repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
joeylamcy/gchp | [
"0e1676300fc91000ecb43539cabf1f342d718fb3"
] | [
"ESMF/src/addon/ESMPy/examples/locstream_grid_regrid.py"
] | [
"# This example demonstrates how to regrid between a LocStream and a Grid.\n# The data files can be retrieved from the ESMF data repository by uncommenting the\n# following block of code:\n#\n# import os\n# DD = os.path.join(os.getcwd(), \"examples/data\")\n# if not os.path.isdir(DD):\n# os.makedirs(DD)\n# from... | [
[
"numpy.array",
"numpy.where",
"numpy.prod",
"numpy.ravel",
"numpy.cos",
"numpy.abs"
]
] |
rohit9934/DRIVE-Digital-Retinal-Images-for-Vessel-Extraction | [
"8ed44675500bdd60b2ba58cdac79b6902fbe4f99"
] | [
"DRIVE/perception/infers/segmention_infer.py"
] | [
"# -- coding: utf-8 --\n\"\"\"\nCopyright (c) 2018. All rights reserved.\nCreated by Rohit Sharma, Abdul Mugeesh and Kanishk Nama..\n\"\"\"\n\n\n#The purpose of the Segmentation Infer file is to help testing process and show How to predict.\n\n\n#Importing all libraries...\nimport glob,cv2,numpy as np\nimport matpl... | [
[
"numpy.reshape",
"matplotlib.pyplot.imread"
]
] |
Dong-gi/Dong-gi.github.io | [
"2c3d083db72e06032a1daf528ee9b175219aa554"
] | [
"Repositories/Raspbian/cv07.py"
] | [
"import numpy as np\nimport cv2\n\nimg1 = cv2.imread('start05.jpg')\nimg2 = cv2.imread('start05-2.jpg')\n\nprint(cv2.add(np.uint8([250]), np.uint8([20])))\n\n# dst = a*img1 + b*img2 + c\ncv2.imshow('Image Blending', cv2.addWeighted(img1, 0.3, img2, 0.7, 0))\ncv2.waitKey(0)\n\n# put logo on top-left\nlogo = cv2.imre... | [
[
"numpy.uint8"
]
] |
vishalbelsare/AmortizedCausalDiscovery | [
"eaea1e4be3583b896bd9c2653e87869b302dd7c4"
] | [
"codebase/train.py"
] | [
"from __future__ import division\nfrom __future__ import print_function\n\nfrom collections import defaultdict\n\nimport time\nimport numpy as np\nimport torch\n\nfrom model.modules import *\nfrom utils import arg_parser, logger, data_loader, forward_pass_and_eval\nfrom model import utils, model_loader\n\n\ndef tra... | [
[
"numpy.log",
"torch.no_grad",
"numpy.mean",
"torch.load"
]
] |
billy000400/MLTracking | [
"e5bd3e1f51919a093bb05d78ec9c3fa7877c3744"
] | [
"python/Utility/Metric.py"
] | [
"import sys\nfrom pathlib import Path\n\nimport tensorflow as tf\nfrom tensorflow.math import exp\nfrom tensorflow.keras.metrics import (\n binary_accuracy,\n categorical_accuracy\n)\nfrom tensorflow.keras.backend import print_tensor\n\n\ndef union(rec_a, rec_b, intersection):\n area_a = (rec_a[1]-rec_a[0]... | [
[
"tensorflow.stack",
"tensorflow.cast",
"tensorflow.shape",
"tensorflow.less",
"tensorflow.math.reduce_sum",
"tensorflow.argmax",
"tensorflow.while_loop",
"tensorflow.math.is_nan",
"tensorflow.add",
"tensorflow.math.reduce_min",
"tensorflow.math.exp",
"tensorflow.mat... |
haniamatera/cds-visual_new | [
"91c52cb607c839e6b23881aca047bda7c9888b29"
] | [
"Assignment4/src/lr-mnist.py"
] | [
"#____Assignment4_____#\n#building logistic regression classifier \n\n#importing necessary packages \n\nimport os\nimport sys\nimport argparse\nsys.path.append(os.path.join(\"..\"))\n\n# Import teaching utils\nimport numpy as np\nimport utils.classifier_utils as clf_util\n\n# Import sklearn metrics\nfrom sklearn im... | [
[
"sklearn.datasets.fetch_openml",
"numpy.array",
"sklearn.metrics.accuracy_score",
"sklearn.metrics.classification_report",
"sklearn.linear_model.LogisticRegression",
"sklearn.model_selection.train_test_split"
]
] |
dsoumis/NeuralNetworks_Intro | [
"9f11600faf867dc6b137848e66f391a9564e137d"
] | [
"new_representation.py"
] | [
"import sys\n\nimport keras\nimport numpy\nimport pandas\nfrom keras import layers\nfrom keras.models import load_model\n\n\ndef assign_values_from_arguments():\n inp = \"\"\n mod = \"\"\n\n if len(sys.argv) != 5:\n print(\"Please re-run with correct arguments.\")\n sys.exit()\n\n for i in... | [
[
"pandas.read_csv",
"numpy.savetxt"
]
] |
bertop89/fnc-1-baseline | [
"c15343b1563a137a293e3b37c57088d09e370365"
] | [
"utils/generate_test_splits.py"
] | [
"import random\nimport os\nfrom collections import defaultdict\nimport numpy as np\nfrom random import randint\n\n\ndef generate_hold_out_split (dataset, training = 0.8, base_dir=\"splits\"):\n r = random.Random()\n r.seed(1489215)\n\n article_ids = list(dataset.articles.keys()) # get a list of article id... | [
[
"numpy.expand_dims",
"numpy.load",
"numpy.save"
]
] |
chuanqi129/tensorflow | [
"84eb083bb5328912dde064b8b0f61d28c6edbe43"
] | [
"tensorflow/lite/testing/op_tests/batch_to_space_nd.py"
] | [
"# Copyright 2019 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.lite.testing.zip_test_utils.make_zip_of_tests",
"tensorflow.compat.v1.compat.v1.placeholder",
"numpy.array",
"tensorflow.compat.v1.batch_to_space_nd",
"tensorflow.lite.testing.zip_test_utils.register_make_test_function",
"tensorflow.lite.testing.zip_test_utils.create_tensor_dat... |
martinschorb/dask-image | [
"03242d151db30b4adce3d6c7f43c05d1e7580bb5",
"03242d151db30b4adce3d6c7f43c05d1e7580bb5"
] | [
"dask_image/ndfilters/_utils.py",
"tests/test_dask_image/test_ndfilters/test_cupy_threshold.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom __future__ import division\n\nimport collections\nimport inspect\nimport numbers\nimport re\n\nimport numpy\n\n\ndef _get_docstring(func):\n # Drop the output parameter from the docstring.\n split_doc_params = lambda s: re.subn( # noqa: E731\n \"... | [
[
"numpy.array",
"numpy.ones"
],
[
"numpy.array"
]
] |
dmitryduev/kowalski-dev | [
"0d568dff8e3f25ed522127584a22dfcef08420d8"
] | [
"kowalski/api.py"
] | [
"from abc import ABC\nfrom aiohttp import web, ClientSession\nfrom aiohttp_swagger3 import SwaggerDocs, ReDocUiSettings\nfrom astropy.io import fits\nfrom astropy.visualization import (\n AsymmetricPercentileInterval,\n MinMaxInterval,\n ZScaleInterval,\n LinearStretch,\n LogStretch,\n AsinhStretc... | [
[
"numpy.array",
"numpy.isnan",
"numpy.nan_to_num",
"numpy.median",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"numpy.flipud",
"matplotlib.pyplot.Axes",
"numpy.abs",
"matplotlib.colors.LogNorm"
]
] |
linklab/e_learning_rl | [
"16c11c17dfb304959cb80912e29d0540e6ed6cd5"
] | [
"basic2/practice_3/cliff_td_comparison.py"
] | [
"import numpy as np\nimport os\nimport matplotlib.pyplot as plt\nimport random\n\nfrom basic.practice_1.cliff import CliffGridWorld\n\n# 그리드월드 높이와 너비\nGRID_HEIGHT = 4\nGRID_WIDTH = 12\n\nNUM_ACTIONS = 4\n\n# 탐색 확률\nEPSILON = 0.1\n\n# 스텝 사이즈\nALPHA = 0.5\n\n# 감가율\nGAMMA = 1.0\n\n# 초기 상태와 종료 상태\nSTART_STATE = (3, 0)\... | [
[
"numpy.max",
"numpy.random.choice",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"numpy.argmax",
"matplotlib.pyplot.ylabel"
]
] |
neutronimaging/BraggEdgeFitting | [
"233407fc000425ee79897e514964ef196ca27a08"
] | [
"notebooks/__code/kropff.py"
] | [
"import numpy as np\nfrom qtpy import QtGui\nfrom qtpy.QtWidgets import QFileDialog\nfrom pathlib import Path\nimport pyqtgraph as pg\n\nfrom __code.table_handler import TableHandler\nfrom __code.bragg_edge_peak_fitting_gui_utility import GuiUtility\nfrom __code.kropff_fitting_job_handler import KropffFittingJobHan... | [
