repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
steffenvan/bachelor-thesis | [
"1472ce1ba32c107e25d4c5cc2ac64edfc04ba1ff"
] | [
"vtrace.py"
] | [
"# Copyright 2018 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"tensorflow.exp",
"tensorflow.convert_to_tensor",
"tensorflow.minimum",
"tensorflow.expand_dims",
"tensorflow.zeros_like",
"tensorflow.name_scope",
"tensorflow.add",
"tensorflow.scan",
"tensorflow.stop_gradient",
"tensorflow.nn.sparse_softmax_cross_entropy_with_logits"
]
... |
developfeng/BCM | [
"8eb5ac950a2d67d10fc707519bb66cd9ea4f14f2"
] | [
"libs/models/msc_bcm.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nclass MSC_BCM(nn.Module):\n \"\"\"\n Multi-scale inputs with Box-driven Class-wise Masking(BCM).\n \"\"\"\n\n def __init__(self, base, scales=None, n_classes=21):\n super(MSC_BCM, se... | [
[
"torch.nn.functional.sigmoid",
"torch.nn.functional.interpolate",
"torch.stack"
]
] |
jhancock1975/keras_tutorials | [
"4ff284a57670150ebf894e2aa090a21c4f604046"
] | [
"mlp-ex1.py"
] | [
"import keras\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Activation\nfrom keras.optimizers import SGD\nimport numpy as np\nimport jh_util as jh\nimport constants as const\nimport logging\n\nlogging.basicConfig(format='%(asctime)s %(message)s', level=logging.DEBUG)\nlogging.info('... | [
[
"numpy.random.random",
"numpy.random.randint"
]
] |
mostafaayesh/openpilot | [
"2313ff46f8552dea4835b689fad48ccdda67cc10"
] | [
"selfdrive/controls/lib/latcontrol_model.py"
] | [
"import math\nimport numpy as np\nfrom common.basedir import BASEDIR\nfrom selfdrive.controls.lib.drive_helpers import get_steer_max\nfrom cereal import log\nfrom common.numpy_fast import clip, interp\nfrom common.realtime import DT_CTRL\n\n\nclass LatControlModel:\n def __init__(self, CP):\n # Model generated ... | [
[
"numpy.array",
"numpy.dot",
"numpy.load",
"numpy.where",
"numpy.sign"
]
] |
henzh/piniverse | [
"77dce494cefc9e8051bb32298a5b32e2397c1634"
] | [
"piniverse/ui/drawer.py"
] | [
"# The MIT License (MIT)\n#\n# Copyright (c) 2019 Henry Zhao\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, including without limitation the rights\n# to use... | [
[
"matplotlib.pyplot.show"
]
] |
sunpeng1996/DSA2F | [
"22ba0e20ef1c5ace50b748dcfe1b94c9c4d11a87"
] | [
"main.py"
] | [
"\"\"\"\n DSA^2 F: Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion\n\"\"\"\nimport os\nimport torch\nfrom torch.autograd import Variable\nfrom torch.utils.data import DataLoader\nimport torch.nn.functional as F\nimport time\nimport torchvision\nimport logging\nimport... | [
[
"torch.cuda.synchronize",
"torch.autograd.Variable",
"torch.no_grad",
"torch.cuda.empty_cache",
"torch.nn.functional.softmax"
]
] |
antmicro/raw-image-data-previewer | [
"1fc14848a27ce628047cf3e473a9f30f83c9892d"
] | [
"tests/yuv_test.py"
] | [
"import unittest\nimport numpy\nimport os\nfrom unittest.mock import (Mock, patch)\nfrom app.parser.yuv import ParserYUV420, ParserYUV422, ParserYUV420Planar, ParserYUV422Planar\nfrom enum import Enum\n\n\nclass DummyPixelFormat(Enum):\n YUV = 1\n YVU = 2\n UYVY = 3\n YUYV = 4\n\n\nclass DummyEndianness... | [
[
"numpy.array"
]
] |
martinbacsi/AlphaZero_Gomoku | [
"a67aeb4a53ede551b69002412952c549356a1220"
] | [
"mcts_alphaZero.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nMonte Carlo Tree Search in AlphaGo Zero style, which uses a policy-value\nnetwork to guide the tree search and evaluate the leaf nodes\n\n@author: Junxiao Song\n\"\"\"\n\nimport numpy as np\nimport copy\n\n\ndef softmax(x):\n probs = np.exp(x - np.max(x))\n probs /= np.sum(pr... | [
[
"numpy.max",
"numpy.array",
"numpy.random.choice",
"numpy.zeros",
"numpy.sum",
"numpy.sqrt"
]
] |
kk49/deca | [
"8a03ea5d1b7ae0d787638f1797b6e2cb46de4bae"
] | [
"deca/db_commands.py"
] | [
"import os\nimport multiprocessing\nimport queue\nimport time\nimport sys\nimport traceback\nimport hashlib\nimport numpy as np\nfrom typing import List, Optional, Callable\n\nfrom .file import ArchiveFile\nfrom .db_core import VfsDatabase, VfsNode, language_codes, node_flag_v_hash_type_4, node_flag_v_hash_type_8\n... | [
[
"numpy.uint64"
]
] |
thomasdubdub/so6-airspace-filtering | [
"ad2f240c420d33686a33665ef5f54657cd9e117d"
] | [
"so6_filter.py"
] | [
"from datetime import datetime\nimport pandas as pd\nimport geopandas as gpd\nfrom shapely.geometry import LineString, Polygon, MultiPolygon\n\n\ndef make_time(row):\n datetime_str = str(row[\"date_begin\"]) + str(row[\"time_begin\"])\n return pd.datetime.strptime(datetime_str, \"%y%m%d%H%M%S\")\n\n\ndef make... | [
[
"pandas.datetime.strptime",
"pandas.read_csv"
]
] |
amareswar-n/repo1 | [
"416acf5f480645e43aaa2c1babfce14cf9775673"
] | [
"python/PyParseYml_Sql.py"
] | [
"## Install modules sqlparse and pyyaml for this pkg to work \n\n\nimport os\nimport sqlparse\nimport yaml\nimport pandas as pd\nfrom yaml.loader import SafeLoader\n\n\ndef ParseSql(filePath):\n #filePath = \"/Volumes/MyDrive/src/main/resources/sql/hl/hl_ongoing.sql\"\n if os.path.exists(filePath): \n ... | [
[
"pandas.DataFrame",
"pandas.ExcelWriter"
]
] |
qsyPython/Python_play_now | [
"278b6d5d30082f8f93b26902c854737c4919405a"
] | [
"yinwei/L3/pm-city.py"
] | [
"#先爬取所有城市以及对应城市的空气质量指标，然后做一个top50的图表\n#http://pm25.in/rank\n\nimport requests\nfrom bs4 import BeautifulSoup\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nplt.rcParams['font.sans-serif'] = ['SimHei']\nplt.rcParams['axes.unicode_minus'] = False # 处理- 显示问题\n\nr = requests.get('http://pm25.in/rank')\nsoup =... | [
[
"numpy.random.rand",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.xticks"
]
] |
S73ph4n/octavvs | [
"adbfa3f489b1928281a55de640c64d20afb4f9e1"
] | [
"octavvs/clustering.py"
] | [
"import sys\nimport csv\nimport glob\nimport os\nimport pandas as pd\nimport collections\nimport traceback\nfrom os.path import basename, dirname\nfrom pkg_resources import resource_filename\nimport argparse\n\n#from PyQt5.QtCore import *\n#from PyQt5.QtGui import QFileDialog\n#from PyQt5 import QtWidgets\nfrom PyQ... | [
[
"numpy.min",
"numpy.mean",
"pandas.concat",
"pandas.read_csv",
"numpy.concatenate",
"numpy.max",
"matplotlib.pyplot.colorbar",
"pandas.DataFrame",
"matplotlib.pyplot.fignum_exists",
"matplotlib.pyplot.tick_params",
"numpy.mod",
"numpy.reshape",
"sklearn.cluster.... |
Omkar-Ranadive/Domain-Adaptation-CycleGAN | [
"85fae5f8b9de568b826d3ba5765c079a9527121a"
] | [
"util/visualizer.py"
] | [
