repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
kakaobrain/bassl | [
"551fe94343debf60a64c787be6752284153a0f7a"
] | [
"bassl/pretrain/utils/metric.py"
] | [
"\"\"\"\n- kNN Precision\n\"\"\"\n\nfrom collections import defaultdict\n\nimport torch\nimport torchmetrics\n\n\nclass KnnPrecisionMetric(torchmetrics.Metric):\n def __init__(self, top_k_list):\n super().__init__(compute_on_step=False, dist_sync_on_step=True)\n self.add_state(\"feat_data\", defaul... | [
[
"torch.stack",
"torch.argsort",
"torch.eye",
"torch.cuda.empty_cache"
]
] |
PolymerGuy/AXITOM | [
"7682be5b21fa933b9bea4082fe9a830076431feb"
] | [
"axitom/phantoms.py"
] | [
"import numpy as np\n\n\"\"\" Phantoms\n\nThis module contains the phantoms that can be used for forward projection and virtual experiments\n\n\"\"\"\n\ndef barrel(domain_size=128, outer_rad_fraction=0.7,center_val=None):\n \"\"\" Barrel shaped phantom with a linear density gradient\n The domain size is cubic... | [
[
"numpy.arange",
"numpy.zeros",
"numpy.sqrt"
]
] |
seanliu96/R-Net | [
"8462330451079a2ff67cd431fe30a57a6ca3d802"
] | [
"util.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport re\nfrom collections import Counter\nimport string\n\n\ndef get_record_parser(config, is_test=False):\n def parse(example):\n para_limit = config.test_para_limit if is_test else config.para_limit\n ques_limit = config.test_ques_limit if is_test e... | [
[
"tensorflow.constant",
"tensorflow.FixedLenFeature",
"tensorflow.less",
"tensorflow.data.TFRecordDataset",
"tensorflow.decode_raw",
"tensorflow.less_equal",
"tensorflow.cast",
"numpy.iinfo",
"tensorflow.where",
"tensorflow.contrib.data.group_by_window"
]
] |
Praneethvvs/CircleCi_FastApi | [
"0aec14fcffcfe7053cf7db688728347feea26f70"
] | [
"selenium_pipeline/hyatt_hotels_fetch_addresses.py"
] | [
"import time\n\nimport pandas as pd\nfrom selenium import webdriver\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.support.ui import WebDriverWait\nfrom selenium.webdriver.support import expected_conditions as EC\nfrom selenium.webdriver.common.desired_capabilities import DesiredCapabilities\... | [
[
"pandas.DataFrame"
]
] |
joshuabuildsthings/GamestonkTerminal | [
"385d12803ae1725a22b0a440c3b88bffa974edcd"
] | [
"openbb_terminal/stocks/discovery/fidelity_view.py"
] | [
"\"\"\" Fidelity View \"\"\"\n__docformat__ = \"numpy\"\n\nimport logging\nimport os\nimport re\n\nimport pandas as pd\n\nfrom openbb_terminal.decorators import log_start_end\nfrom openbb_terminal.helper_funcs import export_data, print_rich_table\nfrom openbb_terminal.stocks.discovery import fidelity_model\nfrom op... | [
[
"pandas.set_option"
]
] |
weaselers/candy_cane_contest | [
"1d619529cd8640c20b534ec9a3f6d5f786bb78aa"
] | [
"pull_vegas_slot_machine_v9.py"
] | [
"import numpy as np\nimport pandas as pd\nimport random, os, datetime, math\nfrom random import shuffle\nfrom collections import OrderedDict\nfrom collections import defaultdict\n\n\ntotal_reward = 0\nbandit_dict = {}\n\n\ndef set_seed(my_seed=42):\n os.environ[\"PYTHONHASHSEED\"] = str(my_seed)\n random.seed... | [
[
"numpy.random.seed"
]
] |
nytbliang/siamattnat | [
"880643ee09e7e4fa6a0af9631a9a8b32dd06c94d"
] | [
"tools/test.py"
] | [
"# Copyright (c) SenseTime. All Rights Reserved.\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nimport argparse\nimport os\n\nimport cv2\nimport torch\nimport numpy as np\n\nfrom pysot.core.config import c... | [
[
"numpy.array",
"torch.set_num_threads"
]
] |
CADWRDeltaModeling/vtools3 | [
"226bd2920c73f36dfc2f4eaedda8adccdfd1dfc3"
] | [
"vtools/datastore/station_info.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport sys\nimport pandas as pd\nimport argparse\nfrom vtools.datastore import station_config\n\ndef station_info(search):\n station_lookup = station_config.config_file(\"station_dbase\")\n if search == \"config\":\n print(station_config.configuration(... | [
[
"pandas.read_csv"
]
] |
adrn/gaia | [
"dac05003f7952af88697b271295a90bb0df091ec"
] | [
"pyia/data.py"
] | [
"# coding: utf-8\n\"\"\" Data structures. \"\"\"\n\n# Standard library\nimport pathlib\n\n# Third-party\nimport astropy.coordinates as coord\nfrom astropy.table import Table, Column\nfrom astropy.time import Time\nimport astropy.units as u\nimport numpy as np\n\nfrom .extinction import get_ext\nfrom .ruwetools impo... | [
[
"numpy.sqrt",
"numpy.isfinite",
"numpy.asarray",
"numpy.isnan",
"numpy.stack",
"numpy.random.RandomState",
"numpy.vstack"
]
] |
lvwuyunlifan/crop | [
"7392d007a8271ff384c5c66ed5717afbc4172b4d"
] | [
"logger.py"
] | [
"# Code referenced from https://gist.github.com/gyglim/1f8dfb1b5c82627ae3efcfbbadb9f514\n\nimport tensorflow as tf\n\nimport numpy as np\n\nimport scipy.misc\n\ntry:\n\n from StringIO import StringIO # Python 2.7\n\nexcept ImportError:\n\n from io import BytesIO # Python 3.x\n\n\nclass Logger(object):\n\n ... | [
[
"tensorflow.summary.FileWriter",
"numpy.min",
"numpy.max",
"tensorflow.Summary.Value",
"numpy.prod",
"tensorflow.HistogramProto",
"tensorflow.Summary",
"numpy.histogram",
"numpy.sum"
]
] |
neurodata/bilateral-connectome | [
"b04162f84820f81cf719e8a5ddd4dae34d8f5f41"
] | [
"pkg/pkg/utils/toy.py"
] | [
"import numpy as np\nimport pandas as pd\nimport seaborn as sns\nfrom graspologic.simulations import sbm\n\n\ndef sample_toy_networks(seed=888888, ns=None, B=None):\n np.random.seed(seed)\n if ns is None:\n ns = [5, 6, 7]\n if B is None:\n B = np.array([[0.8, 0.2, 0.05], [0.05, 0.9, 0.2], [0.... | [
[
"numpy.arange",
"numpy.array",
"numpy.random.seed"
]
] |
DarrenZhang01/Neural_Tangents_TensorFlow | [
"2fd360c8b1b8c9106044034f6a8b5c2734db9c3d"
] | [
"tf_dot_general/tf_dot_general_test.py"
] | [
"# Copyright 2020 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"numpy.array",
"tensorflow.python.platform.test.main",
"numpy.ones"
]
] |
hhcho/densvis | [
"d65bb3133a5072356f45d2d6f4f0d16ad33032fd"
] | [
"densmap/densmap.py"
] | [
"import sys\nimport numpy as np\nimport argparse\nimport pickle\n\nimport densmap\nfrom sklearn.datasets import load_digits\n\ndef parse_args():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument('-i','--input', help='Input .txt or .pkl', default='data.txt')\n parser.add_argument... | [
[
"numpy.savetxt",
"numpy.stack",
"numpy.loadtxt"
]
] |
gkbharathy/econ_model_02 | [
"d91ddf148b009bf79852d9aec70f3a1877e0f79a"
] | [
"dolo/algos/value_iteration.py"
] | [
