repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
philipp128/skypy | [
"7a08288ab50ed8054698b78b1125310614760367"
] | [
"skypy/linear/tests/test_eisenstein_hu.py"
] | [
"import numpy as np\nimport pytest\nfrom astropy.cosmology import default_cosmology\nfrom skypy.linear.eisenstein_hu import power_spectrum\n\n\ndef test_eisenstein_hu():\n \"\"\" Test Eisenstein & Hu Linear matter power spectrum with\n and without wiggles using astropy default cosmology\"\"\"\n cosmology =... | [
[
"numpy.array",
"numpy.allclose",
"numpy.random.uniform",
"numpy.isscalar",
"numpy.logspace"
]
] |
achao2013/DeepRecon | [
"1c9b0480710212e1fe86ab75dcf0b30bd9f654e7"
] | [
"deep3dmap/core/utils/weight_init.py"
] | [
"#!/usr/bin/env python\n# -*- coding=utf8 -*-\n\"\"\"\n# Author: achao\n# File Name: weight_init.py\n# Description:\n\"\"\"\nimport copy\nimport math\nimport warnings\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch import Tensor\n\nfrom deep3dmap.core.utils import Registry, build_from_cfg, ge... | [
[
"torch.nn.init.kaiming_uniform_",
"numpy.log",
"torch.nn.init.constant_",
"torch.no_grad",
"torch.nn.init.kaiming_normal_",
"torch.nn.init.xavier_uniform_",
"torch.nn.init.normal_",
"torch.nn.init.uniform_",
"torch.nn.init.xavier_normal_"
]
] |
mrugeles/mlflow | [
"ff819e69c215c6272cbea4b284a05d22ae8774be"
] | [
"mlflow/keras.py"
] | [
"\"\"\"\nThe ``mlflow.keras`` module provides an API for logging and loading Keras models. This module\nexports Keras models with the following flavors:\n\nKeras (native) format\n This is the main flavor that can be loaded back into Keras.\n:py:mod:`mlflow.pyfunc`\n Produced for use by generic pyfunc-based de... | [
[
"tensorflow.Graph",
"tensorflow.Session"
]
] |
fevorl/BM3D_py | [
"aefd4ceb2bd9e95bd7e67285a714bccd5e2140e5",
"aefd4ceb2bd9e95bd7e67285a714bccd5e2140e5"
] | [
"cpp2py_test/bior_2d_forward_test2.py",
"cpp2py_test/BM_test.py"
] | [
"import math\nimport numpy as np\nfrom cpp2py_test.bior_2d_forward_test1 import original_bior_2d_forward, bior15_coef\n\n\ndef bior_2d_forward(img):\n assert img.shape[0] == img.shape[1]\n N = img.shape[0]\n iter_max = int(math.log2(N))\n\n for iter in range(iter_max):\n coeffs2 = pywt.dwt2(img[:... | [
[
"numpy.abs"
],
[
"numpy.pad",
"numpy.array",
"numpy.empty",
"numpy.matmul",
"numpy.zeros",
"numpy.sum",
"numpy.ones",
"numpy.roll",
"numpy.eye",
"numpy.where",
"numpy.arange",
"numpy.argsort",
"numpy.append",
"numpy.maximum"
]
] |
ReleasedBrainiac/GraphToSequenceNN | [
"70861637088bc38054beeab44a5c478254b5da25"
] | [
"Scripts/Plotter/PlotHistory.py"
] | [
"import re\nimport matplotlib.pyplot as plt\nfrom DatasetHandler.ContentSupport import isNotNone, isNone\nfrom Plotter.SavePlots import PlotSaver\n\nclass HistoryPlotter(object):\n \"\"\"\n This class provides a History plotting pipeline using mathplot.\n \"\"\"\n\n _using_history:bool = False # This fo... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.suptitle",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
openclimatefix/predict_pv_yield_nwp | [
"10229c6976eb63075efb6777103596e4097dced2"
] | [
"predict_pv_yield_nwp/pv.py"
] | [
"# Read PV metadata and timeseries data\n\n# Based on code in https://github.com/openclimatefix/pvoutput\n# E.g. https://nbviewer.jupyter.org/github/openclimatefix/pvoutput/blob/master/examples/analyse_PV_data_for_9th_Aug_2019.ipynb\n\nimport cartopy.crs as ccrs\nimport numpy as np\nimport pandas as pd\n\nimport xa... | [
[
"pandas.DataFrame",
"pandas.read_csv",
"numpy.asanyarray",
"pandas.melt"
]
] |
dlkt-review-and-empirical-evaluation/dlkt-review-and-empirical-evaluation | [
"d1540513056190ab0fbf547d22257dda2dfcd323"
] | [
"scripts/extract_best_kfold_results.py"
] | [
"import argparse\nimport pandas as pd\nimport re\n\nass15 = 'assist15', 'ASSISTments 2015'\nass17 = 'assist17', 'ASSISTments 2017'\nprog19 = 'prog19', 'Programming 2019'\nsynth_k2 = 'synth-k2', 'Synthetic-K2'\nsynth_k5 = 'synth-k5', 'Synthetic-K5'\nass09up = 'assist09up', 'ASSISTments 2009 Updated'\nstat = 'stat', ... | [
[
"pandas.read_csv"
]
] |
emmmoore/vaccinesandcases | [
"74635333edb2569158668e3cc3ef3cbe1b41d88b"
] | [
".scripts/dataprep.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# # Exploring JHU COVID Case, Death, and Vaccine Information\n# This notebook takes the live, updated data from JHU CSSE and GovEx, formats and simplifies it for my purposes, and saves it in csv files in the same directory. The two data sources use slightly different conve... | [
[
"matplotlib.pyplot.xlim",
"pandas.merge",
"pandas.set_option",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.title",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.scatter",
"pandas.read_csv"
]
] |
wgorczyk/LoopStructural | [
"bedc7abd4c1868fdbd6ed659c8d72ef19f793875"
] | [
"LoopStructural/probability/_gradient_calculator.py"
] | [
"import numpy as np\n\nfrom LoopStructural.utils import getLogger\nlogger = getLogger(__name__)\n\ndef gradients(vals, func, releps=1e-3, abseps=None, mineps=1e-9, reltol=1,\n epsscale=0.5):\n \"\"\"\n Calculate the partial derivatives of a function at a set of values. The\n derivatives are ca... | [
[
"numpy.array",
"numpy.copy",
"numpy.isfinite",
"numpy.abs"
]
] |
DSSerialGeneva/cd15c0un7 | [
"93bc45854c5c58802c5ec69613a9253b7f927cb9"
] | [
"src/read/read_train_example.py"
] | [
"import numpy\nimport os\n\nfrom src.readers import SimpleBSONReader\n\n\ndef read_train_example(path='../../data/train_example.bson', pca_reduction=True):\n read_result = SimpleBSONReader.read_all(path)\n pixels = read_result.pixel_matrix\n numpy.savetxt(\"../../out/train_example.csv\", pixels, delimiter=... | [
[
"numpy.savetxt"
]
] |
GJBoth/MultiTaskPINN | [
"8a9bb23b8bfc0d0f678090e015316dbd0cfbf024",
"8a9bb23b8bfc0d0f678090e015316dbd0cfbf024"
] | [
"src/multitaskpinn/training/.ipynb_checkpoints/training-checkpoint.py",
"src/multitaskpinn/training/training.py"
] | [
"import torch\nimport time\nfrom math import pi\nimport numpy as np\n\nfrom ..utils.tensorboard import Tensorboard\nfrom ..utils.output import progress\nfrom .convergence import Convergence\nfrom ..model.deepmod import DeepMoD\nfrom typing import Optional\n\n\ndef train(model: DeepMoD,\n data: torch.Tensor... | [
[
"torch.cat",
"torch.norm",
"torch.split",
"torch.no_grad",
"numpy.arange",
"torch.load",
"torch.zeros_like",
"torch.mean",
"torch.sum"
],
[
"torch.stack",
"torch.arange",
"torch.max",
"torch.any",
"torch.norm",
"torch.split",
"torch.no_grad",
... |
SinghJasdeep/Attention-on-Attention-for-VQA | [
"cbc767541667e9bb32760ac7cd2e822eff232ff5"
] | [
"train.py"
] | [
"import os\nimport time\nimport torch\nimport torch.nn as nn\nimport utils\nfrom torch.autograd import Variable\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef instance_bce_with_logits(logits, labels):\n assert logits.dim() == 2\n\n loss = nn.functional.binary_cross_entropy_with_logits(logits,... | [
[
"torch.nn.functional.binary_cross_entropy_with_logits",
"torch.autograd.Variable",
"torch.max"
]
] |
aMp37/SimpleHTR | [
"2a8bad2990d83caaa004530cd3b3d87c5bd38ab4"
] | [
"venv/lib/python3.7/site-packages/tensorflow_core/contrib/ignite/python/ops/gen_dataset_ops.py"
