repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
ethank5149/PurduePHYS580 | [
"54d5d75737aa0d31ed723dd0e79c98dc01e71ca7"
] | [
"IsingClass.py"
] | [
"import numpy as np\nfrom numpy.random import default_rng\nfrom tqdm import tqdm\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n\nclass Ising:\n def __init__(self, \n rows=25, # Number of rows\n cols=25, # Number of columns\n relax=500, # Number of Equalibrium Cy... | [
[
"numpy.ones_like",
"numpy.zeros",
"matplotlib.pyplot.savefig",
"numpy.sum",
"numpy.negative",
"numpy.random.default_rng",
"numpy.roll",
"matplotlib.pyplot.subplots",
"numpy.mean",
"numpy.linspace"
]
] |
coszero/Modulation-Recognition | [
"26f09db322a491d28ebad7068d1b3e2d34fb69f7"
] | [
"Part1_Feature_based_method/Cumulant_NN_AWGN/plot_fig.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt \n\ncurve_F3 = np.loadtxt('./result/CUM_NN_F3_L100_50000.txt', delimiter = ',', dtype = float)\ncurve_F9 = np.loadtxt('./result/CUM_NN_F9_L100_50000.txt', delimiter = ',', dtype = float)\ncurve_TC = np.loadtxt('./result/cum_based_all_L100.txt', delimiter = ',', d... | [
[
"numpy.array",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"numpy.loadtxt",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots_adjust",
"matplotli... |
weikexin/onnxmltools | [
"b5ea8a43bb0abf5ca23f0913dc2d9ea11b9724b1"
] | [
"onnxmltools/convert/coreml/operator_converters/neural_network/Embed.py"
] | [
"# -------------------------------------------------------------------------\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License. See License.txt in the project root for\n# license information.\n# --------------------------------------------------------------------------\n... | [
[
"numpy.array"
]
] |
aronfothi/mask_cluster_rcnn | [
"5e1dcf0269166f0d2bce36e5b11e0be4cb585355",
"5e1dcf0269166f0d2bce36e5b11e0be4cb585355"
] | [
"tools/ann_file_gen.py",
"mmdet/datasets/transforms.py"
] | [
"import sys\r\nimport os\r\nimport cv2\r\nimport json\r\nimport numpy as np\r\nfrom os import listdir\r\n\r\npath = sys.argv[1]\r\ndest_path = sys.argv[2]\r\n\r\nimages_path = dest_path + 'images'\r\n\r\nif ('mp4' in path.split('/')[-1]) or ('avi' in path.split('/')[-1]):\r\n print(\"Video processing....\")\r\n\... | [
[
"numpy.array",
"numpy.char.find"
],
[
"numpy.array",
"numpy.zeros",
"numpy.round",
"torch.from_numpy",
"numpy.stack",
"numpy.clip"
]
] |
gitter-badger/FlexNeuART | [
"f69e5421bdebe9db0d993b5470dace61872f90df"
] | [
"flexneuart/models/parade/parade_max.py"
] | [
"#\n# Copyright 2014+ Carnegie Mellon University\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appl... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.init.xavier_uniform_"
]
] |
kyleclo/tensorflow-mle | [
"efe00ba11841a1a448fff4166309fc23a713ba30"
] | [
"univariate_random_intercept_adam.py"
] | [
"# Copyright (c) 2017, Kyle Lo\n# All rights reserved.\n#\n# This source code is licensed under the BSD-style license found in the\n# LICENSE file in the root directory of this source tree.\n\n\nimport numpy as np\nimport tensorflow as tf\nfrom util.sprint import sfill, sfloat, sarray\n\n# random intercepts-only\nN... | [
[
"numpy.random.normal",
"numpy.linalg.norm",
"tensorflow.train.AdamOptimizer",
"tensorflow.expand_dims",
"numpy.random.seed",
"tensorflow.Session",
"tensorflow.gradients",
"numpy.subtract",
"tensorflow.placeholder",
"tensorflow.reduce_sum",
"numpy.abs",
"numpy.repeat... |
luciancooper/bbcmd | [
"307aea02d245b3d217bb1a7f76a985b98da54e40"
] | [
"bbsim/matrix/rem.py"
] | [
"\nimport numpy as np\nfrom .util import scolDec\n\n###########################################################################################################\n# REM Matrix #\n##############################################... | [
[
"numpy.dtype"
]
] |
sergiocgdl/Python-SOMCC | [
"3487b14d026d36405f152adfb0e9221eadd02e87"
] | [
"pruebaE1.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport math\nfrom som1 import SCCSOM\nfrom somE1 import SCCSOM_E\nfrom sklearn.metrics.cluster import adjusted_rand_score\nimport sys\n\n################################################################################\n# Función para Lectura y tr... | [
[
"numpy.delete",
"numpy.array",
"numpy.asarray",
"numpy.zeros",
"numpy.argmin",
"sklearn.metrics.cluster.adjusted_rand_score",
"numpy.loadtxt",
"numpy.sqrt"
]
] |
jacarvalho/SimuRLacra | [
"a6c982862e2ab39a9f65d1c09aa59d9a8b7ac6c5",
"a6c982862e2ab39a9f65d1c09aa59d9a8b7ac6c5",
"a6c982862e2ab39a9f65d1c09aa59d9a8b7ac6c5"
] | [
"Pyrado/scripts/training/omo_pepg.py",
"Pyrado/scripts/evaluation/eval_domain_param_robustness.py",
"Pyrado/pyrado/environments/pysim/quanser_qube.py"
] | [
"\"\"\"\nTrain an agent to solve the One-Mass-Oscillator environment using Parameter-Exploring Policy Gradients.\n\"\"\"\nimport numpy as np\n\nfrom pyrado.algorithms.pepg import PEPG\nfrom pyrado.environment_wrappers.action_normalization import ActNormWrapper\nfrom pyrado.environments.pysim.one_mass_oscillator imp... | [
[
"numpy.array"
],
[
"numpy.empty",
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"numpy.mean",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"numpy.linspace",
"nu... |
alexandster/localKfunSpaceTime | [
"37d9adf1a41874e883b77f9d308caab76df407d3"
] | [
"localK_sim.py"
] | [
"#import modules\nimport sys\nimport numpy as np\nimport settings as sett\nfrom datetime import datetime\n\n#------------------------------------------------------------------------------------------------------------\n#distance function\ndef dist(p1,p2):\n return [pow(pow(p1[0]-p2[0],2)+pow(p1[1]-p2[1],2),0.5),... | [
[
"numpy.concatenate",
"numpy.savetxt",
"numpy.reshape",
"numpy.zeros",
"numpy.loadtxt",
"numpy.cumsum"
]
] |
godnpeter/DMC_Clustering_PICA | [
"1b3e14dd4034f3941af1caa06c1d4b6f9d606408"
] | [
"log_sessions/cartpole_8_2_05_1/modules/digideep/environment/storage.py"
] | [
"import torch\n\n\nclass Storage:\n\n def __init__(self, obs_cluster_num, action_cluster_num, num_steps ):\n self.input_batch = torch.zeros(num_steps,5)\n self.obs_cluster_batch = torch.zeros(num_steps, obs_cluster_num)\n self.action_cluster_batch = torch.zeros(num_steps, action_cluster_num)... | [
[
"torch.zeros"
]
] |
zfang-slim/pysit | [
"8fca42b9749841abc302d1f8195a1437fad7ae4d",
"8fca42b9749841abc302d1f8195a1437fad7ae4d"
] | [
"examples/HorizontalReflector1D.py",
"pysit/gallery/gallery_base.py"
] | [
"# Std import block\nimport time\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom pysit import *\nfrom pysit.gallery import horizontal_reflector\n\nif __name__ == '__main__':\n # Setup\n\n # Define Domain\n pmlz = PML(0.1, 100, ftype='quadratic')\n\n# pmlz = Dirichlet()\n\n z_config = ... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.semilogy",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplot"
],
[
"scipy.interpolate.interp1d",
"numpy.ceil",
"numpy.pad",
"numpy.asarray",
"numpy.zeros",
"numpy.ones",
"numpy.load",
... |
nsang0u/TweetMapping | [
"9e88fea27a4d7fc669d4ea5ad669491c4f8b99c2"
] | [
