repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
cambridgeltl/cancer-hallmark-cnn | [
"a1aba55ba425aa0deac4f80c97572a146e4097bb"
] | [
"keras/ltlib/evaluation.py"
] | [
"import numpy as np # TODO remove dependency\n\nfrom collections import namedtuple\nfrom itertools import chain\n\nfrom sklearn import metrics as skmetrics\n\nfrom util import unique\n\nfrom logging import warn\n\nBinaryClassificationCounts = namedtuple('BinaryClassificationCounts',\n ... | [
[
"sklearn.metrics.roc_auc_score",
"sklearn.metrics.precision_recall_curve",
"numpy.argmax",
"sklearn.metrics.average_precision_score",
"numpy.average",
"numpy.sum"
]
] |
Jallet/keras-jl-ac-mean | [
"2bbc1596192fb8c3aefc4a8126482a5283574a59"
] | [
"keras/utils/np_utils.py"
] | [
"from __future__ import absolute_import\nimport numpy as np\nimport scipy as sp\nfrom six.moves import range\nfrom six.moves import zip\n\n\ndef to_categorical(y, nb_classes=None):\n '''Convert class vector (integers from 0 to nb_classes)\n to binary class matrix, for use with categorical_crossentropy.\n '... | [
[
"numpy.log",
"numpy.expand_dims",
"scipy.log",
"scipy.minimum",
"scipy.maximum",
"numpy.linalg.norm",
"numpy.max",
"numpy.copy",
"numpy.argmax",
"numpy.array",
"scipy.subtract"
]
] |
abraia/abraia-python | [
"e49e3869b2ee7e6b1bcb41e0cc1ae126ac39e202"
] | [
"abraia/hsi.py"
] | [
"import os\nimport wget\nimport tempfile\nimport numpy as np\nimport scipy.io as sio\nimport scipy.ndimage as nd\n\nfrom PIL import Image\nfrom sklearn.svm import SVC\nfrom sklearn.utils import resample\nfrom sklearn.decomposition import PCA\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metric... | [
[
"numpy.amax",
"numpy.absolute",
"scipy.ndimage.gaussian_filter",
"numpy.amin",
"sklearn.model_selection.train_test_split",
"numpy.dstack",
"scipy.ndimage.uniform_filter",
"tensorflow.keras.optimizers.Adam",
"numpy.argmax",
"sklearn.svm.SVC",
"numpy.transpose",
"nump... |
rcelebi/android-elfali | [
"314d9cd9b607460f8bfea80fc828b1521ca18443",
"4ea14a58a18356ef9e16aba2e7dae84c02afba12",
"4ea14a58a18356ef9e16aba2e7dae84c02afba12",
"4ea14a58a18356ef9e16aba2e7dae84c02afba12",
"314d9cd9b607460f8bfea80fc828b1521ca18443",
"314d9cd9b607460f8bfea80fc828b1521ca18443",
"4ea14a58a18356ef9e16aba2e7dae84c02afba1... | [
"jni-build/jni/include/tensorflow/python/training/server_lib_test.py",
"jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py",
"jni-build/jni/include/tensorflow/contrib/distributions/python/ops/bijector.py",
"jni-build/jni/include/tensorflow/contrib/metrics/python/ops/... | [
"# Copyright 2016 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.GPUOptions",
"tensorflow.get_default_graph",
"tensorflow.Variable",
"tensorflow.test.main",
"tensorflow.ConfigProto",
"tensorflow.initialize_all_variables",
"tensorflow.Session",
"tensorflow.train.ServerDef",
"tensorflow.matmul",
"tensorflow.fill",
"tensorfl... |
Huite/timml | [
"5eb52066be094326343fe26b46555253fef44dc9"
] | [
"timml/model.py"
] | [
"\"\"\"\nModel classes\n\n\"\"\"\n\nimport numpy as np\nimport sys\nimport inspect # Used for storing the input\nfrom .aquifer import Aquifer\nfrom .aquifer_parameters import param_maq, param_3d\nfrom .constant import ConstantStar\nfrom .util import PlotTim\nimport multiprocessing as mp\n\n__all__ = ['Model', 'Mod... | [
[
"numpy.hstack",
"numpy.linalg.solve",
"numpy.linspace",
"numpy.ones",
"numpy.atleast_1d",
"numpy.array2string",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.empty"
]
] |
pearlfranz20/AL_Core | [
"6592079330c7ec3ca264b86f8414970ddab06c0e"
] | [
"apprentice/learners/when_learners/actor_critic.py"
] | [
"import torch\nimport torch.nn as nn\n\n\nclass ValueNet(nn.Module):\n \"\"\"\n The part of the actor critic network that computes the state value. Also,\n returns the hidden layer before state valuation, for use in action network.\n \"\"\"\n\n def __init__(self, n_inputs: int, n_hidden: int = None)... | [
[
"torch.nn.Linear",
"torch.nn.ReLU",
"torch.cat"
]
] |
hakanhp/chanel | [
"6825b60e86c46daabb18f40f1e45d3de2ff8e983",
"6825b60e86c46daabb18f40f1e45d3de2ff8e983"
] | [
"tensorflow_model_analysis/eval_saved_model/testutil.py",
"tensorflow_model_analysis/eval_saved_model/export.py"
] | [
"# Copyright 2018 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"tensorflow.core.example.example_pb2.Example"
],
[
"tensorflow.contrib.learn.utils.saved_model_export_utils.garbage_collect_exports",
"tensorflow.Graph",
"tensorflow.train.latest_checkpoint",
"tensorflow.get_collection",
"tensorflow.python.platform.gfile.Rename",
"tensorflow.saved_... |
MDoid10111/EMNLP2020 | [
"97e4da06abc72873a4830cfa53c035a27eb3975b",
"97e4da06abc72873a4830cfa53c035a27eb3975b"
] | [
"torch_utils.py",
"matchzoo/utils/parse.py"
] | [
"import numpy as np\nimport torch, os\nimport torch.nn.utils.rnn as rnn_utils\nfrom typing import Tuple\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom PIL import Image\nimport torchvision\nfrom torchvision import transforms\n\n\ndef flatten(x):\n '''\n flatten high dimensional tensor x into an ... | [
[
"torch.norm",
"torch.cuda.manual_seed",
"torch.manual_seed",
"numpy.arange",
"torch.from_numpy",
"numpy.stack",
"numpy.random.shuffle",
"torch.nn.utils.rnn.pack_padded_sequence",
"torch.sort",
"numpy.isscalar",
"torch.nn.init.xavier_uniform_",
"numpy.argsort",
"... |
kjarczak/balticlsc_module | [
"d104c66fbfeb2147e8a40a0fa5170326843854c5"
] | [
"examples/face_recogniser/content/processing.py"
] | [
"import os\nfrom typing import List, Tuple, Dict\n\nimport face_recognition\n\nfrom matplotlib import pyplot, patches\n\nfrom PIL import Image\n\nimport numpy as np\n\nfrom balticlsc.access.ftp import upload_file, get_connection\nfrom balticlsc.configs.credential.ftp import FTPCredential\nfrom balticlsc.scheme.api ... | [
[
"matplotlib.patches.Rectangle",
"matplotlib.pyplot.Axes",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure"
]
] |
waterzxj/UNF | [
"5eda8e7c60116735f595f4b21b24547708b36cf5",
"5eda8e7c60116735f595f4b21b24547708b36cf5",
"5eda8e7c60116735f595f4b21b24547708b36cf5"
] | [
"UNF/training/metric.py",
"UNF/modules/embedding/embedding.py",
"UNF/models/predictor.py"
] | [
"#coding:utf-8\n\nimport torch\n\nfrom learner_util import get_ner_BIO\n\n\nclass Metric(object):\n def __call__(self,\n predictions,\n gold_labels,\n mask=None):\n \"\"\"\n metric的抽象类\n\n :params predictions 预测结果的tensor\n :params gold_l... | [
[
"torch.ones_like"
],
[
"torch.nn.Dropout",
"torch.empty",
"torch.nn.Embedding"
],
[
"torch.LongTensor"
]
] |
sibo/pysimm_tacticity | [
"cfb20851b26b87b736dbb6a2f4c4e7b668d680d5"
] | [
"pysimm/apps/random_walk.py"
] | [
"# ******************************************************************************\n# pysimm.apps.random_walk module\n# ******************************************************************************\n#\n# psuedo random walk algorithm written using pysimm tools\n#\n# **************************************************... | [
[
"numpy.array"
]
] |
llimeht/sasview | [
"d0c10746a2397c5021ed8bbc842ba99243a9b0ac"
] | [
"test/sascalculator/utest_sas_gen.py"
] | [
"\"\"\"\nUnit tests for the sas_gen\n\"\"\"\n\nimport os.path\nimport warnings\nwarnings.simplefilter(\"ignore\")\n\nimport unittest\nimport numpy as np\n\nfrom sas.sascalc.calculator import sas_gen\n\n\ndef find(filename):\n return os.path.join(os.path.dirname(__file__), 'data', filename)\n\n\nclass sas_gen_tes... | [
[
"numpy.linspace"
]
] |
ddasdkimo/Towards-Realtime-MOT | [
"cfe0e26331969450b6e2a645dfa5c14947514ba5"
] | [
"track.py"
] | [
"import os\r\nimport os.path as osp\r\nimport cv2\r\nimport logging\r\nimport argparse\r\nimport motmetrics as mm\r\n\r\nimport torch\r\nfrom tracker.multitracker import JDETracker\r\nfrom utils import visualization as vis\r\nfrom utils.log import logger\r\nfrom utils.timer import Timer\r\nfrom utils.evaluation imp... | [
[
