repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
whj363636/CamDrop | [
"f8af8c200665145f112b59348f60fc4cf80f04ec"
] | [
"ResNet/imagenet_utils.py"
] | [
"# -*- coding: utf-8 -*-\n# File: imagenet_utils.py\n\n\nimport multiprocessing\nimport numpy as np\nimport os\nfrom abc import abstractmethod\nimport cv2\nimport tensorflow as tf\nimport tqdm\n\nfrom tensorpack import ModelDesc\nfrom tensorpack.dataflow import AugmentImageComponent, BatchData, MultiThreadMapData, ... | [
[
"tensorflow.cond",
"tensorflow.get_variable",
"tensorflow.zeros",
"numpy.asarray",
"tensorflow.stack",
"tensorflow.cast",
"tensorflow.equal",
"tensorflow.image.resize_bicubic",
"tensorflow.image.decode_and_crop_jpeg",
"tensorflow.group",
"tensorflow.summary.scalar",
... |
PacktPublishing/Applied-Computational-Thinking-with-Python | [
"fd9982383c5b473ffa1640998540d602876816e5"
] | [
"Chapter12/ch12_csvAnalysis_3.py"
] | [
"import pandas as pd\nimport matplotlib as mlp\nimport matplotlib.pyplot as plt\nimport os\n\n#Let Python know correct directory for file.\nos.chdir('C:\\\\...')\n\ngraduates = pd.read_csv('ch12_data.csv', index_col = 0)\nprint(graduates[0:13])\n\nfig, ax = plt.subplots()\nax.bar(graduates.index, graduates['Hispani... | [
[
"pandas.read_csv",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show"
]
] |
bryanhpchiang/symbolic-music-diffusion | [
"341daa8c0198c9adda8d540ff14202e238c36c1c"
] | [
"input_pipeline.py"
] | [
"# Copyright 2021 The Magenta 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 o... | [
[
"tensorflow.cast",
"tensorflow.gather",
"tensorflow.reshape",
"numpy.random.randn"
]
] |
hugovk/pyirf | [
"12afef58a27862abfe2a6c049b68f6d05f6fe31d"
] | [
"pyirf/perf/cut_optimisation.py"
] | [
"import os\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport astropy.units as u\nfrom astropy.table import Table, Column\nfrom gammapy.spectrum.models import PowerLaw\nfrom gammapy.stats import significance_on_off\n\nfrom .utils import save_obj, load_obj, plot_hist\n\n__all__ = [\"CutsOptimisation\", \"C... | [
[
"matplotlib.pyplot.gca",
"matplotlib.pyplot.tight_layout",
"numpy.sqrt",
"numpy.linspace",
"numpy.abs",
"numpy.arange",
"matplotlib.pyplot.subplots",
"numpy.cumsum",
"numpy.cos",
"numpy.where",
"numpy.array",
"numpy.histogram",
"numpy.sum",
"numpy.zeros",
... |
zhongmicai/PlantCV | [
"f2ca234100568d431fc1b99b1c0d029f3385f180"
] | [
"plantcv/plantcv/roi_objects.py"
] | [
"import cv2\nimport numpy as np\nimport os\nfrom plantcv.plantcv import print_image\nfrom plantcv.plantcv import plot_image\nfrom plantcv.plantcv import fatal_error\nfrom plantcv.plantcv import params\n\n\ndef roi_objects(img, roi_contour, roi_hierarchy, object_contour, obj_hierarchy, roi_type=\"partial\"):\n \"... | [
[
"numpy.copy",
"numpy.array",
"numpy.shape",
"numpy.vstack"
]
] |
InsaneMonster/USienaRL | [
"95eb35913b448c970b83ab941a24657156cfcd9b",
"95eb35913b448c970b83ab941a24657156cfcd9b"
] | [
"benchmarks/frozen_lake_desarsa.py",
"usienarl/agents/double_deep_q_learning_agent_epsilon_greedy.py"
] | [
"#\n# Copyright (C) 2019 Luca Pasqualini\n# University of Siena - Artificial Intelligence Laboratory - SAILab\n#\n#\n# USienaRL is licensed under a BSD 3-Clause.\n#\n# You should have received a copy of the license along with this\n# work. If not, see <https://opensource.org/licenses/BSD-3-Clause>.\n\n# Import pack... | [
[
"tensorflow.contrib.layers.xavier_initializer"
],
[
"tensorflow.Summary",
"numpy.zeros"
]
] |
Lavendulaa/programming-in-python-for-data-science | [
"22836d9013d3e3d1b1074678ba7dc3ee2e66f398"
] | [
"exercises/en/exc_08_26.py"
] | [
"import pandas as pd\n\nlego = pd.read_csv('data/lego-sets.csv')\n\n# Convert the name column in the lego dataset to lowercase and\n# overwrite the dataframe by saving it as an object named lego \n\n# ____ = ____\n# ____\n\n# Filter the dataset to find all the lego sets that contain \"weetabix\" in the name column... | [
[
"pandas.read_csv"
]
] |
Cxl1013/TINT | [
"479c5899713d149003096fbbc900b3c52793394d"
] | [
"tint/grid_utils.py"
] | [
"\"\"\"\ntint.grid_utils\n===============\n\nTools for pulling data from pyart grids.\n\n\n\"\"\"\n\nimport datetime\n\nimport numpy as np\nimport pandas as pd\nfrom scipy import ndimage\n\n\ndef parse_grid_datetime(grid_obj):\n \"\"\" Obtains datetime object from pyart grid_object. \"\"\"\n dt_string = grid_... | [
[
"numpy.round",
"scipy.ndimage.label",
"numpy.any",
"numpy.prod",
"numpy.array"
]
] |
markamo/xtellixClient | [
"9f2cb6454fa01b2199e7beec20e878890e9b175b"
] | [
"griewank-example.py"
] | [
"import xtellixClient as xm\nimport math\nimport numpy as np\nfrom tqdm import trange\n\ndef griewank_function(x, dim):\n \"\"\"Griewank's function \tmultimodal, symmetric, inseparable \"\"\"\n sumPart = 0\n prodPart = 1\n for i in range(dim):\n sumPart += x[i]**2\n prodPart *= math.cos(fl... | [
[
"numpy.ones"
]
] |
schoyc/foolbox | [
"25d995b1a50f4926e07bc51877d385c0518982f8"
] | [
"foolbox/attacks/newtonfool.py"
] | [
"import logging\n\nfrom .base import Attack\nfrom .base import call_decorator\nfrom ..utils import softmax\n\nimport numpy as np\n\n\nclass NewtonFoolAttack(Attack):\n \"\"\"Implements the NewtonFool Attack.\n\n The attack was introduced in [1]_.\n\n References\n ----------\n .. [1] Uyeong Jang et al... | [
[
"numpy.linalg.norm",
"numpy.clip"
]
] |
Mohamed209/Train-CRNN | [
"6d2fe08d3bc43494158c732dc5997a951aef18c9"
] | [
"ocr/train_model.py"
] | [
"# coding: utf-8\nfrom keras.callbacks import ModelCheckpoint\nfrom keras.utils import to_categorical\nimport keras.backend as K\nfrom keras import optimizers\nfrom keras.activations import relu, sigmoid, softmax\nfrom keras.models import Model\nfrom keras.layers import Dense, LSTM, GRU, Reshape, BatchNormalization... | [
[
"numpy.ones",
"numpy.zeros",
"tensorflow.python.client.device_lib.list_local_devices",
"numpy.random.choice"
]
] |
LUUTHIENXUAN/fast-autoaugment-on-a-single-gpu | [
"20b61678ff09481a8b74e71ebd5a2188a44e8022"
] | [
"FastAutoAugment/data.py"
] | [
"import logging\n\nimport numpy as np\nimport os\n\nimport math\nimport random\nimport torch\nimport torchvision\nfrom PIL import Image\n\nfrom torch.utils.data import SubsetRandomSampler, Sampler, Subset, ConcatDataset\nimport torch.distributed as dist\nfrom torchvision.transforms import transforms\nfrom sklearn.m... | [
[
"torch.utils.data.SubsetRandomSampler",
"numpy.clip",
"torch.utils.data.DataLoader",
"torch.from_numpy",
"numpy.ones",
"torch.utils.data.ConcatDataset",
"torch.utils.data.Subset",
"torch.distributed.get_rank",
"torch.distributed.get_world_size",
"sklearn.model_selection.Str... |
jose-dscience/stylegan2 | [
"4a8e775639c8b70c4dc6653e7b2d73974e268574"
] | [
"dataset_tool.py"
] | [
"# Copyright (c) 2019, NVIDIA Corporation. All rights reserved.\n#\n# This work is made available under the Nvidia Source Code License-NC.\n# To view a copy of this license, visit\n# https://nvlabs.github.io/stylegan2/license.html\n\n\"\"\"Tool for creating multi-resolution TFRecords datasets.\"\"\"\n\nimport os, s... | [
[
"tensorflow.train.Int64List",
"numpy.log2",
"numpy.pad",
"numpy.min",
"numpy.asarray",
"numpy.arange",