"new_plot.py"
] | [
"import sys\nimport csv\nimport geopy\nimport pandas as pd\nimport plotly.express as px\nfrom geopy.geocoders import Nominatim\nfrom optparse import OptionParser\n\nGEO_COLNUM = 5\nDATE_COLNUM = 1\n\ncsv.register_dialect('managequotes', escapechar='\\\\', doublequote=False)\n\ndef location2coords(locationstr, geolo... | [
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
wentaoyuan/sornet | [
"ac25abdd33ef9436b0a00f985ff77f0acb2099eb"
] | [
"networks.py"
] | [
"'''\nMIT License\n\nCopyright (c) 2022 Wentao Yuan\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, modify, me... | [
[
"torch.zeros",
"torch.sigmoid",
"torch.cat",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.nn.MultiheadAttention",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.randn"
]
] |
kim-hyunsu/nctp-hmc | [
"634d14f48bff9be51fd83005ed71a4e63e0a9641"
] | [
"hmc/__init__.py"
] | [
"import tensorflow as tf\nimport numpy as np\n\ndef kinetic_energy(velocity):\n \"\"\"Kinetic energy of the current velocity (assuming a standard Gaussian)\n (x dot x) / 2\n\n Parameters\n ----------\n velocity : tf.Variable\n Vector of current velocity\n\n Returns\n -------\n kin... | [
[
"tensorflow.exp",
"numpy.random.uniform",
"tensorflow.square"
]
] |
usmanwardag/pylayers | [
"2e8a9bdc993b2aacc92610a9c7edf875c6c7b24a",
"2e8a9bdc993b2aacc92610a9c7edf875c6c7b24a"
] | [
"pylayers/location/geometric/exploit_CDF.py",
"pylayers/mobility/ban/c3dtools.py"
] | [
"import numpy as np\nimport scipy as sp\nimport scipy.stats as stats\nimport matplotlib.pyplot as plt\nfrom matplotlib.patches import Circle, Wedge\nfrom matplotlib.collections import PatchCollection\nimport sys\nimport ConfigParser\n\n###############################\n# filename = le meme nom de fichier que dans co... | [
[
"numpy.load"
],
[
"numpy.array"
]
] |
jahwanoh/mmdetection | [
"77d64bf11f57e35eb2efc2df6fa35e923ce0b3a2"
] | [
"demo/mmdetection_demo.py"
] | [
"from mmdet.apis import init_detector, inference_detector, show_result_pyplot\nimport mmcv\nimport cv2\nimport numpy as np\nimport time\nimport sys\nimport glob\nimport os\nfrom datetime import datetime\n\ndef process_video_crcnn(frame_offset, frame_count, config_file, checkpoint_file, video_path, dsort_img_path):\... | [
[
"numpy.concatenate",
"numpy.full",
"numpy.vstack"
]
] |
rmazzier/KENN-Citeseer-Experiments | [
"9a0274f10ff00d8fbc42dd5eebdfbc775dc96b50"
] | [
"training_inductive.py"
] | [
"import tensorflow as tf\nfrom tensorflow import keras\nimport numpy as np\nfrom model import Standard, Kenn\nimport os\nimport settings as s\nfrom training_helper_functions import *\nfrom training_standard import train_and_evaluate_standard\n\nfrom pre_elab import generate_dataset, get_train_and_valid_lengths\n\no... | [
[
"numpy.array",
"tensorflow.random.set_seed",
"numpy.random.seed",
"numpy.load",
"tensorflow.squeeze",
"tensorflow.keras.losses.CategoricalCrossentropy",
"tensorflow.keras.optimizers.Adam"
]
] |
dlod-openvino/yolov5_infer | [
"3374f6486498616d9878cfcc5be2e9a26eefc8ab"
] | [
"openvino2022-device-for-mqtt.py"
] | [
"#version: python 3.x 测试过\n#用于模拟一个基于mqtt协议传输OpenVINO推理结果\n\nimport paho.mqtt.client as mqtt\nimport json\nimport time\nimport queue as Queue\nimport threading,random\nimport cv2\nimport numpy as np\nimport time\nimport yaml\n# from openvino.inference_engine import IECore # the version of openvino <= 2021.4.2\nfrom ... | [
[
"numpy.array",
"numpy.zeros"
]
] |
msnederland/candypicker | [
"98e90dce321f52a443058723165d00d8d45a87c3"
] | [
"train/trainer/train.py"
] | [
"# Copyright 2017 BrainPad 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 ap... | [
[
"tensorflow.initialize_all_variables",
"tensorflow.Session",
"tensorflow.gfile.Exists",
"tensorflow.app.run",
"tensorflow.gfile.MakeDirs",
"tensorflow.train.SummaryWriter"
]
] |
VincentChen123/densenet | [
"431885937fe5a4e7d7255c31f79d4f398a3ad2be"
] | [
"8_SENet/SENet_Keras.py"
] | [
"import keras\nimport math\nimport numpy as np\nfrom keras.datasets import cifar10\nfrom keras.preprocessing.image import ImageDataGenerator\nfrom keras.layers.normalization import BatchNormalization\nfrom keras.layers import Conv2D, Dense, Input, add, Activation, GlobalAveragePooling2D, multiply, Reshape\nfrom ker... | [
[
"tensorflow.ConfigProto",
"tensorflow.Session"
]
] |
mih/PyMVPA | [
"8dd092277a5410b784bd71f760e39a231b3e45ce"
] | [
"mvpa2/datasets/mri.py"
] | [
"# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\n#\n# See COPYING file distributed along with the PyMVPA package for the\n# copyright and license terms.\n#\n### ###... | [
[
"numpy.all",
"numpy.rollaxis",
"numpy.reshape",
"numpy.vstack"
]
] |
yanzhiwei1990/tensorflow | [
"28ede9ed7caee0ce2731d95cc0eb9aff7f360105",
"28ede9ed7caee0ce2731d95cc0eb9aff7f360105"
] | [
"tensorflow/python/ops/image_ops_test.py",
"tensorflow/contrib/timeseries/python/timeseries/math_utils.py"
] | [
"# Copyright 2015 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.ops.image_ops.image_gradients",
"tensorflow.python.ops.image_ops.random_flip_up_down",
"numpy.random.rand",
"numpy.tile",
"tensorflow.python.ops.io_ops.read_file",
"tensorflow.python.ops.array_ops.unstack",
"tensorflow.python.ops.image_ops.rgb_to_yuv",
"tensorflo... |
MR3z4/SemanticSegmentation | [
"513c9b3c995ca6dd7a23b7ad9f9c83c1212a54ad"
] | [
"utils/ext_transforms.py"
] | [
"import numbers\nimport random\n\nimport cv2\nimport numpy as np\nimport torch\nimport torchvision.transforms.functional as F\nfrom PIL import Image\n\n\n#\n# Extended Transforms for Semantic Segmentation\n#\nclass ExtRandomHorizontalFlip(object):\n \"\"\"Horizontally flip the given PIL Image randomly with a gi... | [
[
"numpy.array",
"numpy.sin",
"numpy.zeros",
"numpy.float32",
"numpy.cos"
]
] |
Zen-Reportz/zen_knit | [
"104c2693d2cc61520657131da769f5d59d2df8e9"
] | [
"doc/example/demo.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nfrom zen_knit.formattor import get_formatter\nfrom zen_knit.formattor.html_formatter import HTMLFormatter\nfrom zen_knit.data_types import ChunkOption, OrganizedData, GlobalOption, OrganizedChunk, OrganizedChuckType, Input, Output, latexOupu... | [
[
"matplotlib.pyplot.savefig",
"numpy.array",
"matplotlib.pyplot.plot",
"pandas.DataFrame"
]
] |
VladPodilnyk/Kalman-and-Bayesian-Filters-in-Python | [
"1b47e2c27ea0a007e8c36d9f6d453c47402b3615",
"1b47e2c27ea0a007e8c36d9f6d453c47402b3615"
] | [
"experiments/ukf_baseball.py",
"kf_book/gh_internal.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Feb 8 09:55:24 2015\n\n@author: rlabbe\n\"\"\"\n\nfrom math import radians, sin, cos, sqrt, exp, atan2, radians\nfrom numpy import array, asarray\nfrom numpy.random import randn\nimport numpy as np\nimport math\nimport matplotlib.pyplot as plt\nfrom filterpy.kalman ... | [
[
"numpy.array",
"matplotlib.pyplot.plot",
"numpy.random.randn",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.show"
],
[
"matplotlib.pylab.axes",
"matplotlib.pylab.text",
"matplotlib.pylab.ylabel",
"numpy.sum",
