repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
rashidhaffadi/Language-Identification | [
"03f69c2017daf12f7373697e9c76017b6631ab97"
] | [
"shingle.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n@author: Rashid Haffadi\n\"\"\"\nimport pickle\nimport itertools\nfrom exceptions import ArgumentError\nfrom collections import Counter\nfrom text import * #create_dataframe, read_dataframe, trn_tst\nimport pandas as pd\nfrom sklearn.metrics import f1_score, accuracy_score\nfrom fu... | [
[
"pandas.DataFrame"
]
] |
mikkeljakobsen/Open3D | [
"1b085653eaa3cc4145c911b8170d6d9f9f8a6d87"
] | [
"examples/python/6d_pose_annotation/common3Dfunc.py"
] | [
"# Common functions for 3D processiong \n# Shuichi Akizuki, Chukyo Univ.\n# Email: s-akizuki@sist.chukyo-u.ac.jp\n#\nimport open3d as o3 \nimport numpy as np\nimport copy\nimport json\nfrom math import *\n\ndef Centering( _cloud_in ):\n \"\"\"\n Centering()\n offset an input cloud to its centroid.\n \n ... | [
[
"numpy.dot",
"numpy.min",
"numpy.asarray",
"numpy.identity",
"numpy.mean",
"numpy.array"
]
] |
mekman/nigraph | [
"f49766672d1cc189d8ec20cc6fed5d47c1b19a75"
] | [
"nigraph/nigraph.py"
] | [
"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n\"\"\"Commonly used utility functions.\"\"\"\n\n# mainly backports from future numpy here\n\nfrom __future__ import absolute_import, division, print_function\nimport numpy as np\nimport nibabel as nib\n\n\ndef thresholding_abs(A, thr, smaller=True, copy=True):\n \"\"\... | [
[
"numpy.zeros",
"numpy.mean",
"numpy.empty",
"numpy.unique"
]
] |
AppliedMechanics/AMfe | [
"be209dffe4d170aca735f1e912fd5cb448502119"
] | [
"tests/unit_tests/test_preconditioner.py"
] | [
"from unittest import TestCase\nfrom numpy.testing import assert_array_equal, assert_allclose\nfrom amfeti.preconditioners import *\nfrom amfeti.linalg import Matrix\nimport numpy as np\nfrom scipy.sparse import csr_matrix\n\n\ndef create5dofExample():\n K = Matrix(csr_matrix(np.array([[2, -3, 0, 0, 0],\n ... | [
[
"numpy.testing.assert_array_equal",
"numpy.array",
"numpy.testing.assert_allclose"
]
] |
guyao/koalas | [
"5c59a8253c7ba8c093c89b4c740f6a6aabed8f3a"
] | [
"databricks/koalas/tests/test_indexes.py"
] | [
"#\n# Copyright (C) 2019 Databricks, Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable la... | [
[
"pandas.Index",
"pandas.DataFrame",
"pandas.MultiIndex.from_arrays",
"numpy.random.randn",
"pandas.date_range"
]
] |
xuhuasheng/Dive2DeepLearning-pytorch | [
"b8e6bb175081037baf0342df66cb7ed7eae504aa"
] | [
"convolutional-modern/ResNet.py"
] | [
"import torch\nfrom torch import nn\nfrom torch.nn import functional as F \nfrom d2l import torch as d2l\n\n# 残差单元\nclass Residual(nn.Module):\n def __init__(self, input_channels, num_channels, use_1x1conv=False, strides=1):\n super().__init__()\n self.conv1 = nn.Conv2d(input_channels, num_channels... | [
[
"torch.nn.Conv2d",
"torch.nn.Flatten",
"torch.nn.MaxPool2d",
"torch.nn.Linear",
"torch.nn.functional.relu",
"torch.nn.AdaptiveAvgPool2d",
"torch.rand",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU"
]
] |
apple-phi/Advent-of-Code | [
"7227b5692eb456f23afd1a9f93a44c48436cb1ad"
] | [
"2021/day_23.py"
] | [
"# ridiculously slow (had to leave overnight!!); in future should use complex numbers to model graph instead of strings\n\nfrom collections import namedtuple, defaultdict\nimport functools\nimport math\nimport heapq\nimport itertools\n\ngraph = {\n \"h1\": {\"h2\"},\n \"h2\": {\"h1\", \"h3\"},\n \"h3\": {\... | [
[
"matplotlib.pyplot.show"
]
] |
vykhand/Mask_RCNN | [
"beab350f9656339cfaee93811283fa9f931687b5"
] | [
"samples/nucleus/nucleus.py"
] | [
"\"\"\"\nMask R-CNN\nTrain on the nuclei segmentation dataset from the\nKaggle 2018 Data Science Bowl\nhttps://www.kaggle.com/c/data-science-bowl-2018/\n\nLicensed under the MIT License (see LICENSE for details)\nWritten by Waleed Abdulla\n\n------------------------------------------------------------\n\nUsage: imp... | [
[
"numpy.reshape",
"matplotlib.use",
"numpy.stack",
"numpy.ones",
"tensorflow.ConfigProto",
"numpy.concatenate",
"tensorflow.Session",
"numpy.argsort",
"numpy.array",
"numpy.zeros",
"numpy.where"
]
] |
DirkEilander/CaMa-Flood_v4 | [
"a8e6a157a08c2a0144b8143bc2eb78d5d81eb9a7"
] | [
"etc/downscale_flddph/draw_flddph.py"
] | [
"import sys\nimport os\n\nimport numpy as np\nfrom numpy import *\n\nimport matplotlib as mpl\nimport matplotlib.pyplot as plt\nimport matplotlib.cm as cm\nfrom matplotlib import colors\nfrom matplotlib.ticker import FormatStrFormatter\nfrom mpl_toolkits.axes_grid1 import make_axes_locatable\n\nimport warnings;warn... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.colors.BoundaryNorm",
"numpy.fromfile",
"numpy.asarray",
"numpy.arange",
"numpy.less",
"matplotlib.pyplot.savefig",
"numpy.greater_equal",
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.text",
"numpy.ma.masked_where",
"matpl... |
luis-puhl/minas-py | [
"7a665da366ab65bbb05b1713292492cf5ab4a859"
] | [
"minas/kafka/producer.py"
] | [
"import time\nimport logging\nimport os\n\nimport numpy as np\nfrom kafka import KafkaConsumer\nfrom kafka import KafkaProducer\nimport msgpack\n\nfrom minas.map_minas_support import *\nfrom minas.ext_lib.humanize_bytes import humanize_bytes\n\nDATA_SET_FAKE = 'DATA_SET_FAKE'\nDATA_SET_COVTYPE = 'DATA_SET_COVTYPE'\... | [
[
"sklearn.datasets.fetch_covtype",
"numpy.random.choice",
"numpy.random.random_sample",
"numpy.random.normal",
"numpy.array",
"sklearn.datasets.fetch_kddcup99"
]
] |
thangduong/dlframework | [
"791838f1323552f849c34341907938b1c0c054f1"
] | [
"framework/subgraph/nlp.py"
] | [
"import tensorflow as tf\nimport framework.subgraph.core as core\n\ndef dump_variables():\n total_size = 0\n for var in tf.trainable_variables():\n var_size = np.prod(var.get_shape().as_list())\n print(\"%s : %s parameters, %s mb\" % (var.name, str(var_size), str(var_size / (1024 * 1024))))\n total_size ... | [
[
"tensorflow.nn.bias_add",
"tensorflow.nn.relu",
"tensorflow.get_variable",
"tensorflow.truncated_normal_initializer",
"tensorflow.nn.l2_loss",
"tensorflow.variable_scope",
"tensorflow.trainable_variables",
"tensorflow.nn.conv1d",
"tensorflow.add_to_collection",
"tensorflow.... |
scottslusher/Portfolio-Builder | [
"adcac6f29924259da083e9b71045feee8a7cf0a9"
] | [
"app.py"
] | [
"# A Database CLI Application\n\n# Import modules\nimport pandas as pd\nimport sqlalchemy as sql\nimport os\nimport questionary\nimport yfinance as yf\nfrom pathlib import Path\nimport csv\nimport fire\nimport requests\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport scipy.optimize as optimization\nimpo... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.read_sql_table",
"pandas.DataFrame",
"numpy.array"
]
] |
domyounglee/baseline | [
"2261abfb7e770cc6f3d63a7f6e0015238d0e11f8",
"2261abfb7e770cc6f3d63a7f6e0015238d0e11f8"
] | [
"python/hpctl/tests/human_collisions.py",
"python/baseline/pytorch/classify/train.py"
] | [
