repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
hutao965/lightseq | [
"9a617306fa711a3d6a25ef3eab9bfbe408692189"
] | [
"lightseq/training/ops/pytorch/transformer_decoder_layer.py"
] | [
"import math\nfrom dataclasses import dataclass\n\nimport torch\nfrom torch import nn\nfrom torch.autograd import Function\n\nfrom lightseq.training.ops.pytorch import transformer_cuda_module\nfrom lightseq.training.ops.pytorch.builder import TransformerBuilder\nfrom lightseq.training.ops.pytorch.util import (\n ... | [
[
"torch.empty_like",
"torch.cuda.set_device",
"torch.cat",
"torch.Tensor",
"torch.zeros",
"torch.nn.init._calculate_fan_in_and_fan_out",
"torch.is_grad_enabled"
]
] |
0mza987/azureml-examples | [
"2abb872f1278d4b4e65587e033f38a058512b2e3"
] | [
"cli/jobs/single-step/pytorch/word-language-model/src/generate.py"
] | [
"# Copyright (c) 2017 Facebook, Inc. All rights reserved.\n# BSD 3-Clause License\n#\n# Example adapted from: https://github.com/pytorch/examples/tree/master/word_language_model\n# ==============================================================================\n\n#####################################################... | [
[
"torch.randint",
"torch.Tensor",
"torch.load",
"torch.cat",
"torch.manual_seed",
"torch.multinomial",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device"
]
] |
Wolfgang9999/image-super-resolution | [
"6e22da94711e9fc95d012cf84b0944a1000faebf"
] | [
"modules/data.py"
] | [
"import os\r\nimport random\r\nimport tensorflow as tf\r\nimport numpy as np\r\n\r\n\r\n# DATA_PATH = \"/media/shareef/MLDev/Datasets/DIV2K/DIV2K_train_HR\"\r\nDATA_PATH=\"data/DIV2K_valid_HR/SampleDataISR\"\r\n\r\ndef scale_input_image(img):\r\n #img/ 255.\r\n return tf.image.convert_image_dtype(img, dtype=t... | [
[
"tensorflow.clip_by_value",
"tensorflow.image.decode_jpeg",
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.random.uniform",
"tensorflow.equal",
"tensorflow.image.decode_png",
"tensorflow.image.flip_left_right",
"tensorflow.data.Dataset.zip",
"tensorflow.image.resize"... |
sega-hsj/Video_Feature | [
"4cb6d9a91504df9877c73d3fa73ee1a5adce14c0"
] | [
"videocnn/TSD/mmdet/models/detectors/two_stage.py"
] | [
"import torch\nimport torch.nn as nn\n\nfrom mmdet.core import (\n bbox2result,\n bbox2roi,\n bbox_mapping,\n build_assigner,\n build_sampler,\n merge_aug_bboxes,\n multiclass_nms,\n)\nfrom .. import builder\nfrom ..registry import DETECTORS\nfrom .base import BaseDetector\nfrom .test_mixins im... | [
[
"torch.randn",
"torch.zeros",
"torch.ones",
"torch.cat"
]
] |
gmum/lcw-generator | [
"fde1128505194bd04f04bbddcbe7fcec453b0052"
] | [
"src/common/math.py"
] | [
"import torch\r\n\r\n\r\ndef pairwise_distances(x: torch.Tensor, y: torch.Tensor = None) -> torch.Tensor:\r\n if y is None:\r\n y = x\r\n return torch.cdist(x, y)**2\r\n\r\n\r\ndef euclidean_norm_squared(X: torch.Tensor, axis: int) -> torch.Tensor:\r\n return torch.linalg.norm(X, 2, axis)**2\r\n"
] | [
[
"torch.cdist",
"torch.linalg.norm"
]
] |
Rabbit1010/TensorFlow2.0-Tutorial-2019 | [
"def2ec0a93d73d81b9d95e60639ebe6bed383579"
] | [
"Topic2/4_UNet.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Dec 8 20:13:52 2019\n\n@author: Wei-Hsiang, Shen\n\"\"\"\n\nimport tensorflow as tf\nfrom tensorflow.keras import layers\n\n\ndef downsample(filters, size, apply_batchnorm=True):\n result = tf.keras.Sequential()\n result.add(layers.Conv2D(filters, size, stride... | [
[
"tensorflow.keras.layers.Concatenate",
"tensorflow.keras.layers.LeakyReLU",
"tensorflow.keras.layers.ReLU",
"tensorflow.keras.layers.Conv2DTranspose",
"tensorflow.keras.utils.plot_model",
"tensorflow.keras.Sequential",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.Model",
... |
maksym-taranukhin/lightning-transformers | [
"aa7202657973b5b65c3c36eb745621043859ebc4"
] | [
"lightning_transformers/core/callback.py"
] | [
"# Copyright The PyTorch Lightning team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"torch.cuda.max_memory_allocated",
"torch.cuda.synchronize",
"torch.cuda.reset_peak_memory_stats"
]
] |
Mistobaan/tensor2tensor | [
"91d4e1c83f9abb1ca8fcd94a65d6b74aaa3458da"
] | [
"tensor2tensor/layers/common_layers.py"
] | [
"# coding=utf-8\n# Copyright 2017 The Tensor2Tensor 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 requir... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.control_dependencies",
"tensorflow.reduce_sum",
"tensorflow.tanh",
"tensorflow.image.random_flip_left_right",
"tensorflow.summary.image",
"tensorflow.layers.dense",
"tensorflow.train.get_global_step",
"tensorflow.square",
"tensorf... |
DXYyang/shenNeng_gasAnalysis | [
"d94e2451d1938c090d1377dfbd487d0c6a649188"
] | [
"app/main/analysis/gas_kmeans_plt.py"
] | [
"def gas_kmeans_pit(dist,list,clusters):\n import matplotlib.pyplot as plt\n from sklearn.manifold import MDS\n plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签\n plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号\n MDS()\n mds = MDS(n_components=2, dissimilarity=\"precomputed\", ran... | [
[
"sklearn.manifold.MDS",
"matplotlib.pyplot.subplots"
]
] |
GregHilston/Google-Trends-Scraper | [
"fa5ccd0443bccffa99299748759491acf040e561"
] | [
"google_trends_scraper/google_trends_scraper.py"
] | [
"import sys\nimport os\nimport time\nimport pandas as pd\nfrom selenium import webdriver\n\nprint(f\"before path: {sys.path}\")\n\n# Adding geckodriver to our path so whoever imports our library can run correctly\nsys.path.insert(0, \"google_trends_scraper\")\n\nprint(f\"after path: {sys.path}\")\n\nclass GoogleTre... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.Timedelta",
"pandas.date_range"
]
] |
dapatil211/Jacinle | [
"37117de4abf1774548786e9534c90977d67091d8"
] | [
"jaclearn/vision/coco/setup.py"
] | [
"from setuptools import setup, Extension\nimport numpy as np\n\n# To compile and install locally run \"python setup.py build_ext --inplace\"\n# To install library to Python site-packages run \"python setup.py build_ext install\"\n\next_modules = [\n Extension(\n 'pycocotools._mask',\n sources=['src... | [
[
"numpy.get_include"
]
] |
cmla-psu/dpgen | [
"f9ba8bd140cc8978f20c52de175ed52cb870fe09"
] | [
"dpgen/algorithms/adaptive_svt_private.py"
] | [
"import time\n\nimport numba\nimport numpy as np\nimport pyswarms as ps\nimport sympy as sp\n\nLENGTH = 100\nEPSILON = 1\n\n\n@numba.njit\ndef my_assert(cond):\n if not cond:\n return 1\n else:\n return 0\n\n\n@numba.njit\ndef unpack_inputs(all_inputs):\n q, dq = all_inputs[:LENGTH], all_inpu... | [
[
"numpy.square",
"numpy.abs",
"numpy.asarray",
"numpy.linalg.norm",
"numpy.concatenate",
"numpy.random.laplace",
"numpy.array",
"numpy.zeros",
"numpy.empty"
]
] |
gdaisukesuzuki/cudf | [
"aa5c8b686b1513dba7bce168200c1259f1eda908"
] | [
"python/cudf/cudf/core/column/lists.py"
] | [