"matplotlib.pylab.legend",
"matplotlib.pylab.grid",
... |
armandmcqueen/detectron2_fork | [
"3bb1ec0925d86578b33fd04a0432956cc7c65219",
"3bb1ec0925d86578b33fd04a0432956cc7c65219"
] | [
"projects/PointRend/point_rend/dataset_mapper.py",
"tests/layers/test_mask_ops.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport copy\nimport logging\nimport numpy as np\nimport torch\nfrom fvcore.common.file_io import PathManager\nfrom fvcore.transforms.transform import CropTransform\nfrom PIL import Image\n\nfrom detectron2.data import detection_utils as utils\... | [
[
"numpy.max",
"numpy.asarray",
"numpy.sum",
"numpy.random.randint",
"numpy.unique"
],
[
"torch.rand",
"numpy.array",
"torch.cat",
"torch.stack",
"torch.device",
"numpy.asarray",
"torch.cuda.synchronize",
"torch.clamp",
"torch.from_numpy",
"torch.manua... |
Kaixi26/org.alloytools.alloy | [
"1671f0f6ff1a1449f71b0ba0b725afbcaf8020c4"
] | [
"beafix_benchmarks/stats.py"
] | [
"#!/usr/bin/env python\nimport json\nimport sys\nimport os\nimport re\nimport numpy as np\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom matplotlib.ticker import ScalarFormatter\nfrom matplotlib_venn import venn2, venn3\nfrom venn import venn\n\ndef str_is_int(str):\n try:\n _ = int(str)\n e... | [
[
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.tick_params",
"numpy.arange",
"matplotlib.rcParams.update",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
baradist/maddpg | [
"b10e3c824f988376233de7eb297d4d96b88b1823"
] | [
"experiments/std_plotter.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nfrom scipy.signal import savgol_filter\n\nfrom experiments.plotter import Plotter\n\n\nclass StdPlotter(Plotter):\n def __init__(self, vis, frequency=100, title=None, ylabel=None, xlabel=None, legend=None):\n super(StdPlotter, self).__init__(vis, frequ... | [
[
"scipy.signal.savgol_filter",
"matplotlib.pyplot.subplots",
"numpy.transpose"
]
] |
civilServant-666/Foreign_obj_in_water_channel | [
"98fe63c6e3114583c860d2e4840a327afadab816"
] | [
"ML_classifiers/DT_classifier1.py"
] | [
"import pandas as pd\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport pylab as pl\r\nimport time\r\nstart_time = time.time()\r\n\r\n# Read and exam the data\r\nfp_train = \"./classifier1_iswater_training_lbp.csv\";\r\nfp_test = \"./classifier1_iswater_test_lbp_original_expand.csv\";\r\ndf_train = ... | [
[
"sklearn.metrics.confusion_matrix",
"sklearn.model_selection.cross_validate",
"sklearn.metrics.classification_report",
"sklearn.tree.DecisionTreeClassifier",
"pandas.read_csv"
]
] |
TheTwoCentsRespository/materials | [
"c18a5b4384fcea51b7138871b6567e17bf706720"
] | [
"opencv-color-spaces/finding-nemo.py"
] | [
"\"\"\"\nCode link for RealPython article with minimal commentary.\nAuthor: Rebecca Stone @ysbecca\n\"\"\"\n\nimport cv2\nimport numpy as np\n\nimport matplotlib.pyplot as plt\nfrom matplotlib import colors\n\nfrom mpl_toolkits.mplot3d import Axes3D # noqa\nfrom matplotlib.colors import hsv_to_rgb\n\n# To get a li... | [
[
"numpy.full",
"matplotlib.colors.hsv_to_rgb",
"numpy.shape",
"matplotlib.pyplot.figure",
"matplotlib.colors.Normalize",
"matplotlib.pyplot.show",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.subplot"
]
] |
jhwnkim/nanopores | [
"98b3dbb5d36464fbdc03f59d224d38e4255324ce"
] | [
"nanopores/tools/utilities.py"
] | [
"''' some utility functions for global use after importing * from nanopores '''\n\nfrom importlib import import_module\nimport inspect, os, sys, glob\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom numpy import array\nimport json\nimport dolfin\nfrom nanopores.dirnames import DATADIR\nfrom nanopores.tool... | [
[
"numpy.array",
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.plot",
"scipy.io.savemat",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.get_fignums",
"matplotlib.pyplot.ylabel",
"matplotl... |
StanislavParovoy/tf_multispeakerTTS_fc | [
"8663a9b6aad39d4e30e83668ff9525ead1aa01e1",
"cf618dfbe7f58edba15d06cd7c206d20f5dd330a"
] | [
"synthesizer/train.py",
"synthesizer/models/tacotron.py"
] | [
"from synthesizer.utils.symbols import symbols\nfrom synthesizer.utils.text import sequence_to_text\nfrom synthesizer.hparams import hparams_debug_string\nfrom synthesizer.feeder import Feeder\nfrom synthesizer.models import create_model\nfrom synthesizer.utils import ValueWindow, plot\nfrom synthesizer import info... | [
[
"tensorflow.train.get_checkpoint_state",
"tensorflow.contrib.tensorboard.plugins.projector.ProjectorConfig",
"tensorflow.global_variables_initializer",
"tensorflow.Summary",
"tensorflow.set_random_seed",
"tensorflow.summary.histogram",
"tensorflow.Variable",
"tensorflow.train.Saver... |
Proteusiq/languages | [
"8ab361ec10b078ae198da42642ad400c1c2b00cc"
] | [
"luga/artifacts.py"
] | [
"from dataclasses import dataclass, field\nfrom pathlib import Path\nfrom typing import Any, List, Optional, Tuple, Union\nfrom gdown import download\nfrom fasttext import FastText, load_model # type: ignore\nfrom numpy import array\nfrom nptyping import NDArray\n\n\n__MODEL_PATH = Path(__file__).parent / \"models... | [
[
"numpy.array"
]
] |
baudcode/sox-chords | [
"b3217fa3cd32a49979ab43ad903fb8febf37754f"
] | [
"sox_chords/util/image.py"
] | [
"from sox_chords import values\n\n# from random import randint\n\nimport numpy as np\nfrom PIL import Image\n\n\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\nmatplotlib.rcParams['axes.titlesize'] = 8\nmatplotlib.rcParams['axes.labelsize'] = 5\nmatplotlib.rcParams['xtick.labelsize'] = 5... | [
[
"matplotlib.use",
"matplotlib.pyplot.show",
"numpy.dot",
"matplotlib.pyplot.imshow"
]
] |
mc-nya/federated-learning | [
"575d2af61c869ac6891727b0cc3b917e42a45f51"
] | [
"reproduce/fig2.py"
] | [
"import matplotlib.pyplot as plt\nimport yaml\nimport numpy as np\n\nfile_list = [\n \"results/HR/tau/1_1.yaml\",\n \"results/HR/optim/noniid_sgd_1.yaml\",\n\n \"results/HR/tau/iid_1_1.yaml\",\n \"results/HR/optim/iid_sgd_1.yaml\",\n\n]\nname_list = [\n r\"$\\mathrm{FedNest}$, non-iid\",\n r\"$\\m... | [
[
"matplotlib.pyplot.grid",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.cla",
"matplotlib.pyplot.xticks"
]
] |
Katze2664/Incan_Gold | [
"3e362c9a353db2e556e60cc1fc20e56eff0c51fb"
] | [
"solo_random.py"
] | [
"import time\ntime.perf_counter()\nfrom game_mechanics import Player, Simulator\nfrom strategies import make_random_strat\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n# A bot plays Incan Gold in single-player mode.\n# The bot leaves when with a probability of Random Threshold each turn.\n# The game is si... | [
[
"matplotlib.pyplot.errorbar",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"numpy.std",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.xticks"
]
] |
skyoung/MemDTC | [
"0d9d3faf625a766367964c98dc5dee41ec744b68"
] | [
"memnet/addressing.py"
] | [
"# ------------------------------------------------------------------\n# Tensorflow implementation of\n# \"Visual Tracking via Dynamic Memory Networks\", TPAMI, 2019\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Tianyu Yang (tianyu-yang.com)\n# ------------------------------------------... | [
