repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
timsainb/spiketoolkit | [
"20f954db6f400f6675f2d843d804d605b77702b1"
] | [
"spiketoolkit/postprocessing/postprocessing_tools.py"
] | [
"import numpy as np\nimport spiketoolkit as st\nimport spikeextractors as se\nfrom sklearn.decomposition import PCA\nfrom pathlib import Path\nimport warnings\nimport shutil\nfrom joblib import Parallel, delayed\nfrom spikeextractors import RecordingExtractor, SortingExtractor\nimport csv\nfrom tqdm import tqdm\nfr... | [
[
"numpy.dot",
"numpy.sqrt",
"numpy.dtype",
"numpy.max",
"numpy.mean",
"numpy.argmin",
"numpy.where",
"numpy.arange",
"numpy.argmax",
"numpy.zeros",
"numpy.min",
"numpy.median",
"numpy.memmap",
"numpy.corrcoef",
"numpy.argsort",
"numpy.array",
"num... |
loriab/qccddb | [
"d9e156ef8b313ac0633211fc6b841f84a3ddde24",
"d9e156ef8b313ac0633211fc6b841f84a3ddde24"
] | [
"qcdb/tests/nwchem_tests/test_prop_dipole_h2o.py",
"qcdb/tests/test_bfs.py"
] | [
"import os\nimport sys\n\nimport numpy as np\nimport pytest\n\nimport qcdb\n\nfrom ..utils import *\n\n# import pprinter as pp\n\n\ndef check_dipole(return_value):\n\n dip_x = -0.0000000000\n dip_y = -0.0000000000\n dip_z = -2.2247923027\n dip_grad = np.array([-0.0000000, -0.000000, -2.2247923027])\n\n ... | [
[
"numpy.array"
],
[
"numpy.asarray"
]
] |
hzyjerry/stable-baselines3 | [
"9dc6c1949fa1f19a1dcdde6858838686ec898412",
"9dc6c1949fa1f19a1dcdde6858838686ec898412"
] | [
"stable_baselines3/common/buffers.py",
"stable_baselines3/common/vec_env/vec_frame_stack.py"
] | [
"import warnings\nfrom abc import ABC, abstractmethod\nfrom typing import Dict, Generator, Optional, Union\n\nimport numpy as np\nimport torch as th\nfrom gym import spaces\n\ntry:\n # Check memory used by replay buffer when possible\n import psutil\nexcept ImportError:\n psutil = None\n\nfrom stable_basel... | [
[
"torch.tensor",
"numpy.random.permutation",
"numpy.random.randint",
"numpy.array",
"numpy.zeros",
"torch.as_tensor"
],
[
"numpy.concatenate",
"numpy.repeat",
"numpy.zeros",
"numpy.roll"
]
] |
manganganath/QuantConnect-Trading-Strategies | [
"207ccdc203bd8a43714e7b9a755823948dec5022",
"207ccdc203bd8a43714e7b9a755823948dec5022"
] | [
"LogesticsRegressionForex_v1.py",
"AUDUSD_LSTM_model.py"
] | [
"import numpy as np\nfrom numpy.random import seed\n\nfrom sklearn.linear_model import LogisticRegression\nimport matplotlib.pyplot as plt\nfrom sklearn.preprocessing import MinMaxScaler\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.model_selection import TimeSeriesSplit\nfrom sklearn.preproce... | [
[
"pandas.concat",
"sklearn.linear_model.LogisticRegression",
"pandas.DataFrame",
"numpy.transpose"
],
[
"pandas.concat",
"numpy.random.seed",
"numpy.reshape",
"pandas.DataFrame",
"sklearn.model_selection.TimeSeriesSplit",
"tensorflow.get_default_graph",
"numpy.array"... |
IgnaceP/IPtools | [
"b940ef9d6c8f059a814fd1e59479123480450792",
"b940ef9d6c8f059a814fd1e59479123480450792"
] | [
"pol2pol.py",
"generalizepoints.py"
] | [
"\"\"\" Reproject a shapely MultiPolygon\n\nThis module reprojects a shapely MultiPolygon based on epsg codes\n\nAuthor: Ignace Pelckmans\n (University of Antwerp, Belgium)\n\n\"\"\"\n\nimport numpy as np\nfrom pyproj import CRS\nfrom pyproj import Transformer\nfrom shapely.geometry import Polygon\nfrom shape... | [
[
"numpy.asarray"
],
[
"numpy.asarray",
"numpy.argsort",
"numpy.unique"
]
] |
idea-iitd/NeuroSED | [
"8df1526046c11f6cd676877a6625958016e039c2"
] | [
"neuro/viz.py"
] | [
"import IPython as ipy\nimport IPython.display\nimport matplotlib.pyplot as plt\nimport networkx as nx\nimport numpy as np\nimport torch\nimport torch_geometric as tg\nimport torch_geometric.data\nimport torch_geometric.utils\n\nfrom . import config, datasets, metrics\n\ndef plot_graph(g, shell=False, **kwargs):\n ... | [
[
"torch.mean",
"torch.max",
"torch.sum",
"matplotlib.pyplot.get_cmap",
"matplotlib.pyplot.plot",
"torch.unique",
"torch.no_grad",
"torch.flatten",
"torch.device",
"torch.tensor",
"matplotlib.pyplot.subplot",
"torch.std",
"torch.ones_like",
"matplotlib.pyplot.... |
davijo/superpoint_graph | [
"0d60fb364bfa37fb70570784899ce46c0296ee22"
] | [
"learning/modules.py"
] | [
"\"\"\"\r\n Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs\r\n http://arxiv.org/abs/1711.09869\r\n 2017 Loic Landrieu, Martin Simonovsky\r\n\"\"\"\r\nfrom __future__ import division\r\nfrom __future__ import print_function\r\nfrom builtins import range\r\n\r\nimport torch\r\nimport to... | [
[
"torch.nn.functional.softmax",
"torch.cat",
"torch.nn.InstanceNorm1d",
"torch.nn.functional.sigmoid",
"torch.nn.Linear",
"torch.nn.functional.tanh",
"torch.nn.functional.linear",
"torch.autograd.Variable"
]
] |
baierxxl/mssdk | [
"c72770ef0a44060db0384937e94f23ebca738872",
"c72770ef0a44060db0384937e94f23ebca738872"
] | [
"mssdk/futures/cot.py",
"mssdk/tool/trade_date_hist.py"
] | [
"#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n\"\"\"\nDate: 2021/1/12 15:06\nDesc: 期货-中国-交易所-会员持仓数据接口\n大连商品交易所、上海期货交易所、郑州商品交易所、中国金融期货交易所\n采集前 20 会员持仓数据;\n建议下午 16:30 以后采集当天数据, 避免交易所数据更新不稳定;\n郑州商品交易所格式分为三类\n大连商品交易所有具体合约的持仓排名, 通过 futures_dce_position_rank 获取\n20171228\nhttp://www.czce.com.cn/cn/DFSStaticFiles/Future... | [
[
"pandas.read_excel",
"pandas.read_csv",
"pandas.DataFrame",
"pandas.read_html"
],
[
"pandas.to_datetime",
"pandas.DataFrame"
]
] |
michaeltashman/Horizon | [
"ee310b34adeb807bbae379a6e1703d0f725f26a9"
] | [
"ml/rl/test/world_model/simulated_world_model.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.\nimport torch\nimport torch.nn as nn\n\n\nclass SimulatedWorldModel(nn.Module):\n \"\"\"\n A world model used for simulation. Underlying is an RNN with fixed\n parameters. Given a sequence of actions and states... | [
[
"torch.zeros",
"torch.cat",
"torch.manual_seed",
"torch.nn.LSTM",
"torch.nn.Linear",
"torch.nn.init.normal_"
]
] |
PSE-TECO-2020-TEAM1/e2e-ml_model-management | [
"7f01a008648e25a29c639a5e16124b2e399eb821"
] | [
"app/ml/objects/imputation/factory.py"
] | [
"from app.ml.objects.imputation import Imputation\nfrom sklearn.impute import SimpleImputer\nfrom pyts.preprocessing import InterpolationImputer\n\nimputer_factory_dict = {\n Imputation.MEAN_IMPUTATION: lambda: SimpleImputer(strategy=\"mean\"),\n Imputation.ZERO_INTERPOLATION: lambda: InterpolationImputer(str... | [
[
"sklearn.impute.SimpleImputer"
]
] |
hroncok/cython | [
"3dc2b9dfc23638fbef2558d619709b5235d5df08"
] | [
"runtests.py"
] | [
"#!/usr/bin/env python\n\nfrom __future__ import print_function\n\nimport atexit\nimport os\nimport sys\nimport re\nimport gc\nimport heapq\nimport locale\nimport shutil\nimport time\nimport unittest\nimport doctest\nimport operator\nimport subprocess\nimport tempfile\nimport traceback\nimport warnings\nimport zlib... | [
[
"numpy.distutils.misc_util.get_info",
"numpy.get_include"
]
] |
terraswat/clusterDb | [
"3ba83cffc2d6172eee7f99b498affa2d2df125d1"