"from __future__ import absolute_import, division, print_function, unicode_literals\n\nimport argparse\nimport numpy as np\nfrom hpctl.sample import random_name\n\ndef main():\n parser = argparse.ArgumentParser()\n parser.add_argument('--trials', '-t', default=1000, type=int)\n args = parser.parse_args()\n... | [
[
"numpy.max",
"numpy.std",
"numpy.mean",
"numpy.min"
],
[
"torch.nn.DataParallel",
"torch.load"
]
] |
derpyninja/nlp4cciwr | [
"235b9b90681c98bd2cb80a2fb6cb6eb4352390c7"
] | [
"src/data/io.py"
] | [
"# -*- coding: utf-8 -*-\nimport logging\nimport textacy\nimport pandas as pd\n\n\ndef read_corpus(fpath, language_model, store_user_data=True):\n \"\"\"\n\n Parameters\n ----------\n fpath : str\n file path\n language_model : spaCy\n nlp\n store_user_data : bool\n custom ext... | [
[
"pandas.read_pickle"
]
] |
CaveSven/od_experiments | [
"91a4e10d17794d8e56c3adef9130f4f10a8722d7"
] | [
"src/models/vgg/vgg16.py"
] | [
"from tensorflow.python.keras.models import Sequential\nfrom tensorflow.python.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D, Dropout\nfrom tensorflow.python.keras.regularizers import l2\ndef build_vgg(img_rows:int=224, img_cols:int=224, num_classes:int =1000):\n vgg = Sequential()\n vgg.add(Conv2D... | [
[
"tensorflow.python.keras.layers.Flatten",
"tensorflow.python.keras.layers.MaxPooling2D",
"tensorflow.python.keras.models.Sequential",
"tensorflow.python.keras.regularizers.l2",
"tensorflow.python.keras.layers.Dropout"
]
] |
bk7084/framework | [
"c364174409c63dbee90e36d8b08fde17df482e8c"
] | [
"bk7084/geometry/shape.py"
] | [
"import abc\nfrom typing import Sequence\n\nimport numpy as np\n\nfrom ..graphics.util import DrawingMode\nfrom ..misc import Color, PaletteDefault\n\n\nclass Shape(metaclass=abc.ABCMeta):\n @classmethod\n def __subclasshook__(cls, subclass):\n return hasattr(subclass, 'vertices') and \\\n ... | [
[
"numpy.array",
"numpy.tile"
]
] |
giuse/numpy | [
"5f7f8e192534e728c3a8b66170377240fb1ece2a"
] | [
"numpy/core/numeric.py"
] | [
"from __future__ import division, absolute_import, print_function\n\nimport functools\nimport itertools\nimport operator\nimport sys\nimport warnings\nimport numbers\nimport contextlib\n\nimport numpy as np\nfrom numpy.compat import pickle, basestring\nfrom . import multiarray\nfrom .multiarray import (\n _fastC... | [
[
"numpy.compat.pickle.loads",
"numpy.issubdtype",
"numpy.eye",
"numpy.compat.pickle.load",
"numpy.ravel"
]
] |
kathyxchen/PathCORE-dev | [
"9d079d5ebffea2fe9fb9ab557588d51ad67d2c9c"
] | [
"pathcore/feature_pathway_overrepresentation.py"
] | [
"\"\"\"Determine the pathways overrepresented in a constructed feature.\n\"\"\"\nfrom crosstalk_correction import crosstalk_correction\nimport numpy as np\nimport pandas as pd\nfrom scipy import stats\nfrom statsmodels.sandbox.stats.multicomp import multipletests\n\n\n# handle the floating point errors thrown in th... | [
[
"pandas.concat",
"pandas.Series",
"numpy.seterr",
"scipy.stats.fisher_exact",
"numpy.array"
]
] |
RenanMP12/coding_engineering | [
"c7b543299faae899d7f15223ceaed4e70286dff4"
] | [
"codes/python/circular_geometry.py"
] | [
"# Libraries\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\n# Coordinate matrix\n# number of nodes\nnnos = 11\n# number of elements\nnel = nnos - 2\n\n# coordinate matrix pre-allocation\ncoord = np.zeros((nnos, 3)) \ncoord[0][0] = 1\n\n# theta value\ntheta = (np.pi/2)/(nnos-2)\n\nfor i in range(0, nnos... | [
[
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.subplots",
"numpy.cos",
"numpy.sin",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.xlabel",
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.figure"
]
] |
Akanshay/librosa | [
"17885667683a9c401de567494ceeb28fcac0901f"
] | [
"librosa/beat.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\nBeat and tempo\n==============\n.. autosummary::\n :toctree: generated/\n\n beat_track\n estimate_tempo\n\"\"\"\n\nimport numpy as np\nimport scipy\n\nfrom . import cache\nfrom . import core\nfrom . import onset\nfrom . import util\nfrom .util.exception... | [
[
"numpy.log",
"numpy.log2",
"numpy.asarray",
"numpy.arange",
"numpy.argwhere",
"numpy.round",
"numpy.argmax",
"numpy.zeros_like",
"scipy.signal.hann",
"numpy.array"
]
] |
godspeed1989/DANConv | [
"a1c5e543964e51546622a7600d78c004650163d3"
] | [
"nearest_neighbors/test.py"
] | [
"import numpy as np\nimport lib.python.nearest_neighbors as nearest_neighbors\nimport time\n\nbatch_size = 16\nnum_points = 81920\nK = 30\npc = np.random.rand(batch_size, num_points, 3).astype(np.float32)\n\n# nearest neighbours\nstart = time.time()\nneigh_idx = nearest_neighbors.knn_batch(pc, pc, K, omp=True)\npri... | [
[
"numpy.random.rand",
"numpy.stack"
]
] |
akma327/StillWaters | [
"46eb5b84f4896116a08d4c36c0928e4e5bc44d1b"
] | [
"src/utils.py"
] | [
"# Author: Anthony Kai Kwang Ma\n# Email: anthonyma27@gmail.com, akma327@stanford.edu\n# Date: 07/13/17\n# utils.py\n\nimport os\nimport vmd, molecule, sys\nfrom vmd import *\nfrom atomsel import *\nfrom multiprocessing import *\nimport datetime \nimport glob \nimport re\nimport numpy as np\n\ndef atoi(text):\n\tre... | [
[
"numpy.array",
"numpy.linalg.norm"
]
] |
daggertye/tensorforce | [
"520a8d992230e382f08e315ede5fc477f5e26bfb"
] | [
"tensorforce/contrib/openai_gym.py"
] | [
"# Copyright 2017 reinforce.io. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by ap... | [
[
"numpy.float32"
]
] |
rushike/rmidipy | [
"7d80dc2cc584cb2e8b8df0eeedc34e9e11ab0de7"
] | [
"rmidi/dataset/piano_roll.py"
] | [
"from rmidi.dataset import config\nfrom rmidi import mutils\nfrom rmidi import MIDI\nfrom rmidi import AbsoluteMidi\nfrom rmidi.constant import converter\nimport numpy\n\nclass PianoRoll:\n def __init__(self, midi, print_threshold = 25):\n self.midi = midi\n self.print_threshold = print_threshold\n... | [
[
"numpy.shape",
"numpy.zeros"
]
] |
formyfamily/pytorch-CycleGAN-and-pix2pix | [
"57f6ba195bd4c6c3f6acdce8fb11295b59532545"
] | [
"options/base_options.py"
] | [
"import argparse\nimport os\nfrom util import util\nimport torch\nimport models\nimport data\n\n\nclass BaseOptions():\n \"\"\"This class defines options used during both training and test time.\n\n It also implements several helper functions such as parsing, printing, and saving the options.\n It also gat... | [
[
"torch.cuda.set_device"
]
] |
alessioprestileo/freesif | [
"8a7d519b5a8b2cd48c1f6bab2f648a18456beb8a",
"8a7d519b5a8b2cd48c1f6bab2f648a18456beb8a"
] | [
"freesif/calc/principal.py",
"freesif/sequentialparser/parsers.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Apr 30 20:24:59 2018\n\n@author: audun\n\"\"\"\n\nfrom __future__ import division\n\nimport numpy as np\n\n\ndef principal2d(arr):\n \"\"\"2d principal stress calculation.\n\n *arr* must be at least a (...,3) shaped array where the three first\n elements on ... | [
[
"numpy.sqrt",
"numpy.abs",
"numpy.linalg.eig",
"numpy.stack",
"numpy.delete",
"numpy.zeros_like",
"numpy.ndindex",
"numpy.empty"
],
[
"numpy.mod",
"numpy.array",
"numpy.empty"
]
] |
jimitgandhi/tagan_private | [
"654f565ea8de05e4f4eb1e43c2a7225f121a6e7a"
] | [
"train.py"
] | [
