repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
SimonDeussen/dope-drone-desegmentation-dlrv | [
"ba920b953f83fe10ea4baaee15cad9700662afd4"
] | [
"code/assets/config.py"
] | [
"# we need the os modules for working with the paths\nfrom os.path import join, isdir\nimport torch\n\nNUM_CHANNELS = 3\nNUM_CLASSES = 1\nNUM_LEVELS = 3\n\n\nINIT_LR = 0.001\nNUM_EPOCHS = 4\nBATCH_SIZE = 128\nTEST_SPLIT = 0.15\n\n\nINPUT_IMAGE_WIDTH = 256\nINPUT_IMAGE_HEIGHT = 256\n\nTHRESHOLD = 0.5\nBASE_OUTPUT = ... | [
[
"torch.cuda.is_available",
"torch.cuda.current_device"
]
] |
kslymn/rtlsdr5 | [
"e4527016e94de6288fababb03c87daf86b6dd720"
] | [
"views.py"
] | [
"import math\nimport sys\n\nimport numpy as np\nimport pygame\n\nimport freqshow\nimport ui\n\n\n# Spectrogram renkleri.\n\ndef lerp(x, x0, x1, y0, y1):\n\t\n\treturn y0 + (y1 - y0)*((x - x0)/(x1 - x0))\n\ndef rgb_lerp(x, x0, x1, c0, c1):\n\t\n\treturn (math.floor(lerp(x, x0, x1, float(c0[0]), float(c1[0]))),\n\t\t... | [
[
"numpy.floor"
]
] |
davis191/stingray | [
"9c4d03013ec58a27a04fc99b0f390d6b130a3c8e"
] | [
"stingray/pulse/tests/test_pulse.py"
] | [
"from __future__ import division, print_function, absolute_import\n\nimport numpy as np\nfrom stingray.pulse.pulsar import fold_events, get_TOA\nfrom stingray.pulse.pulsar import stat, z_n, pulse_phase, phase_exposure\nfrom stingray.pulse.pulsar import fold_detection_level, z2_n_detection_level\nfrom stingray.pulse... | [
[
"numpy.array",
"numpy.random.seed",
"numpy.random.poisson",
"numpy.ones",
"numpy.testing.assert_array_almost_equal",
"numpy.allclose",
"numpy.arange",
"numpy.cos",
"numpy.abs"
]
] |
robinsaheb/Encryption | [
"d58d939ca37b25fc2fde04bc25b48e744cf895a2"
] | [
"keygen.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Oct 11 22:10:22 2020\n\n@author: sahebsingh\n\"\"\"\n\nfrom util import *\nfrom math import ceil, log2\nimport numpy as np\nimport random\n\nclass GSWKeys:\n def __init__(self, k, q, t, e, A, B, datatype):\n self.n = k\n ... | [
[
"numpy.random.normal",
"numpy.dot",
"numpy.random.randint",
"numpy.append",
"numpy.all"
]
] |
scwolof/GPdoemd | [
"485265a66585a8ebe88d1ba3da957199159dbcbf",
"485265a66585a8ebe88d1ba3da957199159dbcbf"
] | [
"GPdoemd/case_studies/analytic/vthr2014linear.py",
"demos/demo_utils/case_study_graphics.py"
] | [
"\"\"\"\nMIT License\n\nCopyright (c) 2018 Simon Olofsson\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modi... | [
[
"numpy.sin",
"numpy.array",
"numpy.random.randn",
"numpy.sqrt"
],
[
"numpy.array",
"numpy.min",
"matplotlib.pyplot.rc",
"matplotlib.pyplot.tight_layout",
"numpy.sqrt",
"matplotlib.pyplot.subplot2grid",
"matplotlib.pyplot.show",
"numpy.linspace"
]
] |
Marc-Ruebsam/MeBaPiNa | [
"f2248be6f6186d366539ab97f5749a14c19fce82"
] | [
"scripts/convert_kreport.py"
] | [
"## SETUP ##\n\n## dependencies\nimport pandas as pd\n\n## logging\nsys.stdout = open(snakemake.log[0], 'w')\nsys.stderr = open(snakemake.log[0], 'w')\n\n## input files\ninput_dict = {\n 'kreport' : snakemake.input['kreport'],\n 'kronataxlist' : snakemake.input['kronataxlist']\n}\n\n## output files\noutput_di... | [
[
"pandas.read_csv",
"pandas.merge"
]
] |
nujabes0321456/Style-transfer | [
"3752df0a4bad660e5262c24e68e9f965bcc62666"
] | [
"main_vgg19_v2.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Wed May 20 04:12:40 2020\r\n\r\n@author: USER\r\n\"\"\"\r\n\r\n# In[import]:\r\nimport tensorflow as tf\r\nimport os\r\nimport sys\r\nimport scipy.io\r\nimport time\r\nimport datetime\r\nfrom IPython.display import Audio, display\r\nimport numpy as np\r\nimport libro... | [
[
"tensorflow.nn.conv2d",
"numpy.load",
"numpy.exp",
"tensorflow.reshape",
"tensorflow.global_variables_initializer",
"numpy.zeros_like",
"matplotlib.pyplot.savefig",
"numpy.save",
"tensorflow.transpose",
"tensorflow.constant",
"numpy.sqrt",
"tensorflow.nn.max_pool",
... |
iancrossfield/Eureka | [
"88b178d1b830c16915045b6387cf91955e0071e2",
"88b178d1b830c16915045b6387cf91955e0071e2"
] | [
"eureka/lib/models_c/py_func/orthoTrans.py",
"eureka/lib/demc.py"
] | [
"import numpy as np\n\n\ndef orthoTrans(params, trans, etc):\n \"\"\"\n This function uses principal component analysis to modify parameter values.\n\n Parameters\n ----------\n params: Array of params to be modified, length is npars for 1D\n If 2D, shape is npars x nsteps\n inv... | [
[
"numpy.asarray"
],
[
"numpy.random.rand",
"numpy.copy",
"numpy.min",
"numpy.exp",
"numpy.mean",
"numpy.multiply",
"numpy.where",
"numpy.concatenate",
"numpy.random.normal",
"numpy.divide",
"numpy.random.randint",
"numpy.arange",
"numpy.sqrt",
"numpy.... |
ankitkumarsamota121/smart-disease-prediction-dashboard | [
"863928ea053fad2da3a22e4db9f993ce951b9fa6"
] | [
"web_app/apps/world_dashboard.py"
] | [
"import dash_core_components as dcc\r\nimport dash_html_components as html\r\nfrom dash.dependencies import Input, Output, State\r\nfrom web_app.app import app\r\nimport pandas as pd\r\nfrom web_app.apps.helpers.helper_functions import get_tweets, get_polarity\r\n\r\ndf = pd.read_csv(\"/mnt/data/Events/CODE19/smart... | [
[
"pandas.read_csv"
]
] |
Tanvi141/JetpackJoyride | [
"cb74b135a60a37f2068eb73b2630d33b56b6f2bc"
] | [
"mando.py"
] | [
"import numpy as np\nfrom headerfile import *\n\n\nclass Mando:\n '''Define the mando\n '''\n\n def __init__(self, dirn, fly):\n self.__x = PLACEWIDTH # x coordinate of the torso\n self.__y = HEIGHT-GROUND-2 # y coordinate of the torso\n self.__dirn = dirn # -1 means left, 0 means s... | [
[
"numpy.zeros"
]
] |
navacarlos/prueba_fondea | [
"b1ab7c4f1c345c4d1a0c78d713d5ce67a643d7a3"
] | [
"auroramysql_to_redshift.py"
] | [
"#!/usr/bin/env python\n\nimport boto3\nimport psycopg2\nimport pymysql\nimport csv\nimport time\nimport sys\nimport os\nimport datetime\nfrom sqlalchemy import create_engine\nimport pandas as pd\nfrom datetime import date\n\ndatetime_object = datetime.datetime.now()\n\nprint (\"Data Pipeline: Aurora MySQL -> EC2 -... | [
[
"pandas.read_csv",
"pandas.merge"
]
] |
saidwho12/JulyGame | [
"064654aaaf516931a074ce4d5021f2ecdbe621e0"
] | [
"scripts/gui.py"
] | [
"import numpy as np\nimport glm\n\nfrom OpenGL.GL import *\n\nfrom scripts import mesh\n\n\nclass Rectangle(object):\n verts = np.array((-1, -1, 0,\n 1, -1, 0,\n 1, 1, 0,\n -1, 1, 0), dtype=np.float32)\n tex_coords = np.array((0, 0,\n ... | [
[
"numpy.array"
]
] |
TimZaman/keras | [
"04e0a10aea5024b6f135d7ee71c38ea5ddf548e0"
] | [
"keras/backend/tensorflow_backend.py"
] | [