] | [
"cluster/api/scorect.py"
] | [
"from flask_restplus import Resource\nfrom cluster.api.restplus import api\nfrom cluster.scorect import _score_celltypes\nimport pandas as pd\nfrom cluster.api.user import parse_genes\n\nns = api.namespace('scorect')\n\n\ndef read_markers_gmt(filepath):\n \"\"\"\n Read a marker file from a gmt.\n \"\"\"\n... | [
[
"pandas.read_csv",
"pandas.Series"
]
] |
kaushikponnapalli/OpenMDAO | [
"d01fd526e71add4a203b7d32c534e1eab07dafaf",
"d71f86240bd87447b2517b658819a986f1d22f36"
] | [
"openmdao/solvers/nonlinear/broyden.py",
"openmdao/components/tests/test_meta_model_structured_comp.py"
] | [
"\"\"\"\nDefine the BroydenSolver class.\n\nBased on implementation in Scipy via OpenMDAO 0.8x with improvements based on NPSS solver.\n\"\"\"\nimport numpy as np\n\nfrom openmdao.recorders.recording_iteration_stack import Recording\nfrom openmdao.solvers.linesearch.backtracking import BoundsEnforceLS\nfrom openmda... | [
[
"numpy.linalg.norm",
"numpy.full",
"numpy.iscomplexobj",
"numpy.sum",
"numpy.empty"
],
[
"numpy.random.random",
"numpy.sqrt",
"numpy.random.seed",
"numpy.linspace",
"numpy.meshgrid",
"numpy.sin",
"numpy.ones",
"numpy.testing.assert_almost_equal",
"numpy.... |
hefecaso/0980_Proyectos_de_computacion_aplicada_a_IE_1S_2022 | [
"2c8134a290cc7391683703710c9b376d98f12dc3"
] | [
"Tareas/Tarea_9/code/chapter-07/grayscale_histogram.py"
] | [
"# USAGE\n# python grayscale_histogram.py --image ../images/beach.png\n\n# Import the necessary packages\nfrom matplotlib import pyplot as plt\nimport argparse\nimport cv2\n\n# Construct the argument parser and parse the arguments\nap = argparse.ArgumentParser()\nap.add_argument(\"-i\", \"--image\", required = True... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
aidendoherty/biobankAccelerometerAnalysis | [
"735fe063fb8a8bf80bb0514838311a89c10dcbc5"
] | [
"accelerometer/accUtils.py"
] | [
"\"\"\"Module to provide generic utilities for other accelerometer modules.\"\"\"\n\nfrom collections import OrderedDict\nimport datetime\nimport glob\nimport json\nimport math\nimport numpy as np\nimport os\nimport pandas as pd\nimport re\n\nDAYS = ['mon', 'tue', 'wed', 'thur', 'fri', 'sat', 'sun']\nTIME_SERIES_CO... | [
[
"pandas.read_csv",
"pandas.to_datetime",
"pandas.DataFrame",
"pandas.DataFrame.from_dict"
]
] |
lucifersteph/rqalpha | [
"34b2404872203486e19d18b0d4b64e2e589ba414"
] | [
"rqalpha/utils/config.py"
] | [
"# -*- coding: utf-8 -*-\n# 版权所有 2019 深圳米筐科技有限公司（下称“米筐科技”）\n#\n# 除非遵守当前许可，否则不得使用本软件。\n#\n# * 非商业用途（非商业用途指个人出于非商业目的使用本软件，或者高校、研究所等非营利机构出于教育、科研等目的使用本软件）：\n# 遵守 Apache License 2.0（下称“Apache 2.0 许可”），您可以在以下位置获得 Apache 2.0 许可的副本：http://www.apache.org/licenses/LICENSE-2.0。\n# 除非法律有要求或以书面形式达成协议，否则本软件分发... | [
[
"pandas.Timestamp"
]
] |
fks/ntire-dehaze | [
"6d55dd4e11e6f0402ae2be8cbf9eceb613d7b123",
"6d55dd4e11e6f0402ae2be8cbf9eceb613d7b123"
] | [
"src/kf_util.py",
"src/train_dehaze.py"
] | [
"# coding=utf-8\nimport errno\nimport numpy as np\nimport sys\nimport time\nimport os\nimport glob\n\ndef mkdir_p(path):\n\ttry:\n\t\tos.makedirs(path)\n\texcept OSError as exc: # Python >2.5\n\t\tif exc.errno == errno.EEXIST and os.path.isdir(path):\n\t\t\tpass\n\t\telse:\n\t\t\traise\n\ndef find_best_weights(log... | [
[
"numpy.asarray",
"numpy.max",
"numpy.min"
],
[
"tensorflow.ConfigProto",
"numpy.hstack",
"sklearn.model_selection.train_test_split",
"tensorflow.Session"
]
] |
riskaware-ltd/Stone-Soup | [
"ef3a2fb7e121c00dcf458e370794db3785b732e3"
] | [
"stonesoup/models/transition/linear.py"
] | [
"# -*- coding: utf-8 -*-\nimport math\nfrom functools import lru_cache\n\nimport scipy as sp\nfrom scipy.linalg import block_diag\nfrom scipy.integrate import quad\nfrom scipy.stats import multivariate_normal\n\nfrom ...base import Property\nfrom ...types.array import CovarianceMatrix\nfrom ..base import (LinearMod... | [
[
"scipy.linalg.block_diag",
"scipy.zeros",
"scipy.diag",
"scipy.integrate.quad",
"scipy.sin",
"scipy.array",
"scipy.power",
"scipy.exp",
"scipy.cos"
]
] |
Zarbokk/ping360_sonar | [
"b4873a318bffbc2732ebead3592b7bc48b46a136"
] | [
"src/ping360_sonar/node.py"
] | [
"#!/usr/bin/env python\n\nfrom math import cos, pi, sin\n\nimport numpy as np\nimport rospy\nimport cv2\n\nfrom cv_bridge import CvBridge, CvBridgeError\nfrom dynamic_reconfigure.server import Server\nfrom sensor_msgs.msg import Image\nfrom sensor_msgs.msg import LaserScan\n\nfrom ping360_sonar.cfg import sonarConf... | [
[
"numpy.zeros"
]
] |
bswood9321/PHYS-3210 | [
"d780cac166688338ce91099cba4a4f6628430647"
] | [
"Exam2/Exam2_Q1_BSW.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Nov 3 23:54:26 2019\n\n@author: Brandon\n\"\"\"\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\nx = np.linspace(-10,10,100)\ny = (5/4)*x -2\n\nplt.plot(x,y)\nplt.grid()\nplt.title(\"A linear equation; Y=5/4X-2\")\nplt.show()\n\ny1=x**3-4\n\nplt.plot(x,y1... | [
[
"matplotlib.pyplot.title",
"numpy.linspace",
"numpy.cos",
"numpy.sin",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.show"
]
] |
cyriel/models | [
"33cca6c3e09be4e434f39bd337d7b1fbe3672872"
] | [
"research/object_detection/inputs.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.compat.v1.reduce_all",
"tensorflow.compat.v1.concat",
"tensorflow.compat.v1.random.uniform",
"tensorflow.compat.v1.equal",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.constant",
"tensorflow.compat.v1.string_to_hash_bucket_fast",
"tensorflow.compat.v1.ones",
... |
srxh/tensorflow | [
"a2ecddb2c140384e9c7931e1704bfe7b347a26ec",
"a1e5d73663152b0d7f0d9661e5d602b442acddba"
] | [
"tensorflow/python/eager/def_function_test.py",
"tensorflow/python/keras/layers/preprocessing/category_encoding.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.python.ops.variable_scope.variable_creator_scope",
"tensorflow.python.ops.resource_variable_ops.var_is_initialized_op",
"tensorflow.python.ops.array_ops.placeholder",
"tensorflow.python.ops.variables.Variable",
"tensorflow.python.ops.array_ops.zeros",
"tensorflow.python.ops.mat... |
olimjonibr/seqlearn | [
"5ea3f5d7a455df639149382061347856cf511cd9"
] | [
"seqlearn/_utils/tests/test_safeadd.py"
] | [
"from numpy.testing import assert_array_equal\n\nimport numpy as np\nfrom scipy.sparse import csr_matrix\n\nfrom seqlearn._utils import safe_add\n\n\ndef test_safe_add():\n X1 = np.zeros((4, 13), dtype=np.float64)\n X2 = X1.copy()\n Y = csr_matrix(np.arange(4 * 13, dtype=np.float64).reshape(4, 13) % 4)\n\n... | [
[
"numpy.testing.assert_array_equal",
"numpy.arange",
"numpy.zeros"
]
] |
pyannote/pyannote-algorithms | [
"5a646fdaf3250527569e3f9a1c666d6397e53ce4"
] | [
"pyannote/algorithms/clustering/hac/linkage.py"
] | [
"#!/usr/bin/env python\n# encoding: utf-8\n\n# The MIT License (MIT)\n\n# Copyright (c) 2012-2017 CNRS\n\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, includin... | [
[
"numpy.mean"
]
] |
kai-storms/omega_format | [