[
"numpy.log",
"numpy.arange",
"numpy.float"
]
] |
valentinlemaire/pydl8.5 | [
"a846f3c36bacbbe01ff87c31413342069b0cf61b"
] | [
"dl85/supervised/regressors/quantile_regressor.py"
] | [
"from sklearn.base import RegressorMixin\nfrom ...predictors.quantile_predictor import DL85QuantilePredictor\nfrom sklearn.neighbors import KernelDensity\nimport numpy as np\nfrom math import floor, ceil\nimport json\n\n\nclass DL85QuantileRegressor(DL85QuantilePredictor, RegressorMixin):\n \"\"\"An optimal bina... | [
[
"numpy.argsort"
]
] |
NothingToSay99/HOB-net | [
"77d52fbd6cab5d24f6a724f146dc71e80759c1f9"
] | [
"reid/engine/trainer.py"
] | [
"# encoding: utf-8\n\nimport logging\n\nimport torch\nimport torch.nn as nn\nfrom ignite.engine import Engine, Events\nfrom ignite.handlers import ModelCheckpoint, Timer\nfrom ignite.metrics import RunningAverage\n\nfrom utils.reid_metric import R1_mAP\n\nglobal ITER\nITER = 0\n\ndef create_supervised_trainer(model... | [
[
"torch.nn.DataParallel",
"torch.cuda.device_count"
]
] |
Jibanprakash/tensorflow | [
"dcb10b1d557168646204239bea6ca5bf1abc40a3"
] | [
"tensorflow/python/kernel_tests/segment_reduction_ops_test.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"numpy.array",
"tensorflow.python.framework.ops.Graph",
"numpy.asarray",
"numpy.zeros",
"tensorflow.python.ops.math_ops.unsorted_segment_sum",
"numpy.place",
"numpy.ones",
"tensorflow.python.client.session.Session",
"tensorflow.python.framework.constant_op.constant",
"tenso... |
Mrprogrammernobrainz/informaticscalc | [
"5dbdd29128cb45f59efac7cc407f2e474b454ccd"
] | [
"MAIN.py"
] | [
"import numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport random as rand\r\nimport time as tm\r\ndef plus():\r\n print(\"Вы выбрали 'Сложение', ответ будет дан в десятичной\\nУкажите первое число\")\r\n firstnum = int(input())\r\n print(\"Укажите систему счисления первого числа\")\r\n firstnumsys... | [
[
"matplotlib.pyplot.pie",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.pyplot.axes"
]
] |
godmoves/PhoenixGo | [
"8c813d10315660626f18e3985bbcb87ea5c684a5"
] | [
"training/tf_training/v2_write_training.py"
] | [
"#!/usr/bin/env python3\n#\n# Used to dump training games in V2 format from MongoDB or V1 chunk files.\n#\n# Usage: v2_write_training [chunk_prefix]\n# If run without a chunk_prefix it reads from MongoDB.\n# With a chunk prefix, it uses all chunk files with that prefix\n# as input.\n#\n# Sets up a dataflow pipe... | [
[
"numpy.random.randint"
]
] |
leoagneau/Bib_Racer | [
"83c90bb3177ca13a78bee3ff0e800fbf0dd8484e"
] | [
"SVHN/SVHN_recognizer_single_digit.py"
] | [
"############################\n### Prepare SVHN dataset ###\n############################\n\nimport os\nimport numpy as np\nimport h5py\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.optim import lr_scheduler\nfrom torch.utils.data import DataLoader\nimport torchvision\nfrom torchvisi... | [
[
"torch.nn.Linear",
"torch.device",
"numpy.array",
"torch.optim.lr_scheduler.StepLR",
"torch.max",
"matplotlib.pyplot.title",
"torch.set_grad_enabled",
"torch.sum",
"torch.cuda.is_available",
"matplotlib.pyplot.pause",
"torch.utils.data.DataLoader",
"numpy.clip",
... |
vedraiyani/MyJupyterWorkflow | [
"cc97c3d6166e7d917099fdcd9e227371c11c5521"
] | [
"jupyterworkflow/tests/test_data.py"
] | [
"# python -m pytest jupyterworkflow\n\nfrom jupyterworkflow.data import get_fremont_data\nimport pandas as pd\nimport numpy as np\n\ndef test_fremont_data():\n df=get_fremont_data()\n assert all(df.columns==['East', 'West', 'Total'])\n assert isinstance(df.index,pd.DatetimeIndex)\n assert len(np.unique(... | [
[
"numpy.unique"
]
] |
yyht/cleanlab | [
"00678f1ec08d97ffcba40de544859d64dc3fb1ad"
] | [
"examples/classifier_comparison.py"
] | [
"\n# coding: utf-8\n\n# # Classifier Comparison Tutorial\n# ## In this example, we demonstrate how the cleanlab package can be used with any classifier and dataset distribution. We compare performance across 10 classifiers and 4 dataset distributions in both the binary and multiclass classification setting.\n# \n# ... | [
[
"numpy.bincount",
"sklearn.svm.SVC",
"sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis",
"numpy.arange",
"sklearn.datasets.make_circles",
"matplotlib.pyplot.tight_layout",
"sklearn.datasets.make_moons",
"sklearn.datasets.make_classification",
"sklearn.ensemble.AdaBoo... |
bethgelab/robustness | [
"aa0a6798fe3973bae5f47561721b59b39f126ab7"
] | [
"examples/imagenet_d/main.py"
] | [
"import argparse\nimport os\nimport random\nimport shutil\nimport time\nimport warnings\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.parallel\nimport torch.backends.cudnn as cudnn\nimport torch.distributed as dist\nimport torch.optim\nimport torch.multiprocessing as mp\nimport torch.utils.data\nimport to... | [
[
"torch.zeros",
"torch.distributed.init_process_group",
"torch.save",
"torch.no_grad",
"torch.multiprocessing.spawn",
"torch.nn.parallel.DistributedDataParallel",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.cuda.is_available",
"torch.u... |
marioviti/nn_segmentation | [
"b754b38cd1898c0746e383ecd32d9d4c33c60b33"
] | [
"models/MimoNet.py"
] | [
"from layers import *\nfrom serialize import *\nfrom metrics_and_losses import *\nfrom GenericModel import GenericModel\n\nimport numpy as np\n\nfrom keras import backend as K\nfrom keras.losses import binary_crossentropy, categorical_crossentropy\nfrom keras.utils import to_categorical\nfrom keras.optimizers impor... | [
[
"tensorflow.convert_to_tensor",
"scipy.ndimage.filters.gaussian_filter",
"numpy.zeros",
"tensorflow.cast"
]
] |
llavkush/greyatom-python-for-data-science | [
"c82f9e28c9ef000becdf635d00ab0a8816e683fb"
] | [
"Visualization/code.py"
] | [
"# --------------\n#Importing header files\r\nimport pandas as pd\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\ndata = pd.read_csv(path)\r\nloan_status= data[\"Loan_Status\"].value_counts()\r\nloan_status.plot(kind =\"bar\")\r\n\r\n\r\n#Code starts here\n\n\n# --------------\n#Code starts here\r\nprop... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.ylabel",
"pandas.read_csv",
"matplotlib.pyplot.xticks"
]
] |
riciche/RetinaNet_Tensorflow_Rotation | [
"b03a7eafba21bfbb78dbffe1be53ab914080201e"
] | [
"libs/configs/cfgs_res50_dota_v6.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import division, print_function, absolute_import\nimport os\nimport tensorflow as tf\nimport math\n\n\"\"\"\nThis is your evaluation result for task 1:\n\n mAP: 0.6089394631017461\n ap of each class:\n plane:0.8859576592098442,\n baseball-diamond:0.6745883911474... | [
[
"tensorflow.constant_initializer",
"tensorflow.random_normal_initializer"
]
] |
Manikant92/BioSyn | [
"2f0f02769acf82fc110c724a581dd2675c47d655"
] | [
"src/biosyn/rerankNet.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nimport logging\nfrom tqdm import tqdm\nLOGGER = logging.getLogger(__name__)\n\nclass RerankNet(nn.Module):\n def __init__(self, encoder, learning_rate, weight_decay, sparse_weight, use_cuda):\n\n LOGGER.inf... | [
[
"torch.cat",
"torch.no_grad",
"torch.clamp",
