repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
qianhk/FeiPython | [
"c87578d3c04b7345a99fef7390c8ea12c6f2c716",
"c87578d3c04b7345a99fef7390c8ea12c6f2c716"
] | [
"Python3Test/TensorflowTest.py",
"Python3Test/Numpy/array_index.py"
] | [
"#!/usr/bin/env python3\n# coding=utf-8\n\nimport tensorflow as tf\nimport numpy as np\n\n# with tf.device('/cpu:0'):\n#\n# sess = tf.Session()\n#\n# # a_gpu = tf.Variable(0, name=\"a_gup\")\n# # sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True))\n#\n# hello = tf.constant('Hello, Te... | [
[
"tensorflow.nn.in_top_k",
"tensorflow.diag",
"tensorflow.matmul",
"tensorflow.global_variables_initializer",
"tensorflow.argmax",
"tensorflow.random_uniform",
"tensorflow.Variable",
"tensorflow.transpose",
"tensorflow.cholesky",
"tensorflow.constant",
"numpy.array",
... |
Kreidl/pymailtojira | [
"abca5ad83d5cb9dcf526b2f3aa661d42ba69d9d6"
] | [
"main.py"
] | [
"#import pandas for reading the xlsx File\nimport pandas as pd\n#import pymsgbox for displaying a messagebox, the request to check if the URL from the mapping is available, the Handler for outlook, the time for the sleep, the custom py for jira\nimport pymsgbox, urllib.request,urllib.parse,urllib.error, win32com.cl... | [
[
"pandas.read_excel"
]
] |
mparthasarathy25/DiscordBotPython | [
"057a528ed6ee8852abe6e54ab5cc21a299f12d66"
] | [
"main.py"
] | [
"#imports with methods labeled, some imports were for the full library\nfrom discord import File, Embed\nfrom discord.ext import commands, tasks\nfrom sqlite3 import connect\nfrom datetime import datetime, timedelta, date\nfrom matplotlib.pyplot import xticks, yticks, xlabel, ylabel, show, close, bar, savefig, plot... | [
[
"numpy.random.normal",
"pandas.Index",
"scipy.stats.norm.ppf",
"numpy.zeros_like",
"numpy.random.seed",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"pandas.DataFrame",
"matplotlib.pyplot.close",
"matplotlib.pyplot.yticks",
"mat... |
NiallJeffrey/BornRaytrace | [
"cb07ed78d206563243ace6e9015804e87c6513e5"
] | [
"nersc/run_pkd_grav.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nimport healpy as hp\nimport os, sys, gc\n\nfrom astropy.io import fits\nfrom astropy.cosmology import FlatLambdaCDM\nfrom astropy import units as u\nfrom astropy.cosmology import z_at_value\n\nsys.path = ['../'] + sys.path\nimport born_raytrace as br\n\nindex = ... | [
[
"numpy.where",
"numpy.genfromtxt",
"numpy.mean"
]
] |
cescalara/icecube_tools | [
"d1695294f7cfab17500838ffeb72ac0ba06d3f8d"
] | [
"icecube_tools/cosmology.py"
] | [
"import numpy as np\n\nOm = 0.3\nOl = 0.7\nH0 = 70 # km s^-1 Mpc^-1\nc = 3e5 # km s^-1\nDH = c / H0 # Mpc\n\nMpc_to_cm = 3.086e24\nm_to_cm = 100\nyr_to_s = 3.154e7\n\n\ndef xx(z):\n \"\"\"\n Helper function for the computation of\n :py:func:`icecube_tools.cosmology.luminosity_distance`.\n \"\"\"\n\n ... | [
[
"numpy.power",
"numpy.sqrt"
]
] |
drewlinsley/ffn_membrane | [
"4b4638c00eed847fa6a7958a7fdbeedca4236561",
"4b4638c00eed847fa6a7958a7fdbeedca4236561"
] | [
"merge_predictions.py",
"membrane/membrane_ops/initialization.py"
] | [
"import numpy as np\nfrom matplotlib import pyplot as plt\nfrom skimage.measure import regionprops as rgp\n\n\nv1 = np.load('seg-0_0_0.npz')['segmentation']\nv2 = np.load('ding_segmentations/x0015/y0015/z0017/v0/0/0/seg-0_0_0.npz')['segmentation']\nbg = 0\n\n# 1. Count size of all segments in v1 and v2\nv1segs = rg... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.load",
"numpy.argsort"
],
[
"tensorflow.python.ops.random_ops.random_uniform",
"tensorflow.python.ops.random_ops.truncated_normal"
]
] |
ssattari/neural_prophet | [
"e121234d2f64d2b81f9c53f52b30d21a2cf1c6e0"
] | [
"neuralprophet/forecaster.py"
] | [
"import time\nfrom collections import OrderedDict\nimport numpy as np\nimport pandas as pd\n\nimport torch\nfrom torch.utils.data import DataLoader\nimport logging\nfrom tqdm import tqdm\n\nfrom neuralprophet import configure\nfrom neuralprophet import time_net\nfrom neuralprophet import time_dataset\nfrom neuralpr... | [
[
"torch.zeros",
"numpy.concatenate",
"torch.cos",
"numpy.log",
"pandas.DataFrame",
"torch.no_grad",
"torch.utils.data.DataLoader",
"torch.ones_like",
"pandas.concat",
"torch.zeros_like",
"pandas.Series",
"numpy.expand_dims",
"torch.sum"
]
] |
ActuallyRuben/home-assistant | [
"b09f5b67436d8db44825d146b78ddce391d4469c"
] | [
"homeassistant/components/iqvia/sensor.py"
] | [
"\"\"\"Support for IQVIA sensors.\"\"\"\nimport logging\nfrom statistics import mean\n\nimport numpy as np\n\nfrom homeassistant.components.iqvia import (\n DATA_CLIENT, DOMAIN, SENSORS, TYPE_ALLERGY_FORECAST, TYPE_ALLERGY_OUTLOOK,\n TYPE_ALLERGY_INDEX, TYPE_ALLERGY_TODAY, TYPE_ALLERGY_TOMORROW,\n TYPE_AST... | [
[
"numpy.array",
"numpy.polyfit"
]
] |
banne2266/UAV-autopilot-NCTU-2021 | [
"1a25d4add2de9659516d045054935e3b6e04d06d",
"1a25d4add2de9659516d045054935e3b6e04d06d"
] | [
"util.py",
"final/evaluation.py"
] | [
"from cv2 import cv2\r\nimport tello\r\nimport time\r\nimport numpy as np\r\nimport math\r\nfrom enum import Enum\r\n\r\ndef get_coloser(drone, tvec, rvec, go_distance, idx):\r\n up_down = tvec[idx][0][1] + 5\r\n distance = tvec[idx][0][2] - go_distance\r\n left_right = tvec[idx][0][0]\r\n\r\n dst, jaco... | [
[
"numpy.sum",
"numpy.array"
],
[
"numpy.matrix",
"pandas.DataFrame",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"pandas.concat",
"matplotlib.pyplot.show",
"pandas.read_csv",
"numpy.linalg.inv"
]
] |
wd15/graspi | [
"4319cad2d5490903998094cdee85f039f70a4ff6"
] | [
"setupGraspiCython.py"
] | [
"from setuptools import Extension, setup\nfrom Cython.Build import cythonize\n\nimport numpy\n\nsourcefiles = ['cythonizeGraspi/graspi.pyx', 'src/graph_constructors.cpp']\n\nextensions = [\n Extension('graspi', sourcefiles,\n include_dirs=[numpy.get_include(), '/Users/owodo/Packa... | [
[
"numpy.get_include"
]
] |
lukasz-tuz/kids-control-panel | [
"2f04087b198aa24d4039552fc61bbb4e4788a2f8"
] | [
"control-panel/conversions.py"
] | [
"# uint32_t RgbLed:: rectToRGB(float x, float y)\n# {\n# auto cval = [](float theta, float ro, float phase) {\n# float val = sin(0.6 * theta - phase)\n# if (val < 0)\n# val = 0\n# return val\n# }\n# float theta = atan2(y, x) * RAD_TO_DEG\n# float ro = sqrt(x * x + y *... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"numpy.arange"
]
] |
martiansideofthemoon/language | [
"2aca4d197f48a96e79aac36c8b5a643b14204469"
] | [
"language/conpono/cpc/run_cpc.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unl... | [
[
"tensorflow.contrib.tpu.TPUEstimatorSpec",
"tensorflow.data.experimental.sample_from_datasets",
"tensorflow.data.TFRecordDataset",
"tensorflow.contrib.tpu.TPUEstimator",
"tensorflow.reshape",
"tensorflow.stack",
"tensorflow.one_hot",
"tensorflow.random.shuffle",
"tensorflow.par... |
brio50/beam-calc | [
"7b05001ddbb8b45ab5c538973efab517730ae98d"
] | [
"main.py"
] | [
"from sympy.physics.continuum_mechanics.beam import Beam\nfrom sympy import *\nfrom sympy.plotting import plot, PlotGrid\nimport matplotlib.pyplot as plt\n\n# https://docs.sympy.org/latest/modules/physics/continuum_mechanics/beam_problems.html#example-7\n\ndef beam_me_up(rxn, __L, __E, __I, __F, color):\n\n ## s... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots"
