repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
cyrilcero/mmdetection | [
"e54a1f453a63e3c53623d4b3960d18af093a6d3d"
] | [
"mmdet/datasets/catchall_lpr.py"
] | [
"import mmcv\nimport os\nimport pickle\nimport numpy as np\nimport os.path as osp\nfrom .builder import DATASETS\nfrom .custom import CustomDataset\nfrom torch.utils.data import Dataset\nfrom mmdet.core import eval_map, eval_recalls\nfrom .pipelines import Compose\n\n@DATASETS.register_module()\nclass CatchAllDatas... | [
[
"numpy.array"
]
] |
CharlesRngrd/toucan-connectors | [
"906481c6f4bbead406efcd0879d1ac21a3071b6e"
] | [
"tests/google_big_query/test_google_big_query.py"
] | [
"import pandas\nimport pytest\nfrom google.cloud.bigquery import Client, ScalarQueryParameter\nfrom google.cloud.bigquery.job.query import QueryJob\nfrom google.cloud.bigquery.table import RowIterator\nfrom google.oauth2.service_account import Credentials\nfrom mock import patch\nfrom pandas.util.testing import ass... | [
[
"pandas.DataFrame"
]
] |
fhashim/time_series_test | [
"41a5659dea2f02a6d3ff587029f91a3cb86ec976"
] | [
"clean_data.py"
] | [
"import pandas as pd\n\ndf = pd.read_excel('Data/time_series.xlsx', header=None)\n\ndata = df.iloc[3:, ] \\\n .set_index(0).rename_axis('Date') \\\n .T \\\n .set_index(pd.MultiIndex.from_arrays(df.iloc[:2, 1:].values, names=df.iloc[:2, 0])) \\\n .T \\\n .stack(level=[0, 1]) \\\n .rename('Price') \... | [
[
"pandas.read_excel",
"pandas.MultiIndex.from_arrays"
]
] |
HamidDoost/computer-vision-techniques | [
"9f1a81862ad5212dde5fe87df7775ce2c1514711"
] | [
"text_detction_by_contour_MSER.py"
] | [
"'''\r\n===============================================================================\r\n-- Author: Hamid Doostmohammadi, Azadeh Nazemi\r\n-- Create date: 04/11/2020\r\n-- Description:\tThis code is for text detection using contours and \r\n Maximally Stable Extremal Regions (MSER)feature dete... | [
[
"numpy.median"
]
] |
fotonower/py-RFCN-priv | [
"3a81642206324530d2ceceaf9bd643aa7d6dc2b7"
] | [
"lib/rpn/assign_rois_layer.py"
] | [
"# --------------------------------------------------------\n# FPN\n# Copyright (c) 2017 BUPT-PRIV\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Soeaver Yang\n# --------------------------------------------------------\n\nimport caffe\nimport numpy as np\nimport yaml\nfrom fast_rcnn.confi... | [
[
"numpy.asarray"
]
] |
stephaniewang526/gcs-bq-streaming-python | [
"87a71271de552eeb937d8dda07a7c2fe1ef8726b"
] | [
"transfer_files/generate_data.py"
] | [
"import datetime\nimport json\nimport os\nimport random\nimport uuid\nimport lorem\nimport pandas as pd\nimport sys\n\n\ndef people_generator(length):\n for x in range(length):\n generated_name = generate_name() + ' ' + generate_name()\n generated_company = random_pick_from_list(COMPANIES)\n yield {\n ... | [
[
"pandas.read_html"
]
] |
cwlseu/eznlp | [
"9d1397d8e9630c099295712cbcffa495353a3268"
] | [
"scripts/text_classification.py"
] | [
"# -*- coding: utf-8 -*-\nimport os\nimport sys\nimport argparse\nimport datetime\nimport pdb\nimport logging\nimport pprint\nimport numpy\nimport torch\n\nfrom eznlp import auto_device\nfrom eznlp.token import TokenSequence\nfrom eznlp.dataset import Dataset\nfrom eznlp.config import ConfigDict\nfrom eznlp.model i... | [
[
"torch.cuda.set_device",
"torch.load",
"torch.randn",
"torch.utils.data.DataLoader",
"torch.save"
]
] |
Darylgolden/manim-videos | [
"ddc566b268e4db03933d5de36353ddfa24c36cbb"
] | [
"manim/scene/scene_file_writer.py"
] | [
"import numpy as np\nfrom pydub import AudioSegment\nimport shutil\nimport subprocess\nimport os\nimport _thread as thread\nfrom time import sleep\nimport datetime\nfrom PIL import Image\n\nfrom ..constants import FFMPEG_BIN, GIF_FILE_EXTENSION\nfrom ..config import file_writer_config\nfrom ..logger import logger\n... | [
[
"numpy.ceil"
]
] |
gle-bellier/sdia-python | [
"f4d2d7f53a2bfd07cf75b1a9b295a50675a3c9e0"
] | [
"tests/lab2/testf.py"
] | [
"from lab2.box_window import BoxWindow\n\nimport numpy as np\n\nbounds = np.array([[2.5, 2.5]])\n\nbox = BoxWindow(bounds)\n\nprint(box.dimension())\n"
] | [
[
"numpy.array"
]
] |
jmren168/botorch | [
"6c067185f56d3a244c4093393b8a97388fb1c0b3",
"6c067185f56d3a244c4093393b8a97388fb1c0b3"
] | [
"botorch/models/fidelity_kernels/exponential_decay_kernel.py",
"test/test_functions/test_hartmann6.py"
] | [
"#!/usr/bin/env python3\n\n# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\nfrom typing import Optional\n\nimport torch\nfrom gpytorch.constraints import Interval, Positive\nfrom gpytorch.kernels import Kernel\nfrom gpytorch.priors import Prior\nfrom torch import Tensor\n\n\nclass ExpDecayK... | [
[
"torch.as_tensor",
"torch.is_tensor",
"torch.zeros"
],
[
"torch.Size",
"torch.zeros",
"torch.tensor",
"torch.cuda.is_available",
"torch.device",
"torch.autograd.grad"
]
] |
shaform/DeepNetworks | [
"5064c8e80f519fe0291ff5dba9db93eae7fcd4ca"
] | [
"deep_networks/models/blocks.py"
] | [
"import functools\nimport logging\nimport operator\n\nimport tensorflow as tf\n\nfrom ..layers import conv2d_with_weight_norm\nfrom ..layers import conv2d_transpose_with_weight_norm\nfrom ..layers import dense_with_weight_norm\nfrom ..ops import conv2d_subpixel\nfrom ..ops import opt_activation\nfrom ..ops import s... | [
[
"tensorflow.nn.relu",
"tensorflow.layers.flatten",
"tensorflow.concat",
"tensorflow.reduce_mean",
"tensorflow.shape",
"tensorflow.zeros_initializer",
"tensorflow.reshape",
"tensorflow.contrib.layers.xavier_initializer",
"tensorflow.variable_scope"
]
] |
datpnguyen/QANet-CS224N | [
"a7e4ba3c17ba1ea1649d0383533ef44c78ceb65b"
] | [
"layers.py"
] | [
"\"\"\"Assortment of layers for use in models.py.\nModified from CS224n Default Project starter code by Chris Chute (chute@stanford.edu)\n\"\"\"\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom util import masked_softmax\n\n\nclass Embedding(nn.Module):\n \"\"\"Embedding layer used... | [
[
"torch.max",
"torch.cat",
"torch.zeros",
"torch.sin",
"torch.nn.Embedding.from_pretrained",
"torch.pow",
"torch.nn.Dropout",
"torch.nn.MultiheadAttention",
"torch.nn.functional.relu",
"torch.bmm",
"torch.arange",
"torch.cos",
"torch.empty",
"torch.nn.Linear"... |
juankaUAB/cas_kaggle | [
"7011cd9c984c33606e782354c3a9944876fec6a7"
] | [
"Code/DataMining.py"
] | [
"import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom sklearn.preprocessing import MinMaxScaler\nimport scipy\nimport seaborn as sns\n\ntitols = [\"Engine Capacity\",\"Cylinders\",\"Drive Type\",\"Tank Capacity\", \"Fuel Economy\",\"Fuel Type\",\"Horsepower\",\"Torque\",\"Transmission\",\"... | [
[
"pandas.read_csv",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"numpy.std",