"import tensorflow as tf\nfrom tensorflow.python.training import moving_averages\nfrom tensorflow.python.ops import tensor_array_ops\nfrom tensorflow.python.ops import control_flow_ops\nfrom tensorflow.python.ops import functional_ops\nfrom tensorflow.python.ops import ctc_ops as ctc\nfrom tensorflow.python.ops imp... | [
[
"tensorflow.group",
"tensorflow.ones",
"tensorflow.ones_like",
"tensorflow.zeros_like",
"tensorflow.nn.separable_conv2d",
"tensorflow.clip_by_value",
"tensorflow.greater",
"tensorflow.stack",
"tensorflow.nn.avg_pool",
"tensorflow.random_normal_initializer",
"tensorflow.... |
nzahasan/pyheclib | [
"225c1497944b1a9b0ad5564d1f4e356b13e90752"
] | [
"tests/test_reg_tseries.py"
] | [
"#!/usr/bin/env python3\nimport numpy as np\nimport pyheclib as phl\n\n# write regular time series\n\n\ndss_tseries6 = phl.hecdss(\"tseries_dss6.dss\",6)\ndss_tseries7 = phl.hecdss(\"tseries_dss7.dss\",7)\n\n\n\n# write regular tseries data \n\nreg_data = np.array([1.11, 2.12, 45.33, 2.32, 7.486868686, 9.89, 888888... | [
[
"numpy.array"
]
] |
grantseiter/OG-USA | [
"1a1ecde41876c97516099be61c6e4ed4e74eb593"
] | [
"ogcore/tests/test_output_plots.py"
] | [
"'''\nTests of output_plots.py module\n'''\n\nimport pytest\nimport os\nimport numpy as np\nimport matplotlib.image as mpimg\nfrom ogcore import utils, output_plots\n\n\n# Load in test results and parameters\nCUR_PATH = os.path.abspath(os.path.dirname(__file__))\nbase_ss = utils.safe_read_pickle(\n os.path.join(... | [
[
"matplotlib.image.imread",
"numpy.ones"
]
] |
sokovninn/yolact-artwin | [
"f1b7a55b76104cb03ca47498230563639782115c"
] | [
"train.py"
] | [
"from data import *\nfrom utils.augmentations import SSDAugmentation, BaseTransform\nfrom utils.functions import MovingAverage, SavePath\nfrom utils.logger import Log\nfrom utils import timer\nfrom layers.modules import MultiBoxLoss\nfrom yolact import Yolact\nimport os\nimport sys\nimport time\nimport math, random... | [
[
"torch.zeros",
"torch.stack",
"torch.set_default_tensor_type",
"torch.no_grad",
"torch.isfinite",
"torch.cuda.device_count",
"torch.cuda.is_available",
"torch.utils.data.DataLoader"
]
] |
chrismayemba/covid-19-open-data | [
"5bcba7f9253465ad817e073fab996fc9e6d97b38"
] | [
"src/pipelines/epidemiology/de_authority.py"
] | [
"# Copyright 2020 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"pandas.concat"
]
] |
UserAdminD3us/Microsoft-Certified-Azure-Data-Scientist-Associate-Certification-Guide | [
"62873b5a99120d240a8df8c0b7f81e6c95d5be02"
] | [
"chapter11/step01/prepare_data_runs_local.py"
] | [
"import argparse\nfrom azureml.core.run import Run, _OfflineRun\nfrom sklearn.model_selection import train_test_split\nimport lightgbm as lgb\nimport os\n\n\nparser = argparse.ArgumentParser()\nparser.add_argument(\"--dataset\", type=str, dest=\"dataset\", default=\"loans\")\nparser.add_argument(\n \"--output-pa... | [
[
"sklearn.model_selection.train_test_split"
]
] |
ajguss/FlapPy-Bird | [
"5dbb2f65bb564be5f6e7c99b02253b2c1b52c35d"
] | [
"flappy.py"
] | [
"import time\r\nimport arcade\r\nimport random\r\nfrom bird import Bird\r\nfrom pipe import Pipe\r\nfrom game_state import State\r\nfrom game_variables import *\r\nimport numpy as np\r\n\r\n\r\nclass Game(arcade.Window):\r\n\r\n def __init__(self, width, height):\r\n\r\n \"\"\"\r\n Initializer for ... | [
[
"numpy.array"
]
] |
cainja/RMG-Py | [
"413e74bb526f56077cd5f70bb41fb7a075636174"
] | [
"rmgpy/statmech/schrodingerTest.py"
] | [
"#!/usr/bin/env python\n# encoding: utf-8\n\n################################################################################\n#\n# RMG - Reaction Mechanism Generator\n#\n# Copyright (c) 2002-2017 Prof. William H. Green (whgreen@mit.edu), \n# Prof. Richard H. West (r.west@neu.edu) and the RMG Team (rmg_dev@mi... | [
[
"numpy.array",
"numpy.arange",
"numpy.exp"
]
] |
TxWENTY/30830_practical2 | [
"60e9ca3ea645c1c04de1153aecd4862a4bac24b4"
] | [
"pandas/core/tools/numeric.py"
] | [
"import numpy as np\n\nfrom pandas._libs import lib\n\nfrom pandas.core.dtypes.cast import maybe_downcast_to_dtype\nfrom pandas.core.dtypes.common import (\n ensure_object, is_datetime_or_timedelta_dtype, is_decimal, is_number,\n is_numeric_dtype, is_scalar)\nfrom pandas.core.dtypes.generic import ABCIndexCla... | [
[
"pandas.Index",
"numpy.array",
"pandas.core.dtypes.common.is_number",
"pandas.core.dtypes.common.is_decimal",
"pandas.core.dtypes.common.is_scalar",
"pandas.core.dtypes.cast.maybe_downcast_to_dtype",
"numpy.min",
"pandas.core.dtypes.common.is_numeric_dtype",
"pandas.core.dtypes... |
hyschn/practice-code | [
"cfa1eb373f723488a11af1107af16956a5851905"
] | [
"pytorch/trace.py"
] | [
"# encoding:utf-8\n\"\"\"\n@Time : 2020-02-12 18:24\n@Author : yshhuang@foxmail.com\n@File : trace.py\n@Software: PyCharm\n\"\"\"\n\nimport torch\nimport torchvision\n\n# An instance of your model.\nmodel = torchvision.models.resnet18()\n\n# An example input you would normally provide to your model's forward... | [
[
"torch.rand",
"torch.jit.trace",
"torch.ones"
]
] |
juanmabelda/FuzzyClassifier | [
"8020756e062ab4d2a36d2a6cb40640fbab69f801"
] | [
"FuzzyTree/FT_optimize.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Sep 3 16:07:03 2014\n\n@author: juanma\n\"\"\"\n\nfrom .FuzzyVars import *\nfrom scipy.optimize import fmin_slsqp\nfrom numpy import percentile, array, diff\n\ndef optimize_partition(FClass, Variable, VarName, terms):\n '''Optimize the partition of a variable to ... | [
[
"numpy.percentile",
"scipy.optimize.fmin_slsqp",
"numpy.diff"
]
] |
Ram-Aditya/Healthcare-Data-Analytics | [
"201b75462a436197862e77ae997701138fdf6c56",
"201b75462a436197862e77ae997701138fdf6c56"
] | [
"configs/c_128_5x5_32.py",
"configs/c_blend.py"
] | [
"import numpy as np\n\nfrom config import Config\nfrom data import BALANCE_WEIGHTS\nfrom layers import *\n\ncnf = {\n 'name': __name__.split('.')[-1],\n 'w': 112,\n 'h': 112,\n 'train_dir': 'data/train_tiny',\n 'test_dir': 'data/test_tiny',\n 'batch_size_train': 128,\n 'batch_size_test': 128,\n... | [
[
"numpy.array"
],
[
"numpy.array"
]
] |
saralsy/brain-tokyo-workshop | [
"c10bba435dff452427914fec6c985a560921b121"
] | [
"WANNRelease/WANN/wann_train.py"
] | [
"import os\nimport sys\nimport time\nimport math\nimport argparse\nimport subprocess\nimport numpy as np\nnp.set_printoptions(precision=2, linewidth=160) \n\n# MPI\nfrom mpi4py import MPI\ncomm = MPI.COMM_WORLD\nrank = comm.Get_rank()\n\nfrom wann_src import * # WANN evolution\nfrom domain import * # Task environ... | [
[
"numpy.empty",
"numpy.set_printoptions",
"numpy.tile",
"numpy.mean",
"numpy.shape",
"numpy.random.randint"
]
] |
YeongSeokJeong/Conditioned-Source-Separation-LaSAFT | [
"fc06d200de0f369d447b247ca007c686583ec87a"