[
"tensorflow.expand_dims",
"tensorflow.nn.top_k",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.sqrt",
"tensorflow.layers.conv2d",
"tensorflow.reduce_sum",
"tensorflow.stack",
"tensorflow.layers.dense",
"tensorflow.nn.softmax",
"tensorflow.squeeze",
"tensorf... |
fxnnxc/text_summarization | [
"b8c8a5f491bc44622203602941c1514b2e006fe3",
"b8c8a5f491bc44622203602941c1514b2e006fe3"
] | [
"fairseq/custom/abex4/criterions/kld_loss.py",
"experiments/experiment1/train.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\nimport math\n\nimport torch\nimport torch.nn as nn\nfrom fairseq import metrics, utils\nfrom fairseq.criterions import FairseqCriter... | [
[
"torch.autograd.set_detect_anomaly",
"torch.exp",
"torch.pow",
"torch.sum"
],
[
"torch.autograd.profiler.emit_nvtx",
"numpy.random.seed",
"torch.cuda.profiler.profile",
"torch.autograd.profiler.record_function",
"torch.utils.tensorboard.SummaryWriter"
]
] |
TizianThieringer/model-vs-human | [
"17729b8167520f682d93d55c340c27de07bb2681",
"17729b8167520f682d93d55c340c27de07bb2681",
"17729b8167520f682d93d55c340c27de07bb2681"
] | [
"modelvshuman/models/pytorch/pycontrast/pycontrast_resnet50.py",
"modelvshuman/models/pytorch/dino/eval_linear.py",
"modelvshuman/datasets/decision_mappings.py"
] | [
"from collections import OrderedDict\n\nimport torch\nimport torch.nn as nn\n\nCLASSIFIER_WEIGHTS = {\n \"InsDis\": \"https://github.com/bethgelab/model-vs-human/releases/download/v0.2/InsDis_classifier.pth\",\n \"CMC\": \"https://github.com/bethgelab/model-vs-human/releases/download/v0.2/CMC_classifier.pth\"... | [
[
"torch.nn.Linear",
"torch.hub.load"
],
[
"torch.nn.Linear",
"torch.nn.Identity",
"torch.cat",
"torch.cuda.synchronize",
"torch.optim.lr_scheduler.CosineAnnealingLR",
"torch.no_grad",
"torch.nn.parallel.DistributedDataParallel",
"torch.utils.data.DataLoader",
"torch.... |
axbaretto/mxnet | [
"102f8d0ed59529bbd162c37bf07ae58ad6c4caa1",
"102f8d0ed59529bbd162c37bf07ae58ad6c4caa1",
"5f593885356ff6d14f5519fa18e79b944beb51cd",
"102f8d0ed59529bbd162c37bf07ae58ad6c4caa1"
] | [
"example/model-parallel-lstm/lstm.py",
"example/recommenders/crossentropy.py",
"tools/caffe_converter/convert_model.py",
"tests/python/train/test_conv.py"
] | [
"# pylint:skip-file\nimport sys\nsys.path.insert(0, \"../../python\")\nimport mxnet as mx\nimport numpy as np\nfrom collections import namedtuple\nimport time\nimport math\nLSTMState = namedtuple(\"LSTMState\", [\"c\", \"h\"])\nLSTMParam = namedtuple(\"LSTMParam\", [\"i2h_weight\", \"i2h_bias\",\n ... | [
[
"numpy.log",
"numpy.zeros",
"numpy.exp",
"numpy.argmax",
"numpy.maximum"
],
[
"numpy.abs",
"numpy.log",
"numpy.random.RandomState"
],
[
"numpy.array"
],
[
"numpy.sum",
"numpy.argmax"
]
] |
stuara/echopype | [
"e01d57592385324b5747fb5c98d498ff50c42194"
] | [
"echopype/convert/parse_azfp.py"
] | [
"import math\nimport os\nimport xml.dom.minidom\nfrom collections import defaultdict\nfrom datetime import datetime as dt\nfrom struct import unpack\n\nimport fsspec\nimport numpy as np\n\nfrom .parse_base import ParseBase\n\nFILENAME_DATETIME_AZFP = \"\\\\w+.01A\"\n\n\nclass ParseAZFP(ParseBase):\n \"\"\"Class ... | [
[
"numpy.isinf",
"numpy.array",
"numpy.log10",
"numpy.unique"
]
] |
morales-gregorio/elephant | [
"70ee3c8dcd3fdc7792815ff2417b95b5be01fc0f"
] | [
"elephant/spectral.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nIdentification of spectral properties in analog signals (e.g., the power\nspectrum).\n\n:copyright: Copyright 2015-2016 by the Elephant team, see `doc/authors.rst`.\n:license: Modified BSD, see LICENSE.txt for details.\n\"\"\"\n\nfrom __future__ import division, print_function, uni... | [
[
"numpy.rollaxis",
"numpy.angle",
"numpy.asarray",
"numpy.abs"
]
] |
studiawan/pylogsentiment | [
"e2ce2cb44cacc9e4c3537af8fb984e6630ee531f"
] | [
"pylogsentiment/sentiment/pylogsentiment_method.py"
] | [
"import os\nimport numpy as np\nimport pickle\nfrom sklearn.metrics import precision_recall_fscore_support\nfrom sklearn.metrics import accuracy_score\nfrom keras.models import Sequential, load_model\nfrom keras.layers import Embedding, SpatialDropout1D, Dense, GRU\nfrom keras.utils import to_categorical\nfrom kera... | [
[
"numpy.asarray",
"sklearn.metrics.accuracy_score",
"sklearn.metrics.precision_recall_fscore_support"
]
] |
jenfly/monsoon-onset | [
"6d8651a337daa174960e716d378292452db77246"
] | [
"scripts/save-momentum-budget.py"
] | [
"import sys\nsys.path.append('/home/jwalker/dynamics/python/atmos-tools')\nsys.path.append('/home/jwalker/dynamics/python/atmos-read')\nsys.path.append('/home/jwalker/dynamics/python/monsoon-onset')\n\nimport numpy as np\nimport xarray as xray\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport collection... | [
[
"numpy.arange"
]
] |
codePerfectPlus/ComputerVision-Essentials | [
"cfaa9e45ddc73cf6f3a6450f64a0d03268a60392"
] | [
"17. Color Trackbar/colorTrackbar.py"
] | [
"\"\"\" Color Tracker GUI \"\"\"\n\nimport numpy as np\nimport cv2\n\ndef nothing(x):\n pass\n\n# Create a black image, a window\nimg = np.zeros((300, 512, 3), np.uint8)\ncv2.namedWindow('Color Tracker')\n\n# create trackbars for color change\ncv2.createTrackbar('R','image',0,255,nothing)\ncv2.createTrackbar('G'... | [
[
"numpy.zeros"
]
] |
kant/open-solution-home-credit | [
"0105fcffadcfc7c743a71b1ff2ea99453b445ee8"
] | [
"src/feature_extraction.py"
] | [
"from copy import deepcopy\nfrom functools import partial\n\nimport category_encoders as ce\nimport numpy as np\nimport pandas as pd\nimport cmath\nfrom scipy.stats import kurtosis, iqr, skew\nfrom sklearn.externals import joblib\nfrom sklearn.linear_model import LinearRegression\nfrom steppy.base import BaseTransf... | [
[
"pandas.isnull",
"scipy.stats.iqr",
"numpy.isnan",
"numpy.asarray",
"pandas.merge",
"sklearn.linear_model.LinearRegression",
"pandas.concat",
"pandas.DataFrame",
"sklearn.externals.joblib.dump",
"numpy.nansum",
"sklearn.externals.joblib.load",
"scipy.stats.skew",
... |
M-a-s-o/PyTorch-GAN | [
"2120fc89aa1a5ba45ecfe8631fc791d39b98a01b"
] | [
"implementations/bicyclegan/datasets.py"
] | [
"import glob\nimport os\nimport numpy as np\nfrom torch.utils.data import Dataset\nfrom PIL import Image\nimport torchvision.transforms as transforms\nfrom torchvision.transforms import InterpolationMode\n\nclass ImageDataset(Dataset):\n def __init__(self, root, input_shape, mode=\"train\"):\n self.transf... | [
[
"numpy.random.random",
"numpy.array"
]
] |
leogao2/lm-evaluation-harness | [
"7ff58fe17c9c212f5387a3fcfaf86d22075cb79a"
] | [
"lm_eval/tasks/superglue.py"
] | [
"\"\"\"\nTo-do:\n - WSC requires free-form generation\n - ReCoRD\n\"\"\"\nimport numpy as np\nimport sklearn\nimport transformers.data.metrics.squad_metrics as squad_metrics\nfrom . common import HFTask, yesno\nfrom lm_eval.base import rf\nfrom ..metrics import mean, acc_all, metric_max_over_ground_truths\nfr... | [
