repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
jackonelli/ensemble_distr_distillation | [
"1abfb0d3b546b4e232e0ad05e1717bfe5489d6f8",
"1abfb0d3b546b4e232e0ad05e1717bfe5489d6f8"
] | [
"src/dataloaders/cifar10.py",
"src/experiments/cifar10/resnet_utils.py"
] | [
"\"\"\"Data loader for CIFAR data\"\"\"\nimport logging\nimport torch\nimport torchvision\nimport torchvision.transforms as transforms\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom PIL import Image\n\n\nclass Cifar10Data:\n \"\"\"CIFAR data wrapper\n Create instance like this:\n trainloader = ... | [
[
"numpy.array",
"matplotlib.pyplot.show",
"torch.utils.data.DataLoader",
"torch.tensor"
],
[
"torch.nn.Sequential",
"torch.nn.Conv2d",
"torch.nn.functional.relu",
"torch.nn.BatchNorm2d"
]
] |
askmetoo/One-FM | [
"c93ed63695a3e62ee8129bd9adf563116b749030"
] | [
"one_fm/api/mobile/roster.py"
] | [
"import frappe\r\nfrom frappe import _\r\nfrom frappe.utils import getdate, cint, cstr, random_string, now_datetime\r\nfrom frappe.client import get_list\r\nimport pandas as pd\r\nimport json, base64, ast, itertools, datetime\r\nfrom frappe.client import attach_file\r\nfrom one_fm.one_fm.page.roster.roster import g... | [
[
"pandas.offsets.MonthBegin",
"pandas.DatetimeIndex",
"pandas.date_range",
"pandas.offsets.MonthEnd",
"pandas.Timestamp"
]
] |
mvinyard/python-developer-kit | [
"0f92baef747a052c03e209126a8ed5ce65977aa8"
] | [
"pydk/_rounding.py"
] | [
"import numpy as np\n\n\ndef _ceil(x, precision=0):\n\n \"\"\"\n Round to the nearest lower bound within the given precision.\n\n Parameters:\n -----------\n x\n array or value\n type: numpy.ndarray or int or float\n\n precision\n positions left (negative) or right (positive) of the decim... | [
[
"numpy.ceil",
"numpy.floor"
]
] |
carsonmckee/bayesglm | [
"443c65c1763fb287e7a0ad1fa516ebf92557f0b3"
] | [
"tests/test_utils.py"
] | [
"import unittest\nimport sys\nsys.path.append('/Users/carsonmckee/Dev/bayesglm_2/bayesglm')\nimport utils\nimport pandas\n\nclass TestModelMatrix(unittest.TestCase):\n\n def setUp(self):\n self.data = pandas.DataFrame(data=[[1,\"A\",3,4,5], [6,\"B\",8,9,10], [11,\"C\",13,14,15]],\n ... | [
[
"pandas.DataFrame"
]
] |
plus2047/overiva | [
"9339a7dbb484d4ba8c3f84a9b111c51e77055bfa"
] | [
"ive.py"
] | [
"# Copyright (c) 2019 Robin Scheibler\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, merge, ... | [
[
"numpy.conj",
"numpy.sqrt",
"numpy.linalg.inv",
"numpy.linalg.eig",
"numpy.linalg.norm",
"numpy.ones",
"numpy.max",
"numpy.argmax",
"numpy.array",
"numpy.zeros"
]
] |
YYD888/deeprl-baselines | [
"773eaede741f5db9c52046e3016f06dff41d0d8f"
] | [
"baselines/rainbow/experiments/atari/model.py"
] | [
"import tensorflow as tf\nimport tensorflow.contrib.layers as layers\n\n\ndef layer_norm_fn(x, relu=True):\n x = layers.layer_norm(x, scale=True, center=True)\n if relu:\n x = tf.nn.relu(x)\n return x\n\n\ndef model(img_in, num_actions, scope, reuse=False, layer_norm=False, distributed=False, atoms=... | [
[
"tensorflow.nn.relu",
"tensorflow.contrib.layers.convolution2d",
"tensorflow.shape",
"tensorflow.reduce_mean",
"tensorflow.reshape",
"tensorflow.expand_dims",
"tensorflow.contrib.layers.fully_connected",
"tensorflow.contrib.layers.layer_norm",
"tensorflow.contrib.layers.flatten... |
yCobanoglu/mmocr | [
"3d2a91955efe134a0a33ca00d0d45632813b6b46"
] | [
"mmocr/models/textdet/modules/proposal_local_graph.py"
] | [
"import cv2\nimport numpy as np\nimport torch\ntry:\n from lanms import merge_quadrangle_n9 as la_nms\nexcept:\n pass\nfrom mmcv.ops import RoIAlignRotated\n\nfrom mmocr.models.textdet.postprocess.wrapper import fill_hole\nfrom .utils import (euclidean_distance_matrix, feature_embedding,\n ... | [
[
"numpy.sqrt",
"torch.cat",
"torch.zeros",
"numpy.max",
"numpy.mean",
"numpy.hstack",
"numpy.clip",
"torch.from_numpy",
"torch.tensor",
"numpy.zeros",
"torch.squeeze",
"torch.sigmoid",
"numpy.min",
"numpy.arccos",
"torch.stack",
"numpy.argsort",
"... |
chenhaox/wrs | [
"c16ce81d07da962119bd7edac6165b6df0d5b53a"
] | [
"0000_ripps/utils.py"
] | [
"import os\n\nimport nptyping\nimport numpy as np\nimport basis.robot_math as rm\nimport modeling.collision_model as cm\n\n\nclass Base(cm.CollisionModel):\n def __init__(self, file):\n super().__init__(initor=file, expand_radius=.009)\n self._hole_pos_list = []\n self._pos_z0 = .037\n ... | [
[
"numpy.asarray",
"numpy.array",
"numpy.radians"
]
] |
GlobalFishingWatch/vessel-scoring | [
"6bdd224f5090a0dfa55f285a3958131d5fc78d34"
] | [
"vessel_scoring/logistic_model.py"
] | [
"import numpy as np\nfrom sklearn.linear_model import LogisticRegression\nfrom vessel_scoring.utils import get_polynomial_cols, zigmoid\nimport vessel_scoring.base_model\nimport vessel_scoring.colspec\n\ndef make_features(base_cols, order, cross):\n n_base_cols = len(base_cols)\n cols = []\n for total_orde... | [
[
"sklearn.linear_model.LogisticRegression.__init__",
"sklearn.linear_model.LogisticRegression.fit",
"numpy.concatenate",
"numpy.array",
"sklearn.linear_model.LogisticRegression.predict_proba"
]
] |
kakashihatakae/fury | [
"a187110c7b738cd1f2bc18066fbc30d23d1403de"
] | [
"fury/tests/test_utils.py"
] | [
"import sys\nimport numpy as np\nimport numpy.testing as npt\nfrom fury.utils import (map_coordinates_3d_4d,\n vtk_matrix_to_numpy,\n numpy_to_vtk_matrix,\n get_grid_cells_position,\n rotate, vtk)\nfrom fury import actor, wi... | [
[
"numpy.testing.assert_equal",
"numpy.expand_dims",
"numpy.unique",
"numpy.flipud",
"numpy.ones",
"numpy.testing.assert_array_equal",
"numpy.testing.assert_almost_equal",
"numpy.testing.assert_raises",
"numpy.where",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"nu... |
anjianli21/ilqgames | [
"2be8e2bc6d34a9a6296d341b75d59e37c9057ad5"
] | [
"python/pytorch_examples.py"
] | [
"import torch\nimport numpy as np\n\nx = torch.ones(2, 1, requires_grad=True)\n\n# Try out some gradient descent.\nprint(\"Trying out some gradient descent.\")\nii = 1\nwhile True:\n y = torch.sum(x ** 2 - 1.5 * x[0, 0] + 2.4 * x[1, 0])\n y.backward()\n if x.grad.norm() < 1e-3 or ii > 1000:\n break\... | [
[
"torch.ones",
"torch.empty",
"torch.sin",
"torch.cat",
"torch.sum",
"numpy.concatenate",
"torch.autograd.grad",
"torch.cos"
]
] |
cgx027/cc_edu | [
"62694a527501ab5d88a950c60251d8f6d20ccd04"
] | [
"baidu_python_record.py"
] | [
"# -*- coding: utf-8 -*-\nfrom pyaudio import PyAudio, paInt16\nimport numpy as np\nfrom datetime import datetime\nimport wave\nimport time\nimport urllib, pycurl\nfrom urllib.request import urlopen\nimport base64\nimport json\nimport os\nimport sys\nfrom importlib import reload\n\n# reload(sys)\n# sys.setdefaulten... | [
[
"numpy.max",
"numpy.fromstring",
"numpy.sum"
]
] |
alphavector/pandera | [
"7e1742fa4b750fdd47530c4107693ed72aa0f8e6"
] | [
"tests/fastapi/test_app.py"
] | [