] | [
"lasaft/source_separation/conditioned/cunet/dcun_base.py"
] | [
"from argparse import ArgumentParser\nfrom typing import Tuple\nfrom warnings import warn\n\nimport torch\nimport torch.nn as nn\nfrom torch import Tensor\n\nfrom lasaft.data.musdb_wrapper import SingleTrackSet\nfrom lasaft.source_separation.conditioned.separation_framework import Spectrogram_based\nfrom lasaft.uti... | [
[
"numpy.concatenate",
"torch.zeros",
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.BatchNorm2d",
"torch.no_grad",
"torch.nn.Conv2d",
"torch.tensor",
"torch.flatten",
"torch.nn.Embedding"
]
] |
arifmudi/Machine-Learning-Engineering-with-Python | [
"05c3fb9ae9fb9124a13812f59f8e681d66832d3b"
] | [
"Chapter04/outlier_package/outliers/utils/data.py"
] | [
"from sklearn.datasets import make_blobs\n\ndef create_data():\n # Define datasets\n # Example settings\n n_samples = 300\n outliers_fraction = 0.15\n n_outliers = int(outliers_fraction * n_samples)\n n_inliers = n_samples - n_outliers\n\n blobs_params = dict(random_state=0, n_samples=n_inliers... | [
[
"sklearn.datasets.make_blobs"
]
] |
ByzanTine/RobustMDP | [
"6a17ed857ff77fdf1aeddac9296e99688775d160"
] | [
"nominal-mdp/value_iteration.py"
] | [
"### MDP Value Iteration and Policy Iteratoin\n# You might not need to use all parameters\n\nimport numpy as np\nimport gym\nimport time\nfrom test_env import *\nimport os\n\nnp.set_printoptions(precision=3)\n\n\ndef BellmanOp(P, V, state, action, gamma):\n \"\"\"Represent R(s,a) + gamma * sum(p(s'|(s,a)) * V(s'... | [
[
"numpy.set_printoptions",
"numpy.abs",
"numpy.zeros",
"numpy.argmin"
]
] |
actcwlf/panelexpr | [
"a13a01981daab965b314b328f346b641634c7de1"
] | [
"panelexpr/_utils/utils.py"
] | [
"import pandas as pd\nimport numpy as np\n\n\ndef mean_absolute_deviation(s1, s2):\n if len(s1) != len(s2):\n return np.nan\n return np.abs(s1 - s2).mean()\n\n\ndef nan_matching(s1, s2):\n if len(s1) != len(s2):\n return False\n flag = True\n for i, j in zip(s1, s2):\n if pd.isnu... | [
[
"pandas.isnull",
"numpy.abs"
]
] |
OlegMoiseev/introduction-to-ml | [
"9444dce96954c546333d5aecc92a06c3bfd19aa5",
"9444dce96954c546333d5aecc92a06c3bfd19aa5"
] | [
"venv/lib/python3.7/site-packages/sklearn/kernel_approximation.py",
"venv/lib/python3.7/site-packages/sklearn/multiclass.py"
] | [
"\"\"\"\nThe :mod:`sklearn.kernel_approximation` module implements several\napproximate kernel feature maps base on Fourier transforms.\n\"\"\"\n\n# Author: Andreas Mueller <amueller@ais.uni-bonn.de>\n#\n# License: BSD 3 clause\n\nimport warnings\n\nimport numpy as np\nimport scipy.sparse as sp\nfrom scipy.linalg i... | [
[
"scipy.sparse.issparse",
"numpy.zeros_like",
"numpy.dot",
"numpy.sin",
"numpy.log",
"numpy.cosh",
"scipy.sparse.hstack",
"scipy.linalg.svd",
"numpy.tan",
"numpy.sqrt",
"numpy.cos",
"numpy.hstack",
"scipy.sparse.csr_matrix",
"numpy.maximum"
],
[
"nump... |
Zhihaosh/datamart | [
"85d16e109af3899f22d87779901df1e856d4796d"
] | [
"datamart/unit_tests/test_utils.py"
] | [
"from datamart.utilities.utils import Utils\nimport unittest, os, json\nfrom datamart.materializers.materializer_base import MaterializerBase\nfrom datamart.materializers.noaa_materializer import NoaaMaterializer\nimport pandas as pd\nfrom pandas.util.testing import assert_frame_equal\n\n\nclass TestUtils(unittest.... | [
[
"pandas.DataFrame"
]
] |
Xiul109/eeglib | [
"b447b3fece88502a958fa13f54a71feff73e69e5"
] | [
"eeglib/tests/test_DFA.py"
] | [
"import unittest\n\nimport numpy as np\nimport colorednoise\n\nfrom itertools import product\n\nimport eeglib.features as features\n\n#Supress warnings\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n\nclass TestDFA(unittest.TestCase):\n n_tests = 100\n n_points = 1000\n \n def test_white_noise(... | [
[
"numpy.random.normal",
"numpy.zeros",
"numpy.mean",
"numpy.random.random"
]
] |
kalefranz/seldon-python-microservice | [
"fbf7fde0a9edf51556014465e4e14a578f39ef82"
] | [
"seldon_microservice/common.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import absolute_import, division, print_function\nimport json\n\nfrom google.protobuf.struct_pb2 import ListValue\n\nfrom flask import Flask, Blueprint, request\nimport numpy as np\n\nfrom .proto import prediction_pb2\n\n\nclass SeldonMicroserviceException(Exception):\n ... | [
[
"numpy.array"
]
] |
ideaguy3d/moabb | [
"73d9a1e01f9d63c423fa855fb517b398d7e3cfc8"
] | [
"moabb/datasets/ssvep_mamem.py"
] | [
"\"\"\"\nSSVEP MAMEM1 dataset.\n\"\"\"\n\nimport glob\nimport logging\nimport os\n\nimport numpy as np\nfrom mne import create_info\nfrom mne.channels import make_standard_montage\nfrom mne.datasets.utils import _get_path\nfrom mne.io import RawArray\n\nfrom .base import BaseDataset\n\n\ntry:\n import wfdb\nexce... | [
[
"numpy.concatenate",
"numpy.zeros"
]
] |
Arjung27/DeepThinking | [
"13a2ce534bcb0b9379a22fffef52d975d650adb2"
] | [
"models/recur_cnn.py"
] | [
"\"\"\"recur_cnn.py\nRecurrent CNN models.\n\"\"\"\nimport torch\nimport torch.nn as nn\n\n\nclass RecurCNN(nn.Module):\n def __init__(self, num_outputs, width, depth, in_channels):\n super().__init__()\n self.num_outputs = num_outputs\n self.width = width\n self.iters = depth - 3\n ... | [
[
"torch.nn.Linear",
"torch.zeros",
"torch.nn.MaxPool2d",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
church06/Pythons | [
"87271619abb2dd6398fbe08d746d4b03c54bcd4d"
] | [
"Training/MOOC Tensorflow 2.0/BeiDa/class5/CIFAR10_CNN/P31_cifar10_lenet5.py"
] | [
"import tensorflow as tf\nimport os\nimport numpy as np\nfrom matplotlib import pyplot as plt\nfrom tensorflow.keras.layers import Conv2D, BatchNormalization, Activation, MaxPool2D, Dropout, Flatten, Dense\nfrom tensorflow.keras import Model\n\nnp.set_printoptions(threshold=np.inf)\n\ncifar10 = tf.keras.datasets.ci... | [
[
"tensorflow.keras.layers.Flatten",
"numpy.set_printoptions",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"tensorflow.keras.layers.MaxPool2D",
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.l... |
uit-cosmo/2d-propagating-blobs | [
"2c19458a5ba6d0d138461fadf3e935273bee4b5c"
] | [
"examples/custom_blobfactory.py"
] | [
"from blobmodel import Model, BlobFactory, Blob, show_model\nimport numpy as np\n\n# create custom class that inherits from BlobFactory\n# here you can define your custom parameter distributions\nclass CustomBlobFactory(BlobFactory):\n def __init__(self) -> None:\n pass\n\n def sample_blobs(\n s... | [
[
"numpy.linspace",
"numpy.random.uniform",
"numpy.sort",
"numpy.zeros"
]
] |
naivelogic/sixdpose | [
"88857c55c984d31e5cb9082b652f2873f8c76009"
] | [
