets.load_boston"
],
[
"numpy.array",
"matplotlib.pyplot.plot",
"numpy.arange",
"matplotlib.pyplot.show",
"matplotlib.pyplot.scatter"
]
] |
Isaac-Flath/lightning-flash | [
"320f87707587d92a13c8831778864b33af4fe421"
] | [
"flash/image/embedding/vissl/transforms/utilities.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.utils.data._utils.collate.default_collate",
"torch.stack"
]
] |
eddy-ilg/iviz | [
"8c392dcc75a6563c5d076bbbd84152273a3c0f71"
] | [
"python/iviz/Util.py"
] | [
"#!/usr/bin/env python3\n#-*- coding: utf-8 -*-\n\nfrom PyQt5.QtGui import QImage, qRgb, QPixmap\nimport numpy as np\nimport numpy as np\n\ngray_color_table = [qRgb(i, i, i) for i in range(256)]\n\ndef toQImage(data, copy=True):\n if data is None:\n return QImage()\n\n data = data.copy()\n\n data[da... | [
[
"numpy.frombuffer"
]
] |
dalpengholic/Udacity_Recommendations_with_IBM | [
"8c620b733bf91b7b97b607373d0e6ff86934d03d"
] | [
"model/recommendation_functions.py"
] | [
"import pandas as pd\nimport re\nimport nltk\nfrom nltk.corpus import stopwords\nfrom nltk.stem.wordnet import WordNetLemmatizer\nfrom nltk.tokenize import word_tokenize\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.metrics.pairwise import cosine_similarity\nfrom sklearn.metrics.pairwis... | [
[
"pandas.DataFrame",
"sklearn.metrics.pairwise.linear_kernel",
"sklearn.feature_extraction.text.TfidfVectorizer"
]
] |
hurwitzlab/viral-learning | [
"8d7aebc0d58fa32a429f4a47593452ee2722ba82"
] | [
"vl/model/training.py"
] | [
"\"\"\"\nTraining and validation method for arbitrary models.\n\"\"\"\nimport io\nimport os\nimport sys\nimport time\n\nfrom keras import Sequential\nfrom keras.layers import Dense, Dropout, BatchNormalization\n\nfrom matplotlib.backends.backend_pdf import PdfPages\nimport matplotlib.pyplot as plt\nimport matplotli... | [
[
"matplotlib.pyplot.switch_backend",
"matplotlib.ticker.MultipleLocator",
"matplotlib.backends.backend_pdf.PdfPages",
"pandas.RangeIndex",
"matplotlib.pyplot.subplots"
]
] |
lerry-lee/similarity-model | [
"74ea7f4fc97382d87e6ab71531e66182ca1ba3f4"
] | [
"ernie/classification/service/client.py"
] | [
"# Copyright (c) 2018 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.concatenate",
"numpy.save",
"numpy.expand_dims"
]
] |
mczhuge/Kaleido-BERT | [
"1b14073e3ad3490c50bbd1e7e94846830671b332"
] | [
"easytransfer/losses/kd_loss.py"
] | [
"# coding=utf-8\n# Copyright (c) 2019 Alibaba PAI 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... | [
[
"tensorflow.nn.l2_loss",
"tensorflow.squeeze",
"tensorflow.nn.softmax",
"tensorflow.reduce_mean",
"tensorflow.stop_gradient"
]
] |
UNIZAR-30226-2022-09/back-end | [
"7f20e141e34bf0ae7cce70515a1e4bb0cd85b173"
] | [
".vscode-server/data/User/History/-1f47d17c/IWlp.py"
] | [
"# from flask import Flask, Blueprint\n# from flask_sqlalchemy import SQLAlchemy\n# from flask_login import LoginManager\n# import os\n\nfrom flask import Flask, jsonify, request, make_response, redirect, url_for\nimport jwt\nimport datetime\nimport os\nfrom functools import wraps\nfrom flask_sqlalchemy import SQLA... | [
[
"numpy.array"
]
] |
sushmaakoju/parser | [
"e40e3f818921141044b499e231ae75e6bf4141c2"
] | [
"src/equation_parser/equations.py"
] | [
"from __future__ import absolute_import\n\n#SymPy is a non-commercial alternative to Mathematica and Maple\n# SymPy can map variable to a value or a matrix.\n# SymPy's Symbolic Statistical Modelling uses scintific computing.\nimport sys\nimport numpy as np\nimport sympy as sp\nimport pandas as pd\nfrom pathlib impo... | [
[
"pandas.DataFrame.from_dict",
"pandas.DataFrame",
"pandas.read_excel"
]
] |
rejux/rklearn-lib | [
"56bc4f087a8c971cb545d65b0c1f9bafaaec3d67",
"56bc4f087a8c971cb545d65b0c1f9bafaaec3d67"
] | [
"rklearn/tests/it/cifar10_cnn.py",
"rklearn/tests/it/test_rklearn_perceptron_binary_mnist.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n#############\n## Imports ##\n#############\n\nimport os\nimport sys ; sys.path.append(\"/home/developer/workspace/rklearn-lib\")\nimport tensorflow as tf\n\nfrom rklearn.tfoo_v1 import BaseModel\n\n#################\n## CIFAR10CNN ##\n#################\n\nclass C... | [
[
"tensorflow.compat.v1.placeholder",
"tensorflow.layers.dropout",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.compat.v1.train.AdamOptimizer",
"tensorflow.layers.max_pooling2d",
"tensorflow.contrib.layers.fully_connected",
"tensorflow.argmax",
"tensorflow.reshape",... |
gmweir/QuasiOptics | [
"0974178984f845597c5209217613c26edf931ed0",
"0974178984f845597c5209217613c26edf931ed0"
] | [
"colorpy/colorpy-0.1.0/blackbody.py",
"colorpy/ColorPy/ColorPy-master/plots.py"
] | [
"'''\nblackbody.py - Color of thermal blackbodies.\n\nDescription:\n\nCalculate the spectrum of a thermal blackbody at an arbitrary temperature.\n\nConstants:\n\nPLANCK_CONSTANT - Planck's constant, in J-sec\nSPEED_OF_LIGHT - Speed of light, in m/sec\nBOLTZMAN_CONSTANT - Boltzman's constant, in J/K\nSUN_TEMPER... | [
[
"numpy.empty"
],
[
"numpy.max",
"numpy.empty"
]
] |
AtsushiHashimoto/SpectralClusteringFD | [
"dd150a08898ce354a1b59457dea2f5185d145ed7"
] | [
"spectral_clustering_fd/laplacian_sketch.py"
] | [
"# coding: utf-8\nimport numpy as np\nfrom frequent_direction import FrequentDirection\nfrom sklearn.preprocessing import normalize\n\nfrom sklearn.metrics.pairwise import pairwise_kernels\n\n\ndef laplacian_sketch(X,ell,k,do_normalize_feature,normed,callback,**args):\n fd = FrequentDirection(ell,k)\n\n D = n... | [
[
"numpy.dot",
"numpy.zeros",
"numpy.sum",
"numpy.exp",
"sklearn.metrics.pairwise.pairwise_kernels",
"sklearn.preprocessing.normalize",
"numpy.power",
"numpy.sqrt"
]
] |
acproject/GNNs | [
"953d175f672f0bb1b7cd25f371878728f3d27f09"
] | [
"NAACL/ensemble.py"
] | [
"'''Ensemble some predictions. '''\r\nimport argparse\r\nimport collections\r\nimport math\r\nfrom scipy.special import logsumexp\r\nimport sys\r\n\r\nMODES = ['mean', 'max', 'logsumexp', 'noisy_or', 'log_noisy_or', 'odds_ratio']\r\n\r\ndef parse_args(args):\r\n parser = argparse.ArgumentParser()\r\n parser.a... | [