] | [
"\"\"\"Python wrappers around TensorFlow ops.\n\nThis file is MACHINE GENERATED! Do not edit.\nOriginal C++ source file: gen_dataset_ops.cc\n\"\"\"\n\nimport collections as _collections\nimport six as _six\n\nfrom tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow\nfrom tensorflow.python.eager import ... | [
[
"tensorflow.python.framework.ops.RegisterShape",
"tensorflow.python.util.dispatch.dispatch",
"tensorflow.python.util.tf_export.kwarg_only",
"tensorflow.python.eager.context.context",
"tensorflow.python.framework.ops.convert_to_tensor",
"tensorflow.python.eager.execute.execute",
"tensor... |
accidentalgenius09/competitive-programming-solution | [
"210746a7928dcd601ad9a735de52cf7135851070"
] | [
"HackerRank/PythonHackerRankSolutions/Numpy/ShapeandReshape.py"
] | [
"'''\nTitle : Shape and Reshape\nSubdomain : Numpy\nDomain : Python\nAuthor : codeperfectplus\nCreated : 06 May 2020\n'''\nimport numpy as np\n\narr = list(map(int,input().split()))\narr = np.array(arr)\n\nprint(np.reshape(arr,(3,3)))\n\n"
] | [
[
"numpy.array",
"numpy.reshape"
]
] |
repeating/stock-analyzer | [
"c190fb23d22300abb9b2a060adcc213ebe4d8dbc"
] | [
"backend/data_merge.py"
] | [
"import glob\nimport pandas as pd\nimport os\nimport datetime\n\n\nclass DataMerge:\n def __init__(self, directory):\n self.directory = directory\n self.__data = self.get_data_from(self.directory)\n\n def date_to_int(self, dates):\n \"\"\"\n calculates number of days between 01/01/... | [
[
"pandas.read_csv"
]
] |
noah-kuo/modin | [
"a54875acbbe9e5db17b38f42fe236f3fe51207f4"
] | [
"modin/pandas/test/test_general.py"
] | [
"# Licensed to Modin Development Team under one or more contributor license agreements.\n# See the NOTICE file distributed with this work for additional information regarding\n# copyright ownership. The Modin Development Team licenses this file to you under the\n# Apache License, Version 2.0 (the \"License\"); you... | [
[
"pandas.isnull",
"pandas.notnull",
"numpy.array",
"pandas.isna",
"pandas.value_counts",
"pandas.to_datetime",
"pandas.merge",
"pandas.DataFrame",
"numpy.testing.assert_array_equal",
"pandas.merge_asof",
"pandas.notna",
"pandas.Timestamp",
"pandas.Series",
"p... |
mirestrepo/voxels-at-lems | [
"df47d031653d2ad877a97b3c1ea574b924b7d4c2"
] | [
"bvpl/bvpl_octree/taylor_vs_pca.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Mar 7 16:41:25 2011\n\n@author: -\n\"\"\"\n\nimport os;\nimport time;\nimport sys;\nimport plot_pca_functions;\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport math\n\ntaylor_error_capitol= 0.608546356589;\npca_error_9_capitol = 0.614236131016; #at 10% ... | [
[
"matplotlib.pyplot.figure"
]
] |
jinjiren/ParlAI | [
"40799aeee69f2a0bb25a1341bb8da0c44861268e"
] | [
"parlai/agents/transformer/modules.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\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nimport math\nimport numpy as np\n\nfrom parlai.core.torch_gener... | [
[
"torch.nn.Linear",
"torch.nn.ModuleList",
"torch.bmm",
"torch.LongTensor",
"numpy.cos",
"numpy.sin",
"torch.nn.LayerNorm",
"torch.nn.Softmax",
"torch.nn.init.constant_",
"torch.is_tensor",
"torch.nn.init.normal_",
"numpy.sqrt",
"torch.index_select",
"torch.n... |
jancami/edibles | [
"51263b24c5e8aef786692011289b906a810ad2f7"
] | [
"edibles/sightline.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport bisect\nfrom lmfit import Parameters\nimport astropy.constants as cst\n\nfrom edibles.models import ContinuumModel, VoigtModel\nfrom edibles.utils.edibles_spectrum import EdiblesSpectrum\n\n\nclass Sightline:\n '''A model of the sightline between the t... | [
[
"numpy.max",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"numpy.min",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
idnowgmbh/tensorflow | [
"8fb93c17234af9383aee3a911d5443e124f2988d"
] | [
"tensorflow/contrib/distributions/python/ops/gamma.py"
] | [
"# 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.python.framework.tensor_shape.TensorShape",
"tensorflow.python.ops.array_ops.identity",
"tensorflow.python.ops.math_ops.select",
"tensorflow.python.ops.math_ops.log",
"tensorflow.python.ops.math_ops.lgamma",
"tensorflow.python.framework.constant_op.constant",
"tensorflow.py... |
datawowio/automl | [
"0b368fdc0ff7aaa4f0ade0a5825f3d0a36fb4691"
] | [
"efficientdet/aug/autoaugment.py"
] | [
"# Copyright 2020 Google Research. 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... | [
[
"tensorflow.compat.v1.nn.depthwise_conv2d",
"tensorflow.compat.v1.map_fn",
"tensorflow.compat.v1.zeros",
"tensorflow.compat.v1.logging.info",
"tensorflow.compat.v1.transpose",
"tensorflow.compat.v1.tile",
"tensorflow.compat.v1.ones_like",
"tensorflow.compat.v1.equal",
"tensorfl... |
stevenaldinger/eden | [
"c5d749651101dabc06d7dea8e1d39544258f0d37"
] | [
"controllers/delphi.py"
] | [
"# coding: utf8\n\n\"\"\"\n Delphi Decision Maker - Controllers\n\"\"\"\n\nmodule = request.controller\nresourcename = request.function\n\nif not settings.has_module(module):\n raise HTTP(404, body=\"Module disabled: %s\" % module)\n\n# =========================================================================... | [
[
"numpy.arange"
]
] |
zhaipro/keras-wdsr | [
"4cb2084d1780739b4d4854087c7cb0c35e875711"
] | [
"src/train.py"
] | [
"import os\n\nimport numpy as np\nfrom keras import backend as K\nfrom keras.losses import mean_absolute_error\n\nimport utils\nfrom model import wdsr_b\n\n\ndef psnr(hr, sr, max_val=2):\n mse = K.mean(K.square(hr - sr))\n return 10.0 / np.log(10) * K.log(max_val ** 2 / mse)\n\n\ndef data_generator(path, batc... | [
[
"numpy.array",
"numpy.random.shuffle",
"numpy.log"
]
] |
psychemedia/numpyarray_to_latex | [
"b729fe7473de51f5e62c0b7092706226ef9c2d65"
] | [
"numpyarray_to_latex/main.py"
] | [
"\"\"\"\nProvides `to_ltx` to convert numpy arrays to LaTeX.\n\"\"\"\n\nimport numpy as np\n\nfrom numpyarray_to_latex.utils import (\n math_form,\n )\n\ndef to_ltx(a,\n fmt='{:6.4f}',\n latexarraytype='array',\n imstring='i',\n is_row_vector=True,\n ... | [
[
"numpy.array",
"numpy.real",
"numpy.iscomplexobj",
"numpy.arange",
"numpy.imag"
]
] |
Roryoung/realworldrl_suite | [
"be7a51cffa7f5f9cb77a387c16bad209e0f851f8"
] | [
"realworldrl_suite/utils/evaluators_test.py"
] | [
"# coding=utf-8\n# Copyright 2020 The Real-World RL Suite 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 ... | [
[
"numpy.random.uniform",
"numpy.load"
]
] |
veds12/aiheaven | [
"4a257f652164870e4d0f0e3f1358834802955562"
] | [
"gcn/layers.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"layers.ipynb\n\nAutomatically generated by Colaboratory.\n\nOriginal file is located at\n https://colab.research.google.com/drive/1fCQ_zLCcWNzgE99LK9B2cWrql8J3HgBO\n\"\"\"\n# Author : Vedant Shah\n# E-mail : vedantshah2012@gmail.com\n\nimport torch\nimport torch.nn as nn\nfrom tor... | [
[
"torch.rand",
"torch.empty",
"torch.eye",
"torch.dot"
]
] |
aryamccarthy/ANES | [
"29c56f8c46fd4e8b6725f329cb609f4f14a8acb0"
] | [
"notebooks/as_script/1.0-adm-load-data-2012-Copy1.py"
] | [