"numpy.rint",
"tensorflow.python_io.TFRecordWriter",
"numpy.concatenate",
"numpy.all",
"numpy.max",
"numpy.round",
"numpy.fromstring",
"numpy.load",
"n... |
CFM-MSG/Code_SelectiveHCN | [
"1f624c5debd03925f0732d1d732c69c46d1fc39d"
] | [
"model/agc_layer.py"
] | [
"import math\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\n\nfrom .utils import *\n\n\nclass unit_tcn(nn.Module):\n def __init__(self, in_channels, out_channels, kernel_size=9, stride=1):\n super(unit_tcn, self).__init__()\n pad = int((kernel_size - ... | [
[
"torch.nn.Softmax",
"torch.nn.Dropout",
"torch.nn.init.constant_",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.matmul",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU"
]
] |
ok97465/npzheader | [
"f0540c378ac83ad13ea98a1f51818b2d73714ae6"
] | [
"npzheader/parser.py"
] | [
"\"\"\"Parse numpy binary format.\"\"\"\n# ------------ Import\n# Standard library imports\nimport os.path as osp\nimport zipfile\nfrom dataclasses import dataclass\nfrom typing import Union, Dict\n\n\n# Third party imports\nimport numpy as np\nfrom scipy.io import whosmat, loadmat\n\n\n# ----------- function\n@dat... | [
[
"scipy.io.whosmat",
"scipy.io.loadmat"
]
] |
JonathanThangadurai/ludwig | [
"c167b33079e32983196f0c8a75ce486883180164"
] | [
"ludwig/api.py"
] | [
"# !/usr/bin/env python\n# coding=utf-8\n# Copyright (c) 2019 Uber Technologies, Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENS... | [
[
"pandas.DataFrame"
]
] |
elb3k/perceiver-pytorch | [
"b07d5154c5dee63684c59f57d02a1b405701845f"
] | [
"perceiver_pytorch/experimental.py"
] | [
"import torch\nfrom torch import nn, einsum\nimport torch.nn.functional as F\n\nfrom einops import rearrange, repeat\n\nfrom perceiver_pytorch.perceiver_pytorch import exists, default, cache_fn, fourier_encode, PreNorm, FeedForward, Attention\n\n# linear attention\n\nclass LinearAttention(nn.Module):\n def __ini... | [
[
"torch.nn.Dropout",
"torch.linspace",
"torch.cat",
"torch.einsum",
"torch.nn.ModuleList",
"torch.randn",
"torch.nn.Linear",
"torch.meshgrid"
]
] |
yufeiwang63/ROLL | [
"aba0b4530934946eb9c41fbe5a0d6c27775596ff",
"aba0b4530934946eb9c41fbe5a0d6c27775596ff"
] | [
"test_latent_space/test_vae.py",
"segmentation/test_script.py"
] | [
"import numpy as np\nimport argparse\nfrom os import path as osp\nimport torch\nimport multiworld, gym\nfrom multiworld.core.image_env import ImageEnv, unormalize_image, normalize_image\nimport rlkit.torch.pytorch_util as ptu\nfrom multiworld.envs.mujoco.cameras import sawyer_init_camera_zoomed_in, sawyer_init_came... | [
[
"matplotlib.pyplot.legend",
"numpy.arange",
"numpy.load",
"matplotlib.pyplot.subplots",
"numpy.linalg.norm",
"matplotlib.pyplot.savefig",
"numpy.argmin",
"matplotlib.pyplot.close",
"numpy.argsort",
"matplotlib.pyplot.show",
"numpy.sum"
],
[
"numpy.hstack",
"... |
chummels/trident_test | [
"259339b1d46f96565d862ad8f11d6d7970a2f73d"
] | [
"tests/test_line_database.py"
] | [
"\"\"\"\nTests for Line Database classes and functions\n\n\"\"\"\n\n#-----------------------------------------------------------------------------\n# Copyright (c) 2016, Trident Development Team.\n#\n# Distributed under the terms of the Modified BSD License.\n#\n# The full license is in the file LICENSE, distribute... | [
[
"numpy.arange",
"numpy.ones"
]
] |
VedantMadane/text | [
"66e250ed638e8161c28c654b4d37403871d23a71"
] | [
"tensorflow_text/python/ops/bert_tokenizer.py"
] | [
"# coding=utf-8\n# Copyright 2021 TF.Text 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 appl... | [
[
"tensorflow.python.eager.monitoring.Counter",
"tensorflow.python.ops.string_ops.string_lower",
"tensorflow.python.ops.array_ops.expand_dims",
"tensorflow.python.ops.string_ops.regex_replace"
]
] |
wangwei14/tensorflow_learn | [
"d2d6e10a52c31fd177295375639a88d06f045bee",
"d2d6e10a52c31fd177295375639a88d06f045bee"
] | [
"aymericdamien/linear_regression.py",
"rnnlm/test_PTB.py"
] | [
"'''\nA linear regression learning algorithm example using TensorFlow library.\nAuthor: Aymeric Damien\nProject: https://github.com/aymericdamien/TensorFlow-Examples/\n'''\n\nfrom __future__ import print_function\n\nimport tensorflow as tf\nimport numpy\nimport matplotlib.pyplot as plt\nrng = numpy.random\n\n# Para... | [
[
"matplotlib.pyplot.legend",
"tensorflow.multiply",
"tensorflow.pow",
"numpy.asarray",
"tensorflow.placeholder",
"matplotlib.pyplot.plot",
"tensorflow.global_variables_initializer",
"tensorflow.train.GradientDescentOptimizer",
"tensorflow.Session",
"matplotlib.pyplot.show"
... |
nash911/PyDL | [
"b0b6f599184c0046f503b9ee1703dc3dfe9a89f2",
"b0b6f599184c0046f503b9ee1703dc3dfe9a89f2"
] | [
"pydl/tests/test_pool.py",
"pydl/tests/test_batchnorm.py"
] | [
"# ------------------------------------------------------------------------\n# MIT License\n#\n# Copyright (c) [2021] [Avinash Ranganath]\n#\n# This code is part of the library PyDL <https://github.com/nash911/PyDL>\n# This code is licensed under MIT license (see LICENSE.txt for details)\n# ------------------------... | [
[
"numpy.ones_like",
"numpy.pad",
"numpy.sum",
"numpy.min",
"numpy.testing.assert_almost_equal",
"numpy.max",
"numpy.ceil",
"numpy.mean",
"numpy.floor",
"numpy.random.uniform",
"numpy.array",
"numpy.zeros",
"numpy.isinf",
"numpy.empty"
],
[
"numpy.ones... |
weinixuehao/Recursive-CNNs | [
"2f5c66c07b5f7d0c0cbd59da310eb48bf2c91cad"
] | [
"train_model.py"
] | [
"''' Document Localization using Recursive CNN\n Maintainer : Khurram Javed\n Email : kjaved@ualberta.ca '''\n\nfrom __future__ import print_function\n\nimport argparse\n\nimport torch\nimport torch.utils.data as td\n\nimport dataprocessor\nimport experiment as ex\nimport model\nimport trainer\nimport utils\n\npars... | [
[
"torch.manual_seed",
"torch.utils.data.DataLoader",
"torch.cuda.manual_seed",
"torch.cuda.is_available"
]
] |
maxilse/hi-ml | [
"7902a6e1387a74ef0d861109450a5c93674de764"
] | [
"hi-ml-azure/src/health_azure/utils.py"
] | [
"# ------------------------------------------------------------------------------------------\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.\n# -----------------------------------------------------------... | [
[
"torch.distributed.is_available",
"torch.distributed.is_initialized",
"torch.distributed.barrier",
"pandas.DataFrame.from_dict"
]
] |
FelixFu520/segmentation | [
"66503244826110e19446cf274f49d6e018e57f2c"
] | [
"data/Data_preprocess.py"
] | [
"import numpy as np\nimport os\nimport cv2\nimport re\nfrom itertools import chain\nfrom glob import glob\n\n\ndef gen_mean_std(root_path=\"/root/data/segmentation/VOCtrainval_11-May-2012/VOCdevkit/VOC2012/JPEGImages\", txt_path=\"\"):\n \"\"\"\n 功能：获得 1、root_path路径下所有图片\n 2、txt_path文件中所有图片路径（TODO... | [
[
"numpy.sum",
"numpy.sqrt"
]
] |
snap-stanford/ConE | [
"f765c3d72dcdb9ae2a0b86db6f4c5c0e39a73a63"
] | [
"codes/utils/manifolds/euclidean.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) 2018-present, Facebook, Inc.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom .manifold import Manifold\nimport torch as th\nimport numpy as np\n\n\nclass EuclideanMan... | [
[
"numpy.sqrt"
]
] |
michaelStettler/BVS | [