"torch.from_numpy"
]
] |
erikw/taiga_stats | [
"7e28ffff5169707e248be6a4ab6e31326fc2ca85"
] | [
"taiga_stats/helpers.py"
] | [
"import datetime as dt\nimport sys\n\nimport matplotlib\n\nimport taiga_stats.constants as c\n\nmatplotlib.use(\"TkAgg\") # Reference: https://stackoverflow.com/a/48374671/265508\n\n\nDOT_HEADER_FMT = \"\"\"digraph {:s} {{\n labelloc=\"t\";\n //labelfontsize=\"40\"\n label=\"{:s}\";\n //size=\"7.5,10\"\n rati... | [
[
"matplotlib.use"
]
] |
mayankj/xView2-Solution | [
"804aa15a3d9f28c7c1d73e50ce0ed0c359a0493e",
"804aa15a3d9f28c7c1d73e50ce0ed0c359a0493e"
] | [
"xview/models/unetv2.py",
"fit_predict.py"
] | [
"from functools import partial\r\nfrom typing import List, Union, Callable\r\n\r\nimport torch\r\nfrom pytorch_toolbelt.modules import ABN, ACT_RELU, ACT_SWISH\r\nfrom pytorch_toolbelt.modules import encoders as E\r\nfrom pytorch_toolbelt.modules.decoders import DecoderModule\r\nfrom pytorch_toolbelt.modules.encode... | [
[
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.Upsample",
"torch.cat"
],
[
"torch.utils.data.DataLoader",
"torch.cuda.empty_cache"
]
] |
adelmuursepp/ML-React-App-Template | [
"d0afed66b8dd037464edc39b1be7709b6207e834"
] | [
"example/iris-data-classifier/ML-React-App-Template/service/model_generator.py"
] | [
"# Import libraries\nimport numpy as np\nprint('imported numpy')\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.externals import joblib\nimport pandas as pd\n\n\n\n\n\n#Otsustuspuud\nfrom sklearn.tree import DecisionTreeClassifier\n\nprint('impor... | [
[
"sklearn.externals.joblib.dump",
"pandas.read_csv",
"sklearn.model_selection.train_test_split",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.preprocessing.LabelEncoder"
]
] |
Garsiet/MchLE | [
"4afca0328a5710f16fa08f22b38431a6e84e6910"
] | [
"lab-10-2-mnist_nn.py"
] | [
"# Lab 10 MNIST and NN\nimport tensorflow as tf\nimport random\n# import matplotlib.pyplot as plt\n\nfrom tensorflow.examples.tutorials.mnist import input_data\n\ntf.set_random_seed(777) # reproducibility\n\nmnist = input_data.read_data_sets(\"MNIST_data/\", one_hot=True)\n# Check out https://www.tensorflow.org/ge... | [
[
"tensorflow.matmul",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.cast",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.Session",
"tensorflow.train.AdamOptimizer",
"tensorflow.set_random_seed",
"tensorflow.argmax",
"tensor... |
bell-one/pifuhd | [
"3221d266a042ad58de702e65e588ada5426b08f6"
] | [
"apps/recon.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.\n\nimport sys\nimport os\n\nsys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))\nROOT_PATH = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))\n\nimport time\nimport json \nimport numpy as np\nimport cv... | [
[
"numpy.ones_like",
"torch.cat",
"torch.load",
"numpy.linalg.inv",
"torch.from_numpy",
"numpy.concatenate",
"torch.no_grad",
"torch.cuda.is_available",
"numpy.zeros"
]
] |
rahulgovind/pysph | [
"3d493e6f2c5284ea9c0f0d008e4eb9a0870da0d9",
"3d493e6f2c5284ea9c0f0d008e4eb9a0870da0d9",
"3d493e6f2c5284ea9c0f0d008e4eb9a0870da0d9"
] | [
"pysph/sph/rigid_body.py",
"examples/cpy/axpb_jit.py",
"pysph/examples/surface_tension/square_droplet.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Rigid body related equations.\n\"\"\"\nfrom pysph.base.reduce_array import parallel_reduce_array\nfrom pysph.sph.equation import Equation\nfrom pysph.sph.integrator_step import IntegratorStep\nimport numpy as np\nimport numpy\nfrom math import sqrt\n\n\ndef skew(vec):\n import sym... | [
[
"numpy.log",
"numpy.sum",
"numpy.sqrt"
],
[
"numpy.zeros_like",
"numpy.linspace"
],
[
"numpy.ones_like"
]
] |
yoxu515/aot-benchmark | [
"99f74f051c91ac221e44f3edab3534ae4dd233f7",
"99f74f051c91ac221e44f3edab3534ae4dd233f7"
] | [
"tools/train.py",
"networks/layers/transformer.py"
] | [
"import importlib\nimport random\nimport sys\n\nsys.setrecursionlimit(10000)\nsys.path.append('.')\nsys.path.append('..')\n\nimport torch.multiprocessing as mp\n\nfrom networks.managers.trainer import Trainer\n\n\ndef main_worker(gpu, cfg, enable_amp=True):\n # Initiate a training manager\n trainer = Trainer(... | [
[
"torch.multiprocessing.spawn"
],
[
"torch.nn.Dropout",
"torch.nn.ModuleList",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.nn.init.xavier_uniform_"
]
] |
ghislainp/mishchenko_brf | [
"de7fe70730b53f17fb7e7aa9a45f08bf7d97abd1"
] | [
"tests/test_mishchenko_refllib.py"
] | [
"#!/usr/bin/env python\n\n\"\"\"Tests for `mishchenko_brf` package.\"\"\"\n\nimport numpy as np\n\nfrom mishchenko_brf.lib.refl import brf\n\n\ndef test_brf():\n \"\"\"Sample pytest test function with the pytest fixture as an argument.\"\"\"\n # from bs4 import BeautifulSoup\n # assert 'GitHub' in Beautifu... | [
[
"numpy.array",
"numpy.testing.assert_allclose"
]
] |
ririw/scipy | [
"680ecf8c52966343827903e6b7983b1ef7323fe2"
] | [
"scipy/sparse/compressed.py"
] | [
"\"\"\"Base class for sparse matrix formats using compressed storage.\"\"\"\nfrom __future__ import division, print_function, absolute_import\n\n__all__ = []\n\nfrom warnings import warn\nimport operator\n\nimport numpy as np\nfrom scipy._lib._util import _prune_array\n\nfrom .base import spmatrix, isspmatrix, Spar... | [
[
"numpy.resize",
"numpy.asarray",
"numpy.issubdtype",
"numpy.cumsum",
"numpy.concatenate",
"numpy.all",
"numpy.unique",
"numpy.empty_like",
"numpy.arange",
"numpy.diff",
"numpy.repeat",
"numpy.zeros",
"numpy.multiply",
"numpy.isnan",
"numpy.atleast_2d",
... |
athatheo/House-GANs-Reproduction | [
"00cc807f1e74f88eef5ed81615bfd87a39c52f94"
] | [
"src/models.py"
] | [
"import torch\nfrom torch import cat\nfrom torch.nn import Conv2d\nfrom torch.nn import Linear\nfrom torch.nn import Module\nfrom torch.nn import ConvTranspose2d\nfrom torch.nn import LeakyReLU\nfrom torch.nn import Tanh\nfrom torch.nn import MaxPool2d\nfrom torch import zeros_like\n\n\nclass ConvMPN(Module):\n ... | [
[
"torch.max",
"torch.nn.ConvTranspose2d",
"torch.cat",
"torch.zeros",
"torch.nn.Conv2d",
"torch.zeros_like",
"torch.nn.Tanh",
"torch.nn.Linear",
"torch.nn.LeakyReLU",
"torch.where"
]
] |
dyahadila/ood_cartography | [
"ff65bf2b1a170e2913f0019a15af3398a1808f0f"
] | [
"cartography/classification/glue_utils.py"
] | [
"import logging\nimport os\n\nfrom transformers import glue_compute_metrics\nfrom transformers import glue_convert_examples_to_features as convert_examples_to_features\nfrom transformers import glue_output_modes\nfrom transformers import glue_processors\n\nfrom transformers.data.processors.glue import MnliMismatche... | [
[
"tensorflow.TensorShape",
"tensorflow.data.experimental.cardinality"
]
] |
Forest216/BigDL | [
"840da9a2eaf395978dd83730b02aa5e5dfbd7989",
"840da9a2eaf395978dd83730b02aa5e5dfbd7989",
"840da9a2eaf395978dd83730b02aa5e5dfbd7989",
"840da9a2eaf395978dd83730b02aa5e5dfbd7989",
"840da9a2eaf395978dd83730b02aa5e5dfbd7989",
"840da9a2eaf395978dd83730b02aa5e5dfbd7989"
] | [
"python/nano/src/bigdl/nano/automl/tf/objective.py",
"python/chronos/src/bigdl/chronos/autots/tspipeline.py",
"python/orca/test/bigdl/orca/ray/integration/test_yarn_reinit_raycontext.py",
"python/dllib/src/bigdl/dllib/utils/file_utils.py",
"python/orca/src/bigdl/orca/data/tf/data.py",
"python/dllib/src/bi... | [
"#\n# Copyright 2016 The BigDL Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law ... | [
[
"tensorflow.keras.backend.clear_session",
"tensorflow.keras.models.clone_model"
],
[
"numpy.concatenate",
"torch.cat",
"torch.from_numpy",
"torch.load"
],
[
"numpy.random.seed"
],
[
"numpy.array",
"numpy.isscalar"
],
[
"tensorflow.python.distribute.coordinat... |
Khanhnn00/blind_sr_denoise | [
"3153f90d20fd884ab69b47c30c685e0175276055",
"3153f90d20fd884ab69b47c30c685e0175276055",
"3153f90d20fd884ab69b47c30c685e0175276055"
] | [
"DNCNN/common.py",
"DNCNN/networks/__init__.py",
"KernelGANFKP/model/model.py"
] | [