"import os\nimport argparse\nimport visdom\n\nimport torch\nimport torch.nn.functional as F\nfrom torch.utils.data import DataLoader\nimport torch.optim.lr_scheduler as lr_scheduler\nimport torchvision.transforms as transforms\n\nfrom model import Generator, Discriminator\nfrom data import ConvertCapVec, ReadFromVe... | [
[
"torch.nn.functional.l1_loss",
"torch.load",
"torch.zeros_like",
"torch.utils.data.DataLoader",
"torch.exp",
"torch.pow",
"torch.cuda.is_available",
"torch.device",
"torch.ones_like",
"torch.optim.lr_scheduler.StepLR"
]
] |
francescocastelli/pytorch | [
"83d875d43150b0b7542095ee30999dd6a1b08386"
] | [
"torch/_refs/special/__init__.py"
] | [
"import torch\n\nimport torch._prims as prims\nimport torch._prims.utils as utils\nfrom torch._prims.utils import TensorLikeType\nfrom torch._prims.wrappers import out_wrapper, elementwise_type_promotion_wrapper\nfrom torch._refs import _make_elementwise_unary_reference\n\n__all__ = [\n \"i0e\",\n \"i1e\",\n]... | [
[
"torch._refs._make_elementwise_unary_reference"
]
] |
lucasgiutavares/docker-dash | [
"f93b54f2ede1efdaf07bf223186af025e26fff90"
] | [
"app/plotting.py"
] | [
"import pandas as pd\nimport numpy as np\nimport sys\nsys.path.insert(1, '/')\nimport pdm_viz.EDA.EDA as eda\nsys.path.insert(1, '/app')\nimport plotly.graph_objects as go\nimport datetime\n\ntagList = ['MV26_PDI-1535A-02.PV_mean', 'MV26_PDI-1535B-02.PV_mean']\n\ndf = pd.read_csv('/app/data/preprocessed/temp.csv').... | [
[
"numpy.max",
"pandas.read_csv",
"pandas.to_datetime"
]
] |
jmabry/pyaf | [
"afbc15a851a2445a7824bf255af612dc429265af",
"afbc15a851a2445a7824bf255af612dc429265af"
] | [
"tests/perf/test_perf2.py",
"scripts/num_diff.py"
] | [
"import pandas as pd\nimport numpy as np\n\nimport pyaf.TS.Perf as tsperf\n\ndef test_perf(x , y):\n lPerf = tsperf.cPerf();\n lPerf.compute(x, y, \"xxx\");\n print(x.shape , lPerf.mL2 , lPerf.mMAPE);\n\n\nfor n in range(200, 1000000, 10000):\n df = pd.DataFrame();\n df['x'] = range(n);\n df['y'] ... | [
[
"pandas.DataFrame",
"numpy.sin"
],
[
"numpy.isclose"
]
] |
zgcr/pytorch-ImageNet-CIFAR-COCO-voc-training | [
"c5878df46ac874097d1a5076a81cd7d41630fb98"
] | [
"classification_training/cifar100/resnet50halfcifar/test_config.py"
] | [
"import os\nimport sys\n\nBASE_DIR = os.path.dirname(\n os.path.dirname(os.path.dirname(os.path.dirname(\n os.path.abspath(__file__)))))\nsys.path.append(BASE_DIR)\n\nimport numpy as np\n\nfrom tools.path import CIFAR100_path\n\nfrom simpleAICV.classification import backbones\nfrom simpleAICV.classificati... | [
[
"numpy.array"
]
] |
SchenbergZY/keras-xlnet | [
"3ac36496af1f74511d00a206c196e1a78563845b"
] | [
"demo/extract/token_embed_chinese_mid.py"
] | [
"import os\nimport sys\n\nimport numpy as np\n\nfrom keras_xlnet import Tokenizer, load_trained_model_from_checkpoint, ATTENTION_TYPE_BI\n\n\nif len(sys.argv) == 2:\n '''Can be found at https://github.com/ymcui/Chinese-PreTrained-XLNet'''\n checkpoint_path = sys.argv[1]\n vocab_path = os.path.join(checkpoi... | [
[
"numpy.array",
"numpy.zeros_like",
"numpy.zeros"
]
] |
bassemessam/disaster-reponse-project | [
"57abd4f836ad35d32fa2cbc41e599aa8d3bd9751"
] | [
"data/process_data.py"
] | [
"import sys\nimport pandas as pd\nimport numpy as np\nfrom sqlalchemy import create_engine\n\n\ndef load_data(messages_filepath, categories_filepath):\n '''A function to load the data from .csv files (messages and categories)\n and merge them.\n Args:\n - messages_filpath: A string of the messages datas... | [
[
"pandas.concat",
"pandas.read_csv",
"numpy.where"
]
] |
kpedro88/mplhep | [
"d39d737b63c6a94548b4d4789b91d57cc46db470"
] | [
"tests/test_styles.py"
] | [
"import os\nimport sys\n\nimport matplotlib.pyplot as plt\nimport pytest\nfrom matplotlib.testing.decorators import check_figures_equal\n\nos.environ[\"RUNNING_PYTEST\"] = \"true\"\n\nimport mplhep as hep # noqa\n\n\"\"\"\nTo test run:\npytest --mpl\n\nWhen adding new tests, run:\npytest --mpl-generate-path=tests/... | [
[
"matplotlib.pyplot.switch_backend",
"matplotlib.testing.decorators.check_figures_equal",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.rcParams.update",
"matplotlib.pyplot.style.use"
]
] |
jackypheno/flavio | [
"2fe4e8af49b7449bd12bd352c39326e9bbcd9cc6"
] | [
"flavio/physics/bdecays/bvll/qcdf.py"
] | [
"r\"\"\"QCD factorization corrections to $B\\to V\\ell^+\\ell^-$ at low $q^2$\"\"\"\n\n\nfrom math import pi,exp\nfrom cmath import sqrt,atan,log\nimport numpy as np\nfrom scipy.special import eval_gegenbauer\nfrom flavio.physics import ckm\nfrom flavio.math.functions import li2, ei\nfrom flavio.physics.running imp... | [
[
"scipy.special.eval_gegenbauer"
]
] |
Stochastik-TU-Ilmenau/covid19-forecast-hub-de | [
"384d9ed2d84e9733f630973fb1a43b079f2b57a1",
"384d9ed2d84e9733f630973fb1a43b079f2b57a1"
] | [
"code/hub_transfer/download_eu.py",
"code/auto_download/MZ_download.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon May 10 14:10:33 2021\n\n@author: Jannik\n\"\"\"\n\nimport requests\nimport pandas as pd\nfrom datetime import datetime, date, timedelta\nfrom pathlib import Path\n\n# list all forecast files already present in the eu hub\nurl = \"https://api.github.com/repos/epiforec... | [
[
"pandas.read_csv"
],
[
"pandas.concat",
"pandas.read_csv",
"pandas.to_datetime",
"pandas.Series"
]
] |
joselynzhao/One-shot-Person-Re-ID-with-Variance-Subsampling-Method | [
"65096680921129496d424960799dae3ff7e3b06b",
"65096680921129496d424960799dae3ff7e3b06b"
] | [
"reid/evaluators.py",
"reid/feature_extraction/cnn.py"
] | [
"from __future__ import print_function, absolute_import\r\nimport time\r\nfrom collections import OrderedDict\r\n\r\nimport torch\r\n\r\nfrom .evaluation_metrics import cmc, mean_ap\r\nfrom .feature_extraction import extract_cnn_feature\r\nfrom .utils.meters import AverageMeter\r\n\r\nimport tqdm\r\n\r\nfrom torch.... | [
[
"torch.no_grad",
"torch.pow"
],
[
"torch.no_grad",
"torch.autograd.Variable"
]
] |
s-okugawa/HDNNP-tools | [
"54842ec0e95f9daf7bac04d0eefa760c6a92a1f0",
"54842ec0e95f9daf7bac04d0eefa760c6a92a1f0"
] | [
"tools/AI-MD/plotSymF-G-md.py",
"tools/Lmps-MD/plotSymF-TP2.py"
] | [
"# -*- coding: utf-8 -*-\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\"\"\"\nThis script is for plotting G1/G2/G4 data of calculated Symm-Func\nof MD 1000K/1200K sample\n\"\"\"\n\nif __name__ == '__main__': \n mdfolder=\"/home/okugawa/HDNNP/Si-190808-md/\"\n outfolder=mdfolder+\"/result/symf/\"\n ... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.setp",
"matplotlib.pyplot.close",
"numpy.load",
"matplotlib.pyplot.figure"
],
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.setp",
"matplotlib.pyplot.close",
"n... |
dada00321/clothes_db_crawler_v2 | [
"52557a636c6eca03e4cd9a7d9dabdbc8d2ca1f2b"
] | [
"modules/supplier_utils/uniform_category_transformer.py"
] | [
"import pandas as pd\nimport os\n\ndef transform_big_categories_to_uniform(is_show=True):\n '''\n Returns\n -------\n similar_categories : <dict>\n key: big-category for classification\n value: big-category(defined by supplier) defined by administrator,\n ... | [
[
"pandas.read_csv"
]
] |
sungjunhong/yolov1-tensorflow | [