"# pylint: disable=redefined-outer-name,unused-argument\n\"\"\"Unit tests for using pandera types in fastapi endpoints.\"\"\"\n\nimport io\nimport subprocess\nimport time\nfrom copy import deepcopy\n\nimport pandas as pd\nimport pytest\nimport requests\nfrom hypothesis import given\n\nfrom tests.fastapi.models impo... | [
[
"pandas.read_parquet",
"pandas.read_json"
]
] |
kahartma/eeggan | [
"1fd5b45938ea6f1033f301430a5c7fb3b9bf4fb4",
"1fd5b45938ea6f1033f301430a5c7fb3b9bf4fb4"
] | [
"eeggan/examples/high_gamma/models/baseline.py",
"eeggan/pytorch/modules/modify/noise.py"
] | [
"# Author: Kay Hartmann <kg.hartma@gmail.com>\n\nimport numpy as np\nfrom torch import nn\nfrom torch.nn.init import calculate_gain\n\nfrom eeggan.model.builder import ProgressiveModelBuilder\nfrom eeggan.pytorch.modules.conv.multiconv import MultiConv1d\nfrom eeggan.pytorch.modules.normalization.pixelnorm import ... | [
[
"torch.nn.ReflectionPad1d",
"torch.nn.init.calculate_gain",
"torch.nn.Linear",
"torch.nn.LeakyReLU",
"numpy.floor",
"torch.nn.Conv1d",
"torch.nn.ConvTranspose1d"
],
[
"torch.nn.Conv1d"
]
] |
mwpb/bayesian-regression | [
"b7ee557d9301c1352e630aee998cbf652e4a481f"
] | [
"main.py"
] | [
"import math\nimport scipy.stats\nimport numpy as np\nimport pandas\nfrom collections import defaultdict\n\ndf = list(pandas.read_csv(\"poverty.csv\").itertuples(index=False))\n\ncache = {}\n\ndef probability(mean, intercept, std):\n if (mean, intercept, std) not in cache:\n p = 0\n for row in df:\... | [
[
"numpy.random.uniform",
"pandas.from_dict",
"pandas.read_csv",
"numpy.random.normal"
]
] |
tritus/ml-courses | [
"687c5006863ead9bee07dc3d76245a173c21528e"
] | [
"mnist/part2-mnist/nnet_cnn.py"
] | [
"#! /usr/bin/env python\n\nimport _pickle as c_pickle, gzip\nimport numpy as np\nfrom tqdm import tqdm\nimport torch\nimport torch.autograd as autograd\nimport torch.nn.functional as F\nimport torch.nn as nn\nimport sys\nsys.path.append(\"..\")\nimport utils\nfrom utils import *\nfrom train_utils import batchify_da... | [
[
"torch.nn.Dropout",
"numpy.random.seed",
"numpy.reshape",
"torch.manual_seed",
"torch.nn.Conv2d",
"numpy.random.shuffle",
"torch.nn.MaxPool2d",
"torch.nn.Linear",
"torch.nn.ReLU"
]
] |
shamimrezasohag/pyod | [
"5b5e1b355a5be4def2544ecd26d17e6e279d648c"
] | [
"pyod/test/test_iforest.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport os\nimport sys\n\nimport unittest\n# noinspection PyProtectedMember\nfrom numpy.testing import assert_allclose\nfrom numpy.testing import assert_array_less\nfrom numpy.testing import assert_equal\nfrom numpy... | [
[
"numpy.testing.assert_equal",
"sklearn.metrics.roc_auc_score",
"scipy.stats.rankdata",
"numpy.testing.assert_array_less",
"sklearn.base.clone",
"numpy.testing.assert_raises"
]
] |
mrn-mln/neuralet | [
"9c73511d5cd585fbf6b3511d374b2133a2e0bb80",
"9c73511d5cd585fbf6b3511d374b2133a2e0bb80"
] | [
"applications/facemask/libs/core.py",
"applications/facemask/libs/classifiers/x86/face_mask.py"
] | [
"import cv2 as cv\nimport numpy as np\n\n\nclass FaceMaskAppEngine:\n \"\"\"\n Perform detector which detects faces from input video,\n and classifier to classify croped faces to face or mask class\n :param config: Is a Config instance which provides necessary parameters.\n \"\"\"\n\n def __init__... | [
[
"numpy.array",
"numpy.shape",
"numpy.multiply"
],
[
"tensorflow.keras.models.load_model",
"numpy.argmax",
"numpy.shape"
]
] |
xhan97/zenml | [
"8d87d76c6a4cca8862af3183975c8f292dafa49d"
] | [
"examples/functional_api/chapter_1.py"
] | [
"# Copyright (c) ZenML GmbH 2021. 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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless req... | [
[
"tensorflow.keras.datasets.mnist.load_data"
]
] |
Mariam05/DeepPurpose | [
"f78b089f2289a9f6498332cf6bd4eaf8bd170732"
] | [
"DeepPurpose/dataset.py"
] | [
"import pandas as pd\nimport numpy as np\nimport wget\nfrom zipfile import ZipFile\nfrom DeepPurpose.utils import *\nimport json\nimport os\n\n'''\nAcknowledgement:\nThe BindingDB dataset is hosted in https://www.bindingdb.org/bind/index.jsp.\n\nThe Davis Dataset can be found in http://staff.cs.utu.fi/~aatapa/data/... | [
[
"numpy.array",
"pandas.read_csv",
"pandas.concat"
]
] |
McStasMcXtrace/ufit | [
"02640e2b802bf6d42ae6829a1c1852b21c6fa9f7"
] | [
"ufit/models/base.py"
] | [
"# -*- coding: utf-8 -*-\n# *****************************************************************************\n# ufit, a universal scattering fitting suite\n#\n# Copyright (c) 2013-2019, Georg Brandl and contributors. All rights reserved.\n# Licensed under a 2-clause BSD license, see LICENSE.\n# *********************... | [
[
"numpy.concatenate"
]
] |
louisoutin/deep_gas_oracle | [
"1f69483ee5e0310e8c533e6cf3f9668a54f9fdf5"
] | [
"deep_gas_oracle/modeling/model.py"
] | [
"from pathlib import Path\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import DataLoader\nfrom torch.utils.tensorboard import SummaryWriter\nfrom .dataset import TimeSeriesDataset\nfrom ..preprocessing.norm import Normalizer\n\n\nclass GruMultiStep(nn.Module):... | [
[
"torch.mean",
"torch.linspace",
"pandas.to_datetime",
"pandas.concat",
"torch.nn.GRU",
"torch.utils.data.DataLoader",
"pandas.DataFrame",
"torch.nn.Linear",
"torch.no_grad",
"torch.device",
"torch.nn.MSELoss"
]
] |
ZhouBo20171229/- | [
"56c9d859d6931cd971419c5225199acca6c189e5"
] | [
"RoiMatching.py"
] | [
"import os\r\nimport zipfile\r\nimport struct\r\nimport shutil\r\nimport numpy as np\r\nfrom AreaComputing import *\r\nfrom BatchRename import *\r\n# import time\r\nfrom math import *\r\nfrom BatchZip import *\r\n\r\n\r\n\r\ndef DicBuild(Path):\r\n # print(Path)\r\n # print(os.path.isfile(Path))\r\n if ~(o... | [
[
"numpy.zeros"
]
] |
RC-Car-Racing-Team-17/Automold--Road-Augmentation-Library | [
"866dc62fd18323fce948edcbd65e4c899dc26fda"
] | [
"Automold.py"
] | [
"\n# import glob\nimport cv2 as cv2\nimport numpy as np\n# import matplotlib.pyplot as plt\nimport random\nimport math\n\n\n###################### HLS #############################\n\ndef hls(image,src='RGB'):\n verify_image(image)\n if(is_list(image)):\n image_HLS=[]\n image_list=image\n ... | [
[
"numpy.linspace",
"numpy.ones",
"numpy.copy",
"numpy.zeros_like",
"numpy.average",
"numpy.random.uniform",
"numpy.array",
"numpy.zeros",
"numpy.random.randint"
]
] |
TamasSzepessy/DJITelloOpticalControl | [
"00b704afea1eb9e2bcb82fcde41baae83934c48e"
] | [
"src/targeter.py"
] | [
"import csv\nimport numpy as np\n\n# distance from marker in camera Z coordinates\nDIST = 0.9\n\nclass TargetDefine():\n def __init__(self):\n with open('marker_list/marker_conf.csv', 'rt', encoding='utf-8') as f:\n reader = csv.reader(f, delimiter=';')\n self.marker_nav = list(reade... | [
[
"numpy.array"
]
] |
mon02118/azure_vton | [
"2ec3fe38fb2e94f59fe6cabc29eac5d08e4a21fd"
] | [
"test.py"
] | [