"745f67d774d2da04201de9fe24fa24468a8b191b",
"745f67d774d2da04201de9fe24fa24468a8b191b",
"745f67d774d2da04201de9fe24fa24468a8b191b"
] | [
"omega_format/perception/converter.py",
"omega_format/weather/cloudiness.py",
"omega_format/visualization/visualizer.py"
] | [
"import os\nimport random\nimport tempfile\nfrom collections import UserDict\nfrom copy import deepcopy\nfrom json import load\nfrom pathlib import Path\nfrom typing import Union, Optional\n\nimport h5py\nimport numpy as np\nimport omega_format\nimport pyproj\nimport typer\nfrom PyQt5 import QtWidgets\nfrom PyQt5.Q... | [
[
"numpy.arange",
"numpy.deg2rad",
"numpy.empty",
"numpy.full"
],
[
"numpy.array",
"numpy.mean"
],
[
"numpy.diff"
]
] |
jgodwin/MMdnn | [
"53546fa91894a7cc570c39db8b396e937b27c66f"
] | [
"mmdnn/conversion/tensorflow/tensorflow_frozenparser.py"
] | [
"import numpy as np\nimport tensorflow\nfrom tensorflow.python.framework import tensor_util\nfrom tensorflow.core.framework import attr_value_pb2\nfrom mmdnn.conversion.tensorflow.tensorflow_graph import TensorflowGraph\nimport mmdnn.conversion.common.IR.graph_pb2 as graph_pb2\nfrom mmdnn.conversion.common.IR.graph... | [
[
"tensorflow.python.framework.tensor_util.MakeNdarray",
"tensorflow.Graph",
"tensorflow.import_graph_def",
"tensorflow.python.tools.strip_unused_lib.strip_unused",
"tensorflow.python.platform.gfile.GFile",
"tensorflow.placeholder",
"tensorflow.reset_default_graph",
"tensorflow.Sessi... |
duoergun0729/MIAA | [
"5451f7d78462c45533d2c5f78e8c54a60ed13721"
] | [
"model/model/fccnet_location.py"
] | [
"from __future__ import print_function\nimport keras\nfrom keras.regularizers import l2\nfrom keras import backend as K\nfrom keras.models import Model\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Activation, Input, concatenate\nimport numpy as np\nnp.random.seed(10000)\n\nimport l... | [
[
"numpy.random.seed"
]
] |
chipmyersjr/great_expectations | [
"fa88b0c0fdd98a80fe9e4f2422bd3f7b47ad904f"
] | [
"great_expectations/core/__init__.py"
] | [
"import datetime\nimport json\nimport logging\nimport warnings\nfrom collections import namedtuple\nfrom copy import deepcopy\n\nfrom dateutil.parser import ParserError as DateUtilParserError\nfrom dateutil.parser import parse\nfrom IPython import get_ipython\nfrom marshmallow import Schema, ValidationError, fields... | [
[
"numpy.isnan"
]
] |
Dundj/Convex_Geomotry | [
"38507824d97270b3e4ead194a16148ff6158b59f"
] | [
"Tests/Laminar/Accuracy_Test/Channel_Re_2000/Results/python_matplotlib_script.py"
] | [
"#!/bin/python\n# this python template is used to plot data from ??????.dat files\n# produced by test_build.sh(Process accuracy test)\n# it is executed automatically by test_build.sh script\n#\n# You can also launch it manually according to readme_python_matplotlib_script\n\n# Header\nimport numpy as... | [
[
"matplotlib.pyplot.legend",
"numpy.logspace",
"matplotlib.lines.Line2D",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"numpy.append",
"numpy.shape",
"matplotlib.pyplot.subplots_adjust",
"numpy.savetxt",
"numpy.array",
"matplotlib.offsetbox.AnchoredText",
... |
proloyd/StabBB | [
"c90f50d615d60720c4c72382af4bdb7018a84de1"
] | [
"stabbb/stab_bb.py"
] | [
"import numpy as np\nimport pdb\n\ndef stab_BB(\n x0,\n costFn,\n gradFn,\n bb = 1,\n deltaUpdateStrategy = 'adaptative',\n deltaInput = 1e6,\n c = 0.2,\n maxIt = 10000,\n tol = 1e-7,\n verbose=False,\n):\n \"\"\" Stabilized Barzilai-Borwein Method for unconstrained optimization\n\n... | [
[
"numpy.argmin",
"numpy.linalg.norm"
]
] |
gaowexu/pointpillar | [
"34926ea7f09dcdb77439a2434281d948bf2b02cb"
] | [
"src/point_pillars.py"
] | [
"import torch\nfrom torch import nn\nfrom point_pillar_net import PointPillarFeatureNet\nfrom point_pillars_scatter import PointPillarScatter\nfrom point_pillars_backbone import PointPillarBackbone\nfrom point_pillars_anchor_head_single import PointPillarAnchorHeadSingle\n\n\nclass PointPillars(nn.Module):\n def... | [
[
"torch.ones",
"torch.zeros",
"torch.cat",
"torch.cuda.is_available",
"numpy.load",
"numpy.where"
]
] |
ncrubin/Cirq | [
"24772f4713338247d9fb61fc36fc81984731c2ac"
] | [
"cirq/contrib/paulistring/pauli_interaction_gate.py"
] | [
"# Copyright 2018 The Cirq Developers\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law o... | [
[
"numpy.diag",
"numpy.eye",
"numpy.array",
"numpy.kron"
]
] |
mcx/pytorch | [
"f09c696ecda155c42006f85d2687445dfb24774f"
] | [
"test/jit/test_save_load_for_op_version.py"
] | [
"# Owner(s): [\"oncall: jit\"]\n\nfrom itertools import product as product\nimport io\nimport os\nimport sys\nimport hypothesis.strategies as st\nfrom hypothesis import example, settings, given\nfrom typing import Union\n\nimport torch\n\n# Make the helper files in test/ importable\npytorch_test_dir = os.path.dirna... | [
[
"torch.jit.save",
"torch.div",
"torch.jit.load",
"torch.linspace",
"torch.logspace",
"torch.empty",
"torch.jit.mobile._load_for_lite_interpreter",
"torch.true_divide",
"torch.tensor",
"torch.divide",
"torch.rand",
"torch.stft"
]
] |
feizhihui/deepnlp | [
"cc6647d65ec39aadd35e4a4748da92df5b79bd48"
] | [
"deepnlp/pos_tagger.py"
] | [
"#!/usr/bin/python\n# -*- coding:utf-8 -*-\n'''\nPOS module global function 'predict'\n@author: xichen ding\n@date: 2016-11-15\n'''\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals # compatible with python3 uni... | [
[
"tensorflow.global_variables",
"tensorflow.global_variables_initializer",
"numpy.argmax",
"tensorflow.Session",
"tensorflow.variable_scope",
"tensorflow.train.Saver"
]
] |
koukyo1994/tabular-data-analysis-pipeline | [
"d4007be7dceb8bf86f7d9bad3fd3e2e5dc3ed2b2"
] | [
"src/core/callbacks/fe.py"
] | [
"import gc\n\nimport numpy as np\nimport pandas as pd\n\nimport src.utils as utils\n\nfrom typing import Optional\n\nfrom scipy.io import savemat\nfrom scipy.sparse import csr_matrix, hstack\n\nfrom src.core.state import State\nfrom src.core.callbacks import Callback, CallbackOrder\n\n\n# on_fe_start\nclass AssignT... | [
[
"pandas.concat",
"scipy.sparse.csr_matrix",
"numpy.save",
"scipy.io.savemat",
"scipy.sparse.hstack"
]
] |
slava-kerner/cityfinder | [
"f4bd1b53b6970492f168dc13e990e56d7e75e2e4"
] | [
"tests/test_city_detector.py"
] | [
"import os\nimport itertools\n\nimport rasterio\nfrom PIL import Image\nimport numpy as np\nimport unittest\nfrom cityfinder.city_detector import CityDetector\nfrom cityfinder.city_vector import CityVector, israel, israel_utm, match\n\n\nGEOGRAPHIC = {'init': 'EPSG:4326'}\nUTM = {'init': 'EPSG:32636'}\n\n\nclass Te... | [
[
"numpy.arange",
"numpy.abs"
]
] |
estevaogalvao/Deep-Learning-detect-faces-movies | [
"43aaf73bee753bed8fd1e1026032185517cb105c",
"43aaf73bee753bed8fd1e1026032185517cb105c"
] | [
"Reconhecimento-Facial-ESTEVAO/venv/Lib/site-packages/mtcnn/box_utils.py",
"Reconhecimento-Facial-ESTEVAO/venv/Lib/site-packages/mtcnn/detector.py"
] | [