"torch.nn.functional.softmax",
"torch.log"
]
] |
Lingistic/GraBTax | [
"ff8e313891da88ffaebc5393cf9b2d7a8650131c"
] | [
"lib/build_graph.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nprocesses a document topic matrix and determines the strength of a topic as a function of it's co-occurrences among\nthe corpus, beyond a threshold\n\"\"\"\n\nimport numpy\nfrom networkx import Graph, write_graphml, read_graphml, get_edge_attributes\nimport logging\nimport os\nimport... | [
[
"numpy.logical_or",
"numpy.zeros",
"numpy.nansum",
"numpy.logical_and",
"numpy.where"
]
] |
ajleite/basic-ppo | [
"e9d823275dda3c376e3e0f7d66e8dfb815b434d8"
] | [
"ppo.py"
] | [
"#!/usr/bin/python3\n\n# Copyright 2019 Abe Leite\n# Based on \"Proximal Policy Optimization Algorithms\", Schulman et al 2017\n# For the benefit of my fellow CSCI-B 659 students\n# While I hope that this code is helpful I will not vouch for its total accuracy;\n# my primary aim here is to elucidate the ideas from ... | [
[
"tensorflow.zeros",
"tensorflow.range",
"tensorflow.where",
"tensorflow.keras.layers.InputLayer",
"tensorflow.expand_dims",
"tensorflow.gradients",
"tensorflow.stop_gradient",
"tensorflow.keras.layers.Dense",
"tensorflow.clip_by_value",
"tensorflow.reduce_sum",
"tensorf... |
YingzhenLi/SteinGrad | [
"6c9b3f3bd51fabfa61890c75bdbccb22c03baa61"
] | [
"began/kernel.py"
] | [
"import tensorflow as tf\n\ndef Epanechnikov_kernel(z, K):\n z_ = tf.expand_dims(z, 1)\n pdist_square = (z - tf.stop_gradient(z_))**2\n kzz = tf.reduce_mean(1 - pdist_square, -1)\n\n return kzz, tf.constant(1.0)\n \n"
] | [
[
"tensorflow.constant",
"tensorflow.reduce_mean",
"tensorflow.stop_gradient",
"tensorflow.expand_dims"
]
] |
quoctrinh8811/AI-for-Finance | [
"d57f1ed0d98c1659d9ea953a9fa8d1c8194811c5"
] | [
"Section 5/source/prep.py"
] | [
"\"\"\"\nPrepare stock prices data for use in an LSTM network.\n\nOur goal here is to predict a closing price of a share/stock\non a given day of a company based on the metrics from previous day.\n\nWe're working with historical stock prices data in .CSV format\nfor Apple (APPL) (but the code is general and you can... | [
[
"numpy.array",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.show",
"pandas.read_csv",
"numpy.expand_dims"
]
] |
hpi-sam/minimum-wage-rl | [
"f9342168955d2fa2623f427a6869e402592944b4"
] | [
"plot_data.py"
] | [
"import time\nimport matplotlib.pyplot as plt\nfrom numpy.core import umath\nfrom numpy.core.numeric import count_nonzero\nfrom numpy.lib.function_base import average\nplt.ion()\nimport numpy as np\nimport pandas as pd\n\nplt.style.use(\"dark_background\")\n\nclass DynamicUpdate():\n #Suppose we know the x range... | [
[
"matplotlib.pyplot.ion",
"pandas.read_excel",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.style.use",
"matplotlib.pyplot.show"
]
] |
shinke-li/Campus3D | [
"21768908b064d19ce8daacc2fa0a1fe9e0331514"
] | [
"dataset/data_utils/point_util.py"
] | [
"import numpy as np\n\n\ndef gen_gaussian_ball(center, radius, size):\n if not isinstance(radius, np.ndarray):\n radius = np.asarray([radius, radius, radius])\n pts = [np.random.normal(loc=center[i], scale=radius[i], size=size) for i in range(center.shape[0])]\n return np.asarray(pts).transpose()\n\... | [
[
"numpy.concatenate",
"numpy.random.normal",
"numpy.array",
"numpy.random.rand",
"numpy.asarray",
"numpy.sum",
"numpy.min",
"numpy.vstack"
]
] |
cyq373/SSD-GAN | [
"9dc956fd79cc2b21492fcc9bf1e4cdc5b276bdaf"
] | [
"ssd_gan.py"
] | [
"\"\"\"\nImplementation of Base SSD-GAN models.\n\"\"\"\nimport torch\n\nfrom torch_mimicry.nets.basemodel import basemodel\nfrom torch_mimicry.modules import losses\nimport numpy as np\n\n\nclass SSD_Generator(basemodel.BaseModel):\n r\"\"\"\n Base class for a generic unconditional generator model.\n\n At... | [
[
"torch.sigmoid",
"torch.randn"
]
] |
AWIS99/Emojinator | [
"bc331eba1b37520e54103a7d542e2fc9ec3a0115"
] | [
"emoji_model.py"
] | [
"import numpy as np\nfrom keras import layers\nfrom keras.layers import Input, Dense, Activation, ZeroPadding2D, BatchNormalization, Flatten, Conv2D\nfrom keras.layers import AveragePooling2D, MaxPooling2D, Dropout, GlobalMaxPooling2D, GlobalAveragePooling2D\nfrom keras.utils import np_utils\nfrom keras.models impo... | [
[
"numpy.array",
"pandas.read_csv",
"numpy.random.shuffle"
]
] |
wjones30309/ML-Server-Python-Samples | [
"975da57979dcd9c63c79d9452277cc27c175b875",
"975da57979dcd9c63c79d9452277cc27c175b875"
] | [
"microsoftml/202/plot_grid_search.py",
"microsoftml/101/plot_regression_wines.py"
] | [
"\"\"\"\nGrid Search\n===========\n\nAll learners have what we call \n`hyperparameters <https://en.wikipedia.org/wiki/Hyperparameter_(machine_learning)>`_\nwhich impact the way a model is trained. Most of the time, they have a default\nvalue which works on most of the datasets but that does not mean that's the best... | [
[
"pandas.read_csv",
"sklearn.cross_validation.train_test_split",
"matplotlib.pyplot.subplots",
"sklearn.metrics.confusion_matrix"
],
[
"matplotlib.pyplot.subplots",
"pandas.concat",
"sklearn.metrics.r2_score",
"pandas.read_csv",
"sklearn.cross_validation.train_test_split"
... |
elian204/melime | [
"aef885fa4b6b02f7bf7294140d78a85fe546b622"
] | [
"melime/explainers/local_models/local_model_linear.py"
] | [
"import numpy as np\n\nfrom sklearn import metrics\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.linear_model import SGDRegressor, Ridge, HuberRegressor\n\nfrom melime.explainers.local_models.local_model_base import LocalModelBase\n\n\ndef transformer_id... | [
[
"sklearn.linear_model.HuberRegressor",
"sklearn.metrics.mean_squared_error",
"sklearn.linear_model.Ridge",
"sklearn.linear_model.SGDRegressor",
"numpy.arange"
]
] |
kareem1925/pennylane | [
"04bb5ba0fcced558e1273b94b3ea8c39622c5ca4"
] | [
"pennylane/templates/state_preparations/mottonen.py"
] | [
"# Copyright 2018-2020 Xanadu Quantum Technologies Inc.\n\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n\n# http://www.apache.org/licenses/LICENSE-2.0\n\n# Unless required by ap... | [
[
"scipy.sparse.dok_matrix",
"numpy.isclose",
"numpy.ceil",
"numpy.angle",
"numpy.array",
"numpy.arcsin",
"numpy.abs",
"numpy.absolute",
"numpy.log2"
]
] |
abwilf/Factorized | [
"64e7d2a54bbfbc8b1c5a2130f2b941c376402fe6"
] | [
"util.py"
] | [
"import random\nimport os\nimport torch\n\nimport numpy as np\nimport zipfile\nfrom tqdm import tqdm\n\n\nfrom datetime import datetime\nfrom contextlib import contextmanager\nfrom time import time\n\n\ndef set_seed(my_seed):\n\n os.environ['PYTHONHASHSEED'] = str(my_seed)\n random.seed(my_seed)\n np.rando... | [
[
"numpy.random.seed",
"torch.manual_seed",
"torch.cuda.manual_seed",
"torch.cuda.manual_seed_all"
]
] |
Kadantte/VideoSuperResolution | [
"4c86e49d81c7a9bea1fe0780d651afc126768df3"
] | [
"VSR/Backend/Torch/Models/Esrgan.py"
] | [
"# Copyright (c): Wenyi Tang 2017-2019.\n# Author: Wenyi Tang\n# Email: wenyi.tang@intel.com\n# Update Date: 2019 - 3 - 15\n\nimport logging\n\nimport numpy as np\nimport torch.nn as nn\n\nfrom .Ops.Blocks import Activation, EasyConv2d, Rrdb\nfrom .Ops.Discriminator import DCGAN\nfrom .Ops.Scale import Upsample... | [