"import os\nimport random\nimport numpy as np\nimport scipy.misc as misc\nimport imageio\nfrom tqdm import tqdm\nimport cv2\nfrom PIL import Image\n\nimport torch\nimport torch.nn.functional as F\n\nIMG_EXTENSIONS = ['.jpg', '.JPG', '.jpeg', '.JPEG', '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP']\nBINARY_EXTENSION... | [
[
"numpy.ascontiguousarray",
"numpy.copy",
"numpy.expand_dims",
"numpy.transpose"
],
[
"torch.nn.init.constant_",
"torch.nn.init.normal_",
"torch.nn.init.orthogonal_",
"torch.cuda.is_available",
"torch.nn.DataParallel",
"torch.nn.init.kaiming_normal_"
],
[
"torch.... |
tinyrobots/Generalized-PixelVAE | [
"ee99634be08c726c3da7e8ba2675c8d1448e15af"
] | [
"fast_pixel_cnn_pp/test_end_to_end.py"
] | [
"from . import model\nfrom . import fast_nn\n\nimport tensorflow as tf\nimport numpy as np\n\nimport os\nimport unittest\n\n\nclass FastPixelCNNPPEndToEndTest(tf.test.TestCase):\n def test_end_to_end(self):\n with self.test_session() as sess:\n print('Creating model')\n image_size = ... | [
[
"numpy.allclose",
"numpy.random.seed",
"tensorflow.global_variables",
"tensorflow.variables_initializer",
"tensorflow.placeholder",
"numpy.ones",
"tensorflow.train.ExponentialMovingAverage",
"tensorflow.make_template",
"numpy.prod",
"tensorflow.train.Saver",
"numpy.load... |
zhangyanyu0722/EC523_Project | [
"72673713bb798023e82ccc257e8c05459c34a4b9"
] | [
"carla-data-export/dataexport.py"
] | [
"\"\"\"\nThis file contains all the methods responsible for saving the generated data in the correct output format.\n\n\"\"\"\nimport cv2\nimport numpy as np\nimport os\nimport logging\nfrom utils import degrees_to_radians\nimport json\n\n\ndef save_groundplanes(planes_fname, player_measurements, lidar_height):\n ... | [
[
"numpy.ravel",
"numpy.array",
"numpy.identity"
]
] |
lizhipengTouch/CSA-inpainting | [
"50602607ddc9153af5bfe627e355b0466fc4944f"
] | [
"models/vgg16.py"
] | [
"import torch\nimport torchvision\nfrom torchvision import models\nfrom collections import namedtuple\n\nclass Vgg16(torch.nn.Module):\n def __init__(self, requires_grad=False):\n super(Vgg16, self).__init__()\n vgg_pretrained_features = models.vgg16(pretrained=True).features # 获取预训练vgg网络层\n ... | [
[
"torch.nn.Sequential"
]
] |
alphaciel/Balancing-Robot-Raspberry-Pi-DIY | [
"8a61acf688ea0915017c40eaff3841a9b219f9b7"
] | [
"matplotlib/matplotlib_test/plot_lib_test.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nfrom matplotlib.widgets import Slider, Button, RadioButtons\n\nfig = plt.figure()\nax = fig.add_subplot(111)\nfig.subplots_adjust(left=0.25, bottom=0.25)\nmin0 = 0\nmax0 = 25000\n\nim = max0 * np.random.random((10,10))\nim1 = ax.imshow(im)\nfig.colorbar(im1)\n\n... | [
[
"matplotlib.widgets.Slider",
"matplotlib.pyplot.show",
"numpy.random.random",
"matplotlib.pyplot.figure"
]
] |
Honghe/AnchorDETR | [
"fc3d45441241cd689b28878d3aa4b0bffb33a8b8"
] | [
"models/transformer.py"
] | [
"# ------------------------------------------------------------------------\n# Copyright (c) 2021 megvii-model. All Rights Reserved.\n# ------------------------------------------------------------------------\n# Modified from Deformable DETR (https://github.com/fundamentalvision/Deformable-DETR)\n# Copyright (c) 20... | [
[
"torch.nn.Dropout",
"torch.nn.init.uniform_",
"torch.ones",
"torch.nn.MultiheadAttention",
"torch.cat",
"torch.nn.init.constant_",
"torch.nn.Embedding",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.arange",
"torch.nn.ReLU",
"torch.meshgrid"
]
] |
SIMEXP/nilearn | [
"4f51aea58f38689ca32c2edd748528d521e6cfb0",
"4f51aea58f38689ca32c2edd748528d521e6cfb0",
"4f51aea58f38689ca32c2edd748528d521e6cfb0",
"4f51aea58f38689ca32c2edd748528d521e6cfb0",
"4f51aea58f38689ca32c2edd748528d521e6cfb0"
] | [
"examples/01_plotting/plot_colormaps.py",
"nilearn/plotting/surf_plotting.py",
"nilearn/plotting/tests/test_html_stat_map.py",
"nilearn/plotting/cm.py",
"nilearn/decoding/tests/test_tv.py"
] | [
"\"\"\"\nMatplotlib colormaps in Nilearn\n================================\n\nVisualize HCP connectome workbench color maps shipped with Nilearn\nwhich can be used for plotting brain images on surface.\n\nSee :ref:`surface-plotting` for surface plotting details.\n\"\"\"\nimport numpy as np\nimport matplotlib.pyplot... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.title",
"numpy.arange",
"matplotlib.pyplot.get_cmap",
"numpy.ones",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.figure"
],
[
"numpy.nanmax",
"numpy.lins... |
raznem/sac_ppo | [
"c18e9bd32a70fcc4bc413565c6b885d7560b8b5a"
] | [
"rltoolkit/rl.py"
] | [
"import logging\nfrom pathlib import Path\nfrom typing import Any, Optional, Tuple, Union\n\nimport gym\nimport torch\nimport pickle as pkl\n\nfrom rltoolkit import config, utils\nfrom rltoolkit.buffer import Memory\nfrom rltoolkit.stats_logger import StatsLogger\nfrom rltoolkit.tensorboard_logger import Tensorboar... | [
[
"torch.ones",
"torch.zeros",
"torch.tensor",
"torch.cuda.is_available",
"torch.device"
]
] |
samggreenberg/pynndescent | [
"f97bc2fe01e4e59c5dad20ed23b9cb47e8182b6c"
] | [
"pynndescent/utils.py"
] | [
"# Author: Leland McInnes <leland.mcinnes@gmail.com>\n#\n# License: BSD 2 clause\n\nimport time\n\nimport numba\nfrom numba.core import types\nimport numba.experimental.structref as structref\nimport numpy as np\n\n\n@numba.njit(\"void(i8[:], i8)\", cache=True)\ndef seed(rng_state, seed):\n \"\"\"Seed the random... | [
[
"numpy.sqrt",
"numpy.empty",
"numpy.full"
]
] |
RonnyLV/PRNet | [
"0c2ded7042ceee2b2f9bba02bc19d91d4c3993c5"
] | [
"prnet/utils/render_app.py"
] | [
"import numpy as np\nfrom prnet.utils.render import vis_of_vertices, render_texture\nfrom scipy import ndimage\n\ndef get_visibility(vertices, triangles, h, w):\n triangles = triangles.T\n vertices_vis = vis_of_vertices(vertices.T, triangles, h, w)\n vertices_vis = vertices_vis.astype(bool)\n for k in r... | [
[
"numpy.squeeze",
"scipy.ndimage.binary_closing",
"numpy.ones"
]
] |
miramirakim227/SwapNeRF_single_GT | [
"55a842ec4155fa782ca1c48b5c6863aeca8ca295"
] | [
"im2scene/camera.py"
] | [
"import numpy as np\nimport torch\nfrom scipy.spatial.transform import Rotation as Rot\nimport pdb \nimport math \n\ndef get_camera_mat(fov=49.13, invert=True):\n # fov = 2 * arctan( sensor / (2 * focal))\n # focal = (sensor / 2) * 1 / (tan(0.5 * fov))\n # in our case, sensor = 2 as pixels are in [-1, 1]\... | [
[
"torch.sin",
"torch.zeros",
"numpy.cross",
"torch.device",
"torch.norm",
"torch.ones",
"torch.eye",
"torch.from_numpy",
"torch.inverse",
"torch.tensor",
"torch.rand",
"torch.cos",
"numpy.tan",
"torch.stack",
"scipy.spatial.transform.Rotation.from_euler",... |
gerritholl/typhon | [
"dbde147be12922ec730bd072dc4797c9da9a6d6b"
] | [
"typhon/retrieval/common.py"
] | [
"from ast import literal_eval\nimport copy\nfrom importlib import import_module\nimport json\n\nimport numpy as np\nimport pandas as pd\nfrom sklearn.pipeline import Pipeline\nfrom typhon.utils import to_array\n\n__all__ = [\n 'RetrievalProduct',\n]\n\n\nclass NotTrainedError(Exception):\n \"\"\"Should be rai... | [
[
"numpy.array",
"numpy.asscalar",
"sklearn.pipeline.Pipeline",
"pandas.DataFrame"
]
] |
BernhardRiemann/iree | [
"471349762b316f7d6b83eb5f9089255d78052758"
] | [
"integrations/tensorflow/e2e/broadcasting_test.py"
] | [
"# Lint as: python3\n# Copyright 2020 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appl... | [
[
"tensorflow.compat.v2.enable_v2_behavior",
"tensorflow.compat.v2.TensorSpec",
"tensorflow.compat.v2.test.main"
]
] |
mannyray/sort | [
"f0ee0488aa4e7213d30ff50bcb848a843fedde42"
] | [
"python_implementation/example/example7.py"
] | [
"import commonExample\nimport math\nimport sys\nsys.path.insert(0,'..')\nimport generate\nimport constants\nfrom numpy import random\nimport intersection\nfrom PIL import Image, ImageDraw, ImageFont\n\ngif_file=\"example7\"\n\n\nxcoords = [constants.width,constants.width,constants.width,100,400,700,1000,1300]\nycoo... | [