[
"scipy.special.logsumexp"
]
] |
csepreghy/spectral_analysis | [
"1cbd9770347a71721164a7daf7b133ad0eeba8e4"
] | [
"spectral_analysis/unsupervised_learning/autoencoder/autoencoder_bestmodel.py"
] | [
"import numpy as np\nimport pandas as pd\nimport os\nimport matplotlib.pyplot as plt\nimport time\n\nfrom tensorflow.keras.layers import Input, Dense, Flatten, Conv1D, MaxPooling1D, UpSampling1D, BatchNormalization, Reshape\nfrom tensorflow.keras.models import Model, Sequential\nfrom tensorflow.keras.callbacks impo... | [
[
"tensorflow.keras.layers.Conv1D",
"numpy.delete",
"tensorflow.keras.layers.Input",
"sklearn.preprocessing.StandardScaler",
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.MaxPooling1D",
"tensorflow.keras.layers.UpSampli... |
ved432/test | [
"779914d1bc876414d1149161ec0d838d7bb16601"
] | [
"utils/heatmap-coverage.py"
] | [
"from pandas import DataFrame\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport csv,sys\n\nExperimentName=sys.argv[1]\n\nwith open(ExperimentName+'.csv', newline='') as f:\n reader = csv.reader(f)\n data = list(reader)\n\nif ExperimentName == \"pod-delete\":\n Index = ['Validation','For deplo... | [
[
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.title"
]
] |
minwook-shin/aws-data-wrangler | [
"304e734db5e96cc5e11ff54b4f3a1cf7c4e5736b"
] | [
"awswrangler/neptune/neptune.py"
] | [
"\"\"\"Amazon Neptune Module.\"\"\"\n\nimport logging\nimport re\nfrom typing import Any\n\nimport pandas as pd\nfrom gremlin_python.process.graph_traversal import GraphTraversalSource, __\nfrom gremlin_python.process.translator import Translator\nfrom gremlin_python.process.traversal import Cardinality, T\nfrom gr... | [
[
"pandas.DataFrame.from_records",
"pandas.json_normalize",
"pandas.DataFrame.from_dict",
"pandas.DataFrame",
"pandas.concat",
"pandas.notna",
"pandas.Series"
]
] |
MediaBrain-SJTU/GroupNet | [
"607541c8843f8b6206b1ffefd2d27fb07dcca073"
] | [
"datasets/nba/Game.py"
] | [
"import pandas as pd\nfrom Event import Event\nfrom Team import Team\nfrom Constant import Constant\nimport numpy as np\n\n\nclass Game:\n \"\"\"A class for keeping info about the games\"\"\"\n def __init__(self, path_to_json):\n # self.events = None\n self.home_team = None\n self.guest_t... | [
[
"numpy.concatenate",
"pandas.read_json"
]
] |
cperales/Fourier-classifying-songs | [
"54d13e2ce2d7d05fe7126bbbd884917758188d6d"
] | [
"test/test_b_plot.py"
] | [
"import unittest\nfrom foucluster.plot import song_plot, diff_plot, heatmap_song\nimport configparser\nimport os\nimport json\nfrom scipy.io.wavfile import read\nimport numpy as np\nimport pandas as pd\n\n\nclass TestPlot(unittest.TestCase):\n\n @staticmethod\n def _get_series(i=0):\n \"\"\"\n\n ... | [
[
"numpy.mean"
]
] |
trxw/qutip | [
"b923c973edd9a071d86eb849650661549f73585f"
] | [
"qutip/graph.py"
] | [
"# This file is part of QuTiP: Quantum Toolbox in Python.\n#\n# Copyright (c) 2011 and later, Paul D. Nation and Robert J. Johansson.\n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without \n# modification, are permitted provided that the following conditions ar... | [
[
"numpy.any",
"numpy.abs",
"scipy.sparse.csc_matrix",
"scipy.sparse.isspmatrix_csc"
]
] |
liangan1/fairseq | [
"31b54e8ec03824bad61a80bea376c987e2e7c721"
] | [
"fairseq_cli/eval_lm.py"
] | [
"#!/usr/bin/env python3 -u\n# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\n\"\"\"\nEvaluate the perplexity of a trained language model.\n\"\"\"\n\nimport logging\nimport math\nimpo... | [
[
"torch.cuda.set_device",
"torch.cuda.is_available"
]
] |
sbrunk/flytekit | [
"0aa9cdb1be928f799170da61f1135121ccb64657"
] | [
"tests/flytekit/unit/core/test_type_hints.py"
] | [
"import datetime\nimport os\nimport typing\nfrom dataclasses import dataclass\n\nimport pandas\nimport pytest\nfrom dataclasses_json import dataclass_json\n\nimport flytekit\nfrom flytekit import ContainerTask, SQLTask, dynamic, kwtypes, maptask\nfrom flytekit.common.translator import get_serializable\nfrom flyteki... | [
[
"pandas.DataFrame"
]
] |
rousseab/pymatgen | [
"ecfba4a576a21f31c222be8fd20ce2ddaa77495a"
] | [
"pymatgen/io/vasp/tests/test_sets.py"
] | [
"# coding: utf-8\n\nfrom __future__ import unicode_literals\n\nimport unittest\nimport os\nimport shutil\n\nimport numpy as np\nfrom monty.json import MontyDecoder\n\nfrom pymatgen.io.vasp.sets import MITVaspInputSet, MITHSEVaspInputSet, \\\n MPVaspInputSet, MITGGAVaspInputSet, MITNEBVaspInputSet,\\\n MPStati... | [
[
"numpy.allclose",
"numpy.array"
]
] |
Rougnt/ArkNightAutoClick | [
"693ba25227bdfbf228a3d5b3a04d86ea8135b78b"
] | [
"Photo.py"
] | [
"import cv2\nimport os,shutil\nimport numpy as np\nfrom Adb import Adb\nimport time\n\nclass Photo():\n '''\n 提取图片信息，比较图片\n '''\n def __init__(self,img_path) -> None:\n '''\n 读取图片\n '''\n self.img = cv2.imread(img_path)\n\n\n \n\nclass sourceData():\n '''\n ... | [
[
"numpy.sum",
"numpy.var",
"numpy.mean"
]
] |
Pathetiue/safe-exploration | [
"e6c0bc57b7b51fe3e3c97d51721893fe297b2b11"
] | [
"safe_exploration/visualization/utils_visualization.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Sep 21 15:49:49 2017\n\n@author: tkoller\n\"\"\"\n\nimport numpy as np\nimport numpy.linalg as nLa\n\nfrom ..utils import unavailable\ntry:\n import matplotlib.pyplot as plt\n _has_matplotlib = True\nexcept:\n _has_matplotlib = False\n\n\n@unavailable(not _h... | [
[
"numpy.sin",
"numpy.dot",
"numpy.ones_like",
"matplotlib.pyplot.sca",
"numpy.shape",
"numpy.allclose",
"numpy.sqrt",
"numpy.linalg.cholesky",
"numpy.all",
"numpy.cos",
"numpy.linspace"
]
] |
randomvi/opencv-color-detector | [
"8106178434b15c116d8a93140a35f2c341480f11"
] | [
"main.py"
] | [
"import numpy as np \nimport cv2\n\n# To capture webcam live stream, simply change the following line to: cap = cv2.VideoCapture(0)\ncap = cv2.VideoCapture('./assets/video.mp4')\n\nwhile (True):\n # Capture frame by frame\n _, frame = cap.read()\n\n hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n\n # hsv... | [
[
"numpy.array"
]