"import time\nimport numpy as np\nimport numpy\nimport scipy.optimize\nfrom dolo.numeric.processes import DiscretizedIIDProcess\n# from dolo.numeric.decision_rules_markov import MarkovDecisionRule, IIDDecisionRule\nfrom dolo.numeric.decision_rule import DecisionRule, ConstantDecisionRule\nfrom dolo.numeric.grids im... | [
[
"numpy.zeros",
"numpy.zeros_like"
]
] |
dokato/mne-python | [
"a188859b57044fa158af05852bcce2870fabde91"
] | [
"mne/decoding/transformer.py"
] | [
"# -*- coding: utf-8 -*-\n# Authors: Mainak Jas <mainak@neuro.hut.fi>\n# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>\n# Romain Trachel <trachelr@gmail.com>\n#\n# License: BSD (3-clause)\n\nimport numpy as np\n\nfrom .mixin import TransformerMixin\nfrom .base import BaseEstimator\n... | [
[
"numpy.asarray",
"numpy.reshape",
"sklearn.preprocessing.RobustScaler",
"numpy.atleast_2d",
"numpy.atleast_3d",
"numpy.zeros_like",
"numpy.mean",
"numpy.transpose",
"sklearn.preprocessing.StandardScaler"
]
] |
timothyfisherphd/CRISPR_Cancer_Chromatin_State_Activity | [
"91cbd8519baaeccab404574d61e21dbf0ea1f26f"
] | [
"main02_ceres_data.py"
] | [
"## Generating Ceres Data\nfrom collections import defaultdict\nimport pandas as pd\n\nmainDicticionary=defaultdict(list)\nstateDictionary=defaultdict(list)\ncountScoreDictionary=defaultdict(int)\nsumScoreDictionary=defaultdict(int)\nmeanScoreDictionary=defaultdict(int)\n\nn = 0\nwith open('/Users/timothyfisher/Des... | [
[
"numpy.std"
]
] |
AnesBenmerzoug/ray | [
"5921e87ecd4e359fad60dab55f45855456d591e5"
] | [
"rllib/agents/trainer.py"
] | [
"from datetime import datetime\nimport numpy as np\nimport copy\nimport logging\nimport math\nimport os\nimport pickle\nimport time\nimport tempfile\nfrom typing import Callable, Dict, List, Optional, Type, Union\n\nimport ray\nfrom ray.exceptions import RayError\nfrom ray.rllib.agents.callbacks import DefaultCallb... | [
[
"numpy.stack"
]
] |
Archer-pro666/BAAF-Net | [
"663d1681d4d05ad3caaacd98e6dedfdc9caa4930"
] | [
"helper_tf_util.py"
] | [
"\"\"\" Wrapper functions for TensorFlow layers.\n\nAuthor: Charles R. Qi\nDate: November 2016\n\"\"\"\n\nimport numpy as np\nimport tensorflow as tf\n\n\ndef _variable_on_cpu(name, shape, initializer, use_fp16=False):\n \"\"\"Helper to create a Variable stored on CPU memory.\n Args:\n name: name of the ... | [
[
"tensorflow.device",
"tensorflow.get_variable",
"numpy.sqrt",
"tensorflow.control_dependencies",
"tensorflow.nn.max_pool",
"tensorflow.stack",
"tensorflow.nn.conv2d_transpose",
"tensorflow.train.ExponentialMovingAverage",
"tensorflow.nn.l2_loss",
"tensorflow.nn.conv1d",
... |
AdrienCorenflos/tensorflow | [
"1b5220e89fecca70375b372a5bddc7f961c6a736"
] | [
"tensorflow/python/data/util/nest_test.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.data.util.nest.map_structure_up_to",
"tensorflow.python.framework.sparse_tensor.SparseTensorValue",
"tensorflow.python.data.util.nest.assert_same_structure",
"tensorflow.python.data.util.nest.is_sequence",
"tensorflow.python.data.util.nest.flatten_up_to",
"numpy.ones",
... |
tblondelle/TransferLearningProject | [
"1c6a9bba2480919e22dd08756f328a47a321eafa",
"1c6a9bba2480919e22dd08756f328a47a321eafa",
"1c6a9bba2480919e22dd08756f328a47a321eafa"
] | [
"learning/MLP_base.py",
"learning/classifiers_in_progress/Word2Vec_legacy.py",
"learning/classifiers_in_progress/Regressors.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals, print_function, division\nfrom io import open\nimport unicodedata\nimport string\nimport re\nimport random\nimport os\nimport time\n\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.decomposition import TruncatedSVD\nfrom s... | [
[
"sklearn.decomposition.TruncatedSVD",
"torch.Tensor",
"torch.nn.Linear",
"torch.FloatTensor",
"torch.cuda.is_available",
"torch.nn.L1Loss",
"sklearn.feature_extraction.text.TfidfVectorizer",
"torch.save"
],
[
"numpy.zeros",
"numpy.linalg.norm"
],
[
"sklearn.metr... |
chencq1234/ssds.pytorch | [
"340aeac3e5f15ffeee6750f40bfbd64343926fc9"
] | [
"lib/dataset/dataset_factory.py"
] | [
"from lib.dataset import voc\nfrom lib.dataset import coco\n\ndataset_map = {\n 'voc': voc.VOCDetection,\n 'coco': coco.COCODetection,\n }\n\ndef gen_dataset_fn(name):\n \"\"\"Returns a dataset func.\n\n Args:\n name: The name of the dataset.\n\n Returns:\n fu... | [
[
"torch.utils.data.DataLoader",
"torch.from_numpy",
"torch.is_tensor",
"torch.stack",
"numpy.empty"
]
] |
ninamiolane/move | [
"83ab147ad1ebab6972591357f02fa29e186116f0"
] | [
"move/config.py"
] | [
"import logging\nimport torch\n\n#Set the configuration of the model \nlogging.info('Confirgure the run')\nbatch_size = 8\nlearning_rate= 3e-4\nepochs = 10\nseq_len=128\nnegative_slope = 0 #LeakyRelu\n\nlogging.info('Setup device')\nif torch.cuda.is_available():\n device = torch.device('cuda')\nelse:\n device... | [
[
"torch.device",
"torch.cuda.is_available"
]
] |
sc0ttms/SE-TFCN | [
"466a2d641c6ff4184c768c1e7aaf2b8a8158ce51"
] | [
"dataset/compute_metrics.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport sys\nimport os\nimport argparse\nimport toml\nimport librosa\nimport pandas as pd\nimport numpy as np\nfrom tqdm import tqdm\nfrom joblib import Parallel, delayed\n\nsys.path.append(os.getcwd())\nfrom audio.metrics import SI_SDR, STOI, WB_PESQ, NB_PESQ, REGISTERED_METRICS\n\n\ndef... | [
[
"pandas.read_csv",
"numpy.mean",
"pandas.DataFrame"
]
] |
xwhan/fairseq-wklm | [
"9c7c927fca75cd2b08c0207ff7f7682ed95a98e0"
] | [
"fairseq/modules/fb_elmo_token_embedder.py"
] | [
"# Copyright (c) 2017-present, Facebook, Inc.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the LICENSE file in\n# the root directory of this source tree. An additional grant of patent rights\n# can be found in the PATENTS file in the same directory.\n\nfrom typing import Dic... | [
[
"torch.nn.Softmax",
"torch.nn.Dropout",
"torch.ones",
"torch.full",
"torch.cat",
"torch.nn.init.constant_",
"torch.Tensor",
"torch.nn.init.xavier_normal_",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.no_grad",
"torch._dim_arange"
]
] |
revsic/tf-attentive-neural-process | [
"efa3bb0a9b6cfebaa3c1e025a9da00aef8d0a1e2"
] | [
"neural_process/anp.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport tensorflow_probability as tfp\n\nfrom neural_process.module.base import Encoder, Decoder, GaussianProb\n\nclass AttentiveNP:\n \"\"\"Attentive Neural Process\n Attributes:\n z_encoder: Encoder, encoder for latent representation\n z_prob: Gauss... | [
[
"tensorflow.concat",
"tensorflow.shape",
"tensorflow.reduce_sum",
"tensorflow.expand_dims",
"numpy.mean"
]
] |
Spinch/CarND-Capstone | [