"matplotlib.pyplot.clf",
"scipy.stats.gaussian_kde",
"scipy.stats.shapiro",
"matplotlib.pyplot.xlabel",
"numpy.array",
"matplotlib.pyplot.hist",
"... |
choonkiattay/EasyOCRGen | [
"d277aac4c2d0d53433d71c24095ca77b6dd5745a"
] | [
"generators/license_plate.py"
] | [
"import numpy as np\n\n\nclass LicensePlate(object):\n\n def __init__(self, number):\n # print(\"License Plate\")\n self.vlp_list = []\n self.dict = [class_name.rstrip('\\n') for class_name in open('generators/dictionary')]\n # For distribute the number of plate type\n self.a =... | [
[
"numpy.random.randint"
]
] |
Jean-Francois-Lafleche/kaolin | [
"a8055112566d43ca5d3b4d44041ea2303b314a1a"
] | [
"examples/SuperResolution/voxel-ShapeNet/eval.py"
] | [
"import argparse\nimport os\nimport torch\nimport sys\nfrom tqdm import tqdm\n\nfrom torch.utils.data import DataLoader\n\nfrom architectures import EncoderDecoder_32_128, EncoderDecoderForNLL_32_128\nfrom utils import up_sample\nimport kaolin as kal\n\nparser = argparse.ArgumentParser()\nparser.add_argument('--sha... | [
[
"torch.device",
"torch.no_grad",
"torch.utils.data.DataLoader"
]
] |
gargiani/ADP_LP | [
"a1bafd95c5edbaa94090b7a7895a702010620e53"
] | [
"ADP_LP/policies.py"
] | [
"import torch\n\ntype = torch.float64\n\ndef linear_policy(M, X, epsilon=None):\n\n U = torch.matmul(M, X)\n\n if epsilon is not None:\n normal = torch.distributions.normal.Normal(torch.zeros((U.shape[-2], U.shape[-1]), dtype=type),\\\n torch.ones((U.shape[-2], U.shape[-1]), dtype=type)... | [
[
"torch.matmul",
"torch.ones",
"torch.zeros"
]
] |
leah-kstra/yellowbrick | [
"3f2391870ca4ea5e143c972ecd93ee41441f0a95"
] | [
"tests/test_features/test_jointplot.py"
] | [
"# tests.test_features.test_jointplot\n# Test the JointPlotVisualizer\n#\n# Author: Prema Damodaran Roman\n# Created: Mon Apr 10 21:00:54 2017 -0400\n#\n# Copyright (C) 2017 District Data Labs\n# For license information, see LICENSE.txt\n#\n# ID: test_jointplot.py [9e008b0] pdamodaran@users.noreply.github.com $\... | [
[
"matplotlib.__version__.split",
"numpy.array",
"matplotlib.pyplot.figure"
]
] |
michael-k/spaCy | [
"fb73d4943a91d18cd36ded98994a932515f4bf05"
] | [
"spacy/util.py"
] | [
"# coding: utf8\nfrom __future__ import unicode_literals, print_function\n\nimport os\nimport importlib\nimport re\nfrom pathlib import Path\nimport random\nfrom collections import OrderedDict\nfrom thinc.neural._classes.model import Model\nfrom thinc.neural.ops import NumpyOps\nimport functools\nimport itertools\n... | [
[
"numpy.iinfo",
"numpy.random.seed"
]
] |
nitori/neuralintents | [
"7a63075fbdca24ec6a6e5281552f64325dd279ff"
] | [
"neuralintents/main.py"
] | [
"from abc import ABCMeta, abstractmethod\n\nimport random\nimport json\nimport pickle\nimport numpy as np\nimport os\n\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n\nimport nltk\nfrom nltk.stem import WordNetLemmatizer\n\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import Dense, Dropo... | [
[
"tensorflow.keras.models.load_model",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Dropout",
"numpy.array",
"tensorflow.keras.models.Sequential",
"tensorflow.keras.optimizers.SGD"
]
] |
Artemis-Skade/softlearning | [
"407e85f4d9731db7626042f5a76b5d9dbe64b601"
] | [
"examples/development/main.py"
] | [
"import os\nimport copy\nimport glob\nimport pickle\nimport sys\nimport json\n\nimport tensorflow as tf\nimport tree\nimport ray\nfrom ray import tune\n\nfrom softlearning.environments.utils import get_environment_from_params\nfrom softlearning import algorithms\nfrom softlearning import policies\nfrom softlearning... | [
[
"tensorflow.zeros_like",
"tensorflow.train.Checkpoint",
"tensorflow.config.experimental_run_functions_eagerly"
]
] |
aman7895/DeepLearningResearch | [
"de7bc777f8253e164e2658e816a9c6a45f3e93e7"
] | [
"CNN_AuthorshipID/data_helpersTL.py"
] | [
"\n# coding: utf-8\n\n# In[2]:\n\nimport numpy as np\nimport pandas as pd\n\n\n# In[2]:\n\n# This function is called from Main and expects train and test values for x and y\ndef load_ag_data(authors = None, docID = None): \n \n import dataTL\n train = dataTL.getCharAuthorData(authors, docID) #Pass it to da... | [
[
"numpy.matrix",
"sklearn.model_selection.train_test_split",
"numpy.random.shuffle",
"numpy.array",
"numpy.zeros"
]
] |
ml-evs/megnet | [
"5acb5e78e2eb718e06d69d67ed22d2a14be7faf9",
"5acb5e78e2eb718e06d69d67ed22d2a14be7faf9"
] | [
"megnet/utils/molecule.py",
"megnet/layers/readout/set2set.py"
] | [
"from pymatgen import Molecule\nimport numpy as np\nfrom pymatgen.io.babel import BabelMolAdaptor\nimport logging\ntry:\n import pybel as pb\nexcept:\n logging.warning(\"Openbabel is needed for molecule models, try 'conda install -c openbabel openbabel' to install it\")\n pb = None\n\n\nclass MEGNetMolecul... | [
[
"numpy.bitwise_and",
"numpy.where"
],
[
"tensorflow.multiply",
"tensorflow.transpose",
"tensorflow.shape",
"tensorflow.reshape",
"tensorflow.expand_dims",
"tensorflow.exp",
"tensorflow.unique_with_counts"
]
] |
hirokuramoto/Optimizer | [
"6aeaff59c29798caa6cf8e398a3be205eba5dea7"
] | [
"RealCodedGA/leave_one_out.py"
] | [
"# ガウスパラメータ，正則化パラメータの決定のためにCV値を求める\n\nimport numpy as np\nfrom .call_fortran import *\n\nclass LeaveOneOut(object):\n def __init__(self, beta1, lamda1, beta2, lamda2, design_data, object_data):\n \"\"\"ガウスカーネルを使った予測値ベクトルを返す\n Args :\n beta (float) : ガウスパラメータ β\n penalty (float... | [
[
"numpy.linalg.inv",
"numpy.dot",
"numpy.identity"
]
] |
zhuangzhuangliu2345/Transformer-TTS | [
"82cf2bc3ab454cd4eff8f312dcd824626beb834f"
] | [
"preprocess.py"
] | [
"import hyperparams as hp\nimport pandas as pd\nfrom torch.utils.data import Dataset, DataLoader\nimport os\nimport librosa\nimport numpy as np\nfrom text import text_to_sequence\nimport collections\nfrom scipy import signal\nimport torch as t\nimport math\n\n\nclass LJDatasets(Dataset):\n \"\"\"LJSpeech dataset... | [
[
"torch.LongTensor",
"pandas.read_csv",
"numpy.pad",
"numpy.arange",
"torch.FloatTensor",
"numpy.load",
"numpy.zeros"
]
] |
MrMavs/LiuCipher | [
"ce9126793dd0d287c31853e20aca3ec8278003e9"
] | [
"src/liuproto/endpoint.py"
] | [
"#!/usr/bin/env python\n\nr\"\"\"Liu protocol endpoint implementation.\nThis module implements a Liu protocol endpoint, including signal\ngeneration. In particular, it implements the exchange\n\n :math:`M_{k+1} = Z_{k+1} + \\alpha M_k` ,\n \nwhere :math:`{M_k}` are the messages sent across the wire, :math:`\... | [
[
"numpy.sqrt",
"numpy.fft.fft",
"numpy.fft.ifft",
"numpy.array",
"numpy.random.RandomState"
]
] |
zhenglab/multi-action-video | [
"d2a93ca7e44600b610404a16bd301217006781ec"
] | [
"lib/datasets/decoder.py"
] | [