"import numpy as np\nimport os\nimport sys\nimport ntpath\nimport time\nfrom . import util, html\nfrom subprocess import Popen, PIPE\n\n\nif sys.version_info[0] == 2:\n VisdomExceptionBase = Exception\nelse:\n VisdomExceptionBase = ConnectionError\n\n\ndef save_images(webpage, visuals, image_path, aspect_rati... | [
[
"numpy.array"
]
] |
TianhongDai/Self_Imitation_Learning | [
"e49003582fa3d875495d84682f2a3332d4922dbc"
] | [
"sil_module.py"
] | [
"import numpy as np\nimport torch\nimport random\nfrom baselines.common.segment_tree import SumSegmentTree, MinSegmentTree\nfrom utils import evaluate_actions_sil\n\n# replay buffer...\nclass ReplayBuffer:\n def __init__(self, size):\n self._storage = []\n self._maxsize = size\n self._next_i... | [
[
"numpy.max",
"numpy.array",
"numpy.ones_like",
"torch.min",
"numpy.sum",
"torch.clamp",
"numpy.sign",
"torch.tensor",
"torch.sum"
]
] |
k-hanawa/criteria_for_instance_based_explanation | [
"bb6ae19a9164748e1fac08f8a7a1ad0adf28a94c"
] | [
"src/torch/mobilenetv2.py"
] | [
"import torch\nimport torch.nn as nn\nimport os\n\nimport torchvision\nimport torchvision.transforms as transforms\n\nfrom tqdm import tqdm as pbar\nimport numpy as np\nimport time\n\nfrom tqdm import tqdm\n\nimport scipy.linalg\n\nimport random\nfrom random import shuffle\n\nis_print = True\ndef _print(*args, **kw... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_",
"numpy.load",
"torch.load",
"torch.nn.CrossEntropyLoss",
"numpy.vectorize",
"numpy.save",
"torch.nn.init.normal_",
"torch.utils.data.DataLoader",
"torch.nn.init.zeros_",
"nu... |
varikakasandor/sports-prediction | [
"c7f61b6737684ed60d15eeed68a4fbee3555875e"
] | [
"model_loading.py"
] | [
"import numpy as np\nimport pandas as pd\nimport tensorflow as tf\nfrom pathlib import Path\nimport joblib\n\nfrom tensorflow.keras import models\n\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import mean_absolute_error\n\nfrom custom_utils import DateTransformer, create_integer_sco... | [
[
"pandas.DataFrame",
"pandas.read_csv",
"sklearn.metrics.mean_absolute_error"
]
] |
afizs/jina | [
"52c554c2d593e24129e86dfe3c71bf04f1495082"
] | [
"tests/unit/flow/test_flow_yaml_parser.py"
] | [
"import os\nfrom pathlib import Path\n\nimport numpy as np\nimport pytest\n\nfrom jina import Executor\nfrom jina.excepts import BadFlowYAMLVersion\nfrom jina import Flow\nfrom jina.jaml import JAML\nfrom jina.jaml.parsers import get_supported_versions\nfrom jina.parsers.flow import set_flow_parser\nfrom jina.types... | [
[
"numpy.random.random"
]
] |
sissi2017/lpot | [
"968fb136464aa4d89131c62aa5f01a7392571cdf"
] | [
"test/test_metrics.py"
] | [
"\"\"\"Tests for the metrics module.\"\"\"\nimport numpy as np\nimport unittest\nfrom lpot.metric import METRICS\nfrom lpot.experimental.metric.f1 import evaluate\nfrom lpot.experimental.metric import bleu\n\nclass TestMetrics(unittest.TestCase):\n def testmIOU(self):\n metrics = METRICS('tensorflow')\n ... | [
[
"numpy.array",
"numpy.sqrt"
]
] |
claudiu1989/DeepInterpretablePolynomialNeuralNetwork | [
"6280aa3fd8412d5973b7153659d2df0071ca1c83"
] | [
"src/deep_interpretable_polynomial_neural_network.py"
] | [
"import numpy as np\nfrom scipy.optimize import minimize\nfrom enum import Enum\nfrom itertools import combinations_with_replacement\n\nclass GrowthPolicy(Enum):\n ALL_TERMS = 1\n GROW = 2\n PRUNE_AND_GROW = 3\n\nclass DeepInterpretablePolynomialNeuralNetwork:\n def __init__(self, d_max, lambda_param, b... | [
[
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.log",
"numpy.sum",
"numpy.exp",
"numpy.prod",
"numpy.abs",
"numpy.around",
"scipy.optimize.minimize"
]
] |
ed-ortizm/spectra-processing | [
"c25e885746d4344ae095c84c3c0fff093c96b654"
] | [
"sample/train_sets.py"
] | [
"#! /usr/bin/env python3\n####################################################################\n# Idea is to handle everything from the data frame\n####################################################################\nfrom configparser import ConfigParser, ExtendedInterpolation\nimport time\n\nimport numpy as np\ni... | [
[
"numpy.load",
"numpy.random.shuffle",
"numpy.save",
"numpy.invert",
"numpy.stack",
"pandas.read_csv"
]
] |
zereab/PATIENT-Assistant-BOT-main | [
"38d8a43c7f6799f984cd7c8994ae83a716475065"
] | [
"preprocess.py"
] | [
"import nltk\n#nltk.download('wordnet')\nnltk.download('punkt')\nnltk.download('stopwords')\nfrom nltk.tokenize import RegexpTokenizer\nfrom nltk.corpus import stopwords\nimport difflib\n\nimport pandas as pd\n\ndef word_extractor(sentence):\n tokenizer = RegexpTokenizer(r'\\w+')\n tokens =tokenizer.tokenize(... | [
[
"pandas.read_csv"
]
] |
chryssa-zrv/UA_COMET | [
"527e7c86bd0a0d8ff90efda58e820108a5666b92",
"527e7c86bd0a0d8ff90efda58e820108a5666b92"
] | [
"tests/unit/models/test_rank_model.py",
"tests/unit/models/test_comet_estimator.py"
] | [
"# -*- coding: utf-8 -*-\nimport unittest\nfrom argparse import Namespace\nfrom io import StringIO\n\nfrom comet.models import CometRanker\nfrom comet.models.utils import average_pooling, max_pooling\n\nimport torch\n\n\nclass TestCometRanker(unittest.TestCase):\n\n hparams = Namespace(\n **{\"encoder_mod... | [
[
"torch.equal",
"torch.tensor"
],
[
"numpy.array",
"torch.cat",
"torch.tensor",
"numpy.arange",
"torch.equal"
]
] |
adriangonz/kserve | [
"a400bd7f6a3b4d40cc0257e55fb20bb4c8967c9f"
] | [
"python/pytorchserver/pytorchserver/example_model/model/cifar10.py"
] | [
"#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# dist... | [
[
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.Conv2d",
"torch.utils.data.DataLoader",
"torch.nn.CrossEntropyLoss"
]
] |
dav1nci/models | [
"f1a596825b194fa4032e31f7b7e0abad7a28db5f"
] | [
"research/object_detection/exporter.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.contrib.tfprof.model_analyzer.print_model_analysis",
"tensorflow.saved_model.utils.build_tensor_info",
"tensorflow.import_graph_def",
"tensorflow.to_float",
"tensorflow.add_to_collection",
"tensorflow.identity",
"tensorflow.saved_model.signature_def_utils.build_signature_de... |
g37502/nsfw-master | [
"347032fc553e549064c5078e8587942296fe8508"
] | [
"nsfw_predict.py"
] | [
"#-*-coding:utf-8-*-\n\nimport os\nimport io\nimport sys\nimport magic\nfrom raids_h import rehis_zero_pic,rehis_zero\nimport numpy as np\nfrom PIL import Image\nimport tensorflow as tf\nimport base64,time\nfrom config import config_h\n_MODEL_DIR = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'data/mode... | [
[
"numpy.asarray",
"tensorflow.get_default_graph",
"tensorflow.Session",
"numpy.mean",
"numpy.std",
"tensorflow.saved_model.loader.load"
]
] |
Hanawh/CondInst_mmdetection | [