[
"torch.nn.Sequential",
"numpy.log2"
]
] |
sanidhyamangal/gan | [
"6a2bf12f968d0a913e8040121edc8bb6e0680a08",
"6a2bf12f968d0a913e8040121edc8bb6e0680a08"
] | [
"tensorflow_gan/examples/mnist/data_provider_test.py",
"tensorflow_gan/examples/self_attention_estimator/discriminator_test.py"
] | [
"# coding=utf-8\n# Copyright 2020 The TensorFlow GAN 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.executing_eagerly",
"tensorflow.compat.v1.data.make_one_shot_iterator",
"numpy.zeros",
"tensorflow.compat.v1.data.get_output_types",
"tensorflow.compat.v1.data.get_output_classes",
"numpy.ones",
"tensorflow.compat.v1.data.Dataset.from_tensors",
"tensorflow.com... |
vliu15/munit | [
"5789d96590519d729f89c9501eba7692fa7054ef"
] | [
"modules/networks.py"
] | [
"# The MIT License\n#\n# Copyright (c) 2020 Vincent Liu\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, cop... | [
[
"torch.nn.Sequential",
"torch.nn.AvgPool2d",
"torch.nn.Tanh",
"torch.nn.LeakyReLU",
"torch.ones",
"torch.nn.ReLU",
"torch.nn.Upsample",
"torch.nn.Conv2d",
"torch.nn.ReflectionPad2d",
"torch.nn.InstanceNorm2d",
"torch.nn.AdaptiveAvgPool2d"
]
] |
WildGenie/ru-dolph | [
"c80a320a60dcb60ccb66b86c3421e16e33235d97"
] | [
"rudolph/pipelines.py"
] | [
"# -*- coding: utf-8 -*-\nimport os\nfrom glob import glob\nfrom os.path import join\nfrom datetime import datetime\n\nimport torch\nimport torchvision\nimport transformers\nimport more_itertools\nimport numpy as np\nimport torch.nn.functional as F\nimport matplotlib.pyplot as plt\nimport torchvision.transforms as ... | [
[
"torch.zeros",
"torch.cat",
"torch.stack",
"torch.unique",
"numpy.asarray",
"torch.no_grad",
"torch.ones",
"torch.multinomial",
"torch.nn.functional.cross_entropy",
"torch.nn.functional.softmax",
"matplotlib.pyplot.show",
"torch.exp",
"torch.where"
]
] |
royxue/Theano | [
"626104a8c2b16898d270dc99e16a3ddb4a74678e",
"626104a8c2b16898d270dc99e16a3ddb4a74678e"
] | [
"theano/misc/tests/test_pycuda_example.py",
"theano/tensor/utils.py"
] | [
"import numpy\n\nimport theano\nimport theano.misc.pycuda_init\n\nif not theano.misc.pycuda_init.pycuda_available:\n from nose.plugins.skip import SkipTest\n raise SkipTest(\"Pycuda not installed. Skip test of theano op\"\n \" with pycuda code.\")\n\nimport theano.sandbox.cuda as cuda_ndarra... | [
[
"numpy.random.rand"
],
[
"numpy.ascontiguousarray"
]
] |
R3NI3/pytorch-rl | [
"20b3b738ca400b1916197f27a91367878b09803c"
] | [
"core/agents/acer_single_process.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nimport numpy as np\nimport random\nimport time\nimport math\nimport torch\nfrom torch.autograd import Variable, grad, backward\nimport torch.nn.functional as F\n\nfrom utils.helpers import ACER_On_Policy... | [
[
"torch.zeros",
"torch.cat",
"numpy.array",
"torch.autograd.backward",
"numpy.random.rand",
"numpy.asarray",
"torch.autograd.Variable",
"torch.ones",
"torch.from_numpy",
"torch.autograd.grad",
"numpy.stack",
"torch.log"
]
] |
yasunakacho/tensorflow | [
"cf36c3fdefda3c874cd8cebb779744c5035bb435"
] | [
"tensorflow/contrib/summary/summary_test_util.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.python.platform.gfile.ListDirectory",
"tensorflow.core.util.event_pb2.Event",
"tensorflow.python.lib.io.tf_record.tf_record_iterator",
"tensorflow.python.platform.gfile.Exists"
]
] |
nikhilsu/Mixed-modal-learning | [
"4e18877cd010665324d46885530e81226cfc1821"
] | [
"models/modules.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport time\n\nfrom tensorflow.contrib.rnn import GRUCell\nfrom util.infolog import log\n\n\ndef prenet(inputs, is_training, layer_sizes, scope=None):\n x = inputs\n drop_rate = 0.5 if is_training else 0.0\n with tf.variable_scope(scope or 'prenet'):\n f... | [
[
"tensorflow.constant_initializer",
"tensorflow.nn.conv2d",
"tensorflow.matmul",
"numpy.load",
"tensorflow.reshape",
"tensorflow.nn.avg_pool",
"tensorflow.concat",
"tensorflow.layers.batch_normalization",
"tensorflow.layers.conv1d",
"tensorflow.constant",
"tensorflow.var... |
Jaleleddine/gammapy | [
"de9195df40fa5bbf8840cda4e7cd5e8cc5eaadbb",
"de9195df40fa5bbf8840cda4e7cd5e8cc5eaadbb",
"de9195df40fa5bbf8840cda4e7cd5e8cc5eaadbb",
"de9195df40fa5bbf8840cda4e7cd5e8cc5eaadbb",
"015206d2418b1d254f1c9d3ea819ab0c5ece99e9"
] | [
"gammapy/datasets/tests/test_map.py",
"gammapy/modeling/models/tests/test_management.py",
"gammapy/irf/background.py",
"gammapy/maps/tests/test_wcsnd.py",
"gammapy/estimators/core.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\nimport pytest\nimport numpy as np\nfrom numpy.testing import assert_allclose\nimport astropy.units as u\nfrom astropy.coordinates import SkyCoord\nfrom astropy.table import Table\nfrom regions import CircleSkyRegion\nfrom gammapy.data import GTI\nfro... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.ones_like",
"numpy.sum",
"numpy.nansum",
"numpy.ones",
"numpy.all",
"numpy.linspace",
"numpy.logspace"
],
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.ones",
"numpy.all",
"numpy.logspace"... |
asranasinghe/spark | [
"6eee25b2d587016acdc49966510b50edc42053f5"
] | [
"python/pyspark/pandas/utils.py"
] | [
"#\n# Licensed to the Apache Software Foundation (ASF) under one or more\n# contributor license agreements. See the NOTICE file distributed with\n# this work for additional information regarding copyright ownership.\n# The ASF licenses this file to You under the Apache License, Version 2.0\n# (the \"License\"); yo... | [
[
"pandas.api.types.is_list_like"
]
] |
mmuratardag/DS_SpA_W07_Time_Series_Analysis | [
"d3dc95d32f4e0a2efd927eaa9069289baefce7c6"
] | [
"TS_data_prophet_plotly.py"
] | [
"import pandas as pd\nimport geopandas as gpd\nimport json\nimport plotly.express as px\n\n\ndf = pd.read_csv('berlin_weather_forecast.csv') \ndf['date'] = pd.to_datetime(df['date'].astype(str))\ndf_gb = df.groupby(['name','year','week'])['predicted_tempreature'].mean().reset_index()\ndf_gb['predicted_tempreature']... | [
[
"pandas.read_csv"
]
] |
asromahin/fline | [
"a34243878093b3b883607557eeaf968ef4b8acf6"
] | [
"fline/models/models/object_detection/map_net.py"
] | [
"import torch\nimport segmentation_models_pytorch as smp\n\nfrom fline.models.models.segmentation.fpn import TimmFPN\nfrom fline.models.encoders.timm import TimmEncoder\nfrom fline.models.models.research.extractor import VectorsFromMask, VectorsFromMaskV2\nfrom fline.models.models.research.connect_net import Connec... | [
[
"torch.cat",
"torch.min",
"torch.arange",
"torch.max",
"torch.no_grad",
"torch.atan",
"torch.nn.Conv2d",
"torch.nn.Softmax2d",
"torch.zeros_like",
"torch.nn.CrossEntropyLoss"
]
] |
davmre/sigvisa | [
"91a1f163b8f3a258dfb78d88a07f2a11da41bd04",
"91a1f163b8f3a258dfb78d88a07f2a11da41bd04"
] | [
"signals/mask_util.py",
"models/templates/paired_exp.py"
] | [
"import numpy as np\nimport numpy.ma as ma\n\n\ndef grow_mask(mask, n):\n N = len(mask)\n return [mask[max(0, i - n):min(N, i + n + 1)].any() for i in range(N)]\n\n\ndef mask_blocks(mask):\n \"\"\"\n Return a list of masked blocks (contiguous portions of the signal in which the mask is True).\n\n Thr... | [