"import cv2\nimport numpy as np\n\n\ndef nms(boxes, overlap_threshold=0.5, mode='union'):\n \"\"\"Non-maximum suppression.\n\n Arguments:\n boxes: a float numpy array of shape [n, 5],\n where each row is (xmin, ymin, xmax, ymax, score).\n overlap_threshold: a float number.\n mo... | [
[
"numpy.hstack",
"numpy.expand_dims",
"numpy.maximum",
"numpy.minimum",
"numpy.zeros_like",
"numpy.argsort",
"numpy.zeros",
"numpy.where"
],
[
"numpy.expand_dims",
"numpy.round",
"torch.no_grad",
"torch.FloatTensor",
"numpy.where",
"numpy.vstack"
]
] |
Ektagavas/avalanche | [
"6671dc748078532709aad07b9e28ad6c903ab12b"
] | [
"avalanche/training/strategies/base_strategy.py"
] | [
"################################################################################\n# Copyright (c) 2021 ContinualAI. #\n# Copyrights licensed under the MIT License. #\n# See the accompanying LICENSE file for terms. ... | [
[
"torch.utils.data.DataLoader",
"torch.nn.CrossEntropyLoss",
"torch.no_grad"
]
] |
jrmh96/algorithm_toolkit | [
"4a39e26d89973c6d1e229952f46d413b93c27df9"
] | [
"myproject/assets/datasets.py"
] | [
"import glob\nimport math\nimport os\nimport random\nimport shutil\nfrom pathlib import Path\n\nimport cv2\nimport numpy as np\nimport torch\nfrom torch.utils.data import Dataset\nfrom tqdm import tqdm\n\nclass LoadWebcam: # for inference\n def __init__(self, img_size=416):\n self.cam = cv2.VideoCapture(... | [
[
"numpy.ascontiguousarray",
"numpy.mod"
]
] |
blucap/BankHoldingCompanyData | [
"056aa433001240eac86cd9c0d3d757f769f6bbaf"
] | [
"mdrm_scraper.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Dec 30 16:45:43 2018\n\n@author: martien\n# https://linuxhint.com/selenium-web-automation-python/\n\"\"\"\nimport pandas as pd\nimport os\n# from urllib.request import urlopen\nfrom bs4 import BeautifulSoup\nfrom selenium import webdriver\n# f... | [
[
"pandas.isnull",
"pandas.concat",
"pandas.DataFrame"
]
] |
Subhanimuhammed/alphalens | [
"a221fa85cfc1ae9a716d30d539839971051a2649"
] | [
"alphalens/tests/test_utils.py"
] | [
"#\n# Copyright 2018 Quantopian, Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or... | [
[
"pandas.concat",
"pandas.Series",
"pandas.util.testing.assert_series_equal",
"pandas.DataFrame",
"pandas.Timedelta",
"pandas.util.testing.assert_frame_equal",
"pandas.MultiIndex.from_product",
"pandas.date_range",
"pandas.Timestamp"
]
] |
motleystate/moonstone | [
"37c38fabf361722f7002626ef13c68c443ace4ac"
] | [
"moonstone/plot/metadata.py"
] | [
"import pandas as pd\nfrom typing import Optional\n\nfrom moonstone.plot.graphs.bargraph import (\n BarGraph\n)\nfrom moonstone.plot.graphs.histogram import Histogram\nfrom moonstone.utils.plot import (\n add_x_to_plotting_options,\n add_default_titles_to_plotting_options\n)\n\n\nclass PlotMetadataStats:\n... | [
[
"pandas.value_counts"
]
] |
ntnuiotenergy/BattPower | [
"46d183089aae37ffe5bff19f64aae39663e15c7a"
] | [
"Make_Tab_Files_BatPower.py"
] | [
"from pyomo.environ import *\r\nimport pandas as pd\r\n\r\nmodel = AbstractModel()\r\nmodel.is_constructed()\r\n\r\n\r\ndef read_file(excel,sheet,columns):\r\n input_excel = pd.ExcelFile(excel)\r\n input_sheet = pd.read_excel(input_excel, sheet, skiprows=1)\r\n\r\n #First make it so it takes all the rows a... | [
[
"pandas.read_excel",
"pandas.Series",
"pandas.ExcelFile",
"pandas.DataFrame"
]
] |
imelekhov/HNDesc | [
"47680371c0758518a66d5a12f29dc9ded6ae790d",
"47680371c0758518a66d5a12f29dc9ded6ae790d"
] | [
"data/utils.py",
"assets/detectors/base_detector.py"
] | [
"import numpy as np\nimport math\nimport random\nimport cv2\nimport torch\nfrom assets.detectors.detector import LocalDetector\n\n\ndef ssc(keypoints, num_ret_points, tolerance, cols, rows):\n # https://github.com/BAILOOL/ANMS-Codes\n exp1 = rows + cols + 2 * num_ret_points\n exp2 = (4 * cols + 4 * num_ret... | [
[
"numpy.sqrt",
"numpy.cos",
"numpy.sin",
"torch.FloatTensor",
"torch.rand",
"numpy.float32",
"torch.stack",
"numpy.array"
],
[
"numpy.random.randint",
"torch.ones",
"torch.cat"
]
] |
reynoldsnlp/python-alignment | [
"1995d2aac4e593d62e4c7125ac6a4545dcb5762e"
] | [
"alignment/sequencealigner.py"
] | [
"from six import text_type\nfrom six.moves import range\n\ntry:\n import numpypy as numpy\nexcept ImportError:\n import numpy\nfrom abc import ABCMeta\nfrom abc import abstractmethod\n\nfrom .sequence import GAP_CODE\nfrom .sequence import EncodedSequence\n\n\n# Scoring ---------------------------------------... | [
[
"numpy.zeros"
]
] |
unsignedrant/rlalgorithms-tf2 | [
"9bbd4ba62873044cf7bda5ac01d2d625f1e32e67",
"9bbd4ba62873044cf7bda5ac01d2d625f1e32e67"
] | [
"rlalgorithms_tf2/utils/common.py",
"rlalgorithms_tf2/trpo/agent.py"
] | [
"import configparser\nimport os\nimport re\nfrom collections import deque\nfrom pathlib import Path\n\nimport cv2\nimport gym\nimport numpy as np\nimport pandas as pd\nimport pyarrow as pa\nimport pyarrow.parquet as pq\nimport rlalgorithms_tf2\nfrom gym.spaces import Box, Discrete\nfrom matplotlib import pyplot as ... | [
[
"matplotlib.pyplot.legend",
"numpy.expand_dims",
"matplotlib.pyplot.title",
"tensorflow.keras.models.Model",
"numpy.stack",
"matplotlib.pyplot.plot",
"pandas.read_parquet",
"tensorflow.keras.optimizers.Adam",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"numpy.... |
Risto90/gpt-2 | [
"fee186261f7691f501995924c8e27da3ffc78bb1"
] | [
"train.py"
] | [
"#!/usr/bin/env python3\n# Usage:\n# PYTHONPATH=src ./train --dataset <file|directory|glob>\n\nimport argparse\nimport json\nimport os, sys\nimport numpy as np\nimport tensorflow.compat.v1 as tf\nimport tensorflow as tf2\nimport time\nimport tqdm\n\nif tf.VERSION >= '2':\n tf.disable_eager_execution()\n tf.c... | [
[
"tensorflow.compat.v1.train.AdamOptimizer",
"tensorflow.compat.v1.summary.merge",
"tensorflow.compat.v1.train.latest_checkpoint",
"tensorflow.compat.v1.config.experimental.enable_tensor_float_32_execution",
"tensorflow.compat.v1.trainable_variables",
"tensorflow.compat.v1.global_variables_... |
jaycedowell/bifrost | [
"9cedf6dee7d5b66f9a9221f8969826c05c6a2056"
] | [
"python/bifrost/blocks/transpose.py"
] | [
"\n# Copyright (c) 2016-2021, The Bifrost Authors. All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions\n# are met:\n# * Redistributions of source code must retain the above copyright\n# notice, this lis... | [
[
"numpy.transpose"
]
] |
TEAlab/DPSpark | [
"4d53ee13b03e2e12119c28fe2b2241ad20231eac",
"4d53ee13b03e2e12119c28fe2b2241ad20231eac"
] | [
"DPSparkImplementations/paf_collect_broadcast.py",
"DPSparkImplementations/ge_collect_broadcast.py"
] | [
"__author__ = \"Zafar Ahmad, Mohammad Mahdi Javanmard\"\n__copyright__ = \"Copyright (c) 2019 Tealab@SBU\"\n__license__ = \"MIT\"\n__version__ = \"1.0.0\"\n__maintainer__ = \"Zafar Ahmad\"\n__email__ = \"zafahmad@cs.stonybrook.edu\"\n__status__ = \"Development\"\n\nimport numpy as np\nimport glob\nimport paf_kernel... | [
[
"numpy.memmap"
],