"\n# coding: utf-8\n\n# # Load and preprocess 2012 data\n# \n# We will, over time, look over other years. Our current goal is to explore the features of a single year.\n# \n# ---\n\n# In[1]:\n\nget_ipython().magic('pylab --no-import-all inline')\nimport pandas as pd\n\n\n# ## Load the data.\n# \n# ---\n# \n# If thi... | [
[
"pandas.read_stata"
]
] |
Adrian123K/pandas_ml | [
"05a901c1f5a49aafb4513ef8f0f825210f378983"
] | [
"7.1_simple_linear_regression.py"
] | [
"# -*- coding: utf-8 -*-\n\n### 기본 라이브러리 불러오기\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n'''\n[Step 1] 데이터 준비 - read_csv() 함수로 자동차 연비 데이터셋 가져오기\n'''\n# CSV 파일을 데이터프레임으로 변환\ndf = pd.read_csv('./auto-mpg.csv', header=None)\n\n# 열 이름 지정\ndf.columns = ['mpg','cyl... | [
[
"pandas.set_option",
"sklearn.linear_model.LinearRegression",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.show",
"pandas.read_csv"
]
] |
diwgan32/IKEA_ASM_Dataset | [
"8f41c15c4a7fb47f53235d2292d0eff8136ae492"
] | [
"action/pose_based/net/utils/graph.py"
] | [
"import numpy as np\n\nclass Graph():\n \"\"\" The Graph to model the skeletons extracted by the openpose\n\n Args:\n strategy (string): must be one of the follow candidates\n - uniform: Uniform Labeling\n - distance: Distance Partitioning\n - spatial: Spatial Configuration\n ... | [
[
"numpy.dot",
"numpy.zeros",
"numpy.sum",
"numpy.stack",
"numpy.linalg.matrix_power"
]
] |
ZhengDeQuan/AAA | [
"7755c6aa1cfa484a2836ae6059bca721de2a90e8",
"7755c6aa1cfa484a2836ae6059bca721de2a90e8",
"7755c6aa1cfa484a2836ae6059bca721de2a90e8"
] | [
"zqtflearn2/tests/test_inputs.py",
"zqtflearn2/examples/nlp/cnn_sentence_classification.py",
"tflearn_wide_and_deep.py"
] | [
"'''\n This file contains test cases for tflearn\n'''\n\nimport tensorflow as tf\nimport zqtflearn\nimport unittest\n\nclass TestInputs(unittest.TestCase):\n '''\n This class contains test cases for serval input types\n '''\n INPUT_DATA_1 = [ [ 1 ], [ 2 ], [ 3 ], [ 4 ], [ 5 ] ]\n INPUT_DATA_2 ... | [
[
"tensorflow.Graph",
"tensorflow.placeholder"
],
[
"tensorflow.expand_dims"
],
[
"tensorflow.variable_op_scope",
"pandas.crosstab",
"numpy.exp",
"tensorflow.reshape",
"tensorflow.greater",
"pandas.read_csv",
"tensorflow.add_to_collection",
"tensorflow.cast",
... |
EvanBagis/gb_rf_evolution | [
"82e9c904eaa2f1ea05a330dea5087bf07caebf48"
] | [
"gb_rf_evolution/gb_train.py"
] | [
"import lightgbm as lgb\nimport xgboost as xgb\nfrom sklearn.metrics import mean_squared_error, mean_absolute_error, explained_variance_score, r2_score\nfrom matplotlib import pyplot as plt\nimport numpy as np\nimport pandas as pd\n\ndef compile_model(network):\n \"\"\"\n :param network dict: dictionary with ... | [
[
"sklearn.metrics.r2_score",
"numpy.array"
]
] |
AMReX-Astro/MAESTRO- | [
"53b99e9451c1d4f8f113b19d7de5ba7963531382"
] | [
"Exec/test_problems/reacting_bubble/scaling/sc20/plot.py"
] | [
"import matplotlib\nmatplotlib.use('agg')\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport os\nimport argparse\n\ndef plot():\n\n results_dir = './'\n\n results_files = [result for result in os.listdir(results_dir) if 'MAESTROeX' in result]\n\n n_gpus_per_node = 6\n\n throughput_list = []\n ... | [
[
"matplotlib.use",
"numpy.array",
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.tick_params",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.ylabel",
"mat... |
dperl-sol/cctbx_project | [
"b9e390221a2bc4fd00b9122e97c3b79c632c6664",
"b9e390221a2bc4fd00b9122e97c3b79c632c6664",
"b9e390221a2bc4fd00b9122e97c3b79c632c6664"
] | [
"xfel/amo/pnccd_ana/mpi_fxs_mask.py",
"mmtbx/regression/tls/tst_tls_utils.py",
"xfel/command_line/radial_average.py"
] | [
"from __future__ import absolute_import, division, print_function\nfrom six.moves import range\n\nfrom psana import *\nimport sys\nimport numpy as np\nfrom xfel.amo.pnccd_ana import pnccd_tbx\nfrom xfel.amo.pnccd_ana import pnccd_hit\nfrom xfel.amo.pnccd_ana import fx... | [
[
"numpy.equal",
"numpy.array",
"matplotlib.pyplot.ion",
"numpy.savetxt",
"numpy.zeros",
"numpy.copy",
"numpy.genfromtxt",
"numpy.seterr",
"numpy.nonzero",
"numpy.column_stack"
],
[
"numpy.random.seed",
"numpy.array",
"numpy.mean"
],
[
"numpy.concatena... |
Neo-X/R_multiworld | [
"839513a48ddf2f5ae2eadc43435ac6981ddea1f4"
] | [
"multiworld/envs/mujoco/sawyer_xyz/pickPlace/sawyer_coffee.py"
] | [
"from collections import OrderedDict\nimport numpy as np\nfrom gym.spaces import Box, Dict\n\nfrom multiworld.envs.env_util import get_stat_in_paths, \\\n\tcreate_stats_ordered_dict, get_asset_full_path\nfrom multiworld.core.multitask_env import MultitaskEnv\nfrom multiworld.envs.mujoco.sawyer_xyz.push.sawyer_push ... | [
[
"numpy.concatenate",
"numpy.rot90",
"numpy.array",
"numpy.linalg.norm",
"numpy.exp",
"numpy.mean",
"numpy.random.uniform",
"numpy.transpose"
]
] |
MarcusTL12/School | [
"f7302f2d390e99ad9d06004e15da032c05ec59e7"
] | [
"18Host/TMA4120/latex/PyplotTesting/Scripts/subfactorial.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef subf(n):\n\tif n <= 1:\n\t\treturn 0\n\telif n == 2:\n\t\treturn 1\n\t\n\treturn (n - 1) * (subf(n - 1) + subf(n - 2))\n\n\nx = np.arange(1, 5, 1)\n\ny = np.vectorize(subf)(x)\n\nplt.plot(x, y)\n\nplt.show()\n\n"
] | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot",
"numpy.arange",
"numpy.vectorize"
]
] |
NishthaShukla/eda | [
"4190604dcb24c2f9a03a7d0ad59be30aca18f05a"
] | [
"code.py"
] | [
"# --------------\n# Code starts here\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom sklearn.preprocessing import Imputer\nfrom sklearn.preprocessing import LabelEncoder\nimport numpy as np\nfrom scipy.stats import skew\n#### Data 1\n# Load the data\n\ndf = pd.read_csv(path)\n\n# Overview of the data\n... | [
[
"matplotlib.pyplot.colorbar",
"sklearn.preprocessing.LabelEncoder",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"scipy.stats.skew",
"numpy.sqrt",
"pandas.read_csv",
"sklearn.preprocessing.Imputer"
]
] |
matheusMoreno/BentoML | [
"4c139142fae486ba1ccf6b24e89505c030e3df3f",
"4c139142fae486ba1ccf6b24e89505c030e3df3f",
"4c139142fae486ba1ccf6b24e89505c030e3df3f"
] | [
"bentoml/_internal/frameworks/tensorflow_v2.py",
"bentoml/_internal/frameworks/detectron.py",
"tests/integration/frameworks/test_catboost_impl.py"
] | [
"import os\nimport re\nimport uuid\nimport typing as t\nimport logging\nimport pathlib\nimport functools\nfrom typing import TYPE_CHECKING\nfrom distutils.dir_util import copy_tree\n\nfrom simple_di import inject\nfrom simple_di import Provide\n\nimport bentoml\nfrom bentoml import Tag\nfrom bentoml.exceptions impo... | [
[
"tensorflow.compat.v1.global_variables_initializer",
"tensorflow.convert_to_tensor",
"tensorflow.compat.v1.get_default_graph",
"tensorflow.compat.v1.saved_model.load_v2",
"tensorflow.device",
"tensorflow.saved_model.save",
"tensorflow.config.set_visible_devices"
],
[
"torch.Ten... |
klauer/caproto-image-viewer | [
"5f267648d645c5950d1dfa5025a7a2a582200efb"
] | [
"caimageviewer/gl_util.py"
] | [
"import sys\nimport numpy as np\nfrom contextlib import contextmanager\nfrom qtpy.QtGui import QOpenGLBuffer\n\n\ndef setup_vertex_buffer(gl, data, shader, shader_variable):\n 'Setup a vertex buffer with `data` vertices as `shader_variable` on shader'\n vbo = QOpenGLBuffer(QOpenGLBuffer.VertexBuffer)\n vbo... | [
[
"numpy.array",
"numpy.ctypeslib.ndpointer",