[
"numpy.ma.masked_array",
"numpy.ceil",
"numpy.floor"
],
[
"numpy.isnan",
"numpy.empty",
"numpy.log",
"numpy.exp",
"scipy.weave.inline"
]
] |
hainingpan/inverse_volatility_caculation | [
"b1684cc9bd2c399468c67841ce6360db88c45a88"
] | [
"rebalance.py"
] | [
"from datetime import datetime, date\r\nimport math\r\nimport numpy as np\r\nimport time\r\nimport sys\r\nimport requests\r\nimport re\r\nfrom ortools.linear_solver import pywraplp\r\n\r\n# if len(sys.argv) == 1:\r\n# symbols = ['UPRO', 'TMF']\r\n# else:\r\n# symbols = sys.argv[1].split(',')\r\n# for i ... | [
[
"numpy.std",
"numpy.array",
"numpy.sqrt",
"numpy.floor"
]
] |
aldebaran1/pyTID | [
"f4a2fc3a5398306573af924c74e2f12a23e60d51"
] | [
"pytid/scint2ix.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu May 23 09:55:19 2019\n\n@author: smrak\n\"\"\"\nimport os\nimport yaml\nimport h5py\nimport numpy as np\nfrom datetime import datetime\nfrom pyGnss import pyGnss\nfrom pyGnss import gnssUtils as gu\nfrom pyGnss import scintillation as scint\ni... | [
[
"numpy.median",
"numpy.copy",
"matplotlib.dates.DateFormatter",
"numpy.where",
"numpy.nanmean",
"numpy.radians",
"numpy.nan_to_num",
"numpy.empty",
"numpy.arange",
"numpy.isfinite",
"numpy.nanmedian",
"numpy.nanstd",
"numpy.vstack",
"numpy.array",
"numpy... |
tgeral68/OpenNIR | [
"225b26185bd67fdc00f24de3ef70d35768e22243"
] | [
"onir/predictors/reranker.py"
] | [
"import os\nimport json\nimport torch\nimport onir\nfrom onir import util, spec, predictors, datasets\nfrom onir.interfaces import trec, plaintext\n\n\n@predictors.register('reranker')\nclass Reranker(predictors.BasePredictor):\n name = None\n\n @staticmethod\n def default_config():\n return {\n ... | [
[
"torch.is_tensor",
"torch.no_grad"
]
] |
jessecha/OPCAS | [
"2b51543b4ad1ee37dba2e45a0c7d0b872309d418"
] | [
"CNN_Model/run_3d_cnn.py"
] | [
"from __future__ import absolute_import\r\nfrom __future__ import division\r\nfrom __future__ import print_function\r\nimport argparse\r\nimport numpy as np\r\nimport cv2\r\nimport tensorflow as tf\r\nfrom keras.backend.tensorflow_backend import set_session\r\nconfig = tf.ConfigProto(allow_soft_placement=True, devi... | [
[
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"tensorflow.Session",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"tensorflow.ConfigProto",
"tensorflow.python.client.device_lib.list_local_devices",
"matplotlib.pyplot.ylabel",
"tensorflow... |
andrey-avdeev/catalyst | [
"fd17aaba7775c99b7e2b1ce86e60aa8f2379acc3",
"fd17aaba7775c99b7e2b1ce86e60aa8f2379acc3"
] | [
"catalyst/dl/meters/classerrormeter.py",
"catalyst/contrib/models/segmentation/encoder/resnet.py"
] | [
"import numbers\n\nimport numpy as np\n\nimport torch\n\nfrom . import meter\n\n\nclass ClassErrorMeter(meter.Meter):\n def __init__(self, topk=[1], accuracy=False):\n super(ClassErrorMeter, self).__init__()\n self.topk = np.sort(topk)\n self.accuracy = accuracy\n self.reset()\n\n ... | [
[
"numpy.asarray",
"torch.is_tensor",
"torch.from_numpy",
"numpy.sort",
"numpy.ndim"
],
[
"torch.nn.ModuleList"
]
] |
vas-group-imperial/venus2 | [
"c0fa7f095a0b3fdaff93fc5e7d948035fae6412a"
] | [
"venus/solver/milp_solver.py"
] | [
"# ************\n# File: milp_solver.py\n# Top contributors (to current version): \n# \tPanagiotis Kouvaros (panagiotis.kouvaros@gmail.com)\n# This file is part of the Venus project.\n# Copyright: 2019-2021 by the authors listed in the AUTHORS file in the\n# top-level directory.\n# License: BSD 2-Clause (see the f... | [
[
"numpy.zeros"
]
] |
BuysDB/siCloneFitIO | [
"b5b1ff320d13e8fe1062a1ed5d55ab161daa9644"
] | [
"visual/plot_imp_matrix.py"
] | [
"#!/usr/bin/env python3\nimport warnings\nwarnings.filterwarnings(\"ignore\")\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.patches as patches\nimport matplotlib\nimport seaborn as sns\nimport os\nimport sparsebinarydistance.distance as distance\nimport traceback\n\nma... | [
[
"pandas.isnull",
"numpy.array",
"numpy.isnan",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"matplotlib.patches.Rectangle",
"matplotlib.pyplot.xticks"
]
] |
aluo-x/3D_SLN | [
"0a29dbf17e3ca58064e76f9227f536a127c4863b"
] | [
"data/suncg_dataset.py"
] | [
"import random\nfrom collections import defaultdict\nimport torch\nfrom torch.utils.data import Dataset\nfrom data.base_dataset import BaseDataset\nfrom utils import load_json, compute_rel\n\nclass SuncgDataset(BaseDataset):\n def __init__(self, data_dir, train_3d, touching_relations=True, use_attr_30=False):\n ... | [
[
"torch.FloatTensor",
"torch.cat",
"torch.LongTensor",
"torch.stack"
]
] |
nerox8664/pytracer | [
"10ef0d2a309b6b2840b2d43ec7cb0f742578ee4e"
] | [
"tracer.py"
] | [
"#!/bin/python\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport multiprocessing as mp\nfrom functools import partial\nimport argparse\n\nfrom plane import Plane\nfrom sphere import Sphere\n\nfrom common_utils import *\n\n# Defines\ndepth_max = 3\nlight_depth_max = 3\nshadow_steps = 8\nh = 768\nw = 102... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.dot",
"numpy.zeros",
"matplotlib.pyplot.imsave",
"numpy.random.uniform",
"numpy.linspace",
"numpy.flip"
]
] |
further2006/h2o-3 | [
"b0dcacaeaf0814755334214c0897a976ee151c40"
] | [
"h2o-py/h2o/frame.py"
] | [
"# -*- encoding: utf-8 -*-\n\"\"\"\nH2O data frame.\n\n:copyright: (c) 2016 H2O.ai\n:license: Apache License Version 2.0 (see LICENSE for details)\n\"\"\"\nfrom __future__ import absolute_import, division, print_function, unicode_literals\nfrom h2o.utils.compatibility import * # NOQA\n\nimport csv\nimport dateti... | [
[
"matplotlib.use",
"scipy.sparse.issparse",
"scipy.sparse.find",
"numpy.zeros",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"scipy.sparse.csr_matrix",
"matplotlib.pyplot.ylabel",
"pandas.concat",
"numpy.argsort",
"matplotlib.pyplot.show... |
alxlampe/d3rlpy | [
"af7e6bd018a51f95138d121f59c50dc36ec87e3a",
"af7e6bd018a51f95138d121f59c50dc36ec87e3a"
] | [
"setup.py",
"tests/algos/torch/test_utility.py"
] | [
"import os\n\nfrom setuptools import setup, Extension\n\nos.environ['CFLAGS'] = '-std=c++11'\n\nif __name__ == \"__main__\":\n from numpy import get_include\n from Cython.Build import cythonize\n\n # setup Cython build\n ext = Extension('d3rlpy.dataset',\n sources=['d3rlpy/dataset.pyx... | [
[
"numpy.get_include"
],
[
"torch.nn.Linear",
"numpy.allclose",
"torch.tensor",
"numpy.random.random",
"torch.allclose"
]
] |
yangle293/FDRnet | [
"8906936b192cd8905e7fd12e1fabed5ace962d6c"
] | [
"example/locfdr_compute.py"
] | [
"from __future__ import print_function\nimport sys\nsys.path.insert(0, \"../locfdr-python\")\nfrom locfdr import locfdr\nfrom collections import OrderedDict\nfrom os import listdir\nfrom os.path import isfile, join, basename, splitext\nimport math\nimport numpy as np\nimport re\nfrom scipy.stats import norm as norm... | [
[
"scipy.stats.norm.ppf"
]
] |
aguptaisae/Masters-Research-Project-S2 | [
"b44cd21a95a60b8fb38852dac5a5b0794e1f3e3f",
"b44cd21a95a60b8fb38852dac5a5b0794e1f3e3f"
] | [
"Garteur Model/Reference Model/modal_optim_GARTEUR_COBYLA.py",