"16c718f7d17de96d7def85102394beee67cda4b4"
] | [
"mmdet/core/post_processing/mask_nms.py"
] | [
"import torch\n\n\ndef matrix_nms(seg_masks, cate_labels, cate_scores, kernel='gaussian', sigma=2.0, sum_masks=None):\n \"\"\"Matrix NMS for multi-class masks.\n\n Args:\n seg_masks (Tensor): shape (n, h, w)\n cate_labels (Tensor): shape (n), mask labels in descending order\n cate_scores ... | [
[
"torch.exp"
]
] |
littlealexchen/Deep-Learning-with-TensorFlow-master | [
"7ea73195922bce6919864352b529b84194ec9d30"
] | [
"Chapter02/Python 3.5/single_neuron_model_1.py"
] | [
"import tensorflow as tf\n\nweight = tf.Variable(1.0, name=\"weight\")\ninput_value = tf.constant(0.5, name=\"input_value\")\nexpected_output = tf.constant(0.0, name=\"expected_output\")\nmodel = tf.multiply(input_value,weight, \"model\")\nloss_function = tf.pow(expected_output - model, 2, name=\"loss_function\")\n... | [
[
"tensorflow.multiply",
"tensorflow.summary.scalar",
"tensorflow.Session",
"tensorflow.Variable",
"tensorflow.constant",
"tensorflow.summary.merge_all",
"tensorflow.summary.FileWriter",
"tensorflow.pow",
"tensorflow.global_variables_initializer",
"tensorflow.train.GradientDe... |
zhuyawen/baselines | [
"6d1c6c78d38dd25799145026a590cc584ea22c88"
] | [
"baselines/common/tests/envs/identity_env.py"
] | [
"import numpy as np\nfrom abc import abstractmethod\nfrom gym import Env\nfrom gym.spaces import MultiDiscrete, Discrete, Box\n\n\nclass IdentityEnv(Env):\n def __init__(\n self,\n episode_len=None\n ):\n\n self.observation_space = self.action_space\n self.episode_len = epi... | [
[
"numpy.dot"
]
] |
pgxcentre/ExPheWAS | [
"dee85ecea74958431a71e8abd9be8021aa51fa3d"
] | [
"analysis/atc_all_enrichments.py"
] | [
"#!/usr/bin/env python\n\n\"\"\"\nCompute the enrichment of all ATC codes and all outcomes.\n\"\"\"\n\nimport sys\nimport csv\nfrom itertools import product\nimport functools\nimport collections\nimport multiprocessing\n\nimport pandas as pd\nimport numpy as np\nimport scipy.stats\n\nfrom exphewas.utils import qval... | [
[
"pandas.DataFrame",
"pandas.read_csv",
"pandas.pivot_table"
]
] |
Okroshiashvili/feature_engine | [
"e40457ce8b4baa1e146976bf1af1bbdf6eae1305"
] | [
"feature_engine/transformation/reciprocal.py"
] | [
"# Authors: Soledad Galli <solegalli@protonmail.com>\n# License: BSD 3 clause\n\nfrom typing import List, Optional, Union\n\nimport numpy as np\nimport pandas as pd\n\nfrom feature_engine.base_transformers import BaseNumericalTransformer\nfrom feature_engine.variable_manipulation import _define_variables\n\n\nclass... | [
[
"numpy.reciprocal"
]
] |
emilyhawkins-drizly/dagster | [
"bfb90e8b0b442f657e5256082d3116aefa8c330b"
] | [
"examples/hacker_news/hacker_news_tests/test_resources/test_snowflake_io_manager.py"
] | [
"import os\nimport uuid\nfrom contextlib import contextmanager\n\nfrom dagster import build_init_resource_context, build_input_context, build_output_context\nfrom hacker_news.resources.snowflake_io_manager import ( # pylint: disable=E0401\n connect_snowflake,\n snowflake_io_manager,\n)\nfrom pandas import Da... | [
[
"pandas.DataFrame"
]
] |
gvishal/segmentation | [
"8e2963e7c4c68f68eab9ab7e57f500bfcef8f1bc"
] | [
"code/segmentart.py"
] | [
"import re\nimport sys\n\nimport numpy as np\nimport scipy as sp\nimport matplotlib.pyplot as plt\n\nsys.path.insert(0, '../../')\nfrom segmentation.code import tools, splitters, representations\n\n\npunctuation_pat = re.compile(r\"\"\"([!\"#$%&\\'()*+,-./:;<=>?@[\\\\\\]^_`{|}~])\"\"\")\nhyphenline_pat = re.compile... | [
[
"numpy.array"
]
] |
rcbyron/robo-showdown | [
"b9ab239b08519ebe9a58e3eda7422b976bfa22d5"
] | [
"__main__.py"
] | [
"\"\"\"Initialize and start pygame.\"\"\"\nimport pygame\nimport pygame.gfxdraw\nimport random\nimport time\nimport signal\nimport numpy as np\nimport tensorflow as tf\n\nfrom bullet import Bullet\nfrom fighter import Fighter, Vision\nfrom colors import *\nfrom settings import *\nfrom gene_functions import *\n\n\nd... | [
[
"numpy.savetxt",
"tensorflow.summary.scalar",
"tensorflow.Session",
"tensorflow.Variable",
"tensorflow.summary.merge_all",
"tensorflow.global_variables_initializer"
]
] |
SimonUnterstrasser/ColumnModel | [
"8c4e8c105fdfa552938c3dcbe71de99be72243f3"
] | [
"Sedimentation.gcc.py"
] | [
"'''\nComputation of terminal fall speed\n'''\n#GCCif (KERNEL == 1 && LongK_Options == 2) || (COLUMN == 1 && PROCESS != 2) \n# this block is active, if Long kernel values are explicitly computed (and not read from a file) or if sedimentation is switched on in the column model\n\nimport sys\nimport Misc as FK\nimpo... | [
[
"numpy.array",
"numpy.zeros"
]
] |
samuelduchesne/osmnx | [
"d5ae24aa3f125ee8d7980438525e03d2679fa280"
] | [
"osmnx/buildings.py"
] | [
"################################################################################\n# Module: buildings.py\n# Description: Download and plot building footprints from OpenStreetMap\n# License: MIT, see full license in LICENSE.txt\n# Web: https://github.com/gboeing/osmnx\n##############################################... | [
[
"matplotlib.collections.PatchCollection",
"matplotlib.pyplot.subplots"
]
] |
caserec2018/CaseRecommender | [
"1b63fe79aa26786c99f35e6b8f0a0dd9e591811b"
] | [
"caserec/recommenders/rating_prediction/matrixfactorization.py"
] | [
"# coding=utf-8\n\"\"\"\n Matrix Factorization Collaborative Filtering Recommender\n [Rating Prediction]\n\n Literature:\n Koren, Yehuda and Bell, Robert and Volinsky, Chris:\n Matrix Factorization Techniques for Recommender Systems\n Journal Computer 2009.\n http://dl.acm.org/c... | [
[
"numpy.dot",
"numpy.random.seed",
"numpy.multiply",
"numpy.fabs",
"numpy.sqrt"
]
] |
supriya-gdptl/pointnet.pytorch | [
"2b79f2502fca60182ccfd5eb0f5d9bb0f4334820"
] | [
"utils/show_cls.py"
] | [
"from __future__ import print_function\nimport argparse\nimport torch\nimport torch.nn.parallel\nimport torch.utils.data\nfrom torch.autograd import Variable\nfrom pointnet.dataset import HDF5_ModelNetDataset, ModelNetDataset\nfrom pointnet.model import PointNetCls\nimport torch.nn.functional as F\nimport trimesh\n... | [
[
"torch.autograd.Variable",
"torch.nn.functional.nll_loss",
"torch.utils.data.DataLoader",
"torch.load"
]
] |
cdj0311/Keras-TextClassification | [
"34746c01ed3976deea108937e023bc6cd4037473"
] | [
"keras_textclassification/m00_Bert/predict.py"
] | [
"# -*- coding: UTF-8 -*-\r\n# !/usr/bin/python\r\n# @time :2019/6/12 14:11\r\n# @author :Mo\r\n# @function :\r\n\r\n\r\n# 适配linux\r\nimport pathlib\r\nimport sys\r\nimport os\r\nproject_path = str(pathlib.Path(os.path.abspath(__file__)).parent.parent.parent)\r\nsys.path.append(project_path)\r\n# 地址\r\nfrom ke... | [