] |
martinhoang11/vietnamese-ocr-toolbox | [
"524b4908bedceb0c87b2c7cd7b5e3f6e1126ace5",
"524b4908bedceb0c87b2c7cd7b5e3f6e1126ace5",
"524b4908bedceb0c87b2c7cd7b5e3f6e1126ace5"
] | [
"modules/__init__.py",
"modules/retrieval/text_classification/libs/losses/focal.py",
"modules/retrieval/text_classification/libs/loggers/tsboard.py"
] | [
"import os\nimport cv2\nimport shutil\nimport argparse\nimport torch\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image\nimport matplotlib.pyplot as plt\nimport matplotlib\nfrom .preprocess import DocScanner\nimport modules.detection as detection\nimport modules.ocr as ocr\nimport modules.retrieval as ... | [
[
"pandas.DataFrame",
"numpy.array",
"numpy.argmax",
"pandas.read_csv"
],
[
"torch.autograd.Variable",
"torch.Tensor",
"torch.nn.functional.log_softmax"
],
[
"torch.utils.tensorboard.SummaryWriter"
]
] |
ybettan/AirSimTensorFlow | [
"7c9a17d97a68e99da310f2e537bfb66433056066"
] | [
"run_demo.py"
] | [
"from __future__ import print_function\n\nimport pprint\nimport os\nimport time\nimport msgpackrpc\nimport math\nimport msgpackrpc #install as admin: pip install msgpack-rpc-python\nimport msgpack\nimport sys\nimport inspect\nimport types\nimport re\nimport shutil\n\nimport numpy as np #pip install numpy\n\n\n\n#==... | [
[
"numpy.uint8",
"numpy.reshape",
"numpy.asarray",
"numpy.flipud",
"numpy.float32",
"numpy.fromfile",
"numpy.uint64",
"numpy.fromstring"
]
] |
Henrynaut/Py622 | [
"1ac33db96f82c562fe4a85ca5dc0b9b77c5fd088"
] | [
"logAxes.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\nfrom matplotlib.ticker import NullFormatter # useful for `logit` scale\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)\n\n# make up some data in the interval ]0, 1[\ny = np.random.normal(loc=0.5, scale=0.4, size=1000)\ny = y[(y > 0) & (... | [
[
"numpy.random.normal",
"numpy.random.seed",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.show",
"matplotlib.ticker.NullFormatter",
... |
arp95/pytorch_image_classifier | [
"81db0a99b79dcebc39843869bf684c5090db6fdb"
] | [
"models/densenet121.py"
] | [
"# header files\nimport torch\nimport torch.nn as nn\nimport torchvision\nimport numpy as np\n\n\n# define network (remember input size: (224 x 224 x 3))\nclass DenseNet_121(torch.nn.Module):\n \n # define dense block\n def dense_block(self, input_channels):\n return torch.nn.Sequential(\n ... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.flatten",
"torch.nn.MaxPool2d",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.AdaptiveAvgPool2d"
]
] |
fugue-project/tune | [
"bf2288ddcb29c8345d996a9b22c0910da9002da1"
] | [
"tests/tune/_utils/test_values.py"
] | [
"import json\n\nimport numpy as np\nfrom tune._utils import normalize_hp\n\n\ndef test_normalize_hp():\n assert isinstance(np.int64(10), np.int64)\n assert 10 == normalize_hp(np.int64(10))\n assert not isinstance(normalize_hp(np.int64(10)), np.int64)\n\n assert json.dumps(dict(a=[0, 1], b=1.1, c=\"x\"))... | [
[
"numpy.float64",
"numpy.int64"
]
] |
IshitaTakeshi/DVO | [
"2c5a3db1db7e651bfaa7808bbf79a6c1c6a42fc5"
] | [
"examples/rgbd_desk.py"
] | [
"import csv\nimport sys\nfrom pathlib import Path\n\nsys.path.append(str(Path(__file__).resolve().parent.parent))\n\nfrom skimage.color import rgb2gray\nimport numpy as np\nfrom tqdm import tqdm\n\nfrom tadataka import VisualOdometry, CameraParameters\nfrom tadataka.rigid import exp_se3, log_se3\nfrom tadataka.proj... | [
[
"numpy.array",
"numpy.argmin",
"numpy.set_printoptions",
"numpy.copy",
"numpy.eye",
"matplotlib.pyplot.figure",
"numpy.power",
"matplotlib.pyplot.show",
"numpy.linspace",
"numpy.linalg.inv"
]
] |
YanchengWang/RegNet-Search-PyTorch | [
"e15f2d33d5e2191ff22e65f5257693894156b4fd"
] | [
"train.py"
] | [
"##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n## Created by: Hang Zhang\n## Email: zhanghang0704@gmail.com\n## Copyright (c) 2020\n##\n## LICENSE file in the root directory of this source tree \n##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n\nimport os\... | [
[
"torch.cuda.manual_seed",
"torch.distributed.init_process_group",
"torch.no_grad",
"torch.optim.SGD",
"torch.multiprocessing.spawn",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.utils.data.DataLoader",
"torch.utils.data.distributed.Distrib... |
ne7ermore/deeping-flow | [
"9414fa48139bac99824ae89cc45c6f59855fe7d4"
] | [
"hierarchical-sc/corpus.py"
] | [
"import os\nimport pickle\nimport math\n\nimport pandas as pd\n\nfrom const import *\n\n\ndef middle_save(obj, inf):\n pickle.dump(obj, open(inf, \"wb\"), True)\n\n\ndef middle_load(inf):\n return pickle.load(open(inf, \"rb\"))\n\n\ndef word2idx(sents, word2idx):\n return [[word2idx[w] if w in word2idx els... | [
[
"pandas.read_csv"
]
] |
vivekkhurana/handsign | [
"315e40e2d7b00a7e34cad870e6f90679e7bf7100"
] | [
"utils/general.py"
] | [
"# -*- coding: utf-8 -*-\n#\n# ColorHandPose3DNetwork - Network for estimating 3D Hand Pose from a single RGB Image\n# Copyright (C) 2017 Christian Zimmermann\n# \n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# ... | [
[
"tensorflow.reduce_min",
"numpy.ones_like",
"tensorflow.constant_initializer",
"tensorflow.nn.conv2d",
"tensorflow.nn.dilation2d",
"numpy.median",
"tensorflow.contrib.layers.xavier_initializer",
"numpy.copy",
"tensorflow.contrib.framework.assign_from_values",
"tensorflow.on... |
Mopolino8/postcipes | [
"5d67b383aa3e314b581b5262ba95f734ecb6369f"
] | [
"postcipes/bfs.py"
] | [
"# This file is part of postcipes\r\n# (c) Timofey Mukha\r\n# The code is released under the MIT Licence.\r\n# See LICENCE.txt and the Legal section in the README for more information\r\n\r\nfrom __future__ import absolute_import\r\nfrom __future__ import division\r\nfrom __future__ import print_function\r\nfrom .p... | [
[
"numpy.max",
"numpy.abs",
"numpy.zeros",
"numpy.append"
]
] |
GreatGameDota/CNN-Numpy-1D-Images | [
"6016701b54d7475b0c294355801bf8f6ce534852"
] | [
"CNN/Dense.py"
] | [