"# Code adapted from:\n# https://github.com/facebookresearch/SlowFast\n\nimport math\nimport numpy as np\nimport random\nimport torch\nimport torchvision.io as io\n\nimport lib.utils.logging as logging\nlogger = logging.get_logger(__name__)\n\ndef temporal_sampling(frames, start_idx, end_idx, num_samples):\n \"\... | [
[
"torch.Size",
"torch.linspace",
"numpy.stack",
"numpy.frombuffer",
"torch.clamp",
"torch.index_select"
]
] |
Sandeep-krish/Project_Leanardo | [
"6955e41dfd5c6cc39fd33ac443afbee1e76dbde0"
] | [
"facets_overview/python/base_generic_feature_statistics_generator.py"
] | [
"# Copyright 2017 Google Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appl... | [
[
"numpy.issubdtype",
"numpy.isneginf",
"numpy.max",
"numpy.mean",
"numpy.histogram",
"numpy.asscalar",
"numpy.unique",
"numpy.std",
"numpy.count_nonzero",
"numpy.min",
"numpy.isnan",
"numpy.median",
"pandas.Timedelta",
"numpy.array",
"numpy.isfinite",
... |
dulaku/AdversarialServer | [
"49772099f7ba939f6ee08af6fb946e4ea85bc732"
] | [
"AdversarialServer.py"
] | [
"import os, json, io, traceback\nimport base64\n\nimport torch\nimport torchvision\nfrom PIL import Image\n\npage = '''\n<form action=\"/\" method=\"post\" enctype=\"multipart/form-data\">\n <input type=\"file\" name=\"unmodified.png\" accept=\"image/png\"></br>\n <input type=\"submit\" value=\"Submit\"><!--v=vSt... | [
[
"torch.nn.Softmax",
"torch.max",
"torch.nn.functional.nll_loss",
"torch.no_grad",
"torch.clamp",
"torch.as_tensor"
]
] |
skamano/occupancy_networks | [
"ae400b8430584e4af41bfb9bfcff699f54b695b7"
] | [
"tsne.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom tsnecuda import TSNE\nimport torch\n# import torch.distributions as dist\nimport os\nimport shutil\nimport argparse\nimport copy\nfrom tqdm import tqdm\nimport time\nfrom collections import defaultdict\nimport pandas as pd\nfrom im2im.autoencoder import VAE... | [
[
"matplotlib.pyplot.scatter",
"torch.load",
"torch.utils.data.DataLoader",
"pandas.DataFrame",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device",
"numpy.array"
]
] |
Popcorn-sugar/Deep_v2 | [
"23c25f74e36016658558e690890499bc7fd2aeb2"
] | [
"nets/pix2pix_test.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required... | [
[
"tensorflow.ones",
"tensorflow.test.main",
"tensorflow.compat.v1.global_variables_initializer"
]
] |
PtrMan/20NAR1 | [
"e8e1a62c29c76bb6122358d84c82b29eb1cf330c"
] | [
"ExpRobot1.py"
] | [
"pathTo20Nar = \"/home/r0b3/dev/rust/20mlish6\"\n# load module from path for python 3.5+\n# from https://stackoverflow.com/a/67692/388614\nimport importlib.util\nspec = importlib.util.spec_from_file_location(\"module.Binding\", pathTo20Nar+\"/Binding.py\")\nBinding = importlib.util.module_from_spec(spec)\nspec.load... | [
[
"numpy.array",
"numpy.abs"
]
] |
floydhub/dockerfiles | [
"dc896f04f97912e6fd0c5f568457591dfad572e8"
] | [
"dl/tensorflow/tests/2.0/tf_keras_mnist.py"
] | [
"# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT... | [
[
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Flatten",
"tensorflow.test.gpu_device_name",
"tensorflow.keras.layers.Dropout"
]
] |
mertsayar8/detectron2 | [
"6b3ddd5959b5ff81a982ffc9f26ede4c61bb4955"
] | [
"convert_prima_to_coco.py"
] | [
"\"\"\"\r\nThe script is updated from:\r\nhttps://github.com/Layout-Parser/layout-model-training/blob/master/tools/convert_prima_to_coco.py\r\n\"\"\"\r\n\r\nimport os, re, json\r\nimport imagesize\r\nfrom glob import glob\r\nfrom bs4 import BeautifulSoup\r\nimport numpy as np\r\nfrom PIL import Image\r\nimport argp... | [
[
"numpy.roll"
]
] |
i-supermario/Cifar100_CL | [
"6c22151ea2c4c3014a569112fdf8a549331b27c4"
] | [
"train.py"
] | [
"import numpy as np\nimport torch\nfrom torch.utils.data import ConcatDataset\nimport tqdm\nimport copy\nimport utils\nfrom models.cl.continual_learner import ContinualLearner\n\n\ndef train(model, train_loader, iters, loss_cbs=list(), eval_cbs=list(), save_every=None, m_dir=\"./store/models\",\n args=None... | [
[
"torch.max",
"torch.tensor",
"numpy.ceil",
"torch.utils.data.ConcatDataset",
"torch.no_grad"
]
] |
aws-samples/easy-amazon-sagemaker-deployments | [
"54e50970c53895d3e18ebef3a05357ac3523d072"
] | [
"notebooks/modelscript_sklearn.py"
] | [
"import sklearn\nfrom joblib import load\nimport numpy as np\nimport os\n\n#Return loaded model\ndef load_model(modelpath):\n print(modelpath)\n clf = load(os.path.join(modelpath,'model.joblib'))\n print(\"loaded\")\n return clf\n\n# return prediction based on loaded model (from the step above) and an i... | [
[
"numpy.frombuffer"
]
] |
kraalfar/DEDPUL | [
"f7c3824d694eb7a5879171cf1a71a73a9d15f00e"
] | [
"TIcE.py"
] | [
"\"\"\"\nThe script for python 2 was retrieved from the original paper \"Estimating the Class Prior in Positive and Unlabeled Data\nthrough Decision Tree Induction\" https://dtai.cs.kuleuven.be/software/tice, and was adapted for python3\n\"\"\"\n\nimport numpy as np\nimport math\nfrom bitarray import bitarray\nimpo... | [
[
"numpy.linspace",
"numpy.genfromtxt"
]
] |
ViditGoel/BloodBank-Managment-System-BMS | [
"e878c58a1d853516b29fe6647c18dc4f100a857b"
] | [
"Backend/Predection_Units.py"
] | [
"#importing lib\nimport pandas as pd\n\n#Reading csv data\nblood_df=pd.read_csv(\"blood.csv\")\n#blood_df\n\n#Blood units per person inserted using random\nimport random\nfrom random import randint\nunits=[]\nfor i in range(blood_df.shape[0]):\n value = randint(1, 10)\n units.append(value)\nblood_df[\"units\"... | [
[
"pandas.read_csv",
"sklearn.linear_model.LinearRegression",
"pandas.DataFrame"
]
] |
AlgTUDelft/wind-farm-env | [
"4019c54069260858304a745f48f3f4b3334ea3df"
] | [
"code/agent/naive_agent.py"
] | [
"from wind_farm_gym import WindFarmEnv\nfrom .agent import Agent\nimport numpy as np\n\n\nclass NaiveAgent(Agent):\n\n def __init__(self, name, env: WindFarmEnv):\n super().__init__(name, 'Naive', env)\n self._stored_representation = env.action_representation\n env.action_representation = 'w... | [
[
"numpy.zeros"
]
] |
sharpe5/xgboost | [
"816b789bf06864b37d3b2eacd4ce5d75fa3865cf"
] | [
"python-package/xgboost/data.py"
] | [
"# pylint: disable=too-many-arguments, too-many-branches\n# pylint: disable=too-many-return-statements, import-error\n'''Data dispatching for DMatrix.'''\nimport ctypes\nimport json\nimport warnings\nimport os\nfrom typing import Any\n\nimport numpy as np\n\nfrom .core import c_array, _LIB, _check_call, c_str, _arr... | [
[
"pandas.api.types.is_categorical_dtype",
"numpy.ascontiguousarray",
"numpy.isnan",
"scipy.sparse.csr_matrix",
"numpy.vectorize",
"pandas.api.types.is_sparse",
"numpy.array"
]
] |
crstn/PopNet | [
"7501c0af1e36b00347ed4f8682ac2ab235e901b8"
] | [