]
] |
deb-intel/LPOTtest | [
"f7b7524c733e581668d15192b69f9d9a7ca5222d",
"f7b7524c733e581668d15192b69f9d9a7ca5222d"
] | [
"lpot/adaptor/ox_utils/onnxrt_mid.py",
"lpot/adaptor/tf_utils/quantize_graph/quantize_graph_concatv2.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n#\n# Copyright (c) 2021 Intel Corporation\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.... | [
[
"numpy.float32"
],
[
"tensorflow.python.framework.dtypes.as_dtype",
"tensorflow.core.framework.node_def_pb2.NodeDef"
]
] |
giftmischer69/squash | [
"78ce87bf42911b5065e02d9622137a613bc78634"
] | [
"pypefx/shell.py"
] | [
"import logging\nimport os\nfrom cmd import Cmd\nfrom glob import glob\nfrom os import listdir\nfrom os.path import join, isfile\nfrom pathlib import Path\nfrom typing import List\n\nimport yaml\nfrom numpy.core.defchararray import isnumeric\nfrom wasabi import msg\n\nfrom pypefx._version import __version__\nfrom p... | [
[
"numpy.core.defchararray.isnumeric"
]
] |
ktobah/client | [
"e7d6ce75f9ab5158139ceed5d86c7afde8a21009"
] | [
"tests/test_data_types.py"
] | [
"import wandb\nfrom wandb import data_types\nimport numpy as np\nimport pytest\nimport PIL\nimport os\nimport matplotlib\nimport six\nimport sys\n\nfrom wandb.data_types import ImageMask, BoundingBoxes2D\n\nmatplotlib.use(\"Agg\")\nfrom click.testing import CliRunner\nimport matplotlib.pyplot as plt\nfrom click.tes... | [
[
"matplotlib.use",
"numpy.histogram",
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.plot",
"numpy.random.uniform",
"numpy.random.randint",
"numpy.random.random"
]
] |
AntonFirc/SUR | [
"3173a80731e601cdcc590166a8ba2ef801e60325"
] | [
"speech/speech_keras_predict.py"
] | [
"from pathlib import Path\nfrom tqdm import tqdm\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow import keras\nimport speech_keras_config as Config\nimport speech_keras_data_man as dm\nimport os\nfrom tensorflow.compat.v1 import ConfigProto\nfrom tensorflow.compat.v1 import InteractiveSession\nimport ... | [
[
"numpy.log",
"tensorflow.compat.v1.ConfigProto",
"tensorflow.compat.v1.InteractiveSession",
"numpy.load",
"tensorflow.keras.models.load_model",
"numpy.argmax",
"numpy.average",
"tensorflow.split"
]
] |
daimon99/distributed | [
"85b3b99bfe25e93cfcaf1d1f9a3f7408fb2e29c1"
] | [
"distributed/dashboard/components/scheduler.py"
] | [
"import logging\nimport math\nimport operator\nimport os\nfrom collections import defaultdict\nfrom numbers import Number\n\nfrom bokeh.core.properties import without_property_validation\nfrom bokeh.io import curdoc\nfrom bokeh.layouts import column, row\nfrom bokeh.models import (\n AdaptiveTicker,\n Arrow,\... | [
[
"numpy.histogram",
"numpy.array"
]
] |
jstaker7/espaloma | [
"d80d280acd608dc04c93966afe15cc3cb74f65a8"
] | [
"espaloma/utils/geometry.py"
] | [
"import numpy as np\n\n\ndef _sample_unit_circle(n_samples: int = 1) -> np.ndarray:\n \"\"\"\n >>> np.isclose(np.linalg.norm(_sample_unit_circle(1)), 1)\n True\n\n \"\"\"\n theta = np.random.rand(n_samples) * 2 * np.pi\n x = np.cos(theta)\n y = np.sin(theta)\n xy = np.array([x, y]).T\n as... | [
[
"numpy.array",
"numpy.sin",
"numpy.random.rand",
"numpy.linalg.norm",
"numpy.multiply",
"numpy.arctan2",
"numpy.cos",
"numpy.cross"
]
] |
lubosmj/I2I-GANs | [
"059e3896afc8524825164b612cbe120d72d676e6"
] | [
"examples/travelgan_trainer.py"
] | [
"import os\nimport tensorflow as tf\n\nfrom contextlib import ExitStack\nfrom functools import partial\n\nfrom tensorflow import keras\n\nfrom i2i_gans import parsers, datasets, callbacks, TraVeLGAN\n\n\nclass TraVeLGANParser(parsers.Parser):\n def init_train_subparser(self):\n super().init_train_subparse... | [
[
"tensorflow.distribute.MirroredStrategy",
"tensorflow.data.experimental.sample_from_datasets",
"tensorflow.data.Dataset.list_files",
"tensorflow.keras.layers.Input",
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.layers.experimental.preprocessing.Rescaling",
"tensorflo... |
jacobpostman/incubator-tvm | [
"fdef79d317d455eb5c9e9e86feb97416eb594690",
"02643d39798c6ec28348235d36d8da626f50d9dd"
] | [
"tests/python/unittest/test_tir_buffer.py",
"python/tvm/te/hybrid/runtime.py"
] | [
"# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); y... | [
[
"numpy.random.uniform",
"numpy.zeros"
],
[
"numpy.exp",
"numpy.ones_like",
"numpy.zeros",
"numpy.sqrt"
]
] |
malteos/aspect-document-embeddings | [
"0836ea54a9192dbc2b01bb212c7521668bb398af"
] | [
"sentence_transformer_cli.py"
] | [
"#!/usr/bin/env python\nimport logging\nimport os\nimport sys\nfrom typing import Union\n\nimport fire\nimport pyarrow\nfrom sentence_transformers.models import Pooling, Transformer\nfrom smart_open import open\nfrom tqdm import tqdm\nfrom sentence_transformers import SentenceTransformer, losses\nimport torch\n\nfr... | [
[
"torch.utils.data.DataLoader"
]
] |
drunkcoding/huggingface-utils | [
"4baad306857c357d94607076c6ab0cb5d6350cbe"
] | [
"hfutils/monte_carlo.py"
] | [
"import numpy as np\nfrom tqdm import tqdm\n\ndef monte_carlo_execute(func, bounds, dtype, n=100):\n # print(bounds)\n rnd = [np.random.uniform(b_l, b_h+0.01*b_h, n).tolist() for b_l, b_h in bounds]\n rnd_choices = [\n [rnd[i][np.random.randint(0, n)] for i in range(len(bounds))]\n for _ in r... | [
[
"numpy.max",
"numpy.array",
"numpy.round",
"numpy.min",
"numpy.random.uniform",
"numpy.random.randint",
"numpy.argpartition",
"numpy.append"
]
] |
zhangyx96/MAPPO | [
"b7535092d5e8f7b0de108191a9229dfa01e1628c"
] | [
"a2c_ppo_acktr/model_sp.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom a2c_ppo_acktr.distributions import Bernoulli, Categorical, DiagGaussian\nfrom a2c_ppo_acktr.utils import init\nimport time\n\nclass Flatten(nn.Module):\n def forward(self, x):\n return x.view(x.size(0), -1)\n... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.LayerNorm",
"torch.stack",
"torch.mul",
"torch.nn.GRU",
"torch.nn.init.constant_",
"torch.nn.Tanh",
"torch.FloatTensor",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"numpy.sqrt",
"torch.nn.functional.softmax",
"torch.nn.init... |
yuehaowang/SoGCN | [
"bd65b2d8667791b79d6174a1dd2ac13b7bd50db5"
] | [
"main_superpixels_graph_classification.py"
] | [
"\n\n\n\n\n\"\"\"\n IMPORTING LIBS\n\"\"\"\nimport dgl\n\nimport numpy as np\nimport os\nimport socket\nimport time\nimport random\nimport glob\nimport argparse, json\nimport pickle\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nimport torch.optim as optim\nfrom torch.utils.data impor... | [
[
"torch.device",
"numpy.array",
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.cuda.get_device_name",
"numpy.mean",
"torch.manual_seed",
"numpy.std",
"torch.cuda.is_available",
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"torch.utils.data.DataLoader"
]
] |
ivychill/reid | [
"6dc8a2ea21dfa8037d26a7184c86e2fb59e3ab9e"
] | [
"test.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom __future__ import print_function, division\n\nimport argparse\nimport torch\nimport torch.nn as nn\n# import torch.optim as optim\n# from torch.optim import lr_scheduler\nfrom torch.autograd import Variable\nimport torch.backends.cudnn as cudnn\nimport numpy as np\n# import torchvis... | [