"Goland Wing/Scale 1by9/modal_optim_GOLAND_COBYLA_scale1by9.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Tue Mar 29 10:50:10 2016\r\n\r\n@author: © Joan Mas Colomer\r\n\"\"\"\r\n\r\nfrom __future__ import print_function\r\n\r\nfrom openmdao.api import Problem, Group, IndepVarComp, ExecComp, ScipyGMRES, SqliteRecorder, ScipyOptimizer, view_model\r\n\r\nfrom aerostructure... | [
[
"numpy.array",
"numpy.zeros",
"numpy.ones",
"numpy.split",
"numpy.sqrt"
],
[
"numpy.array",
"numpy.zeros",
"numpy.ones",
"numpy.split",
"numpy.sqrt"
]
] |
rhgkrsus1/diffco | [
"d5e393abee110b84ac94df449986dd0ed3f011a2"
] | [
"diffco/kernel.py"
] | [
"import numpy as np\nimport torch\n\nclass KernelFunc:\n def __init__(self):\n pass\n\n def __call__(self):\n raise NotImplementedError('You need to define your own __call__ function.')\n\n\nclass RQKernel(KernelFunc):\n def __init__(self, gamma, p=2):\n self.gamma = gamma\n sel... | [
[
"numpy.array",
"torch.isnan",
"numpy.sum",
"torch.log",
"torch.cdist",
"torch.sum"
]
] |
shahmoradi/paramonte-1 | [
"77c81c14e475bfacb19fa6de1f41629380e453d3"
] | [
"src/interface/Python/paramonte/_paradram.py"
] | [
"####################################################################################################################################\n####################################################################################################################################\n####\n#### MIT License\n####\n#### ParaMont... | [
[
"numpy.array"
]
] |
Bayaniblues/strawberryfields | [
"9d9e2f4488ef3783d3d4b2f226afac0bc431257e"
] | [
"strawberryfields/apps/qchem/dynamics.py"
] | [
"# Copyright 2020 Xanadu Quantum Technologies Inc.\n\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n\n# http://www.apache.org/licenses/LICENSE-2.0\n\n# Unless required by applica... | [
[
"numpy.iscomplex",
"numpy.array",
"numpy.zeros"
]
] |
ypark234/pyne | [
"b7c4932c0399e6a0881aea943b392fb97cd0b6bd",
"b7c4932c0399e6a0881aea943b392fb97cd0b6bd"
] | [
"pyne/ensdf.py",
"pyne/xs/cache.py"
] | [
"from __future__ import division\nimport re\nimport sys\nimport copy\nfrom collections import defaultdict\nfrom warnings import warn\nfrom pyne.utils import QAWarning\nfrom pyne.utils import time_conv_dict\n\nimport numpy as np\n\nfrom pyne import nucname, rxname, data\n\nif sys.version_info[0] > 2:\n basestring... | [
[
"numpy.isscalar",
"numpy.sqrt"
],
[
"numpy.asarray"
]
] |
philshams/FC_analysis | [
"cabe2385d5061d206a21b230605bfce9e39ec7f2",
"cabe2385d5061d206a21b230605bfce9e39ec7f2"
] | [
"Utils/tdms_to_video_converter.py",
"Plotting/Maze_session_summary.py"
] | [
"import numpy as np\nimport os\nfrom tempfile import mkdtemp\nfrom nptdms import TdmsFile\nimport psutil\nimport gc\nimport time\nfrom multiprocessing.dummy import Pool as ThreadPool\nfrom tqdm import tqdm\n\nimport cv2\n\n\nclass TDMs_to_Video():\n \"\"\" current implementation: takes one .tdms video and saves... | [
[
"numpy.linspace",
"numpy.asarray"
],
[
"matplotlib.pyplot.rcParams.update",
"numpy.array",
"numpy.asarray",
"pandas.DataFrame",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"matplotlib.rc",
"matplotlib.pyplot.subplot2grid",
"matplotlib.pyplot.show"
]
] |
dahe-cvl/apa_paper | [
"bec38e0270fda6f0fd092eacc6f10344b26a0f19"
] | [
"3D_CNN/SequenceBatchGenerator.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom DataAugmentation import DataAugmentation\n\nclass SequenceBatchGenerator:\n\t# Create minibatches of a given size from a dataset.\n\t# Preserves the original sample order unless shuffle() is used.\n\n\tbatchsize = 0;\n\tdataset = None;\n\ttform = None; \n\t... | [
[
"numpy.reshape",
"numpy.zeros",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.show",
"matplotlib.pyplot.imshow"
]
] |
MSXC/CNTK | [
"d223d48b411bc994acd465ed333c9f6bed64dd7f",
"d223d48b411bc994acd465ed333c9f6bed64dd7f",
"d223d48b411bc994acd465ed333c9f6bed64dd7f"
] | [
"bindings/python/cntk/ops/tests/block_test.py",
"bindings/python/cntk/layers/tests/layers_test.py",
"bindings/python/cntk/logging/tests/graph_test.py"
] | [
"# Copyright (c) Microsoft. All rights reserved.\n\n# Licensed under the MIT license. See LICENSE.md file in the project root\n# for full license information.\n# ==============================================================================\n\n\"\"\"\nUnit tests for as_block operation, only forward pass is tested\n... | [
[
"numpy.arange",
"numpy.array_equal",
"numpy.multiply.reduce",
"numpy.asarray"
],
[
"numpy.max",
"numpy.array",
"numpy.matrix",
"numpy.sum",
"numpy.testing.assert_array_equal",
"numpy.ones",
"numpy.exp",
"numpy.mean",
"numpy.testing.assert_array_almost_equal"... |
atocplusplus/test | [
"471ff64c25d27eaad58d8b5a9e787249db974d44"
] | [
"ch06/overfit_dropout.py"
] | [
"# coding: utf-8\nimport os\nimport sys\nsys.path.append(os.pardir) # 親ディレクトリのファイルをインポートするための設定\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom dataset.mnist import load_mnist\nfrom common.multi_layer_net_extend import MultiLayerNetExtend\nfrom common.trainer import Trainer\n\n(x_train, t_train), (x_tes... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
cre-os/pub-data-visualization | [
"229bb7a543684be2cb06935299345ce3263da946",
"68eea00491424581b057495a7f0f69cf74e16e7d",
"e5ec45e6397258646290836fc1a3b39ad69bf266"
] | [
"pub_data_visualization/global_tools/compute_delivery_period_index.py",
"pub_data_visualization/load/plot/forecasting_error.py",
"pub_data_visualization/load/load/eco2mix/load.py"
] | [
"\nimport pandas as pd\nimport re\n#\nfrom .. import global_var\n\ndef compute_delivery_period_index(frequency = None,\n delivery_begin_dt_local = None,\n delivery_end_date_local = None,\n tz_local ... | [
[
"pandas.isnull"
],
[
"matplotlib.font_manager.FontProperties",
"matplotlib.pyplot.ion",
"matplotlib.pyplot.savefig",
"matplotlib.dates.DateFormatter",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.ioff",
"pandas.plotting.register_matplotlib_con... |
sjsrey/segregation | [
"bdf53f5423477f0c66975f994f48ce3a16000788"
] | [
"segregation/tests/test_multi_squared_coefficient_of_variation.py"
] | [
"import unittest\nfrom libpysal.examples import load_example\nimport geopandas as gpd\nimport numpy as np\nfrom segregation.aspatial import MultiSquaredCoefficientVariation\n\n\nclass Multi_Squared_Coefficient_of_Variation_Tester(unittest.TestCase):\n def test_Multi_Squared_Coefficient_of_Variation(self):\n ... | [
[
"numpy.testing.assert_almost_equal"
]
] |
rmroczkowski/transformers | [
"c988db5af2a5f1ccfcb5ad19bd735b6a77516637"
] | [
"src/transformers/trainer.py"
] | [
"# coding=utf-8\n# Copyright 2020-present the HuggingFace Inc. 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# Unles... | [
[
"torch.distributed.get_world_size",
"torch.cat",
"torch.utils.data.sampler.RandomSampler",
"torch.utils.data.dataloader.DataLoader",
"torch.cuda.amp.autocast",
"torch.no_grad",
"torch.nn.parallel.DistributedDataParallel",
"torch.utils.data.sampler.SequentialSampler",
"torch.ten... |
YoanRouleau/BachelorDIM-Lectures-Algorithms-2020 | [
"eafb79a096325dc9bf75c3a20520edb191bfa3e1"
] | [
"assignements/S1_algotools.py"
] | [