"03_3DModeling/03_Camera_Projection/main.py"
] | [
"import os, json, cv2\nfrom scipy.spatial.transform import Rotation\nimport scipy.ndimage\nimport numpy as np\n\ndef load_params_from_json(json_path):\n with open(json_path, 'r') as f:\n return json.load(f)\n\ndef load_scene(file_path):\n with open(os.path.join(file_path, 'scene_gt.json')) as fid:\... | [
[
"numpy.array",
"scipy.spatial.transform.Rotation.from_quat",
"numpy.roll"
]
] |
acidcoma/OpenSeq2Seq | [
"a44eee8929df6535fc6e5a164b6b19b2f7b5d462"
] | [
"open_seq2seq/data/speech2text/speech_utils_test.py"
] | [
"# Copyright (c) 2017 NVIDIA Corporation\nfrom __future__ import absolute_import, division, print_function\nfrom __future__ import unicode_literals\n\nimport math\nimport os\n\nimport numpy as np\nimport numpy.testing as npt\nimport scipy.io.wavfile as wave\nimport tensorflow as tf\nfrom six.moves import range\n\nf... | [
[
"numpy.testing.assert_allclose",
"numpy.sin",
"scipy.io.wavfile.read",
"numpy.zeros_like",
"numpy.not_equal",
"numpy.mean",
"numpy.std",
"numpy.arange",
"tensorflow.test.main",
"numpy.abs"
]
] |
TuahZh/pywcsgrid2 | [
"5aed5a2e52519680e2fc26ef58cb10d5d402b673"
] | [
"examples/demo_skyview_delta.py"
] | [
"from astropy.io import fits as pyfits\n\nimport matplotlib.pyplot as plt\nimport matplotlib.cm as cm\nfrom mpl_toolkits.axes_grid1.axes_grid import AxesGrid\n#from pywcsgrid2.axes_wcs import GridHelperWcs, AxesWcs\nimport pywcsgrid2\n\n# read in the first image\nxray_name=\"pspc_skyview.fits\"\nf_xray = pyfits.ope... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.draw",
"matplotlib.pyplot.figure"
]
] |
cojimaru3/management_stock | [
"f8dddeb494f13f112babdeb2b2cc2305f1042a9e"
] | [
"utility.py"
] | [
"#!/usr/bin/env python\r\n# -*- coding: utf-8 -*-\r\n\r\nfrom openpyxl import utils\r\nimport pandas as pd\r\nimport os\r\n\r\n\"\"\"\r\n# Purpose\r\nConvert source variable contained in str variable to destination variable.\r\n\"\"\"\r\ndef util_replace(text, source, destination):\r\n # if text has source\r\n ... | [
[
"pandas.ExcelWriter"
]
] |
ohshyuk5/stable-baselines-tf2 | [
"02442226c6b2b3729c8772e2903963ad590313f7"
] | [
"common/tf_util.py"
] | [
"import os\nimport collections\nimport functools\nimport multiprocessing\n\nimport numpy as np\nimport tensorflow as tf\nfrom collections import deque\n\n\ndef is_image(tensor):\n \"\"\"\n Check if a tensor has the shape of\n a valid image for tensorboard logging.\n Valid image: RGB, RGBD, GrayScale\n\n... | [
[
"tensorflow.exp",
"tensorflow.nn.conv2d",
"tensorflow.group",
"tensorflow.compat.v1.global_variables",
"tensorflow.matmul",
"tensorflow.gradients",
"tensorflow.nn.moments",
"tensorflow.reshape",
"tensorflow.sqrt",
"tensorflow.clip_by_norm",
"numpy.mean",
"tensorflow... |
hoangen/codeathon-backend | [
"32d879cd67b25c044190a0c19af40fc3a80358fe"
] | [
"wide_deep/laundry.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.logging.set_verbosity",
"tensorflow.decode_csv",
"tensorflow.train.AdamOptimizer",
"numpy.asarray",
"tensorflow.feature_column.numeric_column",
"tensorflow.gfile.Exists",
"tensorflow.estimator.DNNLinearCombinedClassifier",
"tensorflow.estimator.inputs.numpy_input_fn",
... |
Thien223/Multilanguage_Tacotron_2 | [
"ee93c23117b317e5f7bda95aea45bf3095893c0a"
] | [
"train.py"
] | [
"import os\r\nimport time\r\nimport argparse\r\nimport math\r\nfrom numpy import finfo\r\nimport torch\r\nfrom distributed import apply_gradient_allreduce\r\nimport torch.distributed as dist\r\nfrom torch.utils.data.distributed import DistributedSampler\r\nfrom torch.utils.data import DataLoader\r\n\r\nfrom model i... | [
[
"torch.cuda.manual_seed",
"torch.distributed.init_process_group",
"torch.no_grad",
"torch.cuda.device_count",
"torch.manual_seed",
"numpy.finfo",
"torch.cuda.is_available",
"torch.distributed.all_reduce",
"torch.load",
"torch.utils.data.DataLoader",
"torch.utils.data.di... |
tozech/properscoring | [
"bf940c16a738cbbe69c9e65d2cc9655ff50eda70"
] | [
"properscoring/tests/test_energy_score.py"
] | [
"import functools\nimport unittest\nimport warnings\n\nimport numpy as np\nfrom scipy import stats, special\nfrom numpy.testing import assert_allclose\n\nfrom properscoring import energy_score\n\n\nclass TestESSimple(unittest.TestCase):\n def test_one_observation_trivial(self):\n obs = np.array([[1, 2]])\... | [
[
"numpy.array",
"numpy.testing.assert_equal"
]
] |
dtczhl/Slimmer | [
"c93dac6a59828016484d8bef1c71e9ccceabab9c",
"c93dac6a59828016484d8bef1c71e9ccceabab9c"
] | [
"C_Sparse/layer_test.py",
"PointFeature/max_point_cloud.py"
] | [
"import torch\nimport sparseconvnet as scn\n\n# Use the GPU if there is one, otherwise CPU\nuse_gpu = torch.cuda.is_available()\n\nmodel = scn.Sequential().add(\n scn.SparseVggNet(2, 1,\n\t\t [['C', 8], ['C', 8], ['MP', 3, 2],\n\t\t ['C', 16], ['C', 16], ['MP', 3, 2],\n\t\t ['C', 24], ['C', 24], ... | [
[
"torch.FloatTensor",
"torch.cuda.is_available",
"torch.LongTensor"
],
[
"torch.load"
]
] |
salmanhiro/yolo-service | [
"dc2575b5dc66b8fe7d6d809e6163eb05539fd27c"
] | [
"detector.py"
] | [
"import streamlit as st\nimport cv2\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ndef detect_objects(input_image):\n col1, col2 = st.columns(2)\n\n col1.subheader(\"Sample Image\")\n st.text(\"\")\n plt.figure(figsize = (15,15))\n plt.imshow(input_image)\n col1.pyplot(use_column_width=Tr... | [
[
"matplotlib.pyplot.imshow",
"numpy.argmax",
"matplotlib.pyplot.figure"
]
] |
PeterDeWeirdt/gpp-guide-design | [
"c12680b4bfadca9460c486a083de0bb440991ce0"
] | [
"get_context.py"
] | [
"'''\nAuthor: Mudra Hegde\nEmail: mhegde@broadinstitute.org\nGets guide context given the guide sequence, PAM length, Transcript ID and taxon\n'''\n\nfrom urllib import request\nimport pandas as pd\nimport csv\n\n\ndef revcom(s):\n basecomp = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'}\n letters = list(s[::-1])\... | [
[
"pandas.read_csv"
]
] |
ComicShrimp/Trabalho-Comunicacoes-Digitais | [
"076a583404e7d0f5719bdfff51a622ecec794382"
] | [
"src/main.py"
] | [
"import random\nimport tkinter as tk\nfrom tkinter import ttk\n\nimport matplotlib\nimport matplotlib.animation as animation\nimport numpy as np\nfrom matplotlib.backends.backend_tkagg import FigureCanvasTkAgg\nfrom matplotlib.figure import Figure\nfrom scipy import signal\nfrom scipy.fftpack import fft, fftshift\n... | [
[
"matplotlib.use",
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg",
"matplotlib.figure.Figure",
"matplotlib.animation.FuncAnimation"
]
] |
buschju/pushnet | [
"503bc3745fa40c35dc80548630d28693de74d1dc"
] | [
"src/training.py"