"tests/test.py"
] | [
"import numpy as np\nimport numpy as np\nimport os\nimport sys\nfrom osgeo import gdal\nimport osr\n\nbase_dir = os.path.dirname(os.path.abspath(__file__))\nsys.path.append(base_dir)\ndata_dir = os.path.relpath('..\\\\data', base_dir)\nconfig_dir = os.path.relpath('..\\\\configs', base_dir)\n\n\n# Loads the geotiff... | [
[
"numpy.delete"
]
] |
scmarquez/Hause-Price-Kaggle-Competition | [
"5fe32fed87a7bf2c6e5f41761ea1c4dd00761f21"
] | [
"Prueba1.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Fri Dec 29 16:40:53 2017\r\n\r\n@author: Sergio\r\n\"\"\"\r\n\r\n#Analisis de variables\r\nimport pandas as pd\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport seaborn as sns\r\nfrom sklearn import ensemble, tree, linear_model\r\nfrom sklearn.model_... | [
[
"numpy.log",
"pandas.read_csv",
"pandas.concat",
"sklearn.model_selection.cross_val_score",
"sklearn.metrics.r2_score",
"sklearn.utils.shuffle",
"sklearn.linear_model.ElasticNetCV",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"sklearn.ensemble.GradientBo... |
ti-ginkgo/classifier-template | [
"eb838dbce0288334a4307ab7398a6d96d8287847"
] | [
"{{cookiecutter.package_name}}/src/exp_000/ishtos_datasets.py"
] | [
"import cv2\nimport numpy as np\nimport torch\nfrom ishtos_transforms import get_transforms\nfrom torch.utils.data import Dataset\nfrom tqdm import tqdm\n\n\nclass MyDataset(Dataset):\n def __init__(self, config, df, transforms=None, phase=\"train\"):\n self.config = config\n self.image_paths = df[... | [
[
"numpy.repeat",
"torch.tensor"
]
] |
MapaRobo/tracking_pid | [
"8a179dfde004612e4de19589a769f9d445bf0427"
] | [
"test/test_tracking_pid_system.py"
] | [
"#!/usr/bin/env python\nPKG='tracking_pid'\n\nfrom geometry_msgs.msg import PoseStamped\nfrom nav_msgs.msg import Path\nfrom std_msgs.msg import Bool\nfrom tracking_pid.msg import traj_point, PidDebug\nimport math\nimport numpy as np\nimport rospy\nimport sys\nimport tf\nimport unittest\n\n\nclass TestTrackingPID(u... | [
[
"numpy.linalg.norm"
]
] |
Karol-G/block.bootstrap.pytorch | [
"6a39ed2c6fc931a9df39d2fdd8e4f2aa3168919e"
] | [
"block/models/networks/mlp.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numbers\n\nclass MLP(nn.Module):\n \n def __init__(self,\n input_dim,\n dimensions,\n activation='relu',\n dropout=0.):\n super(MLP, self).__init__()\n self.input_dim = input... | [
[
"torch.nn.Linear",
"torch.nn.functional.dropout"
]
] |
JISock/models | [
"cab74a2c2b5e0cf385c37ebd3631153f76c77035"
] | [
"object_detection/Juils_codes/TFRecord_generation/create_synthetic_depth_tfrecord_cups.py"
] | [
"import hashlib\nimport io\nimport logging\nimport os\nimport PIL.Image\nimport tensorflow as tf\nimport pickle\nimport matplotlib.pyplot as plt\nimport matplotlib.patches as patches\nimport inout\nimport sys\nsys.path.append(\"../..\")\nfrom object_detection.utils import dataset_util\nfrom object_detection.utils i... | [
[
"scipy.misc.imsave",
"tensorflow.gfile.GFile",
"tensorflow.python_io.TFRecordWriter",
"scipy.misc.imread",
"numpy.zeros"
]
] |
nebw/rendergan_pytorch | [
"249c5ab0cd3d7098418b0df3ffc254c2fe9e1c2c"
] | [
"rendergan/util.py"
] | [
"import numpy as np\nimport torch\n\n\ndef normalize_labels(z, param_gen):\n device = z.device\n batch_size = z.shape[0]\n\n l = param_gen(z)\n \n #z_rot = (l[:, 0] * np.pi)[:, None]\n z_rot = (torch.rand((batch_size, 1), dtype=torch.float32, device=device) * 2 - 1) * np.pi\n y_rot = (l[:, 1] *... | [
[
"numpy.random.binomial",
"torch.rand",
"torch.cos",
"torch.sin"
]
] |
microsoft/VoxHRNet | [
"be72d6448ff4b45c531163a6a6b46ff1ff5e60fd"
] | [
"unetpp.py"
] | [
"# --------------------------------------------------------------------------\n# Source: https://gist.github.com/jinglescode/9d9ed6027e62e389e3165b59209e838e\n# --------------------------------------------------------------------------\n\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nc... | [
[
"torch.nn.Sequential",
"torch.cat",
"torch.nn.MaxPool3d",
"torch.nn.Conv3d",
"torch.nn.Upsample",
"torch.nn.functional.interpolate",
"torch.nn.ReLU",
"torch.nn.BatchNorm3d"
]
] |
amagge/flair | [
"4cdc41da77297531f8a9ebe6f47ae9ac8a1eb620"
] | [
"flair/models/language_model.py"
] | [
"from pathlib import Path\n\nimport torch.nn as nn\nimport torch\nimport math\nfrom typing import Union, Tuple\nfrom typing import List\n\nfrom torch.optim import Optimizer\n\nimport flair\nfrom flair.data import Dictionary\n\n\nclass LanguageModel(nn.Module):\n \"\"\"Container module with an encoder, a recurren... | [
[
"torch.nn.CrossEntropyLoss",
"torch.nn.Dropout",
"torch.LongTensor",
"torch.max",
"torch.nn.LSTM",
"torch.cat",
"torch.multinomial",
"torch.tensor",
"torch.nn.Linear",
"torch.no_grad"
]
] |
usyd-fsalab/NeuralNetworkRandomness | [
"16e029e11768d6605d29a0592a5bc80e85112e41"
] | [
"src/training_script/resnet_celeba.py"
] | [
"import argparse\nparser = argparse.ArgumentParser()\nparser.add_argument('--epochs', type=int, default=10)\nparser.add_argument('--lr', type=float, default=1e-3)\nparser.add_argument('--ckpt_folder', type=str, required=True)\nparser.add_argument('--deterministic_algo', action='store_true')\nparser.add_argument('--... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.keras.metrics.BinaryAccuracy",
"tensorflow.keras.callbacks.LambdaCallback",
"tensorflow.keras.mixed_precision.set_global_policy",
"tensorflow.config.experimental.set_memory_growth",
"tensorflow.keras.mixed_precision.Policy",
"tensorflow.tpu.e... |
moble/spherical | [
"089cc3f5afca6d8d4bcad01b36d208dbafc234f0"
] | [
"tests/test_wigner_rotate.py"
] | [
"#!/usr/bin/env python\n\n# Copyright (c) 2021, Michael Boyle\n# See LICENSE file for details: <https://github.com/moble/spherical/blob/master/LICENSE>\n\nimport math\nimport numpy as np\nimport quaternionic\nimport spherical as sf\nimport pytest\n\nslow = pytest.mark.slow\n\n\n# @slow ### Note that the following ... | [
[
"numpy.abs",
"numpy.allclose",
"numpy.random.seed"
]
] |
dalexander/jax | [
"983f6fe8e5aa6c18d09b0f2b9a32487b60183fac"
] | [
"jax/random.py"
] | [
"# Copyright 2018 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.right_shift",
"numpy.log",
"numpy.sqrt",
"numpy.uint32",
"numpy.ndim",
"numpy.binary_repr",
"numpy.delete",
"numpy.shape",
"numpy.uint64",
"numpy.prod",
"numpy.float32",
"numpy.array"
]
] |
Daulbaev/adversarial-library | [
"6f979a511ad78908374cd55855a9e2c5a874be7d",
"6f979a511ad78908374cd55855a9e2c5a874be7d"
] | [
"adv_lib/utils/color_conversions.py",
"adv_lib/utils/visdom_logger.py"
] | [