"947f1e505ccc3ebcf1926c8f52924d823bd1e101",
"947f1e505ccc3ebcf1926c8f52924d823bd1e101",
"947f1e505ccc3ebcf1926c8f52924d823bd1e101"
] | [
"tests/v1_and_BotUpSaliency/utils/draw_on_grid.py",
"tests/CNN/t02b_compare_PCA_idx.py",
"utils/evaluate_model.py"
] | [
"import numpy as np\n\n\ndef draw_on_grid(img):\n \"\"\"\n draw_on_grid will replicate what would be the input image look like from the gabor filter activations (input).\n It will draw a line corresponding to each orientation into a small box for each x, y coordinate of the input image.\n\n This functio... | [
[
"numpy.expand_dims",
"numpy.min",
"numpy.max",
"numpy.argmax",
"numpy.shape",
"numpy.array",
"numpy.zeros"
],
[
"numpy.amax",
"numpy.expand_dims",
"numpy.random.seed",
"numpy.set_printoptions",
"numpy.std",
"numpy.shape",
"numpy.argsort"
],
[
"nu... |
RyosukeDTomita/cyclone_track | [
"91238a7a8af2e23b3ae697c35f3b6c40516dc80a"
] | [
"cyclonetrack/biquadratic.py"
] | [
"# coding: utf-8\n\"\"\"\nCopied by https://github.com/tenomoto/pytrack/blob/master/biquadratic.py interpolate(), https://github.com/tenomoto/pytrack/blob/master/grid.py __set_stencil().\n\"\"\"\nimport numpy as np\n\n\ndef set_stencil(g, i0, j0):\n ny, nx = g.shape\n ia = (i0 + nx - 1) % nx\n ib = (i0 + 1... | [
[
"numpy.zeros",
"numpy.zeros_like"
]
] |
marc-rigter/dsac | [
"6023ebacd7c8be1764f41567c4cbe6f79fab1c26"
] | [
"rlkit/torch/dsac/networks.py"
] | [
"\"\"\"\nGeneral networks for pytorch.\n\nAlgorithm-specific networks should go else-where.\n\"\"\"\nimport numpy as np\nimport torch\nfrom torch import nn as nn\nfrom torch.nn import functional as F\n\nfrom rlkit.torch import pytorch_util as ptu\n\n\ndef softmax(x):\n return F.softmax(x, dim=-1)\n\n\nclass Quan... | [
[
"torch.nn.Sequential",
"torch.nn.functional.softmax",
"torch.cat",
"numpy.arange",
"torch.nn.Sigmoid",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.nn.Identity",
"torch.nn.ReLU"
]
] |
iriziotis/biopython | [
"171697883aca6894f8367f8f20f1463ce7784d0c"
] | [
"Bio/Affy/CelFile.py"
] | [
"# Copyright 2004 by Harry Zuzan. All rights reserved.\n# Copyright 2016 by Adam Kurkiewicz. All rights reserved.\n# This file is part of the Biopython distribution and governed by your\n# choice of the \"Biopython License Agreement\" or the \"BSD 3-Clause License\".\n# Please see the LICENSE file that should have ... | [
[
"numpy.zeros",
"numpy.empty"
]
] |
leelew/MetReg | [
"b38e28326374e30521eab70625b9c22105688d8d",
"b38e28326374e30521eab70625b9c22105688d8d",
"b38e28326374e30521eab70625b9c22105688d8d"
] | [
"tests/test_pcmci.py",
"MetReg/data/data_loader.py",
"MetReg/models/dl/layers/constrain.py"
] | [
"# Imports\nfrom CausalityTest import Granger\nimport numpy as np\nimport matplotlib\nfrom matplotlib import pyplot as plt\n# matplotlib inline\n# use `%matplotlib notebook` for interactive figures\n# plt.style.use('ggplot')\nimport sklearn\nimport h5py\nimport pandas as pd\n\nimport tigramite\nfrom tigramite impor... | [
[
"numpy.array",
"pandas.read_csv",
"matplotlib.pyplot.show"
],
[
"tensorflow.data.Dataset.from_tensor_slices"
],
[
"tensorflow.keras.layers.AveragePooling2D",
"tensorflow.reshape",
"tensorflow.concat",
"tensorflow.keras.layers.MaxPooling2D"
]
] |
SomaKishimoto/AwA-Pose | [
"b9877d538af25d07a6e2f9fa0b5aa2fdf544db99",
"b9877d538af25d07a6e2f9fa0b5aa2fdf544db99"
] | [
"code/deep-high-resolution-net.pytorch/lib/models/pose_hrnet.py",
"code/cocoapi/PythonAPI/pycocotools/cocoeval_atrw.py"
] | [
"# ------------------------------------------------------------------------------\n# Copyright (c) Microsoft\n# Licensed under the MIT License.\n# Written by Bin Xiao (Bin.Xiao@microsoft.com)\n# ------------------------------------------------------------------------------\n\nfrom __future__ import absolute_import\... | [
[
"torch.nn.Sequential",
"torch.load",
"torch.nn.init.constant_",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.init.normal_",
"torch.nn.Upsample",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU"
],
[
"numpy.logical_not",
"numpy.spacing",
"numpy.unique",
"numpy.... |
yjbang/math6380 | [
"045bf9dd877b4b387580459fd747a4e428cbe8ff"
] | [
"GCE/GCEloss.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport math\nimport numpy as np\n\nclass GCELoss(nn.Module):\n\n def __init__(self, q=0.7, k=0.5, trainset_size=50000, num_classes=2):\n super(GCELoss, self).__init__()\n self.q = q\n self.k = k\n self.weight = tor... | [
[
"torch.mean",
"torch.nn.functional.softmax",
"torch.ones",
"torch.sum",
"torch.from_numpy",
"torch.unsqueeze",
"torch.cuda.is_available",
"torch.nn.functional.one_hot",
"torch.gt"
]
] |
mazx4960/CTFs | [
"f262e733afe79eed3482781a0aff2ba36acc9e72"
] | [
"2020/X-MAS CTF/Programming/many paths/paths.py"
] | [
"from pwn import *\nimport math\nimport numpy as np\n\n\nurl = 'challs.xmas.htsp.ro'\nport = 6053\n\nconn = remote(url, port)\n\ndef exponentiation(bas, exp): \n t = np.identity(N, dtype=np.int64); \n while(exp > 0): \n if (exp % 2 != 0): \n t = (t.dot(bas)) % 666013; \n \n bas = (b... | [
[
"numpy.asarray",
"numpy.dot",
"numpy.identity"
]
] |
TeaPearce/Bayesian_NN_Ensembles | [
"cb1f4cfc7c4095905ce5d7f23707fea4e0679af9"
] | [
"regression/hyperparams.py"
] | [
"# -*- coding: utf-8 -*-\nimport numpy as np\n\n\"\"\"\ncontains params to run experiments on\n\"\"\"\n\ndef get_hyperparams(data_set, activation_fn,hidden_size,is_deep_NN=False):\n\t# create a dict of hyperparams\n\thyp = {}\n\thyp = \t{'batch_size': 64, 'optimiser_in': 'adam', 'learning_rate': 0.001}\n\n\tif data... | [
[
"numpy.sqrt"
]
] |
SimonLaub/AI_Intro | [
"08f1dcf4a99d8e1311cd334d3fdd900ea70c0c57"
] | [
"ReinforcementLearning/PiEstimate.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Apr 18 12:47:56 2020\n@author: Sila\n\"\"\"\n\n# Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms\n# that rely on repeated random sampling to obtain numerical results.\n\nimport numpy as np\nimport math\nimport random\nim... | [
[
"numpy.linspace",
"numpy.cos",
"numpy.sin",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.show"
]
] |
ZhuangweiKang/tods | [
"fe3f55f8ccb306dd292c668e0f1154f1afdfa556",
"fe3f55f8ccb306dd292c668e0f1154f1afdfa556"
] | [
"tods/detection_algorithm/core/KDiscord.py",
"tods/tests/test_PyodCOF.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Autoregressive model for multivariate time series outlier detection.\n\"\"\"\nimport numpy as np\nfrom sklearn.utils import check_array\nfrom sklearn.utils.validation import check_is_fitted\n\nfrom .CollectiveBase import CollectiveBaseDetector\nfrom pyod.models.knn import KNN\n\nfrom... | [
[
"numpy.asarray",
"sklearn.utils.check_array",
"sklearn.utils.validation.check_is_fitted"
],
[
"pandas.testing.assert_frame_equal",
"pandas.DataFrame"
]
] |
Linda-liugongzi/DIGITS-digits-py3 | [
"6df5eb6972574a628b9544934518ec8dfa9c7439",
"6df5eb6972574a628b9544934518ec8dfa9c7439"
] | [
"plugins/view/textClassification/digitsViewPluginTextClassification/view.py",
"digits/tools/pb/label_image.py"
] | [