[
"torch.nn.Sequential",
"torch.norm",
"torch.FloatTensor",
"torch.no_grad",
"torch.nn.functional.interpolate",
"torch.cuda.set_device",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.load",
"numpy.sqrt"
]
] |
JaneliaSciComp/exllsm-synapse-detector | [
"bb2683009fb18dfaea2743e15747f6bd86254940"
] | [
"training/ExLLSM_unet_performance_evaluate.py"
] | [
"from skimage.measure import label, regionprops\nimport numpy as np \nimport nrrd\nfrom skimage import io\n\n\ndef tif_read(file_name):\n \"\"\"\n read tif image in (rows,cols,slices) shape\n \"\"\"\n im = io.imread(file_name)\n im_array = np.zeros((im.shape[1],im.shape[2],im.shape[0]), dtype=im.dtyp... | [
[
"numpy.count_nonzero",
"numpy.zeros"
]
] |
Namir0806/FETILDA | [
"d4a3e720dccef3ba0221e6d59214e54a11c6fc5b",
"d4a3e720dccef3ba0221e6d59214e54a11c6fc5b",
"d4a3e720dccef3ba0221e6d59214e54a11c6fc5b"
] | [
"US-bank-experiments-source-code/unfreeze/finbert-original/max-4-1-hk-finbert-bilstm-hist-1.py",
"US-bank-experiments-source-code/unfreeze/finbert-original/finbert-max-3.py",
"US-bank-experiments-source-code/freeze/longformer-original/finbert-bilstm-1.py"
] | [
"from scipy import stats\nfrom sklearn.svm import SVR\nfrom sklearn.linear_model import LinearRegression\nimport os\nimport random\nimport sys\nimport csv\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.utils.data import TensorDataset, DataL... | [
[
"torch.nn.Linear",
"torch.nn.LSTM",
"torch.stack",
"torch.cuda.amp.autocast",
"torch.nn.LeakyReLU",
"pandas.read_csv",
"numpy.concatenate",
"tensorflow.random.set_seed",
"torch.manual_seed",
"torch.tensor",
"torch.device",
"numpy.array",
"torch.cuda.manual_seed_... |
AaratiAkkapeddi/nnabla-examples | [
"db9e5ad850303c158773aeb275e5c3821b4a3935",
"db9e5ad850303c158773aeb275e5c3821b4a3935"
] | [
"reinforcement_learning/dqn/atari_utils.py",
"image-translation/stargan/train.py"
] | [
"# Copyright 2019,2020,2021 Sony Corporation.\n# Copyright 2021 Sony Group 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/LICE... | [
[
"numpy.squeeze"
],
[
"numpy.random.permutation",
"numpy.random.randint"
]
] |
ahheo/climi | [
"d51d8faedb9bf1b6554733af469d15e1cffdc4e2"
] | [
"climi/pppp/plt_hwmi_map_evolution_obsVSmodel.py"
] | [
"import numpy as np\nimport matplotlib as mpl\nmpl.use('Agg', warn=False, force=True)\nimport matplotlib.pyplot as plt\nimport iris\nimport iris.plot as iplt\nimport os\nimport warnings\nimport logging\nfrom ffff import rPeriod_, schF_keys_\nfrom cccc import extract_period_cube, guessBnds_cube, load_res_, en_mm_, \... | [
[
"matplotlib.use",
"numpy.array",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"matplotlib.colors.BoundaryNorm",
"numpy.arange",
"matplotlib.colors.ListedColormap"
]
] |
iqbal-lab-org/paper_pandora2020_analyses | [
"952e348107c3fec60482bb30a91620ee2ce32cb5"
] | [
"scripts/csv_to_paper_plots/precision_recall/preprocess_20_way_nanopore_ROC.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport pandas as pd\n\n\n# In[2]:\n\nimport sys\ndf = pd.read_csv(sys.argv[1], sep=\"\\t\")\ndf\n\n\n# In[3]:\n\n\n# add some custom columns\ndf[\"tool_long_name\"] = df[\"tool\"]\n\ndef get_tool_category(tool):\n if tool == \"pandora_nanopore_nodenovo\":\... | [
[
"pandas.read_csv"
]
] |
amarczew/stacked-denoising-autoencoder | [
"64e4f62bffc9eb805f8569df0f92d14a7473a9bf"
] | [
"SdA/logistic_sgd.py"
] | [
"\"\"\"\nThis tutorial introduces logistic regression using Theano and stochastic\ngradient descent.\n\nLogistic regression is a probabilistic, linear classifier. It is parametrized\nby a weight matrix :math:`W` and a bias vector :math:`b`. Classification is\ndone by projecting data points onto a set of hyperplanes... | [
[
"numpy.mean",
"numpy.asarray",
"numpy.zeros"
]
] |
bigboyabhisthi/reaction-network | [
"b84f16b7261ecd62d7aa8e2681907f6ea0c35565"
] | [
"src/rxn_network/costs/softplus.py"
] | [
"\" Implementation of the softplus cost function\"\nfrom typing import List\n\nimport numpy as np\n\nfrom rxn_network.core import CostFunction\nfrom rxn_network.reactions import ComputedReaction\n\n\nclass Softplus(CostFunction):\n \"\"\"\n The softplus cost function is a smooth version of the Rectified Linea... | [
[
"numpy.array",
"numpy.dot",
"numpy.exp"
]
] |
ML-PSE/Machine_Learning_for_PSE | [
"b53578d7cc0e0eca4907527b188a60de06d6710e",
"b53578d7cc0e0eca4907527b188a60de06d6710e"
] | [
"Chapter_SupportVectorMachines/polymerPlantData_Softsensing_SVR.py",
"Chapter_LatentVariable2/DimensionalityReduction_FDA.py"
] | [
"##%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\r\n## SVR model with polymer plant data\r\n## %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\r\n\r\n#%% import required packages\r\nimport numpy as np\r\nimport matplotlib.pyplot a... | [
[
"matplotlib.pyplot.xlabel",
"sklearn.metrics.r2_score",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"numpy.loadtxt",
"sklearn.svm.SVR",
"matplotlib.pyplot.ylabel",
"sklearn.model_selection.GridSearchCV",
"numpy.linspace"
],
[
"sklearn.discriminant_analysis.Lin... |
nutalk/Image-coregistration-translation-rotation | [
"3aee41120f80b9ed17f996dd38ff7a828887fdba"
] | [
"demo_image_coregestration.py"
] | [
"'''\ndemo_image_coregestration.py\n\nCoregister two 2D (single channel) same size images differing by translation and rotation\n'''\n\nimport numpy as np\nimport matplotlib.image as mpimg \nimport matplotlib.pyplot as plt \nfrom utils.coreg_utils import ImageTranslate, ImageRotate\nfrom utils.translation_coreg_mut... | [
[
"numpy.random.normal",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.title",
"matplotlib.image.imread",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.imshow"
]
] |
Liang813/zhusuan | [
"4386b2a12ae4f4ed8e694e504e51d7dcdfd6f22a"
] | [
"zhusuan/distributions/utils.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nfrom __future__ import absolute_import\nfrom __future__ import division\n\nimport tensorflow as tf\nimport numpy as np\n\n\n__all__ = [\n 'log_combination',\n 'explicit_broadcast',\n 'maybe_explicit_broadcast',\n 'is_same_dynamic_shape',\n]\n\n\ndef log... | [
[
"tensorflow.rank",
"tensorflow.convert_to_tensor",
"tensorflow.shape",
"tensorflow.assert_rank",
"tensorflow.ones_like",
"tensorflow.constant",
"numpy.finfo",
"tensorflow.lgamma",
"tensorflow.control_dependencies",
"tensorflow.assert_rank_at_least",
"tensorflow.identity... |
dvoram/open_spiel | [
"aaff14f482acdcbe834e962abaebceca934e8095",
"aaff14f482acdcbe834e962abaebceca934e8095"
] | [
"open_spiel/python/algorithms/cfr.py",
"open_spiel/python/rl_environment.py"
] | [
"# Copyright 2019 DeepMind Technologies Ltd. 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 r... | [
[
"numpy.prod",
"numpy.zeros"
],
[
"numpy.random.RandomState"
]
] |
zhangzylogo/arrow | [
"e095ca5748e20cf81b6b8ddc128a916976e4cdea"
] | [
"python/pyarrow/tests/test_parquet.py"
] | [
"# -*- coding: utf-8 -*-\n# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.... | [
[
"pandas.to_datetime",
"numpy.array",
"pandas.util.testing.assert_frame_equal",
"pandas.DatetimeIndex",