[
"numpy.array",
"sklearn.metrics.f1_score",
"numpy.argmax"
]
] |
k4ntz/procgen | [
"dca9c99379ba1f68573d035b0c6522f11c726808"
] | [
"procgen/env.py"
] | [
"import os\nimport random\nfrom typing import Sequence, Optional, List\n\nimport gym3\nfrom gym3.libenv import CEnv\nimport numpy as np\nfrom .builder import build\n\nSCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))\n\nMAX_STATE_SIZE = 2 ** 20\n\nENV_NAMES = [\n \"bigfish\",\n \"bossfight\",\n \"cav... | [
[
"numpy.array"
]
] |
BlackBoxOperator/GotchaTheNames | [
"a90691910b42d8a168ab3dc6e8edd08c4f349214"
] | [
"models/oracle.py"
] | [
"#!/usr/bin/env python3.6\n# coding: utf-8\n\nfrom tqdm import *\nimport numpy as np\nimport time, os, json, csv, re, sys\nimport shutil\n\nfrom sklearn.metrics.pairwise import cosine_similarity\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransforme... | [
[
"numpy.sum",
"numpy.zeros",
"sklearn.feature_extraction.text.TfidfVectorizer",
"sklearn.metrics.pairwise.cosine_similarity"
]
] |
Inujal/jiant | [
"095fd4ab7613fe270fd7b7c64b00a90b32b18b5b"
] | [
"jiant/shared/initialization.py"
] | [
"import json\nimport numpy as np\nimport os\nimport random\nimport time\nimport torch\nfrom dataclasses import dataclass\nfrom typing import Any\n\nimport jiant.utils.python.io as py_io\nimport jiant.utils.zlog as zlog\n\n\n@dataclass\nclass QuickInitContainer:\n device: Any\n n_gpu: int\n log_writer: Any\... | [
[
"torch.device",
"torch.cuda.manual_seed_all",
"numpy.random.seed",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.cuda.is_available",
"numpy.random.randint"
]
] |
bkj/sgm | [
"65e7f932042c9d3a2f8e14b7a55dc1b217371f32"
] | [
"examples/kasios/kasios.py"
] | [
"#!/usr/bin/env python\n\n\"\"\"\n sgm/examples/kasios/kasios.py\n\"\"\"\n\nimport warnings\nwarnings.filterwarnings(\"ignore\", module=\"scipy.sparse\")\n\nimport sys\nimport json\nimport argparse\nimport numpy as np\nfrom time import time\n\nfrom scipy import sparse\n\nfrom sgm import factory as sgm_factory\n\... | [
[
"numpy.random.RandomState",
"numpy.random.seed",
"numpy.ones",
"numpy.load",
"scipy.sparse.eye",
"numpy.arange",
"numpy.sort"
]
] |
NumEconCopenhagen/Suggested-Solutions-2021 | [
"1f5189a3c398251993fd9c58e0ec4a9ec13ccaae"
] | [
"inaugralproject/inauguralproject.py"
] | [
"import numpy as np\nfrom scipy import optimize\n\ndef u_func(c, h, mp):\n \"\"\" Calculates utility of chosen (consumption, housing) bundle.\n\n Args:\n\n c (float): consumption\n h (float): housing \n mp (dict): model parameters. \n\n Returns:\n\n (float): utility of bundle\n \"\"\"\n r... | [
[
"scipy.optimize.minimize_scalar"
]
] |
aliakbar09a/Practising_CV_using_opencv-python | [
"ed797d4a29ae16aeec5f833c32a94b10cf92ffe7"
] | [
"opencv/object_tracking.py"
] | [
"import numpy as np\nimport cv2\n\ncap = cv2.VideoCapture(0)\nwhile(1):\n ret, frame = cap.read()\n\n\n lower_blue = np.array([110,50,50])\n upper_blue = np.array([130,255,255])\n lower_red = np.array([-10,100,100])\n upper_red = np.array([10,255,255])\n lower_green = np.array([50,100,100])\n u... | [
[
"numpy.array"
]
] |
alexandrugavril/habitat-api | [
"95106a965355e024dc7ebd109519799a64530660"
] | [
"habitat_baselines/rl/ppo/ppo_trainer.py"
] | [
"#!/usr/bin/env python3\n\n# 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 os\nimport time\nfrom collections import deque\nfrom typing import Dict, List\n\nimport numpy as np\ni... | [
[
"torch.zeros",
"torch.device",
"torch.no_grad",
"torch.cuda.is_available",
"torch.tensor",
"torch.load"
]
] |
SimonCW/NVTabular | [
"229d6da5cfcf26dece7867ff43a1414b711b07be"
] | [
"tests/unit/ops/test_categorify.py"
] | [
"#\n# Copyright (c) 2021, NVIDIA CORPORATION.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicabl... | [
[
"pandas.DataFrame",
"pandas.isna",
"numpy.dtype",
"pandas.Series"
]
] |
whlll-coder/Python- | [
"89ef9a85e6b985f7f991695c8838a0356888cb76",
"89ef9a85e6b985f7f991695c8838a0356888cb76",
"89ef9a85e6b985f7f991695c8838a0356888cb76"
] | [
"PythonCode/03/3.5.4_SupportVectorMachine.py",
"PythonCode/App_A/linear_regression_iterative_solution.py",
"PythonCode/05/fig5-4.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport matplotlib.pyplot as plt\nfrom sklearn import datasets\nfrom sklearn import svm\nfrom sklearn.metrics import accuracy_score, confusion_matrix\nfrom sklearn.metrics import precision_score, recall_score, f1_score\n\n# 加载digits数据\ndigits = datasets.load_digits()\n\n# 在第2行第5列显示图像\nfor... | [
[
"sklearn.metrics.confusion_matrix",
"sklearn.datasets.load_digits",
"sklearn.metrics.f1_score",
"sklearn.svm.SVC",
"sklearn.metrics.accuracy_score",
"sklearn.metrics.recall_score",
"matplotlib.pyplot.show",
"sklearn.metrics.precision_score",
"matplotlib.pyplot.imshow",
"mat... |
joshtemple/tfx | [
"527fe2bab6e4f62febfe1a2029358fabe55f418c"
] | [
"tfx/components/trainer/rewriting/tflite_rewriter.py"
] | [
"# Lint as: python2, python3\n# Copyright 2020 Google LLC. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\... | [
[
"tensorflow.compat.v1.io.gfile.isdir",
"tensorflow.compat.v1.io.gfile.rmtree",
"tensorflow.compat.v1.io.gfile.makedirs",
"tensorflow.compat.v1.io.gfile.exists",
"tensorflow.compat.v1.io.gfile.mkdir",
"tensorflow.compat.v1.lite.TFLiteConverter.from_saved_model"
]
] |
knutankv/knutils | [
"3c2c2e38a51b41e24e7f62af7bfdf1c6849e39ef"
] | [
"knutils/plot.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib\nfrom mpl_toolkits.mplot3d import Axes3D\nimport copy as cp\n\ndef equal_3d(ax=plt.gca()):\n x_lims = np.array(ax.get_xlim())\n y_lims = np.array(ax.get_ylim())\n z_lims = np.array(ax.get_zlim())\n\n x_range = np.diff(x_lims)\n y... | [
[
"numpy.max",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"numpy.mean",
"matplotlib.pyplot.figure",
"numpy.diff",
"numpy.where",
"numpy.shape",
"matplotlib.pyplot.gcf",
"numpy.sqrt",
"matplotlib.pyplot.gca",
"numpy.vstack"
]
] |
zylMozart/tods | [
"a4c0192b43b438276d2228306c0e9c896d9e3809"
] | [
"tods/tests/sk_interface/detection_algorithm/test_ski_So_Gaal.py"
] | [
"import numpy as np\nimport pandas as pd\nimport os\nfrom tods.sk_interface.detection_algorithm.So_Gaal_skinterface import So_GaalSKI\n\nfrom pyod.utils.data import generate_data\nimport unittest\nfrom numpy.testing import assert_allclose\nfrom numpy.testing import assert_array_less\nfrom unittest import TestCase\n... | [
[
"sklearn.metrics.roc_auc_score"
]
] |
DiogoRibeiro7/Finance | [
"6babc706bd523fc83e1dd1fda7f57aef969c5347"
] | [
"efficient_frontier_sharpe_ratio.py"
] | [
"# import needed modules\r\nimport quandl\r\nimport pandas as pd\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\n\r\n# get adjusted closing prices of 5 selected companies with Quandl\r\nquandl.ApiConfig.api_key = '8bbPKo8xjyoors-yMfr-'\r\nselected = ['CNP', 'F', 'WMT', 'GE', 'TSLA']\r\ndata = quandl.get... | [
[
"numpy.dot",
"numpy.random.seed",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"numpy.sum",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.style.use",