[
"numpy.memmap"
]
] |
kristery/dmcontrol-generalization-benchmark | [
"c732d3292e23ef70b9a5e1a9f573b51a5195d28d"
] | [
"src/algorithms/sac_exp.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom copy import deepcopy\nimport utils\nimport algorithms.modules as m\n\n\nclass SAC_EXP(object):\n def __init__(self, obs_shape, action_shape, args):\n self.discount = args.discount\n s... | [
[
"torch.optim.Adam",
"numpy.log",
"torch.min",
"torch.nn.functional.mse_loss",
"torch.no_grad",
"torch.FloatTensor",
"numpy.prod",
"numpy.array"
]
] |
WEHI-Proteomics/ms_deisotope | [
"24a289a7903e033b8b6cf6e3a1e6931ab75668b3"
] | [
"ms_deisotope/feature_map/map_viz.py"
] | [
"from itertools import cycle\ntry:\n from matplotlib import pyplot as plt\n from matplotlib import patches as mpatches, colors as mcolors\nexcept (RuntimeError, ImportError):\n pass\nimport numpy as np\n\n\nfrom .profile_transform import interpolate, smooth_leveled\n\n\nEllipse = mpatches.Ellipse\nFancyBbo... | [
[
"numpy.random.rand",
"numpy.argmax",
"matplotlib.pyplot.subplots",
"matplotlib.patches.BoxStyle.Round"
]
] |
robinsingh1/squash | [
"44dd13330f4f6ea7311b82333cc505051265a2b5"
] | [
"question_generation/train.py"
] | [
"# Copyright (c) 2019-present\n# Original codebase written by HuggingFace Inc. (https://github.com/huggingface/transfer-learning-conv-ai)\n# Forked and modified by Kalpesh Krishna (http://martiansideofthemoon.github.io/)\n\nimport os\nimport math\nimport logging\nfrom pprint import pformat\nfrom collections import ... | [
[
"torch.nn.CrossEntropyLoss",
"torch.distributed.init_process_group",
"torch.utils.data.distributed.DistributedSampler",
"torch.cuda.set_device",
"torch.utils.data.TensorDataset",
"torch.utils.data.DataLoader",
"torch.tensor",
"torch.no_grad",
"torch.device",
"torch.distribu... |
LuChungYing/yt8mtest | [
"07e54b387ee027cb58b0c14f5eb7c88cfa516d58",
"07e54b387ee027cb58b0c14f5eb7c88cfa516d58",
"07e54b387ee027cb58b0c14f5eb7c88cfa516d58"
] | [
"all_frame_models/logistic_model.py",
"all_frame_models/lstm_memory_normalization_model.py",
"all_frame_models/lstm_attention_max_pooling_model.py"
] | [
"import sys\nimport models\nimport model_utils\nimport math\nimport numpy as np\nimport video_level_models\nimport tensorflow as tf\nimport utils\nimport tensorflow.contrib.slim as slim\nfrom tensorflow import flags\nFLAGS = flags.FLAGS\n\nclass FrameLevelLogisticModel(models.BaseModel):\n\n def create_model(self,... | [
[
"tensorflow.contrib.slim.l2_regularizer",
"tensorflow.reduce_sum",
"tensorflow.tile",
"tensorflow.expand_dims"
],
[
"tensorflow.nn.l2_normalize",
"tensorflow.nn.dynamic_rnn",
"tensorflow.reduce_mean",
"tensorflow.maximum",
"tensorflow.contrib.rnn.BasicLSTMCell",
"tensor... |
Yuxing-Wang-THU/EWC | [
"06d8f0eeeba368c07100c428d6a4b4a87648d378"
] | [
"visual.py"
] | [
"import numpy as np\nfrom torch.cuda import FloatTensor as CUDATensor\n\n_WINDOW_CASH = {}\n\n\ndef visualize_image(vis, tensor, name, label=None, w=250, h=250,\n update_window_without_label=False):\n tensor = tensor.cpu() if isinstance(tensor, CUDATensor) else tensor\n title = name + ('-{}... | [
[
"numpy.array",
"numpy.column_stack"
]
] |
beyondhtx/awd-lstm-lm | [
"9bce8026d9be147b7ee7d95aaaef8e1c2f808cd8"
] | [
"pointer.py"
] | [
"import argparse\nimport time\nimport math\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\n\nimport data\nimport model\n\nfrom utils import batchify, get_batch, repackage_hidden\n\nparser = argparse.ArgumentParser(description='PyTorch PennTreeBank RNN/LSTM Language Mod... | [
[
"torch.nn.CrossEntropyLoss",
"torch.nn.functional.softmax",
"torch.mv",
"torch.load",
"torch.from_numpy",
"torch.log",
"numpy.zeros",
"torch.autograd.Variable"
]
] |
amacd31/pypi_download_counter | [
"10c0c239185d0c76dbb0717561b4548439847cc6"
] | [
"count.py"
] | [
"from datetime import date\nimport pandas as pd\nimport requests\n\nfrom phildb.database import PhilDB\nfrom phildb.exceptions import DuplicateError\n\nMEASURANDS = ['last_day', 'last_week', 'last_month']\n\ndb = PhilDB('pypi_downloads')\n\ndef get_pypi_info(package_name):\n r = requests.get('https://pypi.python... | [
[
"pandas.Series"
]
] |
Alisa-lisa/TrackMeCore | [
"503b072fef92a5441777f6f473a443b12321f7c9"
] | [
"trackme/tracking/analytics/multifactor_analysis.py"
] | [
"\"\"\" analysis of interaction of multiple factors \"\"\"\nfrom typing import List, Optional\nfrom trackme.tracking.types.tracking import TrackingActivity as TA\nimport scipy.stats as stats\nimport numpy as np\n\n\ndef _avg_estimation(date, array: List[TA]) -> Optional[int]:\n estimations = [\n item.esti... | [
[
"scipy.stats.pearsonr",
"numpy.array",
"numpy.mean"
]
] |
debowin/nn4nlp-code | [
"a599c8bd11374a205e6f1007a22b26855f02e3bd"
] | [
"08-condlm/batched_enc_dec_pytorch.py"
] | [
"import time\n\nfrom collections import defaultdict\nimport random\nimport math\nimport sys\nimport argparse\n\nimport torch\nfrom torch import nn\nfrom torch.autograd import Variable\nfrom bleu import bleu, bleu_stats\nimport numpy as np\n\n\n# some of this code borrowed from Qinlan Shen's attention from the MT cl... | [
[
"torch.nn.CrossEntropyLoss",
"torch.nn.Dropout",
"torch.LongTensor",
"torch.load",
"torch.nn.LSTM",
"torch.zeros",
"torch.nn.Embedding",
"numpy.max",
"torch.nn.Linear",
"torch.cuda.is_available",
"numpy.array",
"torch.save"
]
] |
muzishen/VIPriors-Object-Detection-Challenge | [
"e885411025ae3817e0106144935b9425e49d77fc"
] | [
"mmdection/mmdet/models/roi_heads/bbox_heads/convfc_bbox_head.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom mmcv.cnn import ConvModule\n\nfrom mmdet.models.builder import HEADS\nfrom .bbox_head import BBoxHead\n\nclass Mish(nn.Module):\n def __init__(self):\n super(Mish, self).__init__()\n\n def forward(self, input):\n return ... | [
[
"torch.nn.init.constant_",
"torch.nn.ModuleList",
"torch.nn.Linear",
"torch.nn.init.xavier_uniform_",
"torch.nn.ReLU",
"torch.nn.functional.softplus"
]
] |
tmthyln/triplet-net-keras | [
"2235cd2b0d813b309659c2a6714fd2e8c43dbfaa"
] | [
"test.py"
] | [
"import keras.utils as ku\nimport matplotlib.pyplot as plt\n\nfrom data import BeeLoader\nfrom model import build_model\n\n\nif __name__ == '__main__':\n bee_data = BeeLoader()\n for i, (images, ids) in enumerate(bee_data.generator(6)):\n print('images shape: ', images.shape)\n print('ids: ', id... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.show"
]
] |
Septaris/das2py | [
"ee657afe706f4aec6e016b17b63a093ed271f7f6"
] | [
"test/TestSortMinimal.py"
] | [
"\"\"\"Testing Dataset sorting algorithms\"\"\"\n\nimport sys\nimport numpy as np\nimport das2\n\n# Make a test dataset in the style of a sweep frequency radar sounder.\n# This dataset will have values occupying the parameter spaces:\n#\n# Time, Pulse Frequency, Range, and Spectral Density\n#\n# That will be ma... | [
[
"numpy.all",
"numpy.arange",
"numpy.array"
]
] |