[
"numpy.random.normal"
]
] |
FastSense/rosbot-ros2 | [
"063c897a16129d9aa88c2c7c52bdf6547af894e4",
"063c897a16129d9aa88c2c7c52bdf6547af894e4"
] | [
"ros2_ws/src/utils/logger/logger/logger.py",
"ros1_ws/src/hdf5_data_publisher/scripts/hdf5_pcd_publisher.py"
] | [
"import os\nimport pandas as pd\nfrom matplotlib import pyplot as plt\nimport rclpy\nimport numpy as np\n\nfrom rclpy.node import Node\nfrom geometry_msgs.msg import Twist\nfrom nav_msgs.msg import Odometry\nfrom std_srvs.srv import Empty\n\nfrom logger.utils import convert_ros2_time_to_float\nfrom logger.create_gr... | [
[
"numpy.float",
"pandas.DataFrame"
],
[
"numpy.eye",
"numpy.array",
"numpy.zeros"
]
] |
bgpeyton/QCElemental | [
"2e84cd686d5fff0fc79accb28ffa985de4684704"
] | [
"qcelemental/util/misc.py"
] | [
"import math\nimport re\nfrom typing import Dict, List\n\nimport numpy as np\n\nfrom ..physical_constants import constants\n\n\ndef distance_matrix(a: np.ndarray, b: np.ndarray) -> np.ndarray:\n \"\"\"Euclidean distance matrix between rows of arrays `a` and `b`. Equivalent to\n `scipy.spatial.distance.cdist(a... | [
[
"numpy.einsum",
"numpy.degrees",
"numpy.linalg.norm",
"numpy.arccos",
"numpy.arctan2",
"numpy.atleast_2d",
"numpy.cross",
"numpy.zeros"
]
] |
DavidHurst/palbolts | [
"72f9ca3f82499b532f14d0e797426e1b425d3efe"
] | [
"conduit/fair/models/gpd.py"
] | [
"\"\"\"Zhang Gradient Projection Debiasing Baseline Model.\"\"\"\nfrom __future__ import annotations\nfrom typing import NamedTuple, cast\n\nimport ethicml as em\nfrom kit import implements\nfrom kit.torch import CrossEntropyLoss, TrainingMode\nimport pandas as pd\nimport pytorch_lightning as pl\nfrom pytorch_light... | [
[
"torch.finfo",
"torch.sum",
"torch.no_grad",
"torch.rand_like"
]
] |
Tulioas/dfp_analyser | [
"d66ff94ba0b88a5d421a992ad27661011db36091"
] | [
"primary_info.py"
] | [
"import pandas as pd\nfrom zipfile import ZipFile\nimport numpy as np\nimport re\nimport os\n\n\ndef year_identifier(file_name):\n\n '''\n Abstrait: identify the year of the file\n '''\n\n folder_regex = re.compile(r'20\\d\\d')\n match = folder_regex.search(str(file_name))\n year = match.group()\n... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.merge",
"pandas.DataFrame",
"numpy.array"
]
] |
rabbitsun2/toy_python | [
"32f84b4d15b13c4daa4fa212a40e685abc0d2a5d",
"32f84b4d15b13c4daa4fa212a40e685abc0d2a5d"
] | [
"practice/3_basic_tensorflow/Keras/Example_simpleLinearRegression.py",
"practice/4_basic_tensorflow_2/220404_Pima_indian2.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\nx = np.arange(1, 6)\n\ny = 3 * x + 2\n\nprint(x)\nprint(y)\n\n# 시각화\nplt.plot(x, y)\nplt.title('y = 3x + 2')\nplt.show()\n",
"import pandas as pd\n\ndf = pd.read_csv('dataset/pima-indians-diabetes.csv', \n names = [\"pregnant\", \"plasma\", \"pressure\", ... | [
[
"matplotlib.pyplot.plot",
"numpy.arange",
"matplotlib.pyplot.show",
"matplotlib.pyplot.title"
],
[
"pandas.read_csv"
]
] |
manuelciosici/DeepSpeed | [
"3da841853ca07abf3a09e7bd325a576c4e642c11",
"3da841853ca07abf3a09e7bd325a576c4e642c11",
"3da841853ca07abf3a09e7bd325a576c4e642c11",
"3da841853ca07abf3a09e7bd325a576c4e642c11"
] | [
"deepspeed/runtime/zero/linear.py",
"deepspeed/module_inject/replace_module.py",
"deepspeed/runtime/utils.py",
"deepspeed/runtime/zero/utils.py"
] | [
"#Linear Module to use with ZeRO Stage 3 to allow for parameter memory release\n#after the module execution during forward\n#Instead of saving variables using save_for_backward, we save variable ids\n#Allowing us to retrieve the variable without creating pointer to it\n#Which allows for underlying tensor to be garb... | [
[
"torch.nn.init.uniform_",
"torch.Tensor",
"torch.distributed.get_rank",
"torch.tensor",
"torch.nn.init._calculate_fan_in_and_fan_out"
],
[
"torch.nn.Parameter",
"torch.empty",
"torch.cat",
"torch.cuda.current_device",
"torch.nn.Embedding",
"torch.matmul",
"torch... |
daniel-falk/nnabla | [
"3fe132ea52dc10521cc029a5d6ba8f565cf65ccf",
"3fe132ea52dc10521cc029a5d6ba8f565cf65ccf",
"3fe132ea52dc10521cc029a5d6ba8f565cf65ccf",
"3fe132ea52dc10521cc029a5d6ba8f565cf65ccf",
"3fe132ea52dc10521cc029a5d6ba8f565cf65ccf"
] | [
"python/test/function/refs.py",
"python/test/experimental/test_tb_graph_writer.py",
"python/test/function/test_gru.py",
"python/test/function/test_squared_error.py",
"python/test/solver/test_momentum.py"
] | [
"# Copyright 2017,2018,2019,2020,2021 Sony 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... | [
[
"numpy.ix_",
"numpy.linspace",
"numpy.asarray",
"numpy.arange",
"numpy.cos",
"numpy.stack",
"numpy.ones",
"numpy.concatenate",
"numpy.sin",
"numpy.floor",
"numpy.repeat",
"numpy.meshgrid",
"numpy.zeros"
],
[
"numpy.array",
"numpy.sin"
],
[
"n... |
prannayk/MSRASI17 | [
"f7277d90ffdd062c1ba94391b7f82c621e619743"
] | [
"models/wc3.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nimport operator\nimport collections\nimport math\nimport time\nimport os\nimport random\nimport zipfile\nimport time\nimport numpy as np\nimport sys\nfrom six.moves import urllib\nfrom six.moves import x... | [
[
"tensorflow.device",
"tensorflow.zeros",
"tensorflow.stack",
"tensorflow.train.AdamOptimizer",
"tensorflow.nn.nce_loss",
"tensorflow.Graph",
"numpy.save",
"tensorflow.Session",
"tensorflow.square",
"tensorflow.train.Saver",
"tensorflow.matmul",
"tensorflow.placehold... |
ruohoruotsi/pyro | [
"b54a4b42b9474eb3ecee11505e45fde85b1cdc54"
] | [
"pyro/distributions/relaxed_straight_through.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nimport torch\n\nfrom pyro.distributions.torch import RelaxedOneHotCategorical, RelaxedBernoulli\nfrom pyro.distributions.util import copy_docs_from\nfrom torch.distributions.utils import clamp_probs\n\n\n@copy_docs_from(RelaxedOneHotCategorical)\n... | [
[
"torch.Size",
"torch.zeros_like",
"torch.distributions.utils.clamp_probs"
]
] |
tsingqguo/ABA | [
"c32edbbe5705b0332a08951b5ee436b5f58c2e70",
"c32edbbe5705b0332a08951b5ee436b5f58c2e70",
"c32edbbe5705b0332a08951b5ee436b5f58c2e70"
] | [
"ltr/dataset/lasot.py",
"utils/neuron/data/datasets/vot.py",
"OSABA/pix2pix/models/copy_network.py"
] | [
"import os\nimport os.path\nimport torch\nimport numpy as np\nimport pandas\nimport csv\nimport random\nfrom collections import OrderedDict\nfrom .base_video_dataset import BaseVideoDataset\nfrom ltr.data.image_loader import jpeg4py_loader\nfrom ltr.admin.environment import env_settings\n\n\nclass Lasot(BaseVideoDa... | [
[
"pandas.read_csv",
"torch.tensor"
],
[
"numpy.sqrt",
"numpy.min",
"numpy.linalg.norm",
"numpy.max",
"numpy.mean",
"numpy.array",
"numpy.loadtxt"
],
[
"torch.nn.Sequential",
"torch.nn.functional.softmax",
"torch.nn.ConvTranspose2d",
"torch.cat",
"torc... |
anton-potapov/openvino | [
"84119afe9a8c965e0a0cd920fff53aee67b05108",
"84119afe9a8c965e0a0cd920fff53aee67b05108",
"84119afe9a8c965e0a0cd920fff53aee67b05108",
"84119afe9a8c965e0a0cd920fff53aee67b05108",
"84119afe9a8c965e0a0cd920fff53aee67b05108",
"84119afe9a8c965e0a0cd920fff53aee67b05108"
] | [
"model-optimizer/mo/middle/passes/fusing/decomposition_test.py",
"model-optimizer/extensions/back/InterpolateReshape_test.py",
"model-optimizer/extensions/middle/ConvToBinaryConv.py",
"tools/python_api_reproducer.py",
"ngraph/python/test/ngraph/test_ops_unary.py",
"model-optimizer/mo/front/onnx/extractors... | [
"\"\"\"\n Copyright (C) 2018-2020 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... | [
[
"numpy.array"
],
[
"numpy.array"
],
[
"numpy.unique",
"numpy.ones",
"numpy.round",
"numpy.array",
"numpy.zeros",
"numpy.isclose"
],
[
"numpy.load",
"numpy.savez"
],
[
"numpy.logical_not",
"numpy.maximum",
"numpy.allclose",
"numpy.random.seed"... |
DottD/pynger | [
"9a24b43a2170234e5059a54ed20329e036260b0a"
] | [
"pynger/fingerprint/FVC_utilities.py"
] | [