[
"sklearn.metrics.classification_report",
"numpy.array"
]
] |
deltabravozulu/pytorch | [
"c6eef589971e45bbedacc7f65533d1b8f80a6895",
"c6eef589971e45bbedacc7f65533d1b8f80a6895"
] | [
"benchmarks/operator_benchmark/benchmark_pytorch.py",
"torch/testing/_internal/dist_utils.py"
] | [
"import time\nimport json\nimport torch\nimport cpp_extension # noqa: F401\n\n\n\"\"\"PyTorch performance microbenchmarks.\n\nThis module contains PyTorch-specific functionalities for performance\nmicrobenchmarks.\n\"\"\"\n\nclass TorchBenchmarkBase(torch.nn.Module):\n \"\"\" This is a base class used to create... | [
[
"torch.cuda.current_device",
"torch.jit.script",
"torch.ones"
],
[
"torch.distributed.is_available",
"torch.distributed.init_process_group",
"torch.distributed.rpc.backend_registry.construct_rpc_backend_options",
"torch.distributed.is_initialized",
"torch.distributed.rpc.init_r... |
lesley-byte/enviroplus-python | [
"df08c238c8b550c9041ff06a0b6bef6b330af611"
] | [
"lesley-byte/graphpm1.py"
] | [
"from requests import get\nimport matplotlib.pyplot as plt\nimport matplotlib.animation as animation\nimport datetime as dt\n\nfrom pms5003 import PMS5003, ReadTimeoutError as pmsReadTimeoutError\nfig = plt.figure()\nax = fig.add_subplot(1, 1, 1)\nxs = []\nys =[]\npms5003 = PMS5003()\n\ndef animate(i, xs, ys):\n\n ... | [
[
"matplotlib.animation.FuncAnimation",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.xticks"
]
] |
jeremycfd/conga | [
"204bfd14cab3c4c07fd9b95d072b1b7b79c3d239"
] | [
"scripts/run_conga.py"
] | [
"######################## MAX LINE LENGTH OF ABOUT 120 ##################################################################\nimport argparse\n\nparser = argparse.ArgumentParser(description=\"Run the CoNGA clonotype neighbor-graph analysis pipeline\")\n\n#type is str by default\nparser.add_argument('--gex_data', help=... | [
[
"pandas.concat",
"matplotlib.pyplot.xticks",
"numpy.max",
"numpy.full",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"numpy.nonzero",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"numpy.log10",
"matplotlib.pyplot.subplot",
"matplotlib.use",
"numpy.array... |
IIDANGII/mmsegmentation | [
"e383ba2383005e4f8a219e1ade1b95dcb005faea"
] | [
"tools/pytorch2onnx.py"
] | [
"# Copyright (c) OpenMMLab. All rights reserved.\nimport argparse\nimport warnings\nfrom functools import partial\n\nimport mmcv\nimport numpy as np\nimport onnxruntime as rt\nimport torch\nimport torch._C\nimport torch.serialization\nfrom mmcv import DictAction\nfrom mmcv.onnx import register_extra_symbolics\nfrom... | [
[
"torch.cat",
"numpy.random.RandomState",
"torch.nn.BatchNorm2d",
"torch.no_grad",
"torch.FloatTensor",
"torch.manual_seed",
"numpy.stack",
"torch.LongTensor",
"torch.onnx.export"
]
] |
jskim0406/Study | [
"07b559b95f8f658303ee53114107ae35940a6080"
] | [
"2.Model Implementation/0. DNN/jskim_DNN/losses.py"
] | [
"import numpy as np\nfrom numpy import ndarray\n\nfrom jskim_DNN.utils.np_utils import (assert_same_shape,\n softmax,\n normalize,\n #exp_ratios,\n unnormalize)\n\nclass Loss(object):\n '''\n 신경망 모델의 손실을 계산하는 클래스\n '''\n\n... | [
[
"numpy.sum",
"numpy.power",
"numpy.log",
"numpy.clip"
]
] |
jroakes/tech-seo-crawler | [
"c60619cb6517069665e229917cfbc4fd0614d36f"
] | [
"lib/bert.py"
] | [
"#! /usr/bin/env python\n# coding: utf-8\n#\n# Copyright (c) 2019 JR Oakes\n#\n# Permission is hereby granted, free of charge, to any person obtaining\n# a copy of this software and associated documentation files (the\n# \"Software\"), to deal in the Software without restriction, including\n# without limitation the... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.Tanh",
"torch.FloatTensor",
"pandas.DataFrame",
"torch.no_grad",
"torch.nn.CosineSimilarity",
"torch.mean"
]
] |
itminner/Paddle | [
"1957192f05133c5c15e9c30fb55cffccc39a291d"
] | [
"python/paddle/fluid/tests/unittests/test_variable.py"
] | [
"# Copyright (c) 2018 PaddlePaddle 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 ... | [
[
"numpy.array",
"numpy.random.randint",
"numpy.array_equal"
]
] |
jadecastro/imitation | [
"e05d7f5a4adfb021699647b80576c74ba6bd9443"
] | [
"src/imitation/algorithms/dagger.py"
] | [
"\"\"\"DAgger (https://arxiv.org/pdf/1011.0686.pdf).\n\nInteractively trains policy by collecting some demonstrations, doing BC, collecting more\ndemonstrations, doing BC again, etc. Initially the demonstrations just come from the\nexpert's policy; over time, they shift to be drawn more and more from the imitator's... | [
[
"numpy.array",
"numpy.random.RandomState",
"numpy.sum",
"torch.save",
"numpy.load",
"torch.utils.data.DataLoader"
]
] |
erastorgueva-nv/NeMo | [
"d23ee3e3d5ed2fd17608b736ebae2b415a258a9e"
] | [
"nemo/collections/asr/models/classification_models.py"
] | [
"# Copyright (c) 2020, NVIDIA CORPORATION. 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 re... | [
[
"torch.no_grad",
"torch.stack"
]
] |
windshirely/sparse_mkl | [
"933af0e8c3bc9df7fc6e08a8b2033fbfe833b081"
] | [
"sparse_mkl/tests/test_sparse_sparse.py"
] | [
"import unittest\nimport numpy as np\nimport numpy.testing as npt\nimport scipy.sparse as _spsparse\nfrom sparse_mkl import dot_product_mkl\nfrom sparse_mkl._mkl_interface import _create_mkl_sparse, _export_mkl, sparse_matrix_t, set_debug_mode\nfrom sparse_mkl._sparse_sparse import _matmul_mkl\nfrom sparse_mkl.test... | [
[
"scipy.sparse.coo_matrix",
"numpy.dot",
"scipy.sparse.bsr_matrix",
"scipy.sparse.csc_matrix",
"numpy.testing.assert_array_almost_equal"
]
] |
stephaneckstein/transport-and-related | [
"e30e1f44e0171237e2187596a69bcac596def642"
] | [
"GAN_Toy/tflib/ops/deconv2d.py"
] | [
"import GAN_Toy.tflib as lib\n\nimport numpy as np\nimport tensorflow as tf\n\n_default_weightnorm = False\ndef enable_default_weightnorm():\n global _default_weightnorm\n _default_weightnorm = True\n\n_weights_stdev = None\ndef set_weights_stdev(weights_stdev):\n global _weights_stdev\n _weights_stdev ... | [
[
"numpy.square",
"tensorflow.shape",
"numpy.zeros",
"tensorflow.expand_dims",
"tensorflow.transpose",
"tensorflow.pack",
"tensorflow.name_scope",
"numpy.sqrt",
"tensorflow.stack",
"tensorflow.nn.conv2d_transpose",
"tensorflow.nn.bias_add",
"tensorflow.square"
]
] |
wecacuee/votenet | [
"e40b4a124e9fad41cddb6b1da5557aee390d64c8"
] | [
"votenet_catkin/src/votenet_service.py"
] | [