] | [
"import time\nfrom typing import Dict, List, Tuple\n\nimport torch\nfrom torch import Tensor\nfrom torch.nn import Module\nfrom torch.nn.functional import nll_loss\nfrom torch.optim import Adam, Optimizer\nfrom torch_geometric.data import Data\n\n\ndef train_step(model: Module,\n data: Data,\n ... | [
[
"torch.nn.functional.nll_loss",
"torch.no_grad"
]
] |
TonyZ1Min/Yolo-digit-detector | [
"b805c957d51c8e276fc3206ca782c891ad20dca4"
] | [
"train.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport numpy as np\nnp.random.seed(111)\nimport argparse\nimport os\nimport json\nfrom yolo.frontend import create_yolo, get_object_labels\n\nos.environ[\"CUDA_DEVICE_ORDER\"]=\"PCI_BUS_ID\"\nos.environ[\"CUDA_VISIBLE_DEVICES\"]=\"0\"\n\nargparser = argparse.ArgumentParser(\n descript... | [
[
"numpy.random.seed"
]
] |
heronsystems/ray | [
"beda876c9afe9ce38ddfe1abd686767811063041"
] | [
"rllib/utils/tests/test_framework_agnostic_components.py"
] | [
"from abc import ABCMeta, abstractmethod\nfrom gym.spaces import Discrete\nimport numpy as np\nfrom pathlib import Path\nimport unittest\n\nfrom ray.rllib.utils.exploration.exploration import Exploration\nfrom ray.rllib.utils.framework import try_import_tf, try_import_torch\nfrom ray.rllib.utils.from_config import ... | [
[
"numpy.array"
]
] |
erjel/emdrp | [
"0b04a164989dd2f8ab8d1defc38353a6c0c11c8c",
"0b04a164989dd2f8ab8d1defc38353a6c0c11c8c"
] | [
"pipeline/K0057_webknossos_test/sample_read_wkw.py",
"emdrp/emdrp/scripts/plot_iter_lda.py"
] | [
"\n# to export raw nrrd (using emdrp toolset):\n#dpLoadh5.py --srcfile /mnt/cne/from_externals/K0057_D31/K0057_D31.h5 --chunk 90 78 15 --size 192 192 32 --offset 96 96 96 --dataset data_mag1 --outraw ~/Downloads/K0057_webknossos_test/K0057_D31_x90o96_y78o96_z15o96.nrrd --dpL\n\n# script to read the webknossos forma... | [
[
"numpy.logical_not",
"numpy.logical_and",
"numpy.zeros"
],
[
"matplotlib.pyplot.xlim",
"matplotlib.pylab.ylabel",
"numpy.mean",
"matplotlib.pylab.show",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.get_cmap",
"matplotlib.pylab.subplot",
"numpy.arange",
"matplotli... |
QRemy/gammapy | [
"fe799e8a8e792d216fdb11fb7abcb64d58f273dd",
"fe799e8a8e792d216fdb11fb7abcb64d58f273dd"
] | [
"gammapy/catalog/tests/test_gammacat.py",
"gammapy/catalog/hess.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\nimport pytest\nfrom numpy.testing import assert_allclose\nfrom astropy import units as u\nfrom astropy.utils.data import get_pkg_data_filename\nfrom gammapy.catalog import SourceCatalogGammaCat\nfrom gammapy.utils.gauss import Gauss2DPDF\nfrom gammap... | [
[
"numpy.testing.assert_allclose"
],
[
"numpy.isnan",
"numpy.asanyarray",
"numpy.nonzero"
]
] |
mcalingo/pandas | [
"d4a6ea53b87ac54fe094d08751e2e3443a586ea4"
] | [
"pandas/core/indexes/base.py"
] | [
"from datetime import datetime\nimport operator\nfrom textwrap import dedent\nfrom typing import FrozenSet, Union\nimport warnings\n\nimport numpy as np\n\nfrom pandas._libs import algos as libalgos, index as libindex, lib\nimport pandas._libs.join as libjoin\nfrom pandas._libs.lib import is_datetime_array\nfrom pa... | [
[
"pandas.core.ops.comp_method_OBJECT_ARRAY",
"pandas.core.common.asarray_tuplesafe",
"pandas.core.dtypes.common.is_float_dtype",
"pandas.core.ops.get_op_result_name",
"pandas.core.reshape.merge._get_join_indexers",
"pandas.core.index.RangeIndex",
"pandas._libs.lib.infer_dtype",
"pan... |
shridharathi/cudf | [
"664712eb124e35dd2e8f28c287adbb48fc8049d6"
] | [
"python/cudf/cudf/core/column/column.py"
] | [
"# Copyright (c) 2018-2021, NVIDIA CORPORATION.\n\nfrom __future__ import annotations\n\nimport builtins\nimport pickle\nimport warnings\nfrom types import SimpleNamespace\nfrom typing import (\n Any,\n Dict,\n List,\n MutableSequence,\n Optional,\n Sequence,\n Tuple,\n TypeVar,\n Union,\... | [
[
"numpy.ceil",
"numpy.isnan",
"numpy.find_common_type",
"numpy.asarray",
"pandas.StringDtype",
"numpy.ascontiguousarray",
"numpy.isscalar",
"pandas.Series",
"numpy.int32",
"numpy.issubdtype",
"numpy.dtype",
"numpy.datetime64"
]
] |
leewujung/echopype | [
"3db32490b6c0296ba99bf38113257f15b94abbc3"
] | [
"echopype/convert/parse_base.py"
] | [
"import os\nfrom collections import defaultdict\nfrom datetime import datetime as dt\n\nimport numpy as np\n\nfrom .utils.ek_raw_io import RawSimradFile, SimradEOF\n\nFILENAME_DATETIME_EK60 = (\n \"(?P<survey>.+)?-?D(?P<date>\\\\w{1,8})-T(?P<time>\\\\w{1,6})-?(?P<postfix>\\\\w+)?.raw\"\n)\n\n\nclass ParseBase:\n... | [
[
"numpy.concatenate",
"numpy.full",
"numpy.array",
"numpy.log10",
"numpy.dtype",
"numpy.unique"
]
] |
MengZhang0904/Learn_New_World | [
"6f5b865a22093fa2dd5a24dd6a7883c8fa2f51c3"
] | [
"WordModel1.py"
] | [
"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import style\nstyle.use('ggplot')\nimport seaborn as sns\nfrom gensim.models import Word2Vec\n\ndef find_pct(word,age):\n df = pd.read_csv('word_acq_pct1.csv')\n row = df[df.definition2 == word]\n pct = row.iloc[0][i... | [
[
"matplotlib.pyplot.rcParams.update",
"numpy.array",
"matplotlib.style.use",
"matplotlib.pyplot.savefig",
"pandas.read_csv"
]
] |
xiecong/Ax | [
"f6501807bbc6bb952d636391231ebeb10646769a"
] | [
"ax/models/torch/botorch_mes.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom typing import Any, Callable, Dict, List, Optional, Tuple\n\nimport torch\nfrom ax.core.types import TCo... | [
[
"torch.tensor",
"torch.ones"
]
] |
lan496/parsevasp | [
"7b39b9936d9ef5435aba5f09d018a4da095d8a68"
] | [
"parsevasp/doscar.py"
] | [
"#!/usr/bin/python\nimport sys\nimport logging\nimport re\nimport numpy as np\n\nfrom parsevasp import utils\nfrom parsevasp.base import BaseParser\n\n# Map from number of columns in DOSCAR to dtype for the total density of states.\nDTYPES_DOS = {\n 3: np.dtype([('energy', float), ('total', float), ('integrated'... | [
[
"numpy.array",
"numpy.squeeze",
"numpy.dtype",
"numpy.zeros"
]
] |
charpagne/sampleScripts | [
"6ca334779a72468faed2e34c48c1ef18288f771f"
] | [
"align_ebsd_to_dic.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Mon Jul 27 12:12:09 2020\r\n\r\n@author: Arsenic\r\nalign AM 316L HT 02 dataset\r\n\"\"\"\r\n\r\nimport numpy as np\r\nfrom argos import align, process\r\nfrom argos.gui import kbentry, loadtxtfile, loadimgfile, loadimgfile, msgbox\r\nfrom skimage.io import imread, i... | [
[
"numpy.ma.size"
]
] |
leelige/RecBole | [
"66eb93d7b6f416cd0f603a0a5cf2bef94e80f658"
] | [
"recbole/model/sequential_recommender/comirec_sa.py"
] | [