"import os\nimport re\nimport io\nimport numpy as np\nimport PIL.Image\nimport typing\nfrom pynger.types import Image, Mask, Field\nfrom pynger.fingerprint.tuning_lro import LROEstimator\nfrom pynger.fingerprint.sampling import convert_to_full, subsample\nfrom pynger.field.manipulation import polar2cart\nfrom pynge... | [
[
"numpy.array",
"numpy.empty"
]
] |
rhwhite/rhwhitepackages3 | [
"91d5677ea57d7cc9a3643708cd8c82a74fb6188d"
] | [
"SSWs.py"
] | [
"# Module to search for and get data on SSWs\n# Using the definition of Charlton and Polvani (2007):\n\n# Author rachel.white@cantab.net\n\n# Created July 2017\n\nimport numpy as np\nimport xarray as xr\nimport math\nimport sys\n\ndef adddays(U,itime,ndays):\n # Find ndays consecutive days with easterlies\n n... | [
[
"numpy.timedelta64",
"numpy.datetime64"
]
] |
haihabi/GenerativeCRB | [
"d53c01bec7214bb087fbe17dba241e12eb60858e",
"d53c01bec7214bb087fbe17dba241e12eb60858e",
"d53c01bec7214bb087fbe17dba241e12eb60858e"
] | [
"experiments/analysis/edge_bound/training_nlf/camera_nlf_training.py",
"experiments/models_architecture/simple_normalzing_flow.py",
"experiments/data_model/doa/doa_signal_generator.py"
] | [
"import torch\nimport numpy as np\nfrom tqdm import tqdm\nfrom torch.utils.data import DataLoader\nfrom experiments.data_model.image_denoising.noise_dataset import NoiseDataSet\nfrom experiments.models_architecture.camera_nlf_flow import generate_nlf_flow\n\n\ndef train_step(in_noise, in_cond_vector):\n opt.zero... | [
[
"torch.permute",
"torch.utils.data.DataLoader"
],
[
"torch.nn.SiLU",
"torch.eye",
"torch.zeros"
],
[
"torch.linspace",
"torch.sin",
"torch.zeros",
"torch.randn",
"torch.unsqueeze",
"numpy.sin",
"torch.matmul",
"torch.pow",
"torch.rand",
"torch.st... |
RelationRx/pyrelational | [
"41ededeff84158bd88b76d39006764de3388c821"
] | [
"pyrelational/models/mcdropout_model.py"
] | [
"import copy\nimport logging\nfrom abc import ABC\nfrom typing import Dict, Optional, Type, Union\n\nimport torch\nfrom pytorch_lightning import LightningModule\nfrom torch.nn.modules import Module\nfrom torch.utils.data import DataLoader\n\nfrom .generic_model import GenericModel\nfrom .lightning_model import Ligh... | [
[
"torch.stack",
"torch.no_grad",
"torch.cat"
]
] |
ravish0007/fairml | [
"bdfb707ff9554c1a789dc8de3926c1ef3cfb1fc8",
"bdfb707ff9554c1a789dc8de3926c1ef3cfb1fc8"
] | [
"fairml/tests/test_orthogonal_projection.py",
"fairml/utils.py"
] | [
"from __future__ import division\n\n\nimport pytest\nimport numpy as np\nfrom random import randint\n\nfrom fairml.orthogonal_projection import audit_model\nfrom fairml.orthogonal_projection import get_orthogonal_vector\n\nfrom fairml.utils import mse\nfrom fairml.utils import accuracy\nfrom fairml.utils import det... | [
[
"numpy.random.binomial",
"numpy.dot",
"numpy.random.normal",
"numpy.random.uniform"
],
[
"numpy.square",
"numpy.reshape",
"numpy.mean",
"numpy.repeat",
"numpy.array",
"numpy.sum"
]
] |
mattboggess/pandas | [
"5551bcf9d297ea8a0aeffb70b17ae6730e8abf89",
"5551bcf9d297ea8a0aeffb70b17ae6730e8abf89",
"5551bcf9d297ea8a0aeffb70b17ae6730e8abf89",
"5551bcf9d297ea8a0aeffb70b17ae6730e8abf89",
"5551bcf9d297ea8a0aeffb70b17ae6730e8abf89"
] | [
"pandas/core/indexes/interval.py",
"pandas/core/arrays/base.py",
"scripts/validate_docstrings.py",
"pandas/tests/extension/decimal/array.py",
"pandas/tests/reshape/test_pivot.py"
] | [
"\"\"\" define the IntervalIndex \"\"\"\nimport textwrap\nimport warnings\n\nimport numpy as np\n\nfrom pandas.compat import add_metaclass\nfrom pandas.core.dtypes.missing import isna\nfrom pandas.core.dtypes.cast import find_common_type, maybe_downcast_to_dtype\nfrom pandas.core.dtypes.common import (\n ensure_... | [
[
"pandas.tseries.frequencies.to_offset",
"pandas.core.common._all_not_none",
"numpy.linspace",
"pandas.core.dtypes.common.is_datetime64tz_dtype",
"pandas._libs.interval.IntervalTree",
"pandas.core.indexes.base.Index",
"numpy.concatenate",
"pandas._libs.interval.Interval",
"numpy... |
charliezjw/Neural-Signal-Decoder | [
"fb0df09ba0314724c7c90141bd47cc8fb0201b7a"
] | [
"try.py"
] | [
"import numpy as np\nimport tensorflow as tf\n\n# a = tf.placeholder(tf.int32, [None, 3])\n#\n# b = tf.convert_to_tensor(tf.argmax(tf.bincount(a[0])))\n# b = tf.stack([b, tf.argmax(tf.bincount(a[1]))], 0)\n# for i in range(2, 5):\n# max_indx = tf.argmax(tf.bincount(a[i]))\n# b = tf.concat([b, [max_indx]], 0... | [
[
"numpy.asarray",
"numpy.zeros",
"numpy.bincount",
"numpy.equal"
]
] |
lcintron/WhoopClient | [
"46ccc6c3e3b98f4b6c82cf8938056d72a22bd6b6"
] | [
"WhoopClient.py"
] | [
"import requests\nimport pandas as pd\nimport numpy as np\nimport configparser\nfrom datetime import datetime\nfrom dateutil import relativedelta, parser, rrule\nfrom dateutil.rrule import WEEKLY\n\n\nclass WhoopClient:\n '''A class to allow a user to login and store their authorization code,\n then perfo... | [
[
"pandas.concat",
"pandas.to_datetime",
"numpy.isnan",
"pandas.json_normalize",
"pandas.DataFrame",
"pandas.isna"
]
] |
swidi/poemo-generation | [
"3a349ac3a6fc3e82b24410013bced60a24c2d8bf",
"3a349ac3a6fc3e82b24410013bced60a24c2d8bf",
"3a349ac3a6fc3e82b24410013bced60a24c2d8bf"
] | [
"third_party/texar-0.2.0/examples/bert/utils/data_utils.py",
"train_emosup.py",
"split.py"
] | [
"\"\"\"\nThis is the Data Loading Pipeline for Sentence Classifier Task from\nhttps://github.com/google-research/bert/blob/master/run_classifier.py\n\"\"\"\n# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not us... | [
[
"tensorflow.logging.info",
"tensorflow.train.Features",
"tensorflow.gfile.Open",
"tensorflow.python_io.TFRecordWriter"
],
[
"tensorflow.reduce_max",
"tensorflow.transpose",
"tensorflow.local_variables_initializer",
"tensorflow.Variable",
"tensorflow.shape",
"tensorflow.... |
simonlevine/x-transformer-icd | [
"17d0a84f8b8e1f69623a82c0afab26830c7a1eb8"
] | [
"app/lib/models.py"
] | [
"\"\"\"deserialize auto-icd models and provide a consistent interface\"\"\"\n\nimport typing as t\nimport json\nimport pickle\nfrom pathlib import Path\nimport numpy as np\nimport onnxruntime as rt\n\nAPP_ROOT = Path(\"./app\")\nASSETS_DIR = APP_ROOT/\"assets\"\n\n\nclass AutoICDModel:\n\n def __init__(self, onn... | [
[
"numpy.array"
]
] |
kayaei/pands-problem-set | [
"a7c48059e3024955794c67d9e6f969a42f4e3a6d"
] | [
"plotfunction.py"
] | [
"# Etem Kaya 16-Mar-2019\n\n# Solution to Problem-10.\n# File name: \"plotfunction.py\".\n\n# Problem-10: Write a program that displays a plot of the functions x, x2 & 2x\n# in the range [0, 4].\n\n#Import matplotlib and numpy packages \nimport matplotlib.pyplot as plt\nimport numpy as np\n\n# setup the lenght and ... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"numpy.arange",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
srio/shadow3-scripts | [
"10712641333c29ca9854e9cc60d86cb321f3762b"
] | [
"ID09/run_wofry_polychromatic_partial_coherence.py"
] | [
"\n\n\n#\n# Import section\n#\nimport numpy\n\nfrom syned.beamline.beamline_element import BeamlineElement\nfrom syned.beamline.element_coordinates import ElementCoordinates\nfrom wofry.propagator.propagator import PropagationManager, PropagationElements, PropagationParameters\n\nfrom wofry.propagator.wavefront1D.g... | [
[
"numpy.radians",
"numpy.linspace"
]
] |
brianzhang01/tskit | [
"e4d80810e19034cffa77bb14bc0b8d77537103ad"
] | [
"python/tests/test_metadata.py"
] | [
"# -*- coding: utf-8 -*-\n# MIT License\n#\n# Copyright (c) 2018-2019 Tskit Developers\n# Copyright (c) 2017 University of Oxford\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software w... | [
[
"numpy.array_equal"
]
] |
mahnooranjum/Python_Programming | [
"ba251e0e855842112efeb968d06458c60eaf1bd3",
"ba251e0e855842112efeb968d06458c60eaf1bd3",
"ba251e0e855842112efeb968d06458c60eaf1bd3",
"ba251e0e855842112efeb968d06458c60eaf1bd3",
"ba251e0e855842112efeb968d06458c60eaf1bd3"
] | [