"# Copyright (c) 2020-2021, NVIDIA CORPORATION.\n\nimport pickle\nfrom typing import Sequence\n\nimport numpy as np\nimport pyarrow as pa\n\nimport cudf\nfrom cudf._lib.copying import segmented_gather\nfrom cudf._lib.lists import (\n concatenate_list_elements,\n concatenate_rows,\n contains_scalar,\n co... | [
[
"numpy.issubdtype"
]
] |
netneurolab/markello_transcriptome | [
"3abbc85596a5baacd93e5e9e56c906c9dbb080f3"
] | [
"scripts/generate_parameters.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\nGenerates CSVs containing all combinations of processing parameters to test\n\"\"\"\n\nimport itertools\nfrom pathlib import Path\nimport uuid\n\nimport pandas as pd\n\nDATA_DIR = Path('./data/derivatives').resolve()\n\n# generate giant list of lists of dict ... | [
[
"pandas.DataFrame"
]
] |
AliGhadirzadeh/yumi_follow_trajectory | [
"d30b05c979d6dc4d79f92bb207da47d1d527f9f5"
] | [
"scripts/waypoint_to_trajectory.py"
] | [
"#!/usr/bin/env python\nimport numpy as np\nfrom time import sleep\nfrom scipy import interpolate\nimport argparse\nimport os\nimport matplotlib.pyplot as plt\n\nparser = argparse.ArgumentParser()\nparser.add_argument(\"--file-name\", type=str, default=None, help=\"Filename of the waypoint file with .npy extention\... | [
[
"numpy.arange",
"numpy.save",
"matplotlib.pyplot.plot",
"numpy.append",
"matplotlib.pyplot.subplot",
"scipy.interpolate.CubicSpline",
"numpy.savetxt",
"numpy.load",
"matplotlib.pyplot.show",
"numpy.zeros"
]
] |
tranlethaison/NumpyNeuralNet | [
"8a22784348b07e9414c70bdc3674d9a51dd81641"
] | [
"numpynn/losses.py"
] | [
"import numpy as np\n\n\nclass MSE:\n @staticmethod\n def f(y, a):\n return np.mean(0.5 * np.sum(np.square(y - a), axis=0))\n\n @staticmethod\n def df_da(y, a):\n \"\"\"Return partial derivative wrt `a` (element-wise).\"\"\"\n return a - y\n\n\nclass CrossEntropy:\n @staticmethod... | [
[
"numpy.square",
"numpy.log",
"numpy.argmax",
"numpy.mean",
"numpy.zeros"
]
] |
poc1673/ML-for-Networks | [
"201ca30ab51954a7b1471740eb404b98f1d26213"
] | [
"gcn-master/gcn-master/gcn/Forced Implementation.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Sun Dec 6 16:45:47 2020\r\n\r\n@author: USER\r\n\"\"\"\r\n\r\nimport os \r\n\r\nos.chdir(\"C://Users//USER//Dropbox//Projects//Work on Graphs//gcn-master//gcn-master//gcn\")\r\n\r\nimport setup_for_forced_procedures\r\nfrom __future__ import division\r\nfrom __futur... | [
[
"tensorflow.sparse_placeholder",
"tensorflow.constant",
"tensorflow.placeholder_with_default",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.Session",
"tensorflow.set_random_seed"
]
] |
vaibhav02498/NumberPlateDetection | [
"043183f5e7c0cf31ddfcf5179799c4d99f413ed4"
] | [
"tools.py"
] | [
"\"\"\"\nAuthor : Vaibhav Goyal : Automatic licence plate detection and recognition\n\n\"\"\"\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.externals import joblib\nfrom matplotlib import pyplot as plt\nimport scipy.ndimage\nimport numpy as... | [
[
"matplotlib.pyplot.imshow",
"numpy.arange",
"matplotlib.pyplot.plot",
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.show"
]
] |
jhonore/jesse | [
"5b54e7abd20e3d5d5461dc0714e00bd64da468ac"
] | [
"tests/test_indicators.py"
] | [
"import numpy as np\n\nimport jesse.indicators as ta\nfrom jesse.factories import fake_range_candle_from_range_prices\nfrom .data.test_candles_indicators import *\n\n\ndef test_acosc():\n candles = np.array(test_candles_19)\n single = ta.acosc(candles)\n seq = ta.acosc(candles, sequential=True)\n\n asse... | [
[
"numpy.array"
]
] |
expeditiona/expeditiona.github.io | [
"85c6cbddf724d87ab1c7f924d717a6aadc23286e"
] | [
"Activity327Folder/327 q2.py"
] | [
"import matplotlib.pyplot as plt\nf = open(\"3.2.7 Investigating Data - Ques 2.csv\", 'r') #Open file\n\nspot = [] #Create empty lists\npct = []\nshotpct = []\ncombined = [] \n\nlineNumber = 1\n\nfor line in f: #Iterate through lines of file\n line = line.strip()\n if lineNumber > 1 and lineNumber < 9: \n ... | [
[
"matplotlib.pyplot.subplots"
]
] |
ACasey13/senpy | [
"00b5403dc95a0741abfc56c3a3e2a1e6247f15d4"
] | [
"senpy/logistic_funcs.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Feb 28 15:29:17 2020\n\n@author: alexc\n\"\"\"\n\nimport numpy as np\nfrom scipy.special import expit\n\nSTABILITY = 1E-8\n\ndef z(x, mu, sigma):\n \"\"\"\n Returns the z-location of the given stimulus levels\n \"\"\"\n return (x - mu) / sigma\n \ndef ... | [
[
"numpy.hstack",
"numpy.log",
"numpy.maximum",
"scipy.special.expit",
"numpy.min",
"numpy.max",
"numpy.exp",
"numpy.array",
"numpy.sum"
]
] |
GT-AcerZhang/paddle-voice | [
"b243144a86e9d34cabe8a5def9e8a2dae013b3fa"
] | [
"src/train.py"
] | [
"get_ipython().system('pip install paddlex -i https://mirror.baidu.com/pypi/simple')\n\n#开始模型的训练\n\n# 设置使用0号GPU卡\nimport os\nos.environ['CUDA_VISIBLE_DEVICES'] = '0'\nimport paddlex as pdx\n\n# 图像预处理+数据增强\nfrom paddlex.det import transforms\ntrain_transforms = transforms.Compose([\n transforms.MixupImage(mixup_e... | [
[
"matplotlib.pyplot.imshow"
]
] |
anotherjoshsmith/NovoNordisk_Capstone | [
"a39adb2ae68f001bdf0e4b2200d7b8f923f27c2f"
] | [
"ndac/predict.py"
] | [
"import numpy as np\nimport pandas as pd\n\nfrom keras.models import Sequential\nfrom keras.layers import Dense\nfrom keras.layers import LSTM\nfrom keras.layers import Flatten\nfrom keras.layers import Dropout\nfrom keras.layers.embeddings import Embedding\nfrom keras.layers.convolutional import Conv1D\nfrom keras... | [
[
"sklearn.model_selection.GridSearchCV",
"numpy.random.seed",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"numpy.isscalar"
]
] |
alexjones85/aXeleRate | [
"52437fc0b1d6cd9de2ccd6071f5fb489dc84e99d"
] | [
"example_scripts/arm_nn/yolov2.py"
] | [
"# Copyright © 2020 Arm Ltd and Contributors. All rights reserved.\r\n# SPDX-License-Identifier: MIT\r\n\r\n\"\"\"\r\nContains functions specific to decoding and processing inference results for YOLO V3 Tiny models.\r\n\"\"\"\r\n\r\nimport cv2\r\nimport numpy as np\r\nfrom box import BoundBox, nms_boxes, boxes_to_a... | [
[
"numpy.max",
"numpy.exp",
"numpy.sum",
"numpy.min"
]
] |
fangyuchu/rethinking-network-pruning | [
"3d3726e1277b5d9bd12b2b26d3c9bf1730709a42",
"3d3726e1277b5d9bd12b2b26d3c9bf1730709a42",
"3d3726e1277b5d9bd12b2b26d3c9bf1730709a42",
"3d3726e1277b5d9bd12b2b26d3c9bf1730709a42"
] | [
"cifar/soft-filter-pruning/pruning_cifar10_pretrain.py",
"imagenet/l1-norm-pruning/main_finetune.py",
"cifar/weight-level/cifar_finetune.py",
"cifar/soft-filter-pruning/pruning_resnet_longer_scratch.py"
] | [
"from __future__ import division\n\nimport os, sys, shutil, time, random\nimport argparse\nimport torch\nimport torch.backends.cudnn as cudnn\nimport torchvision.datasets as dset\nimport torchvision.transforms as transforms\nfrom utils import AverageMeter, RecorderMeter, time_string, convert_secs2time\nimport model... | [