"#coding=utf-8\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nimport argparse\nimport os\nimport time\nfrom cp_dataset import CPDataset, CPDataLoader\nfrom networks import GMM, UnetGenerator, load_checkpoint\n\nfrom tensorboardX import SummaryWriter\nfrom visualization import board_add_ima... | [
[
"torch.cat",
"torch.nn.functional.sigmoid",
"torch.nn.functional.grid_sample",
"torch.no_grad",
"torch.split",
"torch.nn.functional.tanh"
]
] |
rikrd/libri-light | [
"34c3f43774c374a529e67c88b87a79041f07b402"
] | [
"data_preparation/metadata_completion/utilities.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nfrom pathlib import Path\nimport pickle\nimport json\nimport torchaudio\nimport progressbar\nimport argparse\nimport os\nimport matplotlib\nmatplotlib.use('agg')\n\n\ndef get_all_metadata(path_dir, suffix=\"_metadata.json\"):\n out = []\n ... | [
[
"matplotlib.use"
]
] |
itismesam/Courses-1 | [
"7669c4460be02b8bbaea2ae79182af2667e9e6b2"
] | [
"MOOCS/Cs224n_2019/a2/run.py"
] | [
"#!/usr/bin/env python\n\nimport random\nimport numpy as np\nfrom utils.treebank import StanfordSentiment\nimport matplotlib\nmatplotlib.use('agg')\nimport matplotlib.pyplot as plt\nimport time\n\nfrom word2vec import *\nfrom sgd import *\n\n# Check Python Version\nimport sys\nassert sys.version_info[0] == 3\nasser... | [
[
"numpy.linalg.svd",
"numpy.random.seed",
"numpy.min",
"matplotlib.use",
"matplotlib.pyplot.savefig",
"numpy.concatenate",
"numpy.max",
"numpy.mean",
"numpy.random.rand",
"numpy.zeros"
]
] |
cbwang2016/quimb | [
"a06fb9fc58976936bf7d631179ece0f832bf96a9"
] | [
"tests/test_evo.py"
] | [
"from pytest import fixture, mark, raises\n\nfrom math import pi, gcd, cos\nfrom functools import reduce\n\nimport numpy as np\nfrom numpy.testing import assert_allclose\n\nimport quimb as qu\nfrom quimb.evo import (\n schrodinger_eq_ket,\n schrodinger_eq_dop,\n schrodinger_eq_dop_vectorized,\n lindblad... | [
[
"numpy.diag",
"numpy.linspace",
"numpy.random.seed",
"scipy.sparse.linalg.aslinearoperator",
"numpy.testing.assert_allclose",
"numpy.exp",
"numpy.array",
"numpy.random.randint"
]
] |
priyanshu2103/Rotate-and-Render | [
"34771076e1284a1de534a391d724128bfba6f06f"
] | [
"3ddfa/inference.py"
] | [
"#!/usr/bin/env python3\n# coding: utf-8\n\n__author__ = 'cleardusk'\n\n\"\"\"\nThe pipeline of 3DDFA prediction: given one image, predict the 3d face vertices, 68 landmarks and visualization.\n\n[todo]\n1. CPU optimization: https://pmchojnacki.wordpress.com/2018/10/07/slow-pytorch-cpu-performance\n\"\"\"\n\nimport... | [
[
"numpy.concatenate",
"torch.no_grad",
"scipy.io.loadmat",
"torch.load"
]
] |
kachayev/dataclasses-tensor | [
"ec7dcb15ee8bd15e8d6f4bcab484d78a5ec3cf68"
] | [
"dataclasses_tensor/adapters.py"
] | [
"from typing import Union\n\nclass TensorAdapter:\n def zeros(self, size: int, dtype: str):\n raise NotImplemented()\n \n def argmax(self, arr):\n raise NotImplemented()\n\n def get(self, tensor, pos):\n raise NotImplemented()\n\ntry:\n import numpy as np\n class NumpyAdapter(... | [
[
"torch.zeros",
"torch.__getattribute__",
"numpy.argmax",
"numpy.zeros",
"torch.argmax"
]
] |
garedaba/BERMUDA | [
"ad989cbdae03efafe81d1d0aa36673dd6ffa2e14"
] | [
"main-synthetic-data.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# create code to generate and run on synthetic data\nimport torch\nimport os\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport yaml\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import mean_squared_error, pl... | [
[
"torch.cuda.set_device",
"numpy.unique",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"sklearn.metrics.mean_squared_error",
"pandas.DataFrame",
"matplotlib.pyplot.ioff",
"numpy.concatenate",
"numpy.shape",
"torch.cuda.is_available",
"sklearn.preprocessing.... |
jackd/grax | [
"99baaea786c59c1f5fe4314ba26d04b9a69499d6"
] | [
"grax/projects/gcn2/modules.py"
] | [
"import functools\nimport typing as tp\n\nimport gin\nimport haiku as hk\nimport jax\nimport jax.numpy as jnp\nimport numpy as np\nimport optax\nfrom jax.experimental.sparse.ops import JAXSparse\n\nfrom grax import hk_utils\nfrom grax.optax_utils import partition\n\nconfigurable = functools.partial(gin.configurable... | [
[
"numpy.log"
]
] |
DnyaneshwarIT/Recognizing-Handwritten-Digits | [
"caadb0feea80686fae668557d224ff0fb536f37b"
] | [
"Number_Recog.py"
] | [
"#Recognizing Handwritten Numbers\r\nimport cv2\r\nimport numpy as np\r\n # generate the Number set\r\ntxtSize, baseline = cv2.getTextSize('0123456789', cv2.FONT_HERSHEY_SIMPLEX, 3, 5)\r\n ... | [
[
"numpy.zeros",
"numpy.sum"
]
] |
desti-nation/Easy-diagnose | [
"db8b1f079a0717b2f28f1a2ff645d64e5708f38e"
] | [
"Python_Scripts/predict.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Sun Dec 24 14:33:48 2017\r\n\r\n@author: 309\r\n\"\"\"\r\nfrom keras.models import load_model\r\nimport numpy as np\r\nimport os\r\nfrom sys import argv\r\n\r\nif __name__ == '__main__':\r\n INPUT_PATH = argv[1]\r\n model_path = argv[2]\r\n TEMP_DATA_PATH = ... | [
[
"numpy.reshape",
"numpy.load",
"numpy.argmax"
]
] |
Varal7/chemprop-1 | [
"0b41649fb3c79d5d21c9165a345af4e59cfde688"
] | [
"chemprop/utils.py"
] | [
"from argparse import Namespace\nimport csv\nimport logging\nimport math\nimport os\nimport pickle\nfrom typing import Callable, List, Tuple, Union\n\nfrom sklearn.metrics import auc, mean_absolute_error, mean_squared_error, precision_recall_curve, r2_score,\\\n roc_auc_score, accuracy_score, log_loss\nimport to... | [
[
"torch.optim.Adam",
"torch.nn.CrossEntropyLoss",
"torch.load",
"sklearn.metrics.accuracy_score",
"sklearn.metrics.precision_recall_curve",
"sklearn.metrics.mean_squared_error",
"torch.nn.BCEWithLogitsLoss",
"sklearn.metrics.auc",
"torch.nn.MSELoss",
"torch.save"
]
] |
threefoldo/pytext | [
"41d4041a833b1aa1615418e448ed6e3f08f90025"
] | [
"pytext/trainers/trainer.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\nimport itertools\nimport time, re\nfrom contextlib import ExitStack as contextlib_ExitStack\nfrom typing import Any, Iterable, List, Optional, Tuple\n\nimport torch\nfrom pytext.common.constants import BatchContext, S... | [
[
"torch.no_grad",
"torch.cuda.current_device"
]
] |
WangQingjiehello/homework | [
"b81ce855c73b0a2fc7a2f0359cf283bef5582370"
] | [
"SeResnet-visdom-b.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.utils.data import DataLoader\nimport torch.nn.functional as F\nimport torch.optim as optim\nimport torch.nn.init as init\nimport argparse\nfrom torch.nn.utils import clip_grad_norm\nimport torchvision\nfrom torch.autograd import Variable\nimport torchvision.transform... | [
[
"torch.nn.Sequential",
"torch.nn.CrossEntropyLoss",
"torch.nn.Dropout",
"torch.load",
"torch.nn.ReLU",
"torch.nn.functional.avg_pool2d",
"torch.utils.data.DataLoader",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.functional.relu",