"Misc/d3_heatmap.py",
"StatisticalTests_Snippets/U10_PvalWrappers8.py",
"Research_Autocolorization/m15_llandmarks2ab.py",
"Research_Autocolorization/m6_lhog2ab_n5.py",
"Research_Autocolorization/m2_lsift2ab_n7.py"
] | [
"'''\n Mahnoor Anjum\n Python:\n Trivariate Analysis\n'''\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport numpy as np\nimport math\nimport random \nfrom mpl_toolkits.mplot3d import Axes3D\n# sns.set()\n\n\npath = 'data/private/savepath/'\nfilename = 'v3_1'\ngenpath ... | [
[
"pandas.read_csv",
"pandas.DataFrame",
"matplotlib.pyplot.figure"
],
[
"scipy.stats.mannwhitneyu",
"pandas.read_csv",
"matplotlib.pyplot.subplots"
],
[
"matplotlib.pyplot.legend",
"pandas.read_csv",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Dense",
... |
mtzgroup/aimsprop | [
"464d88ad7a817da73027fd2ab7b12476bf59f83d",
"464d88ad7a817da73027fd2ab7b12476bf59f83d"
] | [
"aimsprop/pes.py",
"aimsprop/iam/diffraction.py"
] | [
"import numpy as np\n\nfrom .bundle import Bundle\n\n\ndef compute_pes(\n bundle: Bundle,\n carrier_frequency: float,\n alpha: float,\n eKT: np.ndarray,\n) -> Bundle:\n\n \"\"\"Compute the simple photoelectron spectroscopy, with Guassian blurring\n\n User is responsible for calculating and assigni... | [
[
"numpy.where",
"numpy.exp",
"numpy.zeros_like",
"numpy.sqrt"
],
[
"numpy.dot",
"numpy.sqrt",
"numpy.meshgrid",
"numpy.arcsin",
"numpy.abs",
"numpy.eye",
"numpy.cos",
"numpy.sin",
"numpy.zeros_like",
"numpy.array",
"numpy.sum"
]
] |
frssp/pymatgen | [
"5cc42912a12a265a603df7e34c856561f76edc1f",
"bdd977f065b66191557c7398b31a1571bc541fdb"
] | [
"dev_scripts/chemenv/equivalent_indices.py",
"pymatgen/analysis/diffraction/xrd.py"
] | [
"# coding: utf-8\n# Copyright (c) Pymatgen Development Team.\n# Distributed under the terms of the MIT License.\n\nfrom __future__ import division, unicode_literals\n\n\"\"\"\nDevelopment script of the ChemEnv utility to get the equivalent indices of the model coordination environments\n\"\"\"\n\n__author__ = \"Dav... | [
[
"numpy.mod"
],
[
"numpy.abs",
"numpy.subtract",
"numpy.transpose",
"numpy.array",
"numpy.exp"
]
] |
MostaSchoolOfAI/crab | [
"1c1fc21e902e4ee422ab367d691df16978972f8c"
] | [
"scikits/crab/recommenders/knn/classes.py"
] | [
"\"\"\"\nGeneralized Recommender models.\n\nThis module contains basic memory recommender interfaces used throughout\nthe whole scikit-crab package.\n\nThe interfaces are realized as abstract base classes (ie., some optional\nfunctionality is provided in the interface itself, so that the interfaces\ncan be subclass... | [
[
"numpy.isnan",
"numpy.lexsort",
"numpy.setdiff1d",
"numpy.vectorize",
"numpy.array",
"numpy.sum"
]
] |
Dipeshtamboli/domain-shift | [
"3f29577df6ab7269ad69a5fc651b63ed78708f0b",
"3f29577df6ab7269ad69a5fc651b63ed78708f0b"
] | [
"data_statistics.py",
"plot_tsne.py"
] | [
"import pdb\r\nimport numpy as np\r\nimport os\r\nimport glob\r\nimport torch\r\nimport torch.nn as nn\r\nimport torchvision.models as models\r\nimport torchvision.transforms as transforms\r\nfrom torch.autograd import Variable\r\nfrom PIL import Image\r\nfrom tqdm import tqdm\r\n\r\nrelative_path = 'datasets/resne... | [
[
"numpy.load",
"numpy.zeros",
"numpy.unique"
],
[
"matplotlib.pyplot.tight_layout",
"numpy.unique",
"matplotlib.pyplot.savefig",
"sklearn.manifold.TSNE",
"numpy.load",
"numpy.zeros"
]
] |
hephaex/probability | [
"740d0db0bf2b1e1a04cfd0b55481c44380b3cb05",
"740d0db0bf2b1e1a04cfd0b55481c44380b3cb05",
"740d0db0bf2b1e1a04cfd0b55481c44380b3cb05",
"740d0db0bf2b1e1a04cfd0b55481c44380b3cb05",
"740d0db0bf2b1e1a04cfd0b55481c44380b3cb05",
"740d0db0bf2b1e1a04cfd0b55481c44380b3cb05"
] | [
"tensorflow_probability/python/distributions/poisson_lognormal.py",
"tensorflow_probability/python/distributions/multivariate_student_t.py",
"tensorflow_probability/python/bijectors/transpose.py",
"tensorflow_probability/python/monte_carlo/expectation_test.py",
"tensorflow_probability/python/bijectors/recip... | [
"# Copyright 2018 The TensorFlow Probability 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 a... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.concat",
"numpy.sqrt",
"tensorflow.zeros",
"tensorflow.cast",
"tensorflow.random.poisson",
"tensorflow.linspace",
"tensorflow.reduce_logsumexp",
"tensorflow.broadcast_static_shape",
"tensorflow.name_scope",
"numpy.polynomial.h... |
endymecy/NDIToolbox | [
"f7a0a642b4a778d9d0c131871f4bfb9822ecb3da",
"f7a0a642b4a778d9d0c131871f4bfb9822ecb3da"
] | [
"models/tests/test_dataio.py",
"models/tests/test_preview_window_model.py"
] | [
"\"\"\"test_dataio.py - tests the dataio module\n\nChris R. Coughlin (TRI/Austin, Inc.)\n\"\"\"\n\n__author__ = 'Chris R. Coughlin'\n\nimport unittest\nfrom models import dataio\nfrom controllers import pathfinder\nfrom utils.skiptest import skipIfModuleNotInstalled\nimport h5py\nimport numpy as np\nimport numpy.te... | [
[
"numpy.fromfile",
"numpy.array_equal",
"numpy.genfromtxt",
"numpy.loadtxt",
"numpy.load",
"numpy.empty"
],
[
"numpy.array_equal"
]
] |
Kohulan/Decimer-Python | [
"17373e02faedb28ba94742f61001bb3c6b015798"
] | [
"Networks/4_layer_net_Parameter_optimization.py"
] | [
"'''\r\n * This Software is under the MIT License\r\n * Refer to LICENSE or https://opensource.org/licenses/MIT for more information\r\n * Written by Kohulan Rajan\r\n * © 2019\r\n'''\r\n#Parallelized datareading network\r\n\r\nimport tensorflow as tf\r\nimport os\r\nimport sys\r\nimport numpy as np\r\nimport matpl... | [
[
"matplotlib.pyplot.legend",
"numpy.amax",
"numpy.asarray",
"tensorflow.cast",
"matplotlib.pyplot.plot",
"numpy.mean",
"tensorflow.train.AdamOptimizer",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.gcf",
"tensorflow.ConfigProto",
"matplotlib.pyplot.subplot",
"matplotl... |
PyJedi/quantum | [
"3f4a3c320e048b8a8faf3a10339975d2d5366fb6"
] | [
"tensorflow_quantum/core/ops/batch_util_test.py"
] | [
"# Copyright 2020 The TensorFlow Quantum 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# Unl... | [
[
"numpy.arange",
"tensorflow.test.main",
"numpy.pad",
"scipy.stats.entropy"
]
] |
maxgreat/dsve-loc | [
"dd6807d02c0d5fd3e215be8e5c7a88e73102e561"
] | [
"text_features_extraction.py"
] | [
"\"\"\"\r\n****************** COPYRIGHT AND CONFIDENTIALITY INFORMATION ******************\r\nCopyright (c) 2018 [Thomson Licensing]\r\nAll Rights Reserved\r\nThis program contains proprietary information which is a trade secret/business \\\r\nsecret of [Thomson Licensing] and is protected, even if unpublished, und... | [
[
"torch.load",
"torch.utils.data.DataLoader",
"torch.no_grad",
"torch.device",
"numpy.vstack"
]
] |
MIRCen/brukerapi-python | [
"5455800895924c69bf839fa621fa7a06d343b4ff"
] | [
"test/test_jcampdx.py"
] | [
"from brukerapi.jcampdx import JCAMPDX\nimport numpy as np\nfrom pathlib import Path\nimport pytest\n\n@pytest.mark.skip(reason=\"in progress\")\ndef test_jcampdx(test_jcampdx_data):\n\n j = JCAMPDX(Path(test_jcampdx_data[1]) / test_jcampdx_data[0]['path'])\n for key, ref in test_jcampdx_data[0]['parameters']... | [
[
"numpy.array",
"numpy.array_equal"
]
] |
lkelvinm/OpenAeroStruct | [
"395075d28783c1b99b4ab25ddf034000caf9cd0d",
"395075d28783c1b99b4ab25ddf034000caf9cd0d"
] | [
"openaerostruct/structures/section_properties_tube.py",
"openaerostruct/structures/wingbox_geometry.py"
] | [
"from __future__ import division, print_function\nimport numpy as np\n\nfrom openmdao.api import ExplicitComponent\n\nclass SectionPropertiesTube(ExplicitComponent):\n \"\"\"\n Compute geometric properties for a tube element.\n The thicknesses are added to the interior of the element, so the\n 'radius' ... | [
[
"numpy.arange",
"numpy.zeros",
"numpy.ones"
],
[
"numpy.arccos",
"numpy.zeros",
"numpy.sum",
"numpy.ones"
]
] |
mo-cmyk/wbgapi | [
"a0f8658b7a74ec79256d7b66ff58cb95726e89aa"
] | [
"wbgapi/data.py"
] | [