[
"torch.nn.CrossEntropyLoss",
"torch.norm",
"numpy.abs",
"torch.load",
"torch.manual_seed",
"torch.utils.data.DataLoader",
"torch.backends.cudnn.version",
"numpy.sort",
"numpy.ones",
"torch.autograd.Variable",
"torch.FloatTensor",
"torch.cuda.is_available",
"torc... |
devenxu1985/onnx-tensorflow | [
"4fe611422ad3236973c498c5bff51fdd55657a4e"
] | [
"onnx_tf/common/data_type.py"
] | [
"from numbers import Number\n\nimport numpy as np\nfrom onnx import mapping\nfrom onnx import TensorProto\nimport tensorflow as tf\n\n\ndef tf2onnx(dtype):\n if isinstance(dtype, Number):\n tf_dype = tf.as_dtype(dtype)\n elif isinstance(dtype, tf.DType):\n tf_dype = dtype\n elif isinstance(dtype, list):\n ... | [
[
"numpy.dtype",
"tensorflow.as_dtype"
]
] |
HansBug/dgdvapp | [
"f3142d2c265afda427bbeee46c8073e1126eeef5"
] | [
"app/process/log.py"
] | [
"import os\nfrom operator import itemgetter\nfrom typing import Tuple, Iterator\n\nimport numpy as np\nimport pandas as pd\n\nfrom .exp_center import find_expdata_in_directory, exp_center_file_in_directory, exp_center_trans\nfrom .simudata import find_simudata_in_directory, simudata_file_in_directory, simudata_tran... | [
[
"numpy.mean"
]
] |
aspratyush/neural-structured-learning | [
"6cb6b22174ba5f5d6b621443eb2b147831be320d"
] | [
"neural_structured_learning/tools/pack_nbrs.py"
] | [
"# Copyright 2019 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.io.TFRecordWriter",
"tensorflow.data.TFRecordDataset",
"tensorflow.compat.v1.enable_v2_behavior",
"tensorflow.train.Example"
]
] |
mhd53/ssd-from-torch | [
"1ae6eaab87afd6ef243b2fe444cbb5b15a12cfc7"
] | [
"trainer/trainer.py"
] | [
"import numpy as np\nimport torch\nfrom torchvision.utils import make_grid\nfrom base import BaseTrainer\nfrom utils import inf_loop, MetricTracker\n\n\nclass Trainer(BaseTrainer):\n \"\"\"\n Trainer class\n \"\"\"\n\n def __init__(\n self,\n model,\n criterion,\n metric_ftns... | [
[
"torch.no_grad",
"numpy.sqrt"
]
] |
Lnaden/openmmtools | [
"7a9c61cea5c657e333f433dabbd7c87624f8227f"
] | [
"openmmtools/multistate/sams.py"
] | [
"#!/usr/local/bin/env python\n\n# ==============================================================================\n# MODULE DOCSTRING\n# ==============================================================================\n\n\"\"\"\nSamsSampler\n===========\n\nSelf-adjusted mixture sampling (SAMS), also known as optimally... | [
[
"numpy.log",
"numpy.sum",
"numpy.abs",
"numpy.unique",
"numpy.random.choice",
"numpy.arange",
"numpy.ones",
"numpy.all",
"numpy.where",
"numpy.random.rand",
"numpy.exp",
"numpy.array",
"numpy.zeros",
"scipy.special.logsumexp"
]
] |
tu-rbo/concarne | [
"0e9ae1fa21e132bd240b23e116e7f21e8c45735b"
] | [
"example/simple_multiview.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"\nThis example illustrates how simple it is to train a classifier using\nside information.\n\nIt illustrates the exemplary use of the multi-view pattern; for more info\non how to use other patterns, check out synthetic.py.\n\nFor a realistic example with real data check out handwri... | [
[
"numpy.asarray",
"numpy.random.randn",
"sklearn.linear_model.LogisticRegression"
]
] |
jacr20/pax | [
"d64d0ae4e4ec3e9bb3e61065ed92e9ea23328940"
] | [
"tests/test_posrec_neuralnet.py"
] | [
"import unittest\nimport numpy as np\n\nfrom pax import core, plugin\nfrom pax.datastructure import Event, Peak\n\n\nclass TestPosRecNeuralNet(unittest.TestCase):\n\n def setUp(self):\n self.pax = core.Processor(config_names='XENON100', just_testing=True, config_dict={'pax': {\n 'plugin_group_n... | [
[
"numpy.array",
"numpy.zeros"
]
] |
drholera/olx-parser | [
"837166bca48b39e03bc1987c9ebb2511697fe3fd"
] | [
"parser.py"
] | [
"import requests\nfrom bs4 import BeautifulSoup\nimport pandas as pd\nimport webbrowser\nimport os\nimport io\n\n\nclass Parser(object):\n __url = ''\n __results = []\n\n def __init__(self):\n search_query = input(\"Please, enter your search query \\n\")\n self.__url = 'https://www.olx.ua/lis... | [
[
"pandas.DataFrame"
]
] |
gdevenyi/gabriel.devenyi.ca | [
"cc001f1dc6ed07ff46c3b5cca66865b977710acc"
] | [
"markdown_generator/talks.py"
] | [
"# coding: utf-8\n\n# # Talks markdown generator for academicpages\n#\n# Takes a TSV of talks with metadata and converts them for use with [academicpages.github.io](academicpages.github.io). This is an interactive Jupyter notebook ([see more info here](http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest... | [
[
"pandas.read_csv"
]
] |
saegersven/robocup | [
"3ce18d68d99da43ab12c19417c988bdad38d7373"
] | [
"scripts/calibrate_camera.py"
] | [
"import numpy as np\r\nimport cv2\r\nimport glob\r\nimport array\r\nimport time\r\nimport json\r\n\r\nimage_folder = \"img\" # str(input(\"Input image folder: \"))\r\nout_file = \"test.json\" # str(input(\"Input output file: \"))\r\n\r\nX = 5\r\nY = 7\r\n# Termination criteria\r\ncriteria = (cv2.TERM_CRITERIA_EPS +... | [
[
"numpy.zeros"
]
] |
DavidDePauw1/dairlib | [
"3c75c8f587927b12a58f2e88dda61cc0e7dc82a3"
] | [
"bindings/pydairlib/dircon_trajectory_plotter.py"
] | [
"import sys\nimport matplotlib.pyplot as plt\nimport pydairlib.lcm_trajectory\nfrom pydairlib.common import FindResourceOrThrow\nfrom pydrake.trajectories import PiecewisePolynomial\nimport numpy as np\n\n\ndef main():\n # Default filename for the example\n filename = FindResourceOrThrow(\"examples/Cassie/saved_t... | [
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
jason-sunjiankang/tensorflow_object_detection | [
"dd53b458cb8809b9ec804f31aabdf04c76893977"
] | [
"generate_tfrecord.py"
] | [
"\"\"\"\nUsage:\n # From tensorflow/models/\n # Create train data:\n python generate_tfrecord.py --csv_input=data/train_labels.csv --output_path=train.record\n\n # Create test data:\n python generate_tfrecord.py --csv_input=data/test_labels.csv --output_path=test.record\n\"\"\"\nfrom __future__ import divisi... | [
[
"tensorflow.app.run",
"pandas.read_csv",
"tensorflow.python_io.TFRecordWriter"
]
] |
HashGehlot03/HeartDiseasePrediction | [
"22a24b113d26e2fd776d28fc3c038474fb93741f"
] | [
"model.py"
] | [
"import pandas as pd\r\nfrom sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score\r\nfrom sklearn.linear_model import LogisticRegression\r\nfrom sklearn.tree import DecisionTreeClassifier\r\nfrom sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier... | [
[
"pandas.read_csv",
"sklearn.linear_model.LogisticRegression",
"sklearn.ensemble.RandomForestClassifier",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.ensemble.AdaBoostClassifier",
"sklearn.svm.SVC",
"sklearn.ens... |
feloundou/safe-experts | [
"9592bd48ce7eed721a36cb688dd10dc7f527a13b",
"9592bd48ce7eed721a36cb688dd10dc7f527a13b"
] | [