"\"\"\"\nCreated by Yoan ROULEAU\n@author: myself\n\"\"\"\nfrom random import randint\n\nimport numpy as np\n\ndef average_above_zero(array):\n '''\n Receives an array as a parameter and calculates its average.\n\n :arg\n array: an array\n :returns\n moy: Its average\n '''\n som = 0\... | [
[
"numpy.ones",
"numpy.zeros"
]
] |
andrewsu/RTX | [
"dd1de262d0817f7e6d2f64e5bec7d5009a3a2740"
] | [
"code/ARAX/ARAXQuery/Filter_KG/remove_edges.py"
] | [
"# This class will overlay the normalized google distance on a message (all edges)\n#!/bin/env python3\nimport sys\nimport os\nimport traceback\nimport numpy as np\n\n# relative imports\nsys.path.append(os.path.dirname(os.path.abspath(__file__))+\"/../../../UI/OpenAPI/python-flask-server/\")\nfrom openapi_server.mo... | [
[
"numpy.percentile",
"numpy.std",
"numpy.mean"
]
] |
mindspore-ai/contrib | [
"85dccac7a2ba6e962092ecd51aefd962d7f2aeac"
] | [
"papers/CS-F-LTR/src/decision_tree_semi.py"
] | [
"\"\"\"[summary]\n\"\"\"\nimport pickle\nimport os\nimport numpy as np\nfrom sklearn.tree import DecisionTreeClassifier\nfrom utils import evaluation\nfrom scipy.stats import mode\n\n\nclass DecisionTreeSemi:\n \"\"\"[summary]\n \"\"\"\n def __init__(self, train_relevance_labels, train_features,\n ... | [
[
"numpy.concatenate",
"scipy.stats.mode",
"numpy.random.seed",
"numpy.random.shuffle",
"sklearn.tree.DecisionTreeClassifier"
]
] |
yoonkim/neural-qcfg | [
"c5a2ea05e3108f83e5833f8d0bc368638bab6c9a"
] | [
"predict_styleptb.py"
] | [
"#!/usr/bin/env python3\nimport sys\nimport os\n\nimport argparse\nimport json\nimport random\nimport shutil\nimport copy\nimport pickle\nimport torch\nfrom torch import cuda\nimport numpy as np\nimport time\nimport logging\nfrom tokenizer import Tokenizer\nfrom utils import *\nfrom torch.nn.utils.rnn import pad_se... | [
[
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.no_grad",
"numpy.exp",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.LongTensor",
"torch.load"
]
] |
blink1073/scikit-image | [
"46a8df9c32c5b79d38bc3a1f75dd4fbfeddf98f7"
] | [
"skimage/measure/tests/test_fit.py"
] | [
"import numpy as np\nfrom numpy.testing import assert_equal, assert_raises, assert_almost_equal\nfrom skimage.measure import LineModelND, CircleModel, EllipseModel, ransac\nfrom skimage.transform import AffineTransform\nfrom skimage.measure.fit import _dynamic_max_trials\nfrom skimage._shared._warnings import expec... | [
[
"numpy.random.normal",
"numpy.array",
"numpy.testing.run_module_suite",
"numpy.random.rand",
"numpy.empty",
"numpy.linalg.norm",
"numpy.testing.assert_equal",
"numpy.random.seed",
"numpy.testing.assert_almost_equal",
"numpy.zeros",
"numpy.linspace",
"numpy.nonzero",... |
PanczykowskiK/viadot | [
"44e269790b3debb02318ff4c4f07638b3a37d800"
] | [
"viadot/flows/supermetrics_to_adls.py"
] | [
"import json\nimport os\nimport shutil\nfrom pathlib import Path\nfrom typing import Any, Dict, List, Union\n\nimport pandas as pd\nimport pendulum\nimport prefect\nfrom prefect import Flow, Task, apply_map, task\nfrom prefect.backend import set_key_value\nfrom prefect.tasks.secrets import PrefectSecret\nfrom prefe... | [
[
"pandas.read_csv",
"pandas.read_parquet",
"pandas.concat"
]
] |
JackSchaible/sulphur | [
"1d054131cfc427c0e962d95a32203be075cf730c"
] | [
"epsilonGreedy/greedyOptimistic.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport bandit\n\nclass greedyOptimistic:\n def __init__(self):\n self.payoutModifier1 = 1.0\n self.payoutModifier2 = 2.0\n self.payoutModifier3 = 3.0\n self.iterations = 10000\n\n self.means = [10, 10, 10]\n\n self.ba... | [
[
"matplotlib.pyplot.xscale",
"numpy.empty",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"numpy.ones",
"numpy.argmax",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"numpy.cumsum",
"matplotlib.pyplot.show"
]
] |
Dotnester/estee | [
"55c0834db3d7da407b7c37d46fa41b5b563e2bbe"
] | [
"benchmarks/benchmark.py"
] | [
"import collections\nimport itertools\nimport multiprocessing\nimport os\nimport random\nimport re\nimport signal\nimport sys\nimport threading\nimport time\nimport traceback\n\nimport click\nimport numpy\nimport pandas as pd\nfrom tqdm import tqdm\n\nfrom estee.common import imode\nfrom estee.schedulers import Wor... | [
[
"numpy.random.seed",
"pandas.DataFrame",
"pandas.read_json",
"pandas.concat",
"pandas.read_csv"
]
] |
irxat/geoist | [
"658aadab8074bffcbc6b3861671d35b3012502e9",
"658aadab8074bffcbc6b3861671d35b3012502e9"
] | [
"geoist/catalog/QCmulti.py",
"geoist/magmod/tests/pymm_vrot.py"
] | [
"#!/usr/bin/env python\n\"\"\"Code for creating figures comparing two catalogs spanning the same time\nframe. Run `QCmulti.py -h` for command line options.\n\"\"\"\nimport os\nimport sys\nimport errno\nimport argparse\nimport time\nimport shutil\nfrom datetime import datetime\nfrom math import sqrt, degrees, radian... | [
[
"matplotlib.pyplot.xlim",
"numpy.argmin",
"scipy.stats.linregress",
"pandas.read_csv",
"numpy.histogram",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.tick_params",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.subplot",
"matplotli... |
jameskomo/coffee-data-visualization | [
"6b0812c8791c9cbcb264bafae0cf1d02a6ea30b8"
] | [
"virtual/lib/python3.6/site-packages/numpy/core/tests/test_regression.py"
] | [
"from __future__ import division, absolute_import, print_function\n\nimport copy\nimport sys\nimport gc\nimport tempfile\nimport pytest\nfrom os import path\nfrom io import BytesIO\nfrom itertools import chain\n\nimport numpy as np\nfrom numpy.testing import (\n assert_, assert_equal, IS_PYPY, assert_almost_... | [
[
"numpy.lib.stride_tricks.as_strided",
"numpy.random.rand",
"numpy.string_",
"numpy.binary_repr",
"numpy.sign",
"numpy.count_nonzero",
"numpy.empty",
"numpy.add.reduce",
"numpy.object_",
"numpy.nonzero",
"numpy.bytes_",
"numpy.subtract.accumulate",
"numpy.compat.... |
jinyier/ai_pointnet_attack | [
"4ef16a898f99e825c445ebc7aad7ba1fd953f8f0"
] | [
"utils/eulerangles.py"
] | [
"# emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\n#\n# See COPYING file distributed along with the NiBabel package for the\n# copyright and license terms.\n#\n#... | [
[
"numpy.finfo",
"numpy.array",
"numpy.asarray",
"numpy.eye"
]
] |
vd1371/CBSA | [
"f2b3f03c91ccd9ec02c2331f43573d7d6e72fd47"
] | [
"embedding/_fasttext/_emb_matrix_fasttext.py"
] | [
"import os\nimport numpy as np\n\nfrom multiprocessing import current_process\nif current_process().name == \"MainProcess\":\n from tensorflow.keras.preprocessing.text import Tokenizer\n\nfrom ._load_embedding import _load_embedding\n\nfrom DataLoader import load_unique_words\n\ndef emb_matrix_fasttext(X, **para... | [
[
"numpy.zeros",
"tensorflow.keras.preprocessing.text.Tokenizer"
]
] |
feifeibear/dist-tensorflow | [
"af6ae012f1454aff2c58d26808705e01ed2f1376"
] | [
"terngrad/inception/pruning_common.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport tensorflow as tf\n\ndef pruning_gradients(grads_and_vars, percent, residual_grads):\n \"\"\"\n pruning grads according to the percent.\n \"\"\"\n gradients, variables = zip(*grads_an... | [
[
"tensorflow.shape",
"tensorflow.less",