"numpy.random.seed",
"pandas.DataFrame",
"pandas.date_range",
"numpy.ones",
"numpy.random.randn",
"pandas.util.testing.rands",
"pandas.Categorical.from_codes",
"pa... |
isabella232/tensorboard | [
"77cf61f74dd57e4f3a6256e3972335bbd82feb51"
] | [
"tensorboard/data/provider_test.py"
] | [
"# Copyright 2019 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 requir... | [
[
"numpy.array"
]
] |
czhongyu/information-extraction | [
"6cf9905bed5ee9c33706854cd6ceae04194aa5e4"
] | [
"pytorch/classification/rcnn/model.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\n\n \nclass RCNN(nn.Module):\n def __init__(self, vocab_size, embed_dim, output_dim, hidden_dim, num_layers, dropout, weight):\n super(RCNN, self).__init__()\n self.embedding = nn.Embedding... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.cat",
"torch.nn.LSTM",
"torch.from_numpy",
"torch.nn.Embedding"
]
] |
PiCEulHer/interpret | [
"3d69de83bbf6f1bd22e686406b0895689ea2047d"
] | [
"python/interpret-core/interpret/glassbox/ebm/test/test_internal.py"
] | [
"# Copyright (c) 2019 Microsoft Corporation\n# Distributed under the MIT software license\n\nfrom ..internal import Native, Booster\n\nimport numpy as np\nimport ctypes as ct\nfrom contextlib import closing\n\ndef test_booster_internals():\n with Booster(\n model_type=\"classification\",\n n_classe... | [
[
"numpy.concatenate",
"numpy.histogram",
"numpy.array",
"numpy.array_equal",
"numpy.random.seed",
"numpy.sum",
"numpy.nanmin",
"numpy.random.random_sample",
"numpy.allclose",
"numpy.arange",
"numpy.nanmax"
]
] |
GregorySchwing/wolfCalibration | [
"9ff7ca7f0d144da407c14f0f4e9a202c4691de2d"
] | [
"validation/Free_Energy/signac/project.py"
] | [
"\"\"\"GOMC's setup for signac, signac-flow, signac-dashboard for this study.\"\"\"\n# project.py\n\n\nimport flow\n# from flow.environment import StandardEnvironment\nimport mbuild as mb\nimport mbuild.formats.charmm_writer as mf_charmm\nimport mbuild.formats.gomc_conf_writer as gomc_control\nimport numpy as np\n\... | [
[
"numpy.round",
"pandas.DataFrame",
"numpy.mean",
"numpy.std",
"pandas.read_csv"
]
] |
csc-training/geocomputing | [
"1e8043c864fb663526d1c15cfd3bb390a1379181"
] | [
"machineLearning/04_cnn_solaris/08_1_train.py"
] | [
"import solaris as sol\nimport torch\nimport rasterio\nimport rasterio.merge\nimport pandas as pd\nimport time\nimport os\nfrom PredictSpruceForestsModel import PredictSpruceForestsModel\nimport sys\n\n### The first (and only) input argument for this script is the folder where data exists\nif len(sys.argv) != 2:\n ... | [
[
"pandas.DataFrame",
"torch.cuda.is_available",
"torch.cuda.get_device_name"
]
] |
malexmad/League-Of-Legend-App | [
"94b6957d462ee29f5536112af39c04093faa92b7"
] | [
"pages/predictions.py"
] | [
"import dash\nimport dash_bootstrap_components as dbc\nimport dash_core_components as dcc\nimport dash_html_components as html\nfrom dash.dependencies import Input, Output\nfrom joblib import load\npipe2 = load('assets/pipe2.joblib')\n\nfrom app import app\nCHANGE_COLOR = {'color': 'black',}\n\n\ncolumn1 = dbc.Col(... | [
[
"pandas.DataFrame"
]
] |
Dongfang1021/Python_data_analysis_notebook | [
"210c8bbe1b17736e639bbdbcae19df795fb702d5",
"210c8bbe1b17736e639bbdbcae19df795fb702d5",
"210c8bbe1b17736e639bbdbcae19df795fb702d5"
] | [
"Python-Data-Cleaning-Cookbook-master/3_TakingMeasureOfData/5. stats_continuous.py",
"Python-Data-Cleaning-Cookbook-master/7_Aggregating/4. groupby_more.py",
"Python-Data-Cleaning-Cookbook-master/5._Visualization/5. scatter_plots.py"
] | [
"# import pandas, numpy, and matplotlib\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\npd.set_option('display.width', 75)\npd.set_option('display.max_columns', 7)\npd.set_option('display.max_rows', 20)\npd.options.display.float_format = '{:,.2f}'.format\ncovidtotals = pd.read_pickle(\"da... | [
[
"pandas.read_pickle",
"pandas.set_option",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.hist",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
],
[
"pandas.read_pickle",
"pandas.set_option"
],
[
"pandas.read_pick... |
zarahz/MARL-and-Markets | [
"3591a160e098e7251b9e7c7b59c6d0ab08ba0779"
] | [
"Coloring/learning/utils/agent.py"
] | [
"from learning.dqn.model import DQNModel\nfrom learning.ppo.model import ACModel\n\nimport torch\n\nfrom learning.utils.storage import get_model_state\nfrom learning.utils.format import get_obss_preprocessor\n\n\nclass Agent:\n \"\"\"An agent - It is able to choose an action given an observation for visualizatio... | [
[
"torch.no_grad"
]
] |
dervischooch/face-id-with-medical-masks | [
"4f5f0cd696d7ea3e6d627592c5378d451bf82b26"
] | [
"masked_face_sdk/crop_utils.py"
] | [
"import numpy as np\n\n\ndef create_square_crop_by_detection(frame: np.ndarray, box: list) -> np.ndarray:\n \"\"\"\n Rebuild detection box to square shape\n Args:\n frame: rgb image in np.uint8 format\n box: list with follow structure: [x1, y1, x2, y2]\n Returns:\n Image crop by box... | [
[
"numpy.pad"
]
] |
xing-lab-pitt/dynamo-release | [
"76c1f2a270dd6722b88f4700aac1a1a725a0c261",
"76c1f2a270dd6722b88f4700aac1a1a725a0c261"
] | [
"dynamo/plot/preprocess.py",
"dynamo/estimation/tsc/twostep.py"
] | [
"import numpy as np\nimport pandas as pd\nfrom scipy.sparse import issparse, csr_matrix\nfrom anndata import AnnData\nfrom typing import Optional, Union, Sequence\nimport matplotlib\nfrom matplotlib.axes import Axes\n\nfrom ..preprocessing import preprocess as pp\nfrom ..preprocessing.preprocess_monocle_utils impor... | [
[
"numpy.sign",
"numpy.where",
"numpy.sort",
"numpy.cumsum",
"pandas.DataFrame",
"matplotlib.pyplot.subplots",
"numpy.nanmin",
"numpy.log1p",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"numpy.isfinite",
"numpy.nanmax",
"matplotlib.pyplot.yscale",
"scipy... |
shushu-qin/deeponet | [
"5bbe066279bba055ad80e04c364140363c87634a"
] | [
"seq2seq/learner/integrator/hamiltonian/stormer_verlet.py"
] | [
"\"\"\"\r\n@author: jpzxshi\r\n\"\"\"\r\nimport numpy as np\r\nimport torch\r\n\r\nfrom ...utils import grad\r\n\r\nclass SV:\r\n '''Stormer-Verlet scheme.\r\n '''\r\n def __init__(self, H, dH, iterations=10, order=4, N=1):\r\n '''\r\n H: H(x) or None\r\n dH: dp,dq=dH(p,q) or None\r\n ... | [
[
"numpy.hstack",
"torch.cat"
]
] |
akhilvasvani/machinelearningbasics | [
"5d1a05add8b6b316011cb3e1db4144940161e2b3"
] | [
"supervised_learning/examples/adaboost.py"
] | [
"from __future__ import division, print_function\nimport numpy as np\nfrom sklearn import datasets\n\n# Import helper functions\nfrom mlfromscratch.supervised_learning import Adaboost\nfrom mlfromscratch.utils.data_manipulation import train_test_split\nfrom mlfromscratch.utils.data_operation import accuracy_score\n... | [
[
"numpy.where",
"sklearn.datasets.load_digits"
]
] |
shraddhazpy/keras | [
"21a78464c191c40a90ed4e3ddfed747ae994703e",
"21a78464c191c40a90ed4e3ddfed747ae994703e",
"21a78464c191c40a90ed4e3ddfed747ae994703e",
"21a78464c191c40a90ed4e3ddfed747ae994703e"
] | [
"keras/tests/integration_test.py",
"keras/preprocessing/image_test.py",
"keras/mixed_precision/model_test.py",
"keras/engine/keras_tensor_test.py"
] | [