"import random\n\nimport torch\nfrom torch import nn\nfrom recbole.model.abstract_recommender import SequentialRecommender\nfrom recbole.model.loss import BPRLoss\nimport torch.nn.functional as F\n\n\nclass ComiRec_SA(SequentialRecommender):\n r\"\"\"ComiRec_SA is a model that incorporate Capsule Network for rec... | [
[
"torch.nn.Linear",
"torch.argmax",
"torch.eq",
"torch.arange",
"torch.nn.Tanh",
"torch.nn.CrossEntropyLoss",
"torch.nn.init.kaiming_normal_",
"torch.unsqueeze",
"torch.sum",
"torch.ones_like",
"torch.nn.functional.softmax",
"torch.transpose",
"torch.Tensor",
... |
nickdelgrosso/cellfinder | [
"5577c08d7641f377a36b81c1cde5d6645bc783d3",
"5577c08d7641f377a36b81c1cde5d6645bc783d3"
] | [
"tests/tests/test_integration/test_extract.py",
"cellfinder/utils/xml_crop.py"
] | [
"import os\nimport pytest\n\nimport numpy as np\n\nfrom tifffile import tifffile\nfrom brainio import brainio\n\nfrom imlib.cells.cells import Cell\nfrom imlib.IO.cells import get_cells\n\nfrom imlib.general.system import (\n delete_directory_contents,\n get_sorted_file_paths,\n)\nimport cellfinder.extract.ex... | [
[
"numpy.zeros"
],
[
"pandas.read_csv"
]
] |
tongni1975/Hands-On-Deep-Learning-with-Apache-Spark | [
"1612f7fe7963ffa40c1d22fcdf263188e3b37f77"
] | [
"Chapter12/tfnlp/tf-txtclassifier.py"
] | [
"import tensorflow as tf\nimport tensorflow_hub as hub\nimport numpy as np\nimport os\nimport pandas as pd\nimport re\n\n# Load all files from a directory in a DataFrame.\ndef load_directory_data(directory):\n data = {}\n data[\"sentence\"] = []\n data[\"sentiment\"] = []\n for file_path in os.listdir(directory... | [
[
"tensorflow.estimator.inputs.pandas_input_fn",
"tensorflow.logging.set_verbosity",
"tensorflow.keras.utils.get_file",
"pandas.DataFrame.from_dict",
"tensorflow.Graph",
"tensorflow.train.AdagradOptimizer",
"tensorflow.Session",
"pandas.concat"
]
] |
axelbr/rlephant | [
"d65be0b4e9d0b236368cfc215d950de2cdb73065"
] | [
"rlephant/entities.py"
] | [
"from dataclasses import dataclass, field\nfrom typing import Dict, Union, Iterator, Tuple\n\nimport numpy as np\n\n\n@dataclass\nclass Transition:\n \"\"\"\n A single transition in a MDP, consisting of observations, actions, reward and done flag.\n It holds observations and actions as dictionaries.\n \... | [
[
"numpy.array",
"numpy.isscalar",
"numpy.append",
"numpy.expand_dims",
"numpy.vstack"
]
] |
atfrank/SampleDock | [
"136271a0e836004f1a64a8aecd2fc28d88a15676"
] | [
"models/sample.py"
] | [
"import torch\nimport torch.nn as nn\n\nimport math, random, sys\nimport argparse\nfrom jtvae import Vocab, JTNNVAE\nimport rdkit\n\nlg = rdkit.RDLogger.logger() \nlg.setLevel(rdkit.RDLogger.CRITICAL)\n\nparser = argparse.ArgumentParser()\nparser.add_argument('--nsample', type=int, required=True)\nparser.add_argume... | [
[
"torch.manual_seed",
"torch.cuda.is_available",
"torch.load"
]
] |
drumilT/espnet | [
"944de63aa9ede23cefca7b3d092150ea52e7f1b2"
] | [
"espnet/nets/pytorch_backend/transformer/decoder.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n# Copyright 2019 Shigeki Karita\n# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)\n\n\"\"\"Decoder definition.\"\"\"\n\nimport logging\n\nfrom typing import Any\nfrom typing import List\nfrom typing import Tuple\n\nimport torch\n\nfrom espnet.nets.pytor... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.LayerNorm",
"torch.nn.Module.__init__",
"torch.nn.ReLU",
"torch.nn.Embedding"
]
] |
zimengq/ReCode | [
"e48bee39e662e883a64e8fe17f8c554f00c514a0"
] | [
"seq2seq/seq2seq.py"
] | [
"import copy\nimport logging\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom util import get_mask, tensor_right_shift\nfrom components import Hyp, PointerNet\n\n\nclass Seq2Seq(nn.Module):\n def __init__(self, encoder, decoder, decoder_hidden_dim, rule_num, rule_embed_dim,\n ... | [
[
"torch.nn.Linear",
"torch.zeros",
"torch.cat",
"torch.stack",
"torch.LongTensor",
"torch.tensor",
"torch.t",
"torch.log",
"torch.Tensor",
"torch.randn"
]
] |
philipshurpik/tensorforce | [
"0a30b4a4171fd279fc48a539d74dbd3153aafd9d",
"0a30b4a4171fd279fc48a539d74dbd3153aafd9d"
] | [
"tensorforce/core/preprocessors/grayscale.py",
"tensorforce/core/optimizers/clipped_step.py"
] | [
"# Copyright 2017 reinforce.io. 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 ap... | [
[
"tensorflow.reduce_sum"
],
[
"tensorflow.clip_by_value",
"tensorflow.control_dependencies"
]
] |
exAClior/Cirq | [
"0ff2894e053e4ce3bb1b54e9b9de1cc4345d10b3"
] | [
"cirq/sim/clifford/stabilizer_sampler.py"
] | [
"# Copyright 2020 The Cirq Developers\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 o... | [
[
"numpy.array"
]
] |
lucaborsato/PyORBIT | [
"700146d59674dae77983da979af39cef7c77f408"
] | [
"examples/simulated_dataset/PyORBIT_data_simulator.py"
] | [
"import numpy as np\n\nimport sys\nimport os\nimport matplotlib.pyplot as plt\n\nsys.path.insert(0, '../pyorbit/')\nimport pyorbit.classes.kepler_exo as kp\nimport pyorbit.classes.constants as constants\n\n\n\"\"\"\nInitial realization of the parameters\n\nnp.random.seed(12345678)\n\nplanet_b = {\n 'P': np.rando... | [
[
"numpy.random.normal",
"numpy.arange"
]
] |
busycalibrating/Adversarial-Training | [
"e1fe4061f72e1379d9920b02c1cc281e1be2606f"
] | [
"adv_train/utils/utils.py"
] | [
"import torch.nn as nn\nimport torchvision\nimport math\nimport matplotlib.pyplot as plt\n\n\nclass Flatten(nn.Module):\n def forward(self, x):\n return x.view(len(x), -1)\n\n\ndef plot(tensor, n_adv=100, nrow=None, scale_noise=1, save=None, fig=None):\n if nrow is None:\n nrow = int(math.sqrt(n... | [
[
"matplotlib.pyplot.figure",
"matplotlib.pyplot.imshow"
]
] |
mrluin/EfficientAutoDeeplab | [
"d7a3cb02c4ab48a59088ce5b22e398669328e94d"
] | [
"nas_manager.py"
] | [
"import math\r\nimport torch\r\nimport os\r\nimport time\r\nimport logging\r\nimport json\r\n\r\nfrom exp.sufficient_update.run_manager import *\r\nfrom utils.common import set_manual_seed\r\nfrom utils.common import AverageMeter\r\nfrom utils.common import get_monitor_metric\r\nfrom utils.logger import save_checkp... | [
[
"torch.optim.lr_scheduler.CosineAnnealingLR",
"torch.cuda.is_available",
"torch.load",
"torch.optim.Adam"
]
] |
gglin001/training_results_v1.1 | [
"58fd4103f0f465bda6eb56a06a74b7bbccbbcf24",
"58fd4103f0f465bda6eb56a06a74b7bbccbbcf24",
"58fd4103f0f465bda6eb56a06a74b7bbccbbcf24"
] | [
"Google/benchmarks/bert/implementations/bert-research-JAX-tpu-v4-2048/jax/layers/attentions.py",
"Supermicro/benchmarks/bert/implementations/pytorch_SYS-420GP-TNAR/function.py",
"Supermicro/benchmarks/maskrcnn/implementations/pytorch_SYS-420GP-TNAR/maskrcnn_benchmark/modeling/roi_heads/keypoint_head/roi_keypoin... | [
