repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
fengzileee/OpenTraj | [
"71fdfd1e3420d6a3859ae0acaa4acf85abbc1f64"
] | [
"opentraj/toolkit/ui/pyqt/qtui/opentrajui.py"
] | [
"# This Python file uses the following encoding: utf-8\nimport sys\nimport cv2\nimport numpy as np\n# from PySide2.QtWidgets import QApplication, QCoreApplication, QMainWindow, QGraphicsView\nfrom PyQt5.QtWidgets import QApplication, QMainWindow\nfrom PyQt5.QtWidgets import QGraphicsScene, QGraphicsItem, QGraphicsP... | [
[
"numpy.require"
]
] |
Imarcos/scikit-learn-mooc | [
"b58f051efb591a38859a4242369c9494ccac6a17"
] | [
"python_scripts/cross_validation_grouping.py"
] | [
"# %% [markdown]\n# # Sample grouping\n# We are going to linger into the concept of sample groups. As in the previous\n# section, we will give an example to highlight some surprising results. This\n# time, we will use the handwritten digits dataset.\n\n# %%\nfrom sklearn.datasets import load_digits\n\ndigits = load... | [
[
"numpy.zeros_like",
"matplotlib.pyplot.xlim",
"sklearn.datasets.load_digits",
"matplotlib.pyplot.xlabel",
"pandas.DataFrame",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xticks",
"sklearn.model_selection.GroupKFold",
... |
frewsxcv/scipy | [
"b8b612c54c60e22e2a186dde6264de046ab1fe2b",
"b8b612c54c60e22e2a186dde6264de046ab1fe2b",
"b8b612c54c60e22e2a186dde6264de046ab1fe2b",
"b8b612c54c60e22e2a186dde6264de046ab1fe2b"
] | [
"scipy/linalg/decomp_svd.py",
"scipy/stats/tests/test_stats.py",
"scipy/io/arff/arffread.py",
"scipy/io/netcdf.py"
] | [
"\"\"\"SVD decomposition functions.\"\"\"\nfrom __future__ import division, print_function, absolute_import\n\nimport numpy\nfrom numpy import asarray_chkfinite, asarray, zeros, r_, diag\nfrom scipy.linalg import calc_lwork\n\n# Local imports.\nfrom .misc import LinAlgError, _datacopied\nfrom .lapack import get_lap... | [
[
"numpy.asarray",
"numpy.zeros",
"numpy.sum",
"numpy.finfo",
"numpy.amax",
"numpy.asarray_chkfinite",
"scipy.linalg.calc_lwork.gesdd",
"numpy.diag"
],
[
"numpy.random.chisquare",
"numpy.median",
"scipy.stats.skew",
"scipy.stats.sem",
"numpy.log",
"scipy.s... |
jk7g14/deep-trading-bot | [
"288d84f1bd4fe733c062bccb45b062b27fdc33c8"
] | [
"crypto_env.py"
] | [
"import numpy as np\nimport pandas as pd\nimport time\nimport sys\nimport random\nfrom sklearn.preprocessing import MinMaxScaler\nimport talib\n\n\nclass Crypto:\n def __init__(self, name, data_path, start_cash, fee, drawdown_call, fixed_stake, period):\n self.data_path = data_path\n self.start_cas... | [
[
"pandas.to_datetime",
"pandas.read_csv",
"sklearn.preprocessing.MinMaxScaler"
]
] |
shirui-japina/tensorboardX | [
"9b9933aa6b614de32341142533e7cf9594cdc2c4"
] | [
"tests/test_numpy.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nimport numpy as np\nimport unittest\n\nfrom tensorboardX import x2num\n\n\nclass NumpyTest(unittest.TestCase):\n def test_scalar(self):\n res = x2num.... | [
[
"numpy.float16",
"numpy.random.random_sample",
"numpy.random.randint",
"numpy.float128",
"numpy.int64"
]
] |
pvk-developer/Orion | [
"303af9f35a5e6f855a9801d1ec43abe780890c75"
] | [
"orion/explorer.py"
] | [
"import json\nimport logging\nfrom datetime import datetime\n\nimport pandas as pd\nfrom bson import ObjectId\nfrom bson.errors import InvalidId\nfrom mlblocks import MLPipeline\nfrom mongoengine import connect\nfrom pip._internal.operations import freeze\n\nfrom orion import model\nfrom orion.data import load_sign... | [
[
"pandas.DataFrame"
]
] |
Sammy-py/fire-smoke-detection | [
"322f7d975a8a8f73c5f4beb7edc1a8e8247d64c2"
] | [
"yoloV5-Fire-Smoke-Detect/hubconf.py"
] | [
"# YOLOv5 🚀 by Ultralytics, GPL-3.0 license\n\"\"\"\nPyTorch Hub models https://pytorch.org/hub/ultralytics_yolov5/\n\nUsage:\n import torch\n model = torch.hub.load('ultralytics/yolov5', 'yolov5s')\n\"\"\"\n\nimport torch\n\n\ndef _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbos... | [
[
"torch.cuda.is_available",
"numpy.zeros"
]
] |
gongyu/tensorflow | [
"c230f52807b7670bbe3fe27746c3a232a538ac6c",
"c230f52807b7670bbe3fe27746c3a232a538ac6c"
] | [
"tensorflow/contrib/tensoropt/python/ops/topt_engine_op.py",
"tensorflow/contrib/kernel_methods/python/kernel_estimators_test.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n# Copyright (C) Codeplay Software Limited\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... | [
[
"tensorflow.python.platform.resource_loader.get_path_to_datafile"
],
[
"tensorflow.python.platform.googletest.main",
"numpy.log",
"tensorflow.python.framework.constant_op.constant",
"tensorflow.contrib.layers.real_valued_column",
"tensorflow.contrib.kernel_methods.python.mappers.random... |
seyyaw/flair | [
"46569a611c6acff739e3c04e78d64f824011e483"
] | [
"flair/embeddings/token.py"
] | [
"import hashlib\nimport inspect\nimport logging\nimport os\nimport re\nfrom abc import abstractmethod\nfrom collections import Counter\nfrom pathlib import Path\nfrom typing import List, Union, Dict, Optional\n\nimport gensim\nimport numpy as np\nimport torch\nfrom bpemb import BPEmb\nfrom torch import nn\nfrom tra... | [
[
"torch.cat",
"torch.nn.LSTM",
"torch.stack",
"torch.enable_grad",
"torch.nn.utils.rnn.pack_padded_sequence",
"torch.nn.LayerNorm",
"torch.FloatTensor",
"torch.tensor",
"torch.zeros_like",
"torch.zeros",
"torch.device",
"torch.min",
"numpy.zeros",
"torch.max"... |
giwankim/precipitation-nowcasting | [
"4ddcd55fecb71bf51f963dd088f43548ea1fa479"
] | [
"src/loss.py"
] | [
"import torch\n\n\nclass LogCoshLoss(torch.nn.Module):\n def __init__(self):\n super().__init__()\n\n def forward(self, inp, targ, epsilon=1e-12):\n error = inp - targ\n return torch.mean(torch.log(torch.cosh(error + epsilon)))\n"
] | [
[
"torch.cosh"
]
] |
nlakshmanan/Transformer | [
"4562f8e9b282d0a70f26903a7b4410cb6132364b",
"4562f8e9b282d0a70f26903a7b4410cb6132364b"
] | [
"train21_v.py",
"Beam.py"
] | [
"import argparse\nimport time\nimport torch\nimport os\nimport shutil\nfrom Models_v import get_model\nfrom Process21 import *\nimport torch.nn.functional as F\nfrom Optim import CosineWithRestarts\nfrom Batch21 import create_masks\nimport dill as pickle\nimport torch\nimport torch.nn as nn\nimport numpy as np\nimp... | [
[
"matplotlib.use",
"torch.zeros",
"torch.cat",
"numpy.savetxt",
"matplotlib.pyplot.savefig",
"torch.no_grad",
"matplotlib.pyplot.plot",
"torch.cuda.get_device_name",
"sklearn.metrics.accuracy_score",
"matplotlib.pyplot.figure",
"torch.cuda.device_count",
"torch.cuda.... |
dpai/workshop | [
"7dbe7989fa99e88544da8bf262beec907c536093"
] | [
"07_train/privacy/tensorflow_privacy/privacy/membership_inference_attack/utils_tensorboard.py"
] | [
"# Copyright 2020, The TensorFlow Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable ... | [
[
"tensorflow.compat.v1.Summary"
]
] |
TruongThuyLiem/keras2tensorflow | [
"726f2370160701081cb43fbd8b56154c10d7ad63",
"726f2370160701081cb43fbd8b56154c10d7ad63",
"34cfac4a889e2c973651c1c07740ea0908542d68"