"# Copyright 2016 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"numpy.random.seed",
"tensorflow.compat.v2.executing_eagerly",
"tensorflow.compat.v2.test.main"
],
[
"numpy.zeros_like",
"numpy.random.rand",
"numpy.copy",
"tensorflow.compat.v2.data.Dataset.from_tensor_slices",
"numpy.arange",
"numpy.random.random",
"numpy.vstack",
... |
ramiro050/pytorch | [
"dc4f12d9cc15476c545e3a1bb7a74e23d5b0ddf5"
] | [
"test/test_nn.py"
] | [
"# Owner(s): [\"module: nn\"]\n\nimport contextlib\nimport math\nimport random\nimport string\nimport unittest\nimport io\nimport unittest.mock as mock\nimport itertools\nimport warnings\nimport pickle\nfrom copy import deepcopy\nfrom itertools import repeat, product\nfrom functools import reduce, partial\nfrom ope... | [
[
"torch.nn.functional.softshrink",
"torch._nnpack_spatial_convolution",
"torch.nn.SmoothL1Loss",
"torch.nn.functional.adaptive_avg_pool1d",
"torch.nn.functional.fractional_max_pool3d",
"numpy.random.random",
"torch.nan_to_num",
"torch.nn.init.normal_",
"torch._C._select_conv_bac... |
denneb1/pylayers | [
"6aaa06175061a9120044c955b44e9168e9c7ee36",
"6aaa06175061a9120044c955b44e9168e9c7ee36"
] | [
"pylayers/location/geometric/constraints/tdoa.py",
"pylayers/antprop/rays.py"
] | [
"\"\"\"\n\n.. autoclass:: TDOA\n :members:\n\n\"\"\"\n# -*- coding:Utf-8 -*-\n#####################################################################\n#This file is part of RGPA.\n\n#Foobar is free software: you can redistribute it and/or modify\n#it under the terms of the GNU General Public License as published ... | [
[
"numpy.max",
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.sum",
"numpy.min",
"numpy.exp",
"numpy.shape",
"numpy.sqrt",
"numpy.abs",
"numpy.cross",
"numpy.vstack"
],
[
"numpy.arccos",
"numpy.dot",
"numpy.where",
"numpy.sort",
"numpy.cos",... |
ikostina/openvino_training_extensions | [
"b320b41ecf6b8b4952f59c6e1d7eb5148a7149ee"
] | [
"tensorflow_toolkit/vehicle_attributes/infer_ie.py"
] | [
"from __future__ import print_function\nimport sys\nimport os\nfrom argparse import ArgumentParser\nimport logging as log\nimport numpy as np\nimport cv2\n\nfrom openvino.inference_engine import IENetwork, IEPlugin\n\ndef normalized_to_absolute(prediction):\n colorcar = np.zeros((1, 1, 3), dtype=np.uint8)\n for i... | [
[
"numpy.argmax",
"numpy.zeros"
]
] |
OolongQian/SimpleView | [
"4eb0d2518de94ed095d3398223df0dba487d7841"
] | [
"ScanObjectNN/SpiderCNN/draw_cmat.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport argparse\nimport socket\nimport importlib\nimport time\nimport os\nimport scipy.misc\nimport sys\nBASE_DIR = os.path.dirname(os.path.abspath(__file__))\nROOT_DIR = BASE_DIR\nsys.path.append(BASE_DIR)\nsys.path.append(os.path.join(BASE_DIR, 'models'))\nsys.path.ap... | [
[
"sklearn.metrics.confusion_matrix",
"matplotlib.pyplot.xticks",
"numpy.nan_to_num",
"tensorflow.train.Saver",
"tensorflow.ConfigProto",
"numpy.argmax",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.subplot",
"numpy.array",
"numpy.zeros",
"tensorflow.Session",
... |
XuezheMax/apollo | [
"852991fd769f80689415abee8653c0a5eedbab40"
] | [
"language_model/train_1bw.py"
] | [
"import os\nimport sys\n\ncurrent_path = os.path.dirname(os.path.realpath(__file__))\nroot_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))\nsys.path.append(root_path)\n\nimport argparse\nimport random\nimport pickle\nimport math\nimport json\nimport numpy as np\nimport torch\nfrom utils import c... | [
[
"torch.device",
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.no_grad",
"torch.optim.SGD",
"torch.optim.Adam",
"torch.optim.lr_scheduler.MultiStepLR",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.cuda.is_available",
"torch.load"
]
] |
edbeeching/transformers | [
"b18dfd95e1f60ae65a959a7b255fc06522170d1b"
] | [
"examples/pytorch/translation/run_translation.py"
] | [
"#!/usr/bin/env python\n# coding=utf-8\n# Copyright The HuggingFace Team and The HuggingFace Inc. team. 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# ... | [
[
"numpy.where",
"numpy.count_nonzero",
"numpy.mean"
]
] |
kimbyeolhee/ML-DL-Algorithms-Study | [
"c8fb919083707dc43d400da35a4d176cc3af56fe"
] | [
"ML/Naive Bayes/naive bayes implementaion/dataset.py"
] | [
"import pandas as pd\r\n\r\ndef load_data():\r\n training_sentences = [[], []]\r\n\r\n # 데이터 로드 및 Na값 제거\r\n df = pd.read_csv('./ratings.txt', header=0, delimiter='\\t')\r\n df = df.dropna(axis=0)\r\n df.reset_index(drop=True, inplace=True)\r\n\r\n for i in range(len(df)):\r\n if df['label'... | [
[
"pandas.read_csv"
]
] |
DeepanshS/csdmpy | [
"bd4e138b10694491113b10177a89305697f1752c"
] | [
"tests/numpy_wrapper/dimension_reduction_test.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Test for the csdm object\n 1) sum, mean, var, std, prod.\n\"\"\"\nimport numpy as np\nimport pytest\n\nimport csdmpy as cp\n\ndata = np.random.rand(50 * 15).reshape(15, 5, 10)\na = cp.new()\n\ndim = [\n {\"type\": \"linear\", \"count\": 10, \"increment\": \"1\"},\n {\"type\"... | [
[
"numpy.sum",
"numpy.random.rand"
]
] |
CCHiggins/statsmodels | [
"300b6fba90c65c8e94b4f83e04f7ae1b0ceeac2e",
"300b6fba90c65c8e94b4f83e04f7ae1b0ceeac2e",
"300b6fba90c65c8e94b4f83e04f7ae1b0ceeac2e"
] | [
"examples/python/statespace_arma_0.py",
"statsmodels/discrete/count_model.py",
"docs/source/plots/graphics_functional_fboxplot.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# DO NOT EDIT\n# Autogenerated from the notebook statespace_arma_0.ipynb.\n# Edit the notebook and then sync the output with this file.\n#\n# flake8: noqa\n# DO NOT EDIT\n\n# # Autoregressive Moving Average (ARMA): Sunspots data\n\n# This notebook replicates the existing A... | [
[
"scipy.stats.normaltest",
"pandas.DataFrame",
"pandas.date_range",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure"
],
[
"numpy.max",
"numpy.nextafter",
"numpy.zeros_like",
"numpy.dot",
"numpy.triu_indices",
"numpy.asarray",
... |
bradyrx/xskillscore | [
"6521f9d114edf012a2829e5ac7f423190bb8de4a"
] | [
"xskillscore/tests/test_mask_skipna.py"
] | [
"import numpy as np\nimport pytest\nimport xarray as xr\n\nfrom xskillscore.core.deterministic import (\n mae,\n mape,\n median_absolute_error,\n mse,\n pearson_r,\n pearson_r_p_value,\n r2,\n rmse,\n smape,\n spearman_r,\n spearman_r_p_value,\n)\n\n# Should only have masking issues... | [
[
"numpy.isnan",
"numpy.arange",
"numpy.random.rand"
]
] |
mmabadal/dgcnn | [
"bb2e4c23917c9b47ee96519baeef1d25b6c2cdf0"
] | [
"sem_seg/indoor3d_util.py"
] | [
"import numpy as np\nimport glob\nimport os\nimport sys\n\n\n\ndef get_info_classes(cls_path):\n\n classes = []\n colors = []\n\n for line in open(cls_path):\n data = line.split()\n classes.append(data[0])\n colors.append([int(data[1]), int(data[2]), int(data[3])])\n\n labels = {cls... | [
[
"numpy.concatenate",
"numpy.max",
"numpy.array",
"numpy.ceil",
"numpy.random.choice",
"numpy.zeros",
"numpy.sum",
"numpy.ones",
"numpy.load",
"numpy.random.shuffle",
"numpy.save",
"numpy.loadtxt",
"numpy.arange",
"numpy.amax",
"numpy.random.uniform",
... |
mirrorcoloured/slcypi | [
"c47975b3523f770d12a521c82e2dfca181e3f35b"
] | [
"MA/ImageAnalysis.py"
] | [