"algos/train_expert_ppo_penalized.py",
"algos/training_regimes.py"
] | [
"# Main entrance of GAIL\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom adabelief_pytorch import AdaBelief\nimport gym\nimport safety_gym\nimport time\n\n\nfrom neural_nets import ActorCritic, count_vars\n\nfrom utils import BufferActor\nfrom utils import mpi_fork, proc_id, num_procs, Epoc... | [
[
"numpy.random.seed",
"torch.Tensor",
"torch.manual_seed",
"torch.min",
"torch.exp",
"torch.nn.functional.mse_loss",
"torch.clamp",
"numpy.exp"
],
[
"torch.Tensor",
"numpy.random.seed",
"torch.load",
"torch.manual_seed",
"numpy.ones",
"torch.nn.functional... |
Johannes0Horn/Cooperative-Deep-RL-Multi-Agents | [
"fd30246d33a91ae488c3c093a0de55825a43f8b9"
] | [
"SingleAgentProfiling/TD3.py"
] | [
"# Library Imports\nimport numpy as np\nimport tensorflow as tf\n\nclass ReplayBuffer:\n \"\"\"Defines the Buffer dataset from which the agent learns\"\"\"\n def __init__(self, max_size, input_shape, dim_actions):\n self.mem_size = max_size\n self.mem_cntr = 0\n self.state_memory = np.zer... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.clip_by_value",
"tensorflow.concat",
"numpy.random.choice",
"tensorflow.random.normal",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.losses.MSE",
"tensorflow.math.reduce_mean",
"tensorflow.keras.optimizers.Adam",
"numpy.zero... |
czielinski/facerecognition | [
"2ddd9b74a96e3e7eef3dbab52e5eaf7669d33dc4"
] | [
"facerecognition/facerecognition.py"
] | [
"#!/usr/bin/python\n\n# The MIT License (MIT)\n#\n# Copyright (c) 2015 Christian Zielinski\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 l... | [
[
"numpy.hstack"
]
] |
michaelhall28/clone-competition-simulation | [
"deaa68ce020fa3c1b8fa499c91c829bad4f0def6",
"deaa68ce020fa3c1b8fa499c91c829bad4f0def6"
] | [
"clone_competition_simulation/general_sim_class.py",
"clone_competition_simulation/fitness_classes.py"
] | [
"import numpy as np\nimport math\n# import matplotlib as mpl\n# mpl.use('Agg')\nimport matplotlib.pyplot as plt\nimport matplotlib.cm as cm\nimport itertools\nimport bisect\nfrom collections import Counter\nimport pickle\nfrom clone_competition_simulation.useful_functions import mean_clone_size, mean_clone_size_fit... | [
[
"numpy.cumsum",
"numpy.any",
"numpy.searchsorted",
"numpy.where",
"matplotlib.pyplot.gca",
"numpy.unique",
"numpy.arange",
"numpy.full",
"numpy.random.set_state",
"numpy.diff",
"matplotlib.pyplot.close",
"numpy.zeros",
"numpy.isnan",
"matplotlib.pyplot.ylim"... |
samyoo78/NearPy | [
"1b534b864d320d875508e95cd2b76b6d8c07a90b"
] | [
"tests/distances_tests.py"
] | [
"# -*- coding: utf-8 -*-\n\n# Copyright (c) 2013 Ole Krause-Sparmann\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#... | [
[
"scipy.sparse.rand",
"numpy.random.randn"
]
] |
Csinclair0/fairseq | [
"6d9cf6a850c31d12a3ac63e89b005756b09cebeb"
] | [
"fairseq/models/fairseq_model.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\"\"\"\nBase classes for various fairseq models.\n\"\"\"\n\nimport logging\nfrom argparse import Namespace\nfrom typing import Dict, L... | [
[
"torch.nn.functional.log_softmax",
"torch.is_tensor",
"torch.nn.utils.remove_weight_norm",
"torch.nn.functional.softmax"
]
] |
willcanniford/python-notes | [
"1c2a33ab976e589fc6f801de2b6bd740d3aca2d7"
] | [
"machine_learning/sklearn-polynomial.py"
] | [
"# Import the libraries and functions that we are going to need\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.preprocessing import PolynomialFeatures\n\n# Load in some fake data for comparison\ndata = pd.read_csv('./data/po... | [
[
"pandas.read_csv",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.title",
"sklearn.preprocessing.PolynomialFeatures",
"matplotlib.pyplot.plot",
"sklearn.linear_model.LinearRegression",
"matplotlib.pyplot.show"
]
] |
BlinkCreator/Machinelearning_MINIST | [
"02ccefa92c9fd794d7fc1cbc0e2b7767c931c563"
] | [
"main.py"
] | [
"from __future__ import print_function\nimport torch\nimport torch.optim as optim\nimport torchvision\nfrom torchvision import datasets, transforms\nfrom torch.optim.lr_scheduler import StepLR\nfrom models.conv import Net\nfrom models.rnn_conv import ImageRNN\nimport torch.nn.functional as F\nimport matplotlib.pypl... | [
[
"torch.nn.CrossEntropyLoss",
"torch.nn.functional.nll_loss",
"torch.manual_seed",
"torch.no_grad",
"torch.cuda.is_available",
"numpy.transpose",
"torch.device",
"torch.optim.lr_scheduler.StepLR"
]
] |
alumae/audiomentations | [
"275347fcfcf14ea395d228c192efa57496addf8f"
] | [
"audiomentations/augmentations/transforms.py"
] | [
"import functools\nimport os\nimport random\nimport sys\nimport tempfile\nimport uuid\nimport warnings\n\nimport librosa\nimport numpy as np\nfrom scipy.signal import butter, sosfilt, convolve\n\nfrom audiomentations.core.audio_loading_utils import load_sound_file\nfrom audiomentations.core.transforms_interface imp... | [
[
"numpy.amax",
"numpy.ones_like",
"numpy.minimum",
"numpy.linspace",
"numpy.clip",
"numpy.amin",
"scipy.signal.sosfilt",
"numpy.abs",
"numpy.percentile",
"numpy.concatenate",
"scipy.signal.butter",
"numpy.std",
"numpy.zeros_like",
"scipy.signal.convolve",
... |
benjeffery/tsconvert | [
"a7d68389fedf269d45387ecc44842f6ffe24b2cc"
] | [
"tests/test_newick.py"
] | [
"#\n# MIT License\n#\n# Copyright (c) 2019 Tskit Developers\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,... | [
[
"numpy.allclose",
"numpy.linalg.norm",
"numpy.ones"
]
] |
rafmudaf/dash-slicer | [
"e959f1ea94f3bb1d061acd3f18727227a08144ed"
] | [
"tests/test_utils.py"
] | [
"from dash_slicer.utils import (\n img_as_ubyte,\n img_array_to_uri,\n get_thumbnail_size,\n shape3d_to_size2d,\n mask_to_coloured_slices,\n)\n\nimport numpy as np\nfrom pytest import raises\n\n\ndef test_img_as_ubyte():\n\n im = np.zeros((100, 100), np.float32)\n im[0, 0] = 100\n\n # Anythi... | [
[
"numpy.random.uniform",
"numpy.zeros"
]
] |
pji/pjinoise | [
"3967d69fa57be1136cdeb8f4a5d187ee455fa783"
] | [
"tests/test_sources.py"
] | [
"\"\"\"\ntest_sources\n~~~~~~~~~~~~\n\nUnit tests for the pjinoise.generator module.\n\"\"\"\nfrom copy import deepcopy\nimport unittest as ut\nfrom unittest.mock import call, patch\n\nimport numpy as np\n\nfrom pjinoise import sources as s\nfrom pjinoise.common import grayscale_to_ints_list, print_array\nfrom pjin... | [
[
"numpy.around",
"numpy.array",
"numpy.zeros"
]
] |
richford/qsiprep | [
"7499a1479691394775eeab571f36a86c1dac4b54"
] | [
"qsiprep/interfaces/reports.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n\"\"\"\nInterfaces to generate reportlets\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n\n\"\"\"\n\nimport os\nimport os.path as op\nimport time\nimport json\n... | [
[
"numpy.sqrt",
"pandas.DataFrame",
"numpy.concatenate",
"numpy.zeros_like",
"matplotlib.pyplot.tight_layout",