"# Copyright (c) 2016-2017, NVIDIA CORPORATION. All rights reserved.\n\n\nimport os\n\nimport numpy as np\n\nfrom digits.utils import subclass, override\nfrom digits.extensions.view.interface import VisualizationInterface\nfrom .forms import ConfigForm\nfrom flask_babel import lazy_gettext as _\n\n\nCONFIG_TEMPLAT... | [
[
"numpy.max",
"numpy.exp"
],
[
"tensorflow.Graph",
"tensorflow.image.resize_bilinear",
"tensorflow.import_graph_def",
"tensorflow.read_file",
"tensorflow.gfile.GFile",
"numpy.squeeze",
"tensorflow.cast",
"tensorflow.image.decode_png",
"tensorflow.expand_dims",
"t... |
pandera-labs/pandera | [
"c494ee76691199a878e0594f2b4ad3741af26ef8"
] | [
"tests/core/test_schemas.py"
] | [
"\"\"\"Testing creation and manipulation of DataFrameSchema objects.\"\"\"\n# pylint: disable=too-many-lines,redefined-outer-name\n\nimport copy\nfrom datetime import datetime, timedelta\nfrom functools import partial\nfrom typing import Any, Callable, Dict, List, Tuple, Type, Union\n\nimport numpy as np\nimport pa... | [
[
"pandas.Series",
"pandas.Index",
"pandas.DataFrame",
"pandas.MultiIndex.from_arrays",
"pandas.Timedelta",
"pandas.testing.assert_frame_equal",
"pandas.DataFrame.from_dict",
"pandas.isna",
"pandas.Timestamp"
]
] |
joennlae/halutmatmul | [
"69340d3386298401d421b0e67dcb0649534b0c12"
] | [
"maddness/python/maddness/util/hash_function_helper.py"
] | [
"# type: ignore\nimport copy\nimport numba\nimport numpy as np\n\n\n@numba.njit(fastmath=True, cache=True, parallel=False)\ndef _cumsse_cols(X):\n # TODO: can be optimized with numpy\n N, D = X.shape\n cumsses = np.empty((N, D), X.dtype)\n cumX_column = np.empty(D, X.dtype)\n cumX2_column = np.empty(... | [
[
"numpy.square",
"numpy.maximum",
"numpy.asarray",
"numpy.copy",
"numpy.argmin",
"numpy.argsort",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.empty"
]
] |
Rohitpandit021/jina | [
"f3db4d5e480375d8dc3bceda814ac1963dee76d7"
] | [
"tests/distributed/test_simple_hub_pods/hub-mwu/mwu_encoder.py"
] | [
"from typing import Any\n\nimport numpy as np\n\nfrom jina.executors.encoders import BaseEncoder\n\n\nclass MWUEncoder(BaseEncoder):\n def __init__(self, greetings: str, *args, **kwargs):\n super().__init__(*args, **kwargs)\n self._greetings = greetings\n self.logger.success(f'look at me! {g... | [
[
"numpy.random.random"
]
] |
meyer-lab/valentBind | [
"e8c6e568b1e63dd6c735a9b0aa5585ac9f158b1b"
] | [
"examples/figure4.py"
] | [
"import numpy as np\nfrom valentbind import polyc, polyfc\nfrom matplotlib import gridspec, rcParams, pyplot as plt\nimport matplotlib.cm as cm\nfrom matplotlib.patches import Ellipse\nimport seaborn as sns\n\ndef getSetup(figsize, gridd):\n \"\"\" Establish figure set-up with subplots. \"\"\"\n sns.set(style... | [
[
"numpy.log",
"matplotlib.patches.Ellipse",
"matplotlib.pyplot.clabel",
"numpy.meshgrid",
"numpy.logspace",
"numpy.arange",
"matplotlib.pyplot.Normalize",
"matplotlib.cm.ScalarMappable",
"matplotlib.gridspec.GridSpec",
"numpy.array",
"matplotlib.pyplot.figure"
]
] |
vishalbelsare/deep-scientific-discovery | [
"41e8480314a9f4001c43521b0ec2a7cf1ab28347"
] | [
"hsic.py"
] | [
"import torch\nimport numpy as np\nfrom sklearn.metrics import pairwise_distances as pdist\n\n\ndef pairwise_distances(x):\n x_distances = torch.sum(x**2, -1).reshape((-1, 1))\n return -2*torch.mm(x, x.t()) + x_distances + x_distances.t()\n\n\ndef kernelMatrixGaussian(x, sigma=1):\n pairwise_distances_ = p... | [
[
"torch.mm",
"numpy.maximum",
"torch.ones",
"torch.zeros",
"torch.sum",
"torch.eye",
"torch.exp"
]
] |
noklam/trains | [
"8ec6bba4d91104a2bdd2e537bec21078529540e0",
"8ec6bba4d91104a2bdd2e537bec21078529540e0"
] | [
"examples/pipeline/step2_data_processing.py",
"trains/external/kerastuner.py"
] | [
"import pickle\nfrom trains import Task, StorageManager\nfrom sklearn.model_selection import train_test_split\n\n\n# Connecting TRAINS\ntask = Task.init(project_name=\"examples\", task_name=\"pipeline step 2 process dataset\")\n\n# program arguments\n# Use either dataset_task_id to point to a tasks artifact or\n# u... | [
[
"sklearn.model_selection.train_test_split"
],
[
"pandas.DataFrame"
]
] |
matthew-gaddes/InSAR-Tools | [
"03141faeca9322f0616bf74445c40f93a2b77d92"
] | [
"insar_tools/plotting.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Thu Jun 29 17:02:02 2017\r\n\r\nA collection of functions for plotting synthetic interferograms\r\n\r\n@author: eemeg\r\n\"\"\"\r\n\r\n\r\n#%%\r\n\r\n\r\ndef xticks_every_nmonths(ax_to_update, day0_date, time_values, include_tick_labels, \r\n ... | [
[
"matplotlib.gridspec.GridSpecFromSubplotSpec",
"numpy.min",
"numpy.arange",
"numpy.ndarray.flatten",
"matplotlib.pyplot.get_cmap",
"matplotlib.pyplot.subplots",
"numpy.cumsum",
"numpy.sin",
"numpy.max",
"numpy.size",
"matplotlib.pyplot.subplot",
"matplotlib.gridspec... |
minmie/nlp-tutorial | [
"e2aab7758f6477cc5d69785353da1863434caea5"
] | [
"3-2.TextLSTM/TextLSTM-Torch.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"“TextLSTM-Torch.ipynb”的副本\n\nAutomatically generated by Colaboratory.\n\nOriginal file is located at\n https://colab.research.google.com/drive/1K75NsbkuejOzp2tfsXGDJxP-nQl9V0DC\n\"\"\"\n\n'''\n code by Tae Hwan Jung(Jeff Jung) @graykode, modify by wmathor\n'''\nimport torch\nimpo... | [
[
"torch.nn.CrossEntropyLoss",
"torch.LongTensor",
"torch.Tensor",
"torch.nn.LSTM",
"torch.zeros",
"torch.utils.data.TensorDataset",
"numpy.eye",
"torch.utils.data.DataLoader",
"torch.nn.Linear"
]
] |
FiniteStateInc/clearcode-toolkit | [
"521c3a2ab9d9fa6d7b9059227c6af9d09b031c33"
] | [
"src/finitestate/firmware/ghidra/lsh_hash.py"
] | [
"\"\"\"\n lsh_hash.py\n\n Algorithm for performing function hashing over IR representations\n\"\"\"\nimport hashlib\nimport numpy as np\n\nfrom . import model\n\n# type aliases\nVector = np.ndarray\n\n\n# ### FUNCTION HASHING FUNCTIONS #####\ndef gen_planes(num_planes: int = 100) -> Vector:\n \"\"\"\n G... | [
[
"numpy.dot"
]
] |
dev2l0per/Cartoonify | [
"20c769220e0256a0c1ae1ff50a05993beb8db555"
] | [
"src/utils/utils.py"
] | [
"import torch.nn as nn\n\ndef initialize_weights(model):\n # Initializes weights according to the DCGAN paper\n for m in model.modules():\n if isinstance(m, (nn.Conv2d, nn.ConvTranspose2d, nn.BatchNorm2d)):\n nn.init.normal_(m.weight.data, 0.0, 0.02)"
] | [
[
"torch.nn.init.normal_"
]
] |
Joey61Liuyi/TAS | [
"19699f2a12c8c7ab09f9aef0562cd58ea79c2826"
] | [
"exps/basic-main.py"
] | [
"#####################################################\n# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019.01 #\n#####################################################\nimport sys, time, torch, random, argparse\nfrom PIL import ImageFile\n\nImageFile.LOAD_TRUNCATED_IMAGES = True\nfrom copy import deepcopy\nfrom pathli... | [
[
"torch.load",
"torch.utils.data.DataLoader",
"torch.cuda.empty_cache",
"torch.set_num_threads",
"torch.cuda.is_available",
"torch.nn.DataParallel"
]
] |
marenan/Vitis-Tutorials | [
"047afda718ccf98467ca9f9563ceb12418c50474",
"047afda718ccf98467ca9f9563ceb12418c50474"
] | [
"Machine_Learning/Design_Tutorials/09-mnist_pyt-master/files/target.py",
"Machine_Learning/Design_Tutorials/08-tf2_flow/files/application/app_mt.py"
] | [
"'''\n Copyright 2020 Xilinx Inc.\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 writ... | [