] | [
"python3/lib/python3.6/site-packages/tensorflow/_api/v1/config/optimizer/__init__.py",
"python3/lib/python3.6/site-packages/tensorflow/python/keras/api/keras/applications/mobilenet/__init__.py",
"python3/lib/python3.6/site-packages/tensorflow_estimator/python/estimator/head/multi_class_head.py"
] | [
"# This file is MACHINE GENERATED! Do not edit.\n# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.\n\"\"\"Public API for tf.config.optimizer namespace.\n\"\"\"\n\nfrom __future__ import print_function as _print_function\n\nfrom tensorflow.python.framework.config import get_optimizer... | [
[
"tensorflow.python.util.deprecation_wrapper.DeprecationWrapper"
],
[
"tensorflow.python.util.deprecation_wrapper.DeprecationWrapper"
],
[
"tensorflow.python.keras.utils.losses_utils.compute_weighted_loss",
"tensorflow.python.ops.lookup_ops.index_to_string_table_from_tensor",
"tensorflo... |
Nir3usHaHaHa/2019-ICML-COMIC | [
"98235977820f3391c49aa79fd63ed41e895b4a1c",
"98235977820f3391c49aa79fd63ed41e895b4a1c"
] | [
"COMIC-release/code/edgeConstruction.py",
"COMIC-release/code/data.py"
] | [
"import numpy as np\n\ndef kNN(X, k, measure='euclidean'):\n \"\"\"\n Construct pairwise weights by finding the k nearest neighbors to each point\n and assigning a Gaussian-based distance.\n\n Parameters\n ----------\n X : [n_samples, n_dim] array\n k : int\n number of neighbors for each... | [
[
"numpy.zeros_like",
"scipy.sparse.find",
"numpy.asarray",
"numpy.zeros",
"numpy.ones",
"numpy.arange",
"scipy.sparse.triu",
"numpy.argsort",
"scipy.sparse.csgraph.minimum_spanning_tree",
"numpy.argpartition",
"scipy.spatial.distance.cdist"
],
[
"numpy.array",
... |
MarcWong/pytorch-deeplab-xception | [
"a9496f62248936149fa028f5ada54a6b1bad77b9"
] | [
"modeling/deeplab.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d\nfrom modeling.aspp import build_aspp\nfrom modeling.decoder import build_decoder\nfrom modeling.backbone import build_backbone\nfrom modeling.module import *\n\nclass ClassMo... | [
[
"torch.nn.Linear",
"torch.rand",
"torch.nn.Dropout",
"torch.nn.AdaptiveMaxPool2d"
]
] |
simon-ball/opexebo | [
"8e44a4890efa60a6ed8c2e9e0df7cc9ab2d80d31"
] | [
"opexebo/general/fit_ellipse.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Jun 4 11:37:57 2019\n\n@author: simoba\n\"\"\"\n\nimport numpy as np\n\n\ndef fit_ellipse(X, Y):\n '''\n Fit an ellipse to the provided set of X, Y co-ordinates\n\n Based on the approach taken in\n Authors: Andrew Fitzgibbon, Maurizio Pilu, Bob Fisher\n ... | [
[
"numpy.concatenate",
"numpy.max",
"numpy.sin",
"numpy.zeros",
"numpy.ones",
"numpy.real",
"numpy.mean",
"numpy.min",
"numpy.sign",
"numpy.arctan2",
"numpy.cos",
"numpy.isfinite",
"numpy.abs",
"numpy.linalg.inv"
]
] |
bao17634/cnn_captcha | [
"98f7689521f77946f0c2177c7b6d970bc7521192",
"98f7689521f77946f0c2177c7b6d970bc7521192"
] | [
"cnnlib/network.py",
"image_binarized.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport cv2 as cv\n\n\nclass CNN(object):\n def __init__(self, image_height, image_width, max_captcha, char_set, model_save_dir):\n # 初始值\n self.image_height = image_height\n self.image_width = image_width\n self.max_captcha = max_captcha\n... | [
[
"tensorflow.nn.conv2d",
"numpy.zeros",
"tensorflow.contrib.layers.xavier_initializer",
"tensorflow.random_normal",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.placeholder",
"tensorflow.name_scope",
"tensorflow.nn.max_pool",
"tensorflow.nn.dropout"
],
[
"n... |
w6688j/nl2sql_baseline | [
"f4e3de24347884b3c117bb0c9def028caeb8e3f5"
] | [
"sqlnet/model/modules/aggregator_predict.py"
] | [
"import json\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\nimport numpy as np\nfrom sqlnet.model.modules.net_utils import run_lstm, col_name_encode\n\n\n\nclass AggPredictor(nn.Module):\n def __init__(self, N_word, N_h, N_depth, use_ca):\n supe... | [
[
"torch.nn.Linear",
"torch.nn.Tanh",
"torch.stack",
"torch.nn.Softmax"
]
] |
MihaiAnton/tudelft-iic-reproduction | [
"342247c444aa1f8b09ea18e3ff9135258d599373",
"342247c444aa1f8b09ea18e3ff9135258d599373"
] | [
"src/scripts/cluster/analysis/overcluster_fewer_labels_greyscale_example.py",
"src/scripts/segmentation/segmentation.py"
] | [
"from __future__ import print_function\n\nimport argparse\nimport os\nimport pickle\nfrom sys import stdout as sysout\n\nimport torch\nimport torchvision\n\nimport src.archs as archs\nfrom src.utils.cluster.cluster_eval import cluster_subheads_eval\nfrom src.utils.cluster.data import _create_mapping_loader\nfrom sr... | [
[
"torch.nn.DataParallel",
"torch.load"
],
[
"matplotlib.use",
"matplotlib.pyplot.subplots",
"torch.nn.DataParallel",
"torch.zeros"
]
] |
ScottWales/cosima-cookbook | [
"0ed83e2165efe5badfca59e2dccf835ab7acecca"
] | [
"test/test_querying.py"
] | [
"import pytest\n\nimport os.path\nimport xarray as xr\nimport pandas as pd\nfrom pandas.util.testing import assert_frame_equal, assert_series_equal\n\nimport cosima_cookbook as cc\n\n@pytest.fixture(scope='module')\ndef session(tmpdir_factory):\n # index test directory into temp database\n d = tmpdir_factory.... | [
[
"pandas.DataFrame.from_dict",
"pandas.Timestamp",
"pandas.util.testing.assert_frame_equal",
"pandas.util.testing.assert_series_equal"
]
] |
lffloyd/reddit-topic-modelling | [
"b34d7095cdd3ee66dfd95f8319f078449213e26f"
] | [
"postprocessing/postprocess.py"
] | [
"from gensim.models import KeyedVectors\nimport numpy as np\nimport pandas as pd\nimport argparse\nimport os\nimport joblib\nimport json\nimport time\nimport logging\n\n\nLOG_FOLDER = \"pipeline_logs/\"\n\nparser = argparse.ArgumentParser(description='Postprocessing of trained models')\nparser.add_argument('--lang'... | [
[
"numpy.multiply",
"pandas.read_csv",
"numpy.mean"
]
] |
zetayue/prof_dev | [
"ccae1e16826b24c46792fb850f20be55626b7e32"
] | [
"transform_nets.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport sys\nimport os\nBASE_DIR = os.path.dirname(os.path.abspath(__file__))\nsys.path.append(BASE_DIR)\nsys.path.append(os.path.join(BASE_DIR, '../utils'))\nimport tf_util\n\ndef input_transform_net(point_cloud, is_training, bn_decay=None, K=3):\n \"\"\" Input (XYZ)... | [
[
"tensorflow.constant_initializer",
"tensorflow.expand_dims",
"tensorflow.matmul",
"tensorflow.reshape",
"numpy.eye",
"tensorflow.variable_scope",
"tensorflow.nn.bias_add"
]
] |
Jacob-L-Vincent/project-athena | [
"d1d300e375941399f116cbaa4678a9ed7c6652db"
] | [
"Task2/IGNORE_miscellaneousScripts/getPredictions_weakDefenses_old.py"
] | [
"#########################################################\n## generate the ensemble predictions for task 2 ##\n## created by Isaac Keohane isaackeohane95@gmail.com ##\n#########################################################\n\nimport os\nimport sys\nmodule_path = os.path.abspath(os.path.join('../src'))\... | [
[
"numpy.load",
"numpy.save"
]
] |
Starrah/THU-SuperMoon | [
"9394cb5ca31d28df715039ba6e8b4dd852192f71",