"822c5ce0c841a9410aafcdf91af8bfc904d52595",
"822c5ce0c841a9410aafcdf91af8bfc904d52595"
] | [
"yolo/yolo_net.py",
"utils/pascal_voc.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport yolo.config as cfg\n\nslim = tf.contrib.slim\n\n\nclass YOLONet(object):\n\n def __init__(self, is_training=True):\n self.classes = cfg.CLASSES\n self.num_class = len(self.classes) # C = 20\n self.image_size = cfg.IMAG... | [
[
"tensorflow.stack",
"tensorflow.minimum",
"tensorflow.cast",
"tensorflow.summary.scalar",
"tensorflow.losses.get_total_loss",
"numpy.arange",
"tensorflow.truncated_normal_initializer",
"tensorflow.square",
"tensorflow.tile",
"tensorflow.placeholder",
"numpy.array",
... |
aristotelisxs/NeuroKit | [
"61c8c9b26ac7bc8ac5b666ce6cb1dfe59b1c146b",
"61c8c9b26ac7bc8ac5b666ce6cb1dfe59b1c146b",
"61c8c9b26ac7bc8ac5b666ce6cb1dfe59b1c146b",
"61c8c9b26ac7bc8ac5b666ce6cb1dfe59b1c146b"
] | [
"neurokit2/complexity/utils.py",
"data/fantasia/download_fantasia.py",
"neurokit2/signal/signal_timefrequency.py",
"neurokit2/rsp/rsp_eventrelated.py"
] | [
"# -*- coding: utf-8 -*-\nimport numpy as np\nimport sklearn.neighbors\n\nfrom .complexity_embedding import complexity_embedding\n\n\n# =============================================================================\n# Phi\n# =============================================================================\n\n\ndef _phi(... | [
[
"numpy.log",
"numpy.reshape",
"numpy.arange",
"numpy.full",
"numpy.ceil",
"numpy.std",
"numpy.mean",
"numpy.array",
"numpy.exp",
"numpy.zeros",
"numpy.sum",
"numpy.divide"
],
[
"pandas.concat",
"numpy.array",
"pandas.DataFrame"
],
[
"numpy.li... |
biliarski/Geo | [
"3eb8f3073f734ed13d8fa508a2fa29828e13cd11"
] | [
"geo.py"
] | [
"from segpy.reader import create_reader\nfrom segpy.writer import write_segy\n\n\nimport numpy as np\n\n\n\"\"\"\nDocs:\n Segpy https://segpy.readthedocs.io/en/latest/\n \n NumPy https://docs.scipy.org/doc/numpy-1.13.0/reference/index.html\n\"\"\"\n\n\nif __name__ == '__main__':\n with open('data/CUTE.s... | [
[
"numpy.array"
]
] |
fln99/time_warp_filter | [
"77cd483d7154893f2f43f430484e5fcb2d87cc51"
] | [
"app.py"
] | [
"import cv2 as cv\r\nimport numpy as np\r\nimport os\r\n\r\nblank = np.zeros((480, 640, 3), dtype=\"uint8\")\r\ncapture = cv.VideoCapture(0)\r\n\r\ni = 0\r\n\r\nwhile True:\r\n isTrue, frame = capture.read()\r\n\r\n if frame.shape[:2] != (480, 640):\r\n frame = cv.resize(frame, (480, 640), interpolatio... | [
[
"numpy.zeros"
]
] |
AccSrd/multimodal-Parkinson-data-processing | [
"384e178a07cf8eaa739ef9cf5429276778b8b8b5"
] | [
"Scripts/seg2label.py"
] | [
"\"\"\"\n************************************************************************************************\n*********************** Segmented --> Labeled ***********************************\n************************************************************************************************\nLabel the Dat... | [
[
"numpy.array",
"pandas.concat",
"pandas.read_csv",
"pandas.DataFrame"
]
] |
Andrelirao/aulas-graduacao | [
"c7e8ebf1ad6b5309720bab9ea0a2472d153cd169"
] | [
"Data science/Analise de dados/exercicio python/Graficos/GraficoNumpy.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Apr 17 08:42:37 2020\n\n@author: luisc\n\"\"\"\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndata1 = [10,5,2,4,6,8]\ndata2 = [ 1,2,4,8,7,4]\nx = 10*np.array(range(len(data1)))\n\nplt.plot( x, data1, 'go') # green bolinha\nplt.plot( x, data1, 'k:', color... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
vijayshankarrealdeal/Java | [
"2dff1a79c91782bf2aeb1bee057b19c41cafd2a1"
] | [
"Admin-Scripts/graph.py"
] | [
"from mpl_toolkits.basemap import Basemap\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import cm\ndataset = pd.read_csv('Total crimes against women .csv')\n\ndataset['latitude'] = dataset['Lat']\ndataset['longitude'] = dataset['Long']\ntop_pop_cities = dataset.sort_valu... | [
[
"pandas.read_csv",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.title",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.text",
"numpy.array"
]
] |
SooluThomas/qiskit-nature | [
"0d509525b68b76d0f2d613d0e7409b9ea65cfcc0",
"7baf7c7f8c3d18e082e90bc1e593c47aa2f698ca"
] | [
"test/properties/second_quantization/electronic/integrals/test_two_body_electronic_integrals.py",
"test/properties/second_quantization/vibrational/bases/test_harmonic_basis.py"
] | [
"# This code is part of Qiskit.\n#\n# (C) Copyright IBM 2021.\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.\n#\n# Any modifications or ... | [
[
"numpy.allclose",
"numpy.arange",
"numpy.eye",
"numpy.random.rand",
"numpy.isclose"
],
[
"numpy.asarray",
"numpy.nonzero",
"numpy.isclose"
]
] |
Jaghwani/Image-Classifier-Project | [
"c6cb93d26b945962978e1468686d7064f703d9cc"
] | [
"train.py"
] | [
"import torch\nimport numpy as np\nfrom torch import nn\nfrom torch import optim\nfrom torchvision import datasets, transforms, models\nfrom collections import OrderedDict\nimport argparse\n\n\nparser = argparse.ArgumentParser(description='image classifier')\nparser.add_argument(\"--data_dir\", help=\"Where the da... | [
[
"torch.nn.NLLLoss",
"torch.nn.Dropout",
"torch.nn.LogSoftmax",
"torch.max",
"torch.utils.data.DataLoader",
"torch.nn.Linear",
"torch.no_grad",
"torch.nn.ReLU",
"torch.save"
]
] |
IshikuraGaku/ParlAI | [
"bc19b2ead55ace7584674db919347b61f589a203"
] | [
"data/wizard_of_wikipedia2/make_test_val.py"
] | [
"from sklearn.model_selection import train_test_split\nimport json\nimport argparse\nimport pandas\nimport random\n\ndef main():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--input_file\", default=\"data.json\")\n args = parser.parse_args()\n\n input_txt = open(args.input_file).read()\n... | [
[
"sklearn.model_selection.train_test_split",
"pandas.read_json"
]
] |
worldbank/GOSTnets | [
"b3eb446a146a1419cbc761bc75b4fd6c5b350698"
] | [
"GOSTnets/fetch_od.py"
] | [
"# -*- coding: utf-8 -*-\r\n\r\n## library Imports\r\nimport json, sys, os, time, argparse, logging\r\nimport shapely\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\ntry:\r\n import urllib.request as url # python 3\r\nexcept:\r\n import urllib2 as url # python 2\r\n\r\n###### OD Matrix ######\r\ndef Cr... | [
[
"numpy.exp",
"pandas.concat",
"pandas.read_csv",
"pandas.DataFrame"
]
] |
IBM/transition-amr-parser | [
"dfd8352ea2ee3ff153b691edb6cd7ee541d53b2e"
] | [
"fairseq_ext/modules/multihead_attention_old.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\nfrom typing import Dict, Optional, Tuple\n\nimport torch\nfrom torch import Tensor, nn\nfrom torch.nn import Parameter\nimport torch... | [
[
"torch.Size",
"torch.empty",
"torch.Tensor",
"torch.nn.functional.dropout",
"torch.nn.init.constant_",
"torch.cat",
"torch.nn.init.xavier_normal_",
"torch.nn.functional.multi_head_attention_forward",
"torch.nn.Linear",
"torch.bmm",
"torch.nn.init.xavier_uniform_",
"... |
eliarbel/qiskit-experiments | [
"0d6841bfd84f65cbe64f60c5455aeda7173b97c9",
"0d6841bfd84f65cbe64f60c5455aeda7173b97c9"
] | [
"qiskit_experiments/database_service/json.py",
"test/randomized_benchmarking/test_rb_utils.py"
] | [