[
"torch.utils.data.DataLoader"
],
[
"numpy.argmax",
"numpy.empty"
]
] |
baoduydinh1710/dressing-in-order | [
"11d449a6707d4d77756615b144b3f96ae7869841"
] | [
"utils/pose_utils.py"
] | [
"import numpy as np\nfrom scipy.ndimage.filters import gaussian_filter\nfrom skimage.draw import circle, line_aa, polygon\nimport json\n\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\nimport matplotlib.patches as mpatches\nfrom collections import defaultdict\nimport skimage.measure, ski... | [
[
"numpy.matrix",
"pandas.read_csv",
"numpy.expand_dims",
"matplotlib.use",
"numpy.arange",
"numpy.linalg.norm",
"numpy.mean",
"numpy.array",
"numpy.exp",
"numpy.zeros"
]
] |
spietz/face-image-landmarker | [
"add808772bc852a28e6be992a146cc770a463931"
] | [
"models/my_model.py"
] | [
"from base.base_model import BaseModel\nimport tensorflow as tf\nfrom tensorflow.keras import Model\nfrom tensorflow.keras.applications.vgg16 import VGG16\nfrom tensorflow.keras.layers import Input, Flatten, Dense\n\nclass MyModel(BaseModel):\n def __init__(self, config):\n super(MyModel, self).__init__(c... | [
[
"tensorflow.keras.layers.Dense",
"tensorflow.keras.applications.vgg16.VGG16",
"tensorflow.keras.Model",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Input"
]
] |
selflein/fasth | [
"72c4cd47fc4b92203d6313803508104511881816"
] | [
"test_case.py"
] | [
"\"\"\"\n\tSee 'README.md' for details. \n\n Expected output from 'python test_case.py': \n\n Compiling our c++/cuda code, this usually takes 1-2 min. \n Finished compilation, took: 0.0701s\n\n ---------- Assertions ----------\n Multiplication:\t\t\tPASSED!\n Inverse Multiplica... | [
[
"torch.mean",
"torch.set_default_tensor_type",
"torch.cuda.synchronize",
"torch.zeros",
"torch.manual_seed",
"numpy.std",
"numpy.mean",
"torch.allclose"
]
] |
andrewtarzia/stk | [
"0d3e1b0207aa6fa4d4d5ee8dfe3a29561abb08a2",
"0d3e1b0207aa6fa4d4d5ee8dfe3a29561abb08a2"
] | [
"tests/molecular/topology_graphs/vertex/placement/cases/macrocycle/fixtures/utilities.py",
"src/stk/molecular/topology_graphs/cage/two_plus_three/six_plus_nine.py"
] | [
"import stk\nimport numpy as np\nfrom functools import partial\nfrom scipy.spatial.distance import euclidean\n\n\ndef get_fg_position(id, building_block):\n functional_group, = building_block.get_functional_groups(id)\n return building_block.get_centroid(\n atom_ids=functional_group.get_placer_ids(),\n... | [
[
"numpy.array"
],
[
"numpy.sqrt"
]
] |
vishalbelsare/MoguNumerics | [
"4b6b55b562c3fe318552dd48f6b630d618bbbfc2"
] | [
"mogu/voterank/schemes.py"
] | [
"import numpy as np\nfrom scipy.stats import norm\n\ndef diffscore(npos, nneg):\n return npos-nneg\n\ndef fracscore(npos, nneg):\n return npos/np.array(npos+nneg, dtype=float)\n\ndef wilsonscore(npos, nneg, alpha=0.1):\n num = npos+nneg\n p = fracscore(npos, nneg)\n z = norm.ppf(1.-0.5*alpha)\n de... | [
[
"scipy.stats.norm.ppf",
"numpy.array",
"numpy.sqrt"
]
] |
aiir-team/code_TSA_SVC_luxembourg | [
"c3efd636a82ac8279f5b525b2b117eac76d7f1a0"
] | [
"code_TSA_SVC_report_version/draft2/new_on3.py"
] | [
"import re\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport string\nimport seaborn as sns\nimport nltk\n\n\n\n\ndata = pd.read_csv('../dataset/downloadedB.csv', delimiter='\\t', header=None, names=[\"id1\", \"id2\", \"sentiment\", \"tweet\"])\ndata = data.drop(data[(data['tweet'] ==... | [
[
"pandas.read_csv",
"sklearn.model_selection.train_test_split",
"sklearn.feature_extraction.text.CountVectorizer",
"numpy.vectorize",
"sklearn.svm.SVC",
"sklearn.metrics.accuracy_score"
]
] |
MichaelGMZ/MRes-2020DS-Project2 | [
"740f89ecf140b1665697c6b1e76106ecc675e793"
] | [
"PyCodes/LoadCSV.py"
] | [
"# %%\r\n# ----------------------------------------------------------------\r\n# There are two types of raw data format, .xlsx and .csv\r\n# These series of scripts deal with .csv only\r\n# All imports data initialized paths goes here\r\n# ----------------------------------------------------------------\r\nimport o... | [
[
"pandas.read_csv"
]
] |
saksham-kaushal/tardis | [
"ad91bef1a4dc40b247dfc11951bb4e517a09545f",
"ad91bef1a4dc40b247dfc11951bb4e517a09545f"
] | [
"tardis/montecarlo/tests/test_cmontecarlo.py",
"tardis/plasma/tests/test_complete_plasmas.py"
] | [
"\"\"\"\nUnit tests for methods in `tardis/montecarlo/src/cmontecarlo.c`.\n* `ctypes` library is used to wrap C methods and expose them to python.\n\n\nProbable Reasons for Failing Tests:\n-----------------------------------\n\n1. Change made in C struct declarations:\n - Reflect the changes done in C structs, int... | [
[
"numpy.testing.assert_equal",
"numpy.sqrt",
"numpy.linspace",
"numpy.ctypeslib.as_array",
"numpy.reshape",
"numpy.testing.assert_array_equal",
"numpy.testing.assert_almost_equal",
"pandas.HDFStore",
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.histogram"
],
... |
wwqqqqq/tf-pose-estimation | [
"f5d34265d04e810706fd02b043d2bcebae990a6b"
] | [
"tf_pose/estimator.py"
] | [
"import logging\nimport math\n\nimport slidingwindow as sw\n\nimport cv2\nimport numpy as np\nimport tensorflow as tf\nimport time\n\nfrom tf_pose import common\nfrom tf_pose.common import CocoPart\nfrom tf_pose.tensblur.smoother import Smoother\n\ntry:\n from tf_pose.pafprocess import pafprocess\nexcept ModuleN... | [
[
"tensorflow.import_graph_def",
"tensorflow.nn.pool",
"tensorflow.gfile.GFile",
"tensorflow.equal",
"tensorflow.global_variables",
"tensorflow.placeholder",
"numpy.ndarray",
"tensorflow.report_uninitialized_variables",
"tensorflow.zeros_like",
"numpy.copy",
"tensorflow.S... |
aldopareja/fourier_feat | [
"e2d813c78f1d4b831bcf6bcc9ba2def275f248f0",
"e2d813c78f1d4b831bcf6bcc9ba2def275f248f0"
] | [
"model_free_analysis/drqv2_crff_analysis/wavelet/dmc/mlp.py",
"sac_dennis_rff/actor.py"
] | [
"from pathlib import Path\nimport pandas as pd\nfrom params_proto.neo_hyper import Sweep\n\nfrom drqv2_crff.config import Args, Agent\nfrom model_free_analysis import RUN\n\nhyperparams = pd.read_csv('pretrain_hyperparams.csv')\nhyperparams = hyperparams[hyperparams['env_name'].isin(['dmc:Cheetah-run-v1',\n ... | [
[
"pandas.read_csv"
],
[
"torch.tanh",
"torch.nn.functional.softplus",
"torch.distributions.constraints.interval",
"torch.distributions.Normal"
]
] |
ReDeiPirati/tensor2tensor | [
"39f44893b82a5052c9eddba760fc4094d3d706bb",
"39f44893b82a5052c9eddba760fc4094d3d706bb"
] | [
"tensor2tensor/mesh_tensorflow/mtf_model.py",
"tensor2tensor/mesh_tensorflow/mtf_layers_test.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.convert_to_tensor",
"tensorflow.logging.warning",
"tensorflow.device",
"tensorflow.global_variables",
"tensorflow.contrib.tpu.python.tpu.tpu_estimator.TPUEstimatorSpec",
"tensorflow.contrib.summary.always_record_summaries",
"tensorflow.get_default_graph",
"tensorflow.to... |
RICE-EIC/Double-Win-Quant | [
"c245c161608348bfb32c74b09afc1376bc3bc5d4"
] | [
"CIFAR/utils.py"
] | [
"import apex.amp as amp\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torchvision import datasets, transforms\nfrom torch.utils.data.sampler import SubsetRandomSampler\nimport numpy as np\n\ncifar10_mean = (0.4914, 0.4822, 0.4465)\ncifar10_std = (0.2471, 0.2435, 0.2616)\n\nmu = torch.t... | [