"matplotlib.pyplot.show",
"numpy.random.random"
]
] |
AnglinaBhambra/pandas | [
"c03164e8daa812193baa99378fded16695f3ef51",
"c03164e8daa812193baa99378fded16695f3ef51",
"ae6538f5df987aa382ec1499679982aaff1bfd86",
"c03164e8daa812193baa99378fded16695f3ef51"
] | [
"pandas/core/reshape/pivot.py",
"pandas/io/parsers/readers.py",
"pandas/io/formats/html.py",
"pandas/tests/reshape/test_qcut.py"
] | [
"from __future__ import annotations\n\nfrom typing import (\n TYPE_CHECKING,\n Callable,\n Hashable,\n Sequence,\n cast,\n)\n\nimport numpy as np\n\nfrom pandas._typing import (\n AggFuncType,\n AggFuncTypeBase,\n AggFuncTypeDict,\n FrameOrSeriesUnion,\n IndexLabel,\n)\nfrom pandas.uti... | [
[
"pandas.util._decorators.Substitution",
"pandas.core.common.convert_to_list_like",
"pandas.core.common.maybe_make_list",
"pandas.core.indexes.api.get_objs_combined_axis",
"pandas.core.dtypes.common.is_scalar",
"pandas.DataFrame",
"pandas.core.indexes.api.Index",
"pandas.core.dtypes... |
jibanCat/gp_dla_detection_dr16q_public | [
"bf7bd6412aa2954276150e4b69ab12a0b2ad3958"
] | [
"CDDF_analysis/make_multi_dla_plots.py"
] | [
"'''\nMake plots for the Multi-DLA paper\n'''\nimport os\nimport numpy as np\nfrom scipy.stats import pearsonr\nfrom scipy.interpolate import interp1d\nfrom astropy.io import fits\n\nimport matplotlib \nfrom matplotlib import pyplot as plt \nfrom matplotlib import cm\nfrom .qso_loader import QSOLoader, file_loader\... | [
[
"matplotlib.pyplot.xlim",
"numpy.random.choice",
"numpy.exp",
"scipy.stats.pearsonr",
"numpy.min",
"numpy.where",
"numpy.nanmean",
"numpy.max",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.fill_between",
"matplotlib.pyplot.tight_layout",
"numpy.sqrt",
"numpy... |
iuisefinalprojects/ice | [
"fa0575471d90751ff035a41523609a036f02cf8f"
] | [
"release-4.0.0/code/setup/test.py"
] | [
"import VhdlAPI as vhdlapi\nimport urllib\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\nimport scipy.misc\nfrom numpy import genfromtxt\n\n# vhdl_source_bin_file = 'image_3_200x200_pad.min'\n# vhdl_source_bin_path = 'binaries/'\n\n# vhdlapi2 = vhdlapi.VhdlAPI(source_bin_pat... | [
[
"numpy.genfromtxt"
]
] |
Sergei-Lebedev/torch_ucc | [
"a5695ff22831bec140964eb8f71dda72e56603ee"
] | [
"test/torch_ucc_test_setup.py"
] | [
"#\n# Copyright (C) Mellanox Technologies Ltd. 2001-2021.\n#\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#\n\nimport argparse\nimport torch\nimport torch.distributed as dist\nimp... | [
[
"torch.device",
"torch.distributed.new_group",
"torch.eq",
"torch.distributed.init_process_group",
"torch.cuda.set_device",
"torch.randint",
"torch.cuda.is_available",
"torch.tensor"
]
] |
BHD233/PaddleOCR2Pytorch | [
"f114069b3e2669c6adf0adf9596756205f184c9c"
] | [
"pytorchocr/modeling/backbones/det_mobilenet_v3.py"
] | [
"import os, sys\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom pytorchocr.modeling.common import Activation\n\ndef make_divisible(v, divisor=8, min_value=None):\n if min_value is None:\n min_value = divisor\n new_v = max(min_value, int(v + divisor / 2) // divisor * divisor)... | [
[
"torch.nn.ModuleList",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.Conv2d",
"torch.nn.AdaptiveAvgPool2d"
]
] |
showa-yojyo/notebook | [
"5f262ecda3df132cb66206c465d16e174061d6b9"
] | [
"source/_sample/pyopengl/shaderdemo.py"
] | [
"#!/usr/bin/env python\n\"\"\"shaderdemo.py: Demonstrate GLSL.\n\nReferences:\n * rndblnch / opengl-programmable\n <http://bitbucket.org/rndblnch/opengl-programmable>\n * OpenGLBook.com\n <http://openglbook.com/chapter-4-entering-the-third-dimension.html>\n * Tutorials for modern OpenGL (3.3+)\n <http:/... | [
[
"numpy.hstack",
"numpy.array",
"numpy.sin",
"numpy.cos"
]
] |
aktech/numba | [
"986c7d1502fd1dbd5feca77e8ff17ba9952ab237"
] | [
"numba/cuda/api.py"
] | [
"\"\"\"\nAPI that are reported to numba.cuda\n\"\"\"\n\n\nimport contextlib\n\nimport numpy as np\n\nfrom .cudadrv import devicearray, devices, driver\n\n\n# NDarray device helper\n\nrequire_context = devices.require_context\ncurrent_context = devices.get_context\ngpus = devices.gpus\n\n\n@require_context\ndef from... | [
[
"numpy.ndarray.view",
"numpy.ndarray",
"numpy.prod",
"numpy.dtype"
]
] |
bezorro/ACMN | [
"6a1de9cebc98f3057e7ddc93bbd4e00f777ed2d4"
] | [
"vqa_lab/data/dataset_vqav2.py"
] | [
"import h5py\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn.init\nfrom PIL import Image\nfrom torch.utils.data import Dataset\nfrom torchvision import transforms\nfrom vqa_lab.utils import read_json\n\nclass vqa2Dataset(Dataset):\n \"\"\"vqa dataset.\"\"\"\n def __init__(se... | [
[
"numpy.int64",
"numpy.array",
"numpy.int32"
]
] |
Chris10M/Vision-Project-Image-Segmentation | [
"d32fe9302320c74f238bc125f1d62a4e2ddbca22"
] | [
"Task2/demo.py"
] | [
"\"\"\"\nTo visualize the results, demo.py needs two arguments,\n--root (compulsary) - root directory of Cityscapes \n--model_path (compulsary) - path of the saved_model \n\nPress 'q' to quit the demo.\nPress any key to visualize the next image. \n\"\"\"\n\n\nimport torch\nimport numpy as np\nimport cv2\ni... | [
[
"torch.device",
"torch.no_grad",
"torch.cuda.is_available",
"torch.utils.data.DataLoader"
]
] |
amoran-symbio/Open3D | [
"ae7e44e0dcef11a5df763819d47dec8c5bd5294b",
"ae7e44e0dcef11a5df763819d47dec8c5bd5294b"
] | [
"examples/python/geometry/octree_point_cloud.py",
"examples/python/visualization/remove_geometry.py"
] | [
"# ----------------------------------------------------------------------------\n# - Open3D: www.open3d.org -\n# ----------------------------------------------------------------------------\n# The MIT License (MIT)\n#\n# Copyright (c) 2018-2021 www.open3d.org\n#\n# ... | [
[
"numpy.random.uniform"
],
[
"numpy.identity"
]
] |
AngusNicolson/factorial_experiment_analysis | [
"a499642c38cb22a2ce13b93dda82c622193e7e35"
] | [
"ANOVA.py"
] | [
"import itertools\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport pandas as pd\nfrom scipy.stats import f\nfrom scipy.stats import norm\n\nclass ANOVA:\n \"\"\"Analyse DOE experiments using ANOVA. NB: n > 1 for the code to work, where n is the number of repeats.\n Model: y ... | [
[
"scipy.stats.norm.ppf",
"scipy.stats.f",
"matplotlib.pyplot.axvline",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.barh",
"numpy.sqrt",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"pandas.read_csv"
]
] |
amwons/Super-Resolution | [
"11d99ffbae17fdc65c32ccfa0ce3f20ff47c99b5"
] | [
"VDSR/solver.py"
] | [
"from __future__ import print_function\nfrom math import log10\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.backends.cudnn as cudnn\nimport torchvision.transforms as transforms\nfrom VDSR.model import Net\nfrom misc import progress_bar\nfrom PIL import Image\n\n\nclass VDSRTrain... | [
[
"torch.device",
"torch.cuda.manual_seed",
"torch.nn.MSELoss",
"torch.save",
"torch.FloatTensor",
"torch.no_grad",
"torch.optim.lr_scheduler.MultiStepLR",
"torch.manual_seed",
"torch.cuda.is_available"
]
] |
qTipTip/GamestonkTerminal | [