"9394cb5ca31d28df715039ba6e8b4dd852192f71"
] | [
"examples/segmentation/heart_mri/train.py",
"SuperMoon/hygraph/fusion.py"
] | [
"import os.path as osp\n\nimport torch\nimport torch.nn.functional as F\nfrom data_helper import preprocess, split_train_val\n\nfrom SuperMoon.models import HGNN\nfrom SuperMoon.utils import check_dir\nfrom SuperMoon.utils.meter import trans_class_acc, trans_iou_socre\nfrom SuperMoon.utils.visualization import tran... | [
[
"torch.nn.functional.nll_loss",
"torch.cuda.is_available"
],
[
"torch.cat"
]
] |
bkntr/napari-bigwarp | [
"12171a96bc9a753f6ea9dc5d5e311360e759b555"
] | [
"src/napari_bigwarp/_bigwarp_widget.py"
] | [
"\"\"\"\nThis module is an example of a barebones QWidget plugin for napari\n\nIt implements the ``napari_experimental_provide_dock_widget`` hook specification.\nsee: https://napari.org/docs/dev/plugins/hook_specifications.html\n\nReplace code below according to your needs.\n\"\"\"\nimport magicgui\nimport napari\n... | [
[
"numpy.zeros"
]
] |
FlorisHoogenboom/agents | [
"2cd5a61e1838b52012271f1fb8617c29a55279a9",
"2cd5a61e1838b52012271f1fb8617c29a55279a9",
"2cd5a61e1838b52012271f1fb8617c29a55279a9"
] | [
"tf_agents/environments/parallel_py_environment.py",
"tf_agents/utils/nest_utils_test.py",
"tf_agents/environments/test_envs.py"
] | [
"# coding=utf-8\n# Copyright 2018 The TF-Agents Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required b... | [
[
"tensorflow.nest.pack_sequence_as",
"numpy.stack",
"tensorflow.nest.flatten"
],
[
"tensorflow.SparseTensorSpec",
"tensorflow.nest.pack_sequence_as",
"tensorflow.convert_to_tensor",
"tensorflow.zeros",
"tensorflow.compat.v1.global_variables_initializer",
"numpy.array",
"... |
stefangri/SMD | [
"4d46e86ef1a6bcff81e8fb2c3cf41948132926b9"
] | [
"Blatt06/ml/solutions/exercise_5.py"
] | [
"from sklearn.model_selection import cross_validate\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.svm import SVC\n\nnp.random.seed(1234)\ndata = read_titanic()\n\nX = data[['Sex_Code', 'Pclass_Code', 'Fare', 'Age']]\ny = data['Survived_Code']\n\ns... | [
[
"sklearn.model_selection.cross_validate",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.svm.SVC"
]
] |
moboehle/B-cos | [
"5f9218f6773534c80367793d1cd767742869764a"
] | [
"interpretability/explanation_methods/explainers/lime.py"
] | [
"#\n# Adapted from https://github.com/marcotcr/lime/blob/master/doc/notebooks/Tutorial%20-%20images%20-%20Pytorch.ipynb\n#\n\nimport copy\n\nimport numpy as np\nimport torch\nfrom lime import lime_image\nfrom lime.wrappers.scikit_image import SegmentationAlgorithm\n\nfrom interpretability.explanation_methods.ut... | [
[
"numpy.array",
"numpy.zeros",
"torch.no_grad",
"torch.from_numpy",
"numpy.where",
"numpy.unique"
]
] |
sthagen/giswqs-leafmap | [
"be6ccdfa5450b775724547b6ef50f213c820be85"
] | [
"leafmap/plotlymap.py"
] | [
"import os\nimport numpy as np\nimport pandas as pd\nimport ipywidgets as widgets\nfrom .basemaps import xyz_to_plotly\nfrom .common import *\nfrom .osm import *\nfrom . import examples\n\ntry:\n import plotly.express as px\n import plotly.graph_objects as go\nexcept ImportError:\n raise ImportError(\n ... | [
[
"numpy.random.random",
"pandas.read_csv"
]
] |
nakamotoo/lifelong_rl | [
"a8376a57cdeff158810e71cd31cba089852399b7",
"a8376a57cdeff158810e71cd31cba089852399b7"
] | [
"lifelong_rl/trainers/q_learning/sac.py",
"scripts/viz_hist.py"
] | [
"import numpy as np\nimport torch\nimport torch.optim as optim\nfrom torch import nn as nn\n\nfrom collections import OrderedDict\n\nimport lifelong_rl.torch.pytorch_util as ptu\nfrom lifelong_rl.torch.distributions import TanhNormal\nfrom lifelong_rl.util.eval_util import create_stats_ordered_dict\nfrom lifelong_r... | [
[
"numpy.prod",
"torch.exp",
"torch.nn.MSELoss"
],
[
"torch.load"
]
] |
sooftware/oslo | [
"f51d3fd95b3a0341c9d1a7de1df22b3e5a6afd7d",
"f51d3fd95b3a0341c9d1a7de1df22b3e5a6afd7d",
"f51d3fd95b3a0341c9d1a7de1df22b3e5a6afd7d"
] | [
"tests/gpt2/gpt2_test_3d_inference.py",
"tests/gpt_neo/gpt_neo_test_tp_training_with_ddp.py",
"tests/gpt2/gpt2_test_tp_inference.py"
] | [
"# Copyright 2021 TUNiB Inc.\n\nimport torch\nimport torch.distributed as dist\nfrom transformers import GPT2Tokenizer\n\nfrom oslo.models.gpt2.modeling_gpt2 import (\n GPT2ForSequenceClassification,\n GPT2LMHeadModel,\n GPT2Model,\n)\n\n\nclass Test3DInference:\n def __init__(self, num_gpus):\n ... | [
[
"torch.distributed.get_rank",
"torch.no_grad",
"torch.isclose"
],
[
"numpy.random.seed",
"torch.nn.parallel.DistributedDataParallel",
"torch.cuda.current_device",
"torch.manual_seed",
"torch.utils.data.distributed.DistributedSampler",
"torch.distributed.get_rank"
],
[
... |
joshspicer/pvscc-logo | [
"7113c26bd760d9a206263ff5b2aba69804379484"
] | [
"logo_app/generate_logo.py"
] | [
"import base64\nimport io\nimport pathlib\nfrom os import path\n\nimport httpx\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom bs4 import BeautifulSoup as bs\nfrom PIL import Image\nfrom wordcloud import STOPWORDS, ImageColorGenerator, WordCloud\n\n\ndef generate_fig(url, mask_path):\n logo_path = mas... | [
[
"matplotlib.pyplot.axis",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots"
]
] |
LearningChanging/Data-analysis-in-action | [
"b09259a212f88bf88745b05efbfbeea210812e53"
] | [
"41-数据挖掘实战（3）：如何对比特币走势进行预测？/shanghai_analysis.py"
] | [
"# 比特币走势预测，使用时间序列ARMA\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom statsmodels.tsa.arima_model import ARMA\nimport warnings\nfrom itertools import product\nfrom datetime import datetime\n\nwarnings.filterwarnings('ignore')\n# 数据加载\ndf = pd.read_csv('./shanghai_1990-12-19_to_2019-2-28.csv')\n# 将时间作为df... | [
[
"pandas.to_datetime",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.suptitle",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"pandas.concat",
"matplotlib.pypl... |
googleinterns/betel | [
"2daa56081ccc753f5b7eafbd1e9a48e3aca4b657"
] | [
"betel/classifier_data_set_builder.py"
] | [
"import shutil\nimport pathlib\nfrom typing import List, Optional\nimport pandas as pd\nfrom betel import utils\nfrom betel import info_files_helpers\nfrom betel import data_set_builder\n\n\nclass ClassifierDataSetBuilder(data_set_builder.DataSetBuilder):\n \"\"\"A class for splitting classifier data into train-... | [
[
"pandas.DataFrame"
]
] |
JAV27/Coop-Games | [
"37eb9bb05cc56a663a15e6faa8f1dc7b4595495c"
] | [
"compute_sv.py"
] | [
"import numpy as np\nfrom wvg import wvg\nfrom itertools import combinations\nimport math\n\n# Generates the dynamic programming table required in order to \n# compute the Shapley value in weighted voting games.\n\n# The returned table is of dimensions n-1 x w(N) x n-1\n# where the X[j][w][s] entry has the number o... | [
[
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.math.factorial",
"numpy.append"
]
] |
jmaces/keras-adf | [
"e86cde14fd09a6c6cdaa5b5eebb5ae725bedc76d"
] | [
"tests/test_activations.py"
] | [