"import torch\nfrom torch import Tensor\n\n_ycbcr_conversions = {\n 'rec_601': (0.299, 0.587, 0.114),\n 'rec_709': (0.2126, 0.7152, 0.0722),\n 'rec_2020': (0.2627, 0.678, 0.0593),\n 'smpte_240m': (0.212, 0.701, 0.087),\n}\n\n\ndef rgb_to_ycbcr(input: Tensor, standard: str = 'rec_2020'):\n kr, kg, kb ... | [
[
"torch.einsum",
"torch.cat",
"torch.where",
"torch.tensor"
],
[
"torch.tensor",
"torch.as_tensor",
"torch.cat",
"torch.save"
]
] |
hwangdeyu/onnxruntime | [
"9d748afff19e9604a00632d66b97159b917dabb2"
] | [
"onnxruntime/python/tools/quantization/calibrate.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n# -------------------------------------------------------------------------\n# Copyright (c) Microsoft, Intel Corporation. All rights reserved.\n# Licensed under the MIT License. See License.txt in the project root for\n# license information.\n# -----------------------------... | [
[
"numpy.empty",
"numpy.float32"
]
] |
souterjk/dagster | [
"8b744a4959bb04ff9587cfee82a796404fcbc89e"
] | [
"examples/hacker_news_assets/hacker_news_assets/assets/items.py"
] | [
"# pylint: disable=redefined-outer-name\n\nfrom typing import Tuple\n\nfrom dagster import Output, asset\nfrom hacker_news_assets.partitions import hourly_partitions\nfrom pandas import DataFrame\nfrom pyspark.sql import DataFrame as SparkDF\nfrom pyspark.sql.types import ArrayType, DoubleType, LongType, StringType... | [
[
"pandas.DataFrame"
]
] |
giantoak/dedupe | [
"d276da675e319d5cc6e7cafd4963deebde0d485d"
] | [
"tests/test_haversine.py"
] | [
"import unittest\nfrom dedupe.distance.haversine import compareLatLong\nimport numpy\n\nclass TestHaversine(unittest.TestCase):\n def setUp(self):\n self.sfo = (37.619105, -122.375236)\n self.ord = (41.981649, -87.906670)\n\n def test_haversine_equal(self):\n km_dist_val = compareLatLong(... | [
[
"numpy.isnan"
]
] |
iganichev/scratch | [
"e570f77abb855a21ec4ef893b5cfc97d331d0ce5"
] | [
"act/act_cell_orig.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport tensorflow as tf\nfrom tensorflow.contrib.rnn import RNNCell\nfrom tensorflow.contrib.rnn import static_rnn\nfrom tensorflow.python.ops import variable_scope as vs\n\n\nclass ACTCell(RNN... | [
[
"tensorflow.concat",
"tensorflow.zeros",
"tensorflow.stack",
"tensorflow.cast",
"tensorflow.equal",
"tensorflow.where",
"tensorflow.while_loop",
"tensorflow.layers.dense",
"tensorflow.logical_not",
"tensorflow.fill",
"tensorflow.less",
"tensorflow.zeros_like",
"... |
tuantran1810/lips-image-generation | [
"c7ff84fbd44f0b8aa318c6277da4ebe65039d181"
] | [
"networks/audio_encoder.py"
] | [
"import sys, os\nsys.path.append(os.path.dirname(__file__))\nimport torch\nfrom torch import nn\nimport numpy as np\nfrom nets import Conv2dBlock\n\nclass AudioEncoderGen(nn.Module):\n def __init__(self, in_channels = 1, out_channels = 256, init_inner_channels = 32, nlayers = 4):\n super(AudioEncoderGen, ... | [
[
"torch.nn.Sequential",
"torch.unsqueeze",
"numpy.transpose",
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.flatten",
"torch.stack"
]
] |
nivedvenugopalan/character-based-text-generation | [
"06dbea2c71b712bd7340689a9ccb3f79d4be156c"
] | [
"src/train.py"
] | [
"# this is a rnn model for character based generation\nimport os\nimport keras\nimport numpy as np\nimport tensorflow as tf\nfrom keras.preprocessing import sequence\n\n# build the model\n\n\ndef build_model(vocab_size, embedding_dim, rnn_units, batch_size):\n model = tf.keras.Sequential([\n tf.keras.laye... | [
[
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.layers.Embedding",
"tensorflow.keras.layers.Dense",
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.keras.losses.sparse_categorical_crossentropy",
"tensorflow.keras.layers.LSTM",
"numpy.array"
]
] |
Maplenormandy/staircase-explorer | [
"43380e919dd3e7cb4a80d6b5ad4df967243cd03d"
] | [
"chm_forced/chm.py"
] | [
"\"\"\"\nDedalus script for Balanced Hasegawa-Wakatani equations\n\nFrom Majda PoP 2018\n\nThis script can be ran serially or in parallel, and uses the built-in analysis\nframework to save data snapshots in HDF5 files. The `merge_procs` command can\nbe used to merge distributed analysis sets from parallel runs, an... | [
[
"numpy.sqrt",
"numpy.meshgrid",
"numpy.exp",
"numpy.sum",
"numpy.random.default_rng"
]
] |
FynnFreyer/space-balls | [
"e8360b05911fd62b03932b6d77d2eeee0c26ee71"
] | [
"src/controller.py"
] | [
"from model.body import *\n\nimport numpy as np\nfrom pyglet.window import key\n\n\nclass Player(Body):\n def __init__(self, speed=500, rot_speed=180, view=None, *args, **kwargs):\n super(Player, self).__init__(*args, **kwargs)\n self.speed = speed\n self.rot_speed = rot_speed\n self.... | [
[
"numpy.deg2rad",
"numpy.cos",
"numpy.sin"
]
] |
stillmatic/papermill | [
"1da6937f5ceefb16ed86917507622a60a646a65c"
] | [
"papermill/tests/test_api.py"
] | [
"import unittest\n\ntry:\n from unittest.mock import patch\nexcept ImportError:\n from mock import patch\n\nimport pandas as pd\nfrom pandas.util.testing import assert_frame_equal\n\nfrom nbformat.v4 import new_notebook, new_code_cell, new_markdown_cell, new_output\n\nfrom .. import display, read_notebook, re... | [
[
"pandas.util.testing.assert_frame_equal",
"pandas.DataFrame"
]
] |
FFTYYY/Poem | [
"8836a32d21997afef5381c6ff8fd71c8adeebb75"
] | [
"model/lstm.py"
] | [
"import torch as tc\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport pdb\nimport fitlog\n\nfitlog.commit(__file__)\n\nclass LSTM(nn.Module):\n\tdef __init__(self , input_size , hidden_size , num_layers , bidrect , dropout = 0.0 , pos_len = True , output_mode = None):\n\t\t'''\n\t\t\toutput_mode: \n\t... | [
[
"torch.cat",
"torch.nn.LSTM",
"torch.nn.utils.rnn.pack_padded_sequence",
"torch.nn.utils.rnn.pad_packed_sequence",
"torch.sort",
"torch.arange"
]
] |
ArchitectMCP/CartoonGan-tensorflow | [
"e30ce2f91475046a40f53aa289a5f771d0d64a5f"
] | [
"folder_with_ckpt.py"
] | [
"\"\"\"\nMinimum inference code\n\"\"\"\nimport os\nimport numpy as np\nfrom imageio import imwrite\nfrom PIL import Image\nimport tensorflow as tf\nfrom generator import Generator\nfrom logger import get_logger\n\n\n# NOTE: TF warnings are too noisy without this\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\ntf.get_lo... | [
[
"numpy.expand_dims",
"tensorflow.train.latest_checkpoint",
"tensorflow.get_logger"
]
] |
xplip/adapter-transformers | [
"571c69e507ee13c1f46113540a8540874e63805d"
] | [
"src/transformers/adapters/models/distilbert.py"
] | [
"from typing import Union\n\nimport torch\nfrom torch import nn\n\nfrom ..composition import AdapterCompositionBlock, parse_composition\nfrom ..model_mixin import InvertibleAdaptersMixin, ModelAdaptersMixin\nfrom .bert import BertEncoderAdaptersMixin, BertModelHeadsMixin, BertOutputAdaptersMixin, BertSelfOutputAdap... | [
[
"torch.zeros"
]
] |