"#!/usr/bin/python3\nimport numpy as np\n\nimport rospy\nfrom votenet_catkin.srv import VotenetResponse, Votenet\nfrom ros_numpy.point_cloud2 import pointcloud2_to_array, array_to_pointcloud2\n\nfrom demo import point_cloud_to_detections\n\n\ndef votenet_callback(req):\n points = pointcloud2_to_array(req.pc)\n ... | [
[
"numpy.asarray"
]
] |
ReimarBauer/MSS | [
"ddd0f39b0dbe08bebcccf4020ee953f5d04242c0"
] | [
"mslib/msui/kmloverlay_dockwidget.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n\n mslib.msui.kmloverlay_dockwidget\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n Control widget to configure kml overlays.\n\n This file is part of mss.\n\n :copyright: Copyright 2017 Joern Ungermann\n :copyright: Copyright 2017-2021 by the mss team, see AUTHORS.\n :... | [
[
"matplotlib.patheffects.withStroke"
]
] |
taconite/PTF | [
"a8789c9f752aea2944c2a75e04cc2aa21c7e4a00"
] | [
"im2mesh/data/cape_sv.py"
] | [
"import os\nos.environ['PYOPENGL_PLATFORM'] = 'osmesa'\nimport glob\nimport numpy as np\nimport torch\nimport yaml\nimport trimesh\nimport numbers\n\nimport pickle as pkl\n\nfrom torch.utils import data\n\nfrom scipy.spatial import cKDTree as KDTree\nfrom scipy.spatial.transform import Rotation as R\n# from human_b... | [
[
"scipy.spatial.cKDTree",
"numpy.dot",
"numpy.random.rand",
"numpy.random.choice",
"numpy.load",
"numpy.min",
"numpy.cos",
"numpy.concatenate",
"numpy.max",
"numpy.random.normal",
"numpy.sin",
"numpy.unpackbits",
"numpy.eye",
"torch.utils.data.items",
"nu... |
dannadori/selfie2anime_webhooker | [
"37186231e1dbfe8ea89b8a3d84158cc5251d2c24"
] | [
"UGATIT/UGATIT.py"
] | [
"from ops import *\r\nfrom utils import *\r\nfrom glob import glob\r\nimport time\r\nfrom tensorflow.contrib.data import prefetch_to_device, shuffle_and_repeat, map_and_batch\r\nimport numpy as np\r\n\r\nclass UGATIT(object) :\r\n def __init__(self, sess, args):\r\n self.light = args.light\r\n\r\n ... | [
[
"tensorflow.contrib.data.prefetch_to_device",
"tensorflow.contrib.data.shuffle_and_repeat",
"tensorflow.contrib.data.map_and_batch",
"numpy.mod"
]
] |
shubham303/Decoupled-attention-network | [
"0dedb621603863adf8ecf0439bbe47dc0589143d"
] | [
"dataset_scene.py"
] | [
"# coding:utf-8\nimport random\nimport torch\nfrom torch.utils.data import Dataset\nfrom torch.utils.data import sampler\nimport torchvision.transforms as transforms\nimport lmdb\nimport six\nimport sys\nfrom PIL import Image\nimport numpy as np\nimport pdb\nimport os\nimport cv2\nfrom abfn import abfn\n\n\nclass l... | [
[
"numpy.array",
"numpy.zeros"
]
] |
jmodelcxc/eng_archive | [
"04017f062ef1ab023a58b6d9e5bde19992c8398c"
] | [
"Ska/engarchive/tests/test_data_source.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\nfrom __future__ import print_function, division, absolute_import\n\nimport numpy as np\nimport pytest\n\n\nfrom .. import fetch, fetch_sci, fetch_eng\nfetch_cxc = fetch\n\n\ndate1 = '2016:001:00:00:00.1'\ndate2 = '2016:001:00:00:02.0'\ndate3 = '2016:... | [
[
"numpy.all",
"numpy.allclose"
]
] |
PKULiuHui/LiveBlogSum | [
"b6a22521ee454e649981d70ddca6c89a1bac5a4c"
] | [
"model/Model3.py"
] | [
"# coding:utf-8\n\n# 层次式encoder + SRL attention\n# 同时预测sent分数和event分数\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numpy as np\n\nuse_cuda = torch.cuda.is_available()\n\n\nclass Model3(nn.Module):\n def __init__(self, args, embed=None):\n super(Model3, self).__init__()\n... | [
[
"torch.nn.Linear",
"torch.zeros",
"torch.cat",
"torch.nn.GRU",
"torch.save",
"torch.FloatTensor",
"torch.sign",
"torch.nn.Bilinear",
"torch.cuda.is_available",
"torch.t",
"numpy.random.random",
"torch.nn.Embedding",
"torch.dot"
]
] |
neiterman21/cheat_detector_keras | [
"a6e9f6e8c55614959ddeeebcaf578ec43edf8d6d"
] | [
"DDetector/Logisticegressiom.py"
] | [
"# model definition (canonical way)\nimport tensorflow as tf\nclass LogisticRegression(tf.keras.Model):\n\n def __init__(self, num_classes):\n super(LogisticRegression, self).__init__()\n self.dense = tf.keras.layers.Dense(num_classes)\n\n def call(self, inputs, training=None, mask=None):\n ... | [
[
"tensorflow.nn.softmax",
"tensorflow.device",
"tensorflow.keras.layers.Dense"
]
] |
manzt/wsireg | [
"7d81b830957cd8e88582727f1f1739a72a48b163"
] | [
"wsireg/reg_images/np_reg_image.py"
] | [
"import warnings\nimport SimpleITK as sitk\nimport numpy as np\nfrom wsireg.reg_images import RegImage\nfrom wsireg.utils.im_utils import (\n std_prepro,\n guess_rgb,\n)\n\n\nclass NumpyRegImage(RegImage):\n def __init__(\n self,\n image,\n image_res,\n mask=None,\n pre_r... | [
[
"numpy.concatenate",
"numpy.dot",
"numpy.squeeze"
]
] |
edsonjunior14/mp_classification | [
"dafbec182afc6e787911ec9cf0948a472477c368"
] | [
"param_grid.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Mar 23 08:50:53 2021\n\n@author: Edson cilos\n\"\"\"\n\n#Standard Packages \nimport numpy as np\n\n#Sklearn API\n\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sk... | [
[
"tensorflow.keras.optimizers.SGD",
"sklearn.ensemble.RandomForestClassifier",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.naive_bayes.GaussianNB",
"tensorflow.keras.layers.Dense",
"sklearn.svm.SVC",
"sklearn.linear_model.LogisticRegression",
"numpy.arange",
"sklearn.tree... |
kylevedder/second.pytorch | [
"d3995825b7106595df02e586dc2e206d940dda5a"
] | [
"torchplus/tools.py"
] | [
"import functools\nimport inspect\nimport sys\nfrom collections import OrderedDict\n\nimport numba\nimport numpy as np\nimport torch\n\n\ndef get_pos_to_kw_map(func):\n pos_to_kw = {}\n fsig = inspect.signature(func)\n pos = 0\n for name, info in fsig.parameters.items():\n if info.kind is info.PO... | [
[
"numpy.dtype"
]
] |
oshToy/Character-Aware-LM-WER | [
"555e04e4ad0acdbc32c7b57a75b0ec72d2d1b762"
] | [
"train.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport os\nimport time\nimport numpy as np\nimport tensorflow as tf\nimport model\nfrom data_reader import load_data, DataReader, FasttextModel, DataReaderFastText, TestDataReader, load_test_data\nimpo... | [
[
"tensorflow.set_random_seed",
"tensorflow.assign",
"numpy.random.seed",
"pandas.DataFrame",
"tensorflow.random_uniform_initializer",
"tensorflow.Session",
"tensorflow.train.Saver",
"tensorflow.Graph",
"tensorflow.variable_scope",
"tensorflow.variables_initializer",
"ten... |
asirabrar7/evoMPS | [
"afae13f055ba2352ce0c9b275e4799c7c135b4ff"
] | [
"evoMPS/tests/tdvp_common_tests.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Jan 11 18:11:02 2013\n\n@author: ash\n\"\"\"\nfrom __future__ import absolute_import, division, print_function\n\nimport scipy as sp\nimport evoMPS.matmul as mm\nimport evoMPS.tdvp_common as tc\nimport unittest\n\ndef make_E_noop(A, B):\n res = sp.zeros((A.shape[1... | [