"import numpy as np\n\n\nclass Dense():\n\n def __init__(self, units, activation=None, use_bias=True, kernel_initializer='glorot_uniform', bias_initializer='zeros', input_shape=None):\n self._units = units\n self._activation = activation\n self._use_bias = use_bias\n self._kernal_init... | [
[
"numpy.random.standard_normal",
"numpy.reshape",
"numpy.zeros",
"numpy.sum",
"numpy.exp"
]
] |
leobxpan/robovat | [
"0d360c34c677cf018c4daab0b8e758943ae1d2c1"
] | [
"robovat/simulation/simulator.py"
] | [
"\"\"\"The Simulator class.\n\"\"\"\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport os.path\n\nimport numpy as np\nimport pybullet\n\nfrom robovat.math.pose import Pose\nfrom robovat.simulation import physics\nfrom robovat.simulation.body imp... | [
[
"numpy.linalg.norm",
"numpy.dot"
]
] |
akhti/torch-blocksparse | [
"49d029660dfa0fcf350f0e20f820872e9973973e"
] | [
"setup.py"
] | [
"#!/usr/bin/env python\n\nimport os\nimport torch\nfrom setuptools import setup, find_packages\nfrom torch.utils.cpp_extension import BuildExtension, CppExtension\n\ncmdclass = {}\ncmdclass['build_ext'] = BuildExtension\n\n\nimport setuptools\n\next_modules = [\n CppExtension(name='torch_blocksparse_cpp_utils',\... | [
[
"torch.utils.cpp_extension.CppExtension"
]
] |
oustar/scipylearn | [
"f3f3223f1170b39dc420606bdf989b6fcb705410"
] | [
"perceptron_np.py"
] | [
"\nimport numpy as np\n\nclass Perceptron(object):\n\n def __init__(self, input_num, activator):\n\n self.activator = activator\n self.weights = np.zeros((input_num))\n self.bias = 0.0\n\n def __str__(self):\n\n return 'weights\\t:%s\\nbias\\t:%f\\n' % (self.weights, self.bias)\n\n... | [
[
"numpy.array",
"numpy.dot",
"numpy.zeros"
]
] |
njamalova/whale_tail_identifier | [
"507ffe8838b42ca75dbd696c2faaa71252f417da"
] | [
"train_valid_split.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport os\nimport cv2\nimport tensorflow as tf\n\n\n# In[2]:\n\n\nimport pandas as pd\nimport numpy as np\n\nimport matplotlib.pyplot as plt\nfrom PIL import Image\n\n\n# In[3]:\n\n\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator\nfrom te... | [
[
"pandas.read_csv"
]
] |
actboy/espnet | [
"66f0f8382b0e1195bed7c280c29711f8436b3db4"
] | [
"espnet2/gan_tts/espnet_model.py"
] | [
"# Copyright 2021 Tomoki Hayashi\n# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)\n\n\"\"\"GAN-based TTS ESPnet model.\"\"\"\n\nfrom contextlib import contextmanager\nfrom distutils.version import LooseVersion\nfrom typing import Any\nfrom typing import Dict\nfrom typing import Optional\n\nimport torch\... | [
[
"torch.cuda.amp.autocast"
]
] |
c-rizz/autoencoding_rl | [
"65775630e87184c8809a31a8ef980853d5b49f9f"
] | [
"src/autoencoding_rl/latent_extractors/dyn_autoencoder/DynAutoencoder.py"
] | [
"\nfrom typing import Tuple\n\nimport torch as th\nimport torch.nn as nn\nfrom torchvision import transforms\n\nfrom autoencoding_rl.latent_extractors.autoencoder.SimpleEncoder import SimpleEncoder\nfrom autoencoding_rl.latent_extractors.autoencoder.SimpleDecoder import SimpleDecoder\nfrom autoencoding_rl.utils imp... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.split",
"torch.nn.ReLU"
]
] |
MBaltz/dival | [
"b7c10ed471d05242312a7d4916900c92e0c36cdb",
"b7c10ed471d05242312a7d4916900c92e0c36cdb"
] | [
"dival/reconstructors/dip_ct_reconstructor.py",
"dival/examples/ct_train_learnedpd.py"
] | [
"from warnings import warn\nfrom functools import partial\nfrom tqdm import tqdm\nimport torch\nimport numpy as np\n\nfrom torch.optim import Adam\nfrom torch.nn import MSELoss\n\nfrom odl.contrib.torch import OperatorModule\n\nfrom dival.reconstructors import IterativeReconstructor\nfrom dival.reconstructors.netwo... | [
[
"torch.nn.MSELoss",
"numpy.asarray",
"torch.random.manual_seed",
"torch.cuda.is_available",
"torch.randn"
],
[
"numpy.mean"
]
] |
meteor1993/python-learning | [
"4ee574c9360caf6e63bb6ee2ef31fa6a9918fa40"
] | [
"python-data-analysis/2019-nCoV-global/global_map.py"
] | [
"from pyecharts import options as opts\r\nfrom pyecharts.charts import Map\r\nimport pandas as pd\r\nimport namemap\r\n\r\ndef read_country_code():\r\n \"\"\"\r\n 获取国家中英文字典\r\n :return:\r\n \"\"\"\r\n country_dict = {}\r\n for key, val in namemap.nameMap.items(): # 将 nameMap 列表里面键值互换\r\n c... | [
[
"pandas.read_csv"
]
] |
santosh653/dtcwt | [
"01d9e87dc9abfa244a89c1f05aebf3dec6999f3a"
] | [
"docs/image-registration.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nAn example of image registration via the DTCWT.\n\nThis script demonstrates some methods for image registration using the DTCWT.\n\n\"\"\"\n\nfrom __future__ import division, print_function\n\nimport itertools\nimport logging\nimport os\n\nfrom matplotlib.pyplot import *\nimport nump... | [
[
"numpy.median",
"numpy.zeros_like",
"numpy.arange",
"numpy.sqrt"
]
] |
aManOf502/tqsdk-python | [
"b766b45bb82c89a0401a6a84e0e42600fa10e6f4"
] | [
"tqsdk/utils.py"
] | [
"#!usr/bin/env python3\n# -*- coding:utf-8 -*-\n__author__ = 'yanqiong'\n\n\nimport random\nimport secrets\nfrom bisect import bisect_right\n\nfrom sgqlc.operation import Operation\nfrom pandas.core.internals import BlockManager\n\nfrom tqsdk.ins_schema import ins_schema, _add_all_frags\n\nRD = random.Random(secret... | [
[
"pandas.core.internals.BlockManager.__init__"
]
] |
jmaces/robust-nets | [
"25d49302f9fa5fcc9ded2727de75e96e25243d09",
"25d49302f9fa5fcc9ded2727de75e96e25243d09",
"25d49302f9fa5fcc9ded2727de75e96e25243d09",
"25d49302f9fa5fcc9ded2727de75e96e25243d09"
] | [
"tvsynth/script_train_unet_it_tikh_jitter.py",
"tvsynth/find_adversarial.py",
"ellipses/config_robustness_radon.py",
"ellipses/script_robustness_fourier_table_adv.py"
] | [
"import os\n\nimport matplotlib as mpl\nimport torch\n\nfrom data_management import Jitter, load_dataset\nfrom networks import IterativeNet, UNet\nfrom operators import TVAnalysis, get_tikhonov_matrix\n\n\n# --- load configuration -----\nimport config # isort:skip\n\n# ----- general setup -----\nmpl.use(\"agg\")\n... | [
[
"matplotlib.use",
"torch.device",
"torch.nn.MSELoss",
"torch.nn.Linear"
],
[
"torch.device",
"torch.nn.MSELoss",
"torch.no_grad",