"\"\"\"Tests for `kerasadf.activations`. \"\"\"\nfrom __future__ import absolute_import, division, print_function\n\nimport numpy as np\nimport pytest\n\nfrom hypothesis import given\nfrom tensorflow.keras import backend as K\n\nimport kerasadf.activations\nimport kerasadf.layers\n\nfrom .strategies import assert_e... | [
[
"numpy.zeros_like",
"numpy.prod",
"tensorflow.keras.backend.placeholder",
"tensorflow.keras.backend.clear_session"
]
] |
prsalm/Kats | [
"786a2d81193fda2ffc6d90d0e8b4d52600ce8ee7"
] | [
"kats/tests/detectors/test_threshold_detector.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom unittest import TestCase\n\nimport numpy as np\nimport pandas as pd\nfrom kats.consts import TimeSeriesData\nfrom kats.detectors.t... | [
[
"numpy.random.seed",
"numpy.random.normal",
"pandas.date_range",
"pandas.DataFrame"
]
] |
sumit-pahwa/simpleScreenScraper | [
"e05d895b8b9c40966da73e60dc3117eb5444bd3f"
] | [
"simpleScreenScraper.py"
] | [
"import argparse\nimport sys\nimport time\nimport selenium\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\nimport pandas\nimport csv\n\ndef main():\n\n #instant... | [
[
"pandas.read_csv"
]
] |
volpatto/py-pde | [
"770183562235179914b2ac67c6236a9f38bb98ea"
] | [
"pde/pdes/allen_cahn.py"
] | [
"\"\"\"\nA Allen-Cahn equation\n\n.. codeauthor:: David Zwicker <david.zwicker@ds.mpg.de> \n\"\"\"\n\nfrom typing import Callable # @UnusedImport\n\nimport numpy as np\n\nfrom ..fields import ScalarField\nfrom ..grids.boundaries.axes import BoundariesData\nfrom ..tools.docstrings import fill_in_docstring\nfrom ..t... | [
[
"numpy.empty"
]
] |
mehdihosseinimoghadam/Complex-Neural-Networks | [
"7f1135d5c6e23113c43f5a9d9aa3d257bf0770de"
] | [
"Complex_Google_Inception.py"
] | [
"\"\"\"\nComplex Valued Google Inception From Scratch\nProgrammed by Mehdi Hosseini Moghadam\n\nThe Base Code Of Google Inception Has Been Taken From:\n https://github.com/aladdinpersson\n\n* MIT Licence\n* 2022-02-15 Last Update\n\"\"\"\n\n\n\nimport torch\nfrom torch import nn\nfrom complex_neural_net imp... | [
[
"torch.nn.ReLU",
"torch.nn.Dropout"
]
] |
jayleicn/moment_detr | [
"a5d0fa0f0b9ab005cf277327da0cb81ac1455194"
] | [
"moment_detr/model.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\"\"\"\nDETR model and criterion classes.\n\"\"\"\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn\n\nfrom moment_detr.span_utils import generalized_temporal_iou, span_cxw_to_xx\n\nfrom moment_detr.matcher import build_matc... | [
[
"torch.nn.Linear",
"torch.device",
"torch.cat",
"torch.nn.LayerNorm",
"torch.nn.Dropout",
"torch.einsum",
"torch.nn.Sequential",
"torch.nn.functional.l1_loss",
"torch.clamp",
"torch.ones",
"torch.full_like",
"torch.nn.functional.cross_entropy",
"torch.full",
... |
Bhaskers-Blu-Org1/complex-linear-network-analyzer | [
"b336a4fca1222a4f284bb39c6c3e6bec402f5efa"
] | [
"examples/symbolicfeedforwardwithtestbench.py"
] | [
"# +-----------------------------------------------------------------------------+\n# | Copyright 2019-2020 IBM Corp. All Rights Reserved. |\n# | |\n# | Licensed under the Apache License, Version 2.0 (the \"License... | [
[
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.ylabel",
"numpy.abs",
"matplotlib.pyplot.show",
"numpy.linspace"
]
] |
BernhardRiemann/GameAISDK | [
"208320760440400d369aa8ab2f2439494195e6bd"
] | [
"tools/SDKTool/bin/ActionSampler/pymodules/actionsampler/ADBEventParser.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nThis source code file is licensed under the GNU General Public License Version 3.\nFor full details, please refer to the file \"LICENSE.txt\" which is provided as part of this source code package.\nCopyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.\n\"\"\"... | [
[
"numpy.array"
]
] |
ssss1029/ethics | [
"e555c81d347a56532f618dca5918acc89f69f278"
] | [
"justice/tune.py"
] | [
"import os\nimport sys\nsys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))\nfrom utils import *\nimport numpy as np\nimport argparse\nfrom itertools import product\nfrom torch.utils.data import DataLoader\n\ndef main(args):\n test_hard_accs = []\n test_accs = []\n test_hard_ems = ... | [
[
"numpy.max",
"torch.utils.data.DataLoader",
"numpy.mean"
]
] |
youngster-all/Finger-Detection-and-Tracking | [
"a96701b6cb66d29f906771c5bc14bcb2eb975ceb"
] | [
"OpenCV models/BlurDialationErosion.py"
] | [
"import cv2\nimport numpy as np\n\n\ndef main():\n kernal = np.ones((5, 5), np.uint8)\n\n image = cv2.imread(\"../data/4.2.05.tiff\", 1)\n\n blurimage = cv2.GaussianBlur(image, (15, 15), 0)\n\n dialate = cv2.dilate(image, kernal, iterations=1)\n erosion = cv2.erode(image, kernal, iterations=1)\n\n ... | [
[
"numpy.ones"
]
] |
moazzamwaheed2017/carparkapi | [
"e52ae1b2aed47321ce9d22ba6cd0b85fa60a417a"
] | [
"CarParkArcGisApi/CarParkArcGisApi/env/Lib/site-packages/arcgis/gis/admin/_usage.py"
] | [
"\"\"\"\nProvides functions to gather usage statistics for Portal/ArcGIS Online\n\"\"\"\nimport os\nimport datetime\nfrom ..._impl.connection import _ArcGISConnection\nfrom ..._impl.common._mixins import PropertyMap\nfrom ..._impl.common._utils import local_time_to_online, timestamp_to_datetime\nfrom ...gis import ... | [
[
"pandas.DataFrame.from_records"
]
] |
the-nose-knows/pandas | [
"dcf7137ccc81986091b6c76624855bb5c32185f7",
"dcf7137ccc81986091b6c76624855bb5c32185f7"
] | [
"pandas/tests/frame/test_nonunique_indexes.py",
"pandas/tests/indexes/test_common.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom __future__ import print_function\n\nimport numpy as np\nimport pytest\n\nfrom pandas.compat import lrange, u\n\nimport pandas as pd\nfrom pandas import DataFrame, MultiIndex, Series, date_range\nfrom pandas.tests.frame.common import TestData\nimport pandas.util.testing as tm\nfrom p... | [
[
"pandas.util.testing.assert_numpy_array_equal",
"numpy.array",
"numpy.random.rand",
"pandas.util.testing.assert_frame_equal",
"pandas.merge",
"pandas.Timedelta",
"pandas.compat.u",
"pandas.DataFrame",
"pandas.date_range",
"numpy.random.randn",
"pandas.MultiIndex.from_tu... |
SeanChen0220/learnable-triangulation-pytorch | [
"780774442c78b8e43d36bbc054346188f95af835"
] | [
"mvn/pipeline/training.py"
] | [
"import os\nimport torch\n\nfrom torch.nn.parallel import DistributedDataParallel\n\nfrom mvn.utils.misc import live_debug_log\nfrom mvn.pipeline.core import one_epoch\nfrom mvn.pipeline.setup import setup_dataloaders, setup_experiment, build_env\nfrom mvn.utils.minimon import MiniMon\n\n\ndef do_train(config_path,... | [
[
"torch.nn.parallel.DistributedDataParallel"
]
] |
mulkkyul/lstm-initStates | [
"f71514118b174410048cc82431bf232af80f7379"
] | [
"myDataloader.py"
] | [
"import torch\r\nfrom torch.utils.data import Dataset, DataLoader\r\nfrom torch.nn.utils.rnn import pad_sequence\r\nimport numpy as np\r\nimport glob, os\r\n\r\nclass myDataset(Dataset):\r\n def __init__(self, data):\r\n self.data_input, self.data_label = data\r\n def __getitem__(self, index):\r\n ... | [