[
"scipy.zeros",
"scipy.rand",
"scipy.allclose",
"scipy.zeros_like"
]
] |
yinjunbo/UMA-MOT | [
"46110c3fae15d440cc3e6b1ac49fc1272082c212"
] | [
"UMA-TEST/tracker/Siamese_inference/Siamese_tracker.py"
] | [
"import logging\nimport numpy as np\nfrom tracker.Siamese_utils.infer_utils import convert_bbox_format, Rectangle\nfrom tracker.Siamese_utils.misc_utils import get_center\n\n\nclass TargetState(object):\n \"\"\"Represent the target state.\"\"\"\n\n def __init__(self, bbox, search_pos, scale_idx, his_feature, orig... | [
[
"numpy.dot",
"numpy.minimum",
"numpy.min",
"numpy.mean",
"numpy.max",
"numpy.linalg.norm",
"numpy.arange",
"numpy.argmax",
"numpy.vstack",
"numpy.array",
"numpy.reshape",
"numpy.floor",
"numpy.ceil",
"numpy.asarray",
"numpy.errstate",
"numpy.hanning"... |
GkAntonius/abitools | [
"7f42500f5da259117db82b9ac74dbe43be00943e"
] | [
"abitools/io/abinitinput.py"
] | [
"from __future__ import print_function, division\nimport textwrap\nimport numpy as np\n\nfrom ..utils import listify, angstrom_to_bohr, header_line\nfrom ..core.writable import Writable\nfrom .sorting import input_variable_blocks\nfrom .variable import InputVariable\nfrom .structures import structure_to_abivars\n\n... | [
[
"numpy.searchsorted",
"numpy.prod"
]
] |
euivmar/MinkowskiEngine | [
"1c887bf0c54b9bdd632b9249cac71b275be8b2c2"
] | [
"MinkowskiEngine/SparseTensor.py"
] | [
"# Copyright (c) Chris Choy (chrischoy@ai.stanford.edu).\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy of\n# this software and associated documentation files (the \"Software\"), to deal in\n# the Software without restriction, including without limitation the rights to\n# use, co... | [
[
"torch.IntTensor",
"torch.cat",
"torch.sparse.DoubleTensor",
"torch.sparse.FloatTensor"
]
] |
qilei123/mmdetection_rop | [
"cbdbb2b521c94c2f3eeebb2f2069663199f679bc"
] | [
"mmdet/datasets/custom.py"
] | [
"import os.path as osp\n\nimport mmcv\nimport numpy as np\nfrom mmcv.parallel import DataContainer as DC\nfrom torch.utils.data import Dataset\n\nfrom .transforms import (ImageTransform, BboxTransform, MaskTransform,\n Numpy2Tensor)\nfrom .utils import to_tensor, random_scale\nfrom .extra_au... | [
[
"numpy.array",
"numpy.random.choice",
"numpy.random.rand",
"numpy.zeros",
"numpy.where",
"numpy.hstack"
]
] |
highgroundmaster/Image-Super-Resolution-Using-Deep-Convolutional-Networks | [
"b94d1aa212d071fb4d551838b7b4dff3ea9393f7"
] | [
"Bicubic Upsampling/Code/Preprocessing/distort_images.py"
] | [
"\"\"\"\n Functions used for distorting images for training\n\"\"\"\n\n# Import the necessary libraries\nimport numpy as np\nimport torch\n\nfrom scipy.ndimage.filters import gaussian_filter\nfrom PIL import Image\n\n# Import the necessary source codes\nfrom Preprocessing.utils import dct_2d\nfrom Preprocessing.... | [
[
"torch.round",
"numpy.array",
"numpy.zeros",
"numpy.copy",
"scipy.ndimage.filters.gaussian_filter",
"torch.cuda.is_available",
"torch.tensor",
"torch.empty_like"
]
] |
soheeyang/denspi | [
"f540b6a547f012823fc6c2bb10077df6bccc13a6"
] | [
"pre.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors, The HugginFace Inc. team and University of Washington.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# ... | [
[
"numpy.concatenate",
"torch.device",
"torch.tensor"
]
] |
NJDFan/fxpmath | [
"a4d67e421c351c3901d62e22c60a5c81d427811d"
] | [
"fxpmath/__init__.py"
] | [
"__version__ = '0.4.0-rc.1'\n\nimport sys\nimport os\n\n_INFO_PRINT_ENABLE = False\n\n# check if __array_function__ methods is enabled in numpy\n# os.environ[\"NUMPY_EXPERIMENTAL_ARRAY_FUNCTION\"] = \"1\"\n_NUMPY_EXPERIMENTAL_ARRAY_FUNCTION_AUTOENABLE = True\nif \"NUMPY_EXPERIMENTAL_ARRAY_FUNCTION\" in os.environ.k... | [
[
"numpy.log2"
]
] |
sungyoon-lee/LossLandscapeMatters | [
"b805939c56eea33beda86560a1289c35878d93de"
] | [
"config.py"
] | [
"\nimport os\nimport json\nimport glob\nimport copy\nimport importlib\nimport torch\nimport numpy as np\nfrom datasets import loaders\n\n# from model_defs import add_feature_subsample, remove_feature_subsample\nfrom model_defs import convert_conv2d_dense, save_checkpoint, load_checkpoint_to_mlpany\n\n# Helper funct... | [
[
"torch.zeros",
"torch.load"
]
] |
yuta-hi/pytorch_bayesian_unet_inference_cpp | [
"390037c244f94457c779e9f79fa2c2dd938a8f46"
] | [
"dump_model.py"
] | [
"import numpy as np\nimport torch\nfrom pytorch_bcnn.models import UNet, BayesianUNet\nfrom pytorch_bcnn.links import MCSampler\n\ndef main():\n\n device='cuda'\n out = 'model.pth'\n\n predictor = BayesianUNet(ndim=2, in_channels=1, nlayer=3, out_channels=10) # NOTE: minimal model\n model = MCSampler(pr... | [
[
"torch.as_tensor",
"torch.no_grad",
"numpy.ones",
"torch.jit.trace"
]
] |
jpollmann102/football-predictor | [
"0025f10240467195c6860f11f01e6e95def7a27f"
] | [
"nflPredict.py"
] | [
"import pandas as pd\r\nimport numpy as np\r\nimport sys\r\n\r\nfrom sklearn.model_selection import train_test_split\r\nfrom sklearn.linear_model import LogisticRegression\r\n# from math import exp\r\n\r\ndef meanAbsolutePercentageError(yTrue, yPredict):\r\n yTrue, yPredict = np.array(yTrue), np.array(yPredict)\... | [
[
"numpy.array",
"sklearn.linear_model.LogisticRegression",
"numpy.abs",
"sklearn.model_selection.train_test_split",
"pandas.read_csv"
]
] |
lrsantana18/BigDL | [
"14b2761616fb0be3872f4a4a92b56e992b504d12"
] | [
"python/orca/src/bigdl/orca/learn/pytorch/pytorch_pyspark_worker.py"
] | [
"#\n# Copyright 2016 The BigDL 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 applicable law ... | [
[
"torch.distributed.destroy_process_group"
]
] |
Mathieu4141/avalanche | [
"09c922459edcf90441abb6912a73e351dcbd8b49"
] | [
"avalanche/training/strategies/icarl.py"
] | [
"import copy\nimport itertools\nfrom typing import TYPE_CHECKING, Optional, List\nimport torch\nfrom torch.optim import Optimizer\n\nfrom avalanche.benchmarks.utils import AvalancheConcatDataset, \\\n AvalancheTensorDataset, AvalancheSubset\nfrom math import ceil\n\nfrom avalanche.models import TrainEvalModel, N... | [
[
"torch.zeros",
"torch.cat",
"torch.argmax",
"torch.norm",
"torch.no_grad",
"torch.ones",
"torch.where",
"torch.tensor",
"torch.mean",
"torch.flip"
]
] |
haginile/pyjstat | [
"fe270a6fbf09e2dee398d7a35e09fc348a6325e1"
] | [
"pyjstat/pyjstat.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"pyjstat is a python module for JSON-stat formatted data manipulation.\n\nThis module allows reading and writing JSON-stat [1]_ format with python,\nusing data frame structures provided by the widely accepted\npandas library [2]_. The JSON-stat format is a simple lightweight JSON form... | [