"7e507df9f1cc72c76514907464ca9ca3d3ac9e85"
] | [
"ros/src/tl_detector/light_classification/tl_classifierNN.py"
] | [
"\nimport rospy\nimport cv2\nimport numpy as np\nfrom styx_msgs.msg import TrafficLight\nfrom darknet_ros_msgs.msg import BoundingBoxes\n\nclass TLClassifierNN(object):\n def __init__(self):\n #TODO load classifier\n self.lastBBox = [[0, 0], [0, 0]]\n self.lastBBoxT = rospy.get_time()\n\n ... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"numpy.multiply"
]
] |
maropu/lljvm-translator | [
"322fbe24a27976948c8e8081a9552152dda58b4b"
] | [
"python/src/test/resources/pyfunc/numpy_random12_test.py"
] | [
"import numpy as np\n\ndef numpy_random12_test(n):\n return np.random.random_sample(n)\n"
] | [
[
"numpy.random.random_sample"
]
] |
ZachMontgomery/PolyFits | [
"0634bcd3a24b12a22b566a0c134cddf733d28641"
] | [
"test/test_multivariablePolynomialFit_Function.py"
] | [
"import numpy as np\nimport polyFits as pf\nimport json\n\nfn = './test/'\nf = open(fn+'database.txt', 'r')\ndatabase = f.readlines()\nf.close()\n\naoa, dp, cl, cd, cm = [], [], [], [], []\nfor line in database[1:]:\n aoa.append( float( line[ 8: 25] ) )\n dp.append( float( line[ 34: 51] ) )\n cl.append( ... | [
[
"numpy.array"
]
] |
tpmp-inra/ipapi | [
"b0f6be8960a20dbf95ef9df96efdd22bd6e031c5"
] | [
"ipt/ipt_filter_contour_by_size.py"
] | [
"from ipso_phen.ipapi.base.ipt_abstract import IptBase\r\nfrom ipso_phen.ipapi.tools import regions\r\nimport numpy as np\r\nimport cv2\r\n\r\nimport logging\r\n\r\nlogger = logging.getLogger(__name__)\r\n\r\nfrom ipso_phen.ipapi.base import ip_common as ipc\r\n\r\n\r\nclass IptFilterContourBySize(IptBase):\r\n ... | [
[
"numpy.zeros_like",
"numpy.dstack"
]
] |
ekhoda/optimization-tutorial | [
"8847625aa49813823b47165c5f457294729459b6"
] | [
"process_data.py"
] | [
"import pandas as pd\n\nfrom helper import load_raw_data\n\n\ndef load_data():\n return get_modified_data(load_raw_data())\n\n\ndef get_modified_data(input_df_dict):\n # Our \"parameters\" table is very simple here. So, we can create a new dictionary\n # for our parameters as follows or just modify our df ... | [
[
"pandas.DataFrame"
]
] |
ericgarza70/machine-learning-book | [
"40520104c3d76d75ce4aa785e59e8034f74bcc8e"
] | [
"ch16/ch16-part1-self-attention.py"
] | [
"# coding: utf-8\n\n\nimport sys\nfrom python_environment_check import check_packages\nimport torch\nimport torch.nn.functional as F\n\n# # Machine Learning with PyTorch and Scikit-Learn \n# # -- Code Examples\n\n# ## Package version checks\n\n# Add folder to path in order to load from the check_packages.py script... | [
[
"torch.nn.functional.softmax",
"torch.empty",
"torch.zeros",
"torch.manual_seed",
"torch.nn.Embedding",
"torch.tensor",
"torch.matmul",
"torch.nn.Linear",
"torch.rand",
"torch.bmm",
"torch.allclose",
"torch.dot"
]
] |
LucasPagano/sga- | [
"5b4b88ebf826c2be022f34eb66d5a712b911724a"
] | [
"scripts/train.py"
] | [
"import argparse\nimport gc\nimport logging\nimport os\nimport sys\nimport time\n\nfrom collections import defaultdict\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\n\nfrom sgan.data.loader import data_loader\nfrom sgan.losses import gan_g_loss, gan_d_loss, l2_loss\nfrom sgan.losses import dis... | [
[
"torch.cuda.synchronize",
"torch.load",
"torch.cat",
"torch.zeros",
"torch.min",
"torch.sum",
"torch.numel",
"torch.no_grad",
"torch.save",
"torch.stack",
"torch.nn.init.kaiming_normal_"
]
] |
BryanYehuda/CompressionMethodComparison | [
"79db365b46242e49116f92bb871545c0fce26635"
] | [
"CompressionCheck.py"
] | [
"from math import log10, sqrt\nimport cv2\nimport numpy as np\n \ndef PSNR(original, compressed):\n mse = np.mean((original - compressed) ** 2)\n if(mse == 0):\n return 100\n max_pixel = 255.0\n psnr = 20 * log10(max_pixel / sqrt(mse))\n return psnr\n\ndef SNR(original, compressed):\n mse ... | [
[
"numpy.mean"
]
] |
A03ki/f-AnoGAN | [
"fecd9672f8f216e2d9ee618b2a03ed6b6d2fa3ba"
] | [
"fanogan/test_anomaly_detection.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.utils.model_zoo import tqdm\n\n\ndef test_anomaly_detection(opt, generator, discriminator, encoder,\n dataloader, device, kappa=1.0):\n generator.load_state_dict(torch.load(\"results/generator\"))\n discriminator.load_state_dict(torch.... | [
[
"torch.nn.MSELoss",
"torch.utils.model_zoo.tqdm",
"torch.load"
]
] |
metehancekic/wireless-fingerprinting | [
"41872761260b3fc26f33acec983220e8b4d9f42f"
] | [
"preproc/preproc_wifi.py"
] | [
"'''\nContains code for fractionally spaced equalization, preamble detection\nAlso includes a modified version of Teledyne's data read and preprocessing code\n'''\n\nimport numpy as np\nimport os\nimport json\nimport csv\nimport math\nimport fractions\nimport resampy\nfrom tqdm import tqdm, trange\nimport matplotli... | [
[
"numpy.sqrt",
"numpy.concatenate",
"numpy.int",
"scipy.fftpack.fft",
"numpy.angle",
"numpy.exp",
"numpy.roll",
"numpy.conjugate",
"matplotlib.pyplot.tight_layout",
"numpy.arange",
"numpy.size",
"numpy.argmax",
"matplotlib.pyplot.subplot",
"numpy.zeros",
... |
tszssong/HRNet-Image-Classification | [
"6d8ee24aedf2e0b3134102c221a29fb9b0ce2e1b"
] | [
"tools/train.py"
] | [
"# ------------------------------------------------------------------------------\n# Copyright (c) Microsoft\n# Licensed under the MIT License.\n# Written by Bin Xiao (Bin.Xiao@microsoft.com)\n# Modified by Ke Sun (sunk@mail.ustc.edu.cn)\n# ---------------------------------------------------------------------------... | [
[
"torch.optim.lr_scheduler.MultiStepLR",
"torch.nn.CrossEntropyLoss",
"torch.load",
"torch.rand",
"torch.cuda.is_available",
"torch.nn.DataParallel",
"torch.optim.lr_scheduler.StepLR"
]
] |
eaidova/UNITER | [
"5b4c9faf8ed922176b20d89ac56a3e0b39374a22"
] | [
"model/model.py"
] | [
"\"\"\"\nCopyright (c) Microsoft Corporation.\nLicensed under the MIT license.\n\nPytorch modules\nsome classes are modified from HuggingFace\n(https://github.com/huggingface/transformers)\n\"\"\"\nimport copy\nimport json\nimport logging\nfrom io import open\n\nimport torch\nfrom torch import nn\nfrom apex.normali... | [
[
"torch.nn.Dropout",
"torch.cat",
"torch.zeros_like",
"torch.nn.Embedding",
"torch.nn.Linear"
]
] |
cybercore-co-ltd/Onnx2Caffe | [
"aa4a90b7539e2b5ee0ad42f507021585da58be80"
] | [
"tools/verify_caffe_model.py"
] | [
"import argparse\nimport numpy as np\nimport onnx\nimport onnxruntime as rt\nimport torch\nimport os\nimport mmcv\nimport caffe\n\nfrom terminaltables import AsciiTable\n\ndef parse_args():\n parser = argparse.ArgumentParser()\n parser.add_argument('onnx_checkpoint', help='onnx checkpoint file')\n parser.a... | [