"numpy.asarray"
]
] |
viraat/skynet-today | [
"fee4f2f2f9298221b9b03ca91c104b27ef3aa423"
] | [
"scripts/csv2md.py"
] | [
"import os\nimport logging\nimport argparse\nfrom collections import Counter\n\nimport pandas as pd\nimport inflect\n\n\nimport sys\nreload(sys)\nsys.setdefaultencoding('utf-8')\n\n_CATEGRORIES = [\n 'Mini Briefs',\n 'Advances & Business',\n 'Concerns & Hype',\n 'Analysis & Policy',\n 'Expert Opinion... | [
[
"pandas.read_csv"
]
] |
markusschmitt/QuSpin | [
"c239d01e6ce76253b03440cda3c8819a9f63e288"
] | [
"quspin/tools/expm_multiply_parallel_core/expm_multiply_parallel_core.py"
] | [
"from scipy.sparse.linalg import LinearOperator,onenormest,aslinearoperator\nfrom .expm_multiply_parallel_wrapper import (_wrapper_expm_multiply,\n\t_wrapper_csr_trace,_wrapper_csr_1_norm)\nfrom scipy.sparse.construct import eye\nfrom scipy.sparse.linalg._expm_multiply import _fragment_3_1,_exact_1_norm\nimport sci... | [
[
"numpy.result_type",
"numpy.array",
"scipy.sparse.linalg.onenormest",
"numpy.asarray",
"numpy.zeros",
"numpy.ascontiguousarray",
"scipy.sparse.linalg._expm_multiply._fragment_3_1",
"scipy.sparse.linalg.LinearOperator",
"numpy.finfo",
"numpy.can_cast",
"numpy.conj",
... |
kazush/tokyo_covid19_stat | [
"dbb856ef2a1bb40a8e7502d27b860cbc69f27cd5"
] | [
"stat_by_area.py"
] | [
"from typing import List\nimport argparse\nimport chart_studio.plotly as py\nimport plotly.express as px\nimport pandas as pd\n\nclass TokyoCovid19Stat:\n \"\"\"Holds Tokyo Covid-19 stat data.\"\"\"\n\n def __init__(self, csv_file_path: str = None):\n self.csv_file_path = csv_file_path\n self._d... | [
[
"pandas.read_csv"
]
] |
RPGroup-PBoC/chann_cap | [
"f2a826166fc2d47c424951c616c46d497ed74b39",
"f2a826166fc2d47c424951c616c46d497ed74b39"
] | [
"src/theory/scripts/channcap_protein_multi_prom_iptg_range.py",
"src/image_analysis/scripts/microscopy_bootstrap.py"
] | [
"#%%\n# Our numerical workhorses\nimport numpy as np\nimport pandas as pd\n\nimport itertools\n# Import libraries to parallelize processes\nfrom joblib import Parallel, delayed\n\n# Import matplotlib stuff for plotting\nimport matplotlib.pyplot as plt\nimport matplotlib.cm as cm\nimport matplotlib as mpl\n\n# Seabo... | [
[
"numpy.array",
"pandas.DataFrame",
"numpy.arange",
"pandas.concat",
"pandas.read_csv"
],
[
"numpy.zeros",
"numpy.random.seed",
"pandas.DataFrame",
"numpy.median",
"numpy.mean",
"numpy.std",
"scipy.stats.skew",
"pandas.Series",
"pandas.read_csv"
]
] |
abdussamettrkr/dirt-t | [
"a605d0c31a4bec9e60eb533704cd5e423601c060"
] | [
"tensorbayes/nputils.py"
] | [
"import numpy as np\n\ndef log_sum_exp(x, axis=-1):\n a = x.max(axis=axis, keepdims=True)\n out = a + np.log(np.sum(np.exp(x - a), axis=axis, keepdims=True))\n return np.squeeze(out, axis=axis)\n\ndef kl_normal(qm, qv, pm, pv):\n return 0.5 * np.sum(np.log(pv) - np.log(qv) + qv/pv +\n ... | [
[
"numpy.concatenate",
"numpy.square",
"numpy.ceil",
"numpy.delete",
"numpy.log",
"numpy.random.seed",
"numpy.exp",
"numpy.random.get_state",
"numpy.squeeze",
"numpy.random.set_state"
]
] |
valmar/lcls2 | [
"1c24da076a8cd252cf6601e125dd721fd2004f2a"
] | [
"psana/psana/detector/UtilsEpix10ka.py"
] | [
"\n\"\"\"\n:py:class:`UtilsEpix10ka` contains utilities for epix10ka and its composite detectors\n=====================================================================================\n\nUsage::\n from psana.detector.UtilsEpix10ka import ...\n\n #inds = segment_indices_det(det)\n #long_name = fullname_det(... | [
[
"numpy.array",
"numpy.ones_like",
"numpy.bitwise_or",
"numpy.sum",
"numpy.right_shift",
"numpy.bitwise_and",
"numpy.take_along_axis",
"numpy.hstack",
"numpy.select"
]
] |
minionssso/PyABSA | [
"fd9a9a6fd55552a60329fd04b6830e1bb144d50f",
"fd9a9a6fd55552a60329fd04b6830e1bb144d50f"
] | [
"pyabsa/core/tc/classic/__bert__/dataset_utils/data_utils_for_training.py",
"pyabsa/core/atepc/models/lcfs_atepc.py"
] | [
"# -*- coding: utf-8 -*-\n# file: data_utils.py\n# author: songyouwei <youwei0314@gmail.com>\n# Copyright (C) 2018. All Rights Reserved.\n\nimport os\nimport pickle\n\nimport numpy as np\nimport tqdm\nfrom findfile import find_file\nfrom google_drive_downloader.google_drive_downloader import GoogleDriveDownloader a... | [
[
"numpy.ones",
"numpy.asarray"
],
[
"torch.nn.Linear",
"torch.zeros",
"torch.nn.Dropout",
"torch.mul",
"torch.cat",
"numpy.argmax",
"torch.tensor",
"torch.nn.CrossEntropyLoss"
]
] |
SU-ECE-17-7/ibeis | [
"b12a45b06d8ce8f52585494c15f6776f5889ed67",
"b12a45b06d8ce8f52585494c15f6776f5889ed67",
"b12a45b06d8ce8f52585494c15f6776f5889ed67"
] | [
"_broken/test_sql_numpy.py",
"ibeis/viz/interact/interact_matches.py",
"ibeis/gui/id_review_api.py"
] | [
"#!/usr/bin/env python2.7\n# -*- coding: utf-8 -*-\nfrom __future__ import absolute_import, division, print_function\nfrom six.moves import range\nimport numpy as np\nimport utool\nfrom ibeis.control import SQLDatabaseControl as sqldbc\nfrom ibeis.control._sql_helpers import _results_gen\nfrom os.path import join\n... | [
[
"numpy.product",
"numpy.empty"
],
[
"numpy.empty"
],
[
"numpy.full",
"numpy.array",
"matplotlib.backends.backend_agg.FigureCanvas",
"matplotlib.backends.backend_agg.Figure",
"matplotlib.is_interactive",
"matplotlib.interactive",
"numpy.hstack",
"numpy.vstack"
... |
yaochenzhu/MMDQEN | [
"d8f7273b8dc51ad28e86e891e26e536e35928080"
] | [
"data.py"
] | [
"import os\r\nfrom pathlib import Path\r\n\r\nimport numpy as np\r\nimport pandas as pd\r\nimport tensorflow as tf\r\nfrom skimage import io\r\nfrom tensorflow import keras\r\n\r\n\r\nclass BimodalDenoiseDataGen(keras.utils.Sequence):\r\n '''\r\n Generate train/validation/test samples for our multimodal\r... | [
[
"tensorflow.keras.utils.to_categorical",
"pandas.read_table",
"numpy.random.choice",
"numpy.zeros",
"numpy.random.shuffle"
]
] |
mexmi2021/mexmi-project | [
"ef735cb290d33b326f592a70fa9b7f7dc6b6281b"
] | [
"mexmi/subset_selection_strategy/bayesian_disagreement_dropout_sss.py"
] | [
"from base_sss import SubsetSelectionStrategy\nimport base_sss\nimport random\nimport torch\n\nclass BALDDropoutStrategy(SubsetSelectionStrategy):\n def __init__(self, size, Y_vec, n_drop=10, previous_s=None):\n self.previous_s = previous_s\n self.n_drop = n_drop\n super(BALDDropoutStrategy,... | [
[
"torch.log"
]
] |
petropusz/DistSup | [
"4f9dc50fb6c96f1e4348bb6b79a0b22d1078161a",
"4f9dc50fb6c96f1e4348bb6b79a0b22d1078161a"
] | [
"distsup/configuration/__init__.py",
"distsup/aligner.py"
] | [
"# -*- coding: utf8 -*-\n# Copyright 2019 JSALT2019 Distant Supervision Team\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/LICEN... | [
[
"torch.cuda.is_available"
],
[
"torch.zeros",
"torch.isnan",
"torch.IntTensor",
"torch.FloatTensor",
"numpy.copy",
"torch.set_printoptions",
"torch.tensor"
]
] |
texpomru13/espnet | [
"7ef005e832e2fb033f356c16f54e0f08762fb4b0",
"7ef005e832e2fb033f356c16f54e0f08762fb4b0",
"7ef005e832e2fb033f356c16f54e0f08762fb4b0",
"7ef005e832e2fb033f356c16f54e0f08762fb4b0",
"7ef005e832e2fb033f356c16f54e0f08762fb4b0",
"7ef005e832e2fb033f356c16f54e0f08762fb4b0",
"7ef005e832e2fb033f356c16f54e0f08762fb4b... | [
"espnet/optimizer/pytorch.py",
"espnet2/torch_utils/device_funcs.py",