[
"torch.max",
"numpy.random.choice",
"torch.zeros",
"numpy.arange",
"torch.min",
"torch.nn.functional.cross_entropy",
"torch.utils.data.DataLoader",
"torch.zeros_like",
"torch.sign",
"torch.tensor",
"torch.no_grad"
]
] |
BlancRay/facedection | [
"e32430b24e08fe3a5f354e56ed0b68489c859694"
] | [
"dlibmodel/face_dlib.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport PIL.Image\nimport dlib\nimport numpy as np\nimport time\n\nfrom pkg_resources import resource_filename\n\n\ndef pose_predictor_model_location():\n return resource_filename(__name__, \"shape_predictor_68_face_landmarks.dat\")\n\n\ndef pose_predictor_five_point_model_location():\... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.empty"
]
] |
jinlinyi/SparsePlanes | [
"fb063dc48f4e2e1a03dd47702275e1b8a4f5c223"
] | [
"sparsePlane/tools/local_refinement_sift.py"
] | [
"import cv2\nimport pickle\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pycocotools.mask as mask_util\nimport quaternion\nimport os\nimport time\n\nfrom scipy.special import huber\nfrom detectron2.data import DatasetCatalog, MetadataCatalog\nfrom sparseplane.data import PlaneRCNNMapper\nfrom sparsep... | [
[
"numpy.dot",
"matplotlib.pyplot.imshow",
"numpy.clip",
"numpy.linalg.inv",
"numpy.vstack",
"numpy.linalg.norm",
"numpy.arccos",
"numpy.ones",
"numpy.round",
"numpy.random.randint",
"numpy.cross",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.fi... |
tony92151/pedestrian_generator | [
"7c01594a32f271687a49c89dec396b89775bec32",
"7c01594a32f271687a49c89dec396b89775bec32"
] | [
"libs/datasets_inference.py",
"04_Detectron2/eval_MR_FPN2.py"
] | [
"import torch.utils.data as data\nimport os\nimport torch\nimport tqdm\nimport imghdr\nimport random\nfrom PIL import Image\nimport glob\nimport json\nimport numpy as np\nimport math\n#from detectron_pro import mask_img,mask_img_composite\nfrom tqdm import tqdm\nimport cv2\n\nclass ImageDataset(data.Dataset):\n ... | [
[
"numpy.array",
"numpy.zeros",
"numpy.ones"
],
[
"numpy.logspace",
"numpy.maximum",
"numpy.where",
"numpy.insert"
]
] |
charlottenosam/21cmfish | [
"c189e6cb448bf5b2970a2e5f0ca5673918f15276"
] | [
"py21cmfish/power_spectra.py"
] | [
"# define functions to calculate PS, following py21cmmc\nimport py21cmfast as p21c\nimport os, sys\nimport numpy as np\nfrom powerbox.tools import get_power\n\ndef get_k_min_max(lightcone, n_chunks=24):\n \"\"\"\n Get the minimum and maximum k in 1/Mpc to calculate powerspectra for\n given size of box and ... | [
[
"numpy.log",
"numpy.sqrt",
"numpy.linspace",
"numpy.isnan",
"numpy.median",
"numpy.ones",
"numpy.log10",
"numpy.floor",
"numpy.zeros"
]
] |
yliess86/BayeTorch | [
"fbd4447bdf2b9402b3c7df83e776f08ae940b313"
] | [
"bayetorch/models/frequentist/vgg.py"
] | [
"from torch import Tensor\n\nimport torch\nimport torch.nn as nn\n\n\nclass VGG11(nn.Module):\n def __init__(self, n_classes: int = 10) -> None:\n super(VGG11, self).__init__()\n self.n_classes = n_classes\n \n self.conv1 = nn.Conv2d( 3, 64, 3, padding=1)\n self.conv2 = nn.Co... | [
[
"torch.nn.Linear",
"torch.nn.Conv2d"
]
] |
ZhouKai90/face_attributes_mxnet | [
"3313177d2e946044b517df9347b8ff301074856b"
] | [
"demo/fa_predictor.py"
] | [
"import cv2\nimport mxnet as mx\nimport numpy as np\nfrom mxnet import ndarray as nd\n\nIMG_WIDTH = 112\nIMG_HIGHT = 112\n\nclass FaceAttributesPredictor:\n def __init__(self, prefix, epoch=0, ctxId=0):\n self.ctx = mx.gpu(ctxId)\n self.prefix = prefix\n self.epoch = epoch\n\n sym, ar... | [
[
"numpy.argmax",
"numpy.zeros"
]
] |
kouohhashi/ratel_voice | [
"b64c7272e50c977f5b4295a4be9ac352251d37c6"
] | [
"jupyter/prediction.py"
] | [
"import os\nos.environ['TF_CPP_MIN_LOG_LEVEL']='2'\n\n# This is a little hack. if we don't turn off stderr, we get error.\n# python-shell catch the error.\nimport sys\nstderr = sys.stderr\nsys.stderr = open('/dev/null', 'w')\n\nimport numpy as np\nfrom data_generator import AudioGenerator\nfrom keras import backend... | [
[
"numpy.expand_dims"
]
] |
oknuutti/visnav-py | [
"bc03a5bb99e39ecd8cd48f8aa971d8287cabda5c"
] | [
"visnav/calibration/ssi_table.py"
] | [
"\r\nimport numpy as np\r\n\r\n\r\n# from \"Odele Coddington, Judith L. Lean, Doug Lindholm, Peter Pilewskie, Martin Snow, and NOAA CDR Program (2015):\r\n# NOAA Climate Data Record (CDR) of Solar Spectral Irradiance (SSI), NRLSSI Version 2.\r\n# NOAA National Centers for Environmental Information.\"\r\... | [
[
"numpy.array"
]
] |
yng87/Gasyori100knock | [
"cdf5e375e8f882420ceb54d170d9c015dcd50722"
] | [
"Question_01_10/005.py"
] | [
"import numpy as np\nimport cv2\nimport matplotlib.pyplot as plt\n\ndef RGB2HSV(img):\n img_cp = img.copy()\n img_cp = img_cp / 255.0\n\n Max = np.max(img_cp, axis=2)\n Min = np.min(img_cp, axis=2)\n arg_min = np.argmin(img_cp, axis=2)\n # BGR\n B = img_cp[:,:,0].copy()\n G = img_cp[:,:,1].c... | [
[
"numpy.abs",
"numpy.min",
"numpy.stack",
"numpy.max",
"numpy.argmin",
"numpy.shape",
"numpy.where",
"numpy.zeros"
]
] |
cnzeki/PSENet | [
"c7e0785404e12866171e9da678736abae9cdb8cb",
"c7e0785404e12866171e9da678736abae9cdb8cb",
"c7e0785404e12866171e9da678736abae9cdb8cb"
] | [
"DB/train.py",
"DB/backbones/resnet.py",
"DB/data/make_seg_detector_data.py"
] | [
"#!python3\nimport argparse\nimport time\n\nimport torch\nimport yaml\n\nfrom trainer import Trainer\n# tagged yaml objects\nfrom experiment import Structure, TrainSettings, ValidationSettings, Experiment\nfrom concern.log import Logger\nfrom data.data_loader import DataLoader\nfrom data.image_dataset import ImageD... | [
[
"torch.distributed.init_process_group",
"torch.cuda.set_device"
],
[
"torch.nn.Sequential",
"torch.nn.init.constant_",
"torch.nn.Conv2d",
"torch.nn.MaxPool2d",
"torch.nn.AvgPool2d",
"torch.nn.Linear",
"torch.nn.ReLU",
"torch.utils.model_zoo.load_url"
],
[
"numpy... |
HACKONDEX/faiss | [
"438b64cd8b04d94c6dbd21204af9197cd5cab2fd"
] | [
"faiss/python/__init__.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\n#@nolint\n\n# not linting this file because it imports * from swigfaiss, which\n# causes a ton of useless warnings.\n\nimport numpy ... | [
[
"numpy.dtype",
"numpy.frombuffer",
"numpy.array",
"numpy.zeros",
"numpy.empty"
]
] |
epcw/housing_equity | [
"074da171880fb445765662a98a816d13779f160f"
] | [
"jupyter-utilities/seattle_census_block_groups.py"
] | [
"import pandas as pd\nimport geopandas as gp\n\npath = '../shapefiles/WACensusBlocks2010/tl_2019_53_tabblock10.shp'\ngdf = gp.read_file(path)\n\ntracts_df = pd.read_csv('../sandbox-singlepage/data/seattle_census_tracts.csv', dtype={'TRACT': str})\n\nstate = '53' # WA = 53\ncounty = '033' # King = 033\n\nseattle_g... | [
[
"pandas.read_csv"
]
] |
gbrammer/eazy-py | [
"c56433beaa6cc24d72ed5a6ccf1db63781b50c58"
] | [
"eazy/photoz.py"
] | [
"import os\nimport time\nimport warnings\nimport numpy as np\n\nfrom collections import OrderedDict\n\ntry:\n from tqdm import tqdm\n HAS_TQDM = True\nexcept:\n HAS_TQDM = False\n \ntry:\n from grizli.utils import GTable as Table\nexcept:\n from astropy.table import Table\n\nimport astropy.io.fits... | [
[
"numpy.diag",
"numpy.dot",
"numpy.minimum",
"numpy.sqrt",