"pandas.read_csv",
"numpy.ones_like",
"numpy.unique",
"numpy.diff",
"matplotlib.pyplot.close",
"numpy.column_stack",
"numpy.load",
"numpy.zeros",
"pa... |
olzhaskabdolov/bot | [
"ea4bd182affe9e607ddb06cf1d7001d6474f10aa"
] | [
"drqa/pipeline/drqa.py"
] | [
"#!/usr/bin/env python3\n# Copyright 2017-present, Facebook, Inc.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\"\"\"Full DrQA pipeline.\"\"\"\n\nimport torch\nimport regex\nimport heapq\nimport math\nimport tim... | [
[
"torch.utils.data.DataLoader"
]
] |
zampie/GAN_framework | [
"8e2ff764b08b9199916fef66e49332ef7d21ae32"
] | [
"refer/train_cartoon_wgan.py"
] | [
"from __future__ import division\nfrom __future__ import print_function\nfrom __future__ import absolute_import\n\nimport glob\nimport utils\nimport traceback\nimport numpy as np\nimport tensorflow as tf\nimport models_64x64 as models\n\n\n\"\"\" param \"\"\"\nepoch = 100\nbatch_size = 64\nlr = 0.0002\nz_dim = 100\... | [
[
"tensorflow.clip_by_value",
"tensorflow.device",
"tensorflow.summary.FileWriter",
"tensorflow.control_dependencies",
"tensorflow.reduce_mean",
"tensorflow.train.RMSPropOptimizer",
"tensorflow.image.resize_images",
"tensorflow.placeholder",
"tensorflow.global_variables_initializ... |
DiddiZ/donk.ai | [
"ccf9a00fb22203a8ab351a5d559d927e6ebfc318"
] | [
"tests/samples_test.py"
] | [
"import unittest\r\n\r\nimport numpy as np\r\nfrom numpy.testing import assert_array_equal\r\n\r\n\r\nclass Test_TransitionPool(unittest.TestCase):\r\n\r\n def test_add(self):\r\n \"\"\"Test TransitionPool.add().\"\"\"\r\n from donk.samples import TransitionPool\r\n\r\n N, T, dX, dU = 3, 10,... | [
[
"numpy.random.default_rng"
]
] |
shanbs/home-assistant | [
"818776d2b4f11e4f51992dc88bc0a6f9055833b2"
] | [
"homeassistant/components/sensor/pollen.py"
] | [
"\"\"\"Support for Pollen.com allergen and cold/flu sensors.\"\"\"\nfrom datetime import timedelta\nimport logging\nfrom statistics import mean\n\nimport voluptuous as vol\n\nfrom homeassistant.components.sensor import PLATFORM_SCHEMA\nfrom homeassistant.const import (\n ATTR_ATTRIBUTION, ATTR_STATE, CONF_MONITO... | [
[
"numpy.array",
"numpy.cumsum"
]
] |
fpirovan/NoiseInjection | [
"d1a8c90aaf45d435d40c476a2d2e74258920ff22"
] | [
"dart/experiments/tools/noise.py"
] | [
"import numpy as np\nimport statistics\n\ndef sample_covariance_lnr(env, lnr, sup, samples, T):\n\n cov = np.zeros(env.action_space.shape[0])\n for s in range(samples):\n states, tmp_actions, _, _ = statistics.collect_traj(env, lnr, T)\n sup_actions = np.array([sup.intended_action(s) for s in st... | [
[
"numpy.dot",
"numpy.identity",
"numpy.array",
"numpy.zeros",
"numpy.trace"
]
] |
dftbplus/phonopy | [
"32d3d52902c314c7f00192d10f7a156d0a8341c9"
] | [
"phonopy/cui/collect_cell_info.py"
] | [
"# Copyright (C) 2018 Atsushi Togo\n# All rights reserved.\n#\n# This file is part of phonopy.\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#\n# * Redistributions of source code must retain the above copyr... | [
[
"numpy.eye"
]
] |
nielsuit227/AutoML | [
"51e2076d52d76dc84a190293b5bb59da2833df89"
] | [
"Amplo/Pipeline.py"
] | [
"import re\nimport os\nimport time\nimport copy\nimport json\nimport Amplo\nimport joblib\nimport shutil\nimport warnings\nimport numpy as np\nimport pandas as pd\nfrom tqdm import tqdm\nfrom datetime import datetime\nfrom shap import TreeExplainer\n\nfrom sklearn import metrics\nfrom sklearn.model_selection import... | [
[
"pandas.read_csv",
"sklearn.model_selection.StratifiedKFold",
"sklearn.model_selection.KFold",
"pandas.DataFrame",
"numpy.std",
"numpy.mean",
"sklearn.metrics.SCORERS.keys",
"numpy.logical_and",
"numpy.where"
]
] |
I-love-lamp/ml-apps | [
"71f65fc284bc68794acd4a39df3a5791fcba7c46"
] | [
"classifier_tuning.py"
] | [
"# -*- coding: utf-8 -*-\r\n\r\nimport streamlit as st\r\nfrom sklearn import datasets\r\nimport pandas as pd\r\nimport numpy as np\r\nfrom sklearn.neighbors import KNeighborsClassifier\r\nfrom sklearn.svm import SVC\r\nfrom sklearn.ensemble import RandomForestClassifier\r\nfrom sklearn.model_selection import train... | [
[
"sklearn.metrics.plot_confusion_matrix",
"sklearn.datasets.load_breast_cancer",
"numpy.unique",
"sklearn.ensemble.RandomForestClassifier",
"sklearn.metrics.accuracy_score",
"sklearn.datasets.load_iris",
"sklearn.model_selection.train_test_split",
"sklearn.metrics.confusion_matrix",... |
FrancisCrickInstitute/hatchet | [
"a92992f3464f4df566ac4e9ff69069e736821b4b"
] | [
"src/hatchet/utils/BBeval.py"
] | [
"#!/usr/bin/python3\n\nimport os\nimport sys\nimport argparse\nimport shutil\nimport subprocess\nimport shlex\nimport sys, os\nimport math\nimport warnings\nimport numpy as np\nimport matplotlib as mpl\nmpl.use('Agg')\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport pandas as pd\nimport matplotlib.co... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.yticks",
"numpy.linspace",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.ylim",
"matplotlib.use",
"pandas.DataFrame",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.close",... |
asbe/PoseCNN | [
"0dc7f4f1d63908a43d5afc1ac4cf327ae88c658c"
] | [
"lib/datasets/ycb.py"
] | [
"__author__ = 'yuxiang'\n\nimport os\nimport datasets\nimport datasets.ycb\nimport datasets.imdb\nimport pickle\nimport numpy as np\nimport cv2\nfrom fcn.config import cfg\nfrom utils.pose_error import *\nfrom transforms3d.quaternions import quat2mat, mat2quat\n\nclass ycb(datasets.imdb):\n def __init__(self, im... | [
[
"numpy.diag",
"numpy.amax",
"numpy.reshape",
"numpy.linalg.norm",
"numpy.stack",
"numpy.nanmean",
"numpy.array",
"numpy.zeros",
"numpy.where",
"numpy.loadtxt"
]
] |
RafalStaszak/TensorflowCourse | [
"af0d7f6d367d078dd8d36ec1e48d0a20f65a90ab"
] | [
"tensorflow/3_regression.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\n\nx_data = np.random.rand(20).astype(np.float32)\ny_data = x_data*1+3+np.random.uniform(0, 0.2, size=[20])\n\nplt.plot(x_data, y_data, 'ro', label='Produced data')\nplt.legend()\nplt.show()\n\na=tf.Variable([0], dtype=tf.float32)\nb=... | [
[
"matplotlib.pyplot.legend",
"tensorflow.Variable",
"matplotlib.pyplot.plot",
"tensorflow.initialize_all_variables",
"tensorflow.train.GradientDescentOptimizer",
"numpy.random.rand",
"tensorflow.Session",
"tensorflow.square",
"numpy.random.uniform",
"matplotlib.pyplot.show"
... |
lpkirwin/pandas | [
"bb929a637ca9d4f24ea78ee4cca9ee17b65a5c1e"
] | [
"pandas/core/internals/blocks.py"
] | [
"from datetime import datetime, timedelta\nimport inspect\nimport re\nfrom typing import TYPE_CHECKING, Any, List, Optional, Type, Union, cast\nimport warnings\n\nimport numpy as np\n\nfrom pandas._libs import NaT, algos as libalgos, internals as libinternals, lib, writers\nfrom pandas._libs.internals import BlockP... | [
[