"# This code is part of Qiskit.\n#\n# (C) Copyright IBM 2021.\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.\n#\n# Any modifications or ... | [
[
"numpy.array"
],
[
"numpy.all",
"numpy.allclose",
"numpy.random.default_rng"
]
] |
cdodd/lotka-volterra-plotter | [
"d461d4ac56639da654bb932b3350b8d2ea131a2c"
] | [
"lotka_volterra_plotter.py"
] | [
"#!/usr/bin/env python\n\n# Python standard library modules\nimport sys\n\n# 3rd party modules\nimport matplotlib\nimport matplotlib.backends.backend_qt4agg as backend_qt4agg\nfrom matplotlib.figure import Figure\nimport PyQt4.QtCore as QtCore\nimport PyQt4.QtGui as QtGui\n\n# Local application modules\nfrom growth... | [
[
"matplotlib.font_manager.FontProperties",
"matplotlib.backends.backend_qt4agg.NavigationToolbar2QTAgg",
"matplotlib.backends.backend_qt4agg.FigureCanvasQTAgg",
"matplotlib.figure.Figure"
]
] |
fschur/Advantage-Actor-Critic-for-OpenAi-gym | [
"c130038789425301684825e09e77f17e89d21859"
] | [
"A2C_memory.py"
] | [
"import torch\n\ndevice = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n\n\nclass Memory:\n def __init__(self):\n self.rewards = []\n self.action_prob = []\n self.state_values = []\n self.entropy = []\n\n def calculate_data(self, gamma):\n # compute the... | [
[
"torch.stack",
"torch.Tensor",
"torch.cuda.is_available"
]
] |
WuLC/fedlearner | [
"7a9dbbecb1388bbb02dc04dfae1ddb810a427c4b"
] | [
"fedlearner/data_join/cmd/raw_data_partitioner_cli.py"
] | [
"# Copyright 2020 The FedLearner Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.compat.v1.gfile.ListDirectory",
"tensorflow.compat.v1.enable_eager_execution"
]
] |
LiZhang-pb/U-net-based-cells-auto-segmentation | [
"35c2d440608effa4dc4be1bd61b72aac9e82d9af"
] | [
"code/assessment.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nPerformance indicator\r\n预测结果性能指数\r\n\"\"\"\r\n\r\nimport numpy as np\r\nimport cv2\r\nimport os\r\n\r\n\"\"\" \r\n混淆矩阵\r\nP/L P N \r\nP TP FP \r\nN FN TN \r\n\"\"\"\r\n\r\n\r\n# 获取颜色字典\r\n# labelFolder 标签文件夹,之所以遍历文件夹是因为一张标签可能不包含所有类别颜色\r\n# classNum 类别... | [
[
"numpy.diag",
"numpy.unique",
"numpy.bincount",
"numpy.nanmean",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] |
olorin/nerven | [
"7f082854cb2b1d4545bd61d68229f15e1167e237"
] | [
"src/nerven/FftPanel.py"
] | [
"import wx, scipy, scipy.fftpack\nimport numpy as np\nfrom numpy import fft\n\nfrom nerven_panels import *\nfrom consts import *\n\n\nclass FftPanel(NervenPlotPanel):\n def do_update(self):\n nplots = len(self.epoc.sensors)\n fig = self.plot.get_figure()\n draw = True\n if self.draw_c... | [
[
"numpy.fft.rfft",
"numpy.array",
"scipy.fftpack.fftfreq"
]
] |
jaws/JustifiedAWS | [
"715921500989d993b777a37a3ed0927ba7856083"
] | [
"jaws/nsidc2nc.py"
] | [
"from datetime import datetime\nimport sys\n\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\n\ntry:\n from jaws import common, sunposition\nexcept ImportError:\n import common, sunposition\n\n\ndef init_dataframe(args, input_file):\n \"\"\"Initialize dataframe with data from input file; conv... | [
[
"pandas.notnull"
]
] |
hsnyder/scikit-cuda | [
"ab2708a1d514373d6760fa6e74ac7545b4ff8ec0"
] | [
"tests/test_cublas.py"
] | [
"#!/usr/bin/env python\n\n\"\"\"\nUnit tests for skcuda.cublas\n\"\"\"\n\nfrom unittest import main, makeSuite, TestCase, TestSuite\n\nimport pycuda.driver as drv\nimport pycuda.gpuarray as gpuarray\nfrom pycuda.tools import clear_context_caches, make_default_context\nimport numpy as np\n\ndrv.init()\n\n_SEPS = np.... | [
[
"numpy.complex128",
"numpy.dot",
"numpy.linalg.solve",
"numpy.allclose",
"numpy.random.seed",
"numpy.einsum",
"numpy.abs",
"numpy.conj",
"numpy.linalg.norm",
"numpy.finfo",
"numpy.argmax",
"numpy.argmin",
"numpy.float64",
"numpy.float32",
"numpy.random.r... |
ludwiglierhammer/pyremo | [
"e06d349530c95007903f02b87e6a1a6b0396008e"
] | [
"pyremo/analysis/analysis.py"
] | [
"\nimport os\nimport glob\n\nimport numpy as np\nimport xarray as xr\n\nfrom ..archive import archive\nfrom ..core.remo_ds import preprocess as remo_preprocess\nfrom ..core import codes\n\nsoil_temps = ['TS', 'TSL', 'TEMP2', 'TSN', 'TD3', 'TD4', 'TD5']\n\n\ndef open_mfdataset(files, use_cftime=True, parallel=True, ... | [
[
"numpy.deg2rad",
"numpy.ones"
]
] |
Qnubo-Tech/epydemic | [
"635f211f3621a5e52acd4dc82f3dd74b5049c36f"
] | [
"src/environment/disease/infection.py"
] | [
"from numpy.random import choice\n\nfrom src.environment.disease.parameter import DiseaseParameter\nfrom src.environment.status import Status\nfrom src.configuration import (\n ImmunityParams,\n InfectionParams\n)\n\n\nclass Infection(DiseaseParameter):\n\n def __init__(self,\n mean_duratio... | [
[
"numpy.random.choice"
]
] |
michalk8/squidpy | [
"b3b5f8a4784250c6792137853092a3d5c9dbf1c7"
] | [
"tests/conftest.py"
] | [
"from abc import ABC, ABCMeta\nfrom typing import Tuple, Mapping, Callable, Optional, Sequence\nfrom pathlib import Path\nfrom functools import wraps\nfrom itertools import product\nimport sys\nimport pickle\nimport pytest\n\nfrom anndata import AnnData\nimport scanpy as sc\n\nimport numpy as np\nimport pandas as p... | [
[
"numpy.random.seed",
"matplotlib.use",
"matplotlib.pyplot.savefig",
"numpy.ones",
"numpy.random.normal",
"matplotlib.pyplot.close",
"matplotlib.cm.get_cmap",
"numpy.random.uniform",
"numpy.array",
"numpy.random.RandomState",
"numpy.zeros",
"numpy.random.randint"
]... |
ydup/tensorflow-class-activation-mapping | [
"d9e267a828ce0e39543876ecd95e6469da3d1945"
] | [
"lenet_slim.py"
] | [
"import tensorflow as tf\n\nslim = tf.contrib.slim\n\n\ndef le_net(images, num_classes=10, scope='LeNet'):\n with tf.variable_scope(scope, 'LeNet', [images, num_classes]):\n net = slim.conv2d(images, 32, [5, 5], scope='conv1')\n net = slim.max_pool2d(net, [2, 2], 2, scope='pool1')\n net = sl... | [
[
"tensorflow.matmul",
"tensorflow.reduce_mean",
"tensorflow.truncated_normal_initializer",
"tensorflow.variable_scope",
"tensorflow.random_normal_initializer"
]
] |
junzhuang-code/audio_classification | [
"3eb9d6fb6f5943ea0b7f9dace5640c3d52980692"
] | [
"audio_classification/vae_rfc.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\n@title: CS590 Competition -- Audio Classification\n@topic: Test 2-D VAE & RFC model on competition dataset\n@author: junzhuang\n\"\"\"\n\nimport numpy as np\nimport pandas as pd\nimport librosa\nimport matplotlib.pyplot as plt\nimport tensorflow as tf\nimpor... | [
[
"tensorflow.reduce_sum",
"tensorflow.keras.layers.Conv2DTranspose",
"tensorflow.keras.layers.InputLayer",
"tensorflow.nn.sigmoid_cross_entropy_with_logits",
"matplotlib.pyplot.plot",
"numpy.hstack",
"pandas.read_csv",
"sklearn.ensemble.RandomForestClassifier",
"tensorflow.keras... |
xuzifu666/spark-1 | [
"e653b8cd89ea13c22823885c71cfb26514c72a03"
] | [
"python/pyspark/pandas/categorical.py"
] | [
"#\n# Licensed to the Apache Software Foundation (ASF) under one or more\n# contributor license agreements. See the NOTICE file distributed with\n# this work for additional information regarding copyright ownership.\n# The ASF licenses this file to You under the Apache License, Version 2.0\n# (the \"License\"); yo... | [