"\n'''Access World Bank API data\n'''\n\nimport wbgapi as w\ntry:\n import numpy as np\n import pandas as pd\nexcept ImportError:\n np = None\n pd = None\n\ndef fetch(series, economy='all', time='all', mrv=None, mrnev=None, skipBlanks=False, labels=False, skipAggs=False, numericTimeKeys=False, params={}... | [
[
"pandas.Series",
"pandas.DataFrame"
]
] |
kpoeppel/pytorch_probgraph | [
"b78595ab03bbe92595ad2f6b35f5dd8bf84d6da0"
] | [
"examples/Model_HM_RWS.py"
] | [
"\nimport site\nsite.addsitedir('..')\n\nimport torch\nfrom pytorch_probgraph import BernoulliLayer\nfrom pytorch_probgraph import InteractionLinear\nfrom pytorch_probgraph import HelmholtzMachine\nfrom itertools import chain\nfrom tqdm import tqdm\n\nclass Model_HM_RWS(torch.nn.Module):\n def __init__(self):\n ... | [
[
"torch.optim.Adam",
"torch.zeros"
]
] |
acmore/ray | [
"9f0f54266064e203b0bdcc9d3fa947cb4518ebc0",
"9f0f54266064e203b0bdcc9d3fa947cb4518ebc0",
"9f0f54266064e203b0bdcc9d3fa947cb4518ebc0"
] | [
"rllib/utils/torch_ops.py",
"rllib/utils/memory.py",
"rllib/agents/es/es_torch_policy.py"
] | [
"import numpy as np\n\nfrom ray.rllib.utils import try_import_tree\nfrom ray.rllib.utils.framework import try_import_torch\n\ntorch, _ = try_import_torch()\ntree = try_import_tree()\n\n\ndef explained_variance(y, pred):\n y_var = torch.var(y, dim=[0])\n diff_var = torch.var(y - pred, dim=[0])\n min_ = torc... | [
[
"numpy.asarray"
],
[
"numpy.concatenate",
"numpy.empty"
],
[
"numpy.reshape",
"numpy.random.randn",
"numpy.prod"
]
] |
kanekosh/openconcept | [
"7878e5725eed78a023136b58250361531c7c7654"
] | [
"openconcept/analysis/performance/solver_phases.py"
] | [
"from __future__ import division\nfrom openmdao.api import Group, ExplicitComponent, IndepVarComp, BalanceComp, ImplicitComponent\nimport openconcept.api as oc\nfrom openconcept.analysis.atmospherics.compute_atmos_props import ComputeAtmosphericProperties\nfrom openconcept.analysis.aerodynamics import Lift, StallSp... | [
[
"numpy.sqrt",
"numpy.clip",
"numpy.arcsin",
"numpy.arange",
"numpy.isnan",
"numpy.less",
"numpy.cos",
"numpy.sin",
"numpy.tan",
"numpy.ones",
"numpy.flip",
"numpy.zeros"
]
] |
jialeli1/From-Voxel-to-Point | [
"b4dba9c4e9cd83e04199d9224f6ec7bf06b71f93"
] | [
"pcdet/utils/loss_utils.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\n\nfrom . import box_utils\nfrom . import center_utils\n\ntry:\n from itertools import ifilterfalse\nexcept ImportError: # py3k\n from itertools import filterfalse as ifilterfalse\n... | [
[
"torch.abs",
"torch.sigmoid",
"torch.norm",
"torch.isnan",
"torch.nn.functional.l1_loss",
"torch.nn.functional.cross_entropy",
"torch.from_numpy",
"torch.nn.functional.mse_loss",
"torch.log",
"torch.sort",
"torch.where",
"torch.nn.functional.smooth_l1_loss",
"to... |
Bharat-Runwal/path2vec | [
"f99188b882752ff9aa2c87334979b75483940ae0"
] | [
"wsd/graph_wsd_test_v1.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon May 7 17:13:25 2018\n\n@author: dorgham\n\"\"\"\n\nimport networkx as nx\nfrom nltk.corpus import wordnet as wn\nfrom nltk.corpus import wordnet_ic\nfrom nltk.stem import WordNetLemmatizer\nimport matplotlib.pyplot as plt\nimport xml.etree.ElementTree as ET\nfrom co... | [
[
"sklearn.metrics.precision_score",
"matplotlib.pyplot.close",
"sklearn.metrics.f1_score",
"matplotlib.pyplot.show",
"sklearn.metrics.recall_score"
]
] |
oshapoval/WarpX | [
"84d687da21ee93db67fdc43efec8a9cc80d0e6f9",
"84d687da21ee93db67fdc43efec8a9cc80d0e6f9"
] | [
"Examples/Tests/PythonWrappers/PICMI_inputs_2d.py",
"Examples/Modules/laser_injection/analysis_2d.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable\nfrom pywarpx import picmi\n\n# Number of time steps\nmax_steps = 100\n\n# Grid\nnx = 128\nnz = 128\n\n# Domain\nxmin = 0.e-6\nzmin = 0.e-6\nxmax = 50.e-6\nzmax = 50.e-6\n\n# Cell size\ndx = (x... | [
[
"numpy.outer",
"numpy.array",
"matplotlib.pyplot.suptitle",
"numpy.abs"
],
[
"numpy.fft.fft2",
"numpy.cross",
"matplotlib.pyplot.tight_layout",
"numpy.sqrt",
"numpy.arctan",
"numpy.linspace",
"numpy.meshgrid",
"matplotlib.use",
"numpy.abs",
"numpy.linalg... |
hlebars/YoutubeDataAnalysis | [
"0845effcdfdf6ab3281adc25840ed090e47498c8"
] | [
"Script/test.py"
] | [
"import pandas as pd\nimport datetime\nimport numpy as np\nimport os\nimport re\nimport matplotlib.pyplot as plot\n\nimport pytz\n# @timeit (repeat=3,number=10)\n\ndef EclatedSubPlot(SerieAfterGrpBy,ActivatePlotting,ListOfDateAndTime,Abbreviation):\n\n\n DicoDayOfWeek={\n \"00\":('Mon','Monday'), \"01\":(... | [
[
"pandas.to_datetime",
"pandas.read_csv",
"pandas.DataFrame",
"pandas.DatetimeIndex",
"matplotlib.pyplot.subplots_adjust",
"pandas.to_timedelta",
"matplotlib.pyplot.show"
]
] |
binnietom/py21cmmc_wv-1 | [
"2d5405700c1d99bd5f22c762999aea89d1ca1c23"
] | [
"devel/test_wv.py"
] | [
"from py21cmmc_wv import morlet\nimport numpy as np\n\nbw = 50.0\nnumin = 130.0\nN = 736\nnu = np.arange(N) * bw/N + numin\nmid = (nu[0] + nu[-1])/2\n\nspectrum = np.exp(-(nu-mid)**2/ (2*4.0**2))\n\ntrnsc, fc, _ = morlet.morlet_transform_c(spectrum, nu)\ntrnsc = np.abs(trnsc)**2\n"
] | [
[
"numpy.arange",
"numpy.exp",
"numpy.abs"
]
] |
vgp314/Udacity-Arvato-Identify-Customer-Segments | [
"6be1d4f1eeac391c17c70fdf584bdc4813f80fd8"
] | [
"cluster.py"
] | [
"from sklearn.cluster import KMeans\nfrom sklearn.cluster import MiniBatchKMeans\nimport matplotlib.pyplot as plt\n\n\ndef plot_clustering(data):\n\t'''\n\t\tDefinition:\n\t\t\tThis function plot the squared error for the clustered points\n\t\targs:\n\t\t\tdata to be clusterd\n\t\treturns:\n\t\t\tNone\n\t\t\n\t'''\... | [
[
"sklearn.cluster.KMeans",
"matplotlib.pyplot.xlabel",
"sklearn.cluster.MiniBatchKMeans",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
tkhe/tkdetection | [
"54e6c112ef2930e755f457e38449736f5743a9ea",
"54e6c112ef2930e755f457e38449736f5743a9ea",
"54e6c112ef2930e755f457e38449736f5743a9ea"
] | [
"projects/PointRend/point_rend/coarse_mask_head.py",
"projects/PointRend/train_net.py",
"tkdet/structures/instances.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom tkdet.layers import Conv2d\nfrom tkdet.layers import ShapeSpec\nfrom tkdet.models.roi_head.mask_head import MASK_HEAD_REGISTRY\nfrom tkdet.utils import weight_init\n\n__all__ = [\"CoarseMaskHead\"]\n\n\n@MASK_HEAD_REGISTRY.register()\ncla... | [
[
"torch.nn.init.constant_",
"torch.nn.Linear",
"torch.nn.init.normal_",
"torch.flatten"
],
[
"torch.cuda.device_count"
],
[
"torch.cat"
]
] |
Chicoryn/dream-go | [
"6a4b71d7e1fcc28110ba859c0a2b59c10041c083"
] | [
"contrib/trainer/dream_tf/layers/policy_head.py"
] | [
"# Copyright (c) 2019 Karl Sundequist Blomdahl <karl.sundequist.blomdahl@gmail.com>\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitati... | [
[
"tensorflow.cast",
"tensorflow.nn.relu",
"numpy.array",
"tensorflow.reshape"
]
] |
eblur/newdust | [
"7e843ae2604a844826606ea04c459694fdd5c178"
] | [
"newdust/graindist/composition/cmdrude.py"
] | [
"import numpy as np\nfrom newdust import constants as c\n\n__all__ = ['CmDrude']\n\nRHO_DRUDE = 3.0 # g cm^-3\nLAM_MAX = c.hc / 0.01 # maximal wavelength that we will allow for RG-Drude\n\nclass CmDrude(object):\n \"\"\"\n | **ATTRIBUTES**\n | cmtype : 'Drude'\n | rho : grain density [g cm^-3]\n... | [
[
"numpy.size",
"numpy.power"
]
] |
luvrpg/cleverhans | [
"1f2ee7a04cff1ec54c96dcba5294f6e2d7780d42",
"1f2ee7a04cff1ec54c96dcba5294f6e2d7780d42"
] | [
"examples/nips17_adversarial_competition/dev_toolkit/sample_defenses/ens_adv_inception_resnet_v2/defense.py",
"cleverhans/attacks.py"
] | [
"\"\"\"Implementation of sample defense.\n\nThis defense loads inception resnet v2 checkpoint and classifies all images\nusing loaded checkpoint.\n\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport os\n\nimport numpy as np\nfrom scipy.m... | [
[
"tensorflow.Graph",
"tensorflow.train.Scaffold",
"tensorflow.gfile.Open",
"tensorflow.flags.DEFINE_string",
"tensorflow.train.MonitoredSession",