[
"pandas.isnull",
"numpy.array",
"pandas.merge",
"pandas.concat"
]
] |
google/dynamic-video-depth | [
"274f5f59604a10121a2445f7b30df4a9ff075946"
] | [
"datasets/shutterstock.py"
] | [
"# Copyright 2021 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed t... | [
[
"numpy.asarray",
"numpy.zeros",
"numpy.ones",
"numpy.load",
"numpy.transpose",
"torch.load",
"numpy.linalg.inv"
]
] |
dbkinghorn/NGC-TF1-nvidia-examples | [
"f3e714c8bb4dcf2b706cca1a4584be52ee91a033"
] | [
"bert/utils/utils.py"
] | [
"# Copyright (c) 2019 NVIDIA CORPORATION. All rights reserved.\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 require... | [
[
"tensorflow.estimator.SessionRunArgs",
"tensorflow.train.get_global_step"
]
] |
jose-gilberto/dml | [
"41f432f6a7b17b9799fdbb6d8124f3b317cdaa20"
] | [
"dml/utils/data.py"
] | [
"from typing import Union\nimport pandas as pd\nimport torch\nfrom torch.utils.data import Dataset\n\n\nclass DiabetesDataset(Dataset):\n\n def __init__(\n self,\n data: Union[str, pd.DataFrame],\n transform = None,\n target_transform = None\n ) -> None:\n super().__init__()... | [
[
"pandas.read_csv",
"torch.tensor"
]
] |
vfdev-5/models-comparison.pytorch | [
"30a895028b19ee4ee0c3875a27e44286b489b378"
] | [
"scripts/compute_inference_time.py"
] | [
"import argparse\nimport gc\nimport numpy as np\nimport sys\nimport json\nimport time\nimport torch\nimport torch.backends.cudnn as cudnn\n\nsys.path.append('..')\nimport pretrainedmodels\nimport pretrainedmodels.utils as utils\n\nmodel_names = sorted(name for name in pretrainedmodels.__dict__\n\tif not name.starts... | [
[
"numpy.asarray",
"torch.cuda.synchronize",
"torch.no_grad",
"torch.manual_seed",
"torch.randn"
]
] |
sagieppel/-Finding-relations-between-two-instances-in-an-image-using-a-convolutional-neural-net. | [
"7779250b101538396386affb1e89936927b0942f"
] | [
"RunExample.py"
] | [
"# Run example on single image and two vessel masks (should run out of the box for a the example image and masks)\n#...............................Imports..................................................................\nimport numpy as np\nimport torch\nimport Visuallization as vis\nimport Net as NetBuild\nimport... | [
[
"numpy.concatenate",
"torch.no_grad",
"numpy.expand_dims",
"torch.load"
]
] |
andersk/cupy | [
"c73a325dd034ee9abfac2c4af11aa9107ec89042"
] | [
"cupy/linalg/product.py"
] | [
"import numpy\nimport six\n\nimport cupy\nfrom cupy import core\nfrom cupy.core import internal\n\nfrom cupy.linalg.solve import inv\nfrom cupy import util\nfrom cupy.util import collections_abc\n\nmatmul = core.matmul\n\n\ndef dot(a, b, out=None):\n \"\"\"Returns a dot product of two arrays.\n\n For arrays w... | [
[
"numpy.isscalar"
]
] |
J-Douglas/Digit-Recognition | [
"0b5c8afff28ea1253b33ffdd07b16c8b4d4cc943"
] | [
"Kaggle/kaggleANN.py"
] | [
"import os\nimport pandas as pd\nimport numpy as np\nimport keras\nfrom keras.models import Sequential\nfrom keras.layers import *\nfrom keras.utils import to_categorical\n\ntrain_dataset = pd.read_csv('datasets/train.csv')\ntest_dataset = pd.read_csv('datasets/test.csv')\n\ntrain_dataset.head()\n\ntrain_images = t... | [
[
"pandas.read_csv"
]
] |
tum-msv/mimo-cnn-est | [
"8915a918c08c5ae61dc2208352ebb9676395b3c8"
] | [
"estimators/DiscreteMMSE_mimo.py"
] | [
"import numpy as np\nfrom scipy.linalg import toeplitz\nfrom .Templates import Estimator_mimo, Descriptor\nfrom training_CNN_mimo import pilot_matrix\n\nclass DiscreteMMSE(Estimator_mimo, Descriptor):\n _object_counter = 1\n\n def __init__(self, channel, snr, n_antennas_BS, n_antennas_MS, n_samples, n_pilots,... | [
[
"scipy.linalg.toeplitz",
"numpy.trace",
"numpy.zeros",
"numpy.sum",
"numpy.exp",
"numpy.eye",
"numpy.amax",
"numpy.kron"
]
] |
YuechengWu/pandas | [
"7f753892eb6b29aaa62176cb9f00ad84c092c09a",
"7f753892eb6b29aaa62176cb9f00ad84c092c09a",
"7f753892eb6b29aaa62176cb9f00ad84c092c09a",
"7f753892eb6b29aaa62176cb9f00ad84c092c09a"
] | [
"pandas/tests/extension/decimal/array.py",
"pandas/tests/tseries/offsets/test_offsets.py",
"pandas/tests/io/test_excel.py",
"pandas/tests/frame/test_mutate_columns.py"
] | [
"import decimal\nimport numbers\nimport random\nimport sys\n\nimport numpy as np\n\nfrom pandas.core.dtypes.base import ExtensionDtype\n\nimport pandas as pd\nfrom pandas.core.arrays import ExtensionArray, ExtensionScalarOpsMixin\n\n\nclass DecimalDtype(ExtensionDtype):\n type = decimal.Decimal\n name = 'deci... | [
[
"numpy.concatenate",
"pandas.api.extensions.take",
"pandas.api.types.is_list_like",
"numpy.asarray"
],
[
"pandas.tseries.frequencies.get_offset",
"pandas._libs.tslibs.Timedelta",
"pandas.tseries.offsets.CBMonthEnd",
"pandas.tseries.offsets.WeekOfMonth",
"pandas.tseries.freq... |
Kludex/thinc | [
"6ac9d908d6d0f32686ba1a6084e015af3007e819"
] | [
"thinc/tests/test_config.py"
] | [
"import pytest\nfrom typing import Iterable, Union, Optional, List, Callable, Dict, Any\nfrom types import GeneratorType\nfrom pydantic import BaseModel, StrictBool, StrictFloat, PositiveInt, constr\nimport catalogue\nimport thinc.config\nfrom thinc.config import ConfigValidationError\nfrom thinc.types import Gener... | [
[
"numpy.array",
"numpy.ones",
"numpy.asarray",
"numpy.zeros"
]
] |
oriolmirosa/dash-recipes | [
"c01372292d60c3fd8c1f3a47bca6330c2b268ba4"
] | [
"dash_sqlite.py"
] | [
"import dash\nimport dash_core_components as dcc\nimport dash_html_components as html\nimport pandas as pd\n\nfrom sqlalchemy import create_engine\n\n# Create a simple database\nengine = create_engine('sqlite:///sample.db')\ndf = pd.DataFrame({\n 'a': [1, 2, 3, 4, 5, 6],\n 'b': ['x', 'y', 'x', 'x', 'z', 'y']\... | [
[
"pandas.DataFrame"
]
] |
busyyang/DL_21tensorflow | [
"ccac457b66a80f3de80d14d503e6cec8681537eb"
] | [
"L3/slim/train_image_classifier.py"
] | [
"# Copyright 2016 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required... | [
[
"tensorflow.group",
"tensorflow.train.AdagradOptimizer",
"tensorflow.control_dependencies",
"tensorflow.identity",
"tensorflow.app.flags.DEFINE_bool",
"tensorflow.train.GradientDescentOptimizer",
"tensorflow.trainable_variables",
"tensorflow.train.latest_checkpoint",
"tensorflo... |
ironartisan/Trajectory-Transformer | [
"52b8a1100de1548a6c757372466c232aca36d0b9"
] | [
"baselineUtils.py"
] | [
"from torch.utils.data import Dataset\nimport os, time\nimport pandas as pd\nimport numpy as np\nimport torch\nimport random\nimport scipy.spatial\nimport scipy.io\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\n\ndim = 3\n\n\nplt.rcParams['font.sans-serif'] = [\"SimHei\"]\n# 防止 - 号出错，和上一... | [