"\n# Import statements\n#import pygame\n#import pygame.camera\n#from PIL import Image\nimport cv2\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nclass ImageAnalysis():\n \"\"\"Class with methods for image analysis\"\"\"\n\n def __init__(self):\n \"\"\"Initialize method\"\"\"\n ... | [
[
"numpy.sum",
"numpy.array",
"numpy.ones"
]
] |
longhuang318/mobile_robot_rl | [
"8f1755be4856f1be8994dd5a156b4278960e6d46"
] | [
"mobile_robot_rl/networks/models.py"
] | [
"from copy import deepcopy\nfrom typing import Callable\nfrom typing import Optional\nfrom typing import Tuple\nfrom typing import Union\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom mobile_robot_rl.networks.heads import DeterministicPolicyHead\nfrom mobile_robot_rl.networks.heads ... | [
[
"torch.rand",
"torch.nn.functional.softmax"
]
] |
tlambert03/pycuda-affine | [
"b815aaa49e4ac55417f9b4916fb4effbad699ab8"
] | [
"pycuda_transforms/transform.py"
] | [
"import pycuda.autoinit # noqa\nfrom pycuda.compiler import SourceModule\nimport pycuda.driver as cuda\nfrom pycuda import gpuarray\nimport numpy as np\nimport os\nfrom functools import wraps\n\ncubic_dir = os.path.join(os.path.dirname(__file__), \"cubic\")\nwith open(__file__.replace(\".py\", \".cu\"), \"r\") as ... | [
[
"numpy.sin",
"numpy.array",
"numpy.ascontiguousarray",
"numpy.isfortran",
"numpy.eye",
"numpy.cos",
"numpy.int32"
]
] |
albarqounilab/MONAI | [
"d4d173362b71a9af6c5414db591994f799e4fd2c",
"bb0b307d68021a243011a58fd82a1d275f00a51a"
] | [
"monai/networks/nets/resnet.py",
"tests/test_compute_roc_auc.py"
] | [
"# Copyright 2020 - 2021 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 agre... | [
[
"torch.nn.Linear",
"torch.nn.functional.avg_pool3d",
"torch.cat",
"torch.nn.Sequential",
"torch.nn.ReLU",
"torch.as_tensor"
],
[
"numpy.testing.assert_allclose",
"torch.tensor"
]
] |
mohsinkhn/tpu | [
"d90362f8b42432763f45d57f541390bc46cd703d",
"d90362f8b42432763f45d57f541390bc46cd703d",
"d90362f8b42432763f45d57f541390bc46cd703d"
] | [
"models/official/retinanet/retinanet_main.py",
"models/experimental/show_and_tell/show_and_tell_tpu_test.py",
"models/experimental/mask_rcnn/box_utils.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.logging.set_verbosity",
"numpy.array",
"tensorflow.contrib.tpu.TPUConfig",
"tensorflow.contrib.tpu.TPUEstimator",
"tensorflow.image.convert_image_dtype",
"tensorflow.logging.info",
"tensorflow.reshape",
"tensorflow.map_fn",
"tensorflow.Session.reset",
"tensorflo... |
WilliamJamieson/astropy-benchmarks | [
"dcff9e1d8a584f7933743a91682806647a4c1e86"
] | [
"benchmarks/units.py"
] | [
"import copy\n\nimport numpy as np\nfrom astropy import units as u\n\n\n# Unit tests\n\ndef time_unit_compose():\n u.Ry.compose()\n\n\ndef time_unit_to():\n u.m.to(u.pc)\n\n\ndef time_unit_parse():\n u.Unit('1e-07 kg m2 / s2')\n\n\ndef time_simple_unit_parse():\n u.Unit('1 d')\n\n\ndef time_very_simple_... | [
[
"numpy.equal",
"numpy.array",
"numpy.sin",
"numpy.add",
"numpy.asarray",
"numpy.true_divide",
"numpy.multiply",
"numpy.subtract",
"numpy.arange",
"numpy.power",
"numpy.sqrt"
]
] |
lorenzocestaro/pandas | [
"a73e4518cf3d10fd239cdbd1be3bcda43443bf2a"
] | [
"pandas/tseries/period.py"
] | [
"# pylint: disable=E1101,E1103,W0232\nfrom datetime import datetime, timedelta\nimport numpy as np\nimport warnings\n\n\nfrom pandas.core import common as com\nfrom pandas.types.common import (is_integer,\n is_float,\n is_object_dtype,\n ... | [
[
"numpy.repeat",
"pandas.tseries.index.Int64Index",
"pandas.core.common._values_from_object",
"pandas._libs.period.period_ordinal",
"pandas._libs.period.period_asfreq_arr",
"pandas._libs.period._validate_end_alias",
"pandas.tseries.base.DatetimeIndexOpsMixin._convert_tolerance",
"pa... |
salt-die/nurses | [
"68fc12bfed7af7fedb0e45d5215ff922ee981f6b"
] | [
"nurses/widgets/array_win.py"
] | [
"import curses\n\nimport numpy as np\n\nfrom .widget import Widget, BORDER_STYLES\n\n\nclass ArrayWin(Widget):\n \"\"\"\n A Widget whose state is stored an a numpy array and whose __getitem__ / __setitem__ use numpy indexing to update text.\n\n Other Parameters\n ----------------\n border: optional\n... | [
[
"numpy.full",
"numpy.nditer",
"numpy.roll"
]
] |
salkaevruslan/sosed | [
"fa948fd339ff3ff08eea1ca3afb5884e63c6e5f3"
] | [
"sosed_test/test_data_processing.py"
] | [
"import unittest\nimport os\nimport numpy as np\n\nfrom pathlib import Path\nfrom collections import Counter\nfrom unittest.mock import patch\n\nfrom sosed.data_processing import *\n\n\nclass ProcessedDataTest(unittest.TestCase):\n\n @classmethod\n def setUpClass(cls):\n cls.actual_index = [0, 1]\n ... | [
[
"numpy.linalg.norm",
"numpy.random.randn",
"numpy.save",
"numpy.arange",
"numpy.all",
"numpy.random.random"
]
] |
jdtuck/scikit-fda | [
"28259dffbc45dfc8dbf3c12839b928f9df200351",
"28259dffbc45dfc8dbf3c12839b928f9df200351",
"28259dffbc45dfc8dbf3c12839b928f9df200351",
"28259dffbc45dfc8dbf3c12839b928f9df200351",
"28259dffbc45dfc8dbf3c12839b928f9df200351"
] | [
"skfda/representation/basis/_basis.py",
"examples/plot_explore.py",
"skfda/representation/interpolation.py",
"examples/plot_boxplot.py",
"skfda/preprocessing/registration/elastic.py"
] | [
"\"\"\"Module for functional data manipulation in a basis system.\n\nDefines functional data object in a basis function system representation and\nthe corresponding basis classes.\n\n\"\"\"\nfrom abc import ABC, abstractmethod\nimport copy\nimport warnings\n\nimport numpy as np\n\nfrom ..._utils import (_domain_ran... | [
[
"numpy.identity",
"numpy.array",
"numpy.atleast_2d"
],
[
"numpy.full",
"numpy.asarray"
],
[
"numpy.zeros_like",
"numpy.empty",
"scipy.interpolate.UnivariateSpline",
"scipy.interpolate.RectBivariateSpline",
"scipy.interpolate.PchipInterpolator",
"numpy.apply_alon... |
SeolhwaLee/DialoGPT | [
"45220d493e8d267d703a7abca0497753cc4cda6c"
] | [
"interact_dbdc.py"
] | [
"import json\nfrom os.path import abspath, dirname, exists, join\nimport argparse\nimport logging\nfrom tqdm import trange\nimport tqdm\nimport torch\nimport torch.nn.functional as F\nimport numpy as np\nimport socket\nimport os, sys\nimport re\nimport logging\nfrom functools import partial\nfrom demo_utils import ... | [
[
"torch.cat",
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.no_grad",
"torch.cuda.device_count",
"torch.random.manual_seed",
"torch.multinomial",
"torch.cuda.is_available",
"torch.tensor",
"torch.nn.functional.softmax",
"torch.sort",
"torch.topk"
]
] |
uashogeschoolutrecht/bbmd | [
"40a5beb0554df00b512e672bf5be8297d0523b9b"
] | [
"bbmd/bmr/base.py"
] | [
"import re\n\nimport numpy as np\nimport scipy.special as special\nfrom scipy import stats\n\nfrom ..utils import get1Dkernel, get_summary_stats\n\n\nclass BMRBase(object):\n\n def clear_results(self):\n self.results = None\n self.model_average = None\n\n def _set_priors(self, priors):\n ... | [
[
"numpy.array",
"numpy.isnan",
"numpy.empty",
"numpy.log",
"scipy.special.erfinv",
"numpy.sqrt"
]
] |
lamfeeling/Stein-Density-Ratio-Estimation | [
"f3b8a3975d99ace5875e603414e0e6d989ceb1d6"
] | [
"examples/nn_MNIST/demo_NN_KSD.py"
] | [