"torch.no_grad",
"torch.cuda.is_... |
leobix/gym-miniworld | [
"8b84c0370c665eb349512d779cc47b1f1b06a41a"
] | [
"pytorch-a2c-ppo-acktr/GatedPixelCNN/core/data/data_test_utils.py"
] | [
"import numpy as np\n\n\ndef test_dataset(dataset, image=None, label=None):\n images = dataset.images \n labels = dataset.labels\n if image is not None:\n print(images[0,18,6:22,:])\n np.testing.assert_almost_equal(images[0,18,6:22,:], image)\n if label is not None:\n if isinstance(label, int):\n ... | [
[
"numpy.testing.assert_almost_equal"
]
] |
zou3519/functorch | [
"48eec0a05bb169cd9e4b699dc191670d47ee61ca"
] | [
"functorch/_src/aot_autograd.py"
] | [
"import os\nimport math\nimport torch\nimport torch.nn as nn\nfrom torch import Tensor\nfrom functorch import make_functional_with_buffers, make_fx\nimport torch.fx as fx\nfrom torch.fx import immutable_collections\nimport torch.utils._pytree as pytree\nimport torch.utils.dlpack\nfrom torch.fx.passes import graph_d... | [
[
"torch.utils._pytree.tree_unflatten",
"torch.fx.GraphModule",
"torch.utils._pytree.tree_flatten",
"torch.enable_grad",
"torch.utils._pytree._register_pytree_node",
"torch.fx.passes.graph_drawer.FxGraphDrawer",
"torch.fx.Graph",
"torch.fx.immutable_collections.immutable_list",
"... |
manjebrinkhuis/attention-priming-decay | [
"067cb8daeebd24dd2726d4d56f7d38ef7185c817"
] | [
"notebooks/tools/glm.py"
] | [
"import numpy as np\n\n\ndef add_regressors(matrix, regressors):\n \"\"\" Add a regressor to a design matrix \"\"\"\n M = np.array(matrix)\n return np.vstack((M, regressors))\n\n\ndef array2dummies(arr):\n \"\"\" Returns matrix \"\"\"\n values = sorted(list(set(arr)))\n values = np.array([[v] for ... | [
[
"numpy.matrix",
"numpy.concatenate",
"numpy.linalg.pinv",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.vstack"
]
] |
bcloutier/PSNM | [
"1cd03f87f93ca6cb1a3cfbe73e8bc6106f497ddf",
"1cd03f87f93ca6cb1a3cfbe73e8bc6106f497ddf"
] | [
"PythonPrograms/Programs/PythonCode/KleinGordon1Dimp.py",
"PythonPrograms/Programs/PythonCode/NLSsplitting2D.py"
] | [
"\"\"\"\nA program to solve the 1D Klein Gordon equation using a\nsecond order semi-explicit method. The numerical solution is \ncompared to an exact solution\n\nMore information on visualization can be found on the Mayavi\nwebsite, in particular:\nhttp://github.enthought.com/mayavi/mayavi/mlab.html\nwhich was last... | [
[
"matplotlib.pyplot.legend",
"numpy.sqrt",
"matplotlib.pyplot.title",
"matplotlib.pyplot.cla",
"numpy.fft.fftn",
"matplotlib.pyplot.draw",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ioff",
"matplotlib.pyplot.ylabel",
"numpy.real",
"numpy.fft.ifftn",
"matplotlib.pyp... |
LulinPollux/lr-scheduler-visualization | [
"44fe47c89b70384f2c70f9842f845985810562f8"
] | [
"visualize_lr_scheduler.py"
] | [
"import torch\nimport matplotlib.pyplot as plt\n\n\nclass Model(torch.nn.Module):\n def __init__(self):\n super(Model, self).__init__()\n self.linear = torch.nn.Linear(3, 1)\n\n def forward(self, x):\n return self.linear(x)\n\n\nmodel = Model()\noptimizer = torch.optim.Adam(model.paramete... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"torch.nn.Linear",
"matplotlib.pyplot.show",
"torch.optim.lr_scheduler.StepLR"
]
] |
johnrachwan123/SNIP-it | [
"a578a0693318f261492331298b6602de225fe21f"
] | [
"models/criterions/SNAP.py"
] | [
"import copy\nimport os\nimport types\nfrom collections import OrderedDict\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn\n\nfrom models.criterions.General import General\nfrom models.networks.assisting_layers.GateDecoratorLayers import GatedBatchNorm\nfrom utils.constant... | [
[
"torch.abs",
"torch.ones",
"torch.nn.functional.nll_loss",
"torch.zeros",
"torch.zeros_like",
"torch.repeat_interleave",
"numpy.prod",
"torch.flatten",
"torch.topk",
"torch.argmax"
]
] |
Tommy-Johannessen/MovementRecognition | [
"be84d7d014a272987dd20d03194336a9244eb900"
] | [
"data_batcher.py"
] | [
"import pickle\n\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\n\n\nclass DataBatcher:\n def __init__(self, path, split_size=.5, do_shuffle=True):\n with open(path, 'rb') as bf:\n features, labels = pickle.load(bf)\n\n self.x_train, self.x_test, self.y_train, ... | [
[
"numpy.concatenate",
"numpy.arange",
"sklearn.model_selection.train_test_split"
]
] |
KarenImmanuel/hangar-py | [
"2a5caff259ad699db56676f14a70cb94e75d8a5b"
] | [
"src/hangar/backends/hdf5_00.py"
] | [
"\"\"\"Local HDF5 Backend Implementation, Identifier: ``HDF5_00``\n\nBackend Identifiers\n===================\n\n* Backend: ``0``\n* Version: ``0``\n* Format Code: ``00``\n* Canonical Name: ``HDF5_00``\n\nStorage Method\n==============\n\n* Data is written to specific subarray indexes inside an HDF5 \"dataset\... | [
[
"numpy.prod",
"numpy.floor",
"numpy.ravel",
"numpy.zeros",
"numpy.empty"
]
] |
fmeynadier/georinex | [
"c54b59f9967e2f2b7bf31e0057adbc9d9e57e423"
] | [
"georinex/obs2.py"
] | [
"from pathlib import Path\nimport numpy as np\nimport logging\nimport io\nfrom math import ceil\nfrom datetime import datetime, timedelta\nimport xarray\nfrom typing import List, Union, Any, Dict, Tuple, Sequence, Optional\nfrom typing.io import TextIO\ntry:\n from pymap3d import ecef2geodetic\nexcept ImportErro... | [
[
"numpy.nonzero",
"numpy.asarray",
"numpy.arange",
"numpy.timedelta64",
"numpy.diff",
"numpy.array",
"numpy.empty"
]
] |
dineshh912/TwitterSentimet-analysis | [
"af6cea57108267da8e68440fd3d3380c4bbb5947"
] | [
"app.py"
] | [
"import dash\nfrom dash.dependencies import Output, Event, Input, State\nimport dash_core_components as dcc\nimport dash_html_components as html\nimport plotly\nimport random\nimport plotly.graph_objs as go\nfrom collections import deque\nimport sqlite3\nimport pandas as pd\nimport time\n\n\napp = dash.Dash(__name_... | [
[
"pandas.to_datetime",
"pandas.read_sql"
]
] |
keiji/face_detector_with_tensorflow | [
"36a440b177c2decaa34ec8cd0311a8283969d932"
] | [
"face_detector_ssd/model_lightweight/model9.py"
] | [
"import tensorflow as tf\n\nNAME = 'model9_lw'\n\nIMAGE_SIZE = 128\nCHANNELS = 3\n\nCLASSES = 1\nOFFSET = 4\n\n\ndef base_layers(image, is_train=True):\n with tf.variable_scope(NAME):\n conv = tf.layers.conv2d(image, 64, [3, 3], [1, 1],\n padding='SAME',\n a... | [
[
"tensorflow.layers.conv2d",
"tensorflow.concat",
"tensorflow.shape",
"tensorflow.reshape",
"tensorflow.layers.max_pooling2d",
"tensorflow.variable_scope"
]
] |
entn-at/NeMo | [
"5ed583ce5a26667bd154e8fb13f324274476d261"
] | [
"nemo/collections/asr/models/label_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... | [
[
"numpy.asarray",
"torch.utils.data.DataLoader",
"torch.linalg.norm",
"torch.tensor",
"torch.no_grad",
"torch.stack",
"numpy.array",
"torch.dot"
]
] |
tkf/adaptiveheatmap | [
"27a58a647d7db20d5325a9640dd37049bd916b6e"
] | [
"examples/plot_demo_pcolor.py"
] | [