"pandas.util._validators.validate_bool_kwarg",
"pandas.core.dtypes.cast.maybe_box_datetimelike",
"pandas.core.arrays.DatetimeArray._simple_new",
"pandas.core.missing.clean_interp_method",
"pandas.core.dtypes.common.is_datetime64_dtype",
"numpy.place",
"numpy.where",
"pandas.core.dt... |
sw32-seo/GTA | [
"86b102a14b78f6c8b50d742a56445c748e59b51e"
] | [
"onmt/utils/stats_manager.py"
] | [
"import numpy as np\n\n\nclass StatsManager(object):\n def __init__(self, stat_names=['step', 'acc', 'ppl']):\n self.stat_names = stat_names\n self.train_stats = {}\n self.val_stats = {}\n\n for name in stat_names:\n self.train_stats[name] = []\n self.val_stats[n... | [
[
"numpy.array",
"numpy.argmin",
"numpy.argmax"
]
] |
pik-copan/pycopanpbcc | [
"3fcf0a895cd444f445e1a36f0373fefa4eefe786"
] | [
"scripts/plot_fig8.py"
] | [
"# -*- coding: utf-8 -*-\n# Author: Vera Heck <heck@pik-potsdam.de>\n# Script generates Fig. 8 of Heck et al. 2016 (ESD)\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.cm as cm\nfrom pylab import *\n\narray = np.array\n\nnstep = 128 # steps of parameter variation \npar1='alpha_max'\npar... | [
[
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots_adjust",
"numpy.load",
"matplotlib.pyplot.show",
"matplotlib.cm.get_cmap"
]
] |
robgon-art/music-generator | [
"88a681bef5ee53fcd764e8c156ee97c892f0caf3"
] | [
"program/GANs/data_generator.py"
] | [
"import random\nfrom random import randint\nfrom numpy import array\nimport numpy\nNOTE_SPACE = 24\t\t#two octaves of notes are valid here.\nTRUE_CHORD_FALSE_MAX = 0.0\n\ndef get_three_notes_and_is_chord(all_major=False):\n\tanswer = [0] * NOTE_SPACE\n\tif(randint(0, 1) == 0 or all_major):\t\t#make half major, half... | [
[
"numpy.random.uniform",
"numpy.array"
]
] |
ruizca/xmmpzcat | [
"03938e96ff7cbb44adca6362f1b4492822d7e857"
] | [
"bin/binning.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nFunctions for the creation of bins based on\ndensity of optical and X-ray sources.\n\"\"\"\nimport os\n\nfrom tqdm import tqdm\nfrom astropy.table import Table, vstack\nfrom astropy.coordinates import SkyCoord\nfrom astropy import units as u\nimport numpy as np\n\n#import matplotli... | [
[
"numpy.abs",
"numpy.min",
"numpy.unique",
"numpy.isnan",
"numpy.median",
"numpy.full",
"numpy.logical_or",
"numpy.max",
"numpy.array",
"numpy.logical_and",
"numpy.sum"
]
] |
gnouveau/birdsonganalysis | [
"58032538c63e9506d386e5fff5c2e8321c1d2983"
] | [
"birdsonganalysis/plot.py"
] | [
"\"\"\"Plotting function for birdsonganalysis.\"\"\"\n\nimport numpy as np\n\n\nimport seaborn as sns\n\nimport matplotlib.patches as p\nimport matplotlib.pyplot as plt\n\nfrom .songfeatures import spectral_derivs\nfrom .constants import FREQ_RANGE\n\n\ndef spectral_derivs_plot(spec_der, contrast=0.1, ax=None, freq... | [
[
"numpy.nanmax",
"matplotlib.patches.Rectangle",
"numpy.nanmin",
"matplotlib.pyplot.subplots",
"numpy.flip"
]
] |
llecaroz/multihead_joint_entity_relation_extraction | [
"6cef17bb88700eda336d106b761352e65d8e4bea"
] | [
"tf_utils.py"
] | [
"import utils\nimport time\nimport eval\n\nclass model:\n \"\"\"Set of classes and methods for training the model and computing the ner and head selection loss\"\"\"\n\n\n def __init__(self,config,emb_mtx,sess):\n \"\"\"\"Initialize data\"\"\"\n self.config=config\n self.emb_mtx=emb_mtx\n... | [
[
"tensorflow.cond",
"tensorflow.compat.v1.nn.dropout",
"tensorflow.concat",
"tensorflow.reduce_sum",
"tensorflow.tanh",
"tensorflow.compat.v1.nn.bidirectional_dynamic_rnn",
"tensorflow.compat.v1.nn.sparse_softmax_cross_entropy_with_logits",
"tensorflow.compat.v1.train.AdamOptimizer"... |
gitter-badger/galaxy2galaxy | [
"1374a32a6be252c1eb426ce21bf1e26ffb253bb9"
] | [
"galaxy2galaxy/models/gan_utils.py"
] | [
"\"\"\" Spectral Norm GAN \"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport tensorflow as tf\nimport tensorflow_gan as tfgan\nimport tensorflow_hub as hub\n\nfrom tensorflow_gan.python.estimator.gan_estimator import Optimizers, get_gan... | [
[
"tensorflow.get_variable_scope",
"tensorflow.random.normal",
"tensorflow.placeholder",
"tensorflow.compat.v1.train.AdamOptimizer"
]
] |
simeoncarstens/ensemble_hic | [
"abaec8972866b593e689e39419d1c2d7ab6788dc",
"abaec8972866b593e689e39419d1c2d7ab6788dc"
] | [
"scripts/plots/nora2012/distance_distributions_SI.py",
"ensemble_hic/sphere_prior.py"
] | [
"import os\nimport sys\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.lines import Line2D\n\nprobes = (\n ('pEN1', 100423573, 100433412, 'Linx'),\n ('pEN2', 100622909, 100632521, 'Xite'),\n ('pLG1', 100456274, 100465704, 'Linx'),\t\n ('pLG10', 100641750, 100646253, 'Dxpas34'),\... | [
[
"numpy.sqrt",
"matplotlib.pyplot.subplots",
"numpy.mean",
"numpy.load",
"numpy.array"
],
[
"numpy.zeros",
"numpy.sum"
]
] |
outlk/read-cryosat-2 | [
"3ca032969f4cf5e9edde1e651d2c900bd84fba09"
] | [
"cryosat_toolkit/read_cryosat_L2I.py"
] | [
"#!/usr/bin/env python\nu\"\"\"\nread_cryosat_L2I.py\nWritten by Tyler Sutterley (05/2021)\n\nReads CryoSat Level-2 Intermediate data products from baselines A, B, BC and C\nReads CryoSat Level-2 netCDF4 data products from baseline D\nSupported CryoSat Modes: LRM, SAR, SARin, FDM, SID, GDR\n\nINPUTS:\n full_file... | [
[
"numpy.fromfile",
"numpy.array",
"numpy.zeros",
"numpy.int32"
]
] |
PhMueller/TrajectoryParser | [
"9c19d37a3ff29a593c9b6d3e7fd3857e8c2d724f"
] | [
"HPOBenchExperimentUtils/optimizer/fabolas_optimizer.py"
] | [
"import logging\nfrom pathlib import Path\nfrom typing import Union, Dict, Tuple, Sequence\nimport sys\nimport numpy as np\nfrom math import log2\nimport enum\n\nfrom HPOBenchExperimentUtils.optimizer.base_optimizer import SingleFidelityOptimizer\nfrom HPOBenchExperimentUtils.core.bookkeeper import Bookkeeper\nfrom... | [
[
"numpy.expand_dims",
"numpy.abs",
"numpy.clip",
"numpy.asarray",
"numpy.arange",
"numpy.tile",
"numpy.concatenate",
"numpy.searchsorted",
"numpy.array"
]
] |
mananeau/ALBERT | [
"4409420b7aa3cd355078689e4963d8ad11000ee3"
] | [
"tokenization.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Team Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requi... | [
[
"tensorflow.compat.v1.gfile.GFile",
"tensorflow.compat.v1.Graph",
"tensorflow.compat.v1.logging.info",
"tensorflow.compat.v1.Session"
]
] |
cmccully/astro-scrappy | [
"3ed58dd537e40efed983ca049602af6e3e9f5ce7"
] | [
"astroscrappy/tests/test_utils.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\nfrom __future__ import (absolute_import, division, print_function,\n unicode_literals)\nimport numpy as np\nfrom numpy.testing import assert_allclose\n\nfrom ..utils import (median, optmed3, optmed5, optmed7, optmed9, optmed25,... | [
[
"scipy.ndimage.filters.convolve",
"numpy.random.random",
"numpy.ascontiguousarray",
"numpy.median",
"numpy.ones",
"numpy.all",