"tensorflow.placeholder",
"tensorflow.logging.set_verbosity",
"scipy.misc.imread",
"tensorflow.argmax",
"numpy.zeros",
"tenso... |
YaoYao1995/mbpo | [
"b9571e469459ce3a632b19dc3fee68c9ac3857b2"
] | [
"mbpo/algorithms/meee.py"
] | [
"## adapted from https://github.com/rail-berkeley/softlearning/blob/master/softlearning/algorithms/sac.py\r\n\r\nimport os\r\nimport math\r\nimport pickle\r\nfrom collections import OrderedDict\r\nfrom numbers import Number\r\nfrom itertools import count\r\nimport gtimer as gt\r\nimport pdb\r\n\r\nimport numpy as n... | [
[
"tensorflow.get_variable",
"tensorflow.python.training.training_util._increment_global_step",
"tensorflow.keras.models.clone_model",
"tensorflow.zeros",
"numpy.concatenate",
"numpy.mean",
"tensorflow.train.AdamOptimizer",
"tensorflow.group",
"tensorflow.stop_gradient",
"num... |
RyoTTa/geopm | [
"74246c8ce70ee47f53bc5629638f51c2c391027b"
] | [
"test_integration/geopm_test_integration.py"
] | [
"#!/usr/bin/env python\n#\n# Copyright (c) 2015, 2016, 2017, 2018, 2019, Intel Corporation\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions\n# are met:\n#\n# * Redistributions of source code must retain the above ... | [
[
"pandas.set_option",
"pandas.concat",
"pandas.DataFrame"
]
] |
lilleswing/Reinvent-1 | [
"ac4e3e6fa6379c6f4af883478dfd1b3407933ada",
"ac4e3e6fa6379c6f4af883478dfd1b3407933ada",
"ac4e3e6fa6379c6f4af883478dfd1b3407933ada",
"ac4e3e6fa6379c6f4af883478dfd1b3407933ada"
] | [
"running_modes/utils/general.py",
"running_modes/transfer_learning/link_invent_actions/collect_stats.py",
"running_modes/transfer_learning/link_invent_transfer_learning_runner.py",
"running_modes/curriculum_learning/logging/remote_curriculum_logger.py"
] | [
"import time\n\nimport numpy as np\nimport torch\n\n\ndef to_tensor(tensor):\n if isinstance(tensor, np.ndarray):\n tensor = torch.from_numpy(tensor)\n if torch.cuda.is_available():\n return torch.autograd.Variable(tensor).cuda()\n return torch.autograd.Variable(tensor)\n\n\ndef set_default_d... | [
[
"torch.set_default_tensor_type",
"torch.from_numpy",
"torch.cuda.is_available",
"torch.autograd.Variable"
],
[
"scipy.stats.entropy",
"numpy.histogram",
"numpy.sum"
],
[
"torch.utils.data.DataLoader"
],
[
"numpy.mean"
]
] |
Shreyashwaghe/monk_v1 | [
"62f34a52f242772186ffff7e56764e958fbcd920",
"62f34a52f242772186ffff7e56764e958fbcd920",
"62f34a52f242772186ffff7e56764e958fbcd920",
"62f34a52f242772186ffff7e56764e958fbcd920",
"62f34a52f242772186ffff7e56764e958fbcd920",
"62f34a52f242772186ffff7e56764e958fbcd920",
"62f34a52f242772186ffff7e56764e958fbcd92... | [
"monk/system_unit_tests/pytorch/test_block_resnet_v2.py",
"monk/system_unit_tests/pytorch/test_layer_average_pooling1d.py",
"monk/system_unit_tests/gluon/test_layer_max_pooling1d.py",
"monk/system_unit_tests/pytorch/test_activation_tanh.py",
"monk/system_unit_tests/gluon/test_layer_convolution2d.py",
"mon... | [
"import os\nimport sys\nsys.path.append(\"../../../monk/\");\nimport psutil\n\nfrom pytorch_prototype import prototype\nfrom compare_prototype import compare\nfrom common import print_start\nfrom common import print_status\n\nimport torch\nimport numpy as np\nfrom pytorch.losses.return_loss import load_loss\n\n\nde... | [
[
"torch.randn"
],
[
"torch.randn"
],
[
"numpy.random.rand"
],
[
"torch.randn"
],
[
"numpy.random.rand"
],
[
"torch.randn"
],
[
"tensorflow.placeholder"
]
] |
teristam/spiketoolk | [
"0ae7adabce46cf620c3627ee0093d890996ef355"
] | [
"spiketoolkit/preprocessing/center.py"
] | [
"from spikeextractors import RecordingExtractor\nfrom .transform import TransformRecording\nimport numpy as np\n\n\nclass CenterRecording(TransformRecording):\n preprocessor_name = 'Center'\n\n def __init__(self, recording, mode, seconds, n_snippets):\n if not isinstance(recording, RecordingExtractor):... | [
[
"numpy.median",
"numpy.mean"
]
] |
DoubleE1/Keras-GAN | [
"775eb82b18cb146203295f19c937d4290de2953f",
"775eb82b18cb146203295f19c937d4290de2953f"
] | [
"dcgan/mnist/InceptionScore.py",
"dcgan/cifar10/dcgan_cifar10.py"
] | [
"# calculate inception score for cifar-10 in Keras\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom math import floor\nfrom numpy import ones, expand_dims, log, mean, std, exp\nfrom numpy.random import shuffle\nfrom keras.applications.inception_v3 import InceptionV3, preprocess_input\nfrom keras.datasets ... | [
[
"numpy.log",
"numpy.asarray",
"numpy.std",
"numpy.mean",
"numpy.exp"
],
[
"matplotlib.pyplot.subplots",
"numpy.ones",
"numpy.random.normal",
"matplotlib.pyplot.close",
"numpy.add",
"numpy.zeros",
"numpy.vstack",
"numpy.random.randint"
]
] |
kaylode/Custom-Template | [
"b2f11bfacf2b03b793476a19781f9046fab6fd82",
"b2f11bfacf2b03b793476a19781f9046fab6fd82",
"b2f11bfacf2b03b793476a19781f9046fab6fd82",
"b2f11bfacf2b03b793476a19781f9046fab6fd82"
] | [
"theseus/utilities/cuda.py",
"theseus/classification/metrics/projection.py",
"configs/semantic/infer.py",
"theseus/base/trainer/supervised_trainer.py"
] | [
"\"\"\" CUDA / AMP utils\nHacked together by / Copyright 2020 Ross Wightman\n\"\"\"\nimport torch\nfrom typing import Any\nfrom theseus.utilities.loggers.observer import LoggerObserver\n\nLOGGER = LoggerObserver.getLogger('main')\n\ndef get_devices_info(device_names=\"0\"):\n\n if device_names.startswith('cuda')... | [
[
"torch.device",
"torch.cuda.get_device_properties",
"torch.is_tensor",
"torch.cuda.is_available"
],
[
"numpy.load",
"numpy.stack",
"numpy.save"
],
[
"matplotlib.use",
"torch.no_grad"
],
[
"torch.cuda.synchronize",
"torch.no_grad",
"torch.cuda.amp.autocas... |
wangx1996/CenterPillarNet | [
"4be3d53265b8ecb1f9572612fa87f7acd8c57669",
"4be3d53265b8ecb1f9572612fa87f7acd8c57669"
] | [
"src/config/train_config.py",
"src/evaluatefile.py"
] | [
"\"\"\"\n# -*- coding: utf-8 -*-\n-----------------------------------------------------------------------------------\n# Author: Nguyen Mau Dung\n# DoC: 2020.08.17\n# email: nguyenmaudung93.kstn@gmail.com\n-----------------------------------------------------------------------------------\n# Description: The config... | [
[
"torch.device",
"torch.cuda.device_count"
],
[
"numpy.amax",
"numpy.sqrt",
"torch.load",
"numpy.concatenate",
"numpy.max",
"numpy.zeros_like",
"torch.no_grad",
"numpy.reshape",
"numpy.sin",
"torch.tensor",
"numpy.min",
"numpy.amin",
"numpy.linalg.inv... |
alimuldal/scipy | [
"713cf7df7b759e2aaeef0f81eb632f48c9b4bae0"
] | [
"scipy/special/__init__.py"
] | [
"\"\"\"\n========================================\nSpecial functions (:mod:`scipy.special`)\n========================================\n\n.. module:: scipy.special\n\nNearly all of the functions below are universal functions and follow\nbroadcasting and automatic array-looping rules. Exceptions are noted.\n\nError h... | [
[
"numpy.dual.register_func",
"numpy.testing.Tester"
]
] |
pradip026/passengerCOVIDscan | [
"1ebbe23beb91963679a97d8e9fe45354c47bbbff"
] | [
"passengerCOVIDscan/glove_detection/tensorflow_infer.py"
] | [
"# -*- coding:utf-8 -*-\nimport cv2\nimport time\nimport argparse\nimport os\nimport numpy as np\nfrom PIL import Image\n#from keras.models import model_from_json\nfrom .utils.anchor_generator import generate_anchors\nfrom .utils.anchor_decode import decode_bbox\nfrom .utils.nms import single_class_non_max_suppress... | [
[
"numpy.max",
"numpy.expand_dims",
"numpy.argmax"
]
] |
KokBob/InitProject | [
"63b7cefb9a130118db9ff5405c5dd87bbe34e9f3"
] | [
"data_postprocessing_10.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\n20181010\r\nciklaminima\r\n\"\"\"\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport os \r\nimport pandas as pd\r\nimport _dataPostprLib_ as lib\r\nimport seaborn as sns\r\nimport importlib \r\n#%%\r\nsns.set()\r\n#sns.set_context(\"poster\")\r\nsns.set_context(... | [
[
"pandas.read_csv",
"matplotlib.pyplot.close"
]
] |
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