"8a3546a636d1b39e79e365d77ad4273c1fc3f7e7"
] | [
"gamestonk_terminal/fundamental_analysis/market_watch_view.py"
] | [
"\"\"\" Fundamental Analysis Market Watch View \"\"\"\n__docformat__ = \"numpy\"\n\nimport argparse\nfrom typing import List\nimport pandas as pd\n\nfrom gamestonk_terminal.fundamental_analysis import market_watch_model as mwm\nfrom gamestonk_terminal.helper_funcs import (\n parse_known_args_and_warn,\n patch... | [
[
"pandas.set_option"
]
] |
vivekveeriah/gym-miniworld | [
"0640074e34d24f61a637820980673b1503e9a840"
] | [
"gym_miniworld/envs/tworoomlarge.py"
] | [
"import numpy as np\nimport math\nfrom gym import spaces\nfrom ..miniworld import MiniWorldEnv, Room\nfrom ..entity import Box, ImageFrame, MeshEnt\nfrom ..params import DEFAULT_PARAMS\n\nclass TwoRoomLarge(MiniWorldEnv):\n \"\"\"\n Outside environment with two rooms connected by a gap in a wall\n \"\"\"\n... | [
[
"numpy.array",
"numpy.random.choice"
]
] |
vivek2301/executors | [
"8159681d68408ab8f797497bc3374be77e6ca392",
"8159681d68408ab8f797497bc3374be77e6ca392"
] | [
"jinahub/encoders/text/TransformerTorchEncoder/transform_encoder.py",
"jinahub/encoders/image/CustomImageTorchEncoder/tests/integration/test_custom_image_torch_encoder.py"
] | [
"__copyright__ = 'Copyright (c) 2021 Jina AI Limited. All rights reserved.'\n__license__ = 'Apache-2.0'\n\nfrom typing import Dict, Iterable, Optional, Tuple\n\nimport numpy as np\nimport torch\nfrom jina import DocumentArray, Executor, requests\nfrom jina_commons.batching import get_docs_batch_generator\nfrom tran... | [
[
"torch.nn.functional.pad",
"torch.no_grad",
"torch.tensor"
],
[
"numpy.random.rand"
]
] |
lily0101/my-tf-faster-rcnn | [
"639670c7dabc212513f25577c3a8b95087a7459d"
] | [
"lib/layer_utils/proposal_top_layer.py"
] | [
"# --------------------------------------------------------\n# Faster R-CNN\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Xinlei Chen\n# --------------------------------------------------------\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ impo... | [
[
"tensorflow.zeros",
"tensorflow.concat",
"tensorflow.nn.top_k",
"tensorflow.reshape",
"tensorflow.to_float",
"tensorflow.gather"
]
] |
aivant/chemprop | [
"43ef898e8717f5ad9646cfccb99f6b6eb1a555ed"
] | [
"chemprop/args.py"
] | [
"import json\nimport os\nimport pickle\nfrom tempfile import TemporaryDirectory\nfrom typing import List, Optional, Tuple\n\nimport torch\nfrom tap import (\n Tap,\n) # pip install typed-argument-parser (https://github.com/swansonk14/typed-argument-parser)\nfrom typing_extensions import Literal\n\nimport chempr... | [
[
"torch.device",
"torch.cuda.is_available",
"torch.cuda.device_count"
]
] |
MHYNW/Dickhunter | [
"dea7ab26854e0f3eb34af668b10e9c7474b87484"
] | [
"PathPlanning/DynamicWindowApproach/dwa_3d.py"
] | [
"# -*- coding: utf-8 -*- \n\n\"\"\"\nMobile robot motion planning sample with Dynamic Window Approach\n\nauthor: Atsushi Sakai (@Atsushi_twi), Göktuğ Karakaşlı\n\n\"\"\"\n\nimport math\nfrom enum import Enum\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom mpl_toolkits.mplot3d import Axes3D\n\nshow_anim... | [
[
"numpy.array",
"numpy.sin",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.plot",
"numpy.min",
"matplotlib.pyplot.cla",
"numpy.arange",
"numpy.hypot",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.Circle",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.show",
"matpl... |
Xorgon/SudokuSolver | [
"44ce1c8e37d7b559598d197ab29621089cadbb3e"
] | [
"sudoku.py"
] | [
"import numpy as np\nimport math\n\nsudoku = np.zeros([9, 9], dtype=list)\n\n\ndef deserialize_sudoku(serialized):\n \"\"\"\n a b c d e f g h i\n j k l . . . . . .\n . . . . . . . . .\n\n would be from\n\n abcdefghijkl...\n \"\"\"\n serialized = serialized.replace(\",\", \"\")\n if len(se... | [
[
"numpy.zeros"
]
] |
kimcoco/mne-python | [
"df227e7a9f67f61cf1322686308a78627d2289f4"
] | [
"mne/viz/_brain/_brain.py"
] | [
"# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>\n# Eric Larson <larson.eric.d@gmail.com>\n# Oleh Kozynets <ok7mailbox@gmail.com>\n# Guillaume Favelier <guillaume.favelier@gmail.com>\n# jona-sassenhagen <jona.sassenhagen@gmail.com>\n# Joan Massich <mailsik@gm... | [
[
"numpy.dot",
"numpy.array_equal",
"numpy.min",
"numpy.mean",
"numpy.where",
"numpy.max",
"numpy.full",
"numpy.concatenate",
"numpy.linalg.norm",
"numpy.empty",
"numpy.interp",
"numpy.eye",
"numpy.unravel_index",
"numpy.prod",
"numpy.arange",
"numpy.i... |
KTH-HPC/StreamBrain | [
"37b16e7c8e02e6d2800bcf89630a0f4419e90cd4"
] | [
"BCPNN/backend/_kernels/kernels_numpy.py"
] | [
"import numpy as np\n\n\ndef update_state(state, weights, bias, inputs):\n return np.matmul(inputs, weights) + bias\n\n\ndef add_bias(a, x):\n # Assert shapes?\n return a + x\n\n\ndef _softmax(x, axis):\n t = np.exp(x - x.max(axis=axis, keepdims=True))\n return t / np.sum(t, axis=axis, keepdims=True)... | [
[
"numpy.zeros_like",
"numpy.matmul",
"numpy.reshape",
"numpy.zeros",
"numpy.log",
"numpy.sum",
"numpy.mean",
"numpy.maximum"
]
] |
IgoRamli/IndoKEPLER | [
"79bd9c2784c0e336b718e0a151593ab3305b3a4c"
] | [
"preprocessing/gen_negative_sampling.py"
] | [
"import numpy as np\nimport math\nimport gc\nimport os\n\nfrom argparse import ArgumentParser\nfrom datasets import load_from_disk, load_dataset\nfrom tqdm import tqdm\nfrom pathlib import Path\n\nparser = ArgumentParser(description='Generate negative sampling')\nparser.add_argument('entity_dir', help='Path to dire... | [
[
"numpy.in1d",
"numpy.random.choice"
]
] |
warmtub/thor-iqa-cvpr-2018 | [
"38358569422a93fa42a782f3022554672507a08a"
] | [
"thor_tests/test_image_overlays.py"
] | [
"import os\nimport numpy as np\nimport scipy.misc\nfrom utils import game_util\n\ndef assert_image(expected_image, actual_image, raise_if_fail=True):\n try:\n assert(np.all(expected_image == actual_image))\n except AssertionError as e:\n print('Failed image comparison')\n import cv2\n ... | [
[
"numpy.all"
]
] |
vvchenvv/Self_Driving_Tutorial | [
"649fddeb1371aa2a02ed49e5dbb8204119b0a3c1"
] | [
"Class1/07-00 Simple_test_on_Keras/Traffic_sign_Classifier_On_Keras.py"
] | [
"# Load pickled data\nimport pickle\nimport numpy as np\nimport tensorflow as tf\ntf.python.control_flow_ops = tf\n#from generator import generator\n\n# WAITING FOR CODE PACKAGE TO SYNC UP\nwith open('train.p', mode='rb') as f:\n data = pickle.load(f)\n\nX_train, y_train = data['features'], data['labels']\n\n# I... | [
[
"numpy.array",
"sklearn.preprocessing.LabelBinarizer"
]
] |
HONGcalmJIN/SMARTS | [
"0e2249a3bc985ee9279512d6154ce32732065835"
] | [
"examples/rllib_agent.py"
] | [
"from pathlib import Path\n\nimport gym\nimport numpy as np\n\nfrom ray.rllib.models import ModelCatalog\nfrom ray.rllib.models.tf.fcnet_v2 import FullyConnectedNetwork\nfrom ray.rllib.utils import try_import_tf\n\nfrom smarts.core.agent_interface import AgentInterface, AgentType\nfrom smarts.core.agent import Agen... | [
[
"numpy.array"
]
] |
juglab/EmbedSeg-napari | [