"# Lint as: python3\n# Copyright 2021 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... | [
[
"numpy.sqrt"
],
[
"torch.cuda.nvtx.range_pop",
"torch.distributed.get_world_size",
"torch.nn.Linear",
"torch.cuda.manual_seed",
"torch.cuda.stream",
"torch.cuda.current_stream",
"torch.distributed.init_process_group",
"torch.manual_seed",
"torch.autograd.grad",
"tor... |
Abhinav-97/Melanoma-Detection | [
"d09313cb1af0006424edeef978f9f4136951d5d1"
] | [
"train.py"
] | [
"import os, random, re, math, time\n\nimport numpy as np\nimport pandas as pd\n\nimport tensorflow as tf\nimport tensorflow.keras.backend as K\nimport efficientnet.tfkeras as efn\n\nfrom kaggle_datasets import KaggleDatasets\n\nimport argparse\n\nparser = argparse.ArgumentParser()\n\nparser = parser.add_argument('-... | [
[
"tensorflow.image.central_crop",
"tensorflow.keras.backend.cast",
"tensorflow.data.TFRecordDataset",
"tensorflow.image.random_flip_left_right",
"tensorflow.ones",
"numpy.mean",
"tensorflow.reshape",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.Model",
"tensorflow.stac... |
iamansoni/fury | [
"2e7971a176c2540e10a9a6da861097583d08cb4a"
] | [
"docs/tutorials/02_ui/viz_tab.py"
] | [
"\"\"\"\n========\nTab UI\n========\n\nThis example shows how to use the Tab UI. We will demonstrate how to\ncreate Tabs for:\n\n1. Slider controls for a Cube\n2. Checkboxes for Cylinder and Sphere\n3. Color combobox for Fury.\n\nFirst, some imports.\n\"\"\"\nfrom fury import ui, window, actor\nimport numpy as np\n... | [
[
"numpy.array"
]
] |
Antimatter543/MCTS-agent-python | [
"5f6cf02839b01c04f3abbcf92a11e5f08241217f"
] | [
"gui.py"
] | [
"from tkinter import (Frame, Canvas, ttk, HORIZONTAL, VERTICAL, IntVar, Scale, Button, Label, PhotoImage, BOTH, LEFT, Y,\n X, TOP, messagebox)\n\nfrom numpy import int_\n\nfrom gamestate import GameState\nfrom meta import GameMeta\nfrom rave_mctsagent import (RaveMctsAgent, LGRMctsAgent, PoolRav... | [
[
"numpy.int_"
]
] |
chulbioinfo/CSAVanalysis | [
"f24b9b5a1060760da70ca83d1a9777d67d2a02c8"
] | [
"04.CSNV/bin/CSNV.py"
] | [
"# CSAV program\n# Version 1.0 (16.Nov.2020)\n# written by Chul Lee (e-mail: chul.bioinfo@gmail.com)\n# This code was developed and conducted in Python 3.7.1 (v3.7.1:260ec2c36a, Oct 20 2018, 14:57:15) [MSC v.1915 64 bit (AMD64)]\n# OS for development and analysis: Windows 10 Education\n\n# Libraries\nimport scipy.s... | [
[
"scipy.stats.fisher_exact"
]
] |
dinhtuyen/PRML01 | [
"b7ead0bd7acf46090f08b859c4864b16db7eac7e"
] | [
"prml/markov_models/kalman.py"
] | [
"import numpy as np\nfrom .state_space_model import StateSpaceModel\n\n\nclass Kalman(StateSpaceModel):\n \"\"\"\n A class to perform kalman filtering or smoothing\n \"\"\"\n\n def __init__(\n self,\n transition,\n observation,\n process_noise,\n measurement_noise,\n ... | [
[
"numpy.isnan",
"numpy.linalg.inv",
"numpy.asarray",
"numpy.eye"
]
] |
quoccuonglqd/SDE_DEEPSORT | [
"42cecff186034ebf66e0fcddea4d228c2d4e69a1"
] | [
"src/detector/yolov4v5/detector.py"
] | [
"import torch\n\nfrom detector.yolov4v5.models.experimental import attempt_load\nfrom detector.yolov4v5.utils import torch_utils\nfrom detector.yolov4v5.utils.utils import non_max_suppression, scale_coords\nfrom detector.yolov4v5.utils.datasets import *\n\nclass YoloModel(object):\n def __init__(self, use_cuda =... | [
[
"torch.from_numpy"
]
] |
joshchang/probability | [
"113d0a00cfa34a1789a789f9fde815e780e012f9"
] | [
"tensorflow_probability/python/distributions/sigmoid_beta.py"
] | [
"# Copyright 2020 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.compat.v2.math.sigmoid",
"tensorflow.compat.v2.math.softplus",
"tensorflow.compat.v2.TensorShape",
"tensorflow.compat.v2.broadcast_to",
"tensorflow.compat.v2.math.log",
"tensorflow.compat.v2.convert_to_tensor",
"tensorflow.compat.v2.name_scope",
"tensorflow.compat.v2.co... |
khalidative/MobilePriceClassification | [
"35660db90cbce52b9dd7e8ebf9ce58df13e6181d"
] | [
"MobilePriceClassification/PriceClassifier/Classifier.py"
] | [
"#=======================================================================\n#Using Keras with tensorflow backend\n#=======================================================================\nimport sys, csv\nimport numpy as np\nimport keras\nfrom keras import models\nfrom keras import layers\nfrom keras.utils.np_utils ... | [
[
"numpy.array",
"numpy.argmax"
]
] |
florianHoidn/spinningup | [
"419ca30849aae11ac53b9421094d2212d4cad652"
] | [
"spinup/algos/pytorch/vpg/core.py"
] | [
"import numpy as np\nimport scipy.signal\nfrom gym.spaces import Box, Discrete\n\nimport torch\nimport torch.nn as nn\nfrom torch.distributions.normal import Normal\nfrom torch.distributions.categorical import Categorical\n\ndef combined_shape(length, shape=None):\n if shape is None:\n return (length,)\n ... | [
[
"torch.no_grad",
"numpy.ones",
"torch.distributions.normal.Normal",
"torch.distributions.categorical.Categorical",
"numpy.prod",
"numpy.isscalar",
"torch.as_tensor",
"torch.exp"
]
] |
DominiqueMakowski/Pyllusion | [
"8a2090097ad1b042996fa1cfb2358c1384a4de5c"
] | [
"pyllusion/utilities/analyze_luminance.py"
] | [
"import numpy as np\n\n\ndef analyze_luminance(image, average=True):\n \"\"\"Image Luminance\n\n Compute the average luminance of an image.\n\n - Linear Luminance (L): linear measure of light, spectrally weighted for normal vision but not adjusted for the non-linear perception of lightness.\n - Perceive... | [
[
"numpy.power",
"numpy.mean"
]
] |
kyokuheishin/ArkPlanner | [
"18f00cad2ec6ee3c3d409e26356e71aca6b1856a"
] | [
"MaterialPlanning.py"
] | [
"import numpy as np\nimport urllib.request, json, time, os, copy, sys\nfrom scipy.optimize import linprog\n\nglobal penguin_url, headers\npenguin_url = 'https://penguin-stats.io/PenguinStats/api/'\nheaders = {'User-Agent':'ArkPlanner'}\n\nclass MaterialPlanning(object):\n \n def __init__(self, \n ... | [
[
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.any",
"numpy.where",
"numpy.argmax",
"numpy.hstack",
"numpy.vstack"
]
] |
JosephKJ/class-incremental-learning | [
"689271b84f2e553930ca6687d036ac99bd84b311"
] | [
"adaptive-aggregation-networks/models/modified_resnet_cifar.py"
] | [
"##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n## Created by: Yaoyao Liu\n## Modified from: https://github.com/hshustc/CVPR19_Incremental_Learning\n## Max Planck Institute for Informatics\n## yaoyao.liu@mpi-inf.mpg.de\n## Copyright (c) 2021\n##\n## This source code is licensed under t... | [
[
"torch.nn.init.constant_",
"torch.nn.Sequential",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