"tensorflow.where",
"tensorflow.subtract",
"tensorflow.reshape",
"tensorflow.nn.top_k",
"tensorflow.add"
]
] |
chinthojuprajwal/IE517_ML_course | [
"4b9a1eae9d5100d3573607c46d0fa37fe35074a9"
] | [
"hy_corporate_bond_curve_prediction_early/hy_corporate_bond.py"
] | [
"import pandas as pd\nimport numpy as np\nimport seaborn as sns\nimport matplotlib.pyplot as plt\n\ndf=pd.read_csv('D:/UIUC_courses/IE517/IE517_FY21_HW3/HY_Universe_corporate_bond.csv')\nprint(df.describe())\n\ndf=df.values\n\n\ndf[:,14]=df[:,14].astype(str)\ndf[:,12]=df[:,12].astype(str)\ndf[:,5:9]=df[:,5:9].astyp... | [
[
"numpy.array",
"numpy.isnan",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"pandas.read_csv"
]
] |
Jabb0/coot-videotext | [
"2da20a3f3a50b69677e59869b02cbd72945913d9"
] | [
"coot/data/ht100m_dataset.py"
] | [
"import json\n\nimport pandas as pd\nimport numpy as np\n\nfrom typing import Union, List\nfrom pathlib import Path\nfrom timeit import default_timer as timer\n\nfrom nntrainer import data as nn_data\n\n\ndef _time_to_seconds(time_column):\n return pd.to_timedelta(time_column).dt.total_seconds()\n\n\nclass HT100... | [
[
"pandas.read_csv",
"pandas.to_timedelta"
]
] |
metataro/minerl_agent | [
"f61a587b778afe5d70d260012ee850013e809a14"
] | [
"minerl_agent/behaviour_cloning/tfrecrods.py"
] | [
"import logging\n\nimport numpy as np\nimport tensorflow as tf\nfrom minerl.env import spaces\n\nfrom utility.utils import flatten_nested_dicts, unflatten_nested_dicts\n\nlogger = logging.getLogger(__name__)\n\n\ndef _bytes_feature(value):\n return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))\n... | [
[
"tensorflow.train.BytesList",
"tensorflow.train.FloatList",
"tensorflow.train.Int64List",
"tensorflow.train.Features",
"tensorflow.FixedLenSequenceFeature",
"tensorflow.decode_raw",
"tensorflow.FixedLenFeature",
"tensorflow.reshape",
"tensorflow.nest.map_structure",
"tensor... |
EvgenyZhvansky/R_matrix | [
"66f5da0af89866da533a5714ffaf4a6567d7d5bc"
] | [
"mzXML2mat.py"
] | [
"# import sys\nimport numpy as np\nfrom pyteomics import mzxml as pymz\nimport xml.etree.ElementTree as ET\nfrom tkinter import Tk\nfrom tkinter.filedialog import askopenfilenames\nimport scipy.io as io\n\n\ndef get_scan_count(tree_local):\n scan_count=0\n for (event, elem) in tree_local:\n if 'msRun' ... | [
[
"numpy.bincount",
"numpy.ceil",
"numpy.zeros",
"numpy.round",
"numpy.sum",
"numpy.median",
"scipy.io.savemat",
"numpy.digitize",
"numpy.argmax",
"numpy.floor"
]
] |
tanishq-arya/Rotten-Scripts | [
"93f62eb1213f739c13103610d3f502e1dc2d3790"
] | [
"Python/Google_News_Scrapper/app.py"
] | [
"import requests\nfrom xml.dom.minidom import parseString\nimport pandas as pd\n\n\ndef get_google_news_result(term, count):\n results = []\n obj = parseString(requests.get(\n 'http://news.google.com/news?q=%s&output=rss' % term).text)\n items = obj.getElementsByTagName('item')\n # Storing the Ti... | [
[
"pandas.DataFrame"
]
] |
rivergold/mmediting | [
"fd972635c48bb065db29d1b5090592a87c7263d2",
"fd972635c48bb065db29d1b5090592a87c7263d2",
"fd972635c48bb065db29d1b5090592a87c7263d2"
] | [
"mmedit/models/common/model_utils.py",
"tests/test_optimizer.py",
"tests/test_deepfill_disc.py"
] | [
"import numpy as np\nimport torch\n\n\ndef set_requires_grad(nets, requires_grad=False):\n \"\"\"Set requies_grad for all the networks.\n\n Args:\n nets (nn.Module | list[nn.Module]): A list of networks or a single\n network.\n requires_grad (bool): Whether the networks require gradie... | [
[
"numpy.concatenate",
"numpy.zeros_like",
"torch.cat",
"numpy.asarray",
"torch.zeros_like",
"torch.Tensor"
],
[
"torch.nn.Conv2d",
"torch.equal"
],
[
"torch.rand",
"torch.cuda.is_available"
]
] |
brainglobe/cellfinder | [
"0466e94f5c5ad58c853a73257d80944a1607ac81"
] | [
"cellfinder/extract/extract_cubes.py"
] | [
"\"\"\"\nCube extraction for CNN-based classification.\n\nBased on, and mostly copied from,\nhttps://github.com/SainsburyWellcomeCentre/cell_count_analysis by\nCharly Rousseau (https://github.com/crousseau).\n\"\"\"\n\nimport os\nfrom collections import deque\nfrom concurrent.futures import ProcessPoolExecutor\nimp... | [
[
"numpy.where",
"numpy.array",
"numpy.zeros"
]
] |
rickyHong/tensor2tensor-repl | [
"b6a57e71b0bb53b35e0f9a1ba8ae75c5169f9af5",
"b6a57e71b0bb53b35e0f9a1ba8ae75c5169f9af5"
] | [
"tensor2tensor/data_generators/image.py",
"tensor2tensor/models/transformer_revnet_test.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.to_float",
"numpy.frombuffer",
"tensorflow.logging.warning",
"tensorflow.cast",
"tensorflow.FixedLenFeature",
"tensorflow.contrib.slim.tfexample_decoder.Tensor",
"tensorflow.random_uniform",
"tensorflow.logging.info",
"tensorflow.gfile.Glob",
"tensorflow.to_int6... |
misken/obflowsim | [
"19cad8e292435082ff47f3a09f68be69edff4361"
] | [
"src/obflowsim/mm/mm_run_fits_ldr.py"
] | [
"import sys\nimport argparse\nfrom pathlib import Path\nimport pickle\n\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\nfrom obflowsim.mm.mm_fitting import crossval_summarize_mm\nfrom obflowsim.mm.mm_process_fitted_models import create_cv_plots, create_coeff_plots\nfrom obflowsim.mm.mm_process_fitted_model... | [
[
"matplotlib.pyplot.ioff"
]
] |
LeoZDong/shape2prog | [
"2185d1d4eb7a1c4c55e644c6af477fd8e8e70241"
] | [
"model.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\nfrom misc import render_block\n\n\nclass BlockOuterNet(nn.Module):\n \"\"\"\n predict block-level programs and parameters\n block-LSTM\n ... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.LSTM",
"numpy.copy",
"torch.multinomial",
"torch.nn.AvgPool3d",
"torch.exp",
"torch.nn.BatchNorm3d",
"torch.autograd.Variable",
"torch.unsqueeze",
"torch.nn.Conv3d",
"torch.nn.functional.relu",
"torch.nn.ConvTranspose3d"... |
mestradam/pymas | [
"528aa81be9848dea65152a359290238f6ba983a7"
] | [
"src/pymas/core.py"
] | [
"import json\nimport numpy as np\n\nfrom pymas.primitives import *\n\n\nclass Structure:\n \"\"\"Model and analyse a framed structure.\n\n Attributes\n ----------\n ux : bool\n Flag analyze translation along x-axis.\n uy : bool\n Flag analyze translation along y-axis.\n uz : bool\n ... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.count_nonzero",
"numpy.empty",
"numpy.dot",
"numpy.zeros",
"numpy.copy",
"numpy.tile",
"numpy.shape",
"numpy.arange",
"numpy.transpose",
"numpy.broadcast_to"
]
] |
JDESLOIRES/eo-flow | [
"def495e9292809656b906cfd6b8e7389ff9cea61"
] | [
"eoflow/models/pse_tae_layers.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport tensorflow.keras.layers as L\n\nfrom .transformer_encoder_layers import scaled_dot_product_attention, positional_encoding\n\npooling_methods = {\n 'mean': tf.math.reduce_mean,\n 'std': tf.math.reduce_std,\n 'max': tf.math.reduce_max,\n 'min': tf.math.... | [
[
"tensorflow.keras.layers.Conv1D",
"tensorflow.shape",
"tensorflow.keras.layers.ReLU",
"tensorflow.expand_dims",
"tensorflow.transpose",
"tensorflow.reshape",
"tensorflow.keras.Sequential",
"tensorflow.keras.layers.LayerNormalization",
"tensorflow.keras.layers.Dropout",
"ten... |
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