"espnet2/tts/utils/duration_calculator.py",
"espnet/nets/pytorch_backend/transducer/transducer_tasks.py",
"espnet2/lm/espnet_model.py",
"espnet2/enh/separator/rnn_separator.py",
"test/espnet2/enh/separator/test_rnn_separator.py"
] | [
"\"\"\"PyTorch optimizer builders.\"\"\"\nimport argparse\n\nimport torch\n\nfrom espnet.optimizer.factory import OptimizerFactoryInterface\nfrom espnet.optimizer.parser import adadelta\nfrom espnet.optimizer.parser import adam\nfrom espnet.optimizer.parser import sgd\n\n\nclass AdamFactory(OptimizerFactoryInterfac... | [
[
"torch.optim.Adam",
"torch.optim.Adadelta",
"torch.optim.SGD"
],
[
"torch.tensor",
"torch.from_numpy"
],
[
"torch.no_grad",
"torch.cat"
],
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.LayerNorm",
"torch.cat",
"torch.log_softmax",
"torch.IntTens... |
halleanwoo/AGMA | [
"a1c4980e05150a9cfa1be338e7c8cbd8ccd6b002"
] | [
"src_convention/modules/agents/rnn_agent.py"
] | [
"import torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass RNNAgent(nn.Module):\n def __init__(self, input_shape, args):\n super(RNNAgent, self).__init__()\n self.args = args\n\n self.fc1 = nn.Linear(input_shape, args.rnn_hidden_dim)\n self.rnn = nn.GRUCell(args.rnn_hidden_dim... | [
[
"torch.nn.Linear",
"torch.nn.GRUCell"
]
] |
MANGA-UOFA/NAUS | [
"8c0c0815a280d0661adf588302848c7f1ecc56da",
"8c0c0815a280d0661adf588302848c7f1ecc56da"
] | [
"fairseq/data/data_utils.py",
"fairseq/data/summarization_dataset.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\ntry:\n from collections.abc import Iterable\nexcept ImportError:\n from collections import Iterable\nimport contextlib\nimport... | [
[
"numpy.random.rand",
"numpy.random.choice",
"numpy.copy",
"numpy.min",
"numpy.full",
"numpy.random.normal",
"numpy.random.poisson",
"numpy.random.get_state",
"numpy.random.randint",
"numpy.array",
"torch.max",
"numpy.random.set_state",
"numpy.asarray",
"torc... |
AnimatedRNG/taichi | [
"f738bc165803c9e5083deb314da1cb6ca42ad591",
"f1f403042dadf8b58887431dbf7a9a661c005bb2"
] | [
"examples/difftaichi/liquid.py",
"examples/difftaichi/liquid_render.py"
] | [
"import taichi as ti\nfrom mpl_toolkits.mplot3d import Axes3D\nimport os\nimport math\nimport numpy as np\nimport random\nimport cv2\nimport matplotlib.pyplot as plt\nimport time\nimport taichi as tc\n\nreal = ti.f32\nti.set_default_fp(real)\n\ndim = 3\n# this will be overwritten\nn_particles = 0\nn_solid_particles... | [
[
"numpy.array",
"matplotlib.pyplot.ion",
"numpy.random.randn",
"matplotlib.pyplot.figure"
],
[
"numpy.zeros",
"numpy.clip"
]
] |
dawnclaude/onnx2keras | [
"3d2a47c0a228b91fd434232274e216e491da36e3"
] | [
"test/layers/activations/test_sigmoid.py"
] | [
"import torch.nn as nn\nimport numpy as np\nimport pytest\n\nfrom test.utils import convert_and_test\n\n\nclass LayerSigmoid(nn.Module):\n \"\"\"\n Test for nn.layers based types\n \"\"\"\n def __init__(self):\n super(LayerSigmoid, self).__init__()\n self.sig = nn.Sigmoid()\n\n def forw... | [
[
"torch.nn.functional.sigmoid",
"numpy.random.uniform",
"torch.nn.Sigmoid"
]
] |
navistar792/web-scraping-challenge | [
"0959fc5bf994f8eb61a966917267be9906deb2dc"
] | [
"Missions_to_Mars/app.py"
] | [
"from flask import Flask, render_template, redirect, request, jsonify, Markup\nfrom flask_pymongo import PyMongo\nimport scrape_mars\nimport json\nimport pandas as pd\nimport time\n\napp = Flask(__name__)\n\n# Use PyMongo to establish Mongo connection\nmongo = PyMongo(app, uri=\"mongodb://localhost:27017/mars_db\")... | [
[
"pandas.DataFrame"
]
] |
AngadSethi/adapter-transformers | [
"b147bba9107a5a561aca28c99f4e4ec2816a6e4f"
] | [
"tests/test_adapter_trainer.py"
] | [
"import unittest\n\nimport torch\n\nfrom transformers import (\n AutoModelForSequenceClassification,\n AutoTokenizer,\n BertConfig,\n BertForSequenceClassification,\n GlueDataset,\n GlueDataTrainingArguments,\n Trainer,\n TrainingArguments,\n)\nfrom transformers.adapters.composition import F... | [
[
"torch.equal"
]
] |
bugrevelio/magenta | [
"a54c6e4aa8b32f2625d416fb1b39b03d123e1e51"
] | [
"magenta/models/rl_tuner/rl_tuner_ops.py"
] | [
"# Copyright 2016 Google Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appli... | [
[
"numpy.max",
"tensorflow.exp",
"tensorflow.contrib.rnn.LSTMCell",
"numpy.asarray",
"numpy.sum",
"tensorflow.global_variables",
"numpy.mean",
"tensorflow.reduce_max",
"tensorflow.squeeze",
"tensorflow.contrib.rnn.MultiRNNCell",
"numpy.random.multinomial",
"tensorflow... |
adi3/NiaAML | [
"e8ff31f16147ac497903cc5bb2e5badecda43ae7"
] | [
"niaaml/classifiers/random_forest.py"
] | [
"from niaaml.classifiers.classifier import Classifier\nfrom niaaml.utilities import MinMax\nfrom niaaml.utilities import ParameterDefinition\nfrom sklearn.ensemble import RandomForestClassifier as RF\nimport numpy as np\n\nimport warnings\nfrom sklearn.exceptions import ChangedBehaviorWarning, ConvergenceWarning, D... | [
[
"sklearn.ensemble.RandomForestClassifier"
]
] |
tangxyw/RecAlgorithm | [
"9d1907b63ef6be67b77660c10af655874a201b8d"
] | [
"algorithm/BST/leakyrelu.py"
] | [
"import tensorflow as tf\n\n\ndef leakyrelu(x, leak=0.01):\n \"\"\"\n leakyrelu激活函数\n Args:\n x (Tensor): input\n leak (int): x<0时的斜率\n\n Returns:\n Tensor\n \"\"\"\n f1 = 0.5 * (1 + leak)\n f2 = 0.5 * (1 - leak)\n return f1 * x + f2 * tf.abs(x)\n\n"
] | [
[
"tensorflow.abs"
]
] |
alexfikl/pyvisfile | [
"756d209237472036f296419751b79fbc4d48a1ef"
] | [
"test/test_xdmf.py"
] | [
"import numpy as np\nimport pytest\n\nfrom pytools.obj_array import make_obj_array\n\n\n# {{{ test_unstructured_vertex_grid\n\n@pytest.mark.parametrize(\"ambient_dim\", [2, 3])\n@pytest.mark.parametrize(\"dformat\", [\"xml\", \"hdf\", \"binary\"])\ndef test_unstructured_vertex_grid(ambient_dim, dformat, npoints=64)... | [
[
"numpy.sin",
"numpy.array",
"numpy.random.rand",
"numpy.empty",
"numpy.prod",
"numpy.arange",
"numpy.cos",
"numpy.linspace"
]
] |
brisvag/dynamotable | [
"baeea6fcebfa8b277be20c591b28fff658f46909"
] | [
"dynamotable/dynamotable.py"
] | [
"from pathlib import Path\nfrom typing import Union\n\nimport pandas as pd\n\nfrom .convention import COLUMN_NAMES\nfrom .table_map import table_map_read\n\n\ndef open(table_file: str, table_map_file: str = None) -> pd.DataFrame:\n \"\"\"\n Opens a dynamo table file, returning a DynamoTable object\n :param... | [
[
"pandas.DataFrame.from_dict",
"pandas.read_csv"
]
] |
AdityaPrasadMishra/TensorflowPractice | [
"7107d9043a4d54980e2106f44c42dd2a3727dced"
] | [
"FSL - Entire Project + Report/Final Project/Code/Exp1.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Nov 30 03:08:17 2017\n\n@author: aditya\n\"\"\"\n\n#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Nov 26 12:46:25 2017\n\n@author: aditya\n\"\"\"\n\nimport math\nimport os\n\nfrom tensorflow.examples.tutorials.mnist im... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.zeros",
"tensorflow.train.AdamOptimizer",
"tensorflow.get_default_graph",
"tensorflow.argmax",
"tensorflow.examples.tutorials.mnist.input_data.read_data_sets",
"tensorflow.Variable",
"matplotlib.pyplot.plot",
"tenso... |
ctuning/inference_results_v1.1 | [
"d9176eca28fcf6d7a05ccb97994362a76a1eb5ab",