"numpy.linspace",
"numpy.random.multivariate_normal",
"numpy.squeeze",
"numpy.cumsum",
"numpy.max",
"numpy.zeros_like",
"numpy.argmin",
"numpy.mean",
"numpy.exp",
"numpy.where",
"numpy.trapz",
... |
raja21068/Research-on-data-mining-of-permission-induced-risk-for-android-IoT-devices | [
"522d3a0d0fde7dd2f51565e57e1bf30d8c7d9712"
] | [
"I-Random-Forest/irf/tests/test_irf_ensemble.py"
] | [
"from irf.ensemble import wrf, wrf_reg\nimport numpy as np\ndef test1():\n X = np.random.normal(size=(100,10))\n y = np.random.choice([0, 1], size=(100,))\n for tt in [wrf, wrf_reg]:\n rf = wrf(\n n_jobs=10,\n n_estimators=400,\n max_depth=None,\n bootstra... | [
[
"numpy.random.normal",
"numpy.random.choice"
]
] |
pragneshrana/Reinforcement-Learning | [
"6d891ff42437eec828e97cbbd2ad53fb112aad9e",
"6d891ff42437eec828e97cbbd2ad53fb112aad9e"
] | [
"Assignment_2/code/Q2/code/rlpa2/vishamC.py",
"Assignment_3/Q2_Cartpole_DQN/CODE_N_RESULT/without_target_reply_DQ.py"
] | [
"from gym import Env\nfrom gym.envs.registration import register\nfrom gym.utils import seeding\nfrom gym import spaces\nimport numpy as np\nfrom math import sqrt\n\n\nclass vishamC(Env):\n metadata = {\n 'render.modes': ['human', 'rgb_array'],\n 'video.frames_per_second': 50\n }\n\n def __in... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.clip"
],
[
"tensorflow.compat.v1.train.import_meta_graph",
"tensorflow.compat.v1.subtract",
"numpy.mean",
"tensorflow.compat.v1.train.Saver",
"tensorflow.compat.v1.summary.merge_all",
"tensorflow.compat.v1.train.AdamOptimizer",
... |
T-head-Semi/csi-nn2 | [
"bca6d703fa9d87d6f47c1182f0c3834f5d75b935",
"bca6d703fa9d87d6f47c1182f0c3834f5d75b935",
"bca6d703fa9d87d6f47c1182f0c3834f5d75b935"
] | [
"tests/python_ref/sin.py",
"tests/python_ref/and.py",
"tests/python_ref/softrelu.py"
] | [
"#!/usr/bin/python\n#-*- coding:utf-8 -*-\n\nimport sys\nimport struct\nimport numpy as np\nimport tensorflow as tf\n\ndef sin_f32():\n para = []\n # init the input data and parameters\n in_dim = int(np.random.randint(1, high=5, size=1))\n in_shape = []\n for i in range(0, in_dim):\n in_shap... | [
[
"numpy.random.uniform",
"tensorflow.sin",
"tensorflow.Session",
"numpy.random.randint"
],
[
"numpy.random.randint"
],
[
"numpy.random.normal",
"numpy.random.randint"
]
] |
Fytch/lehrfempp | [
"c804b3e350aa893180f1a02ce57a93b3d7686e91"
] | [
"examples/lecturedemos/convergencestudies/linquadfelshaped_plot.py"
] | [
"import sys\nimport os\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ninput_file = os.path.abspath(sys.argv[1])\noutput_folder = os.path.dirname(input_file)\n\ndata = np.genfromtxt(input_file, delimiter=',')\nmeshwidth = data[:,0]\nndofs_o1 = data[:,1]\nndofs_o2 = data[:,2]\nH1_err_o1 = data[:,3]\nH1_err_o... | [
[
"matplotlib.pyplot.legend",
"numpy.log",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.title",
"matplotlib.pyplot.loglog",
"numpy.genfromtxt",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylabel"
]
] |
milos-lazic/CMSIS_5 | [
"61b74b70bd961af9e2a8bb6bc1632c1014e7c42e"
] | [
"CMSIS/DSP/Testing/summaryBench.py"
] | [
"# Process the test results\n# Test status (like passed, or failed with error code)\n\nimport argparse\nimport re \nimport TestScripts.NewParser as parse\nimport TestScripts.CodeGen\nfrom collections import deque\nimport os.path\nimport numpy as np\nimport pandas as pd\nimport statsmodels.api as sm\nimport statsmod... | [
[
"pandas.read_csv",
"pandas.Series"
]
] |
svenharris/pandas | [
"ee808033bd5c546e7439a06d2ed37b57c9e66844"
] | [
"pandas/core/frame.py"
] | [
"\"\"\"\nDataFrame\n---------\nAn efficient 2D container for potentially mixed-type time series or other\nlabeled data series.\n\nSimilar to its R counterpart, data.frame, except providing automatic data\nalignment and a host of useful data manipulation methods having to do with the\nlabeling information\n\"\"\"\nf... | [
[
"pandas.util._validators.validate_bool_kwarg",
"pandas.core.common.dict_compat",
"pandas.compat.lzip",
"numpy.where",
"pandas.core.dtypes.common.is_named_tuple",
"pandas.compat.OrderedDict",
"pandas.core.common.standardize_mapping",
"pandas.core.dtypes.cast.maybe_convert_platform",... |
darrenjhsu/Boltzmann_Generator | [
"a0e7694b1451e1390139d4e1fcef55765e1e13e9"
] | [
"deep_boltzmann/models/double_well.py"
] | [
"import numpy as np\n\nclass DoubleWell(object):\n\n params_default = {'a4' : 1.0,\n 'a2' : 6.0,\n 'a1' : 1.0,\n 'k' : 1.0,\n 'dim' : 1}\n\n def __init__(self, params=None):\n # set parameters\n if params is None... | [
[
"matplotlib.pyplot.gca",
"numpy.zeros",
"numpy.sum",
"numpy.linspace"
]
] |
anthonytongUCB/modin | [
"e0dc8fb3cf8f7477a5a3c1a5d4cbdb5e2538eeb0"
] | [
"modin/backends/pandas/query_compiler.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport numpy as np\nimport pandas\n\nfrom pandas.compat import string_types\nfrom pandas.core.dtypes.cast import find_common_type\nfrom pandas.core.dtypes.common import (\n is_list_like,\n is_num... | [
[
"pandas.core.dtypes.common.is_list_like",
"pandas.core.dtypes.common.is_numeric_dtype",
"pandas.concat",
"pandas.Series",
"pandas.Float64Index",
"pandas.DataFrame",
"pandas.Index",
"pandas.core.index.ensure_index",
"numpy.dtype",
"pandas.core.dtypes.cast.find_common_type",
... |
ari-holtzman/transformers | [
"ab90353f1abfd15f8d21f99395658d060679a08c"
] | [
"examples/hans/hans_processors.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.\n# Copyright (c) 2018, 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... | [
[
"tensorflow.TensorShape"
]
] |
Imdrail/GPy | [
"6923d1718494dacb751469ab5bae49e826ef8c56"
] | [
"GPy/kern/_src/ODE_UYC.py"
] | [
"# Copyright (c) 2013, GPy authors (see AUTHORS.txt).\n# Licensed under the BSD 3-clause license (see LICENSE.txt)\n\nfrom .kern import Kern\nfrom ...core.parameterization import Param\nfrom ...core.parameterization.transformations import Logexp\nimport numpy as np\nfrom .independent_outputs import index_to_slices\... | [
[
"numpy.abs",
"numpy.sqrt",
"numpy.exp",
"numpy.zeros",
"numpy.sum"
]
] |
smbadiwe/NLP_with_CNN | [
"333838087913d73148ef0fe8e58825d14c423f0a"
] | [
"data_helpers.py"
] | [
"import numpy as np\nimport re\nfrom sklearn.datasets import fetch_20newsgroups\nfrom sklearn.datasets import load_files\n\n\ndef clean_str(string):\n \"\"\"\n Tokenization/string cleaning for all datasets except for SST.\n Original taken from https://github.com/yoonkim/CNN_sentence/blob/master/process_dat... | [
[
"numpy.asarray",
"numpy.arange",
"sklearn.datasets.load_files",
"numpy.dtype",
"numpy.array",
"sklearn.datasets.fetch_20newsgroups"
]
] |
Lan-lab/sc-GC | [
"f089c0667a0c3bb4148ef56d89909eb9614867d3"
] | [
"Scanpy/Basic_scanpy_analysis.py"
] | [
"import scvelo as scv\r\nimport numpy as np\r\nimport pandas as pd\r\nimport scanpy as sc\r\nimport matplotlib\r\nimport matplotlib.pyplot as plt \r\nimport seaborn as sns\r\nsc.settings.set_figure_params( frameon=True,color_map='Spectral_r') \r\nsc.settings.verbosity = 3 \r\nplt.rcParams[\"axes.grid\"] = False\... | [
[
"pandas.read_csv",
"numpy.sum",
"numpy.percentile"
]
] |
vyarem/DMP-projection | [
"3b2ca974e5393587bf2110a7c900b4877727e0af"
] | [