[
"pandas.api.types.is_list_like",
"pandas.api.types.CategoricalDtype",
"pandas.api.types.is_dict_like"
]
] |
Topaz1618/Plasticine | [
"e436798653ae8668b5e7dad2eb2dea3c06fba18b",
"e436798653ae8668b5e7dad2eb2dea3c06fba18b"
] | [
"utils/cv2_utils.py",
"nnlib/nnlib.py"
] | [
"import cv2\nimport numpy as np\nfrom pathlib import Path\n\n#allows to open non-english characters path\ndef cv2_imread(filename, flags=cv2.IMREAD_UNCHANGED):\n try:\n with open(filename, \"rb\") as stream:\n bytes = bytearray(stream.read())\n numpyarray = np.asarray(bytes, dtype=np... | [
[
"numpy.asarray"
],
[
"numpy.reshape",
"tensorflow.ConfigProto",
"numpy.floor",
"tensorflow.Session",
"numpy.outer",
"numpy.sum"
]
] |
goldford/NEMO-Salish-Sea-2021 | [
"c6a78956293f1741ff9537747dd02ce37c20a4d3"
] | [
"code/adjustERA5_MD_20210526.py"
] | [
"import os\nimport shutil\n\nimport metpy.calc as mpcalc\nimport netCDF4 as nc\nimport numpy as np\nfrom metpy.units import units\n\n\n# def getrh(t2m, d2m):\n# #################################################################################################\n# # relative humidity calculation\n# # https... | [
[
"numpy.zeros"
]
] |
nanand2/models | [
"a84696c426dac967c6f128da7be610578c419884"
] | [
"research/deeplab/vis.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 requi... | [
[
"tensorflow.Graph",
"tensorflow.shape",
"tensorflow.slice",
"numpy.squeeze",
"tensorflow.squeeze",
"tensorflow.train.get_or_create_global_step",
"tensorflow.expand_dims",
"tensorflow.global_variables_initializer",
"tensorflow.gfile.MakeDirs",
"tensorflow.logging.info",
... |
AmrMohamed96/PythonRobotics | [
"ea36fa5fdf92345900f35fb3f0408eac70223917"
] | [
"PathTracking/lqr_speed_steer_control/lqr_speed_steer_control.py"
] | [
"\"\"\"\n\nPath tracking simulation with LQR speed and steering control\n\nauthor Atsushi Sakai (@Atsushi_twi)\n\n\"\"\"\nimport math\nimport sys\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport scipy.linalg as la\n\nsys.path.append(\"../../PathPlanning/CubicSpline/\")\nimport cubic_spline_planner\n\n... | [
[
"matplotlib.pyplot.legend",
"numpy.eye",
"matplotlib.pyplot.cla",
"matplotlib.pyplot.subplots",
"numpy.rad2deg",
"matplotlib.pyplot.plot",
"numpy.deg2rad",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.close",
"matplotlib.pyplot.grid",
"scipy.linalg.inv",
"matplotlib... |
mbrner/unilm | [
"5988aa468a8b86e9a6689a601ca3b0263c74f0c5"
] | [
"deltalm/src/fairseq/search.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\nfrom typing import List, Optional\n\nimport torch\nimport torch.nn as nn\nfrom fairseq.token_generation_constraints imp... | [
[
"torch.LongTensor",
"torch.empty",
"torch.zeros",
"torch.cat",
"torch.zeros_like",
"torch.gather",
"torch.tensor",
"torch.arange",
"torch.full_like",
"torch.masked_select",
"torch.stack"
]
] |
ai-pest/efficientnet | [
"efb7cebfbb2f56a110f9ce26b19e36da6f6ca0a7"
] | [
"utils.py"
] | [
"# Copyright 2019 The TensorFlow Authors. All Rights Reserved.\n# Copyright 2022 Northern System Service Co., 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 ... | [
[
"tensorflow.compat.v1.logging.warn",
"tensorflow.compat.v1.train.ExponentialMovingAverage",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.data.Dataset.from_tensor_slices",
"tensorflow.compat.v1.gfile.GFile",
"tensorflow.compat.v1.train.Saver",
"tensorflow.compat.v1.constant",
... |
thimotyb/Data-Analysis | [
"f6a5f56412e2d7f5f5fae5b04d7e24a56a9ccf1c"
] | [
"sentdex_data_analysis/pandas_TPOT.py"
] | [
"import pandas as pd \nimport numpy as np \nfrom tpot import TPOTClassifier\nfrom sklearn.model_selection import train_test_split\n\nbenchmark = pd.read_pickle('us_pct.pickle') # us overall housing price index percentage change\nHPI = pd.read_pickle('HPI_complete.pickle') # all of the state data, thirty year mortg... | [
[
"numpy.array",
"pandas.read_pickle",
"sklearn.model_selection.train_test_split"
]
] |
sans-dev/mne-python | [
"308a0abf7c8b8b14c9afc6db2e3ed5b57787be31",
"308a0abf7c8b8b14c9afc6db2e3ed5b57787be31",
"308a0abf7c8b8b14c9afc6db2e3ed5b57787be31"
] | [
"mne/io/edf/tests/test_edf.py",
"mne/tests/test_morph.py",
"mne/tests/test_freesurfer.py"
] | [
"# -*- coding: utf-8 -*-\n# Authors: Teon Brooks <teon.brooks@gmail.com>\n# Martin Billinger <martin.billinger@tugraz.at>\n# Alan Leggitt <alan.leggitt@ucsf.edu>\n# Alexandre Barachant <alexandre.barachant@gmail.com>\n# Stefan Appelhoff <stefan.appelhoff@mailbox.org>\n# ... | [
[
"scipy.io.loadmat",
"numpy.testing.assert_array_equal",
"numpy.round",
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.testing.assert_array_almost_equal"
],
[
"numpy.linspace",
"numpy.in1d",
"numpy.concatenate",
"numpy.mean",
"numpy.argmin",
"numpy.allclo... |
kzjeef/sru | [
"a7c30233e2b7bde13187843a7d2fd2dcdd409c48"
] | [
"cuda_functional.py"
] | [
"#from builtins import bytes\nimport sys\nimport time\nimport math\n#import warnings\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Function, Variable\nfrom cupy.cuda import function\nfrom pynvrtc.compiler import Program\nfrom collections import namedtuple\n\nSRU_CODE = \"\"\... | [
[
"torch.mean",
"torch.nn.Parameter",
"torch.ones",
"torch.Tensor",
"torch.cuda.current_device",
"torch.zeros",
"torch.cat",
"torch.nn.ModuleList",
"torch.cuda.current_stream",
"torch.std",
"torch.nn.functional.relu",
"torch.stack"
]
] |
ChenyangTang/bark-ml | [
"1d2ab1957bf49929e27d718dd4bd3912162197b8"
] | [
"src/observers/nearest_state_observer.py"
] | [
"from gym import spaces\nimport numpy as np\nfrom bark.models.dynamic import StateDefinition\nfrom bark.world import World, ObservedWorld\nfrom src.commons.spaces import BoundedContinuous, Discrete\nfrom modules.runtime.commons.parameters import ParameterServer\nimport math\nimport operator\n\nfrom src.observers.ob... | [
[
"numpy.zeros",
"numpy.ones"
]
] |
LoicGRENON/stackoverflow | [
"e555b9dbb479ba2f36cd51dea373e1cfafffa6b1"
] | [
"questions/44603119/PandasModel.py"
] | [
"from PyQt5 import QtCore\n\nimport pandas as pd\n\nclass PandasModel(QtCore.QAbstractTableModel): \n def __init__(self, df = pd.DataFrame(), parent=None): \n QtCore.QAbstractTableModel.__init__(self, parent=parent)\n self._df = df\n\n def headerData(self, section, orientation, role=QtCore.Qt.Di... | [
[
"pandas.DataFrame"
]
] |
Frikallo/YAKbot | [
"bc798fe4ead1f6a3e4828960ea77e2a8f07b5fdc",
"bc798fe4ead1f6a3e4828960ea77e2a8f07b5fdc"
] | [
"Bot/vqgan_clip/helpers.py",
"Bot/taming_transformers/taming/data/imagenet.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.functional as F\nimport math\nfrom PIL import Image\n\ndef sinc(x):\n return torch.where(x != 0, torch.sin(math.pi * x) / (math.pi * x), x.new_ones([]))\n\ndef lanczos(x, a):\n cond = torch.logical_and(-a < x, x < a)\n out = torch.where(cond, sinc(x) * sin... | [
[
"torch.functional.conv2d",
"torch.nn.Parameter",
"torch.empty",
"torch.ones",
"torch.sin",
"torch.functional.interpolate",
"torch.zeros_like",
"torch.tensor",
"torch.no_grad",
"torch.functional.normalize",
"torch.arange",
"torch.logical_and",
"torch.functional.p... |