[
"torch.randn",
"torch.from_numpy",
"numpy.linalg.norm",
"numpy.abs"
]
] |
lsternlicht/tia | [
"fe74d1876260a946e52bd733bc32da0698749f2c"
] | [
"tia/tests/test_rlab_table.py"
] | [
"import unittest\n\nimport pandas as pd\nimport pandas.util.testing as pdtest\n\nimport tia.rlab.table as tbl\n\n\nclass TestTable(unittest.TestCase):\n def setUp(self):\n self.df1 = df1 = pd.DataFrame({'A': [.55, .65], 'B': [1234., -5678.]}, index=['I1', 'I2'])\n # Multi-index frame with multi-ind... | [
[
"pandas.Series",
"pandas.DataFrame",
"pandas.MultiIndex.from_arrays",
"pandas.util.testing.assert_frame_equal",
"pandas.date_range"
]
] |
onlyrico/PyABSA | [
"d0905eb5253eaa564d2244cd777e3a734bca777a"
] | [
"pyabsa/core/apc/classic/__bert__/dataset_utils/data_utils_for_training.py"
] | [
"# -*- coding: utf-8 -*-\n# file: data_utils.py\n# author: songyouwei <youwei0314@gmail.com>\n# Copyright (C) 2018. All Rights Reserved.\n\nimport os\nimport pickle\n\nimport numpy as np\nimport tqdm\nfrom findfile import find_file\nfrom google_drive_downloader.google_drive_downloader import GoogleDriveDownloader a... | [
[
"numpy.asarray",
"numpy.sum",
"numpy.ones"
]
] |
akashpattnaik/pre-ictal-similarity | [
"85f963aa0c6d2d0a6e971ffa005c400e136a0a76"
] | [
"code/05-soz_subgraph.py"
] | [
"# %%\n# %load_ext autoreload\n# %autoreload 2\n# Imports and environment setup\nimport numpy as np\nimport sys\nimport os\nfrom numpy.core.fromnumeric import sort\nimport pandas as pd\nimport json\nfrom scipy.io import loadmat\nimport matplotlib.pyplot as plt\nfrom tqdm import tqdm\nfrom os.path import join as osp... | [
[
"numpy.abs",
"numpy.random.choice",
"numpy.reshape",
"numpy.squeeze",
"scipy.stats.zscore",
"numpy.max",
"numpy.size",
"numpy.argmax",
"numpy.mean",
"scipy.stats.mannwhitneyu",
"numpy.var",
"numpy.argsort",
"numpy.zeros",
"numpy.sum"
]
] |
tkuri/irradiance_estimation | [
"3f7e0e8d4772222faad7257a70a8dec0198e4810"
] | [
"models/variation/pix2pix_tm2_mc_full_in2_model.py"
] | [
"import torch\nfrom .base_model import BaseModel\nfrom . import networks\nfrom torch.nn import functional as F\n\nclass Pix2PixTm2McFullIn2Model(BaseModel):\n \"\"\" This class implements the pix2pix model, for learning a mapping from input images to output images given paired data.\n\n The model training req... | [
[
"torch.transpose",
"torch.cat",
"torch.zeros_like",
"torch.unsqueeze",
"torch.matmul",
"torch.nn.functional.interpolate",
"torch.clamp",
"torch.nn.L1Loss"
]
] |
LI-Mingyu/GraphScope-MY | [
"942060983d3f7f8d3a3377467386e27aba285b33"
] | [
"python/tests/unittest/test_context.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n#\n# Copyright 2020 Alibaba Group Holding Limited. 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# h... | [
[
"pandas.read_csv"
]
] |
proximal-dg/proximal_dg | [
"000e925c7daab099b2c3735f99e65e6b2a00a799"
] | [
"torchgan/metrics/proximal_duality_gap.py"
] | [
"import torch\nimport torch.nn.functional as F\nimport torchvision\nimport copy\nimport time\nimport os\nfrom ..utils import reduce\nfrom .metric import EvaluationMetric\nfrom torchgan.trainer import *\nimport torch.multiprocessing as mp\nimport numpy as np\nfrom ray import tune\nfrom torch.optim import Adam\n__all... | [
[
"torch.no_grad",
"numpy.mean"
]
] |
danielhettegger-rl/stable-baselines3 | [
"23de12e95d96b7bb6136c6a338e407ae7db7c545"
] | [
"stable_baselines3/sac/policies.py"
] | [
"import warnings\nfrom typing import Any, Dict, List, Optional, Tuple, Type, Union\n\nimport gym\nimport torch as th\nfrom torch import nn\n\nfrom stable_baselines3.common.distributions import SquashedDiagGaussianDistribution, StateDependentNoiseDistribution\nfrom stable_baselines3.common.policies import BaseModel,... | [
[
"torch.nn.Sequential",
"torch.zeros_like",
"torch.nn.Linear",
"torch.clamp",
"torch.nn.Hardtanh"
]
] |
ssahn3087/pedestrian_detection | [
"d9a6cb9d10246941cff8575c803ab60b3a9d7d04"
] | [
"train.py"
] | [
"import os\nimport torch\nimport numpy as np\nimport math\nfrom torch.autograd import Variable\nfrom datetime import datetime\nfrom faster_rcnn import network\nfrom faster_rcnn.network import init_data, data_to_variable\nfrom faster_rcnn.network import train_net_params, print_weight_grad\nfrom faster_rcnn.faster_rc... | [
[
"torch.utils.data.DataLoader",
"numpy.random.seed",
"torch.optim.SGD"
]
] |
cameronliang/BayesVP | [
"3a38e6fc8b85f96f402289fde74f996971edec93"
] | [
"bayesvp/tests/test_likelihood.py"
] | [
"import unittest\nimport os\nimport sys\nimport numpy as np\n\nfrom bayesvp.config import DefineParams\nfrom bayesvp.likelihood import Posterior\nfrom bayesvp.utilities import get_bayesvp_Dir\n\n###############################################################################\n# TEST CASE 1: OVI line with stock confi... | [
[
"numpy.array"
]
] |
Aravind-Suresh/CVJyo | [
"6cb324fb538a50939335fd28ee90e23fbb32f2c0"
] | [
"cvjyo.py"
] | [
"import cv2\nimport numpy as np\nimport sys\nimport math\n\ndef markPoints(pts, img):\n for pt in pts:\n cv2.circle(img, tuple((pt[0], pt[1])), 2, 0, -1)\n\ndef contourAreaComparator(cnt1, cnt2):\n\tif cv2.contourArea(cnt1) > cv2.contourArea(cnt2):\n\t\treturn 1\n\telse:\n\t\treturn -1\n\ndef orderClockwi... | [
[
"numpy.asarray",
"numpy.arange",
"numpy.ones",
"numpy.max",
"numpy.array",
"numpy.zeros",
"numpy.where"
]
] |
JuanCRCano/AmericanOpt_Methods | [
"38a4de4da20337e629ab47edf2d2e7e134586264"
] | [
"options/valuation.py"
] | [
"import pandas as pd\nimport numpy as np\nimport math as mt\nfrom sklearn.linear_model import LinearRegression\n\ndef Binomial_Tree(Spot, Strike, Vencimiento, Volatilidad, TLibre_Riesgo, Call_Put, Tasa_Foranea=0, Tasa_Dividendo=0,\n Ramificaciones_Arbol=100, Modelo=\"Cox Equity\"):\n if Modelo =... | [
[
"numpy.maximum",
"numpy.random.normal",
"sklearn.linear_model.LinearRegression",
"numpy.zeros",
"numpy.where"
]
] |
othesoluciones/TFM | [
"8ed46985604c83c517612b38326b39a61b4cf102"
] | [
"static/generaMapas/generaCalendarioPolinico.py"
] | [
"#Conectamos a la base de datos\nimport base64\nimport json\nfrom pymongo import MongoClient as Connection\n\ncadenaCon= 'mongodb://othesoluciones:'+base64.b64decode(\"b3RoZXNvbHVjaW9uZXM=\")+'@ds029635.mlab.com:29635/othesoluciones1'\nMONGODB_URI =cadenaCon\nconexion = Connection(MONGODB_URI)\ndb = conexion.otheso... | [
[
"pandas.DataFrame"
]
] |
insoo223/openCVhowse | [