rodolfolotte/bdc-collection-builder | [
"62583f6c25bca79e7e1b5503bc6308298838c877"
] | [
"bdc_collection_builder/collections/sentinel/harmonization.py"
] | [
"# Python Native\nimport glob\nimport logging\nimport os\nimport re\nimport shutil\nimport xml.etree.ElementTree as ET\n\n# 3rd-party\nfrom osgeo import gdal, osr, ogr\nfrom pathlib import Path\nimport numpy\n\n# BDC Scripts\nfrom ...config import Config\nfrom ..nbar import process_NBAR\nfrom ..utils import load_im... | [
[
"numpy.empty"
]
] |
deeplearning-wisc/vos | [
"25eec0dd1af06bcabccc4b20e8f338bf5de909bb"
] | [
"detection/modeling/roihead_gmm.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\nimport inspect\nimport logging\nimport numpy as np\nfrom typing import Dict, List, Optional, Tuple\nimport torch\nfrom torch import nn\nimport torch.nn.functional as F\nfrom sklearn import covariance\n\nfrom detectron2.config import configurable\nfrom detectron2.... | [
[
"torch.nn.init.uniform_",
"torch.nn.CrossEntropyLoss",
"torch.max",
"torch.empty",
"torch.cat",
"torch.zeros",
"torch.eye",
"torch.zeros_like",
"torch.exp",
"torch.nn.Linear",
"torch.nn.functional.relu",
"torch.no_grad",
"numpy.mean",
"torch.log",
"torch... |
sso0530/Keras-FasterRCNN | [
"d32920c5288abc77a5bb1db060f5861310a270e2"
] | [
"train_frcnn.py"
] | [
"from __future__ import division\nimport random\nimport pprint\nimport sys\nimport time\nimport numpy as np\nfrom optparse import OptionParser\nimport pickle\nimport os\n\nimport tensorflow as tf\nfrom keras import backend as K\nfrom keras.optimizers import Adam, SGD, RMSprop\nfrom keras.layers import Input\nfrom k... | [
[
"numpy.random.choice",
"numpy.mean",
"tensorflow.Summary",
"numpy.zeros",
"numpy.where",
"numpy.random.randint"
]
] |
andyfaff/refnx-models | [
"9d322040a1be3738e5d9246a1eb1cf0350be3c08"
] | [
"polymer_brushes/FreeformVFP.py"
] | [
"import numpy as np\n\nfrom scipy.interpolate import PchipInterpolator as Pchip\nfrom scipy.integrate import simps\n\nfrom refnx.reflect import Structure, Component, SLD, Slab\nfrom refnx.analysis import Parameters, Parameter, possibly_create_parameter\n\nimport warnings\n\n\nEPS = np.finfo(float).eps\n\n\nclass Fr... | [
[
"numpy.linspace",
"numpy.clip",
"numpy.array_equal",
"numpy.cumsum",
"numpy.finfo",
"numpy.all",
"numpy.concatenate",
"numpy.size",
"numpy.cumprod",
"scipy.integrate.simps",
"numpy.array"
]
] |
caetera/DeepLC | [
"18fb8c39e0f80576dee0c1ecff0b6738968f2692"
] | [
"deeplc/deeplc.py"
] | [
"\"\"\"\nMain code used to generate LC retention time predictions.\n\nThis provides the main interface. For the library versions see the .yml file\n\"\"\"\n\n\n__author__ = [\"Robbin Bouwmeester\", \"Ralf Gabriels\"]\n__license__ = \"Apache License, Version 2.0\"\n__maintainer__ = [\"Robbin Bouwmeester\", \"Ralf Ga... | [
[
"tensorflow.keras.models.load_model",
"tensorflow.keras.backend.get_session",
"numpy.arange",
"numpy.median",
"pandas.DataFrame",
"numpy.stack",
"tensorflow.keras.activations.relu",
"numpy.argmax",
"tensorflow.keras.backend.clear_session",
"tensorflow.config.threading.set_i... |
ecobee/building-controls-simulator | [
"c4256224d5b2e171417b60069ccc97dde44de342"
] | [
"src/python/BuildingControlsSimulator/Simulator/Simulation.py"
] | [
"# created by Tom Stesco tom.s@ecobee.com\n\nimport os\nimport logging\nimport time\n\nimport pandas as pd\nimport numpy as np\nimport attr\nfrom tqdm import trange\n\nfrom BuildingControlsSimulator.DataClients.DataStates import STATES\nfrom BuildingControlsSimulator.OutputAnalysis.OutputAnalysis import OutputAnaly... | [
[
"numpy.arange",
"pandas.Timestamp"
]
] |
ProtossDragoon/tensorflow | [
"f349c99e2ea30e8f75ce2c1ee0967e888d24b5de"
] | [
"tensorflow/python/compiler/tensorrt/trt_convert.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.core.protobuf.meta_graph_pb2.MetaGraphDef",
"tensorflow.python.grappler.tf_optimizer.OptimizeGraph",
"tensorflow.python.framework.convert_to_constants.convert_variables_to_constants_v2",
"tensorflow.core.protobuf.config_pb2.GraphOptions",
"tensorflow.python.platform.tf_logging.erro... |
wy36/Networks | [
"2268fcaa79ca61e679176d2c59491e14c083e712"
] | [
"Graph.py"
] | [
"from collections import Counter\nfrom pprint import pprint\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nimport watermark\n\n\n\nclass Graph:\n def __init__(self, directed=False):\n self._nodes = {}\n self._edges = {}\n self._directed = directed\n\n\ndef add_method(cls):\n de... | [
[
"numpy.array",
"numpy.mean"
]
] |
anson0221/NMT-with-bert | [
"ba6ed592ca0677667a1ef8df0be6d9b5a2aa60f5"
] | [
"train.py"
] | [
"from torch.utils.data import DataLoader\nfrom torch.nn.utils.rnn import pad_sequence\nfrom torch.nn.utils import clip_grad_norm_\nimport torch\nimport torch.nn as nn\nfrom torch import optim\nfrom dataset import s2s_dataset, s2s_shortCorpus\nfrom NMTmodel import sequence2sequence\nfrom tqdm import tqdm\nimport os\... | [
[
"torch.nn.NLLLoss",
"torch.load",
"torch.nn.utils.rnn.pad_sequence",
"torch.utils.data.DataLoader",
"torch.cuda.is_available"
]
] |
alanoMartins/Loucutor_MFCC | [
"3358eee3dc8e347dac55595fa24f40cb1aff4934"
] | [
"main.py"
] | [
"from dataset_util import Util\nimport numpy as np\nimport pandas as pd\nfrom sklearn.metrics import accuracy_score, f1_score\nfrom gmm import GMM\nfrom gmm_ubm import GMM_UBM\nimport matplotlib.pyplot as plt\n\n\ndef group_X_y(X, y):\n\n X_by_class = []\n Y_by_class = []\n for cl in np.unique(y):\n ... | [
[
"numpy.unique",
"sklearn.metrics.accuracy_score",
"pandas.DataFrame",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"numpy.array",
"numpy.where",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
anielsen001/sarpy | [
"07bf157f54a5304185fc0e1c34010053fd6ae9d9"
] | [
"sarpy/io/complex/sicd_elements/SICD.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nThe SICDType definition.\n\"\"\"\n\nimport logging\nimport copy\nfrom datetime import datetime\nimport re\nfrom collections import OrderedDict\n\nimport numpy\n\nfrom .base import Serializable, _SerializableDescriptor, DEFAULT_STRICT\nfrom .CollectionInfo import CollectionInfoType\... | [
[
"numpy.deg2rad"
]
] |
SDS-Architect/MAP_1_Food_Poverty | [
"b589fc4e7ba46418f77d31188f34fad3fa7f43b1"
] | [
"Supermarket_Scraping/Utility_Functions/General_Utilities.py"
] | [
"### Import Libs\nimport time\nimport pandas as pd\nfrom selenium import webdriver\nfrom selenium.webdriver.chrome.options import Options\n\n\ndef slow_typing(element, text):\n \"\"\" One-click opening and loading of file.\n \n Parameters\n ----------\n element: string\n A string that represen... | [
[
"pandas.read_csv"
]
] |
vlad-perevezentsev/dpctl | [
"f4a281f821c238ce1f6d1cef083b1f51a95b0ead"
] | [
"dpctl/dptensor/numpy_usm_shared.py"
] | [
"##===---------- numpy_usm_shared.py - dpctl -------*- Python -*----===##\n##\n## Data Parallel Control (dpCtl)\n##\n## Copyright 2020 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... | [