"\"\"\"\n`pcolor <.core.pcolor>` demo\n----------------------------\n\n`pcolor <.core.pcolor>` can be used like\n`matplotlib.pyplot.pcolor`.\n\"\"\"\n\nfrom matplotlib import pyplot\n\nfrom adaptiveheatmap.demos import data_hump_and_spike\nimport adaptiveheatmap\n\npyplot.style.use(\"fivethirtyeight\")\n\nX, Y, Z =... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.style.use"
]
] |
swipswaps/sdr | [
"35af246c08d9153938bcd562003c0adf0965cd41"
] | [
"kwmobile/decoder.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nimport os\nfrom time import sleep, time\nfrom datetime import datetime\n\nimport pigpio as gpio\nimport numpy as np\n\nfrom lib.rfm69 import Rfm69\n\nimport psycopg2 as pg\nimport paho.mqtt.client as mqtt\n\nSILENT = 0\nERROR = 1\nINFO = 2\nTRACE = 3\n\n\nclass De... | [
[
"numpy.append",
"numpy.packbits",
"numpy.empty"
]
] |
EliasPapachristos/AWS_ML_Foundations_Course-Udacity | [
"7e99c33908ca5ac60b220dd989cb44d88d013af4"
] | [
"Binomial/distributions/Gaussiandistribution.py"
] | [
"import math\r\nimport matplotlib.pyplot as plt\r\nfrom .Generaldistribution import Distribution\r\n\r\n\r\nclass Gaussian(Distribution):\r\n \"\"\" Gaussian distribution class for calculating and\r\n visualizing a Gaussian distribution.\r\n\r\n Attributes:\r\n mean (float) representing the mean val... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.ylabel"
]
] |
haroldNLP/Distiller | [
"f3ab5f94a9092fca1e2bdb9f486e66fd0b24bcfd"
] | [
"examples/token_classification/preprocessing.py"
] | [
"import os\nimport logging\nimport torch\nlogger = logging.getLogger(__name__)\nfrom torch.utils.data import TensorDataset\n\nclass Example(object):\n \"\"\"A single training/test example for token classification.\"\"\"\n\n def __init__(self, guid, words, labels):\n \"\"\"Constructs a InputExample.\n\n... | [
[
"torch.utils.data.TensorDataset",
"torch.tensor"
]
] |
lovemefan/Semi-Supervised-Speech-Recognize | [
"2587aa3010dab4ca6308075f79bc8b23ae539d14"
] | [
"scripts/wenetspeech/utils/infer.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\"\"\"\nRun inference for pre-processed data with a trained model.\n\"\"\"\n\nimport logging\nimport math... | [
[
"torch.from_numpy",
"numpy.save",
"numpy.stack",
"torch.no_grad",
"torch.cuda.is_available",
"torch.flatten",
"numpy.load"
]
] |
Siyuan89/self-attention-cv | [
"ae215541d3e33d39f26947924253a63585683226"
] | [
"self_attention_cv/axial_attention_deeplab/axial_attention.py"
] | [
"import torch\nfrom einops import rearrange\nfrom torch import nn\n\nfrom self_attention_cv.pos_embeddings.relative_pos_enc_qkv import Relative2DPosEncQKV\n\n\ndef _conv1d1x1(in_channels, out_channels):\n \"\"\"1D convolution with kernel size of 1 followed by batch norm\"\"\"\n return nn.Sequential(nn.Conv1d(... | [
[
"torch.nn.BatchNorm1d",
"torch.softmax",
"torch.einsum",
"torch.nn.Conv1d",
"torch.nn.BatchNorm2d",
"torch.split"
]
] |
benjaminbeilharz/hierarchical-reinforcement-learning | [
"6076b42d007a5dea513b18c608acdb3aec681032"
] | [
"joeynmt/actor_critic_loss.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nThis module implements Actor Critic Loss with functionalities for target\nnetworks and experience replay.\n\"\"\"\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom copy import deepcopy\nfrom torch import Tensor\n\nfrom random import randrange\nfrom colle... | [
[
"torch.isnan",
"torch.zeros",
"torch.nn.ModuleDict",
"torch.sum",
"torch.tensor",
"torch.no_grad",
"torch.log",
"torch.cuda.is_available",
"torch.stack",
"torch.device"
]
] |
gewitterblitz/lmatools | [
"11a90921a827aaf89d925573c1a55088f4215dfd"
] | [
"density_tools.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import print_function\nimport numpy as np\n\ndef unique_vectors(*args, **kwargs):\n \"\"\" Given D, N-element arrays of vector components return the\n unique vectors as a (D, N_reduced) array. If return_indices_only=True\n is true (the defaul... | [
[
"numpy.hstack",
"numpy.asarray",
"numpy.arange",
"numpy.histogramdd",
"numpy.floor",
"numpy.array",
"numpy.meshgrid",
"numpy.vstack"
]
] |
mlcommons/peoples-speech | [
"1bfaa7d843e0f664e16bbdbc308f7fa40ac7e10c",
"36bb9265f9439b10676fb539d5334cce645e49ef"
] | [
"galvasr2/yamnet/inference.py",
"galvasr2/yamnet/yamnet/features.py"
] | [
"from urllib.parse import urlparse\nfrom google.cloud import storage\nimport numpy as np\nimport resampy\nimport tensorflow as tf\nimport urllib.request\nimport itertools\nimport io\nimport jsonlines\nfrom pydub import AudioSegment\n\n\nimport yamnet.params as yamnet_params\nimport yamnet.yamnet as yamnet_model\n\n... | [
[
"numpy.argsort",
"tensorflow.py_function",
"tensorflow.data.Dataset.list_files",
"numpy.mean"
],
[
"tensorflow.signal.frame",
"tensorflow.signal.linear_to_mel_weight_matrix",
"tensorflow.matmul",
"numpy.imag",
"numpy.log",
"tensorflow.shape",
"tensorflow.maximum",
... |
Coastinger/DCGAN-tensorflow | [
"6d1b8cf99b549d1aa2e1dbc0694dabc7d3f3a318"
] | [
"ops.py"
] | [
"import math\nimport numpy as np\nimport tensorflow as tf\n\nfrom tensorflow.python.framework import ops\n\nfrom utils import *\n\ntry:\n image_summary = tf.image_summary\n scalar_summary = tf.scalar_summary\n histogram_summary = tf.histogram_summary\n merge_summary = tf.merge_summary\n SummaryWriter = tf.trai... | [
[
"tensorflow.nn.bias_add",
"tensorflow.matmul",
"tensorflow.concat",
"tensorflow.image.resize_nearest_neighbor",
"tensorflow.maximum",
"tensorflow.nn.deconv2d",
"tensorflow.ones",
"tensorflow.truncated_normal_initializer",
"tensorflow.nn.conv2d_transpose",
"tensorflow.consta... |
anh/TransformerTTS | [
"ff71b9aba01fa462c7d27877ec1609a1ea6e48ff"
] | [
"utils/losses.py"
] | [
"import tensorflow as tf\n\n\ndef new_scaled_crossentropy(index=2, scaling=1.0):\n \"\"\"\n Returns masked crossentropy with extra scaling:\n Scales the loss for given stop_index by stop_scaling\n \"\"\"\n \n def masked_crossentropy(targets: tf.Tensor, logits: tf.Tensor) -> tf.Tensor:\n cro... | [
[
"tensorflow.reduce_max",
"tensorflow.reduce_mean",
"tensorflow.keras.losses.SparseCategoricalCrossentropy",
"tensorflow.keras.losses.MeanSquaredError",
"tensorflow.cast",
"tensorflow.keras.losses.BinaryCrossentropy",
"tensorflow.math.equal",
"tensorflow.math.logical_not",
"tens... |
aks2203/easy-to-hard-data | [
"8dc98fce818314400fbf54d3ef39bb4e9a1a342a"
] | [
"easy_to_hard_data.py"
] | [
"\"\"\" easy_to_hard_data.py\n Python package with datasets for studying generalization from\n easy training data to hard test examples.\n Developed as part of easy-to-hard (github.com/aks2203/easy-to-hard).\n Avi Schwarzschild\n June 2021\n\"\"\"\n\nimport errno\nimport os\nimport os.path\nimpor... | [
[
"numpy.load",
"torch.from_numpy",
"torch.load"
]
] |
cake-lab/transient_deep_learning | [
"87c6717e4026801623cf0327e78ad57f51cb1461",
"8d3d175d649680c8e5b98a1b1c1c5e782ff492ac"