"d8885ab4f87a9d577fd660e60d41222dc2156332"
] | [
"chapter07/detect_car_bow_svm_sliding_window.py"
] | [
"import cv2\nimport numpy as np\nimport os\n\nfrom non_max_suppression import non_max_suppression_fast as nms\n\nif not os.path.isdir('CarData'):\n print('CarData folder not found. Please download and unzip '\n 'http://l2r.cs.uiuc.edu/~cogcomp/Data/Car/CarData.tar.gz '\n 'or https://github.com/... | [
[
"numpy.array"
]
] |
prokhn/onti-2019-bigdata | [
"b9296141958f544177388be94072efce7bdc7814"
] | [
"experiments_dikower/controllers/drlbox/net/q_net.py"
] | [
"\nimport tensorflow as tf\nfrom drlbox.common.namescope import TF_NAMESCOPE\nfrom drlbox.net.net_base import RLNet\n\n\nclass QNet(RLNet):\n\n def set_model(self, model):\n self.model = model\n self.weights = model.weights\n self.ph_state, = model.inputs\n self.tf_values, = model.out... | [
[
"tensorflow.reduce_sum",
"tensorflow.losses.huber_loss",
"tensorflow.placeholder",
"tensorflow.name_scope",
"tensorflow.one_hot",
"tensorflow.abs"
]
] |
NeutralKaon/spec2nii | [
"52f0dc42ad176fdbb173ac051803372909e9971c"
] | [
"spec2nii/nifti_orientation.py"
] | [
"import numpy as np\nfrom scipy.spatial.transform import Rotation\n\n\nclass NIFTIOrient:\n def __init__(self, affine):\n self.Q44 = affine\n qb, qc, qd, qx, qy, qz, dx, dy, dz, qfac = nifti_mat44_to_quatern(affine)\n self.qb = qb\n self.qc = qc\n self.qd = qd\n self.qx ... | [
[
"numpy.diag",
"scipy.spatial.transform.Rotation.from_euler",
"numpy.zeros",
"numpy.sqrt"
]
] |
DavidBraun777/TensorNetwork | [
"55942a12a859a8c6f8be473e623dbf0ddfd790b5"
] | [
"tensornetwork/backends/backend_test.py"
] | [
"\"\"\"Tests for graphmode_tensornetwork.\"\"\"\nimport builtins\nimport sys\nimport pytest\nimport numpy as np\n\n\ndef clean_tensornetwork_modules():\n for mod in list(sys.modules.keys()):\n if mod.startswith('tensornetwork'):\n sys.modules.pop(mod, None)\n\n\n@pytest.fixture(autouse=True)\ndef clean_bac... | [
[
"numpy.array",
"numpy.ones"
]
] |
jvc2688/cpm | [
"409e9ada39fc6238a63a75fb8474a3af70410347"
] | [
"cpm/code/leastSquareSolver.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom __future__ import division, print_function\n\n__all__ = [\"linear_least_squares\"]\n\nimport numpy as np\nfrom scipy import linalg\n\n\ndef linear_least_squares(A, y, yvar=None, l2=None):\n \"\"\"\n Solve a linear system as fast as possible.\n \n :param A: ``... | [
[
"numpy.dot",
"scipy.linalg.cho_factor",
"numpy.diag_indices_from",
"numpy.isscalar",
"numpy.zeros"
]
] |
Jimmy2027/torchio | [
"98e5f4f379e877fa20c49f93645a3d0e0834f650"
] | [
"torchio/data/inference/aggregator.py"
] | [
"from typing import Tuple\nimport torch\nimport numpy as np\nfrom ...utils import to_tuple\nfrom ...torchio import TypeData, TypeTuple\nfrom ..subject import Subject\n\n\nclass GridAggregator:\n r\"\"\"Aggregate patches for dense inference.\n\n This class is typically used to build a volume made of batches af... | [
[
"numpy.ones_like",
"torch.zeros",
"numpy.max",
"numpy.copy",
"numpy.floor"
]
] |
life-game-player/Hephaestus | [
"0c695193d8d2d8c70061e2e26ec8c718544342c6"
] | [
"services/models/mnemosyne.py"
] | [
"import torch\n\n\ndef create(\n host, user, passwd,\n module, operator, operation, result\n):\n \"\"\"\n Operation:\n 1: Create\n 2: Modify\n 3: Query\n 4: Delete\n\n Result:\n 0: Succeeded\n 1: Failed\n \"\"\"\n conn = ... | [
[
"torch.execute_list",
"torch.connect"
]
] |
HERMINDERSINGH1234/ML_Extra_Resolution_Increases | [
"1fefceeab83f03fa8194cb63f78c5dbf7e90aeae"
] | [
"LPIPSmodels/dist_model.py"
] | [
"\r\nfrom __future__ import absolute_import\r\n\r\nimport sys\r\nsys.path.append('..')\r\nsys.path.append('.')\r\nimport numpy as np\r\nimport torch\r\nfrom torch import nn\r\nimport os\r\nfrom collections import OrderedDict\r\nfrom torch.autograd import Variable\r\nimport itertools\r\nfrom .base_model import BaseM... | [
[
"torch.optim.Adam",
"torch.mean",
"torch.load",
"scipy.ndimage.zoom",
"numpy.cumsum",
"numpy.concatenate",
"numpy.mean",
"numpy.argsort",
"torch.clamp",
"numpy.array",
"numpy.sum",
"torch.autograd.Variable"
]
] |
abtinshahidi/astromodels | [
"580e972ccc69f4fad57e22030923ee27f9d59ee3"
] | [
"astromodels/sources/extended_source.py"
] | [
"import collections\n\nimport astropy.units as u\nimport numpy as np\n\nfrom astromodels.core.spectral_component import SpectralComponent\nfrom astromodels.core.tree import Node\nfrom astromodels.core.units import get_units\nfrom astromodels.functions.functions import Constant\nfrom astromodels.sources.source impor... | [
[
"numpy.squeeze",
"numpy.array",
"numpy.repeat",
"numpy.sum"
]
] |
hysunflower/Serving | [
"50d0c2900f3385b049f76b91e38cc69d8e8a102d"
] | [
"python/paddle_serving_app/local_predict.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/lic... | [
[
"numpy.array"
]
] |
cclauss/darts | [
"77a461b62edb232406891028645b2331a24a8b4d"
] | [
"rnn/train_search.py"
] | [
"import argparse\nimport os, sys, glob\nimport time\nimport math\nimport numpy as np\nimport torch\nimport logging\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.backends.cudnn as cudnn\nfrom architect import Architect\n\nimport gc\n\nimport data\nimport model_search as model\n\nfrom utils im... | [
[
"torch.nn.functional.softmax",
"numpy.random.random",
"torch.cuda.set_device",
"numpy.random.seed",
"torch.manual_seed",
"torch.cuda.is_available",
"torch.cuda.manual_seed_all",
"torch.nn.DataParallel"
]
] |
qiuqiangkong/dcase2019_task2 | [
"62575c8cdd4723cfdf497b290b6dddcce316c60b"
] | [
"utils/data_generator.py"
] | [
"import numpy as np\nimport h5py\nimport csv\nimport time\nimport logging\nimport os\nimport glob\nimport matplotlib.pyplot as plt\nimport logging\nimport pandas as pd\n\nfrom utilities import scale\nimport config\n\n\nclass Base(object):\n def __init__(self):\n '''Base class for train, validate and test ... | [
[
"pandas.read_csv",
"numpy.arange",
"numpy.tile",
"numpy.ones",
"numpy.concatenate",
"numpy.array",
"numpy.random.RandomState",
"numpy.zeros"
]
] |
dizcza/cdtw-python | [
"a83fffd6fc222a1691f07421fd4dbf46dc19e0aa"
] | [
"tests/test_cdtw.py"
] | [
"import unittest\nimport math\n\nimport numpy as np\nfrom cdtw.dtw import *\nfrom numpy.testing import assert_array_equal, assert_array_almost_equal\n\ntry:\n import dtaidistance\n DTAIDISTANCE_INSTALLED = True\nexcept ImportError:\n DTAIDISTANCE_INSTALLED = False\n\n\nclass TestCDTW(unittest.TestCase):\n\... | [
[
"numpy.sqrt",
"numpy.random.seed",
"numpy.testing.assert_array_equal",