[
"numpy.concatenate",
"numpy.delete",
"numpy.array",
"numpy.zeros",
"torch.max",
"matplotlib.pyplot.clf",
"numpy.ones",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"numpy.stack",
"numpy.arange",
"matplotlib.pyplot.show",
"torch.Tensor",
"numpy.expa... |
TurtleInMelon/SemanticSegmentationByDeeplabv3plusAndPyQt5 | [
"a925d89b9b936dc75b667ba6264cc16d05c272ca"
] | [
"research/deeplab/utils/save_annotation.py"
] | [
"# Lint as: python2, python3\n# 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/L... | [
[
"tensorflow.gfile.Open",
"numpy.amax",
"numpy.amin"
]
] |
PapStatMechMat/SeaPy | [
"1b30792c011a23172a1ce33fe8ebea976561d59a"
] | [
"Tutorials/predict.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport os,glob,cv2\nimport sys,argparse\n\nparser = argparse.ArgumentParser()\nparser.add_argument(\"--filepath\",help=\"image file path for prediction purposes...\")\nparser.add_argument(\"--trainpath\",help=\"directory where training data is stored...\")\nargs=parser.... | [
[
"numpy.array",
"tensorflow.train.latest_checkpoint",
"tensorflow.get_default_graph",
"tensorflow.train.import_meta_graph",
"tensorflow.Session",
"numpy.multiply"
]
] |
limberc/TorchSSL | [
"b78918964bde9a91ba8bb5be58c2b238951949f8"
] | [
"models/pseudolabel/pseudolabel.py"
] | [
"import contextlib\nimport os\nfrom collections import Counter\nfrom copy import deepcopy\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom sklearn.metrics import *\nfrom torch.cuda.amp import GradScaler, autocast\n\nfrom train_utils import Bn_Controller, EMA, ce_loss, wd_loss\nfrom .pseudo... | [
[
"torch.zeros",
"torch.cat",
"torch.cuda.synchronize",
"torch.cuda.Event",
"torch.max",
"torch.no_grad",
"numpy.array_str",
"torch.softmax",
"torch.cuda.device_count",
"torch.nn.functional.cross_entropy",
"torch.load",
"numpy.clip",
"torch.cuda.amp.GradScaler"
... |
se4u/DeepNetworks | [
"693db0a0148f425b5dbe8d1c69d069dfcf3b6e76"
] | [
"deep_networks/models/discogan.py"
] | [
"import datetime\nimport functools\nimport operator\nimport os\n\nimport tensorflow as tf\n\nfrom .base import GANModel\nfrom .blocks import BasicGenerator, BasicDiscriminator\nfrom ..ops import dragan_perturb\nfrom ..train import IncrementalAverage\n\n\nclass DiscoGAN(GANModel):\n def __init__(self,\n ... | [
[
"tensorflow.train.AdamOptimizer",
"tensorflow.summary.scalar",
"tensorflow.summary.histogram",
"tensorflow.random_uniform",
"tensorflow.ones_like",
"tensorflow.train.Saver",
"tensorflow.reshape",
"tensorflow.nn.sigmoid_cross_entropy_with_logits",
"tensorflow.constant",
"ten... |
harrywang/tutorial-buffe | [
"d71a2e1e71fb85a726da613edbf1cea3a92eca17"
] | [
"streamlit/airbnb.py"
] | [
"import pandas as pd\nimport streamlit as st\nimport plotly.express as px\n\n@st.cache\ndef get_data():\n return pd.read_csv(\"http://data.insideairbnb.com/united-states/ny/new-york-city/2021-04-07/visualisations/listings.csv\") # not avaliable anymore\n\n# df = get_data()\ndf = pd.read_csv(\"listings.csv\")\ns... | [
[
"pandas.read_csv"
]
] |
oguzserbetci/generate-time-series | [
"f1e10a47e2adc88664c1930f5d3e0e9acbd8b386"
] | [
"spawn.py"
] | [
"from sklearn.metrics.pairwise import pairwise_distances\nfrom loaddataset import loaddataset, savedataset\nfrom collections import Counter\nfrom functools import partial\nfrom fastdtw import fastdtw\nfrom dtw_mean import ssg\nimport numpy as np\nimport argparse\nimport time\nimport math\nimport os\n\nSEED = 0\nnp.... | [
[
"numpy.concatenate",
"numpy.array",
"sklearn.metrics.pairwise.pairwise_distances"
]
] |
metocean/xarray | [
"f87bb0beadd937e3e9657e6d686a20b2bb288d2b"
] | [
"xarray/tests/test_indexing.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nimport numpy as np\nimport pandas as pd\n\nfrom xarray import Dataset, DataArray, Variable\nfrom xarray.core import indexing\nfrom . import TestCase, ReturnItem\n\n\nclass TestIndexers(TestCase):\n de... | [
[
"pandas.to_datetime",
"pandas.Index",
"numpy.random.rand",
"numpy.asarray",
"numpy.zeros",
"numpy.random.randn",
"numpy.arange",
"pandas.MultiIndex.from_product",
"numpy.int32"
]
] |
Chatoyant19/handeye_calibration | [
"590c93eba0fef835d0be6da0d750f71e4891a8fb"
] | [
"hand_eye_calibration/bin/compute_aligned_poses.py"
] | [
"#!/usr/bin/env python\nfrom hand_eye_calibration.time_alignment import (\n calculate_time_offset, compute_aligned_poses, FilteringConfig)\nfrom hand_eye_calibration.quaternion import Quaternion\nfrom hand_eye_calibration.csv_io import (\n write_time_stamped_poses_to_csv_file,\n read_time_stamped_poses_fro... | [
[
"numpy.array"
]
] |
ziedbouf/anovos | [
"4cd149fe803f8cec7d49cf1d2ebff5abf6b362ce"
] | [
"src/main/anovos/data_ingest/ts_auto_detection.py"
] | [
"# coding=utf-8\n\n\"\"\"This module help produce the output containing a transformation through auto timestamp / date detection by reading the ingested dataframe from source.\n\nAs a part of generation of the auto detection output, there are various functions created such as -\n\n- regex_date_time_parser\n- ts_loo... | [
[
"pandas.DataFrame"
]
] |
Jeminaje/pycaret | [
"b2833e6a4daa1c6286f3c5a3c17fb8404a01d23e"
] | [
"pycaret/internal/preprocess.py"
] | [
"# Module: Preprocess\n# Author: Fahad Akbar <m.akbar@queensu.ca>\n# License: MIT\n\nimport pandas as pd\nimport numpy as np\nimport ipywidgets as wg\nfrom IPython.display import display\nfrom ipywidgets import Layout\nfrom sklearn.base import BaseEstimator, TransformerMixin, clone\nfrom sklearn.impute._base import... | [
[
"scipy.stats.mode",
"scipy.stats.binom.sf",
"numpy.random.choice",
"numpy.median",
"numpy.tan",
"sklearn.preprocessing.RobustScaler",
"numpy.where",
"sklearn.preprocessing.MinMaxScaler",
"pandas.concat",
"numpy.cos",
"sklearn.pipeline.Pipeline",
"scipy.stats.binom.c... |
yizhouzhao/GenMotion | [
"67e73d06155d888eabda1187aa6ed3bbd796a814"
] | [
"genmotion/algorithm/action_conditioned/datasets/dataset.py"
] | [
"import random\n\nimport numpy as np\nimport torch\n\nfrom .tools import parse_info_name\nfrom ..utils.tensors import collate\nfrom ..utils.misc import to_torch\nfrom ..utils import rotation_conversions as geometry\n\nPOSE_REPS = [\"xyz\", \"rotvec\", \"rotmat\", \"rotquat\", \"rot6d\"]\n\n\nclass Dataset(torch.uti... | [
[
"torch.zeros",
"torch.cat",
"numpy.array",
"numpy.random.choice",
"numpy.ones",
"numpy.mean",
"numpy.argmax",
"numpy.arange",
"numpy.argwhere"
]
] |
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