"torch.optim.Adam",
"torch.tanh",
"torch.log"
],
[
"pandas.read_pickle",
"torch.device",
"torch.nn.MSELoss",
"pandas.Dat... |
robashaw/basisopt | [
"c02fd307bc72c576ed298ea14648818b237d2f30"
] | [
"basisopt/opt/eventemper.py"
] | [
"import numpy as np\nfrom mendeleev import element as md_element\n\nfrom basisopt import api, data\nfrom basisopt.exceptions import PropertyNotAvailable\nfrom basisopt.basis import even_temper_expansion\nfrom basisopt.basis.guesses import null_guess\nfrom .preconditioners import unit\nfrom .strategies import Strate... | [
[
"numpy.sum",
"numpy.array",
"numpy.abs"
]
] |
liuh127/Two-branch-dehazing | [
"2861089977876e2809f094b19dc529200af54f00"
] | [
"perceptual.py"
] | [
"# --- Imports --- #\nimport torch\nimport torch.nn.functional as F\n\n# --- Perceptual loss network --- #\nclass LossNetwork(torch.nn.Module):\n def __init__(self, vgg_model):\n super(LossNetwork, self).__init__()\n self.vgg_layers = vgg_model\n self.layer_name_mapping = {\n '3'... | [
[
"torch.nn.functional.mse_loss"
]
] |
mondrasovic/multi_object_tracking_demo | [
"d4ec6af4e3bca9d47628358967a05890071407ee"
] | [
"vehicle_tracker/visual.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n# Author: Milan Ondrasovic <milan.ondrasovic@gmail.com>\n\nimport random\n\nfrom typing import Sequence, Tuple, Dict, cast\n\nimport cv2 as cv\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom tracking import TrackedDetection\n\nColorT = Tuple[int, int, ... | [
[
"matplotlib.pyplot.cm.get_cmap",
"numpy.ones_like"
]
] |
vikasbahirwani/SequenceTagging | [
"b4e0dc2a71f869a27ada003c9276fd1f269e230d"
] | [
"src/model/lstm_crf/main.py"
] | [
"# reimplementation of https://github.com/guillaumegenthial/tf_ner/blob/master/models/lstm_crf/main.py\n\nimport functools\nimport json\nimport logging\nfrom pathlib import Path\nimport sys\nimport numpy as np\nimport tensorflow as tf\n# tf.enable_eager_execution()\nfrom tf_metrics import precision, recall, f1\n\nD... | [
[
"tensorflow.contrib.rnn.TimeReversedFusedRNN",
"numpy.load",
"tensorflow.nn.embedding_lookup",
"tensorflow.contrib.lookup.index_table_from_file",
"tensorflow.contrib.rnn.LSTMBlockFusedCell",
"tensorflow.concat",
"tensorflow.estimator.TrainSpec",
"tensorflow.Variable",
"tensorfl... |
dredwardhyde/tinygrad-universal | [
"aeb28fc42fb40e9848613ce81811a727fee6f313"
] | [
"tinygrad/ops_cpu.py"
] | [
"import numpy as np\n\nfrom .tensor import Function\n\n\n# ************* unary ops *************\n\nclass ReLU(Function):\n @staticmethod\n def forward(ctx, input):\n ctx.save_for_backward(input)\n return np.maximum(input, 0)\n\n @staticmethod\n def backward(ctx, grad_output):\n inp... | [
[
"numpy.pad",
"numpy.lib.stride_tricks.as_strided",
"numpy.zeros_like",
"numpy.log",
"numpy.zeros",
"numpy.exp",
"numpy.tensordot",
"numpy.swapaxes",
"numpy.transpose",
"numpy.argsort",
"numpy.moveaxis",
"numpy.maximum"
]
] |
pschuh/flax | [
"9eee5149f345bd871555f3b53e3605f58588c883"
] | [
"tests/linen/linen_linear_test.py"
] | [
"# Copyright 2021 The Flax Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or a... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.full",
"numpy.einsum"
]
] |
XpressAI/spark | [
"0a838dcd71c733289e60d9f74e8267027c7b2c4a"
] | [
"python/pyspark/pandas/generic.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.api.types.is_list_like"
]
] |
spongezhang/maskgen | [
"7284e300d1cb326a5349879de0bace9cfa8788a8",
"7284e300d1cb326a5349879de0bace9cfa8788a8"
] | [
"plugins/CropPermutations/__init__.py",
"tests/MedianBlurTest.py"
] | [
"from PIL import Image\nimport numpy\nfrom random import randint\n\n\"\"\"\nA plugin used to create a set of variable spefications for permutation groups.\n\"\"\"\n\ndef transform(img,source,target,**kwargs):\n cv_image = numpy.array(img)\n shape = cv_image.shape\n snapto8 = 'eightbit_boundary' in kwargs ... | [
[
"numpy.array"
],
[
"numpy.random.randint",
"numpy.zeros"
]
] |
dasmy/minibatchNMF | [
"f7f910e290103c26e2925426849f8bfbe75ba242"
] | [
"beta_nmf_minibatch.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nbeta\\_nmf_minibatch.py\n~~~~~~~~~~~\n\n.. topic:: Contents\n\n The beta_nmf_minibatch module includes the betaNMF class,\n fit function and theano functions to compute updates and cost.\n \n Copyright 2014-2016 Romain Serizel\n This software is distributed under the terms... | [
[
"numpy.ceil",
"numpy.asarray",
"numpy.zeros",
"numpy.reshape",
"numpy.true_divide",
"numpy.ones",
"numpy.random.shuffle",
"numpy.arange",
"numpy.hstack",
"numpy.floor"
]
] |
udham2511/Python-Screen-Recorder | [
"419be068398f15128f1279bd68a64c285b60493b"
] | [
"recorder.py"
] | [
"from PIL import ImageGrab\r\nimport pyautogui\r\nimport numpy\r\nimport time\r\nimport cv2\r\nimport os\r\n\r\n\r\ntimeA = time.time()\r\nfourcc = cv2.VideoWriter_fourcc(*\"XVID\")\r\nname = f\"Recording{len(os.listdir())-2}.mp4\"\r\nout = cv2.VideoWriter(name, fourcc, 14.0, (1920, 1080))\r\n\r\nwhite = (255, 255,... | [
[
"numpy.array"
]
] |
Jiaming1999/ChainConsumer | [
"5606696525d91f11d8093085934fa352b98ce97c",
"5606696525d91f11d8093085934fa352b98ce97c"
] | [
"examples/customisations/plot_rainbow_serif_bins.py",
"chainconsumer/diagnostic.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n=======================\nCmap and Custom Bins\n=======================\n\nInvoke the cmap colour scheme and choose how many bins to use with your data.\n\nBy default, the cmap colour scheme is used if you have many, many chains. You can\nenable it before that point if you wish and ... | [
[
"numpy.random.normal",
"numpy.dot",
"numpy.random.seed",
"numpy.identity",
"numpy.random.random"
],
[
"scipy.stats.normaltest",
"numpy.sum",
"numpy.mean",
"numpy.split",
"numpy.sqrt",
"numpy.abs",
"numpy.all",
"numpy.var",
"numpy.floor"
]
] |
hakimakbarmaulana/dtaidistance | [
"ddf4a8111732d4429686d96c9195a81151be1dd8"
] | [
"tests/test_clustering.py"
] | [