[
"numpy.ndarray.__new__",
"numpy.ndarray",
"numpy.dtype",
"numpy.result_type",
"numpy.copy",
"numpy.prod",
"numpy.copyto"
]
] |
mfederici/dsit | [
"7f26f7ce93edb2075fba4aa965aa1ad9bf773aa5"
] | [
"src/models/DANN.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.distributions import Distribution\nfrom src.models.base import ConditionalDistribution, RegularizedModel, AdvarsarialModel, RepresentationModel, \\\n PredictiveModel\n\n\n######################################\n# Domain Adversarial Neural Networks #\n#############... | [
[
"torch.nn.ModuleDict",
"torch.no_grad"
]
] |
hkbonychen/3D-Morphable-Model-training | [
"fa86d7e62f3dfaf20f312d22fa5013d9328f56f8"
] | [
"envs-src/menpo3d/io/test/io_input_test.py"
] | [
"import menpo\nimport menpo3d.io as mio\nimport numpy as np\nfrom menpo.image import Image\nfrom menpo.shape import TriMesh, TexturedTriMesh, PointCloud\nfrom numpy.testing import assert_allclose\n\n# ground truth bunny landmarks\nfrom pytest import raises\n\nbunny_leye = np.array([[-0.0907334573249135,\n ... | [
[
"numpy.array"
]
] |
sarincr/Introduction-to-Flask-Web-framework | [
"69a703b3533b6b12f07712a5473b31176c25c9c7"
] | [
"21.Pandas/main.py"
] | [
"from flask import Flask, request, render_template, session, redirect\nimport numpy as np\nimport pandas as pd\n\n\napp = Flask(__name__)\n\ndf = pd.DataFrame({'A': [0, 1, 2, 3, 4],\n 'B': [5, 6, 7, 8, 9],\n 'C': ['a', 'b', 'c--', 'd', 'e']})\n\n\n@app.route('/', methods=(\"POST\... | [
[
"pandas.DataFrame"
]
] |
wzk1015/PhysicsExperiment | [
"8a2692f64059232d29ee05519b41ba3a5875c5ed"
] | [
"Experiment1/phy1041/RMeasure.py"
] | [
"import xlrd\r\nimport shutil\r\nimport os\r\nfrom numpy import sqrt, abs\r\n\r\nimport sys\r\nsys.path.append('../..') # 如果最终要从main.py调用，则删掉这句\r\nfrom GeneralMethod.PyCalcLib import Fitting, InstrumentError, Method\r\nfrom reportwriter.ReportWriter import ReportWriter\r\n\r\n\r\nclass RMeasure:\r\n report_data... | [
[
"numpy.sqrt"
]
] |
VisionandCognition/pypreclin | [
"e116a92ae7b186964690a645901c58cc31e9c5d5"
] | [
"pypreclin/utils/reorient.py"
] | [
"##########################################################################\n# NSAp - Copyright (C) CEA, 2016\n# Distributed under the terms of the CeCILL-B license, as published by\n# the CEA-CNRS-INRIA. Refer to the LICENSE file or to\n# http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html\n# for details.\... | [
[
"numpy.linalg.det",
"numpy.dot",
"numpy.eye"
]
] |
NunoEdgarGFlowHub/tfx | [
"16038b03b1742ef8f537180907289257221a57b7",
"16038b03b1742ef8f537180907289257221a57b7",
"16038b03b1742ef8f537180907289257221a57b7"
] | [
"tfx/components/schema_gen/executor.py",
"tfx/examples/chicago_taxi_pipeline/taxi_utils.py",
"tfx/examples/chicago_taxi_pipeline/taxi_pipeline_portable_beam_test.py"
] | [
"# Copyright 2019 Google LLC. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appl... | [
[
"tensorflow.logging.info"
],
[
"tensorflow.is_nan",
"tensorflow.estimator.export.build_parsing_serving_input_receiver_fn",
"tensorflow.data.experimental.make_batched_features_dataset",
"tensorflow.constant",
"tensorflow.data.TFRecordDataset",
"tensorflow.parse_example",
"tensor... |
many-hats/espnet | [
"09383303e6f84a22eb71f19b7fa79a1d412ddc9b"
] | [
"espnet/nets/pytorch_backend/hopfield_transformer/optimizer.py"
] | [
"\n# Ranger deep learning optimizer - RAdam + Lookahead + Gradient Centralization, combined into one optimizer.\n\n# https://github.com/lessw2020/Ranger-Deep-Learning-Optimizer\n# and/or\n# https://github.com/lessw2020/Best-Deep-Learning-Optimizers\n\n# Ranger has been used to capture 12 records on the FastAI leade... | [
[
"torch.empty_like",
"torch.zeros_like"
]
] |
tan1889/gce | [
"92ad1e6f35c6a3f2df4403b0d3c40af4a66a3133"
] | [
"optimizers/modelselection.py"
] | [
"import pickle\nimport argparse\nimport os.path\nimport copy\nimport random\nimport launcher\nimport time\nfrom datetime import datetime\nimport torch.multiprocessing as mp\nimport data_utils\nimport torch\nimport warnings\n\n\nclass ModelSelection:\n\n def __init__(self, args, args_grid={}, n_iter=0, n_fold=0, ... | [
[
"torch.cat",
"torch.multiprocessing.Pool",
"torch.cuda.is_available",
"torch.multiprocessing.cpu_count"
]
] |
khurramHashmi/-ocrd_anybaseocr_block_segmentation | [
"cc0b63cf98325ad82633c23d2cc798728476420e"
] | [
"blocks.py"
] | [
"\"\"\"\nMask R-CNN\nTrain on the toy blocks dataset and implement color splash effect.\n\nCopyright (c) 2018 Matterport, Inc.\nLicensed under the MIT License (see LICENSE for details)\nWritten by Waleed Abdulla\n\n------------------------------------------------------------\n\nUsage: import the module (see Jupyter... | [
[
"numpy.array",
"numpy.where",
"numpy.sum"
]
] |
greninja/RobustNNSearch | [
"4dec13d3409c9198f1e7189c07d0df6d6e6b78e8"
] | [
"plot/plot_progress.py"
] | [
"import glob\nfrom pylab import *\nimport brewer2mpl\nimport numpy as np\nimport sys\nimport math\nimport gzip\nimport matplotlib.gridspec as gridspec\n\nfrom collections import defaultdict\nfrom matplotlib import pyplot as plt\n\n # brewer2mpl.get_map args: set name set type number of colors\nbmap = brewer2mpl.g... | [
[
"numpy.loadtxt"
]
] |
sharad28/Tensile_-_compressive_strength | [
"0a5393600ebb5238c654097a881fe8f25ad1c466"
] | [
"src/trainingmodel.py"
] | [
"\"\"\"\nThis is the Entry point for Training the Machine Learning Model.\nWritten By: Sarad Mishra\nVersion: 1.0\n\"\"\"\n\nimport logging\nimport pandas as pd\nimport os\nfrom sklearn.model_selection import train_test_split\nfrom src.best_model_finder import Model_finder\nfrom src.data_preprocessing import prepro... | [
[
"pandas.read_csv",
"sklearn.model_selection.train_test_split"
]
] |
plures/arrayviews | [
"14132bfd68880b8ee75706b2e3f1c1f95a971bf1"
] | [
"arrayviews/cuda/pyarrow_cuda_buffer_as.py"
] | [
"\n\ndef random(size):\n import numpy as np\n import pyarrow as pa\n import pyarrow.cuda as cuda\n ctx = cuda.Context()\n dtype = np.dtype('uint8')\n buf = pa.allocate_buffer(size*dtype.itemsize)\n arr = np.frombuffer(buf, dtype=dtype)\n arr[:] = np.random.randint(low=0, high=255, size=size,... | [
[
"numpy.frombuffer",
"numpy.dtype",
"numpy.random.randint"
]
] |
JuliusKryger/Python_School_Repo | [
"9f7e6fed684dc5c3ae29cc043c4ccee89a13c498"
] | [
"assignments/student_assignment_01/handin.py"
] | [
"# The Datasheet used for this assignment can be downloaded from the following site -> https://www.kaggle.com/sanjeetsinghnaik/top-1000-highest-grossing-movies\nimport pandas as pd\n\n# Taks 1. Find the top 10 highest grossing Disney movies measured by world sales.\nprint('\\n---------- Task 1 ---------- \\n... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
tmthyjames/Achoo | [
"cf7168d305101d06caeb6b828ebad0321e815b8d"
] | [
"data/data/munging/get_data.py"
] | [