"d9176eca28fcf6d7a05ccb97994362a76a1eb5ab"
] | [
"closed/FuriosaAI/code/quantization/mlperf_evaluation/python/ort_quantization.py",
"open/Dell/code/ssd-mobilenet/tensorrt/calibrator.py"
] | [
"import argparse\n\nimport cv2\nimport numpy as np\n\nfrom onnxruntime.quantization import quantize_static, CalibrationDataReader, QuantType\nfrom onnxruntime.quantization.calibrate import CalibrationMethod\nfrom onnxruntime.quantization.quant_utils import QuantFormat\n\nfrom dataset import pre_process_vgg\n\n\ndef... | [
[
"numpy.expand_dims"
],
[
"numpy.ascontiguousarray"
]
] |
WifiSpy/models | [
"9b17d796234b72c93f1d23aa3026657000894a1d"
] | [
"official/resnet/keras/keras_benchmark.py"
] | [
"# Copyright 2018 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.compat.v1.logging.set_verbosity"
]
] |
mishinma/alibi-detect | [
"9cc33902ed5f278d8efbcd9f58bf6ec5496be818"
] | [
"integrations/adserver/adserver/__main__.py"
] | [
"import argparse\n\nimport ceserver\nimport tensorflow as tf\n\ntf.keras.backend.clear_session()\n\nfrom .model import AlibiDetectModel\n\nDEFAULT_MODEL_NAME = \"model\"\n\nparser = argparse.ArgumentParser(parents=[ceserver.server.parser])\nparser.add_argument('--model_name', default=DEFAULT_MODEL_NAME,\n ... | [
[
"tensorflow.keras.backend.clear_session"
]
] |
Dih5/zadeh | [
"3cc0d2a4803a77d8d4d0a90c0012eea0397ee9ca"
] | [
"zadeh/tune.py"
] | [
"from .fis import FIS\n\nimport numpy as np\n\ntry:\n import pandas as pd\nexcept ImportError:\n pd = None\n\ntry:\n from sklearn.model_selection import GridSearchCV\nexcept ImportError:\n GridSearchCV = None\n\n\ndef _get_vars(fis):\n \"\"\"Get an encoded version of the parameters of the fuzzy sets ... | [
[
"numpy.asarray"
]
] |
abdmoh123/tremor-predictor | [
"4378024cc20af23a01195cf76f3268087f6ed785"
] | [
"predict_all_data.py"
] | [
"# libraries imported\nimport os\nimport pathlib\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.font_manager import FontProperties\n\n# uses predict folder code to run predictor on entire folders\nfrom predict_folder import predict_dir\n\n\ndef predict_dirs(model_type, target_prediction):\n ... | [
[
"numpy.max",
"matplotlib.font_manager.FontProperties",
"numpy.round",
"numpy.min",
"matplotlib.pyplot.subplots",
"numpy.mean",
"numpy.multiply",
"matplotlib.pyplot.show"
]
] |
buddhi1/CIFAR-10-project | [
"d80821fa7db21be130c71de2f20d49bdcc5561b6"
] | [
"utils.py"
] | [
"\nfrom sklearn.metrics import roc_curve, auc\nimport numpy as np\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.metrics import classification_report\nimport json\nimport pandas as pd\nfrom pathlib import Path\nimport matplotlib.pyplot as plt\nfrom pylab import rcParams\n# rcParams['figure.figsize'] = ... | [
[
"sklearn.metrics.confusion_matrix",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.xticks",
"pandas.DataFrame.from_records",
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"matplotlib.pyplot.tight_layout",
"matplotli... |
qzzhang/kb_SPAdes | [
"16592d6f56f2ac2d87cb32c59b552073fa917e59"
] | [
"lib/kb_SPAdes/kb_SPAdesImpl.py"
] | [
"# -*- coding: utf-8 -*-\n#BEGIN_HEADER\n# The header block is where all import statements should live\nfrom __future__ import print_function\nimport os\nimport re\nimport uuid\nimport requests\nimport json\nimport psutil\nimport subprocess\nimport numpy as np\nimport yaml\nimport time\nfrom pprint import pformat\n... | [
[
"numpy.histogram"
]
] |
kpj/PySpaMo | [
"673fd6f824b231b412a8ee810bbfe9a2a793661c"
] | [
"evolutionary_optimization.py"
] | [
"\"\"\"\nEvolutionary optimization of something\n\"\"\"\n\nimport random\nimport multiprocessing\n\nimport numpy as np\nimport numpy.random as npr\n\nimport matplotlib.pylab as plt\n\nfrom tqdm import tqdm\n\nfrom automata import SnowDrift\n\n\nclass EvolutionaryOptimizer(object):\n \"\"\" Optimize!\n \"\"\"\... | [
[
"numpy.array",
"numpy.random.random_integers",
"matplotlib.pylab.savefig",
"numpy.argmin",
"matplotlib.pylab.ylabel",
"numpy.sum",
"matplotlib.pylab.legend",
"numpy.mean",
"matplotlib.pylab.show",
"matplotlib.pylab.errorbar",
"matplotlib.pylab.xlabel",
"matplotlib.p... |
amitgupta98/ga-learner-dsmp-repo | [
"0622bb064610a8fca12c1ffb35303550facf8bd7"
] | [
"Make-Sense-of-census/code.py"
] | [
"# --------------\n# Importing header files\r\nimport numpy as np\r\n# print(path)\r\n\r\n# Path of the file has been stored in variable called 'path'\r\n\r\n#New record\r\nnew_record=[[50, 9, 4, 1, 0, 0, 40, 0]]\r\n\r\n#Code starts here\r\ncensus = np.array([])\r\ndata=np.genfromtxt(path, delimiter=\",\", sk... | [
[
"numpy.concatenate",
"numpy.max",
"numpy.array",
"numpy.genfromtxt",
"numpy.min",
"numpy.mean",
"numpy.std"
]
] |
jmdbsa0012/AMTNN | [
"906f99684875e096eb9fd7a626656bfa5d9936e3"
] | [
"MTL.py"
] | [
"\"\"\"\nThis version considers task's datasets have equal number of labeled samples\n\"\"\"\n\nimport os\nimport json\nfrom collections import defaultdict\nimport numpy as np\n\nfrom tensorboardX import SummaryWriter\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd impor... | [
[
"torch.rand",
"torch.cat",
"torch.optim.lr_scheduler.StepLR",
"numpy.fill_diagonal",
"numpy.zeros",
"torch.autograd.Variable",
"numpy.ones",
"numpy.mean",
"torch.nn.functional.cross_entropy",
"torch.cuda.is_available",
"torch.tensor",
"torch.mean",
"torch.nn.fun... |
chineshboy/dist-gnn | [
"e5506739ffed77d6fab39430db9042cbc8a58fb6"
] | [
"1D_CAGNET/dist_1d.py"
] | [
"import os\nimport math\nimport argparse\nimport pickle\n\nimport torch\nimport torch.distributed as dist\n\nfrom torch.nn import Parameter\nimport torch.nn.functional as F\n\nfrom sparse_coo_tensor_cpp import sparse_coo_tensor_gpu, spmm_gpu\n\nimport utils\nfrom dist_data import DistData\n\nrun = 0\n\n\ndef outer_... | [
[
"torch.zeros",
"torch.rand",
"torch.cat",
"torch.cuda.synchronize",
"torch.optim.Adam",
"torch.distributed.all_gather",
"torch.mm",
"torch.manual_seed",
"torch.nn.Parameter",
"torch.nn.functional.log_softmax",
"torch.autograd.grad",
"torch.distributed.all_reduce",
... |
sives5/pymetalog | [
"0cd332b132eb3c9117a827088f7082e346cb77d8"
] | [
"pymetalog/a_vector.py"
] | [
"import pandas as pd\nimport numpy as np\nimport scipy as sp\n\nfrom scipy.optimize import linprog, minimize, NonlinearConstraint\nfrom .pdf_quantile_functions import pdf_quantile_builder\nfrom .support import diffMatMetalog, pdfMetalog, quantileMetalog, newtons_method_metalog\n\nimport time\nimport warnings\n\ndef... | [
[
"numpy.concatenate",
"numpy.append",
"numpy.array",
"numpy.dot",
"numpy.zeros_like",
"numpy.zeros",
"scipy.optimize.NonlinearConstraint",
"numpy.absolute",
"pandas.DataFrame",
"numpy.eye",
"scipy.optimize.linprog",
"numpy.size",
"pandas.concat",
"numpy.repea... |
nonu116/HDR-GAN | [
"239f68dd07f1970e0317515a313b69a9c3914f74"
] | [
"tensorkit/restore.py"
] | [
"import os\n\nimport tensorflow as tf\n\nfrom tensorkit.log import logger, Color\n\n\nclass Restore(object):\n def __init__(self):\n self._var_list = None\n self._restore_saver = None\n self._restore_optimistic = False\n self.restore_ckpt_file = None\n self._inited = False\n\n ... | [
[
"tensorflow.variable_scope",
"tensorflow.train.NewCheckpointReader",