"from sdre.helper import *\r\nfrom scipy.optimize import minimize, Bounds, NonlinearConstraint\r\nfrom multiprocessing import Pool\r\nfrom socket import gethostname\r\nfrom time import time\r\nfrom sdre.trainnn import lastlayer\r\nfrom kgof.kernel import KGauss\r\nimport kgof.util as util\r\nfrom scipy import io as... | [
[
"scipy.optimize.minimize",
"scipy.io.savemat"
]
] |
www2171668/alf | [
"6e3731fc559d3b4e6b5b9ed6251fff728a560d64",
"6e3731fc559d3b4e6b5b9ed6251fff728a560d64",
"6e3731fc559d3b4e6b5b9ed6251fff728a560d64",
"6e3731fc559d3b4e6b5b9ed6251fff728a560d64"
] | [
"alf/algorithms/ppo_loss.py",
"alf/algorithms/actor_critic_loss.py",
"alf/experience_replayers/replay_buffer_test.py",
"alf/optimizers/optimizers.py"
] | [
"# Copyright (c) 2019 Horizon Robotics. 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 requi... | [
[
"torch.isfinite",
"torch.max"
],
[
"torch.var",
"torch.sqrt",
"torch.clamp",
"numpy.prod",
"torch.tensor"
],
[
"torch.rand",
"torch.cat",
"torch.nonzero",
"torch.min",
"torch.arange",
"torch.gather",
"torch.manual_seed",
"torch.all",
"torch.t... |
zhaodongsun/pnp_dip | [
"f8f3802af8c607b3063fc7b92e20729f148d36c1"
] | [
"experiments/superresolution/batch_DIP_TV_subgrad.py"
] | [
"import os\n# os.environ['CUDA_VISIBLE_DEVICES'] = '1'\nos.chdir(os.path.dirname(os.path.abspath(__file__)))\n\nimport numpy as np\nimport torch\nfrom skimage.metrics import peak_signal_noise_ratio\nfrom matplotlib.pyplot import imread, imsave\nfrom skimage.transform import resize\nimport time\nimport sys\nimport g... | [
[
"matplotlib.pyplot.imsave",
"torch.from_numpy",
"torch.abs",
"torch.cuda.is_available",
"numpy.savez",
"torch.zeros_like",
"torch.randn",
"matplotlib.pyplot.imread"
]
] |
aimuch/AIEnvConfig | [
"4ccd54e9c601e8c91efebcec1a50115d75d0cf96"
] | [
"src/tensorrt/tensorrt-4.0.1.6/examples-python/resnet_as_a_service/resnet_as_a_service.py"
] | [
"#\n# Copyright 1993-2018 NVIDIA Corporation. All rights reserved.\n#\n# NOTICE TO LICENSEE:\n#\n# This source code and/or documentation (\"Licensed Deliverables\") are\n# subject to NVIDIA intellectual property rights under U.S. and\n# international Copyright laws.\n#\n# These Licensed Deliverables contained here... | [
[
"numpy.argmax",
"numpy.argsort",
"numpy.argpartition"
]
] |
yecharlie/convnet3d | [
"0b2771eec149b196ef59b58d09eef71c9b201d40"
] | [
"tests/utils/test_nms.py"
] | [
"import numpy as np\nfrom numpy.testing import assert_array_equal\n\nfrom convnet3d.utils.nms import nmsOverlaps\nfrom convnet3d.utils.annotations import computeOverlaps\n\n\ndef test_nms_overlaps():\n boxes = np.array([\n [0, 2, 0, 2, 0, 2], # suppressed\n [0, 2, 0, 2, 0, 2],\n [2, 5, 2... | [
[
"numpy.array",
"numpy.testing.assert_array_equal"
]
] |
kcetskcaz/stylize-datasets | [
"715dc571fb01d9cec4e2a68b7f7f38f2b9a945a6"
] | [
"stylize.py"
] | [
"#!/usr/bin/env python\nimport argparse\nfrom function import adaptive_instance_normalization\nimport net\nfrom pathlib import Path\nfrom PIL import Image\nimport random\nimport torch\nimport torch.nn as nn\nimport torchvision.transforms\nfrom torchvision.utils import save_image\nfrom tqdm import tqdm\nimport numpy... | [
[
"numpy.uint8",
"numpy.array",
"torch.no_grad",
"torch.cuda.is_available",
"torch.load"
]
] |
JinHai-CN/cudf | [
"fd17f2d4cabe86e11e7f172b5b5903bdd5604d81",
"fd17f2d4cabe86e11e7f172b5b5903bdd5604d81"
] | [
"python/cudf/_gdf.py",
"python/cudf/tests/test_replace.py"
] | [
"# Copyright (c) 2018, NVIDIA CORPORATION.\n\n\"\"\"\nThis file provide binding to the libgdf library.\n\"\"\"\nimport contextlib\nimport itertools\n\nimport numpy as np\nimport pandas as pd\nimport pyarrow as pa\n\nfrom libgdf_cffi import ffi, libgdf\nfrom librmm_cffi import librmm as rmm\nimport nvcategory\n\nfro... | [
[
"pandas.api.types.is_categorical_dtype",
"numpy.dtype",
"numpy.require"
],
[
"numpy.array",
"pandas.Timedelta",
"numpy.testing.assert_equal",
"pandas.DataFrame",
"pandas.date_range",
"pandas.Timestamp",
"numpy.random.randint",
"pandas.Series"
]
] |
shub659/StressNet-Detecting-stress-from-thermal-videos | [
"89a06014ba2c456482d1d427cbac0171e477492a"
] | [
"isti_predictor/visualizer/visualizer.py"
] | [
"import numpy as np\nimport cv2\nimport torch\nimport os\nimport sys\nimport random\nimport torch.nn as nn\nimport torch.utils.data as tdata\nimport glob\nfrom matplotlib import pyplot as plt\n\nsys.path.append(\".\")\nfrom visualizer_dataloader import thermaldataset\n\n\ndef visualize(data_sample):\n\tdata = data_... | [
[
"matplotlib.pyplot.close",
"torch.utils.data.DataLoader",
"matplotlib.pyplot.subplots"
]
] |
knaidoo29/magpie | [
"efab3c2666aab2c928ca12a631758bc1b43c149c"
] | [
"magpie/randoms/polar.py"
] | [
"import numpy as np\n\n\ndef randoms_polar(size, r_min=0., r_max=1., phi_min=0., phi_max=2.*np.pi):\n \"\"\"Generates randoms for polar coordinates. Default will produce randoms within\n a unit circle. This can be specified to a ring segment, i.e. with inner radius\n r_min and outer radius r_max and specif... | [
[
"numpy.sqrt",
"numpy.random.random_sample"
]
] |
pranaymethuku/models | [
"7bb793554ef39ab06513138cc9e6be5eb3144bc6"
] | [
"research/object_detection/pre_training_scripts/xml_to_csv.py"
] | [
"\"\"\"\nCreated on Sun Apr 5 2020\n@author: Ruksana Kabealo, Pranay Methuku, Abirami Senthilvelan, Malay Shah\n\nClass: CSE 5915 - Information Systems\nSection: 6pm TR, Spring 2020\nProf: Prof. Jayanti\n\nA Python 3 script to perform the following tasks in order:\n 1) look at source directory, \n 2) extract ... | [
[
"pandas.DataFrame"
]
] |
Thehunk1206/Classical-ML-Algorithms | [
"93704dc4e5e6afdbec2ae0032a86cc6eaef05432"
] | [
"Kmeans/kmeans.py"
] | [
"from typing import List\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits import mplot3d\nfrom sklearn.datasets import make_blobs, make_classification, make_swiss_roll, make_moons \n\nimport sys\n\n# Create a class for k-means clustering algorithm\nclass KMeansClustering(object):\n def __... | [
[
"numpy.array",
"sklearn.datasets.make_blobs",
"numpy.zeros",
"numpy.random.seed",
"numpy.sum",
"numpy.mean",
"matplotlib.pyplot.show",
"numpy.argmax",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.axes"
]
] |
rustatian/ml_samples | [
"688e8b73db62105e62bc8c690f02ae03b4a3abfa"
] | [
"Tools/freeze_session_converter.py"
] | [
"import tensorflow as tf\nfrom keras import backend as K\nfrom keras.models import load_model\n\n\ndef freeze_session(session, keep_var_names=None, output_names=None, clear_devices=True):\n \"\"\"\n Freezes the state of a session into a prunned computation graph.\n\n Creates a new computation graph where v... | [
[
"tensorflow.python.framework.graph_util.convert_variables_to_constants",
"tensorflow.global_variables",
"tensorflow.train.write_graph"
]
] |
uct-cbio/cbio_proteomics | [
"a62ff04bd052dfd0dd312153ccf05c545b7dfcdb"
] | [
"bin/python/mq_blast_orfs2refproteome.py"
] | [
"#!/usr/bin/env python3\n\nimport pandas as pd\nimport numpy as np\nimport pandas as pd\nimport sys\nimport importlib.machinery\nimport Bio; from Bio import SeqIO\nimport os\nimport shutil\nfrom collections import defaultdict\nfrom Bio.SeqRecord import SeqRecord\nfrom Bio.Seq import Seq\nfrom Bio.Seq import transla... | [
[
"pandas.read_csv"
]
] |