"numpy.float32",
"numpy.testing.assert_allclose",
"numpy.array",
"scipy.ndimage.filters.median_filter",
"numpy.zeros"
]
] |
ccuetom/devito | [
"3bd907bed50eff8608e36d83b92c706685a7d275"
] | [
"tests/test_derivatives.py"
] | [
"import numpy as np\nimport pytest\nfrom sympy import simplify, diff, Float\n\nfrom devito import (Grid, Function, TimeFunction, Eq, Operator, NODE, cos, sin,\n ConditionalDimension, left, right, centered, div, grad)\nfrom devito.finite_differences import Derivative, Differentiable\nfrom devito.f... | [
[
"numpy.allclose",
"numpy.linspace",
"numpy.arange",
"numpy.ones",
"numpy.mean",
"numpy.isclose"
]
] |
Fra98/fed-learning-AML | [
"13a4cb3f240ea6ef4340aaf07cf352c7fe075d89"
] | [
"src/fedAVG/server.py"
] | [
"from copy import deepcopy\nimport random\nimport numpy\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\n\nfrom .client import Client\nfrom ..models import *\nfrom ..utils import get_class_priors, load_cifar, run_accuracy, generate_clients_sizes\nfrom ..splits import indexes_split_IID, indexes_spl... | [
[
"torch.utils.data.Subset",
"numpy.sum",
"numpy.random.choice"
]
] |
cihuang123/Next-simulation | [
"e8552a5804184b30022d103d47c8728fb242b5bc"
] | [
"utilities/plot_landing_point.py"
] | [
"import csv\nimport argparse\nimport matplotlib.pyplot as plt\n\ndef toFloat(str):\n try:\n return float(str)\n except ValueError:\n return str\n\nparser = argparse.ArgumentParser(\n description='Read some csv and output landing point.'\n)\nparser.add_argument('golden', help='Input the file p... | [
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
snehasish069/tensorflow-mnist-dataset | [
"9f22235d52c66f37a07359056d5c9ef75a1ccf1a"
] | [
"mnist_tensorflow.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Thu Dec 7 11:19:20 2017\r\n\r\n@author: Snehasish\r\n\"\"\"\r\n\r\nimport tensorflow as tf\r\nfrom tensorflow.examples.tutorials.mnist import input_data\r\n\r\ndata = input_data.read_data_sets(\"/tmp/data/\", one_hot = True)\r\n\r\n#learning rate\r\nLR = 0.001\r\n\r... | [
[
"tensorflow.nn.relu",
"tensorflow.matmul",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.cast",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.Session",
"tensorflow.train.AdamOptimizer",
"tensorflow.argmax",
"tensorflow.exa... |
cortex-lab/phylib | [
"563afac3a7df9ec585fab63b6fe4fc0700f48b7c"
] | [
"phylib/stats/ccg.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"Cross-correlograms.\"\"\"\n\n#------------------------------------------------------------------------------\n# Imports\n#------------------------------------------------------------------------------\n\nimport numpy as np\n\nfrom phylib.utils._types import _as_array\nfrom phylib.i... | [
[
"numpy.maximum",
"numpy.ones_like",
"numpy.clip",
"numpy.asarray",
"numpy.dstack",
"numpy.ravel_multi_index",
"numpy.bincount",
"numpy.diff",
"numpy.transpose",
"numpy.zeros"
]
] |
SamarthMM/cs769-assignments | [
"bac2ad57c50043608276df8e0f21181ef62696c7"
] | [
"assignment2/classifier.py"
] | [
"import time, random, numpy as np, argparse, sys, re, os\nfrom types import SimpleNamespace\n\nimport torch\nimport torch.nn.functional as F\nfrom torch.utils.data import Dataset, DataLoader\nfrom sklearn.metrics import classification_report, f1_score, recall_score, accuracy_score\n\n# change it with respect to the... | [
[
"numpy.random.get_state",
"torch.nn.Dropout",
"torch.LongTensor",
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.nn.functional.log_softmax",
"torch.manual_seed",
"torch.random.get_rng_state",
"torch.load",
"torch.utils.data.DataLoader",
"torch.nn.Linear",
"nu... |
AgusQuintanar/DesignOfAnElectricCircuit | [
"35dd0b96fc4722d6ec5b3c5173ae5cf2147c83d9"
] | [
"graph.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\ndef plot(fun, start, end):\n x = np.arange(float(start), float(end), 0.1)\n \n n_fun = np.vectorize(fun)\n plt.plot(x, n_fun(x))\n\n plt.show()\n\n\nif __name__ == \"__main__\":\n fun = lambda x: x**2 - 1\n plot(fun, -5, 5)"
] | [
[
"numpy.vectorize",
"matplotlib.pyplot.show"
]
] |
jiangwenj02/Meta-weight-net_class-imbalance | [
"5f7cdb3e0b66336a44695a9b8d240de0e3a3a2c8"
] | [
"meta-weight-net-class-imbalance.py"
] | [
"import os\nos.environ[\"CUDA_DEVICE_ORDER\"]=\"PCI_BUS_ID\"\n# os.environ[\"CUDA_VISIBLE_DEVICES\"]=\"0\"\n\nimport time\nimport argparse\nimport random\nimport copy\nimport torch\nimport torchvision\nimport numpy as np\nimport pandas as pd\nimport sklearn.metrics as sm\nimport torch.nn.functional as F\nfrom torch... | [
[
"torch.manual_seed",
"torch.nn.functional.cross_entropy",
"torch.sum",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device",
"torch.autograd.Variable"
]
] |
jchen0506/molecool | [
"dc931c165c34edeae4a38e67976138c017c5857c"
] | [
"molecool/visualize.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\nfrom mpl_toolkits.mplot3d import Axes3D # noqat: F401\n\nfrom .atom_data import (\n atom_colors,\n) # .atome_data relative import, . check the same folder\n\n\ndef bond_histogram(bond_list, save_location=None, dpi=300, graph_min=0, graph_max=2):\n # Dr... | [
[
"numpy.linspace",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.xlabel",
"numpy.array",
"matplotlib.pyplot.ylabel"
]
] |
iwonasob/DCASE_rare | [
"3f9f55a1958602ac61e2e5ab02866d7215a5d131"
] | [
"src/dataset.py"
] | [
"'''\nDownload, extract and partition the datasets\n'''\nimport config as cfg\nimport os\nimport sys\nimport requests\nimport zipfile\nfrom clint.textui import progress\nimport numpy as np\nnp.random.seed(1515)\nimport pandas as pd\n\n\nclass DatasetCreator:\n def __init__(self,\n dataset_name):\... | [
[
"pandas.read_csv",
"numpy.random.seed"
]
] |
Luoyadan/ddpg_power | [
"9f1bcd0c3874229933070b47f96e554738a72a77"
] | [
"ddpg.py"
] | [
"# -----------------------------------\n# Deep Deterministic Policy Gradient\n# Author: Flood Sung\n# Date: 2016.5.4\n# -----------------------------------\n\nimport tensorflow as tf\nimport numpy as np\nfrom ou_noise import OUNoise\nfrom critic_network import CriticNetwork \nfrom actor_network_bn import ActorNetwo... | [
[
"numpy.asarray",
"numpy.resize",
"tensorflow.InteractiveSession"
]
] |
Croydon-Brixton/gedi-biomass-mapping | [
"bd6021a8515597d5ce14221afa47758803b4864a"
] | [
"src/data/gedi_query_tools.py"
] | [
"\"\"\"Module to conveniently query GEDI v002 data (primarily L1B and L2A) locally\"\"\"\nimport pathlib\nfrom dataclasses import dataclass\n\nimport folium\nimport folium.features\nimport folium.plugins\nimport geopandas as gpd\nimport pandas as pd\nimport shapely\nimport shapely.geometry\n\nfrom src.constants imp... | [
[
"pandas.to_datetime"
]
] |
awesome-archive/urh | [
"c8c3aabc9d637ca660d8c72c3d8372055e0f3ec7"
] | [
"src/urh/dev/native/HackRF.py"
] | [