] | [
"code/tensor2tensor/tensor2tensor/models/video/sv2p.py",
"code/tensor2tensor/tensor2tensor/models/image_transformer_2d.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Tensor2Tensor 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 requir... | [
[
"tensorflow.concat",
"tensorflow.scan",
"tensorflow.control_dependencies",
"tensorflow.zeros",
"tensorflow.stack",
"tensorflow.tanh",
"tensorflow.greater",
"tensorflow.summary.image",
"tensorflow.squeeze",
"tensorflow.layers.dense",
"tensorflow.stop_gradient",
"tens... |
thirteenfoil8/Carlo | [
"96258c802acaddb8f729776d050da7150ac4c832"
] | [
"PPO/agent.py"
] | [
"import numpy as np\nfrom world import World\nfrom agents import Car, RingBuilding, CircleBuilding, Painting, Pedestrian\nfrom geometry import Point\nfrom network import Net\nimport random\nimport time\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom torch.uti... | [
[
"numpy.sqrt",
"torch.load",
"numpy.dtype",
"numpy.mean",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device",
"numpy.square",
"numpy.arange",
"torch.from_numpy",
"numpy.sin",
"torch.tensor",
"numpy.zeros",
"torch.distributions.Beta",
"torch.min",
... |
MatheusCL8/Equatorial-Longo-Prazo-master | [
"abf781cad0619500f4abca45dba864fec82e693f"
] | [
"Source/rede_dinamica.py"
] | [
"from Utilities.utilities import build_dbn\nimport topologia\nimport dataframe\nimport argparse\nfrom pprint import pprint\nimport sys\nfrom validacao import separa_arquivo_json, cria_json_final\nimport json\nimport pandas as pd\nfrom datetime import datetime\nimport traceback\n\nusuario='user'\n\ndef callScript(da... | [
[
"pandas.DatetimeIndex"
]
] |
837477/PyTorch_study | [
"7641edb4d1fdb18bc87e16d4b0174d612b045b4c"
] | [
"src/wikidocs/2_linear_regression/custom_dataset.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.utils.data import TensorDataset # 텐서데이터셋\nfrom torch.utils.data import DataLoader # 데이터로더\n'''\n파이토치는 데이터셋을 조금 더 쉽게 다룰 수 있도록 torch.utils.data.Dataset과 torch.utils.data.DataLoader를 제공한다.\n이를 사용하면 미니 배치 학습, 데이터 셔플, 병렬 처리까지 간단하게 수행할 수 있다... | [
[
"torch.manual_seed",
"torch.utils.data.DataLoader",
"torch.nn.Linear",
"torch.nn.functional.mse_loss",
"torch.FloatTensor"
]
] |
dkorduban/lagom | [
"84d90902e70ed15a541406b7423a2d4ef74366e3"
] | [
"test/test_lagom.py"
] | [
"import pytest\n\nimport numpy as np\n\nimport os\n\nfrom lagom import Seeder\nfrom lagom import Logger\nfrom lagom import pickle_load\nfrom lagom import pickle_dump\nfrom lagom import yaml_load\nfrom lagom import yaml_dump\n\n\nclass TestLagom(object):\n def test_seeding(self):\n seeder = Seeder(init_see... | [
[
"numpy.array",
"numpy.allclose"
]
] |
rwenite/msa-thesis | [
"4b72d5571b91ef1ca5266c8e151fdc5e387d57ac"
] | [
"py/thesis.py"
] | [
"\"\"\"\n main.py\n Richard Wen (rwenite@gmail.com)\n\n===============================================================\n\n A script for running random forests for pattern recognition\n of spatial data.\n \n Call python via console:\n python thesis.py config.txt path\\\\to\\\\workspace_folder\n \n===============... | [
[
"pandas.concat",
"sklearn.grid_search.ParameterGrid",
"matplotlib.pyplot.rcParams.update",
"matplotlib.pyplot.close",
"pandas.set_option",
"sklearn.externals.joblib.load",
"matplotlib.pyplot.figure"
]
] |
dnootana/Python | [
"2881bafe8bc378fa3cae50a747fcea1a55630c63"
] | [
"numpy/random_fn.py"
] | [
"#!/usr/bin/env python3.8\n\nfrom numpy import random\n\na = random.randint(100)\nprint(a)\n\na = random.rand()\nprint(a)\n\na = random.randint(100, size=(5))\nprint(a)\n\n\na = random.randint(100, size=(3, 5))\nprint(a)\n\na = random.rand(5)\nprint(a)\n\na = random.rand(5,3)\nprint(a)\n\na = random.choice([1,2,3,4... | [
[
"numpy.random.rand",
"numpy.random.choice",
"numpy.random.randint"
]
] |
ckcortright/CSCI4830MachineLearning | [
"5d1c6c7bfb05b54f7c000c940b1f6410054f10f0"
] | [
"ProgrammingAssignments/KNN/carl_cortright_P3/knn.py"
] | [
"import argparse\nfrom collections import Counter, defaultdict\n\nimport numpy\nfrom numpy import median\nfrom sklearn.neighbors import BallTree\n\n\nclass Numbers:\n \"\"\"\n Class to store MNIST data\n \"\"\"\n\n def __init__(self, location):\n import gzip\n import cPickle\n\n # L... | [
[
"sklearn.neighbors.BallTree"
]
] |
RobertoNegro/unitn-lbdm-201920-corex | [
"16274527776eb83ca5bcfa160220f689e8b1bb88"
] | [
"main_example.py"
] | [
"import linearcorex as lc\nimport numpy as np\n\nprint('\\nInput Matrix\\n==================')\n# A A A A A iA C C A C\nX = np.array([[0.01, 0.01, 0.01, 0.01, 0.01, 1.00, 1.00, 1.00, 0.01, 1.00],\n [0.01, 0.01, 0.01, 0.01, 0.01, 1.00, 0.00, 0.00, 0.01, 0.... | [
[
"numpy.array"
]
] |
intelligent-control-lab/collaborative-aerial-transportation | [
"ec5556d11dda80ab2b9c3bc894fb94c7f63b2dde"
] | [
"rotors_gazebo/scripts/collaborative/MARL/critic_network.py"
] | [
"import tensorflow as tf\r\nimport numpy as np\r\nimport math\r\n\r\n# target updating rate\r\nTAU = .001\r\nL2 = .0001\r\nLEARNING_RATE = 1e-3\r\npreLayer1Size = 256\r\npreLayer2Size = 128\r\nsufLayerSize = 128\r\nSUMMARY_DIR ='/home/lucasyu/catkin_ws/src/collaborative_transportation/rotors_gazebo/scripts/collabor... | [
[
"tensorflow.global_variables",
"tensorflow.variables_initializer",
"tensorflow.nn.bidirectional_dynamic_rnn",
"tensorflow.train.ExponentialMovingAverage",
"tensorflow.nn.l2_loss",
"tensorflow.train.AdamOptimizer",
"tensorflow.summary.scalar",
"tensorflow.get_collection",
"tenso... |
Frederic98/st7735_tft | [
"b6d991b0e82f98937bd4cf4aa8a125101e91f8be"
] | [
"examples/color_cycle.py"
] | [
"import os\nimport sys\nfrom PIL import Image, ImageDraw\nimport time\nimport numpy as np\n\nfrom st7735_tft import ST7735_TFT # To test higher speed library\n# from ST7735 import ST7735 as ST7735_TFT # To test original Pimoroni library\n\n\ndisp = ST7735_TFT(\n port=0,\n cs=0,\n dc=9,\... | [
[
"numpy.floor",
"numpy.linspace"
]
] |
maxwellsh/DIGDriver | [
"1f8503c8c22861d6f9b601fd8c5a131e3dc31fc1",
"1f8503c8c22861d6f9b601fd8c5a131e3dc31fc1"
] | [
"DIGDriver/region_model/trainers/gp_trainer.py",
"DIGDriver/region_model/data_aux/mut_dataset.py"
] | [
"import numpy as np\nimport scipy\nimport torch\nimport gpytorch\nfrom sklearn.preprocessing import StandardScaler\nimport warnings\n\nwarnings.filterwarnings(\"ignore\", category=RuntimeWarning)\n\n\nclass bcolors:\n HEADER = '\\033[95m'\n OKBLUE = '\\033[94m'\n OKCYAN = '\\033[96m'\n OKGREEN = '\\033[... | [
[
"numpy.abs",
"numpy.random.choice",
"numpy.isnan",
"numpy.arange",
"scipy.stats.pearsonr",
"numpy.unique",
"torch.cuda.empty_cache",
"torch.tensor",
"torch.no_grad",
"sklearn.preprocessing.StandardScaler",
"numpy.array"
],
[
"numpy.arange",
"numpy.sort",
... |
mstark5652/ocv | [
"15f94ce5d5c54ca6eb4bb7a8a7f596f4fef0c55a"
] | [
"train.py"
] | [