"import os\nimport sys\nimport tempfile\nimport pytest\nimport logging\nfrom pathlib import Path\n\nfrom dtaidistance import dtw, dtw_ndim, clustering, util_numpy\nimport dtaidistance.dtw_visualisation as dtwvis\nfrom dtaidistance.exceptions import PyClusteringException\n\n\nlogger = logging.getLogger(\"be.kuleuven... | [
[
"matplotlib.pyplot.subplots"
]
] |
pei223/deepext_with_lightning | [
"e40ac19844a05864f803431d8ef4a534286a0950"
] | [
"deepext_with_lightning/metrics/object_detection.py"
] | [
"from typing import List, Tuple, Union\n\nimport numpy as np\nimport torch\n\nimport pytorch_lightning as pl\n\n\ndef calc_area(bbox: np.ndarray):\n return (bbox[2] - bbox[0]) * (bbox[3] - bbox[1])\n\n\ndef calc_bbox_overlap_union_iou(pred: np.ndarray or None, teacher: np.ndarray) -> Tuple[float, float, float]:\... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.count_nonzero",
"numpy.minimum",
"numpy.sum",
"numpy.where",
"numpy.finfo",
"numpy.argsort",
"numpy.cumsum",
"torch.mean",
"numpy.maximum"
]
] |
uw-ipd/numba | [
"26dde2b28cadda403a5549a84dc1698900b23f74",
"26dde2b28cadda403a5549a84dc1698900b23f74",
"26dde2b28cadda403a5549a84dc1698900b23f74",
"26dde2b28cadda403a5549a84dc1698900b23f74"
] | [
"examples/linear_regression/linear_regression_numba.py",
"numba/tests/test_pycc.py",
"numba/typing/arraydecl.py",
"numba/cuda/tests/cudapy/test_smart_array.py"
] | [
"#\n# Copyright (c) 2017 Intel Corporation\n# SPDX-License-Identifier: BSD-2-Clause\n#\n\nimport numba\nimport numpy as np\nimport argparse\nimport time\n\n@numba.njit()\ndef linear_regression(Y, X, w, iterations, alphaN):\n for i in range(iterations):\n w -= alphaN * np.dot(X.T, np.dot(X,w)-Y)\n retur... | [
[
"numpy.dot",
"numpy.zeros",
"numpy.random.seed",
"numpy.sum",
"numpy.random.random"
],
[
"numpy.float64",
"numpy.complex128",
"numpy.random.RandomState"
],
[
"numpy.ndim"
],
[
"numpy.arange"
]
] |
brusic/nlpia | [
"e239074eaa1fd51eb1c9a35d53a69e3b15343f57"
] | [
"nlpia/book/examples/ch09.py"
] | [
"\n# coding: utf-8\n\n# In[ ]:\n\n\nimport os\nimport re\nimport tarfile\n\nimport requests\n\nfrom pugnlp.futil import path_status, find_files\n\n\n# In[ ]:\n\n\n# From the nlpia package for downloading data too big for the repo\n\nBIG_URLS = {\n 'w2v': (\n 'https://www.dropbox.com/s/965dir4dje0hfi4/Goog... | [
[
"numpy.array",
"numpy.asarray",
"numpy.log",
"numpy.sum",
"numpy.exp",
"numpy.argmax",
"numpy.random.multinomial"
]
] |
lbg251/ClusterTrellis | [
"06e9c8cd3f04f606e185b95f4d68703a34cc86ef"
] | [
"src/ClusterTrellis/utils.py"
] | [
"import os\nimport pickle\nimport string\nimport time\nimport logging\nimport numpy as np\n\n\n\ndef get_logger(name=__file__, level=logging.INFO):\n logger = logging.getLogger(name)\n\n if getattr(logger, \"_init_done__\", None):\n logger.setLevel(level)\n return logger\n\n logger._init_done... | [
[
"numpy.sum"
]
] |
matsuken92/optuna | [
"79ce70c24c2150ffc8a4fd243e664976c6e1acef"
] | [
"examples/xgboost_simple.py"
] | [
"\"\"\"\nOptuna example that optimizes a classifier configuration for cancer dataset\nusing XGBoost.\n\nIn this example, we optimize the validation accuracy of cancer detection\nusing XGBoost. We optimize both the choice of booster model and their hyper\nparameters.\n\nWe have following two ways to execute this exa... | [
[
"sklearn.model_selection.train_test_split",
"numpy.rint"
]
] |
J-Moravec/pairtree | [
"91cbba628b78aea31034efb080976fdb47d83976",
"91cbba628b78aea31034efb080976fdb47d83976"
] | [
"comparison/pwgs/convert_inputs.py",
"comparison/pairtree/convert_simdata_to_results.py"
] | [
"import sys\nimport os\nimport argparse\nimport json\nimport numpy as np\n\nsys.path.append(os.path.join(os.path.dirname(__file__), '..', '..', 'lib'))\nimport inputparser\nimport clustermaker\n\ndef write_ssms(variants, outfn):\n _stringify = lambda A: ','.join([str(V) for V in A])\n mu_r = 0.999\n cols = ('id'... | [
[
"numpy.mean"
],
[
"numpy.savez_compressed"
]
] |
tbarford/bg_streamlit_demo | [
"72e54d2c9cff278edf1852ae04893fdb80d8ed4d"
] | [
"streamlit_app.py"
] | [
"##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~##\r\n##python3 script created by tBarford on 20220205\r\n##\r\n##\r\n##File Description: This is the streamlit webapp MVP for BG Golf EI Profile Database Demo\r\n## run in term w/ : streamlit run streamlit_app.py\r\n##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~## \r\n\... | [
[
"matplotlib.pyplot.subplots"
]
] |
Yudonggeun/PySC2-Tutorial | [
"80449c3b5774a58e8ee6490379890e9abd60a11a"
] | [
"7. Using Reward for Agent/reward_agent.py"
] | [
"import random\nimport math\nimport os.path\n\nimport numpy as np\nimport pandas as pd\n\nfrom pysc2.agents import base_agent\nfrom pysc2.lib import actions\nfrom pysc2.lib import features\n\n_NO_OP = actions.FUNCTIONS.no_op.id\n_SELECT_POINT = actions.FUNCTIONS.select_point.id\n_BUILD_SUPPLY_DEPOT = actions.FUNCTI... | [
[
"pandas.read_pickle",
"numpy.random.choice",
"numpy.zeros",
"pandas.DataFrame",
"numpy.random.permutation",
"numpy.random.uniform"
]
] |
UpSea/midProjects | [
"ed6086e74f68b1b89f725abe0b270e67cf8993a8"
] | [
"BasicOperations/05_Pandas/05_Pandas_02_groupby.py"
] | [
"import pandas as pd\nimport numpy as np\n\n\ndf = pd.DataFrame(np.random.randn(10,3),columns=['a','b','c'],index=list('abcdefghij'))\nprint(df)\ndf.ix[::2,0] = np.nan; df.ix[::4,1] = np.nan; df.ix[::3,2] = np.nan;\n\ndf = df.dropna(subset=['a','b']) #mid delete rows where df['htm3']==na\nbins = np.arange(-3,3,0.... | [
[
"numpy.random.randn",
"numpy.arange",
"numpy.digitize"
]
] |
rexxxx1234/SAUNet-demo | [
"20e968e1d42217c89cdf4fc304ed2d8717697eec"
] | [
"data/crop_and_pad_augmentations.py"
] | [
"# Copyright 2017 Division of Medical Image Computing, German Cancer Research Center (DKFZ)\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/... | [
[
"numpy.pad",
"numpy.random.randint"
]
] |
861934367/genecast | [
"b4c5710aef526f4e3bdf0ba3594dab583068eca3"
] | [
"genecast_package/core.py"
] | [
"## this tool is the core function of cnv and snv analysis\n## author: taozhou\n## email: zhou.tao@genecast.com.cn\n\nimport matplotlib as mpl\nmpl.use('Agg')\nimport warnings\nwarnings.filterwarnings(\"ignore\")\nimport itertools\nimport seaborn as sns\nimport matplotlib.pylab as plt\nimport matplotlib.colors as m... | [