dasUtsav/face-detect-disrupt | [
"f4b9734e755642dfcfdc20046b770925990b0314"
] | [
"example.py"
] | [
"import torch\nimport torchvision\nimport torchvision.transforms as transforms\nimport torchvision.utils as vutils\nfrom torch.autograd import Variable\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nimport torch.backends.cudnn as cudnn\nfrom models.vgg import VGG\nfrom models.... | [
[
"torch.max",
"pandas.DataFrame",
"torch.cuda.device_count",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.load",
"torch.nn.CrossEntropyLoss"
]
] |
yunjung-lee/class_python_data | [
"67ceab73e67ec63d408894a6ab016a8d25a4e30b"
] | [
"day05_tmp.py"
] | [
"#이미지 영역 지정\n\nimport scipy as sp\nimport numpy as np\nimport scipy.ndimage\nimport matplotlib.pyplot as plt\n\ndef flood_fill(test_array,h_max=255):\n input_array = np.copy(test_array)\n el = sp.ndimage.generate_binary_structure(2,2).astype(np.int)\n inside_mask = sp.ndimage.binary_erosion(~np.isnan(input... | [
[
"numpy.isnan",
"numpy.array_equal",
"numpy.copy",
"scipy.ndimage.generate_binary_structure",
"scipy.ndimage.grey_erosion",
"matplotlib.pyplot.imread",
"matplotlib.pyplot.imshow"
]
] |
Anirudh-Swaminathan/3d_euclidean_planning | [
"95e8cb52233ce87d36553942f66f5acc32d4c605"
] | [
"src/main_ompl.py"
] | [
"#!/usr/bin/python\n\n# Created by anicodebreaker on May 14, 2020\nimport OMPLPlanner\nfrom pathlib import Path\nimport numpy as np\nimport time\nimport matplotlib.pyplot as plt\n\nplt.ion()\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom mpl_toolkits.mplot3d.art3d import Poly3DCollection\nfrom pyrr import aabb\n\n\... | [
[
"numpy.array",
"matplotlib.pyplot.ion",
"numpy.zeros",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure",
"numpy.loadtxt",
"matplotlib.pyplot.show",
"numpy.vstack"
]
] |
PipGrylls/r-test | [
"5a307f0e9018bcdaf1a745b346cc0dc23a528410"
] | [
"bin/get_schedules.py"
] | [
"\"\"\"Create schedule for the workshop.\n\nDetermines which lesson schedules are required by reading _config.yml. The\nschedule for each lesson is modified by a delta time to account for different\nstart times to what is in the schedule. The schedules are written to HTML in an\n(n x 2) array, with the first column... | [
[
"pandas.read_html"
]
] |
stancld/metrics | [
"d35c3b5cff21e68e6620ebfc9a84e60dc4559e92"
] | [
"tests/text/test_rouge.py"
] | [
"# Copyright The PyTorch Lightning team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"torch.tensor",
"torch.argmax"
]
] |
desbarmitar/monsterforge | [
"75a2d2f305bff329d3c640f18cefa8a1381df8d2"
] | [
"paperminis/generate_minis.py"
] | [
"import io\nimport logging\nimport re\nfrom collections import Counter\nfrom zipfile import ZIP_DEFLATED, ZipFile\n\nimport cv2 as cv\nimport numpy as np\nfrom PIL import Image, ImageDraw, ImageFont\nfrom greedypacker import BinManager\n\nfrom paperminis.models import Creature, CreatureQuantity\nfrom paperminis.uti... | [
[
"numpy.concatenate",
"numpy.rot90",
"numpy.array",
"numpy.ceil",
"numpy.zeros",
"numpy.floor_divide",
"numpy.dstack",
"numpy.flip",
"numpy.floor"
]
] |
tardis-sn/tardisanalysis | [
"c326d0d9559e77366e5d833aef1667020a529b65"
] | [
"tardis_kromer_plot.py"
] | [
"\"\"\"A simple plotting tool to create spectral diagnostics plots similar to those\noriginally proposed by M. Kromer (see, for example, Kromer et al. 2013, figure\n4).\n\"\"\"\nimport logging\nimport numpy as np\nimport astropy.units as units\nimport astropy.constants as csts\nimport pandas as pd\n\ntry:\n impo... | [
[
"matplotlib.cm.ScalarMappable",
"numpy.min",
"matplotlib.pyplot.gcf",
"pandas.concat",
"pandas.read_csv",
"numpy.max",
"matplotlib.pyplot.colorbar",
"numpy.arange",
"matplotlib.pyplot.rcdefaults",
"numpy.in1d",
"matplotlib.lines.Line2D",
"matplotlib.pyplot.figure",
... |
valdersoul/NeuralDialog-LAED | [
"a0a6ccdc54cf17c1815ed956f5454d7102fb18d2"
] | [
"laed/main.py"
] | [
"# -*- coding: utf-8 -*-\n# author: Tiancheng Zhao\nfrom __future__ import print_function\nimport numpy as np\nfrom laed.models.model_bases import summary\nimport torch\nfrom laed.dataset.corpora import PAD, EOS, EOT\nfrom laed.enc2dec.decoders import TEACH_FORCE, GEN, DecoderRNN\nfrom laed.utils import get_dekeniz... | [
[
"numpy.max",
"numpy.array",
"numpy.exp",
"numpy.mean",
"numpy.argmax",
"numpy.average"
]
] |
dipesh1432/nbsite | [
"866c6d747879b9a4b88e0a30a43e35b9802645bd",
"866c6d747879b9a4b88e0a30a43e35b9802645bd"
] | [
"examples/sites/holoviews/holoviews/plotting/plotly/chart3d.py",
"examples/sites/holoviews/holoviews/plotting/bokeh/path.py"
] | [
"import numpy as np\nimport plotly.graph_objs as go\nfrom matplotlib.cm import get_cmap\nfrom plotly import colors\nfrom plotly.tools import FigureFactory as FF\nfrom plotly.graph_objs import Scene, XAxis, YAxis, ZAxis\n\ntry:\n from plotly.figure_factory._trisurf import trisurf as trisurface\nexcept ImportError... | [
[
"numpy.linspace",
"matplotlib.cm.get_cmap",
"scipy.spatial.Delaunay",
"numpy.vstack"
],
[
"numpy.array",
"numpy.unique",
"numpy.diff"
]
] |
pyxidr/data-science-consulting-part1 | [
"b8a34f55d9ab7580d85e27da66abc8d25b7bd3e4"
] | [
"src/python/modules/client_data.py"
] | [
"\"\"\"\nCopyright (c) 2019, Pyxidr and/or its affiliates. All rights reserved.\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions\nare met:\n\n - Redistributions of source code must retain the above copyright\n notice, this ... | [
[
"pandas.DataFrame",
"pandas.read_excel"
]
] |
PasaLab/YAO | [
"2e70203197cd79f9522d65731ee5dc0eb236b005",
"2e70203197cd79f9522d65731ee5dc0eb236b005"
] | [
"Liquid-job-benchmarks/scripts/tf_cnn_benchmarks/models/experimental/deepspeech.py",
"Liquid-optimizer/main.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\r\n#\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n#\r\n# http://www.apache.org/licenses/LICENSE-2.0\r\n#\... | [
[
"tensorflow.compat.v1.nn.dynamic_rnn",
"tensorflow.compat.v1.transpose",
"tensorflow.compat.v1.nn.ctc_loss",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.convert_to_tensor",
"tensorflow.compat.v1.layers.dense",
"tensorflow.compat.v1.to_float",
"tensorflow.compat.v1.keras.bac... |
kevinwss/Deep-SAD-Baseline | [
"b704725cc44ab5e7aa9bb09503a4c5f244fa907b"
] | [
"src/datasets/mnist.py"
] | [
"from torch.utils.data import Subset\nfrom PIL import Image\nfrom torchvision.datasets import MNIST\nfrom base.torchvision_dataset import TorchvisionDataset\nfrom .preprocessing import create_semisupervised_setting\n\nimport torch\nimport torchvision.transforms as transforms\nimport random\n\nimport numpy as np\n\n... | [
[
"torch.utils.data.Subset",
"numpy.concatenate",
"torch.zeros_like",
"torch.from_numpy"
]
] |
palatinuse/feast | [
"7d8126b5d934683469c16fd715f5dc11a6307e6b"
] | [
"sdk/python/feast/job.py"
] | [
"from typing import List\nfrom urllib.parse import urlparse\n\nimport fastavro\nimport grpc\nimport pandas as pd\nfrom google.protobuf.json_format import MessageToJson\n\nfrom feast.constants import CONFIG_TIMEOUT_KEY\nfrom feast.constants import FEAST_DEFAULT_OPTIONS as defaults\nfrom feast.core.CoreService_pb2 im... | [
[
"pandas.DataFrame.from_records"
]
] |
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