junyaoshi/fitvid | [
"a1c56cd31a6f58b22aec8c2b92e8d4a65f608362"
] | [
"nvae.py"
] | [
"# Copyright 2020 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.array"
]
] |
heekhero/MTOR | [
"e0dbc22bb7f4bc864ed7a7d43ffeb22671d8fd40"
] | [
"lib/model/faster_rcnn/resnet_student.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nfrom model.utils.config import cfg\nfrom model.faster_rcnn.faster_rcnn_student import _fasterRCNN\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Var... | [
[
"torch.nn.Sequential",
"torch.load",
"torch.nn.init.constant_",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.AvgPool2d",
"torch.nn.Module.train",
"torch.nn.init.normal_",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.utils.model_zoo.load_u... |
factoryofthesun/MLisNE | [
"0d40564bf505dfbc0c57e98f891be53e6b44f37e"
] | [
"IVaps/aps.py"
] | [
"\"\"\"APS estimation functions\"\"\"\nfrom pathlib import Path\nfrom typing import Tuple, Dict, Set, Union, Sequence, Optional\nimport onnxruntime as rt\nimport warnings\nimport numpy as np\nimport pandas as pd\nimport os\nimport gc\nfrom numba import jit, njit\nfrom numba.core.errors import NumbaDeprecationWarnin... | [
[
"numpy.expand_dims",
"numpy.multiply",
"numpy.random.seed",
"numpy.isnan",
"numpy.empty_like",
"numpy.repeat",
"numpy.cumsum",
"numpy.stack",
"pandas.DataFrame",
"numpy.concatenate",
"numpy.random.normal",
"numpy.vectorize",
"numpy.append",
"numpy.delete",
... |
chico2121/bpe | [
"f05e273bca542f1f1e0bfcb97bfce59b1f837e37"
] | [
"bpe/common_bpe.py"
] | [
"import itertools\nimport os\n\nimport more_itertools\nimport torch\nimport numpy as np\n\nfrom bpe.functional import utils\nfrom collections import namedtuple\nimport multiprocessing\n\n\nBodyPart = namedtuple('BodyPart', [\n 'right_arm',\n 'left_arm',\n 'right_leg',\n 'left_leg',\n 'torso', # 6 jo... | [
[
"numpy.asarray",
"numpy.arange",
"torch.cuda.is_available"
]
] |
kgdunn/multivariate-data-analysis-python | [
"1750c155fc97ad1a35b896564cbf7da681d407d1"
] | [
"tests/basics.py"
] | [
"import numpy as np\r\n\r\n\r\ndef compare_entries(A, B, sig_figs):\r\n \"\"\"\r\n Compares that every entry in array `A` and `B` match to a certain number\r\n of *significant figures*. Note that this is NOT THE SAME AS the number of\r\n decimal places (from zero); it is actually a more useful check th... | [
[
"numpy.sign",
"numpy.array",
"numpy.abs",
"numpy.prod"
]
] |
sassafras13/gnn-dna-sim | [
"458ad35aa64771955f3ef78f1351ca37bcb529ac",
"458ad35aa64771955f3ef78f1351ca37bcb529ac"
] | [
"src/learning_to_simulate/demo_data.py",
"src/learning_to_simulate/save_data.py"
] | [
"# Import modules and this file should be outside learning_to_simulate code folder\nimport functools\nimport os\nimport json\nimport pickle\n\nimport tensorflow.compat.v1 as tf\nimport numpy as np\n\nfrom learning_to_simulate import reading_utils\n\n# enable eager execution\ntf.enable_eager_execution()\n\n# Set dat... | [
[
"tensorflow.compat.v1.data.TFRecordDataset",
"tensorflow.compat.v1.train.BytesList",
"tensorflow.compat.v1.enable_eager_execution",
"tensorflow.compat.v1.train.FloatList",
"tensorflow.compat.v1.train.Int64List",
"numpy.float32",
"tensorflow.compat.v1.python_io.TFRecordWriter",
"ten... |
feitang0/Learn-CUDA-Programming | [
"c53f7de28fddeff45a3b4d9f3081000f8d1228e6"
] | [
"Chapter10/10_deep_learning/04_framework_profile/tensorflow/RN50v1.5/model/layers/conv2d.py"
] | [
"# 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 obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless req... | [
[
"tensorflow.layers.conv2d",
"tensorflow.zeros_initializer",
"tensorflow.variance_scaling_initializer"
]
] |
zsteve/wot | [
"d5c1f2d68053fb96faec9122763801d062df782a"
] | [
"wot/ot/ot_model.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport itertools\nimport logging\nimport os\n\nimport anndata\nimport numpy as np\nimport pandas as pd\nimport scipy\nimport sklearn\n\nimport wot.io\nimport wot.ot\n\nlogger = logging.getLogger('wot')\n\n\nclass OTModel:\n \"\"\"\n The OTModel computes transport maps.\n\n Param... | [
[
"numpy.diag",
"scipy.sparse.isspmatrix",
"pandas.concat",
"numpy.linspace",
"numpy.power",
"numpy.random.choice",
"numpy.asarray",
"numpy.median",
"pandas.DataFrame",
"numpy.ones",
"numpy.concatenate",
"numpy.random.shuffle",
"numpy.random.multinomial",
"num... |
becauseofAI/DemoHub | [
"2b7fdd1f1c6f229ba326e8c1b78c4e7f5982f3da"
] | [
"det/lfd-face/lfd/model/neck/simple_neck.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport torch.nn as nn\n__all__ = ['SimpleNeck']\n\n\ndef get_operator_from_cfg(operator_cfg):\n operator_cfg_copy = operator_cfg.copy()\n construct_str = 'nn.'\n construct_str += operator_cfg_copy.pop('type') + '('\n for k, v in operator_cfg_copy.items():\n construct_s... | [
[
"torch.nn.init.constant_",
"torch.nn.Sequential",
"torch.nn.Conv2d",
"torch.nn.init.kaiming_normal_"
]
] |
strongio/models | [
"44ac3fe31a54796717707548e8a599db66cf3e2e",
"44ac3fe31a54796717707548e8a599db66cf3e2e"
] | [
"research/object_detection/model_lib.py",
"research/object_detection/model_main.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.logging.warning",
"tensorflow.contrib.tpu.bfloat16_scope",
"tensorflow.stack",
"tensorflow.train.init_from_checkpoint",
"tensorflow.contrib.learn.Experiment",
"tensorflow.contrib.tpu.CrossShardOptimizer",
"tensorflow.train.ExponentialMovingAverage",
"tensorflow.add_n",
... |
Shorrts/raspberry-pilot | [
"84bd2e7dc0c9142a420999ed527b8abbd14e0d34"
] | [
"selfdrive/controls/lib/pid.py"
] | [
"import numpy as np\r\nfrom common.numpy_fast import clip, interp\r\n\r\ndef apply_deadzone(error, deadzone):\r\n if error > deadzone:\r\n error -= deadzone\r\n elif error < - deadzone:\r\n error += deadzone\r\n else:\r\n error = 0.\r\n return error\r\n\r\nclass PIController(object):\r\n def __init__(... | [
[
"numpy.sign"
]
] |
tmirzaev-dotcom/signalProcessing | [
"b12e62480467d955a69972b2f275eebaddeec754"
] | [
"asteroid/models/base_models.py"
] | [
"import os\nimport warnings\nimport torch\nfrom torch import nn\nimport numpy as np\n\nfrom .. import torch_utils\nfrom ..utils.hub_utils import cached_download\nfrom ..masknn import activations\n\n\nclass BaseModel(nn.Module):\n def __init__(self):\n super().__init__()\n\n def forward(self, *args, **k... | [
[
"torch.no_grad",
"torch.from_numpy",
"torch.load"
]
] |
DangoMelon0701/OtherStuff | [
"8f1884fc1e18d72e136d4c5b0e24a78438041ca6"
] | [
"Helping Alejandro with his stuff/modified/puntual.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Jun 30 09:18:38 2017\n\n@author: aleja_blkf3w7\n\"\"\"\n\nimport numpy as np\nimport pandas as pd\nimport math as mt\nimport matplotlib.pyplot as plt\nfrom scipy import interpolate\nimport time\n#%%\ndef plot_data(energy,data,save_img=0,name='image'):\n fig,axs = ... | [