[
"torch.nn.utils.rnn.pad_sequence",
"numpy.loadtxt",
"torch.utils.data.DataLoader"
]
] |
dstoeckel/MOE | [
"5b5a6a2c6c3cf47320126f7f5894e2a83e347f5c"
] | [
"moe/bandit/bla/bla.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Classes (Python) to compute the Bandit BLA (Bayesian Learning Automaton) arm allocation and choose the arm to pull next.\n\nSee :class:`moe.bandit.bandit_interface` for further details on bandits.\n\n\"\"\"\nimport copy\n\nimport numpy\n\nfrom moe.bandit.constant import DEFAULT_BLA_S... | [
[
"numpy.random.beta"
]
] |
SaraLatif99/ML_GUI | [
"2ffdd198577f612610c5de4017c1a9067a9a0863"
] | [
"codes/data_visualise.py"
] | [
"import pandas as pd \nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport numpy as np \nfrom sklearn.preprocessing import LabelEncoder,StandardScaler,MinMaxScaler,PowerTransformer\nimport add_steps\nclass data_:\n\t\n\t\n\t\n\tdef read_file(self,filepath):\n\t\t\n\t\treturn pd.read_csv(str(filepath))\n\... | [
[
"sklearn.preprocessing.LabelEncoder",
"numpy.ones_like",
"sklearn.preprocessing.PowerTransformer",
"sklearn.preprocessing.StandardScaler",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"matpl... |
currysesame/linear_programming_question_1 | [
"1b29f51dfc29e04feb69f726ffbbb0722d2eebce"
] | [
"practice.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Thu Mar 26 11:38:49 2020\r\n\r\n@author: currysesame\r\n\"\"\"\r\n\r\n\r\nimport numpy as np\r\nimport copy\r\n\r\nnphs = np.hstack\r\n# create the work table\r\nwork_sheet = np.zeros((6,64))\r\n#initialize the begining of each possible work.\r\nfor i in range(0, 32)... | [
[
"numpy.int",
"numpy.asarray",
"numpy.zeros",
"numpy.round",
"numpy.transpose",
"numpy.all"
]
] |
Mikoto10032/MachineLearning_TensorFlow | [
"398acabb892607adf7795c34962bc75aba9d4afc"
] | [
"TransferLearning/transferLearning_inceptionModel.py"
] | [
"#coding: utf-8\nimport numpy as np\nimport tensorflow as tf\nimport prettytensor as pt\nfrom matplotlib import pyplot as plt\nimport time\nfrom datetime import timedelta\nimport os\nimport inception # 第三方下载inception model的代码\nfrom inception import transfer_values_cache # cache\nimport cifar10 # 也是第三方的库，下载ci... | [
[
"sklearn.metrics.confusion_matrix",
"numpy.random.choice",
"tensorflow.initialize_all_variables",
"numpy.zeros",
"tensorflow.train.AdamOptimizer",
"tensorflow.argmax",
"tensorflow.equal",
"tensorflow.Variable",
"sklearn.manifold.TSNE",
"tensorflow.Session",
"matplotlib.... |
mathislucka/haystack | [
"180befd07a7b28ed858a0c33fa17cee60fd4d973"
] | [
"haystack/document_stores/faiss.py"
] | [
"from typing import TYPE_CHECKING\n\nif TYPE_CHECKING:\n from haystack.nodes.retriever import BaseRetriever\n\nimport json\nimport logging\nfrom pathlib import Path\nfrom typing import Union, List, Optional, Dict, Generator\nfrom tqdm.auto import tqdm\n\ntry:\n import faiss\nexcept ImportError:\n faiss = N... | [
[
"numpy.array"
]
] |
ishitatsuyuki/incubator-tvm | [
"35854c18b04cb6bee092fdc2aa8be5082ae0dd48"
] | [
"tests/python/frontend/onnx/test_forward.py"
] | [
"# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); y... | [
[
"torch.nn.Linear",
"numpy.arccos",
"numpy.random.choice",
"numpy.random.rand",
"numpy.argmin",
"numpy.tan",
"numpy.tile",
"numpy.min",
"numpy.mean",
"numpy.exp",
"numpy.where",
"numpy.sign",
"numpy.cos",
"numpy.random.random",
"numpy.dtype",
"numpy.m... |
mapoulin/aoc-2021 | [
"63af47cdcd9aad6583d7f30d1b2b5d705fb07bc3"
] | [
"d5/main.py"
] | [
"#!/usr/bin/env python3\n\nimport re\nfrom os.path import dirname, abspath\nfrom aoc_utils import read_input\nfrom functools import reduce\nimport numpy as np\n\nDAY = re.search(\"d([0-9]+)\", dirname(abspath(__file__))).group(1) # d[0-9]+ -> [0-9]+\n\ndef solve(data):\n coordinates = parse_input(data)\n\n sh... | [
[
"numpy.count_nonzero",
"numpy.zeros",
"numpy.add.at"
]
] |
mens-artis/Auto-PyTorch | [
"da8528d5cb1d5ac6a9050eaa84a332a5a11ee6d5",
"da8528d5cb1d5ac6a9050eaa84a332a5a11ee6d5"
] | [
"examples/real_data/openml_task.py",
"test/test_pipeline/test_normalization_strategy_selector.py"
] | [
"import openml\nfrom pprint import pprint\nfrom autoPyTorch import AutoNetClassification\nfrom sklearn.metrics import accuracy_score\n\n\n# get OpenML task by its ID\ntask = openml.tasks.get_task(task_id=32)\nX, y = task.get_X_and_y()\nind_train, ind_test = task.get_train_test_split_indices()\n\n\n# run Auto-PyTorc... | [
[
"sklearn.metrics.accuracy_score"
],
[
"numpy.testing.assert_array_almost_equal",
"numpy.array"
]
] |
Ewen2015/BatCat | [
"9e81626c503629ba1c3d3f83b332eeaafcc6bd11"
] | [
"build/lib/batcat/core.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n\"\"\"\nauthor: Ewen Wang\nemail: wolfgangwong2012@gmail.com\nlicense: Apache License 2.0\n\"\"\"\nfrom io import StringIO, BytesIO\nfrom datetime import datetime\nimport pandas as pd\nimport boto3\n\ns3 = boto3.client('s3')\n\n\ndef print_event(event)... | [
[
"pandas.read_sql"
]
] |
ForrestLin0805/rqalpha | [
"b10d03f9a23180a93e39c40fcb048ba6db37b573"
] | [
"rqalpha/data/base_data_source/storages.py"
] | [
"# -*- coding: utf-8 -*-\n# 版权所有 2019 深圳米筐科技有限公司（下称“米筐科技”）\n#\n# 除非遵守当前许可，否则不得使用本软件。\n#\n# * 非商业用途（非商业用途指个人出于非商业目的使用本软件，或者高校、研究所等非营利机构出于教育、科研等目的使用本软件）：\n# 遵守 Apache License 2.0（下称“Apache 2.0 许可”），您可以在以下位置获得 Apache 2.0 许可的副本：http://www.apache.org/licenses/LICENSE-2.0。\n# 除非法律有要求或以书面形式达成协议，否则本软件分发... | [
[
"numpy.load"
]
] |
BrilliantYuKaimin/Paddle | [
"133d63fa5c840213df6b7f3f3966f79011370b48"
] | [
"python/paddle/fluid/layers/nn.py"
] | [
"# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless re... | [
[
"numpy.array",
"numpy.prod",
"numpy.random.randint",
"numpy.asscalar"
]
] |
Hoeppke/PyODESolver | [
"a1c387ff029c84ed7318383a80fea961b796f12e"
] | [
"pyodesolver/method_explicit_euler_test.py"
] | [
"from method_explicit_euler import ExplicitEuler\nfrom rhs_function import ExampleFunc01\nfrom rhs_function import ExampleFunc01_solution\nfrom rhs_function import ExampleFunc02\nfrom rhs_function import ExampleFunc02_solution\nimport numpy as np\nimport unittest\n\n\nclass TestExplicitEulerMethod(unittest.TestCase... | [
[
"numpy.zeros_like",
"numpy.array",
"numpy.linspace",
"numpy.abs"
]
] |
yukatayu/incubator-tvm | [
"02643d39798c6ec28348235d36d8da626f50d9dd"
] | [
"tests/python/frontend/tensorflow/test_forward.py"
] | [
"# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); y... | [
[
"numpy.random.choice",
"tensorflow.image.non_max_suppression",
"tensorflow.python.ops.math_ops.matmul",
"tensorflow.ones",
"tensorflow.Dimension",
"tensorflow.zeros_like",
"tensorflow.clip_by_value",
"tensorflow.stack",
"tensorflow.python.ops.array_ops.unravel_index",
"tens... |
hssinejihene/deepchem | [
"7b5177240eb85a68819b4450635ec9df54afed23"
] | [
"deepchem/feat/tests/test_graph_data.py"
] | [