"#\n# Created by mstark on January 19, 2019\n#\n# Copyright (c) 2019. Michael Stark. All Rights Reserved.\n#\n\n\nimport sys\nimport os\nimport argparse\nimport math\nimport cv2\nimport numpy as np\n\nfrom obj_loader import OBJ\n\n\nWINDOW_SIZE = 2000\n\n\ndef extract_features(model_path):\n \"\"\" \"\"\"\n\n ... | [
[
"numpy.dot",
"numpy.linalg.inv",
"numpy.eye",
"numpy.int32",
"numpy.linalg.norm",
"numpy.stack",
"numpy.float32",
"numpy.cross",
"numpy.array"
]
] |
sunt05/salem | [
"22e64ef02a020a4f742971c6b0a09ac1dad56ee6"
] | [
"docs/conf.py"
] | [
"# -*- coding: utf-8 -*-\n#\n# salem documentation build configuration file, created by\n# sphinx-quickstart on Mon Dec 21 10:03:33 2015.\n#\n# This file is execfile()d with the current directory set to its\n# containing dir.\n#\n# Note that not all possible configuration values are present in this\n# autogenerated... | [
[
"matplotlib.use"
]
] |
BBuf/oneflow | [
"3abfe71617bc04c069b34a68780acbb8bbd959a7"
] | [
"oneflow/python/test/modules/test_maxpool.py"
] | [
"\"\"\"\nCopyright 2020 The OneFlow Authors. All rights reserved.\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by ap... | [
[
"numpy.unravel_index",
"numpy.ones_like",
"numpy.pad",
"numpy.ones",
"numpy.finfo",
"numpy.max",
"numpy.argmax",
"numpy.zeros_like",
"numpy.random.randn",
"numpy.shape",
"numpy.zeros"
]
] |
mriglobal/vorpal | [
"5dd590863e1831df2020d7a70ccdea7807cb88d1"
] | [
"development/binary_amino_model_GSS.py"
] | [
"import os\nimport pandas as pd\nimport numpy as np\nfrom Bio import SeqIO\nfrom skbio import Protein\nimport joblib\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.preprocessing import Binarizer\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.model_selection import GroupShuffleSp... | [
[
"sklearn.model_selection.GroupShuffleSplit",
"pandas.merge",
"sklearn.model_selection.GridSearchCV",
"sklearn.linear_model.LogisticRegression",
"pandas.DataFrame",
"sklearn.preprocessing.Binarizer",
"pandas.read_table",
"sklearn.utils.resample"
]
] |
vl123456/MLBox | [
"f5c528784742721449802d951c49637611a5b01c"
] | [
"mlbox/preprocessing/reader.py"
] | [
"# coding: utf-8\n# Author: Axel ARONIO DE ROMBLAY <axelderomblay@gmail.com>\n# License: BSD 3 clause\nimport sys\nimport pickle\nimport os\nimport time\nimport warnings\nimport numpy as np\nimport pandas as pd\nfrom sklearn.preprocessing import LabelEncoder\nfrom joblib import Parallel, delayed\n\n\ndef convert_li... | [
[
"pandas.read_hdf",
"pandas.read_csv",
"pandas.to_datetime",
"pandas.read_excel",
"pandas.DatetimeIndex",
"pandas.DataFrame",
"numpy.round",
"pandas.read_json",
"sklearn.preprocessing.LabelEncoder",
"pandas.datetime"
]
] |
kuangche-james/tf-quant-finance | [
"25251a75ab19147e72f89704f841ed41fbc354db"
] | [
"tf_quant_finance/experimental/dates/date_tensor_test.py"
] | [
"# Lint as: python3\n# 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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appli... | [
[
"tensorflow.compat.v2.reduce_all",
"numpy.array",
"tensorflow.compat.v2.constant",
"tensorflow.compat.v2.test.main"
]
] |
BPHO-Salk/PSSR | [
"a90b7d208d4369946500a70a6f31c44e3367e4c7"
] | [
"utils/crappifiers.py"
] | [
"import numpy as np\nfrom skimage import filters\nfrom skimage.util import random_noise, img_as_ubyte, img_as_float\nfrom scipy.ndimage.interpolation import zoom as npzoom\nfrom skimage.transform import rescale\nimport PIL\n\ndef no_crap(img, scale=4, upsample=False):\n from skimage.transform import rescale\n ... | [
[
"numpy.clip",
"numpy.random.poisson",
"numpy.random.normal",
"numpy.iinfo",
"numpy.array",
"scipy.ndimage.interpolation.zoom"
]
] |
DevJakobL/Face_detection | [
"2b1227e237337ee6e010b938133d81cf7048641b"
] | [
"TENSORBOX/utils/slim_nets/inception_v1.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 required... | [
[
"tensorflow.variable_scope",
"tensorflow.squeeze",
"tensorflow.truncated_normal_initializer"
]
] |
ztang4/codetest | [
"d7019ae379ddaac2600fcf715b873552a8ba3715"
] | [
"animation/a2.py"
] | [
"#https://stackoverflow.com/questions/63589249/plotly-dash-display-real-time-data-in-smooth-animation/63681810\n\nimport dash\nimport dash_html_components as html\nimport dash_core_components as dcc\nimport numpy as np\n\nfrom dash.dependencies import Input, Output\n\n# Example data (a circle).\nresolution = 20\nt ... | [
[
"numpy.cos",
"numpy.linspace",
"numpy.sin"
]
] |
habout632/AttnGAN | [
"5450e8828fa91f22598838b0e8f21c123bd059fa"
] | [
"code/datasets.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nfrom nltk.tokenize import RegexpTokenizer\nfrom collections import defaultdict\nfrom miscc.config import cfg\n\nimport torch\nimport torch.utils.data as data\nf... | [
[
"pandas.read_csv",
"numpy.minimum",
"numpy.maximum",
"numpy.asarray",
"numpy.arange",
"numpy.random.shuffle",
"numpy.sort",
"torch.autograd.Variable",
"torch.sort",
"numpy.zeros",
"numpy.random.randint"
]
] |
henryShelf/client_python | [
"493af52ac2524e38fd7e05e0d365d02369c64ac1"
] | [
"arize/examples/bulk_client.py"
] | [
"import os\nimport uuid\nimport time\nimport pandas as pd\nimport numpy as np\nimport concurrent.futures as cf\n\nfrom arize.api import Client\nfrom arize.types import ModelTypes\n\nITERATIONS = 1\nNUM_RECORDS = 100\n\narize = Client(\n organization_key=os.environ.get(\"ARIZE_ORG_KEY\"),\n api_key=os.environ.... | [
[
"numpy.random.randint"
]
] |
gstearmit/netron | [
"9989411c613fb91038dd5f505b970bff515d06f2"
] | [
"tools/tf-script.py"
] | [
"\nimport io\nimport json\nimport os\nimport sys\n\nfrom tensorflow.core.framework import api_def_pb2\nfrom tensorflow.core.framework import op_def_pb2\nfrom tensorflow.core.framework import types_pb2\nfrom google.protobuf import text_format\n\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'\n\ndef metadata():\n catego... | [
[
"tensorflow.core.framework.op_def_pb2.OpList",
"tensorflow.core.framework.api_def_pb2.ApiDef",
"tensorflow.core.framework.api_def_pb2.ApiDefs"
]
] |
janewen134/fyp | [
"8fb93ac22d21d5d862035ba794fe9d264add2e63"
] | [
"src/robot_learning/object_detect/scripts/CSPDarknet.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nimport torch\nimport torch.nn.functional as F\nimport torch.nn as nn\nimport math\nfrom collections import OrderedDict\nimport numpy as np\nfrom torch.nn.parameter import Parameter\n\nload_all_layers = True\n\ndef load_model_pth(model, pth):\n print('Loading weig... | [
[
"torch.cat",
"torch.load",
"torch.nn.Conv2d",
"numpy.shape",
"torch.cuda.is_available",
"torch.nn.BatchNorm2d",
"torch.nn.functional.softplus"
]
] |
seetaresearch/Dragon | [
"494774d3a545f807d483fd9e6e4563cedec6dda5"
] | [
"dragon/python/vm/onnx/core/backend/tensorrt.py"
] | [
"# ------------------------------------------------------------\n# Copyright (c) 2017-present, SeetaTech, Co.,Ltd.\n#\n# Licensed under the BSD 2-Clause License.\n# You should have received a copy of the BSD 2-Clause License\n# along with the software. If not, See,\n#\n# <https://opensource.org/licenses/BSD-2-C... | [