"numpy.random.randn",
"numpy.testing.assert_array_almost_equal"
]
] |
huajianjiu/ANSMESC | [
"76323a46f638c717e23388cf529734081a70eeee"
] | [
"attention.py"
] | [
"# author - Richard Liao\n# Dec 26 2016\n# Attention GRU network\n\nfrom keras import backend as K\nfrom keras.engine.topology import Layer\nfrom keras import initializers, regularizers, constraints\n\n\nclass AttentionWithContext(Layer):\n \"\"\"\n Attention operation, with a context/query vector, for te... | [
[
"numpy.random.randint"
]
] |
AlexandrovLab/SigProfilerTopography | [
"34c7cf24392bc77953370038a520ffc8d0bdee50"
] | [
"SigProfilerTopography/source/plotting/TranscriptionReplicationStrandBiasFigures.py"
] | [
"# This source code file is a part of SigProfilerTopography\n# SigProfilerTopography is a tool included as part of the SigProfiler\n# computational framework for comprehensive analysis of mutational\n# signatures from next-generation sequencing of cancer genomes.\n# SigProfilerTopography provides the downstream dat... | [
[
"numpy.nanmax",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.rc",
"pandas.DataFrame",
"numpy.any",
"matplotlib.pyplot.gca",
"pandas.read_csv",
"numpy.arange",
"matplotlib.pyplot.Circle",
"matplotlib.pyplot.subplot",
"matplotlib.gridspec.GridSpec",
"matplotlib.pypl... |
yourtrading-ai/py_yourtrading_ai | [
"b69424f2afc40fe258c7ddae2fb47acc383ecbe5"
] | [
"src/data_upload/batch.py"
] | [
"import asyncio\nimport io\nimport ssl\n\nimport aiohttp\nimport aleph_client.asynchronous\nimport certifi\nimport pandas as pd\n\nfrom data_upload.data_utils import clean_time_duplicates\n\n\ndef get_download_url(symbol, interval=\"hourly\"):\n if interval == \"daily\":\n interval = \"d\"\n elif inter... | [
[
"pandas.read_csv"
]
] |
otsubo/CIFAR-ConvolutionalAutoEncoder-Chainer | [
"bbda81dc7b52f42e07e9daaff38ce7453b24e008"
] | [
"generate_cloth_img.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Jul 21 08:51:18 2018\n\n@author: user\n\"\"\"\n\nimport argparse\n\nimport os\nimport os.path as osp\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom tqdm import tqdm\n\nimport chainer\nfrom chainer import cuda\nfrom chainer.datasets import get_cifar10\nf... | [
[
"matplotlib.pyplot.tight_layout",
"numpy.expand_dims",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.show",
"numpy.random.RandomState",
"matplotlib.pyplot.figure"
]
] |
nataliepopescu/osdi21-artifact | [
"6a268c90a8ce449256b5c290caeb7e0e3b9d7e5c"
] | [
"scripts/table4_run.py"
] | [
"import os\nimport subprocess\nimport re\nimport time\nfrom numpy import average \nfrom ExpStats import runExpWithName\n\nROOT_PATH = os.path.dirname(os.path.realpath(__file__))\n\ndef parseThroughput(out):\n try:\n m = re.search(r'Requests/sec: ([0-9,.]+)', out)\n # m = re.search(r'([0-9,]+) ns/it... | [
[
"numpy.average"
]
] |
noemiefedon/RELAY | [
"1bf9c27ee1bcf1be0a7652fcca0ea38dd47b14b8"
] | [
"src/one_stack.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nFunctions to check a design manufacturability\n\n- check_ss_manufacturability\n checks the manufacturability of a stacking sequence list\n\"\"\"\n__version__ = '1.0'\n__author__ = 'Noemie Fedon'\n\nimport sys\nimport numpy as np\nsys.path.append(r'C:\\RELAY')\nfrom src.contiguit... | [
[
"numpy.array"
]
] |
postpascal/py-futu-api | [
"cb274d5ab5387dca190b739d161f2bc8eabe073d"
] | [
"futu/quote/open_quote_context.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n Market quote and trade context setting\n\"\"\"\n\nimport datetime\nimport math\nfrom time import sleep\n\nimport pandas as pd\nfrom futu.common.open_context_base import OpenContextBase, ContextStatus\nfrom futu.quote.quote_query import *\n\n\nclass OpenQuoteContext(OpenContextB... | [
[
"pandas.DataFrame"
]
] |
david8862/keras-CenterNet | [
"e74b933f6dd5ffac04f2de3eb0d887742be8490f"
] | [
"utils/setup.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nimport setuptools\nfrom setuptools.extension import Extension\nfrom distutils.command.build_ext import build_ext as DistUtilsBuildExt\n\n\nclass BuildExtension(setuptools.Command):\n description = DistUtilsBuildExt.description\n user_options = DistUtils... | [
[
"numpy.get_include"
]
] |
qianqianjun/DCGAN | [
"4e2d37f1d785e592e59334b91d197ef0475c1c99"
] | [
"main.py"
] | [
"\"\"\"\nwrite by qianqianjun\n2019.12.20\n运行GAN进行训练的入口文件。\n\"\"\"\nimport os\nimport tensorflow as tf\nfrom train_argparse import hps\nfrom dataset_loader import train_images\nfrom data_provider import MnistData\nfrom DCGAN import DCGAN\nfrom utils import combine_imgs\n\n# 创建生成结果目录\noutput_dir='./out'\nif not os.p... | [
[
"tensorflow.global_variables_initializer",
"tensorflow.Session"
]
] |
StevenTang1998/TextBox | [
"acd8298c7e6618384d585146f799d02cc475520c"
] | [
"textbox/model/Seq2Seq/t5.py"
] | [
"# @Time : 2021/3/15\n# @Author : Zhuohao Yu\n# @Email : zhuohao@ruc.edu.cn\n\nr\"\"\"\nT5\n################################################\nReference:\n Colin et al. \"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer\" at JMLR 2020.\n\"\"\"\n\nimport torch\nimport torch.nn a... | [
[
"torch.nn.CrossEntropyLoss"
]
] |
comydream/OpenNMT-py | [
"bdca05a3fac8f864b21c86a8ad03c09895212e70"
] | [
"onmt/translate/greedy_search.py"
] | [
"import torch\nimport torch.nn.functional as F\n\nfrom onmt.translate.decode_strategy import DecodeStrategy\n\n\ndef sample_topp(logits, keep_topp):\n sorted_logits, sorted_indices = torch.sort(logits,\n descending=True,\n ... | [
[
"torch.div",
"torch.nn.functional.softmax",
"torch.zeros",
"torch.cat",
"torch.lt",
"torch.distributions.Categorical",
"torch.sort",
"torch.arange",
"torch.topk"
]
] |
Lsplastic/Tensorflow_ssd | [
"f2935079fb8d2cd2288ef5f7a415749243f34542"
] | [
"dataset/dataset_inspect.py"
] | [
"# Copyright 2018 Changan Wang\r\n\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n\r\n# http://www.apache.org/licenses/LICENSE-2.0\r\n\r\n# Unless required by applicable ... | [
[
"tensorflow.python_io.tf_record_iterator",
"tensorflow.python_io.TFRecordOptions"
]
] |
dkkim1005/Neural_Network_Quantum_State | [
"7e94929c5ef65ce87f63bf20c81acaa524adca82"
] | [
"python/meas_smag.py"
] | [
"#!/usr/bin/env python3\nimport numpy as np\nfrom pynqs import sampler\n\nfloatType = 'float32'\nsymmType = 'tr'\n# hyper parameter sets of rbm and MCMC sampler\nkwargs = {\n 'nInputs' : 16,\n 'nHiddens' : 4,\n 'nChains' : 1000,\n 'seedNumber' : 0,\n 'seedDistance' : 123456789,\n 'init_mcmc_steps' : 300\n}\n#... | [
[
"numpy.sum",
"numpy.zeros",
"numpy.mean"
]
] |