"import unittest\nimport pytest\nimport numpy as np\nfrom deepchem.feat.graph_data import GraphData, BatchGraphData\n\n\nclass TestGraph(unittest.TestCase):\n\n def test_graph_data(self):\n num_nodes, num_node_features = 5, 32\n num_edges, num_edge_features = 6, 32\n node_features = np.random.random_sampl... | [
[
"numpy.array",
"numpy.random.random_sample"
]
] |
SquarerFive/pyfastnoisesimd | [
"6ef0abe497433d636e3bfb6c0b1ba74d4b3acdc4"
] | [
"pyfastnoisesimd/helpers.py"
] | [
"import pyfastnoisesimd.extension as ext\r\nimport concurrent.futures as cf\r\nimport numpy as np\r\nfrom enum import Enum\r\n\r\n_MIN_CHUNK_SIZE = 8192\r\n\r\ndef empty_aligned(shape, dtype=np.float32, n_byte=ext.SIMD_ALIGNMENT):\r\n \"\"\"\r\n Provides an memory-aligned array for use with SIMD accelerated i... | [
[
"numpy.product",
"numpy.ceil",
"numpy.empty",
"numpy.minimum",
"numpy.random.randint",
"numpy.int32",
"numpy.dtype"
]
] |
jie311/TraDeS | [
"896491a159abe65f61c6ad05662cda6e28d137a6",
"896491a159abe65f61c6ad05662cda6e28d137a6",
"896491a159abe65f61c6ad05662cda6e28d137a6"
] | [
"src/tools/remove_optimizers.py",
"src/tools/nuscenes-devkit/eval/tracking/algo.py",
"src/tools/nuscenes-devkit/map_expansion/tests/test_arcline_path_utils.py"
] | [
"import os\nimport torch\nOUT_PATH = '../../models/'\nREMOVE_KEYS = ['base.fc']\n\nif __name__ == '__main__':\n models = sorted(os.listdir(IN_PATH))\n for model in models:\n model_path = IN_PATH + model\n print(model)\n data = torch.load(model_path)\n state_dict = data['state_dict']\n keys = state_... | [
[
"torch.save",
"torch.load"
],
[
"numpy.max",
"numpy.array",
"numpy.isnan",
"numpy.sum",
"numpy.ones",
"numpy.interp",
"sklearn.metrics.pairwise.euclidean_distances",
"pandas.concat",
"numpy.linspace",
"numpy.unique"
],
[
"numpy.testing.assert_allclose",
... |
SidewayOutput/Basic-Manim | [
"4dea4b00daa7b6f66ed7b26659045f67609d83b6"
] | [
"manimlib/mobject/mobject.py"
] | [
"from functools import reduce\nimport copy\nimport itertools as it\nimport operator as op\nimport os\nimport random\nimport sys\nfrom functools import wraps\n\nfrom colour import Color\nimport numpy as np\n\nfrom manimlib.utils.directories import get_output_dir\nfrom manimlib.constants import WHITE,XYZ,RU,OUT,ORIGI... | [
[
"numpy.max",
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.min",
"numpy.identity",
"numpy.sign",
"numpy.apply_along_axis",
"numpy.transpose",
"numpy.arange",
"numpy.abs",
"numpy.append",
"numpy.all",
"numpy.linspace"
]
] |
vinhsuhi/Graph-Optimal-Transport | [
"cdf21acd8500b92c222418f2546c3d36890a4fa3"
] | [
"BAN_vqa/base_model.py"
] | [
"\"\"\"\nBilinear Attention Networks\nJin-Hwa Kim, Jaehyun Jun, Byoung-Tak Zhang\nhttps://arxiv.org/abs/1805.07932\n\nThis code is written by Jin-Hwa Kim.\n\"\"\"\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.nn.utils.weight_norm import weight_norm\nimport utils\nfrom attention i... | [
[
"torch.Tensor"
]
] |
MrMonk3y/RL_from_scratch | [
"8d9ed9898a13ea945b7b5be1e9c0d32c32e63577"
] | [
"src/connect4/_version80/dqn.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Dec 2 19:55:38 2018\n\n@author: saschajecklin\n\"\"\"\n\nimport sys\nsys.path.append(\"..\")\nimport random\nimport numpy as np\nfrom collections import deque\nfrom keras.models import Model\nfrom keras.layers import Dense, Flatten, Input, Co... | [
[
"numpy.random.rand",
"numpy.zeros",
"numpy.argmax",
"numpy.expand_dims",
"numpy.flip"
]
] |
ashishpatel26/PSPNet-Keras-tensorflow | [
"53ebf9b0fddf20643c9bfb4460ee2eb2f8775ae7"
] | [
"pspnet.py"
] | [
"#!/usr/bin/env python\nfrom __future__ import print_function\nimport os\nfrom os.path import splitext, join, isfile, isdir, basename\nimport argparse\nimport numpy as np\nfrom scipy import misc, ndimage\nfrom keras import backend as K\nfrom keras.models import model_from_json, load_model\nimport tensorflow as tf\n... | [
[
"numpy.max",
"numpy.pad",
"numpy.array",
"numpy.zeros",
"tensorflow.Session",
"numpy.load",
"scipy.misc.imresize",
"numpy.fliplr",
"numpy.argmax",
"scipy.misc.imsave",
"numpy.expand_dims",
"matplotlib.pyplot.show",
"numpy.flip",
"matplotlib.pyplot.imshow"
... |
kyuhyoung/transformer-evolution | [
"fae06f677df0be55c67cd58efea158e5517ac045"
] | [
"transformer/model.py"
] | [
"import numpy as np\nimport math\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\n\"\"\" sinusoid position encoding \"\"\"\ndef get_sinusoid_encoding_table(n_seq, d_hidn):\n def cal_angle(position, i_hidn):\n return position / np.power(10000, 2 * (i_hidn // 2) / d_hidn)\n de... | [
[
"torch.nn.Linear",
"numpy.sin",
"torch.nn.Dropout",
"torch.nn.LayerNorm",
"torch.nn.Embedding.from_pretrained",
"torch.gt",
"torch.nn.Conv1d",
"torch.max",
"torch.nn.Softmax",
"numpy.power",
"numpy.cos",
"torch.load",
"torch.ones_like",
"torch.matmul",
"... |
marc345/pulp-dsp | [
"5784c235452b22b8f8310d351126ed371e3d8746"
] | [
"test/mrWolf/pulp_dsp_test.py"
] | [
"import os\nimport time\nimport random\nimport shutil\nfrom plptest import Test as PulpTest, Testset\nfrom plptest import Shell, Check\nfrom itertools import product\nfrom functools import partial\nfrom collections import OrderedDict\nfrom copy import deepcopy\nimport numpy as np\nfrom textwrap import dedent, inden... | [
[
"numpy.float32",
"numpy.random.uniform",
"numpy.random.randint",
"numpy.ones"
]
] |
davidcui79/price_models | [
"5307eebeca3d09b8d78b63586947b31ff835f5f3"
] | [
"research/object_detection/trainer.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.group",
"tensorflow.to_float",
"tensorflow.control_dependencies",
"tensorflow.identity",
"tensorflow.cast",
"tensorflow.concat",
"tensorflow.summary.histogram",
"tensorflow.train.Saver",
"tensorflow.losses.get_total_loss",
"tensorflow.ConfigProto",
"tensorfl... |
AnesBenmerzoug/Machine-Learning-Projects | [
"c52b3f55968c042a20299473fb124b75cc410ce0"
] | [
"STL10/src/tester.py"
] | [
"import torch\nfrom torch.autograd import Variable\nfrom torch.utils.data import DataLoader\nfrom torchvision.datasets import STL10\nfrom torchvision.transforms import transforms\nfrom src.model import STL10_Network\nfrom collections import namedtuple\nimport random\n\n\nclass STL10Tester(object):\n def __init__... | [
[
"torch.max",
"torch.autograd.Variable",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.load"
]
] |
SabineEmbacher/xcube | [
"25863c713a27f1ecf6efb25ee0de8d322ab295bc"
] | [
"xcube/webapi/controllers/tiles.py"
] | [
"import io\nimport warnings\nfrom typing import Dict, Any\n\nimport matplotlib\nimport matplotlib.colorbar\nimport matplotlib.colors\nimport matplotlib.figure\n\nfrom xcube.core.tile import get_ml_dataset_tile, parse_non_spatial_labels\nfrom xcube.util.cmaps import get_norm, get_cmap\nfrom xcube.util.tilegrid impor... | [
[
"matplotlib.figure.Figure",
"matplotlib.colorbar.ColorbarBase",
"matplotlib.colors.Normalize"
]
] |
ringw/reikna | [
"0f27f86e35a9f06405de2d99580f766a1b504562"
] | [
"test/test_fft/test_fft.py"
] | [