"import os\nimport requests\nimport pandas as pd\nimport sqlalchemy\nimport time\nimport datetime\nfrom bs4 import BeautifulSoup as BS\n\nengine = sqlalchemy.create_engine(os.environ['ACHOO_PG_CONN_STR'])\ntoday = time.mktime(datetime.datetime.now().timetuple())\n\nusers = engine.execute('select distinct on (zipcod... | [
[
"pandas.DataFrame"
]
] |
DragaDoncila/plugin-tests | [
"ca9bb91a8975bed50b8c7474d179f955dda5d25d"
] | [
"src/plugin_tests/_widget.py"
] | [
"from enum import Enum\nfrom functools import partial\n\nimport dask.array as da\nimport numpy as np\nfrom magicgui import magic_factory\nfrom napari.layers import Image, Labels\nfrom qtpy.QtWidgets import (\n QCheckBox,\n QComboBox,\n QHBoxLayout,\n QLabel,\n QPushButton,\n QVBoxLayout,\n QWid... | [
[
"numpy.histogram",
"numpy.diff",
"numpy.quantile"
]
] |
alexmplastow/RNACircos | [
"4a0f75668bf4d253f12ce2febaf74fd789610c52"
] | [
"circle_graph.py"
] | [
"import functions\nimport numpy as np\nimport math\nimport matplotlib.pyplot as plt\n\nfrom matplotlib.textpath import TextPath\nfrom matplotlib.patches import PathPatch\n\ndef circle_graph(brackets, sqrt_prob, color_0, gradient_0, gradient_color_graph, color_spectrum, mutation_imposition,\n first, ... | [
[
"matplotlib.pyplot.gca",
"numpy.polyfit",
"matplotlib.textpath.TextPath",
"numpy.linspace",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.Circle",
"matplotlib.pyplot.axis",
"matplotlib.patches.PathPatch"
]
] |
kkaryl/AI6121-Computer_Vision | [
"94e333554f7d4b47e4f82bc0273e1f3de7f658b2"
] | [
"project_1/AJCNN/models/VGG.py"
] | [
"from __future__ import print_function\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\n__all__ = ['VGG']\n\nVGG_cfgs = {\n \"VGG11\": [64, 'M', 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'],\n \"VGG13\": [64, 64, 'M', 128, 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'],... | [
[
"torch.nn.Sequential",
"torch.nn.Dropout",
"torch.nn.init.constant_",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.init.normal_",
"torch.nn.BatchNorm2d",
"torch.flatten",
"torch.nn.ReLU",
"torch.nn.init.kaiming_... |
dbbyn/arrow | [
"7029f90ea3b39e97f1a671227ca932cbcdbcee05"
] | [
"cpp/src/arrow/compute/exec/hash_join_graphs.py"
] | [
"#!/bin/env python3\n\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 2.0 (... | [
[
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.ScalarFormatter",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
paw-lu/altair_pandas | [
"3939a606d9851d5ff3363e313eac73fa217c4e4f"
] | [
"altair_pandas/conftest.py"
] | [
"import pytest\nimport pandas as pd\n\n\ndef pytest_addoption(parser):\n parser.addoption(\n \"--backend_name\",\n action=\"store\",\n default=\"altair_pandas\",\n help=\"Plotting backend to use.\",\n )\n\n\n@pytest.fixture(scope=\"session\")\ndef with_plotting_backend(request):\n ... | [
[
"pandas.get_option",
"pandas.set_option"
]
] |
amukher3/Problem_solutions | [
"a330cb04b5dd5cc1c3cf69249417a71586441bc7"
] | [
"TempusAssesment_xgBoost.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Mon Aug 26 17:54:27 2019\r\n\r\n@author: amukher3\r\n\"\"\"\r\n\r\nimport pandas as pd\r\nimport xgboost as xgb\r\nimport numpy as np\r\nfrom numpy import sort\r\nfrom xgboost import XGBClassifier\r\n#from sklearn.model_selection import train_test_split\r\n#from skle... | [
[
"pandas.read_csv",
"matplotlib.pyplot.subplots",
"numpy.sort",
"sklearn.model_selection.train_test_split",
"numpy.argsort",
"sklearn.feature_selection.SelectFromModel",
"matplotlib.pyplot.show",
"sklearn.metrics.accuracy_score"
]
] |
liziliao/MMConv | [
"d052b3da79da2118a6a52f2c834bb21881c5a8bb"
] | [
"multiple tasks/data/dataset/multiwoz.py"
] | [
"import os\nimport json\nimport random\nimport torch\nimport numpy as np\nimport ipdb\nimport warnings\n\nimport spacy\nfrom spacy import displacy\nfrom collections import Counter\n#import en_core_web_sm\nimport json\nimport pickle\n\n\n# DEFINE special tokens\nSOS_token = 0\nEOS_token = 1\nUNK_token = 2\nPAD_token... | [
[
"torch.LongTensor",
"numpy.array",
"torch.cat",
"numpy.ones"
]
] |
DulanWirajith/Real-Tme-Bus-Arrival-Tme-Prediction-Model-using-Tensorflow-Lite | [
"5ad7d2901406d7d008e9b033fa392670852db0e8"
] | [
"Model/LSTM-TimeSeries-One Day.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nfrom tensorflow.keras import Sequential\nfrom tensorflow.keras.layers import Dense, LSTM, Dropout\nfrom sklearn.preprocessing import MinMaxScaler\n\ndataset = pd.read_csv('../Dataset/GPS Database Cleaned Data-One Day.csv', parse_dates=True, ... | [
[
"pandas.read_csv",
"tensorflow.keras.layers.Dense",
"sklearn.preprocessing.OneHotEncoder",
"tensorflow.keras.Sequential",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"tensorflow.keras.layers.LSTM",
"tensorflow.keras.layers.Dropout",
"numpy.array",
"sklea... |
andreastedile/unitn-m-ds2 | [
"138c47f2f857e2b4a08c01edcbf0daa00b281077"
] | [
"lab/02_mesa-tutorial/invoke.py"
] | [
"import matplotlib.pyplot as plt\n\nfrom model.money_model import MoneyModel\n\nmodel = MoneyModel(10)\nfor i in range(10):\n model.step()\n\nplt.show()\n\n# For a jupyter notebook add the following line:\n# %matplotlib inline\n# The below is needed for both notebooks and scripts\n\nagent_wealth = [a.wealth for ... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.hist"
]
] |
ckamtsikis/cmssw | [
"ea19fe642bb7537cbf58451dcf73aa5fd1b66250"
] | [
"SimTracker/SiPhase2Digitizer/python/PixelTestBeamValidation_cfi.py"
] | [
"import FWCore.ParameterSet.Config as cms\nimport numpy as np\n\nfrom DQMServices.Core.DQMEDAnalyzer import DQMEDAnalyzer\n\n\nNx=60\nNy=60\n\n# PSet for the histos\nClusterSize1D = cms.PSet(\n Nxbins = cms.int32(201),\n xmin = cms.double(-0.5),\n xmax = cms.double(199.5)\n )\nCharge1D = cms.PSet(\n ... | [
[
"numpy.radians"
]
] |
abhinav-upadhyay/probability | [
"a91efeb17a6f6fdae97d3465878f5fc7fba12d30"
] | [
"tensorflow_probability/python/experimental/mcmc/windowed_sampling.py"
] | [
"# Copyright 2021 The TensorFlow Probability Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the 'License');\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by app... | [
[
"tensorflow.compat.v2.exp",
"tensorflow.compat.v2.fill",
"tensorflow.compat.v2.concat",
"tensorflow.compat.v2.convert_to_tensor",
"tensorflow.compat.v2.math.abs",
"tensorflow.compat.v2.nest.flatten",
"tensorflow.compat.v2.constant",
"tensorflow.compat.v2.nn.moments"
]
] |
sent-subsent-embs/clustering-network-analysis | [
"05bb04bed7edc2756f251d4465ef7c63d82b0c1e"
] | [
"src/embedding/src/quickthought/s2v_encoder_upgrade.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.io.gfile.isdir",
"tensorflow.import_graph_def",
"tensorflow.train.latest_checkpoint",
"tensorflow.compat.v1.train.Saver",
"tensorflow.compat.v1.train.SaverDef",
"tensorflow.compat.v1.gfile.FastGFile",
"numpy.linalg.norm",
"numpy.concatenate",
"tensorflow.compat.v1.l... |
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