"tensorflow.global_variables",
"tensorflow.train.Saver"
]
] |
Owen-Gillespie/HuntMaster | [
"fcbf7b939122a943c706bfcbb38368b028802449"
] | [
"lib/matplotlib/stackplot.py"
] | [
"\"\"\"\nStacked area plot for 1D arrays inspired by Douglas Y'barbo's stackoverflow\nanswer:\nhttp://stackoverflow.com/questions/2225995/how-can-i-create-stacked-line-graph-with-matplotlib\n\n(http://stackoverflow.com/users/66549/doug)\n\n\"\"\"\nfrom __future__ import (absolute_import, division, print_function,\n... | [
[
"numpy.zeros_like",
"numpy.atleast_2d",
"numpy.zeros",
"numpy.sum",
"numpy.diff",
"numpy.arange",
"numpy.cumsum",
"numpy.row_stack"
]
] |
Whitemane/fluid-engine-dev | [
"fb2256badb80c04702db536b63b14754699038ca"
] | [
"src/tests/python_tests/particle_system_data_tests.py"
] | [
"\"\"\"\nCopyright (c) 2018 Doyub Kim\n\nI am making my contributions/submissions to this project solely in my personal\ncapacity and am not conveying any rights to any intellectual property of any\nthird parties.\n\"\"\"\n\nimport pyjet\nimport unittest\nimport numpy as np\n\n\nclass ParticleSystemData2Tests(unitt... | [
[
"numpy.array"
]
] |
penguinmenac3/leanai | [
"6d26575b248ff03c4a24009cd82f26ea99d96d15",
"6d26575b248ff03c4a24009cd82f26ea99d96d15",
"6d26575b248ff03c4a24009cd82f26ea99d96d15"
] | [
"leanai/core/indexed_tensor_helpers.py",
"examples/coco_faster_rcnn.py",
"tests/model/layers/test_flatten_vectorize.py"
] | [
"import torch\nimport numpy as np\n\n\ndef map_per_batch(fun, values, batch_indices):\n result = []\n for start, stop, value_slice in sliced_per_batch(values, batch_indices):\n result.append(fun(start, stop, value_slice))\n return torch.cat(result)\n\n\ndef sliced_per_batch(values, batch_indices):\n... | [
[
"numpy.where",
"torch.cat",
"torch.where"
],
[
"torch.zeros",
"numpy.array",
"numpy.zeros_like"
],
[
"torch.tensor"
]
] |
avalonstrel/SketchBERT | [
"1aeef221f299a5250243b1f6e23c02280d92f5d6"
] | [
"models/SketchTransformer/models/networks.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.nn.utils.spectral_norm as spectral_norm\nimport math\nimport numpy as np\nimport torchvision.models as models\n\nfrom modules.networks import get_pad\nfrom torch.distributions.multivariate_normal import MultivariateNormal\nfrom util... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.prod",
"torch.nn.ModuleList",
"torch.nn.LeakyReLU",
"torch.ones",
"torch.eye",
"torch.exp",
"torch.sum",
"torch.sqrt",
"torch.tensor",
"torch.zeros",
"torch.nn.Sequential",
"torch.nn.Tanh",
"torch.nn.Conv2d",
"t... |
ksboy/adversarial_attack | [
"cb1e02b8ff31056cdd0eb1f747c1b08ed12527bc",
"cb1e02b8ff31056cdd0eb1f747c1b08ed12527bc"
] | [
"modules.py",
"keras/esim_online.py"
] | [
"import torch\n\nclass FGM():\n def __init__(self, model):\n self.model = model\n self.backup = {}\n\n def attack(self, epsilon=1e-6, emb_name='embed'):\n # emb_name这个参数要换成你模型中embedding的参数名\n for name, param in self.model.named_parameters():\n if param.requires_grad and ... | [
[
"torch.norm",
"torch.isnan"
],
[
"numpy.array",
"sklearn.model_selection.StratifiedKFold",
"pandas.DataFrame",
"numpy.random.shuffle",
"pandas.read_csv"
]
] |
GzuPark/EXTD_Pytorch | [
"e99af10f282d07054c1cf7c4b8c035084daaff78"
] | [
"mobileFacenet_48_PReLU.py"
] | [
"import torch.nn as nn\nimport math\nimport torch\nimport torch.nn.functional as F\n\n\ndef conv_bn(inp, oup, stride, k_size=3):\n return nn.Sequential(\n nn.Conv2d(inp, oup, k_size, stride, 1, bias=False),\n nn.BatchNorm2d(oup),\n nn.PReLU()\n )\n\n\ndef conv_1x1_bn(inp, oup):\n retur... | [
[
"torch.cat",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.Conv2d",
"torch.nn.PReLU"
]
] |
bigaidream-projects/drmad | [
"a4bb6010595d956f29c5a42a095bab76a60b29eb"
] | [
"cpu_ver/hypergrad/kernel_methods.py"
] | [
"import numpy as np\n\ndef make_exp_kernel(L0):\n def exp_kernel(x1, x2):\n x1 = np.expand_dims(x1, 2) # Append a singleton dimension\n x2 = x2.T\n return np.exp(-np.mean(np.abs(x1 - x2), axis=1) / L0)\n return exp_kernel\n\ndef make_sq_exp_kernel(L0):\n def sq_exp_kernel(x1, x2):\n ... | [
[
"numpy.sum",
"numpy.abs",
"numpy.dot",
"numpy.expand_dims"
]
] |
amirbitran/dbfold | [
"f8f04b560da14611aa21ce07600188cb44d67d1c"
] | [
"dbfold/analyze_structures.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Mar 24 17:59:20 2017\n\n@author: amirbitran\n\nVarious functions that serve to compute the contacts matrix for a series of PDB snapshots\n\n\"\"\"\n\nimport numpy as np\nfrom matplotlib import pyplot as plt\nimport sklearn\nfrom sklearn import metrics\nfrom dbfold.ut... | [
[
"numpy.mean",
"numpy.multiply",
"numpy.where",
"numpy.max",
"matplotlib.pyplot.colorbar",
"matplotlib.colors.to_hex",
"matplotlib.pyplot.subplots",
"numpy.nonzero",
"numpy.transpose",
"numpy.nanmax",
"numpy.array",
"numpy.zeros",
"matplotlib.cm.get_cmap",
"m... |
qiujiangkun/mplopengl | [
"f828d17cd7b68856f92958e909456ebb6043445e"
] | [
"tests/test_backend_qt.py"
] | [
"import copy\nfrom unittest import mock\n\nimport matplotlib\nimport pytest\nfrom matplotlib import pyplot as plt\nfrom matplotlib._pylab_helpers import Gcf\n\n\n@pytest.fixture(autouse=True)\ndef mpl_test_settings(qt_module, mpl_test_settings):\n \"\"\"\n Ensure qt_module fixture is *first* fixture.\n\n W... | [
[
"matplotlib.backends.backend_qt5.qApp.processEvents",
"matplotlib.backends.backend_qt5._BackendQT5.mainloop",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure"
]
] |
laugh12321/Hyperspectral-Unmixing | [
"0314bb4ef8f22ab85e8e739f02ccd86564af4d88"
] | [
"src/model/train_unmixing.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Jan 29, 2021\n\n@file: train_unmixing.py\n@desc: Perform the training of the models for the unmixing problem.\n@author: laugh12321\n@contact: laugh12321@vip.qq.com\n\"\"\"\nimport os\nimport numpy as np\nimport tensorflow as tf\nfrom typing import ... | [
[
"numpy.random.seed",
"numpy.array",
"tensorflow.keras.optimizers.Adam",
"tensorflow.keras.callbacks.EarlyStopping"
]
] |
camillepradel/pykeen | [
"92a5186c522c3336e9febb2e5eada9ec4a584947"
] | [
"src/pykeen/models/unimodal/ermlpe.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"An implementation of the extension to ERMLP.\"\"\"\n\nfrom typing import Optional, Type\n\nimport torch\nfrom torch import nn\n\nfrom ..base import EntityRelationEmbeddingModel\nfrom ...losses import BCEAfterSigmoidLoss, Loss\nfrom ...regularizers import Regularizer\nfrom ...triple... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.Dropout",
"torch.repeat_interleave",
"torch.nn.ReLU",
"torch.nn.BatchNorm1d"
]
] |
butala/spectrum | [
"0c81ddaf6d00c05434262d123a16fc39be4c6f64"
] | [
"src/spectrum/criteria.py"
] | [
"\"\"\"Criteria for parametric methods.\n\n.. topic:: This module provides criteria to automatically select order in\n parametric PSD estimate or pseudo spectrum estimates (e.g, music).\n\n Some criteria such as the AIC criterion helps to chose the order of PSD\n models such as the ARMA model. Nevertheless... | [
[
"numpy.sum",
"numpy.array",
"numpy.prod",
"numpy.log"
]
] |
FrankieYin/master_project | [
"bcbc93429f577c6294eb9e8d67e5e0fd56a9c1c9"
] | [
"networks/sdf_net_decoder.py"
] | [