[
"matplotlib.use",
"matplotlib.pylab.savefig",
"matplotlib.pylab.ylabel",
"pandas.DataFrame",
"matplotlib.pylab.legend",
"matplotlib.pylab.close",
"matplotlib.pylab.xlabel",
"matplotlib.pylab.subplots",
"scipy.stats.ranksums",
"pandas.Series",
"matplotlib.pylab.title",
... |
hoangphucITJP/tpu | [
"e4ce0d8eb61a828d4b5fe09effd082356e88545c"
] | [
"models/official/detection/modeling/architecture/resnet.py"
] | [
"# Lint as: python2, python3\n# Copyright 2019 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/... | [
[
"tensorflow.compat.v1.variable_scope",
"tensorflow.compat.v1.identity",
"tensorflow.compat.v1.layers.max_pooling2d"
]
] |
LJeub/Local2Global_embedding | [
"22e1818639043444f97655d944997a171b992745"
] | [
"local2global_embedding/run.py"
] | [
"\"\"\"Training run script\"\"\"\n\nimport argparse\nimport json\nfrom pathlib import Path\nfrom bisect import bisect_left\n\nimport torch\nimport torch_geometric as tg\nimport matplotlib.pyplot as plt\nimport local2global as l2g\n\nfrom local2global_embedding.embedding import speye, train, embedding, VGAE_model, V... | [
[
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.xlabel",
"torch.save",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure",
"torch.as_tensor",
"torch.load",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
... |
KarhouTam/FedLab-benchmarks | [
"6de0ca56f645794ca7eae0f19c6b0117165d3404"
] | [
"fedlab_benchmarks/fedmgda+/standalone.py"
] | [
"from json import load\nimport os\nimport argparse\nimport random\nfrom copy import deepcopy\nimport torchvision\nimport torchvision.transforms as transforms\nfrom torch import nn\nimport sys\nimport torch\nimport numpy as np\nimport cvxopt\ntorch.manual_seed(0)\n\nfrom fedlab.core.client.serial_trainer import Subs... | [
[
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.ones",
"torch.manual_seed",
"torch.nn.CrossEntropyLoss"
]
] |
BrunoKM/rhoana_graph_tools | [
"7150f4bc6337ecf51dd9123cf03561a57d655160"
] | [
"utils/graph_utils.py"
] | [
"import numpy as np\nimport networkx as nx\n\nif __name__ == '__main__':\n from ged4py.algorithm import graph_edit_dist\nelse:\n from .ged4py.algorithm import graph_edit_dist\n\ndef rearrange_adj_matrix(matrix, ordering):\n assert matrix.ndim == 2\n # Check that matrix is square\n assert matrix.shape... | [
[
"numpy.sum",
"numpy.arange",
"numpy.zeros",
"numpy.random.shuffle"
]
] |
webclinic017/qf-lib | [
"96463876719bba8a76c8269cef76addf3a2d836d",
"96463876719bba8a76c8269cef76addf3a2d836d"
] | [
"qf_lib_tests/integration_tests/backtesting/alpha_model_strategy_testers/test_alpha_model_strategy_for_stop_losses_intraday.py",
"qf_lib/plotting/charts/surface_chart_3d.py"
] | [
"# Copyright 2016-present CERN – European Organization for Nuclear Research\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/licen... | [
[
"numpy.testing.assert_almost_equal",
"numpy.arange",
"numpy.reshape",
"numpy.testing.assert_equal"
],
[
"numpy.array",
"matplotlib.pyplot.title",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"numpy.meshgrid",
"matplotlib.get_backend"
]
] |
zhaowt96/models | [
"03182253673b0e2666ad9a33839759834c0acebd",
"03182253673b0e2666ad9a33839759834c0acebd"
] | [
"research/object_detection/builders/calibration_builder_test.py",
"research/slim/datasets/flowers.py"
] | [
"# Lint as: python2, python3\n# Copyright 2019 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/... | [
[
"scipy.interpolate.interp1d",
"tensorflow.convert_to_tensor",
"numpy.asarray",
"tensorflow.constant",
"tensorflow.test.main",
"numpy.repeat",
"numpy.linspace"
],
[
"tensorflow.FixedLenFeature",
"tensorflow.zeros"
]
] |
e-mayo/mscreen | [
"2dd2316837bcb7c19384294443b2855e5ccd3e01"
] | [
"mscreen/autodocktools_prepare_py3k/AutoDockTools/Utilities24/rotate_molecule.py"
] | [
"#!/usr/bin/env python\n#$Id: rotate_molecule.py,v 1.2.10.1 2016/02/11 09:24:08 annao Exp $\nimport os \nfrom MolKit import Read\nfrom MolKit.pdbWriter import PdbWriter, PdbqsWriter, PdbqWriter, PdbqtWriter\nfrom mglutil.math.rotax import rotax\nimport numpy\n\n\nif __name__ == '__main__':\n import sys\n impo... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.dot",
"numpy.add.reduce",
"numpy.ones"
]
] |
ryanhammonds/nilearn | [
"f33cd4e4685d9050e5bba0a8ece1b0b0f0ad1be2",
"f33cd4e4685d9050e5bba0a8ece1b0b0f0ad1be2"
] | [
"nilearn/plotting/tests/test_html_connectome.py",
"nilearn/input_data/tests/test_multi_nifti_masker.py"
] | [
"import warnings\n\nimport numpy as np\n\nfrom nilearn.plotting import cm\nfrom nilearn.plotting.js_plotting_utils import decode\nfrom nilearn.plotting import html_connectome\n\nfrom .test_js_plotting_utils import check_html\n\n\ndef test_prepare_line():\n e = np.asarray([0, 1, 2, 3], dtype=int)\n n = np.asar... | [
[
"numpy.asarray",
"numpy.eye",
"numpy.allclose",
"numpy.arange",
"numpy.diag"
],
[
"numpy.logical_or",
"numpy.random.rand",
"numpy.zeros",
"numpy.testing.assert_array_equal",
"numpy.ones",
"numpy.eye",
"numpy.prod",
"numpy.diag"
]
] |
IkeoluwaStat/QFT | [
"fe36763e90e3601dfab2a78a08962113343efd0c"
] | [
"MetafierV2.py"
] | [
"# Metafier V2: writes directly to output.mc\r\n# Uses numpy and memoization to speed up a crap ton & compress data a bit\r\n# ===REQUIRES metatemplate11.mc===\r\n\r\nimport golly as g\r\nimport numpy as np\r\nfrom shutil import copyfile\r\n\r\n#Get the selection\r\nselection = g.getselrect()\r\nif not selection: g... | [
[
"numpy.isnan",
"numpy.log2",
"numpy.reshape",
"numpy.zeros"
]
] |
Can-Zhao/MONAI | [
"e0db5a564225a7cb62e7a23df97267019006302f",
"e0db5a564225a7cb62e7a23df97267019006302f",
"e0db5a564225a7cb62e7a23df97267019006302f"
] | [
"tests/test_integration_workflows_gan.py",
"tests/test_spacingd.py",
"monai/networks/blocks/warp.py"
] | [
"# Copyright (c) MONAI Consortium\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# http://www.apache.org/licenses/LICENSE-2.0\n# Unless required by applicable law or agreed to in... | [