"import itertools\nimport time\n\nimport numpy\nimport pytest\n\nfrom helpers import *\n\nfrom reikna.helpers import product\nfrom reikna.fft import FFT\nimport reikna.cluda.dtypes as dtypes\nfrom reikna.transformations import mul_param\n\n\ndef pytest_generate_tests(metafunc):\n\n perf_log_shapes = [\n (... | [
[
"numpy.fft.fftn",
"numpy.log2",
"numpy.fft.ifftn"
]
] |
victorpoughon/master-thesis | [
"61565db7dd2ce0909dacfb2a33f10c66bfb11a34"
] | [
"python/view_angle.py"
] | [
"#!/usr/bin/env python3\n\nimport sys\nimport os\nimport os.path\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom features_common import match_angle, base_plot\n\nif __name__ == \"__main__\":\n if len(sys.argv) >= 2:\n path = sys.argv[1]\n else:\n path = \".\"\n\n shape = np.loadt... | [
[
"matplotlib.pyplot.show",
"numpy.arange",
"matplotlib.pyplot.close"
]
] |
AshishMahabal/lamal | [
"3ee2dbab3b17f2afd916a8577898621b4234d3d9"
] | [
"lamal.py"
] | [
"import streamlit as st\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nimport matplotlib.font_manager as font_manager\n\nfont_dirs = ['.', ]\nfont_files = font_manager.findSystemFonts(fontpaths=font_dirs)\nfont_list = font_manager.createFontList(font_files)\nfont_manager.fontManager.tt... | [
[
"matplotlib.font_manager.findSystemFonts",
"matplotlib.pyplot.subplots",
"matplotlib.font_manager.createFontList",
"pandas.read_csv",
"matplotlib.font_manager.fontManager.ttflist.extend"
]
] |
GFDRR/vietnam-transport | [
"71f6fc8cb7f1ca7bccb9a29d544869b442e68bfc"
] | [
"src/vtra/plot/road_network_failures.py"
] | [
"\"\"\"Road network failure maps\n\"\"\"\nimport os\nimport sys\nfrom collections import OrderedDict\n\nimport geopandas as gpd\nimport pandas as pd\nimport cartopy.crs as ccrs\nimport cartopy.io.shapereader as shpreader\nimport matplotlib.pyplot as plt\nfrom shapely.geometry import LineString\nfrom vtra.utils impo... | [
[
"pandas.read_csv",
"matplotlib.pyplot.title",
"matplotlib.pyplot.close",
"pandas.merge"
]
] |
theandygross/pandas | [
"d420334d7e3e52fd812e0648bb3ef8e90c10cc82"
] | [
"pandas/stats/fama_macbeth.py"
] | [
"from cStringIO import StringIO\n\nimport numpy as np\n\nfrom pandas.core.api import Series, DataFrame\nimport pandas.stats.common as common\nfrom pandas.util.decorators import cache_readonly\n\ndef fama_macbeth(**kwargs):\n \"\"\"Runs Fama-MacBeth regression.\n\n Parameters\n ----------\n Takes the sam... | [
[
"numpy.array",
"pandas.stats.common._get_window_type",
"numpy.dot",
"pandas.stats.plm.MovingPanelOLS",
"pandas.core.api.Series",
"pandas.stats.common.banner",
"numpy.sqrt",
"pandas.util.decorators.cache_readonly",
"pandas.core.api.DataFrame",
"numpy.diag"
]
] |
frenzytejask98/gpt-2 | [
"f18a42809050d0be28a9584b3f178c13343e74d7"
] | [
"train.py"
] | [
"#!/usr/bin/env python3\n# Usage:\n# PYTHONPATH=src ./train --dataset <file|directory|glob>\n\nimport argparse\nimport json\nimport os\nimport numpy as np\nimport tensorflow as tf\nimport time\nimport tqdm\nfrom tensorflow.core.protobuf import rewriter_config_pb2\n\nimport model, sample, encoder\nfrom load_dataset... | [
[
"tensorflow.trainable_variables",
"tensorflow.summary.merge",
"tensorflow.train.AdamOptimizer",
"tensorflow.shape",
"tensorflow.train.latest_checkpoint",
"tensorflow.summary.scalar",
"tensorflow.where",
"tensorflow.Session",
"tensorflow.train.Saver",
"numpy.mean",
"tens... |
drewpendergrass/ToyLETKF | [
"386bb6a4168e823f7feac8f593d71ace8256cf8d"
] | [
"assimilation_tools.py"
] | [
"import numpy as np\nimport scipy.linalg as la\nimport pickle\nimport sys\nimport skimage.util as ski\n\n\n#Observation operator class\n\nclass Obs_Operator(object):\n\tdef __init__(self,nature,model_ens,timevals, obs_times, distmat, settings_golem):\n\t\tself.nature = nature\n\t\tself.model_ens = model_ens\n\t\tse... | [
[
"numpy.array",
"numpy.isnan",
"numpy.zeros",
"numpy.copy",
"numpy.mean",
"numpy.shape",
"numpy.identity",
"numpy.where",
"scipy.linalg.sqrtm",
"numpy.stack",
"numpy.arange",
"scipy.linalg.inv",
"numpy.transpose",
"numpy.std",
"numpy.diag"
]
] |
guiligan/incubator-airflow | [
"b3c0ae003037ae6c652b177b9f86ecac84c792a5"
] | [
"airflow/www/views.py"
] | [
"# -*- coding: utf-8 -*-\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 to in wri... | [
[
"pandas.to_datetime",
"pandas.set_option"
]
] |
edrumwri/director | [
"c82aff0ed2ad0083dc5ac9cf4b90994d2d852be8",
"c82aff0ed2ad0083dc5ac9cf4b90994d2d852be8",
"c82aff0ed2ad0083dc5ac9cf4b90994d2d852be8"
] | [
"src/python/director/thirdparty/conversions.py",
"src/python/director/coursemodel.py",
"src/python/director/matlab.py"
] | [
"\n\nimport numbers\n\nimport numpy\nfrom director.thirdparty import transformations\nfrom .geometry_msgs_mock import Pose\n\n\n\ndef rounded(val):\n if isinstance(val, str):\n return rounded(float(val))\n elif isinstance(val, numbers.Number):\n return int(round(val,6) * 1e5) / 1.0e5\n else:\n return nu... | [
[
"numpy.array_str"
],
[
"numpy.array"
],
[
"numpy.ndim"
]
] |
Shunpoco/tfx | [
"85c365cd31943c32a7f3189ed34ad5c18b9b71fd"
] | [
"tfx/examples/bert/mrpc/bert_mrpc_pipeline_e2e_test.py"
] | [
"# Copyright 2020 Google LLC. 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... | [
[
"tensorflow.compat.v1.enable_v2_behavior",
"tensorflow.test.main"
]
] |
PointCloudYC/Pointnet_Pointnet2_pytorch | [
"32ec7975bb463aceab2273ca34e2b9b7820c80e7"
] | [
"data_utils_PSNet/PSNet6Dataloader.py"
] | [
"import os\nimport numpy as np\nfrom torch.utils.data import Dataset\n\n\n\"\"\"\ngenerate a collection of NxD examples, in particular, each room will be used to create round(room_count/4096)*sample_rate blocks (where sample_rate by default is 1)\n\"\"\"\nclass PSNetDataloader(Dataset):\n def __init__(self, spli... | [
[
"numpy.array",
"torch.cuda.manual_seed_all",
"numpy.random.choice",
"numpy.zeros",
"numpy.random.seed",
"numpy.sum",
"numpy.load",
"torch.manual_seed",
"numpy.where",
"numpy.amax",
"torch.utils.data.DataLoader",
"numpy.amin"
]
] |
emuccino/FlexGAN | [
"d45e10d851d1f83a2391c0068434c455a27242c6"
] | [
"flexgan/model.py"
] | [
"from tensorflow.keras.models import Model\nfrom tensorflow.keras.layers import Dense, BatchNormalization, Multiply, Input, Concatenate, LeakyReLU, Lambda\nfrom tensorflow.keras.optimizers import SGD\nfrom tensorflow.keras.losses import BinaryCrossentropy\nfrom tensorflow.keras import backend as K\nimport tensorflo... | [
[
"tensorflow.keras.optimizers.SGD",
"tensorflow.keras.layers.Lambda",
"tensorflow.keras.layers.Input",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.LeakyReLU",
"tensorflow.keras.layers.BatchNormalization",
"tensorflow.keras.losses.Binary... |
dajun2gaigai/CARLA_INVS | [
"a326ad1f587f8e0b7ff156103995783ca873835f"
] | [
"PCDet/pcdet/utils/box_coder_utils.py"
] | [
"import numpy as np\nimport torch\nfrom . import common_utils\n\n\nclass ResidualCoder(object):\n def __init__(self, code_size=7):\n super().__init__()\n self.code_size = code_size\n\n @staticmethod\n def encode_np(boxes, anchors):\n \"\"\"\n :param boxes: (N, 7 + ?) x, y, z, w,... | [
[