[
"numpy.array"
]
] |
Alfons0329/PySyft | [
"d8ede4683cabea1ec3395fee105446b624eacd4a"
] | [
"syft/frameworks/torch/tensors/interpreters/native.py"
] | [
"import math\nfrom typing import List\nfrom typing import Union\nimport warnings\nimport weakref\n\nimport numpy as np\nimport torch\n\nimport syft\nfrom syft.generic.frameworks.hook import hook_args\nfrom syft.generic.frameworks.overload import overloaded\nfrom syft.frameworks.torch.tensors.interpreters.crt_precis... | [
[
"torch.nn.Parameter",
"torch.no_grad",
"torch.native_roll",
"torch.Tensor"
]
] |
martin-sedlacek/ml-for-financial-data | [
"0bfd537576b5303909a16f5d2bade627a0a14b51"
] | [
"training/MADGAN_train.py"
] | [
"import numpy as np\nimport torch\nimport random\nfrom models.MADGAN import AnomalyDetector\nfrom utils.evaluation import excess_mass, mass_volume\nfrom utils.evaluation import accuracy, precision, recall, metric_calc\nimport time\n\n\ndef set_seed(seed=0):\n torch.manual_seed(seed)\n np.random.seed(seed)\n ... | [
[
"torch.Tensor",
"numpy.random.seed",
"torch.cat",
"torch.manual_seed",
"numpy.arange",
"torch.full",
"numpy.random.normal",
"numpy.mean",
"torch.prod"
]
] |
UKPLab/acl2021-metaphor-generation-conceptual | [
"2db0c927ad2e89792030dbdcf0eddd78e18d8e85"
] | [
"cm_bart/fairseq/fairseq/models/transformer.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom collections import namedtuple\nimport math\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom fair... | [
[
"torch.Tensor",
"torch.nn.functional.dropout",
"torch.nn.init.constant_",
"torch.nn.ModuleList",
"torch.nn.Embedding",
"torch.nn.Linear",
"torch.nn.init.normal_",
"torch.FloatTensor",
"torch.nn.init.xavier_uniform_",
"torch.nn.functional.linear"
]
] |
skyu0221/cmput496 | [
"ad1e59805ab49324ec1e387ddeaf3dd3202518bc"
] | [
"Assign3/Go4/Go4.py"
] | [
"#!/usr/bin/python3\nfrom gtp_connection import GtpConnection\nimport numpy as np\nfrom board_util import GoBoardUtil\nimport argparse\nimport sys\nfrom pattern import pat3set\n\nparser = argparse.ArgumentParser(description='Process Arguments for number of simulation')\nparser.add_argument('-s','--sim',type=int, na... | [
[
"numpy.argmax"
]
] |
snapbuy/kiwoom-1 | [
"4a267a917c87dbf4308ab00b2c395d541aa5005f"
] | [
"kiwoom/core/server.py"
] | [
"from kiwoom import config\nfrom kiwoom.config import history\nfrom kiwoom.config.error import msg\nfrom kiwoom.config.types import MULTI\nfrom kiwoom.data.preps import string\nfrom kiwoom.utils.general import name, date\nfrom kiwoom.utils.manager import Downloader\n\nfrom os import getcwd, makedirs\nfrom os.path i... | [
[
"pandas.concat",
"pandas.to_datetime",
"pandas.DateOffset",
"pandas.read_csv"
]
] |
Hvedrug/MAS_Project_Agents_fighting_on_a_map | [
"7dd43c030989ed5d028d289e7596469f6e390edb"
] | [
"src/listThreeKillers/Environment.py"
] | [
"import numpy as np\nfrom gym import Env, spaces, utils\nfrom random import randrange\n\n\nMAP = [\n\"+---------+\",\n\"| | | | | |\",\n\"| | | | | |\",\n\"| | | | | |\",\n\"| | | | | |\",\n\"| | | | | |\",\n\"+---------+\",\n]\n\n\nclass Environment:\n \"\"\"\n inspired by Tom Dietterich work on the Taxi Pro... | [
[
"numpy.asarray",
"numpy.zeros"
]
] |
shaform/Texygen-scratch | [
"79d82ae8753a61bfe78b59c13700056573835239"
] | [
"models/gsgan/Gsgan.py"
] | [
"import json\nfrom time import time\n\nimport tensorflow as tf\nimport numpy as np\n\nfrom models.Gan import Gan\nfrom models.gsgan.GsganDataLoader import DataLoader, DisDataloader\nfrom models.gsgan.GsganDiscriminator import Discriminator\nfrom models.gsgan.GsganGenerator import Generator\nfrom utils.metrics.Bleu ... | [
[
"tensorflow.global_variables_initializer",
"numpy.eye",
"numpy.zeros",
"numpy.argmin"
]
] |
KarlJohnsonnn/cloudnetpy | [
"eae2966a515829108899a527b8d34ddff2472124"
] | [
"cloudnetpy/products/drizzle.py"
] | [
"\"\"\"Module for creating Cloudnet drizzle product.\n\"\"\"\nimport os\nfrom bisect import bisect_left\nfrom typing import Union\nimport numpy as np\nimport numpy.ma as ma\nfrom scipy.special import gamma\nimport netCDF4\nfrom cloudnetpy import utils, output\nfrom cloudnetpy.categorize import DataSource\nfrom clou... | [
[
"scipy.special.gamma",
"numpy.isfinite",
"numpy.ma.copy",
"numpy.ones",
"numpy.deg2rad",
"numpy.copy",
"numpy.zeros_like",
"numpy.any",
"numpy.searchsorted",
"numpy.exp",
"numpy.ma.masked_where",
"numpy.where",
"numpy.zeros"
]
] |
krevas/NER | [
"ffdb726ac420efedb0025a90243f8ac11e289ef9"
] | [
"utils.py"
] | [
"import random\n\nimport torch\nimport numpy as np\nfrom numpy.lib.function_base import average\nfrom seqeval import metrics as seqeval_metrics\nfrom sklearn import metrics as sklearn_metrics\nfrom sklearn.preprocessing import LabelBinarizer\nfrom itertools import chain\nimport matplotlib.pyplot as plt\nfrom sklear... | [
[
"matplotlib.pyplot.imshow",
"sklearn.metrics.confusion_matrix",
"torch.cuda.is_available",
"torch.cuda.manual_seed_all",
"sklearn.metrics.f1_score",
"sklearn.metrics.classification_report",
"matplotlib.pyplot.tight_layout",
"sklearn.preprocessing.LabelBinarizer",
"matplotlib.py... |
jinnerbichler/neural-politician | [
"34e5523709345908a734f7e84621057a924e2d87"
] | [
"backend/views.py"
] | [
"import glob\nimport itertools\nimport logging\nimport re\nimport sys\nfrom pathlib import Path\n\nfrom django.http import JsonResponse\nimport tensorflow as tf\nimport numpy as np\nfrom keras import Sequential\nfrom keras import backend as K\nfrom keras.models import load_model\n\nfrom intelligence.speech_data imp... | [
[
"tensorflow.Graph",
"numpy.array",
"tensorflow.Session"
]
] |
jendelel/rhl-algs | [
"d5b8779d7e271265d4f0bfcb3602bc56958e3eb3"
] | [
"utils/logx.py"
] | [
"\"\"\"\n\nSome simple logging functionality, inspired by rllab's logging.\n\nLogs to a tab-separated-values file (path/to/output_directory/progress.txt)\n\n\"\"\"\nimport json\nimport joblib\nimport shutil\nimport numpy as np\nimport torch\nimport os.path as osp, time, atexit, os\nfrom utils.serialization_utils im... | [
[
"numpy.min",
"numpy.concatenate",
"numpy.max",
"numpy.std",
"numpy.mean",
"numpy.array"
]
] |
davidleo1984/Banana-Collector | [
"c6dbc3047a5a958d9fc0f01c1f416baace343410"
] | [
"navi_agent.py"
] | [
"import numpy as np\nimport random\nfrom collections import namedtuple, deque\n\nfrom model import QNetwork\n\nimport torch\nimport torch.nn.functional as F\nimport torch.optim as optim\n\nBUFFER_SIZE = int(1e5) # replay buffer size\nBATCH_SIZE = 64 # minibatch size\nGAMMA = 0.99 # discount fact... | [
[
"numpy.arange",
"torch.from_numpy",
"torch.nn.functional.mse_loss",
"torch.no_grad",
"torch.cuda.is_available",
"numpy.vstack"
]
] |
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