ermshaua/sktime | [
"b6c7153b4b0fbe601ab2308c53a408f07bc435b2",
"b6c7153b4b0fbe601ab2308c53a408f07bc435b2"
] | [
"sktime/performance_metrics/forecasting/probabilistic/_classes.py",
"sktime/transformations/compose.py"
] | [
"#!/usr/bin/env python3 -u\n# -*- coding: utf-8 -*-\n# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)\n\nimport numpy as np\n\n# TODO: add formal tests\nimport pandas as pd\nfrom sklearn.metrics._regression import _check_reg_targets\n\nfrom sktime.performance_metrics.forecasting._classes impo... | [
[
"pandas.Series",
"sklearn.metrics._regression._check_reg_targets",
"pandas.DataFrame",
"numpy.average",
"numpy.array",
"numpy.vstack"
],
[
"sklearn.base.clone"
]
] |
uberkinder/TA-Transformer | [
"2afa9a82339135eff1c0a731ab082e2b03f0c7db"
] | [
"tasa/models/transformer.py"
] | [
"import torch\nfrom torch import nn\nimport torch.nn.functional as F\n\nfrom tasa.modules import TransformerBlock\nfrom tasa.utils import d\n\n\nclass TATransformer(nn.Module):\n \"\"\"Time-Aware Transformer\"\"\"\n\n def __init__(self,\n emb: int, \n heads: int,\n ... | [
[
"torch.nn.Linear",
"torch.nn.functional.log_softmax",
"torch.nn.Embedding"
]
] |
petroolg/dltpy | [
"8f8d522945f2362efc29e4d5c1aa3d64f30f4f6a"
] | [
"input-preparation/generate_df.py"
] | [
"import os\nimport re\nfrom typing import Tuple\n\nimport pandas as pd\nimport numpy as np\nimport pickle\n\nfrom pandas import DataFrame\nfrom sklearn import preprocessing\nfrom sklearn.preprocessing import LabelEncoder\n\nfrom ast import literal_eval\n\nimport config\n\n# LOCAL CONFIG\nTYPES_FILE = os.path.join(c... | [
[
"pandas.concat",
"pandas.read_csv",
"numpy.invert",
"numpy.unique",
"pandas.DataFrame",
"numpy.concatenate",
"numpy.argsort",
"sklearn.preprocessing.LabelEncoder"
]
] |
chocolatefudge/semi-sup-learning | [
"c92ea4d6a551a646a61770261665d46720ea347f"
] | [
"etc/Implemented_Papers/MixMatch/main.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nimport os\nimport argparse\n\nimport numpy as np\nimport shutil\nimport random\nimport time\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\... | [
[
"torch.mean",
"torch.cat",
"torch.zeros",
"numpy.concatenate",
"torch.no_grad",
"torch.cuda.is_available",
"torch.split",
"torch.cuda.manual_seed_all",
"torch.autograd.Variable",
"torch.softmax",
"numpy.random.beta",
"numpy.clip",
"numpy.argsort",
"torch.cud... |
JuananCampillo/Commit-Antiguos | [
"2311fa6def8a4117af0f477aedbfcaa7c9a441f1"
] | [
"train.py"
] | [
"\"\"\"\r\nLicense: Apache-2.0\r\nAuthor: Suofei Zhang | Hang Yu\r\nE-mail: zhangsuofei at njupt.edu.cn | hangyu5 at illinois.edu\r\n\"\"\"\r\n\r\nimport tensorflow as tf\r\nimport tensorflow.contrib.slim as slim\r\nfrom config import cfg, get_coord_add, get_dataset_size_train, get_num_classes, get_create_inputs\r\... | [
[
"tensorflow.device",
"tensorflow.control_dependencies",
"tensorflow.global_variables",
"tensorflow.train.AdamOptimizer",
"tensorflow.summary.scalar",
"tensorflow.Graph",
"tensorflow.get_collection",
"tensorflow.check_numerics",
"tensorflow.train.exponential_decay",
"tensorf... |
xiezhq-hermann/graphiler | [
"4d3dd2d2e0a095e3e834be3a34f402bf43e4b4fa"
] | [
"examples/GAT/GAT_PyG.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom torch_geometric.nn import MessagePassing\nfrom torch_geometric.nn.inits import glorot, zeros\nfrom torch_geometric.utils import to_undirected, remove_self_loops, add_self_loops, softmax\n\n\nclass GATConv(MessagePassing):\n r\"\"\"The ... | [
[
"torch.nn.Dropout",
"torch.Tensor",
"torch.is_tensor",
"torch.nn.Linear",
"torch.nn.functional.leaky_relu",
"torch.nn.functional.elu"
]
] |
workshopI1/recy-api | [
"662f9e35dbb8281a2fa67b9ba76b9011167c2a23"
] | [
"retrain.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.framework.tensor_shape.scalar",
"tensorflow.python.platform.gfile.Walk",
"tensorflow.zeros",
"tensorflow.stack",
"numpy.squeeze",
"tensorflow.cast",
"tensorflow.image.random_crop",
"tensorflow.python.platform.gfile.Exists",
"tensorflow.compat.v1.placeholder_w... |
rickstaa/panda-gazebo | [
"5b236749399146e837601d8ab356a0eec7a9d749"
] | [
"panda_gazebo/tests/manual/test_joint_position_trajectory_controller.py"
] | [
"\"\"\"Small script that sends a sinusoid command to one of the panda joints.\"\"\"\n\nimport sys\n\nimport actionlib\nimport numpy as np\nimport rospy\nimport time\nfrom control_msgs.msg import FollowJointTrajectoryAction, FollowJointTrajectoryGoal\nfrom sensor_msgs.msg import JointState\nfrom std_msgs.msg import ... | [
[
"numpy.arange",
"numpy.sin"
]
] |
seungjaeryanlee/implementations-dqn | [
"134df06ba92fe3c35a74ee9e1a8be1e6460a345e"
] | [
"dqn/replays.py"
] | [
"\"\"\"Experience replay buffers for Deep Q-Network.\"\"\"\nimport copy\nimport random\nfrom collections import deque, namedtuple\nfrom typing import Callable, Tuple\n\nimport gym\nimport numpy as np\nimport torch\n\nTransition = namedtuple(\"Transition\", [\"obs\", \"action\", \"rew\", \"next_obs\", \"done\"])\n\n... | [
[
"torch.LongTensor",
"numpy.expand_dims",
"numpy.ones_like",
"numpy.clip",
"numpy.sign",
"numpy.zeros_like",
"torch.FloatTensor",
"numpy.array",
"numpy.vstack",
"numpy.random.randint"
]
] |
ykk648/mmhuman3d | [
"26af92bcf6abbe1855e1a8a48308621410f9c047",
"26af92bcf6abbe1855e1a8a48308621410f9c047",
"26af92bcf6abbe1855e1a8a48308621410f9c047"
] | [
"mmhuman3d/data/data_converters/coco.py",
"mmhuman3d/models/losses/prior_loss.py",
"mmhuman3d/core/conventions/cameras/convert_projection.py"
] | [
"import json\nimport os\n\nimport numpy as np\nfrom tqdm import tqdm\n\nfrom mmhuman3d.core.conventions.keypoints_mapping import convert_kps\nfrom mmhuman3d.data.data_structures.human_data import HumanData\nfrom .base_converter import BaseConverter\nfrom .builder import DATA_CONVERTERS\n\n\n@DATA_CONVERTERS.registe... | [
[
"numpy.reshape",
"numpy.array",
"numpy.ones"
],
[
"torch.cat",
"torch.pow",
"torch.norm",
"torch.einsum",
"torch.argmin",
"numpy.stack",
"torch.tensor",
"numpy.linalg.det",
"torch.nn.functional.relu",
"torch.ones_like",
"numpy.linalg.inv",
"torch.min... |
paul-moumita/Dijkstra-Point-and--Rigid-Robot. | [
"40df7215d726966c39b1470e244eee58ad67b089"
] | [
"Obstacles_detected_point.py"
] | [
"import tkinter as tk\r\nfrom tkinter import *\r\nfrom matplotlib.backends.backend_tkagg import FigureCanvasTkAgg\r\nimport numpy as np \r\nimport matplotlib.pyplot as plt\r\nimport math\r\nfrom collections import deque, namedtuple\r\nimport sys\r\nfrom collections import defaultdict\r\nfrom heapq import *\r\nimpor... | [
[
"matplotlib.pyplot.Figure",
"numpy.linspace",
"numpy.sqrt",
"matplotlib.pyplot.subplots",
"numpy.cos",
"numpy.sin",
"matplotlib.animation.FuncAnimation",
"matplotlib.pyplot.tick_params",
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg"
]
] |
liuan0803/YOLOv4-pytorch | [
"354bf1e2a50dc0588fa9d342e783161a335b5606",
"354bf1e2a50dc0588fa9d342e783161a335b5606"
] | [
"make_res_txt.py",
"yolo_save_mAP.py"
] | [