salesforce/DialFact | [
"d400b250147e45c106b18e52254b1060f7c1575d"
] | [
"scripts/run_fever_scoring.py"
] | [
"import argparse\nimport sys\nimport jsonlines\nfrom tqdm import tqdm\nimport logging\nimport json\nimport torch\nimport torch.nn.functional as F\nimport jsonlines\nimport random\nimport os\nimport numpy as np\nfrom scipy.special import softmax\n# os.environ[\"NCCL_SHM_DISABLE\"] = \"1\"\nfrom tqdm import tqdm\nfro... | [
[
"torch.utils.data.DataLoader"
]
] |
praeclarumjj3/CuML | [
"1c812d3b07a11c3a69a284d9960058a874d97bfa"
] | [
"CuSVD/testcases/gen_testcase.py"
] | [
"#!/usr/bin/python3\n\n#########################################################################\n# Generate M x N matrix of real numbers and store #\n# the the matrix in file named 'testcase_<M>_<N>' #\n# Parameters: ... | [
[
"sklearn.preprocessing.StandardScaler"
]
] |
masayoshi-nakamura/CognitiveArchitectureLecture | [
"5e036b48e92f266062eb7be8a366e754dee24f2c"
] | [
"examples/brainsimulator_agent/components/visual_area_component.py"
] | [
"\nimport brica1\nimport numpy as np\nimport pygazebo.msg.poses_stamped_pb2\nimport pickle\n\nclass VisualAreaComponent(brica1.Component):\n def __init__(self):\n super(VisualAreaComponent, self).__init__()\n self.last_position = np.array((0, 0))\n\n def __position_to_area_id(self, pos2d):\n ... | [
[
"numpy.array"
]
] |
vtekur/gnn_pathplanning | [
"150ca315c214134eda8f5c5b55ce71da9360bcce"
] | [
"utils/visualize.py"
] | [
"#!/usr/bin/env python3\nimport yaml\nimport matplotlib\n# matplotlib.use(\"Agg\")\nfrom matplotlib.patches import Circle, Rectangle, Arrow\nfrom matplotlib.collections import PatchCollection\nfrom matplotlib.patches import ConnectionPatch\nfrom matplotlib.patches import FancyArrowPatch\nimport matplotlib.pyplot as... | [
[
"numpy.array",
"matplotlib.pyplot.cm.get_cmap",
"matplotlib.pyplot.ylim",
"numpy.set_printoptions",
"matplotlib.patches.Rectangle",
"scipy.io.loadmat",
"matplotlib.pyplot.Line2D",
"matplotlib.patches.Circle",
"numpy.linalg.norm",
"matplotlib.pyplot.xlim",
"matplotlib.li... |
zyyhhxx/convNet.pytorch | [
"85f65f80b6d75810077c54bd3a8c9094cc2a26f9"
] | [
"models/resnet.py"
] | [
"import torch\nimport torch.nn as nn\nimport torchvision.transforms as transforms\nimport math\nfrom .modules.se import SEBlock\nfrom .modules.checkpoint import CheckpointModule\nimport os\nimport sys\nsys.path.append(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))\nfrom utils.mixup import MixUp\n\n__... | [
[
"torch.nn.Sequential",
"torch.nn.Dropout",
"torch.nn.init.constant_",
"torch.nn.Conv2d",
"torch.nn.MaxPool2d",
"torch.nn.Linear",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU"
]
] |
sahiljuneja/kaggle-ctds | [
"caac226f2c5d33b6d324c5cf33a777758b9163d1"
] | [
"utils/modify_ravdess.py"
] | [
"import re\nimport os\nimport argparse\nimport librosa\nimport librosa.display\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\ndef modify_data(input_path, save_path, dir_dict):\n \n path = os.listdir(input_path)\n for folders in path:\n \n folders = os.path.sep.join([input_path, fol... | [
[
"matplotlib.pyplot.savefig"
]
] |
akhambhati/dyne2 | [
"d2f050b3d14ef429fc9c52821e87f1c9a52a521d"
] | [
"dyne/adjacency/coherence.py"
] | [
"\"\"\"\nCoherence pipes for quantifying signal similarity (i.e. connectivity)\n\nCreated by: Ankit Khambhati\n\nChange Log\n----------\n2016/03/06 - Implemented WelchCoh and MTCoh pipes\n\"\"\"\n\nfrom __future__ import division\nimport numpy as np\nfrom mtspec import mt_coherence, mtspec\nfrom scipy.signal import... | [
[
"scipy.signal.coherence",
"numpy.flatnonzero",
"numpy.mean",
"numpy.diff",
"numpy.float"
]
] |
jwillis0720/seaborn | [
"0dc93d01c78370e91ebdf72c888719fbbc6d1085"
] | [
"seaborn/algorithms.py"
] | [
"\"\"\"Algorithms to support fitting routines in seaborn plotting functions.\"\"\"\nimport numbers\nimport numpy as np\nimport warnings\nfrom math import sqrt\n\n\ndef wls_confidence_interval(data, z=1.96):\n \"\"\"Calculate the Wilson score confidence interval for a data set.\n\n data : array of 1-dimensiona... | [
[
"numpy.unique",
"numpy.asarray",
"numpy.array",
"numpy.random.RandomState",
"numpy.random.default_rng"
]
] |
lluo5779/Robo-Adviser | [
"43aa4b73bfc96e55ed664328330a930975596124"
] | [
"server/models/portfolio/risk.py"
] | [
"import numpy as np\nimport pandas as pd\n\n\ndef risk_prefs(horizon, aversion, cardinal, return_target, l, mu_bl1, mu_bl2, cov_bl1):\n\n if horizon is None:\n horizon = 10\n\n alpha = 0.05\n\n safe_target = float(((mu_bl1 + mu_bl2) / 2).mean())\n\n # set the variances for the first period estima... | [
[
"numpy.diag",
"numpy.divide"
]
] |
haziq9978/PythonChatbot | [
"8eb77140b32a4c6770dab20d4e26be03504ac5ee"
] | [
"train.py"
] | [
"import numpy as np\nimport random\nimport json\n\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\n\nfrom nltk_utils import bag_of_words, tokenize, stem\nfrom model import NeuralNet\n\nwith open('dataCombine.json', 'r') as f:\n intents = json.load(f)\n\nall_words = []\ntags... | [
[
"torch.nn.CrossEntropyLoss",
"torch.utils.data.DataLoader",
"torch.cuda.is_available",
"numpy.array",
"torch.save"
]
] |
whxf/nlp_api | [
"a63b67287e9a90381cac14bb1c5b723ccbeb14a3"
] | [
"tools/similarity.py"
] | [
"\"\"\"\n@author: Li Xi\n@file: similarity.py\n@time: 2019/10/30 15:37\n@desc:\n计算文本相似度：\n1. WordMoverDistance 基于词移距离的文本相似度计算 【比较文档的相似度】\n2. WordVectorSimilarity word-vector的句子相似度计算 【比较句子的相似度】\n注意事项：\n* 两种方法都需要输入句子分词之后的结果，类型需要时list\n* 为提升效率/效果，可对分词结果进行处理，如去除停用词等\n* 具体使用方法见文件的最下\n* 可自定义加载词向量文件\n\"\"\"\nimport os\n\... | [
[
"numpy.zeros",
"numpy.sum"
]
] |
AnonymousExplorer/Conditional-GANs-Pytorch | [
"6c15ec67217156d6f041e34efe29ab62f9ef7c7d"
] | [
"train_InfoGAN1.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport argparse\nimport json\n\nimport model\nimport numpy as np\nimport pylib\nimport PIL.Image as Image\nimport tensorboardX\nimport torch\nimport torchvision\nimport torchvision.datasets as dsets\ni... | [
[
"torch.cat",
"torch.randn",
"numpy.eye",
"torch.nn.functional.cross_entropy",
"torch.cuda.is_available",
"torch.device",
"numpy.random.randint"
]
] |
zooechiu/pyro2 | [
"b0ca4aa7b1b0f0d445c6a8d0ab63fcc0bc8a431c"
] | [
"compressible_sr/problems/rt.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\n\nimport sys\nimport mesh.patch as patch\nimport compressible_sr.eos as eos\nfrom util import msg\n\n\ndef init_data(my_data, rp):\n \"\"\" initialize the rt problem \"\"\"\n\n msg.bold(\"initializing the rt problem...\")\n\n # make sure that we... | [