[
"pandas.read_csv",
"numpy.arange",
"matplotlib.pyplot.subplots",
"numpy.cos",
"numpy.sin",
"numpy.concatenate",
"scipy.interpolate.interp1d",
"numpy.exp",
"numpy.array",
"numpy.zeros"
]
] |
neuropil/sleep_ann | [
"ff2bd03ad5602e5db0bf57c0642e1960688c538e"
] | [
"feedforward_test.py"
] | [
"import numpy as np\nimport pandas as pd\nfrom pprint import pprint as pp\nfrom nn_models import feedforward\nfrom utils import *\n\nfrom sklearn.model_selection import KFold\nfrom sklearn.preprocessing import StandardScaler\n\n'''\nPreprocessed datafiles are mat files with the following keys:\nbands : ndarray\n'''... | [
[
"numpy.concatenate",
"sklearn.preprocessing.StandardScaler",
"sklearn.model_selection.KFold",
"pandas.DataFrame"
]
] |
vwxyzjn/invalid-action-masking | [
"0f9986ef574d36cb9c313f431068f6181615fd82"
] | [
"plots/approx_kl.py"
] | [
"from os import path\nimport pickle\nimport wandb\nimport pandas as pd\nimport numpy as np\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nimport os\nimport argparse\nfrom distutils.util import strtobool\nimport matplotlib as mpl\nmpl.rcParams['text.usetex'] = True\nmpl.rcParams['text.latex.preamble'] = [r... | [
[
"pandas.concat",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.rc",
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"numpy.std",
"matplotlib.pyplot.clf",
"numpy.mean",
"pandas.DataFrame.from_records",
"matplotlib.pyplot.figure"
]
] |
EricSchles/RNN-data-gen | [
"02cc59c8c44fffe375f7c51e1cf8f48811f6cc2f"
] | [
"shakespeare_model.py"
] | [
"# -*- coding: utf-8 -*-\n#\n# Implementing an LSTM RNN Model\n# ------------------------------\n# Here we implement an LSTM model on all a data set of Shakespeare works.\n#\n#\n#\n\nimport os\nimport re\nimport string\nimport requests\nimport numpy as np\nimport collections\nimport random\nimport pickle\nimport m... | [
[
"numpy.resize",
"tensorflow.concat",
"tensorflow.contrib.rnn.core_rnn_cell.BasicLSTMCell",
"tensorflow.reduce_sum",
"tensorflow.global_variables",
"matplotlib.pyplot.plot",
"tensorflow.train.AdamOptimizer",
"numpy.roll",
"tensorflow.squeeze",
"numpy.argmax",
"tensorflow... |
oss-vario/AltitudeEstimation | [
"dcd5de27a9bb0059dd66eb9b859dddc877c8f26e"
] | [
"extras/plot_log.py"
] | [
"import matplotlib.pyplot as plt\n\nwith open(\"log.txt\") as f:\n\tdata = f.readlines()\n\tdata = [d.rstrip().split() for d in data]\n\taccel = [d[0] for d in data]\n\tvel = [d[1] for d in data]\n\theight = [d[2] for d in data]\n\theight_from_baro = [d[3] for d in data]\n\nfig = plt.figure()\n\nax1 = fig.add_subpl... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
AnubhaPandey/VideoDecaptioningChalearn | [
"2c68a03cbb27163b3f7deaf5d25ddd500ee85216",
"2c68a03cbb27163b3f7deaf5d25ddd500ee85216"
] | [
"stage1/data_loader.py",
"stage1/train.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nfrom __future__ import print_function\nfrom PIL import Image\nimport numpy as np\nimport pims\nimport subprocess as sp\nimport re\nimport os, sys\nimport pickle\nimport cv2\nimport scipy.misc as sm\nimport shutil\nfrom os import path\n\nclass dataLoader:\n def _... | [
[
"numpy.asarray",
"numpy.random.shuffle",
"numpy.concatenate",
"numpy.shape",
"numpy.array"
],
[
"tensorflow.train.get_checkpoint_state",
"tensorflow.device",
"numpy.abs",
"tensorflow.Variable",
"tensorflow.summary.image",
"tensorflow.placeholder",
"numpy.random.... |
APinkLemon/Learn-Carla | [
"d9e4198de9b2e1abe0c2d372d1d09e6b9cfad5d7"
] | [
"python/automatic_control_revised.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"Revised automatic control\n\"\"\"\n# Author: Runsheng Xu <rxx3386@ucla.edu>\n# License: MIT\n\nimport os\nimport sys\nimport time\nimport random\n\nimport carla\nfrom queue import Queue\nfrom queue import Empty\n\nimport numpy as np\n\nfrom carla_utils import get_vehicle_info, get_... | [
[
"numpy.array"
]
] |
brinaseidel/squad | [
"73efc77b1296b3d9085f7ccd7f5b8574f3774226"
] | [
"word_embedding.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport constants\n\nclass WordEmbedding(nn.Module):\n\n # word_embeddings comes from numpy\n def __init__(self, word_embeddings):\n super(WordEmbedding, self).__init__()\n self.word_embedding = nn.Embedding(num_embeddings=wor... | [
[
"torch.from_numpy",
"torch.nn.Embedding",
"torch.nn.functional.dropout"
]
] |
ajabri/slot-attention | [
"32acb6614f1bd511f2dc3c263f852ed2dbe9c213"
] | [
"slot_attention/slot_attention.py"
] | [
"from torch import nn\nimport torch\n\nclass SlotAttention(nn.Module):\n def __init__(self, num_slots, dim, iters = 3, eps = 1e-8, hidden_dim = 128):\n super().__init__()\n self.num_slots = num_slots\n self.iters = iters\n self.eps = eps\n self.scale = dim ** -0.5\n\n se... | [
[
"torch.normal",
"torch.randn",
"torch.einsum",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.nn.GRUCell",
"torch.nn.ReLU"
]
] |
bcbcbcbcbcl/apex | [
"7b3ac7221367dc7b7527a68e34cf08b5eeb0fc47"
] | [
"apex/normalization/fused_layer_norm.py"
] | [
"import math\nimport torch\nimport numbers\nfrom torch.nn.parameter import Parameter\nfrom torch.nn import init\n\nimport fused_layer_norm_cuda\n\nclass FusedLayerNormAffineFunction(torch.autograd.Function):\n def __init__(self, normalized_shape, eps=1e-6):\n self.normalized_shape = normalized_shape\n self.e... | [
[
"torch.nn.init.ones_",
"torch.Size",
"torch.Tensor",
"torch.nn.init.zeros_"
]
] |
Stefan-Heimersheim/browser_tools | [
"e574d9f934f2d835617291911c1fefb8d3b0a952"
] | [
"firefox_password_parser.py"
] | [
"#!/usr/bin/env python\n\nimport sys\nimport json\nimport numpy as np\n\njson=json.load(sys.stdin)\nuList = []\npwList = []\nurlList = []\nfor a in json:\n # Split into domain, tld, etc.\n line = a['hostname'].strip().split('.')\n recent = [e+'.' for e in line if e and line.index(e) != len(line)-1]\n re... | [
[
"numpy.argsort",
"numpy.array",
"numpy.shape"
]
] |
lhggomes/computer-vision | [
"d55766c01bf1ef3427581bccfe6b73abbf3a11e5"
] | [
"Operations with Images/imageHistrogram.py"
] | [
"import cv2\nimport numpy as np\nfrom matplotlib import pyplot as plt\n\n# Reading the Image from the disk\nimage = cv2.imread(\"Photos/moedas.jpg\", 0)\n# Crating the histogram\n# In this function, We needed to use another funciont (ravel) to transform the data from a matrice 2x2 to a Vector\nplt.hist(image.ravel(... | [
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.show"
]
] |
ctrl-z-9000-times/HTM_experiments | [
"367f8701ec18226029d7ef070e70e9a8248a1374"
] | [
"mnist_sp.py"
] | [