[
"torch.nn.Sigmoid",
"torch.add",
"numpy.eye",
"torch.manual_seed",
"torch.cuda.is_available",
"torch.nn.BCELoss"
],
[
"numpy.testing.assert_allclose",
"numpy.ones",
"numpy.eye",
"numpy.arange",
"numpy.diag"
],
[
"torch.nn.functional.grid_sample",
"torch.... |
bccp/bananaplots | [
"dbfe107207e07351c7d7125430fde16fb2731cc2"
] | [
"bananas/model.py"
] | [
"import numpy\n# FIXME: copy the functions here\n\nfrom sklearn.mixture.gmm import log_multivariate_normal_density, logsumexp\n\ndef sample_gaussian2(means, cv, size, random_state, mins, maxes):\n def once(size1):\n g = random_state.multivariate_normal(means, cv, size1).T\n g = g.reshape(len(means)... | [
[
"numpy.array",
"numpy.empty",
"numpy.log",
"numpy.percentile",
"sklearn.mixture.gmm.log_multivariate_normal_density",
"numpy.interp",
"numpy.exp",
"sklearn.mixture.GMM",
"numpy.append",
"sklearn.mixture.gmm.logsumexp",
"numpy.logspace"
]
] |
THinnerichs/MiS-Information-Clustering | [
"597c70e1283222e0e841e24f6805b967aaf3c9e0"
] | [
"src/scripts/segmentation/baselines/kmeans_and_sift.py"
] | [
"from __future__ import print_function\n\nimport argparse\nimport os\nimport pickle\nimport sys\n\nimport cv2\nimport numpy as np\nimport torch\nimport vlfeat # calls constructor\nfrom sklearn.cluster import MiniBatchKMeans\n\nfrom src.utils.cluster.eval_metrics import _hungarian_match, _original_match, \\\n _acc... | [
[
"torch.zeros",
"numpy.random.choice",
"sklearn.cluster.MiniBatchKMeans",
"numpy.zeros",
"torch.from_numpy",
"numpy.arange"
]
] |
garston2/tensorflow | [
"bbe056e5a0ab81b67fcb6053400812b3d5805fc7"
] | [
"tensorflow/tensorboard/plugins/projector/projector_plugin_test.py"
] | [
"# Copyright 2017 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... | [
[
"numpy.fromstring",
"numpy.array",
"tensorflow.python.platform.gfile.GFile",
"numpy.array_equal",
"tensorflow.python.framework.ops.Graph",
"tensorflow.python.ops.variable_scope.get_variable",
"tensorflow.tensorboard.plugins.projector.projector_plugin.ProjectorPlugin",
"tensorflow.p... |
Bobgy/model-analysis | [
"a964d2e8430b447c898d271fb6e6d8f5b99adf4b",
"a964d2e8430b447c898d271fb6e6d8f5b99adf4b"
] | [
"tensorflow_model_analysis/api/model_eval_lib.py",
"tensorflow_model_analysis/extractors/auto_slice_key_extractor_test.py"
] | [
"# Lint as: python3\n# Copyright 2018 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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appli... | [
[
"tensorflow.io.gfile.GFile",
"tensorflow.version.VERSION.split",
"tensorflow.io.gfile.makedirs",
"tensorflow.io.gfile.exists",
"tensorflow.compat.v1.logging.warning",
"tensorflow.compat.v1.python_io.tf_record_iterator"
],
[
"numpy.array",
"tensorflow.test.main"
]
] |
saridormi/commit_message_generation | [
"c25db61a5f41accfb566caaea5feb0d275751293"
] | [
"src/model/encoder_decoder_module.py"
] | [
"from copy import copy\nfrom typing import Optional\n\nimport torch\nimport pytorch_lightning as pl\nfrom transformers import (\n EncoderDecoderModel,\n RobertaModel,\n RobertaConfig,\n GPT2LMHeadModel,\n GPT2Config,\n RobertaTokenizer,\n GPT2Tokenizer,\n AdamW,\n get_linear_schedule_with... | [
[
"torch.stack"
]
] |
Xaenalt/model_server | [
"f977dbf1246ebf85e960ca058e814deac7c6a16c"
] | [
"example_client/multi_inputs.py"
] | [
"#\n# Copyright (c) 2019-2020 Intel Corporation\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applic... | [
[
"tensorflow.make_tensor_proto",
"tensorflow.make_ndarray"
]
] |
LaurenceBeard/improver | [
"b7cfe44f3a802d2a3d65f76a325215033c9de074",
"b7cfe44f3a802d2a3d65f76a325215033c9de074"
] | [
"improver_tests/ensemble_copula_coupling/ensemble_copula_coupling/test_ConvertLocationAndScaleParameters.py",
"improver/utilities/solar.py"
] | [
"# -*- coding: utf-8 -*-\n# -----------------------------------------------------------------------------\n# (C) British Crown Copyright 2017-2019 Met Office.\n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following c... | [
[
"numpy.array"
],
[
"numpy.max",
"numpy.zeros_like",
"numpy.sin",
"numpy.arcsin",
"numpy.tan",
"numpy.ones",
"numpy.min",
"numpy.degrees",
"numpy.radians",
"numpy.where",
"numpy.cos"
]
] |
rogall-e/advent_of_code | [
"a8c41fb63478dd7b99c88c4fa99b7ba0bab3842d"
] | [
"2021/day4_part1.py"
] | [
"import numpy as np # import numpy\n\nwith open(\"data/day4.txt\") as f:\n drawing_numbers = f.readline()\n board_lst = []\n board_line = []\n counter = 0\n\n for line in f:\n if line != '\\n':\n board_line.append(line.strip()) \n if len(board_line) == 5:\n board... | [
[
"numpy.where",
"numpy.array",
"numpy.isnan",
"numpy.nansum"
]
] |
wangleon/gamse | [
"ed2a3730469a1eeef3def1beca990e9d2641a53b"
] | [
"gamse/utils/onedarray.py"
] | [
"from itertools import tee\nimport numpy as np\nimport scipy.interpolate as intp\nfrom scipy.signal import savgol_filter\n\ndef get_edge_bin(array):\n \"\"\"Detect the edge indcies of a binary 1-D array.\n\n Args:\n array (:class:`numpy.ndarray`): A list or Numpy 1d array, with binary\n (0/1... | [
[
"numpy.array",
"numpy.ones_like",
"numpy.matrix",
"scipy.interpolate.InterpolatedUnivariateSpline",
"numpy.zeros",
"numpy.roll",
"numpy.logical_and",
"numpy.diff",
"numpy.nonzero",
"numpy.where",
"numpy.arange",
"numpy.append",
"numpy.int64",
"numpy.insert"
... |
RosaYen/DP_FL_recreation | [
"30607645d9633483a4afa50c0e00bea65c0fb355"
] | [
"DP_FL_recreate/opacus/tests/layers_grad_test.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport unittest\n\nimport torch\nimport torch.nn as nn\nfrom opacus import PerSampleGradientClipper\nfrom opacus.dp_model_inspector import DPModelInspector\nfrom opacus.layers import DPLSTM, DPMultiheadAttention, Sequen... | [
[
"torch.nn.Embedding",
"torch.nn.Linear",
"torch.nn.InstanceNorm1d",
"torch.cuda.manual_seed",
"torch.nn.LayerNorm",
"torch.nn.init.uniform_",
"torch.nn.Conv1d",
"torch.nn.GroupNorm",
"torch.nn.L1Loss",
"torch.manual_seed",
"torch.nn.Conv2d",
"torch.randint",
"to... |
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