"import time\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.parallel\nimport torch.utils.data\nfrom torch import optim\nfrom torch.utils import data\nfrom tqdm import tqdm\n\nfrom networks import LATENT_CODE_SIZE, device\n# from train_autoencoder import SDFSampleDataset, save_checkpoint, SIGMA\n\nclass SDF... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.Dropout",
"torch.nn.Tanh",
"torch.nn.ReLU"
]
] |
xuanthuong/DOU-SI | [
"ade175480da5eb7f31dbf70a97463f9304345d94"
] | [
"TrainValue/multiclass_svm.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nKey classification\nusing multiclass Support Vector Machine (SVM)\nreference: \n\nDate: Jun 05, 2017\n@author: Thuong Tran\n@Library: scikit-learn\n\"\"\"\n\n\nimport os, glob, random\nimport numpy as np\nfrom pandas import DataFrame\nfrom sklearn.feature_extraction.text import Co... | [
[
"sklearn.metrics.confusion_matrix",
"matplotlib.pyplot.text",
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.svm.LinearSVC",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.colorbar",
"pandas.DataFrame",
"matplotlib.pyplot.tight_layout",
"numpy.array",
"matplotl... |
anishsingh20/tensor2tensor | [
"8ec4233e1012f2d542adb64835d39b76587367f5"
] | [
"tensor2tensor/bin/make_tf_configs.py"
] | [
"# Copyright 2017 Google Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"tensorflow.app.run"
]
] |
vipmunot/Data-Analysis-using-Python | [
"34586d8cbbc336508c4a7a68abe14944f1096252"
] | [
"Data Analysis with Pandas Intermediate/Challenge_ Summarizing Data-112.py"
] | [
"## 2. Introduction to the Data ##\n\nimport pandas as pd\nall_ages = pd.read_csv('all-ages.csv')\nrecent_grads = pd.read_csv('recent-grads.csv')\nprint(all_ages.head())\nprint(recent_grads.head())\n\n## 3. Summarizing Major Categories ##\n\n# Unique values in Major_category column.\nprint(all_ages['Major_category'... | [
[
"pandas.read_csv"
]
] |
Arcofcosmos/MyYolov4_Pytorch | [
"14c445503d0fc69b8a8b64ecdc87256ac4c1fce1",
"14c445503d0fc69b8a8b64ecdc87256ac4c1fce1"
] | [
".history/nets/CSPdarknet_20210816140029.py",
".history/nets/yolo4_20210816143924.py"
] | [
"import math\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\n#-------------------------------------------------#\n# MISH激活函数\n#-------------------------------------------------#\nclass Mish(nn.Module):\n def __init__(self):\n super(Mish, self).__init__()\n\n def forward(s... | [
[
"torch.cat",
"torch.nn.functional.softplus",
"torch.nn.BatchNorm2d",
"torch.nn.Conv2d",
"torch.load"
],
[
"torch.cat",
"torch.nn.MaxPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.LeakyReLU",
"torch.nn.Upsample",
"torch.nn.Conv2d"
]
] |
daohuei/ucsc-nlp-unicorn | [
"d19c99fc717e458e6cfbf1bbe06193251257afb1"
] | [
"nlp_243/hw3/utils.py"
] | [
"import copy\n\nimport torch\nfrom torch import nn\nimport numpy as np\n\nfrom tokens import *\n\n\ndef tokenize(corpus, callback=lambda sent: sent.split()):\n return [callback(sent) for sent in corpus]\n\n\ndef add_start_stop_tokens(corpus):\n return [[START_TOKEN] + sent + [STOP_TOKEN] for sent in corpus]\n... | [
[
"numpy.random.normal",
"numpy.array",
"numpy.fill_diagonal",
"numpy.zeros",
"torch.tensor",
"torch.nn.Embedding"
]
] |
koaning/polars | [
"9e7b66172d835ddf33eb6af1dfb57ff957463243"
] | [
"pandas_cmp/create_data.py"
] | [
"import pandas as pd\nimport numpy as np\nfrom pandas.util.testing import rands\n\ngroups = np.arange(10)\nstr_groups = np.array(list(\"0123456789\"))\nnp.random.seed(1)\n\nfor size in [1e2, 1e3, 1e4, 1e5, 1e6]:\n size = int(size)\n g = np.random.choice(groups, size)\n sg = np.random.choice(str_groups, siz... | [
[
"numpy.random.choice",
"numpy.random.seed",
"pandas.DataFrame",
"numpy.random.randn",
"numpy.tile",
"pandas.util.testing.rands",
"numpy.arange"
]
] |
karkaroff/castor | [
"881673f3dadb4f757fdfdf5d2ab9031e08512406",
"881673f3dadb4f757fdfdf5d2ab9031e08512406"
] | [
"sm_cnn/train.py",
"common/trainers/msrvid_trainer.py"
] | [
"import time\nimport os\nimport numpy as np\nimport random\n\nimport torch\nimport torch.nn as nn\nimport torch.onnx\nfrom torchtext import data\n\nfrom args import get_args\nfrom model import SmPlusPlus\nfrom utils.relevancy_metrics import get_map_mrr\nfrom trec_dataset import TrecDataset\nfrom wiki_dataset import... | [
[
"numpy.array",
"torch.cuda.manual_seed",
"torch.max",
"numpy.random.seed",
"torch.save",
"torch.FloatTensor",
"torch.optim.Adadelta",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.cuda.is_available",
"torch.load",
"torch.nn.CrossEntropyLoss"
],
[
"tor... |
WING-NUS/RL-for-Question-Generation | [
"d1966a47ef28c076902189469508194f659c5270",
"d1966a47ef28c076902189469508194f659c5270",
"d1966a47ef28c076902189469508194f659c5270"
] | [
"src/onqg/utils/sinusoid.py",
"src/onqg/utils/model_builder.py",
"discriminators/src/answerability/code/run_glue.py"
] | [
"import numpy as np\nimport torch\n\n\ndef get_sinusoid_encoding_table(n_position, d_hid, padding_idx=None):\n ''' Sinusoid position encoding table '''\n\n def cal_angle(position, hid_idx):\n return position / np.power(10000, 2 * (hid_idx // 2) / d_hid)\n\n def get_posi_angle_vec(position):\n ... | [
[
"numpy.sin",
"torch.FloatTensor",
"numpy.power",
"numpy.cos"
],
[
"torch.nn.Linear",
"torch.nn.DataParallel"
],
[
"scipy.stats.pearsonr",
"torch.cuda.is_available",
"sklearn.metrics.f1_score",
"torch.nn.CrossEntropyLoss",
"torch.nn.DataParallel",
"torch.manu... |
ClaudioGuevara/rosetta | [
"beb6a390433e7a98adb125b26a035ecd44e7b15a"
] | [
"datasets/generate_final_csv.py"
] | [
"import os\n\nimport pandas as pd\n\ninteractions_df = pd.read_csv(os.path.join(\n os.getcwd(), './interactions_filters_post_search.csv'))\nresumen_antigen_df = pd.read_csv(os.path.join(\n os.getcwd(), './resume_antigen_info.csv'))\n\n# Borramos las interacciones duplicadas\ninteractions_df = interactions_df.... | [
[
"pandas.merge"
]
] |
Peefy/CLRS_dugu_code-master | [
"33662f46dc346203b220d7481d1a4439feda05d2"
] | [
"src/chapter28/chapter28note.py"
] | [
"# coding:utf-8\n# usr/bin/python3\n# python src/chapter28/chapter28note.py\n# python3 src/chapter28/chapter28note.py\n\"\"\"\n\nClass Chapter28_1\n\nClass Chapter28_2\n\nClass Chapter28_3\n\nClass Chapter28_4\n\nClass Chapter28_5\n\n\"\"\"\nfrom __future__ import absolute_import, division, print_function\n\nimport... | [
[
"numpy.matrix"
]
] |
mkretsch327/causalnex | [
"036938ac7399c3030bb402d987de0c5befc80414"
] | [
"causalnex/structure/pytorch/notears.py"
] | [
"# Copyright 2019-2020 QuantumBlack Visual Analytics 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.org/licenses/LICENSE-2.0\n#\n# THE SOFTWARE IS P... | [
[
"sklearn.utils.check_array",
"numpy.arange"
]
] |
LogAnalysisTeam/logparser | [
"85b68dcc50f53f7cfcf138eefa1e0e162094cdd8"
] | [
"logparser/SLCT/SLCT.py"
] | [
"\"\"\"\r\nDescription: This file implements a wrapper around the original SLCT code in C\r\nAuthor: LogPAI team\r\nLicense: MIT\r\n\"\"\"\r\nimport sys\r\nsys.path.append('../')\r\n\r\nimport hashlib\r\nimport pandas as pd\r\nimport re\r\nfrom datetime import datetime\r\nfrom ..logmatch import regexmatch\r\nimport... | [
[
"pandas.DataFrame"
]
] |
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