"#!/usr/bin/python3\n# Written by David McDougall, 2017\n\nfrom htm import *\nimport genetics\n\ndef load_mnist():\n \"\"\"See: http://yann.lecun.com/exdb/mnist/ for MNIST download and binary file format spec.\"\"\"\n import gzip\n import numpy as np\n\n def int32(b):\n i = 0\n for char in... | [
[
"numpy.logical_not",
"matplotlib.pyplot.title",
"numpy.reshape",
"scipy.ndimage.zoom",
"numpy.squeeze",
"numpy.dstack",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplot",
"numpy.mean",
"numpy.array",
"matplotlib.pyplot.show",
"numpy.zeros",
"numpy.sum",
... |
KarlXing/A2C_test | [
"c77659bd280c4fba61e05d962b81eab5a32b7325"
] | [
"atari_wrappers.py"
] | [
"import numpy as np\nimport os\nos.environ.setdefault('PATH', '')\nfrom collections import deque\nimport gym\nfrom gym import spaces\nimport cv2\ncv2.ocl.setUseOpenCL(False)\n\nclass NoopResetEnv(gym.Wrapper):\n def __init__(self, env, noop_max=30):\n \"\"\"Sample initial states by taking random number of... | [
[
"numpy.sign",
"numpy.array",
"numpy.zeros",
"numpy.concatenate"
]
] |
wmpjrufg/META | [
"c7ed148877fb749779ca6992366870dbe6cd53f3"
] | [
"META_TOOLBOX/META_BENCHMARK_FUNCTIONS.py"
] | [
"# $$\\ $$\\ $$$$$$$$\\ $$$$$$$$\\ $$$$$$\\ $$$$$$$$\\ $$$$$$\\ $$$$$$\\ $$\\ $$$$$$$\\ $$$$$$\\ $$\\ $$\\ \n# $$$\\ $$$ |$$ _____|\\__$$ __|$$ __$$\\ \\__$$ __|$$ __$$\\ $$ __$$\\ $$ | $$ __$$\\ $$ __$$\\ $$ | $$ |\n# $$$$\\ $$$$ |$$ | $$ | $$ / $$ | ... | [
[
"numpy.cos"
]
] |
Shahil98/Deep_Fake_Video_Detection | [
"6c44cd5b7362b45b97d033c766cf181b6a2af08e"
] | [
"code/yolo3/model.py"
] | [
"\"\"\"YOLO_v3 Model Defined in Keras.\"\"\"\n\nfrom functools import wraps\n\nimport numpy as np\nimport tensorflow as tf\nfrom keras import backend as K\nfrom keras.layers import (\n Conv2D,\n Add,\n ZeroPadding2D,\n UpSampling2D,\n Concatenate,\n MaxPooling2D,\n)\nfrom keras.layers.advanced_act... | [
[
"tensorflow.boolean_mask",
"numpy.expand_dims",
"numpy.maximum",
"numpy.minimum",
"tensorflow.image.non_max_suppression",
"numpy.argmax",
"numpy.floor",
"numpy.array"
]
] |
dantreiman/ludwig | [
"daeffd21f9eef524afb2037763abd07a93228c2a",
"daeffd21f9eef524afb2037763abd07a93228c2a",
"daeffd21f9eef524afb2037763abd07a93228c2a"
] | [
"ludwig/utils/visualization_utils.py",
"tests/ludwig/encoders/test_bag_encoders.py",
"tests/ludwig/modules/test_utils.py"
] | [
"#! /usr/bin/env python\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/LICENSE-2.0\n#\n# Unle... | [
[
"matplotlib.pyplot.legend",
"matplotlib.ticker.MultipleLocator",
"numpy.linspace",
"matplotlib.pyplot.get_cmap",
"matplotlib.pyplot.plot",
"numpy.max",
"matplotlib.pyplot.matshow",
"matplotlib.patches.PathPatch",
"matplotlib.pyplot.tight_layout",
"numpy.arange",
"matplo... |
ShiveshM/flavour_ratio | [
"b7e4355173da6835b9e39ec4044ffe08ffc4a818"
] | [
"scripts/sens.py"
] | [
"#! /usr/bin/env python\n# author : S. Mandalia\n# s.p.mandalia@qmul.ac.uk\n#\n# date : March 17, 2018\n\n\"\"\"\nHESE BSM flavor ratio analysis script\n\"\"\"\n\nfrom __future__ import absolute_import, division\n\nimport os\nimport argparse\nfrom functools import partial\n\nimport glob\n\nimport numpy a... | [
[
"numpy.linspace",
"numpy.random.seed",
"numpy.power",
"numpy.isfinite",
"numpy.save",
"numpy.full",
"numpy.concatenate",
"numpy.log10",
"numpy.mean",
"numpy.load",
"numpy.array"
]
] |
lukapecnik/NiaClass | [
"288234df5fa01e05f72e234a38e8ab36eff84f6f"
] | [
"examples/basic_run.py"
] | [
"import os\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import accuracy_score\nfrom niaclass import NiaClass\n\n\"\"\"\nThis example presents how to use the NiaClass classifier instance.\nThe instantiated NiaClass will try to find the best set of classification ru... | [
[
"pandas.read_csv",
"sklearn.model_selection.train_test_split",
"sklearn.metrics.accuracy_score"
]
] |
Arengard/polars | [
"4aef1138f63405625899ad652df6acaf158b0d64"
] | [
"py-polars/tests/test_queries.py"
] | [
"import numpy as np\n\nimport polars as pl\n\n\ndef test_sort_by_bools() -> None:\n # tests dispatch\n df = pl.DataFrame(\n {\n \"foo\": [1, 2, 3],\n \"bar\": [6.0, 7.0, 8.0],\n \"ham\": [\"a\", \"b\", \"c\"],\n }\n )\n out = df.with_column((pl.col(\"foo\")... | [
[
"numpy.random.randint"
]
] |
aroongta/Carla_Controller | [
"bc606bfca3914744b01c64c6ab625bf84d0be2fa"
] | [
"LQR Controller/controller.py"
] | [
"\"\"\"\nYou will design your lateral and longitudinal controllers in this\nscript and execute the main.py script to check.\n\nThis script interfaces with the Carla server, receives the states\n of the actor vehicles and sends the control commands.\n[Script to Control a Single Vehicle]\n\nAuthor: Ashish Roongta\nCo... | [
[
"numpy.matrix",
"numpy.sqrt",
"numpy.abs",
"numpy.power",
"scipy.ndimage.gaussian_filter1d",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"numpy.ones",
"numpy.cos",
"numpy.sin",
"numpy.arctan2",
"numpy.identity",
"scipy.signal.StateSpace",
"num... |
kroniidvul/mpiigaze_project | [
"8a38732df8db6f7f3668b37836d75eb464049794"
] | [
"models/levgg.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Nov 28 20:58:57 2019\n\n@author: iamav\n\"\"\"\n# Upsample in PosNet. \n# No upsampling in PosUp. \n# VGG19 in ImNet. \n# Concatenate the output of these layers in an ensembled scheme.\n\nimport torch.nn as nn\nimport torchvision.models as models\nimport torch.nn.fun... | [
[
"torch.nn.Dropout",
"torch.cat",
"torch.nn.init.constant_",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.init.xavier_uniform_",
"torch.nn.Upsample",
"torch.nn.init.normal_",
"torch.nn.Conv1d",
"torch.nn.ReLU",
"torch.nn.functional.max_pool2d"
]
] |
arpane4c5/DPC | [
"8076e3fbe556095bec62d1124daf94c500c1d0e4"
] | [
"dpc/model_3d.py"
] | [
"import sys\nimport time\nimport math\nimport random\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nsys.path.append('../backbone')\nfrom select_backbone import select_resnet\nfrom convrnn import ConvGRU\n\n\nclass DPC_RNN(nn.Module):\n '''DPC with RNN'''\n def __ini... | [
[
"torch.cuda.manual_seed",
"torch.zeros",
"torch.nn.init.constant_",
"torch.nn.Conv2d",
"torch.matmul",
"torch.nn.functional.avg_pool3d",
"torch.nn.init.orthogonal_",
"torch.arange",
"torch.stack",
"torch.nn.ReLU"
]
] |
xqterry/FaceDetection-DSFD | [
"f25a41496b3475ec131f6d6503663981a0b0f6ae"
] | [
"layers/functions/detection.py"
] | [
"from __future__ import division\nimport torch\nfrom torch.autograd import Function\nfrom ..box_utils import decode, nms, center_size\nfrom ...data import widerface_640 as cfg\nimport pdb\n\nclass Detect(Function):\n \"\"\"At test time, Detect is the final layer of SSD. Decode location preds,\n apply non-max... | [
[
"torch.cat",
"torch.zeros"
]
] |
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