[
"numpy.cos",
"numpy.exp",
"numpy.sqrt"
]
] |
SaadChaouki/ml-eli5-cli5 | [
"625a69edadf4737e41c58193873cf8a54273d7f0"
] | [
"visualisations/linear_regression.py"
] | [
"from supervised.regression.linearRegression import LinearRegression\nfrom visualisations.color_palette import two_colors\nfrom deep_learning.loss import MSELoss\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.datasets import make_regression\n\nfrom matplotlib.animation import FuncAnimation\ni... | [
[
"matplotlib.pyplot.legend",
"matplotlib.use",
"matplotlib.pyplot.subplots",
"sklearn.model_selection.train_test_split",
"sklearn.datasets.make_regression",
"matplotlib.animation.FuncAnimation",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]... |
gaocegege/ray | [
"c852213b8349b6b9e9e7353573e2259a1b9ef925"
] | [
"python/ray/tests/test_basic.py"
] | [
"# coding: utf-8\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport collections\nfrom concurrent.futures import ThreadPoolExecutor\nimport json\nimport logging\nfrom multiprocessing import Process\nimport os\nimport random\nimport re\nimport set... | [
[
"numpy.testing.assert_equal",
"numpy.uint32",
"numpy.arange",
"numpy.uint8",
"numpy.int32",
"numpy.int8",
"pandas.DataFrame",
"numpy.ones",
"numpy.int64",
"numpy.random.normal",
"numpy.random.permutation",
"numpy.uint64",
"numpy.float64",
"numpy.float32",
... |
Bifaxin/pandas | [
"2ec7f2f279d770b286c9c7679ba7ad0e2f14dcbe"
] | [
"pandas/core/indexes/interval.py"
] | [
"\"\"\" define the IntervalIndex \"\"\"\nfrom operator import le, lt\nimport textwrap\nfrom typing import Any, Optional, Tuple, Union\nimport warnings\n\nimport numpy as np\n\nfrom pandas._config import get_option\n\nfrom pandas._libs import Timedelta, Timestamp, lib\nfrom pandas._libs.interval import Interval, Int... | [
[
"pandas.tseries.frequencies.to_offset",
"numpy.linspace",
"pandas.core.dtypes.common.is_dtype_equal",
"pandas.core.dtypes.common.is_datetime64tz_dtype",
"pandas._libs.interval.IntervalTree",
"pandas.core.indexes.base.Index",
"numpy.concatenate",
"pandas._config.get_option",
"nu... |
myforkmachine/pyprobml | [
"a750b6e33e849ca75300fec1b9ee4b61def80c52"
] | [
"auto_generated_scripts/combining_kernels_by_summation.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\ntry:\n import jax\nexcept:\n get_ipython().run_line_magic('pip', 'install jax jaxlib')\n import jax\nimport jax.numpy as jnp\n\ntry:\n import matplotlib.pyplot as plt\nexcept:\n get_ipython().run_line_magic('pip', 'install matplotlib')\n imp... | [
[
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.subplots"
]
] |
iyanmv/galois | [
"a5e6386a684e3e0b47af608217002795dc25c702"
] | [
"galois/_fields/_main.py"
] | [
"\"\"\"\nA module that contains the main classes for Galois fields -- FieldClass, FieldArray,\nand Poly. They're all in one file because they have circular dependencies. The specific GF2\nFieldClass is also included.\n\"\"\"\nimport inspect\nimport math\nimport random\nfrom typing import Tuple, List, Sequence, Iter... | [
[
"numpy.issubdtype",
"numpy.dtype",
"numpy.all",
"numpy.max",
"numpy.any",
"numpy.iinfo",
"numpy.bool_",
"numpy.where",
"numpy.random.default_rng",
"numpy.roll",
"numpy.unique",
"numpy.arange",
"numpy.add.reduce",
"numpy.atleast_1d",
"numpy.count_nonzero"... |
iacercalixto/WALS | [
"7f4b5042591d536f6b371d5fb252616d2da7abaf"
] | [
"onmt/train_single.py"
] | [
"#!/usr/bin/env python\n\"\"\"\n Training on a single process\n\"\"\"\nfrom __future__ import division\n\nimport argparse\nimport os\nimport random\nimport torch\n\nimport onmt.opts as opts\n\nfrom onmt.inputters.inputter import build_dataset_iter, lazily_load_dataset, \\\n _load_fields, _collect_report_featu... | [
[
"torch.cuda.set_device",
"torch.cuda.manual_seed",
"torch.load",
"torch.manual_seed",
"torch.cuda.is_available"
]
] |
HaoranZ99/RL-2 | [
"253c2fd8c705f88d9cc79abd9f331dc99b5895eb"
] | [
"logger.py"
] | [
"import numpy as np\nimport time, datetime\nimport matplotlib.pyplot as plt\n\nclass Logger():\n def __init__(self, save_dir):\n self.save_log = save_dir / \"log\"\n with open(self.save_log, \"w\") as f:\n f.write(\n f\"{'Episode':>8}{'Step':>8}{'Epsilon':>10}{'MeanReward'... | [
[
"numpy.round",
"matplotlib.pyplot.clf",
"numpy.mean"
]
] |
petrux/LiteFlowX | [
"96197bf4b5a87e682c980d303a0e6429cdb34964"
] | [
"liteflow/tests/test_layers_base.py"
] | [
"\"\"\"Test the base class of the layers hierarchy.\"\"\"\n\n# Disable pylint warning about too many statements\n# and local variables since we are dealing with tests.\n# pylint: disable=R0914, R0915\n\nimport mock\nimport tensorflow as tf\n\nfrom liteflow import layers, utils\n\n\nclass Layer(layers.Layer):\n \... | [
[
"tensorflow.variable_scope",
"tensorflow.get_variable",
"tensorflow.get_variable_scope"
]
] |
boknilev/fairseq | [
"5da0bffba945105ef7e0d4e7e5610e1cf966a459"
] | [
"train.py"
] | [
"#!/usr/bin/env python3 -u\n# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\"\"\"\nTrain a new model on one or across multiple GPUs.\n\"\"\"\n\nimport collections\nimport math\nimpor... | [
[
"torch.cuda.set_device",
"torch.multiprocessing.spawn",
"numpy.random.seed",
"torch.manual_seed",
"torch.cuda.is_available",
"torch.cuda.device_count"
]
] |
LSSTDESC/sims_TruthCatalog | [
"348f5d231997eed387aaa6e3fd4218c126e14cdb",
"348f5d231997eed387aaa6e3fd4218c126e14cdb"
] | [
"bin.src/write_star_variability_stats.py",
"scripts/Run3.1i/write_lensed_agn_truth.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nScript to generate stellar_variability table using multiprocessing\non a single 32 core Cori-Haswell node.\n\"\"\"\nimport numpy as np\nimport multiprocessing\nfrom desc.sims_truthcatalog import write_star_variability_stats\n\n\nstars_db_file = ('/global/projecta/projectdirs/lsst/'\n... | [
[
"numpy.array"
],
[
"numpy.linspace"
]
] |
Joshua-Elms/CSCI-B365 | [
"f28dda6da3098ec4b9472ee546c3e6798d358ce8"
] | [
"Meteorology_Modeling_Project/preprocessing/brute_force.py"
] | [
"import pandas as pd\nfrom itertools import combinations, chain\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.impute import KNNImputer\nfrom numpy import corrcoef\nfrom random import shuffle\n\npath = \"/Users/joshuaelms/Desktop/github_repos/CSCI-B365/Meteorology_Modeling_Project/data/pretty_data... | [
[
"pandas.read_csv",
"pandas.DataFrame",
"sklearn.linear_model.LinearRegression",
"sklearn.impute.KNNImputer",
"numpy.corrcoef"
]
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.