"import numpy as np\nimport time\n\nfrom urh.dev.native.Device import Device\nfrom urh.dev.native.lib import hackrf\nfrom urh.util.Logger import logger\n\n\nclass HackRF(Device):\n BYTES_PER_SAMPLE = 2 # HackRF device produces 8 bit unsigned IQ data\n\n def __init__(self, bw, freq, gain, srate, is_ringbuffer... | [
[
"numpy.frombuffer",
"numpy.empty"
]
] |
johnson1228/g2p-seq2seq | [
"2fac457e066df48038a7682be69f3bd8b9fff916"
] | [
"g2p_seq2seq/g2p.py"
] | [
"# Copyright 2016 AC Technologies 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 require... | [
[
"numpy.split",
"tensorflow.gfile.GFile",
"tensorflow.python.util.compat.as_text",
"tensorflow.python.estimator.estimator.ops.Graph",
"tensorflow.get_default_graph",
"tensorflow.py_func",
"tensorflow.python.estimator.estimator._check_hooks_type",
"tensorflow.Graph",
"tensorflow.... |
sebastiengilbert73/synthetic_heatmap | [
"8a1f21f4eaf5a56374b77a4238be97a7005cdb58"
] | [
"src/synthetic_heatmap/generators/stop_sign.py"
] | [
"from synthetic_heatmap.generator import Generator, RegularPolygonVertices, WarpAffinePoints, DownloadRandomImage\nimport cv2\nimport numpy as np\nimport random\nimport math\nimport urllib.request\nimport os\n\nclass StopSign(Generator):\n def __init__(self, octogon_diameter_range=(1.3, 1.3),\n f... | [
[
"numpy.random.random",
"numpy.nonzero",
"numpy.ones",
"numpy.mean",
"numpy.random.uniform",
"numpy.array",
"numpy.zeros"
]
] |
giaba90/python-thesis | [
"8a6d951fc3a1e58b510b7f3f9d1df6ef109711e3"
] | [
"algoritmo2.py"
] | [
"from itertools import combinations\n\nimport numpy as np\nimport utility\n\ndef sol2(vet1, indice, vet_in):\n out = []\n while indice >= 1:\n # converto in lista la combinations\n vet2 = list(combinations(vet1, indice))\n for riga in vet2:\n # trasformo il vettore in input in ... | [
[
"numpy.array"
]
] |
Jingqiao-Zhao/DCASE2020-Task1-SubtaskB | [
"b9474ad68751a7201323364de34bd9630f76f74c"
] | [
"utilities/sparse_image_warp_pytorch.py"
] | [
"# Copyright 2019 RnD at Spoon Radio\r\n\r\n#\r\n\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n\r\n# you may not use this file except in compliance with the License.\r\n\r\n# You may obtain a copy of the License at\r\n\r\n#\r\n\r\n# http://www.apache.org/licenses/LICENSE-2.0\r\n\r\n... | [
[
"torch.transpose",
"torch.max",
"numpy.linspace",
"torch.cat",
"torch.zeros",
"torch.pow",
"torch.ones",
"numpy.reshape",
"torch.solve",
"torch.reshape",
"torch.randn",
"torch.sqrt",
"numpy.stack",
"torch.tensor",
"torch.mul",
"torch.square",
"to... |
DrewRust/lambdata2-drewrust | [
"c2fcd57bf898f5564225e06f465a1b11671b08cf"
] | [
"my_lambdata/ds_utilities.py"
] | [
"import pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\n# from sklearn.datasets import load_wine\n# from pdb import set_trace as breakpoint\n# from IPython.display import display\n\ndef enlarge(n):\n ''' \n This function will multiple the input by 100 \n '''\n ret... | [
[
"pandas.read_csv",
"pandas.to_datetime",
"sklearn.model_selection.train_test_split",
"pandas.Series"
]
] |
saxenam06/Approximate-Dynamic-Programming | [
"de613c10e087ae6b4a87a1730104c59442b33797"
] | [
"plot.py"
] | [
"from config import GeneralConfig, DynamicsConfig, PlotConfig\nimport numpy as np\nimport torch\nimport time\nimport os\nfrom network import Actor, Critic\nfrom solver import Solver\nfrom utils import idplot, numpy2torch, step_relative, recover_absolute_state, cm2inch\nimport matplotlib.pyplot as plt\n\nimport dyna... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.tight_layout",
"numpy.expand_dims",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.ylim",
"torch.from_numpy",
"matplotlib.pyplot.savefig",
"torch.tensor",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlim",
"matplotlib.pyp... |
schackv/shapewarp | [
"36c69a641fc06239eda48b9e7011e3e86f9f7da0"
] | [
"shapewarp/ASM.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Jun 18 11:18:20 2014\n\n@author: schackv\n\"\"\"\n\nfrom . import GPA\nimport numpy as np\n\n\nclass ASM:\n \n def build(self,landmarks):\n \"\"\"Build an active shape model from the landmarks given.\n Landmarks are expected to be a numpy N x 2*p ... | [
[
"numpy.abs",
"numpy.sqrt",
"numpy.linalg.eig",
"numpy.argsort",
"numpy.array",
"numpy.sum"
]
] |
anilgeorge04/learn-ds | [
"f1a9c638e29270d4d72fc3aed0af3ccea8c53350"
] | [
"python-play/hackerstat.py"
] | [
"# Hacker Statistics\r\n# In a 100 storey building, move up and down floors on the roll of dice\r\n# Move up +1 on getting a 3 or 4 or 5\r\n# Move down -1 on getting 1 or 2\r\n# On 6, roll die again and move +n steps (n is the number on second roll)\r\n\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nnp... | [
[
"numpy.random.seed",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.clf",
"numpy.random.rand",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.hist",
"numpy.random.randint"
]
] |
erykoff/redmapper_duster | [
"9058d84905535230c330803de18575670da03bf4"
] | [
"duster/pdfs.py"
] | [
"import numpy as np\n\n\ndef p_dust(rho_0, b, rho_min, rho_vals):\n \"\"\"Compute p_dust(rho | rho_0, b, rho_min)\n\n Parameters\n ----------\n rho_0 : `float`\n The value of rho_0\n b : `float`\n The value of b\n rho_min : `float`\n The value of rho_min\n rho_vals : `np.nd... | [
[
"numpy.exp",
"numpy.zeros"
]
] |
zehuilu/Learning-from-Directional-Corrections | [
"762a05b0d169c0db12932b8bc3f5b4abfa5d6fb9"
] | [
"experiments/run_quad_realtime.py"
] | [
"#!/usr/bin/env python3\nimport os\nimport sys\nsys.path.append(os.getcwd()+'/LFC')\nsys.path.append(os.getcwd()+'/JinEnv')\nsys.path.append(os.getcwd()+'/lib')\nimport numpy as np\nfrom casadi import *\nimport transforms3d\nfrom QuadAlgorithmRealtime import QuadAlgorithmRealtime\nfrom QuadStates import QuadStates\... | [
[
"numpy.array"
]
] |
AndySrb/ProracunOsvetljenjaUlica | [
"1eeeb5f92c24889819594646ee22639943035dd9"
] | [
"main.py"
] | [
"#!/usr/bin/env python3\n\nimport json\nimport math\n\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom matplotlib import cm\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nclass vector2F:\n def __init__(self,x,y):\n self.x=x\n self.y=y\n\nclass vector3F:\n def __init__(self,x,y,z):\n ... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
dibyajit30/Course-Works | [
"f8c275a61651a757cdac562d07d373f15d27f05c"
] | [
"Deep Reinforcement Learning/immitation learning/utils.py"
] | [
"import numpy as np\nfrom torch import argmax\n\nLEFT =1\nRIGHT = 2\nSTRAIGHT = 0\nACCELERATE =3\nBRAKE = 4\n\ndef one_hot(labels):\n \"\"\"\n this creates a one hot encoding from a flat vector:\n i.e. given y = [0,2,1]\n it creates y_one_hot = [[1,0,0], [0,0,1], [0,1,0]]\n \"\"\"\n classes = np.... | [
[
"numpy.dot",
"numpy.unique",
"numpy.array",
"numpy.zeros",
"torch.argmax"
]
] |
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