"dmp-vanilla/dmp_model.py"
] | [
"\"\"\"dmp_model.py\n\nThis file contains the dmp_model class, which contains the parameters\nand equations which characterize the model. \n\nThis class is not intended to be initialized by itself. Currently it\nis inherited by classes for solving/simulating the model.\n\"\"\"\nimport numpy as np\nimport scipy as s... | [
[
"numpy.array",
"numpy.minimum",
"numpy.maximum",
"numpy.meshgrid",
"numpy.linspace",
"scipy.interpolate.interp2d",
"numpy.exp",
"numpy.where",
"numpy.zeros"
]
] |
plugns/central-control-system | [
"166c7e2ed88f8b388606097302774859b5f75033"
] | [
"Modules/module_plot.py"
] | [
"import matplotlib.pyplot as plt\n\n\ndef plot_distance(xRobot,xObstacle,yRobot,yObstacle):\n x = (xRobot, xObstacle)\n y = (yRobot, yObstacle)\n ## plotting the points\n plt.plot(x, y, color='green', linestyle='dashed', linewidth=3, marker='o', markerfacecolor='blue', markersize=15)\n plt.plot(x, y)... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
ekarais/RLFM | [
"479679e39b4fdd230b5a67c2005dd2fb001e7169",
"479679e39b4fdd230b5a67c2005dd2fb001e7169"
] | [
"code/misc/test.py",
"code/report-specific/single_agent_random_interval_mcc/old_code/environments.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\nimport sys\nsys.path.append('.')\nimport pandas as pd\nimport numpy as np\nimport warnings\nimport agents\nfrom agents import Seller, Buyer\nfrom environments import MarketEnvironment\n\n\nimport info_settings\nimport matchers\n\n# Utility functions\ndef get_state(agent_id... | [
[
"numpy.load",
"pandas.DataFrame"
],
[
"pandas.Series",
"pandas.DataFrame"
]
] |
erpmaroc/Depexo-Prestashop-Like | [
"53d01dea6fd56c8ef21394f301df51cf699cd4d7"
] | [
"DepexoTools/BANE.py"
] | [
"#! /usr/bin/env python\n\n\"\"\"\nThis module contains all of the BANE specific code\nThe function filter_image should be imported from elsewhere and run as is.\n\"\"\"\nfrom __future__ import division\n# standard imports\nfrom astropy.io import fits\nimport copy\nimport logging\nimport multiprocessing\nimport mul... | [
[
"numpy.isfinite",
"numpy.squeeze",
"scipy.interpolate.RegularGridInterpolator",
"numpy.ceil",
"numpy.std",
"numpy.mean",
"numpy.ravel_multi_index",
"numpy.ravel",
"numpy.array"
]
] |
kun-woo-park/Mobile_Stereo_Net_RealSense | [
"993e21f35bf4d8b8e060849301d42784f77e53d3"
] | [
"utils/metrics.py"
] | [
"import torch\nimport torch.nn.functional as F\nfrom utils.experiment import make_nograd_func\nfrom torch.autograd import Variable\nfrom torch import Tensor\n\n\ndef check_shape_for_metric_computation(*vars):\n assert isinstance(vars, tuple)\n for var in vars:\n assert len(var.size()) == 3\n ass... | [
[
"torch.stack",
"torch.abs",
"torch.nn.functional.l1_loss",
"torch.tensor"
]
] |
Brechard/Robot-Simulator | [
"201256fdae6d6d1bd7221832ed4646afbe0779aa"
] | [
"old_ARS_2018/bot/kalman.py"
] | [
"\"\"\" Kalman Filter \"\"\"\nimport numpy as np\n\n__author__ = \"Olve Drageset, Andre Gramlich\"\n\n\ndef kalman_filter(mu_t_minus_1, sigma_t_minus_1, u_t, z_t):\n \"\"\"\n Given as input a previous believed pose, previous covariance matrix, control input, and sensor correction on pose,\n determi... | [
[
"numpy.identity",
"numpy.array",
"numpy.matmul",
"numpy.transpose"
]
] |
naitik-dodia/keras-preprocessing | [
"436ceff1eef05fb4cee87e171a199991e47ce335"
] | [
"tests/image/numpy_array_iterator_test.py"
] | [
"import numpy as np\nimport pytest\n\nfrom PIL import Image\n\nfrom keras_preprocessing.image import numpy_array_iterator\nfrom keras_preprocessing.image import utils\nfrom keras_preprocessing.image.image_data_generator import ImageDataGenerator\n\n\n@pytest.fixture(scope='module')\ndef all_test_images():\n img_... | [
[
"numpy.random.random",
"numpy.unique",
"numpy.arange",
"numpy.random.rand",
"numpy.array",
"numpy.vstack"
]
] |
Rita-ritally/Tacotron2-CN-TTS | [
"f67f060750fe12a014e35857d6ff6e279d41d68a"
] | [
"synthesizer/train.py"
] | [
"from synthesizer.utils.symbols import symbols\r\nfrom synthesizer.utils.text import sequence_to_text\r\nfrom synthesizer.hparams import hparams_debug_string\r\nfrom synthesizer.feeder import Feeder\r\nfrom synthesizer.models import create_model\r\nfrom synthesizer.utils import ValueWindow, plot\r\nfrom synthesizer... | [
[
"tensorflow.summary.scalar",
"tensorflow.Variable",
"tensorflow.ConfigProto",
"tensorflow.Session",
"tensorflow.train.Saver",
"tensorflow.Summary",
"tensorflow.norm",
"numpy.isnan",
"tensorflow.train.Coordinator",
"tensorflow.global_variables_initializer",
"tensorflow.s... |
noirmist/res_ae | [
"0ad7ba3e76709e725c552e1848cfbbfdf42e492b"
] | [
"resae/Bottleneck_en.py"
] | [
"# Copyright (C) 2018 Zhixian MA <zx@mazhixian.me>\n\"\"\"A class to contruct the bottleneck for encodeing\n\nupdates\n=======\n[2018-01-26]: Init, summary todo.\n[2018-01-28]: Add odd_flag\n\nnotes\n=====\n1. batch norm only at the end of a bottleneck?\n\nreferences\n==========\nhttp://blog.csdn.net/helei001/artic... | [
[
"tensorflow.summary.histogram",
"tensorflow.contrib.layers.avg_pool2d",
"tensorflow.contrib.layers.conv2d",
"tensorflow.name_scope",
"numpy.random.randint"
]
] |
YinpeiDai/NAUM | [
"d8328b8c10ab26b069bfa12176d7b39c260acafc"
] | [
"Non_DL_models/LR/run_model.py"
] | [
"'''\nbog-of-words + logistic regression\n'''\nimport numpy as np\nimport json, os, pickle\nimport tensorflow as tf\n\nfrom ..input_data import DatasetManager\nfrom .model import LogisticRgression\nfrom utils import F1_score\n\n\nclass Run_LR_BOW:\n def __init__(self, **kwargs):\n self.save_dir = kwargs['... | [
[
"tensorflow.train.Saver",
"tensorflow.global_variables_initializer",
"numpy.squeeze",
"tensorflow.ConfigProto"
]
] |
willbradshaw/killifish-igseq | [
"0a6fb7f77d8d52932994c28e79d2eccdf9ad2bde"
] | [
"analysis/input_files/igor/pygor/pygor/counters/coverage/coverage.py"
] | [
"# Author: Quentin Marcou\n#\n# This source code is distributed as part of the IGoR software.\n# IGoR (Inference and Generation of Repertoires) is a versatile software to\n# analyze and model immune receptors generation, selection, mutation and all\n# other processes.\n# Copyright (C) 2017 Quentin Marco... | [
[
"numpy.asarray",
"pandas.read_csv"
]
] |
tmannen/fast-depth | [
"8189b6c7832a6fd65977872d5bb7dd9437cbe098"
] | [
"dataloaders/nyu.py"
] | [
"import numpy as np\nimport dataloaders.transforms as transforms\nfrom dataloaders.dataloader import MyDataloader\n\niheight, iwidth = 480, 640 # raw image size\n\nclass NYUDataset(MyDataloader):\n def __init__(self, root, split, modality='rgb'):\n self.split = split\n super(NYUDataset, self).__ini... | [
[
"numpy.asfarray",
"numpy.random.uniform"
]
] |
jz462/large_scale_visual_relationship_understanding | [
"7363b997f4cabae39759ce70b7f52c7a1d8d8d41"
] | [
"lib/modeling/VGG16.py"
] | [
"import os\nimport numpy as np\nimport logging\nfrom collections import OrderedDict\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom core.config import cfg\nimport nn as mynn\nimport utils.net as net_utils\nimport torchvision.models as models\n\nlogger = logging.getLogger(__name__)\n\... | [
[
"torch.load"
]
] |
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