"28944dcb88e1cc14a71aea8f1ae9430cb7629cef"
] | [
"embedseg_napari/utils/glasbey.py"
] | [
"\"\"\"\nModified from https://github.com/taketwo/glasbey\n\"\"\"\n\n#!/usr/bin/env python\n# encoding: utf-8\n\nimport os\nimport sys\nimport ast\nimport argparse\n\nimport numpy as np\nfrom colorspacious import cspace_convert\n\nfrom embedseg_napari.utils.view_palette import palette_to_image\n\n# try:\n# # th... | [
[
"numpy.linalg.norm",
"numpy.empty",
"numpy.ones",
"numpy.load",
"numpy.savez_compressed",
"numpy.argmax"
]
] |
ucl-exoplanets/taurex-petitrad | [
"c7cb7904ce414cdd4194e10d753163d77e238738"
] | [
"taurex_petitrad/model/transmission.py"
] | [
"from .petitradtrans import petitRADTRANSModel\nimport numpy as np\nfrom taurex.exceptions import InvalidModelException\nfrom taurex.core import fitparam\n\nclass TransmissionRADTRANS(petitRADTRANSModel):\n\n @classmethod\n def input_keywords(self):\n return ['transmission-petitrad', 'transit-petitrad'... | [
[
"numpy.isnan",
"numpy.zeros"
]
] |
PhilippMarquardt/mmdetection | [
"ca11860f4f3c3ca2ce8340e2686eeaec05b29111"
] | [
"mmdet/apis/inference.py"
] | [
"# Copyright (c) OpenMMLab. All rights reserved.\nimport warnings\nfrom pathlib import Path\n\nimport mmcv\nimport numpy as np\nimport torch\nfrom mmcv.ops import RoIPool\nfrom mmcv.parallel import collate, scatter\nfrom mmcv.runner import load_checkpoint\n\nfrom mmdet.core import get_classes\nfrom mmdet.datasets i... | [
[
"torch.no_grad",
"torch.set_grad_enabled"
]
] |
chengzee/climate_predict | [
"a10f3701f9e2083ac9c0e0f4453dbe5158b481ba"
] | [
"orchid_ClimatePredict/enc-dec_byCZ.py"
] | [
"import numpy as np\nimport pandas as pd\nimport csv\nimport time\nimport matplotlib.pyplot as plt\nimport tensorflow as tf\nimport os\n\nos.environ[\"CUDA_VISIBLE_DEVICES\"] = \"1\"\n\nphysical_devices = tf.config.list_physical_devices('GPU')\ntry:\n tf.config.experimental.set_memory_growth(physical_devices[1], T... | [
[
"tensorflow.keras.layers.RepeatVector",
"numpy.min",
"tensorflow.keras.Sequential",
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.LSTM",
"pandas.read_csv",
"numpy.max",
"numpy.arange",
"tensorflow.keras.Input",
"... |
blueprintparadise/Embedding_Facenet | [
"9b4004243047a82f95739ad1cb508019d762e83b"
] | [
"Face_Recog/extendedmodels/Age.py"
] | [
"from Face_Recog.basemodels import VGGFace\nimport os\nfrom pathlib import Path\nimport gdown\nimport numpy as np\n\nimport tensorflow as tf\ntf_version = int(tf.__version__.split(\".\")[0])\n\nif tf_version == 1:\n\timport keras\n\tfrom keras.models import Model, Sequential\n\tfrom keras.layers import Convolution2... | [
[
"tensorflow.keras.layers.Flatten",
"numpy.sum",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.models.Model",
"tensorflow.keras.models.Sequential",
"tensorflow.keras.layers.Convolution2D",
"tensorflow.__version__.split"
]
] |
Jie-Re/GraphGallery | [
"37a2e807bb21e5ed986ade935ac9619b62bfdd90"
] | [
"graphgallery/nn/models/pytorch/appnp.py"
] | [
"import torch.nn as nn\nfrom torch import optim\n\nfrom graphgallery.nn.models import TorchKeras\nfrom graphgallery.nn.layers.pytorch import APPNProp, PPNProp, activations\nfrom graphgallery.nn.metrics.pytorch import Accuracy\n\n\nclass APPNP(TorchKeras):\n def __init__(self,\n in_features,\n ... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.Sequential",
"torch.nn.ReLU",
"torch.nn.CrossEntropyLoss"
]
] |
AdrianduPlessis/lambdata_adrianduplessis | [
"af61bd8859a392018e9a788d2ee57fb30caf54c3"
] | [
"lambdata_adrianduplessis/df_utils.py"
] | [
"import numpy as np\nimport pandas as pd\n\nONES = pd.Series(np.ones(20))\nZEROS = pd.Series(np.zeros(20))\n\n\ndef remove_observations_with_outliers(df, zscore=3):\n '''\n TODO\n '''\n # Outlier removal\n from scipy import stats\n\n # Get subset within 'zscore' (default=3) stdev\n df_cleaned ... | [
[
"numpy.ones",
"numpy.zeros"
]
] |
diegotg2000/Prueba30 | [
"df83f108fe7b1122f2fec39c1cc6f922416901e7"
] | [
"anima.py"
] | [
"import matplotlib\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport imageio\n\nvec=np.loadtxt('datos.txt',usecols=0)\n\nZ=np.zeros(shape=(401,201))\n\n \nfor i in range(401):\n Z[i,:]=vec[i*201:(i+1)*201]\n\n\ndef plot_for_offset(i):\n # Data for plotting\n x = np.arange(201)/201\n s = Z[... | [
[
"numpy.arange",
"numpy.loadtxt",
"matplotlib.pyplot.subplots",
"numpy.zeros"
]
] |
tejaskannan/ml-models | [
"ad5acad2c0ce75773062ffcdff088a6fbe5ffc17"
] | [
"budget-rnn/src/controllers/noise_generators.py"
] | [
"import numpy as np\nfrom typing import Optional, Dict, Any, Iterable\n\n\nclass NoiseGenerator:\n\n def __init__(self, max_time: int, loc: float, scale: float, seed: int):\n self._max_time = max_time\n self._loc = loc\n self._scale = scale\n\n self._rand = np.random.RandomState(seed=... | [
[
"numpy.sin",
"numpy.random.RandomState"
]
] |
ruizhaogit/mep | [
"0653ab47718d818504644387ed85b8538b5fb210"
] | [
"baselines/her/experiment/train.py"
] | [
"import os\nimport sys\n\nimport click\nimport numpy as np\nimport json\nfrom mpi4py import MPI\n\nfrom baselines import logger\nfrom baselines.common import set_global_seeds\nfrom baselines.common.mpi_moments import mpi_moments\nimport baselines.her.experiment.config as config\nfrom baselines.her.rollout import Ro... | [
[
"numpy.array",
"numpy.random.uniform"
]
] |
ThomazPom/PB2K | [
"02a4b6b028a0d32a73fd4e1d52e8f05c866e09df"
] | [
"ROMs/cut3.py"
] | [
"#!/usr/bin/python\n\nimport sys\nimport array\nimport numpy as np\n\nfull = np.fromfile('pb2k.rom',dtype=np.uint8)\n\nexpansion_size = 0x40 * 512\nsystem_size = full.size - expansion_size\n\nbios = np.empty((expansion_size,),dtype=np.uint8)\nsystem = np.empty((system_size,),dtype=np.uint8)\n\nyy = 0\nfor x in rang... | [
[
"numpy.empty",
"numpy.fromfile"
]
] |
gglin001/onnx_jax | [
"08e2a1181250db48f4436f6430903fc895a3a1d6",
"08e2a1181250db48f4436f6430903fc895a3a1d6"
] | [
"tests/node/test_maxpool.py",
"tests/node/test_acosh.py"
] | [
"import numpy as np\nimport onnx\n\nfrom tests.node.pool_op_common import get_output_shape, get_pad_shape, pool\nfrom tests.tools import expect\n\n\nclass MaxPool:\n @staticmethod\n def export_maxpool_2d_uint8(): # type: () -> None\n \"\"\"\n input_shape: [1, 1, 5, 5]\n output_shape: [1,... | [
[
"numpy.array",
"numpy.pad",
"numpy.add",
"numpy.random.randn",
"numpy.shape"
],
[
"numpy.arccosh",
"numpy.array",
"numpy.random.uniform"
]
] |
qkaren/converse_reading_cmr | [
"d06d981be12930cff8458e2b1b81be4f5df3a329",
"d06d981be12930cff8458e2b1b81be4f5df3a329"
] | [
"model/src/sub_layers.py",
"model/src/my_optim.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.nn.parameter import Parameter\n\n\nclass PositionwiseNN(nn.Module):\n def __init__(self, idim, hdim, dropout=None):\n super(PositionwiseNN, self).__init__()\n self.w_0 = nn.Conv1d(idim, hdim, 1)\n self.w_1 = nn... | [
[
"torch.zeros",
"torch.nn.Linear",
"torch.nn.Conv1d",
"torch.std",
"torch.ones",
"torch.mean"
],
[
"torch.nn.Parameter"
]
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.