LucasFidon/MONAI | [
"a7ef9d567775dd7a222f93bab08191c0e3532c92"
] | [
"tests/test_highresnet.py"
] | [
"# Copyright 2020 MONAI Consortium\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# http://www.apache.org/licenses/LICENSE-2.0\n# Unless required by applicable law or agreed to i... | [
[
"torch.allclose",
"torch.no_grad",
"torch.cuda.is_available",
"torch.randn"
]
] |
xiaoping-yang/ms2pip_c | [
"061fcd8aa8c315b775ac64f5c1f7dfe0a09bdea9"
] | [
"tests/test_match_spectra.py"
] | [
"import unittest\nimport numpy as np\nimport ms2pip.match_spectra\nfrom operator import itemgetter\n\n\nclass TestMatchSpectra(unittest.TestCase):\n def test_get_intense_mzs(self):\n mzs = np.array([72.04435, 143.08147, 214.11859, 285.1557, 414.19827, 527.28235, 598.31946, 697.3879, 147.11276, 246.18117, ... | [
[
"numpy.array",
"numpy.float32"
]
] |
IlyaTrofimov/pt.darts | [
"7cda57ad6b0e5802f852c3908619ffa066b277a7"
] | [
"config.py"
] | [
"\"\"\" Config class for search/augment \"\"\"\nimport argparse\nimport os\nimport genotypes as gt\nfrom functools import partial\nimport torch\n\n\ndef get_parser(name):\n \"\"\" make default formatted parser \"\"\"\n parser = argparse.ArgumentParser(name, formatter_class=argparse.ArgumentDefaultsHelpFormatt... | [
[
"torch.cuda.device_count"
]
] |
XPerianer/Mutester | [
"f77bc98942a17512f9d0e1b81235a3a4358a6017"
] | [
"mutester/data_analysis.py"
] | [
"import logging\nimport os\nimport subprocess\nimport sys\nimport tempfile\nimport shutil\n\nfrom pathlib import Path\n\nfrom typing import List\n\nimport pandas as pd\n\nfrom mutester.data_crawler import DataCrawler\n\n\nclass DataAnalysis:\n def __init__(self, base_repository_path: str, virtual_environment_pat... | [
[
"pandas.DataFrame"
]
] |
ikunsaikou/lhy_ML2021Spring | [
"80d8922077e2f5abba6a440c17654a143ebc8c9c"
] | [
"Dive_into_pytorch/learning_tensor.py"
] | [
"import torch\n\n# %%\nx = torch.arange(12)\n\n# %%\nx\nX = x.reshape(3, -1)\n\n# %%\nX\n\n# %%\ntorch.randn(3, 4)\n\n# %%\ny = torch.tensor([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])\ny.shape\n\n# %%\nX\n# %%\ny\n\n# %%\ntorch.cat((X, y), dim=0)\n\n# %%\ntorch.cat((X, y), dim=1)\n\n# %%\nX < y\n\n# %%\ny[1:3]\... | [
[
"torch.cat",
"torch.tensor",
"torch.randn",
"torch.arange"
]
] |
naveenbanda/Sarcasm_Meter | [
"3754e15ba21c170bcbf5af68cfea14cda7eeb9a3"
] | [
"testing.py"
] | [
"\"\"\" This function loads the trained model and we can give text as input and\nget the classification result \"\"\"\n\nimport nltk\nimport numpy as np\nimport scipy as sp\nfrom sklearn.utils import shuffle\nfrom sklearn.svm import LinearSVC\nfrom sklearn.metrics import classification_report\nfrom sklearn.feature_... | [
[
"numpy.array"
]
] |
pvrancx/SrGan | [
"302ce6b7e8fe242801960beede839a024059a43c"
] | [
"generator.py"
] | [
"import torch\nimport torch.nn as nn\n\n\nclass ResidualBlock(nn.Module):\n def __init__(self):\n super().__init__()\n self.layers = nn.Sequential(\n nn.Conv2d(64, 64, kernel_size=3, stride=1, padding=1),\n nn.BatchNorm2d(64),\n nn.PReLU(),\n nn.Conv2d(64... | [
[
"torch.nn.BatchNorm2d",
"torch.nn.PixelShuffle",
"torch.nn.Conv2d",
"torch.nn.PReLU",
"torch.randn"
]
] |
cgtuebingen/emca | [
"560975bddc1b6176fe25029acb13d7806c8ab35b"
] | [
"controller/controller.py"
] | [
"\"\"\"\n MIT License\n\n Copyright (c) 2020 Christoph Kreisl\n Copyright (c) 2021 Lukas Ruppert\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,... | [
[
"numpy.array",
"numpy.append"
]
] |
agi-hub/AGI-PRIME-dataset | [
"2d96c49f85382a254057fd7c5d33b7d114f6cfa3"
] | [
"Creat AGI-PRIME/creat_object_recall_memory_test.py"
] | [
"import json\nimport os\nimport random\nimport matplotlib.pyplot as plt\nimport util\nimport shutil\nimport matplotlib\nmatplotlib.use('Agg')\nrandom.seed(2021)\n\nimg_huidu =util.read_image(path='./svg-png-gray/')\nimg_back = util.read_image(path='./background/')\n\n\ndef obre(path,p,json_data_list,back=False):\n\... | [
[
"matplotlib.use",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.imshow"
]
] |
vcg-uvic/log-polar-descriptors | [
"aed70f882cddcfe0c27b65768b9248bf1f2c65cb"
] | [
"modules/hardnet/eval_metrics.py"
] | [
"# Copyright 2019 EPFL, Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or a... | [
[
"numpy.sum",
"numpy.argsort",
"numpy.cumsum"
]
] |
zhul9311/XFNTR | [
"4f2e58775c6bb0df9a90e2854e7532f15f0e341a"
] | [
"xfntr/mainwindow.py"
] | [
"import sys\nimport os\n# Use absolute path instead of relative path ('./') to avoid trouble when installed by pip\ndir_path = os.path.dirname(os.path.realpath(__file__)) # the current directory\ndir_path_test = os.path.join(dir_path,'test')\nprint(dir_path)\nUI_path = dir_path + '/GUI/'\nimport time\n\n###########... | [
[
"numpy.array",
"scipy.interpolate.interp1d",
"numpy.savetxt",
"numpy.zeros",
"numpy.argmin",
"numpy.min",
"matplotlib.pyplot.rc",
"numpy.sqrt",
"numpy.all",
"numpy.linspace"
]
] |
Nicolucas/C-Scripts | [
"2608df5c2e635ad16f422877ff440af69f98f960"
] | [
"PythonCodes/Exercises/Class-SEAS/pycycle-student/pycycle/mesh.py"
] | [
"import numpy as np\n\n\nclass LineElement:\n \"\"\"LineElement represents a finite arc in the discretization of the domain boundary.\"\"\"\n def __init__(self, a, b, n, is_fault):\n \"\"\"Constructor.\n\n :param a: Start point\n :param b: End point\n :param n: Outward-pointing nor... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.inner"
]
] |
remilepriol/causal-adaptation-speed | [
"bc876724bef38d5d119282333639bcb9c54c9e63"
] | [
"normal_pkg/plot_distances.py"
] | [
"import os\nimport pickle\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\ndef abline(ax, slope, intercept):\n \"\"\"Plot a line from slope and intercept\"\"\"\n x_vals = np.array(ax.get_xlim())\n y_vals = intercept + slope * x_vals\n ax.plot(x_vals, y_vals, '--', color='grey... | [
[
"matplotlib.use",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.tight_layout"
]
] |
jmunroe/CMSC6950_MarineHeatWaves | [
"c7e3aeb8afcc3eeb881f88932890d76d9fba8c30"
] | [
"mhw_timeseries.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nimport pickle\nfrom datetime import date\n\nwith open('mhws_data.pkl', 'rb') as f:\n [dates, t, sst, mhws, clim] = pickle.load(f)\n\nev = np.argmax(mhws['intensity_max']) # Find largest event\n\nplt.figure(figsize=(14,10))\nplt.subplot(2,1,1)\n# Plot SST, sea... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"numpy.where",
"numpy.argmax",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.fill_between",
"matplotlib.pyplot.subplot"
]
] |
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