"numpy.concatenate",
"torch.cat",
"torch.sqrt",
"numpy.log",
"torch.max",
"torch.split",
"numpy.exp",
"numpy.split",
"torch.tensor",
"numpy.sqrt",
"torch.log",
"torch.exp"
]
] |
igomezv/astroNN | [
"0b970dd1a8d4d5e6d611ffa52cfd3c2ffdcb4643"
] | [
"astroNN/datasets/h5.py"
] | [
"# ---------------------------------------------------------#\n# astroNN.datasets.h5: compile h5 files for NN\n# ---------------------------------------------------------#\n\nimport os\nfrom functools import reduce\n\nimport h5py\nimport numpy as np\n\n\ndef h5name_check(h5name):\n if h5name is None:\n ... | [
[
"numpy.array",
"numpy.column_stack",
"numpy.arange"
]
] |
jiyounglee-0523/FourierModel | [
"49bd90e7465e2c4303c97401d5b1d023a1ffed05"
] | [
"models/encoder.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.distributions.normal import Normal\n\nclass ConvEncoder(nn.Module):\n def __init__(self, args):\n super(ConvEncoder, self).__init__()\n self.num_label = args.num_label\n\n layers = []\n layers.append(nn.Conv1d(in_channels=2+args.num_lab... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.functional.softplus",
"torch.nn.Conv1d",
"torch.nn.Sequential",
"torch.nn.SiLU",
"torch.nn.AdaptiveAvgPool1d",
"torch.nn.MaxPool1d"
]
] |
vlad-danaila/tobit_loss | [
"53c4d0d038d3b09001b963bf293385307e607d01"
] | [
"deep_tobit/util.py"
] | [
"import torch as t\nimport math\n\ndef normalize(x, mean, std, epsilon = 0):\n if x is None:\n return None\n return (x - mean) / (std + epsilon)\n\ndef unnormalize(x, mean, std):\n if x is None:\n return None\n return (x * std) + mean\n\ndef to_numpy(tensor: t.Tensor):\n return tensor.d... | [
[
"torch.tensor",
"torch.stack"
]
] |
jdlc105/dgl | [
"efae0f97d8b18867398981d226423472a3069844"
] | [
"examples/pytorch/gat/train.py"
] | [
"\"\"\"\nGraph Attention Networks in DGL using SPMV optimization.\nMultiple heads are also batched together for faster training.\n\nCompared with the original paper, this code does not implement\nmultiple output attention heads.\n\nReferences\n----------\nPaper: https://arxiv.org/abs/1710.10903\nAuthor's code: http... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.ModuleList",
"torch.max",
"torch.FloatTensor",
"torch.nn.LeakyReLU",
"torch.no_grad",
"torch.exp",
"torch.bmm",
"torch.ByteTensor",
"numpy.mean",
"torch.cuda.set_device",
"torch.LongTensor",
"torch.nn.init.xav... |
manuel-delverme/growspaceenv_baselines | [
"530c3fbc5b8c2efda4e6f23cfb6e5d1b8b60d243"
] | [
"evaluation.py"
] | [
"import array2gif\nimport numpy as np\nimport torch\n\nimport config\nimport wandb\nfrom a2c_ppo_acktr import utils\nfrom a2c_ppo_acktr.envs import make_vec_envs\n\n\ndef evaluate(actor_critic, ob_rms, env_name, seed, num_processes, eval_log_dir, device, custom_gym, gif=False):\n eval_envs = make_vec_envs(env_na... | [
[
"torch.zeros",
"torch.no_grad",
"torch.tensor",
"numpy.mean"
]
] |
kslam07/RWA3-UA | [
"b786659783901196554bd1b93f2c790f4b9a574b"
] | [
"vortex_panel_steady.py"
] | [
"\n## VORTEX PANEL METHOD\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.cm import ScalarMappable\n\n# ---------------------------------- #\n# Flags\n# ---------------------------------- #\n\nenable_flap = True\n\nplot_backmesh = False\nplot_camber = False\nplot_cl_cur... | [
[
"matplotlib.cm.ScalarMappable",
"numpy.copy",
"numpy.mean",
"numpy.where",
"numpy.cos",
"numpy.deg2rad",
"numpy.concatenate",
"numpy.sin",
"matplotlib.pyplot.get_cmap",
"numpy.arange",
"numpy.sqrt",
"numpy.matrix",
"matplotlib.pyplot.contourf",
"numpy.matmul... |
jgieseler/sunpy | [
"9eb01ce9eea43512cc928b17c6d79ac06dce0ece",
"9eb01ce9eea43512cc928b17c6d79ac06dce0ece"
] | [
"examples/plotting/finding_local_peaks_in_solar_data.py",
"sunpy/timeseries/tests/test_timeseries_factory.py"
] | [
"\"\"\"\n=================================\nFinding Local Peaks in Solar Data\n=================================\n\nDetecting intensity peaks in solar images can be useful, for example as\na simple flare identification mechanism. This example illustrates detection\nof areas where there is a spike in solar intensity... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.figure"
],
[
"pandas.DataFrame",
"numpy.arange"
]
] |
sptennak/EmailAnalyzer | [
"9b9bd8c783d20fca8d2418db5d30f721fa74b17d"
] | [
"SEEmailPy.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon May 21 21:08:09 2018\n\n@author: Sumudu Tennakoon\n\"\"\"\n\n# System Utilities\nimport os\nimport io\nimport sys\nimport gc\nimport traceback\n\n# Email and Text processing\nimport email\nfrom email.header import decode_header\nimport re\nimport uuid # unique ID\n\... | [
[
"pandas.DataFrame"
]
] |
apexxs/dldt | [
"17e66dc5a6631d630da454506902bd7c25d4170b",
"17e66dc5a6631d630da454506902bd7c25d4170b"
] | [
"model-optimizer/extensions/front/onnx/affine_ext_test.py",
"model-optimizer/mo/middle/passes/eliminate_test.py"
] | [
"\"\"\"\n Copyright (c) 2018 Intel Corporation\n\n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\n Unless required by applicable law ... | [
[
"numpy.all"
],
[
"numpy.array"
]
] |
hochthom/maskRCNN-Viewer | [
"3d4f4d70cf7533c23c155bd649a6bec3298a1814"
] | [
"app/ImageSequenceControl.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Apr 26 05:59:46 2018\n\n@author: zefa\n\"\"\"\n\nimport os\nimport numpy as np\nimport cv2\nimport glob\n\nfrom .SequenceControl import SequenceControl\n\n\nclass ImageSequenceControl(SequenceControl):\n \n def __init__(self, path=None):\n super(ImageSeq... | [
[
"numpy.zeros"
]
] |
chongjg/Image-Inpainting | [
"c63a9e37bdd07bc4358024cfde1ae49f9972c8c7"
] | [
"code/DIP-final-project/pconv.py"
] | [
"import cv2\nimport numpy as np\nfrom PIL import Image\n\nfrom libs.pconv_model import PConvUnet\n\ndef inpaint_pconv(h, w):\n IMAGE_FILE = './tmp/input.png'\n MASK_FILE = './tmp/mask.png'\n OUTPUT_FILE = './tmp/output.png'\n\n model = PConvUnet(vgg_weights=None, inference_only=True)\n model.load('ch... | [
[
"numpy.array",
"numpy.asarray",
"numpy.expand_dims"
]
] |
lazywithcrazyness/pytorch-dann | [
"f81f06d97134e6e1372d635931a8d175087d2986"
] | [
"core/test.py"
] | [
"import torch.utils.data\nimport torch.nn as nn\n\ndef test(model, data_loader, device, flag):\n \"\"\"Evaluate model for dataset.\"\"\"\n # set eval state for Dropout and BN layers\n model.eval()\n\n # init loss and accuracy\n loss_ = 0.0\n acc_ = 0.0\n acc_domain_ = 0.0\n n_total = 0\n\n ... | [
[
"torch.nn.CrossEntropyLoss"
]
] |
rijoblockchain/nitro-enclave-FL | [
"65f70fdf6b9701548418e0dfd484521f0e1c9283"
] | [
"vsock-parent-local.py"
] | [
"# vsock-parent-local.py\n# usage ex: python3 vsock-parent-local.py server 5005\n# (in a new terminal): python3 vsock-parent-local.py client 16 5006 (16 is the enclave CID)\n\nimport argparse\nimport socket, pickle\nfrom struct import unpack, pack\nimport sys\nfrom crypto_utils import *\nimport time\nimport numpy a... | [
[
"numpy.load",
"numpy.save"
]
] |
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