"#-------------------------------------#\n# 调用yolo_save_mAP.py下的YOLO类，\n# 注意要更改yolo_save_mAP里面的类别和入模型的尺寸\n#-------------------------------------#\nfrom yolo_save_mAP import YOLO\nfrom PIL import Image\nimport numpy as np\nimport cv2, os\nimport time\n\n#use which gpu\nos.environ[\"CUDA_VISIBLE_DEVICES\"... | [
[
"numpy.uint8"
],
[
"numpy.expand_dims",
"torch.cat",
"numpy.asarray",
"torch.load",
"torch.from_numpy",
"torch.no_grad",
"numpy.shape",
"torch.cuda.is_available",
"numpy.transpose",
"numpy.floor",
"torch.nn.DataParallel",
"numpy.array"
]
] |
Open-Speech-EkStep/common_scripts | [
"916f01444e028f9111d5499217abf4443bd24017"
] | [
"extract_text/forced_alignment_espeakng.py"
] | [
"import parameters\nfrom aeneas.executetask import ExecuteTask\nfrom aeneas.language import Language\nfrom aeneas.syncmap import SyncMapFormat\nfrom aeneas.task import Task\nfrom aeneas.task import TaskConfiguration\nfrom aeneas.textfile import TextFileFormat\nimport aeneas.globalconstants as gc\nimport pandas as p... | [
[
"pandas.read_csv"
]
] |
nupurkmr9/ss-ood | [
"bab0aea1e322b3ec90a05f7ffe988555255ca8a8"
] | [
"rot_pgd/train_ss.py"
] | [
"# -*- coding: utf-8 -*-\nimport numpy as np\nimport os\nimport argparse\nimport time\nimport torch\nimport torch.nn as nn\nimport torch.backends.cudnn as cudnn\nimport torchvision.transforms as trn\nimport torchvision.datasets as dset\nimport torch.nn.functional as F\nfrom tqdm import tqdm\nfrom models.wrn_with_pe... | [
[
"numpy.rot90",
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.load",
"torch.manual_seed",
"torch.nn.functional.cross_entropy",
"torch.utils.data.DataLoader",
"numpy.cos",
"torch.nn.Linear",
"torch.FloatTensor",
"torch.no_grad"
]
] |
szymanskir/SpeechCommands-RNN | [
"3426674d88245a831f8816e7de11fae196714322"
] | [
"rnnhearer/data_manipulation.py"
] | [
"import numpy as np\nimport scipy.io.wavfile as wavfile\nimport pandas as pd\nfrom keras.callbacks import History\nfrom keras.utils import to_categorical\nfrom pathlib import Path\nfrom sklearn.preprocessing import LabelEncoder\nfrom typing import List, Tuple, Set\nimport random\nfrom .networks import AudioRepresen... | [
[
"numpy.concatenate",
"sklearn.preprocessing.LabelEncoder",
"scipy.io.wavfile.read",
"pandas.DataFrame.from_dict"
]
] |
moshes7/tello | [
"a313759662649e43f53d83c1cae4daa8cd86dd2d"
] | [
"autonomous_tello/scripts/aruco/generate_video_from_images.py"
] | [
"import os\nimport cv2\nimport numpy as np\n\n# --- parameters\nmax_frame_num = None\n# max_frame_num = 300\n\nimages_dir = r'C:\\Users\\Moshe\\Sync\\Projects\\tello\\images\\tello_stream\\2019-10-30_09.43.19'\n# images_dir = r'C:\\Users\\Moshe\\Sync\\Projects\\tello\\images_gestures\\tello_stream\\2019-10-29_01.24... | [
[
"numpy.mod"
]
] |
bennzo/deep_avsr | [
"63830ca2339279066f8ae4640b36ea50a4ea0956"
] | [
"video_only/utils/decoders.py"
] | [
"\"\"\"\nAuthor: Smeet Shah\nCopyright (c) 2020 Smeet Shah\nFile part of 'deep_avsr' GitHub repository available at -\nhttps://github.com/lordmartian/deep_avsr\n\"\"\"\n\nimport torch\nimport numpy as np\nfrom itertools import groupby\n\n\nnp.seterr(divide=\"ignore\")\n\n\n\ndef ctc_greedy_decode(outputBatch, input... | [
[
"numpy.log",
"numpy.arange",
"torch.tensor",
"torch.exp",
"numpy.seterr",
"torch.no_grad",
"torch.cuda.is_available",
"numpy.exp",
"torch.argmax"
]
] |
IanHawke/toy-conslaw | [
"bb93a62f39f4fb4f770bd4ca15105967adf03663",
"bb93a62f39f4fb4f770bd4ca15105967adf03663"
] | [
"toy-conslaw/sr_euler_blast1_fvs.py",
"toy-conslaw/models/euler_gamma_law.py"
] | [
"# Second blast wave test\n# Oscillations are too large - get superluminal v\n\nimport numpy\nfrom models import sr_euler_gamma_law\nfrom bcs import outflow\nfrom simulation import simulation\nfrom methods import fvs_method\nfrom rk import rk3\nfrom grid import grid\nfrom matplotlib import pyplot\n\nNgz = 3\nNpoint... | [
[
"numpy.array",
"matplotlib.pyplot.show"
],
[
"numpy.abs",
"numpy.zeros_like",
"numpy.sqrt",
"numpy.zeros"
]
] |
jechague/transform | [
"3338036a35de8d8fcaa8da294d2041e29ba62a5b",
"3338036a35de8d8fcaa8da294d2041e29ba62a5b",
"3338036a35de8d8fcaa8da294d2041e29ba62a5b"
] | [
"tensorflow_transform/beam/tukey_hh_params_integration_test.py",
"tensorflow_transform/beam/analysis_graph_builder.py",
"tensorflow_transform/beam/analysis_graph_builder_test.py"
] | [
"# Lint as: python3\n# Copyright 2020 Google Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unl... | [
[
"tensorflow.io.FixedLenFeature",
"numpy.array",
"tensorflow.cast",
"tensorflow.as_dtype"
],
[
"tensorflow.compat.as_bytes",
"tensorflow.compat.v1.Graph",
"tensorflow.compat.as_str_any",
"tensorflow.compat.v1.name_scope"
],
[
"tensorflow.lookup.TextFileInitializer",
... |
SauravMaheshkar/FNet-Flax | [
"942cd6b39fce7fe0fbc316eb13bc09ffd582c2ba"
] | [
"tests/test_model.py"
] | [
"import flax.linen as nn\nimport numpy as np\nfrom jax import random\n\nfrom fnet_flax import FNet\n\n\ndef test_instance():\n\n model = FNet(depth=2, dim=32)\n assert isinstance(model, nn.Module)\n\n\ndef test_init():\n\n x = np.random.randn(2, 8, 32)\n init_rngs = {\"params\": random.PRNGKey(0), \"dro... | [
[
"numpy.random.randn"
]
] |
anish-pratheepkumar/anish-pratheepkumar.github.io | [
"a9f4a41ec3452c45077fcb8a83a5a4996fa61e23"
] | [
"models/prednet/test_prednet.py"
] | [
"import copy\nimport os\nimport random\n\nimport numpy as np\nimport tensorflow as tf\nfrom tqdm import tqdm\n\nimport utils.data_generation.data_utils\nfrom experiments import config\nfrom models.prednet import data_utils\nfrom models.prednet.train_prednet import check_action, create_model, print_results\n\n\ndef ... | [
[
"numpy.random.seed",
"numpy.subtract",
"numpy.stack",
"tensorflow.ConfigProto",
"tensorflow.GPUOptions",
"numpy.mean",
"tensorflow.set_random_seed",
"numpy.zeros"
]
] |
jiawu/Roller | [
"a70e350905a59c2254dcefda7ab23c6417cf8f7d",
"a70e350905a59c2254dcefda7ab23c6417cf8f7d"
] | [
"pipelines/run_pipeline_RF_window_scan_100.py",
"scripts/figure4/preprocessing_dream5_invitro.py"
] | [
"import matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\nimport sys\nimport Swing_old\nimport uuid\nimport pickle\n\"\"\"\nThis pipeline scans a range of window sizes for a given inference method and generates roller objects for post analysis.\n\nThis is the 100 node variation of it.\n\"\"\"\nINP... | [
[
"matplotlib.use",
"matplotlib.pyplot.ioff"
],
[
"pandas.read_csv",
"scipy.stats.zscore",
"pandas.DataFrame"
]
] |
hufengchuichui/yolov5-flask | [
"107c828a356cdef05edf9c0ed62c8a6d925b7aa7"
] | [
"ultralytics/yolov5/detect.py"
] | [
"# YOLOv5 🚀 by Ultralytics, GPL-3.0 license\n\"\"\"\nRun inference on images, videos, directories, streams, etc.\n\nUsage:\n $ python path/to/detect.py --source path/to/img.jpg --weights yolov5s.pt --img 640\n\"\"\"\n\nimport argparse\nimport os\nimport sys\nfrom pathlib import Path\n\nimport cv2\nimport numpy ... | [
[
"tensorflow.keras.models.load_model",
"torch.jit.load",
"tensorflow.Graph",
"tensorflow.constant",
"tensorflow.compat.v1.import_graph_def",
"torch.zeros",
"torch.load",
"tensorflow.lite.Interpreter",
"torch.from_numpy",
"torch.tensor",
"torch.no_grad",
"tensorflow.n... |
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