repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
keshav47/pytorch-metric-learning | [
"501e4cb5e56c56d09413c98a93039669abc2232b",
"1fb343124d15fd2f63d535df26aa1463daf4ceee"
] | [
"src/pytorch_metric_learning/losses/ntxent_loss.py",
"src/pytorch_metric_learning/utils/inference.py"
] | [
"import torch\n\nfrom ..distances import CosineSimilarity\nfrom ..utils import common_functions as c_f\nfrom .generic_pair_loss import GenericPairLoss\n\n\nclass NTXentLoss(GenericPairLoss):\n def __init__(self, temperature=0.07, **kwargs):\n super().__init__(mat_based_loss=False, **kwargs)\n self.... | [
[
"torch.exp",
"torch.max"
],
[
"torch.stack",
"torch.no_grad",
"numpy.where",
"torch.nn.functional.normalize"
]
] |
mortbopet/NetCracker | [
"8b5c1dbe1780c111d1f6810d3ef13400f26f9cb0"
] | [
"src/analysis/adjacencyAnalysis.py"
] | [
"import argparse\nimport json\nimport re\nimport pprint\nimport sys\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom src.sbhelper import *\nfrom src.analysis.IOAnalysis import *\nfrom src.analysis.analysispass import *\nfrom src.logger import *\n\n\n# ============================== Analysis results ==... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
]
] |
MarvinStuede/copa-map | [
"f477d1254d99988b2d997e69316d4ffbec721fff",
"f477d1254d99988b2d997e69316d4ffbec721fff"
] | [
"src/copa_map/model/model_utils.py",
"src/copa_map/plots/plot_domain_allocation.py"
] | [
"\"\"\"Utilities for optimization of a model\"\"\"\nimport gpflow\nimport tensorflow as tf\nfrom tensorflow_probability import bijectors as tfb\nfrom termcolor import colored\n\n\ndef get_kernel_instance(kern, name):\n \"\"\"\n Returns requested kernel instance of a combined kernel\n\n Args:\n kern:... | [
[
"tensorflow.cast"
],
[
"numpy.array",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.pause"
]
] |
msdrigg/RayTracing | [
"700ce020c6faa93757100edae4543a1a59c4f3c8",
"700ce020c6faa93757100edae4543a1a59c4f3c8"
] | [
"atmospheres/base.py",
"magnetic_fields/implementations.py"
] | [
"from abc import ABC, abstractmethod\nfrom typing import Optional, Tuple\n\nimport numpy as np\nfrom matplotlib import pyplot as plt\nfrom numpy.typing import ArrayLike\nfrom scipy.spatial.transform.rotation import Rotation\n\nfrom utilities import Vector\nfrom utilities import Constants\n\n\nclass BaseAtmosphere(A... | [
[
"numpy.linspace",
"matplotlib.pyplot.subplots",
"numpy.cross",
"matplotlib.pyplot.show",
"numpy.zeros"
],
[
"numpy.square",
"numpy.power",
"numpy.cos",
"numpy.sin",
"numpy.array"
]
] |
valohai/valohai-sagemaker-adapter | [
"c945a691c7dfef136f66c19ae79a67d981a64cfa"
] | [
"examples/jupyter-example/train.py"
] | [
"import torch\nimport imblearn\nimport os, sys\n\n\ndef list_files(startpath):\n for root, dirs, files in os.walk(startpath):\n level = root.replace(startpath, '').count(os.sep)\n indent = ' ' * 4 * (level)\n print('{}{}/'.format(indent, os.path.basename(root)))\n subindent = ' ' * 4 ... | [
[
"torch.cuda.is_available"
]
] |
OOXXXXOO/UnitNet | [
"304c58a7ac6e4d78c8bf2ef528f817eed3ff7c7a"
] | [
"Src/Model/BackBone/efficientnet/model.py"
] | [
"import torch\nfrom torch import nn\nfrom torch.nn import functional as F\n\nfrom Src.Nets.BackBone.efficientnet.utils import (\n relu_fn,\n round_filters,\n round_repeats,\n drop_connect,\n get_same_padding_conv2d,\n get_model_params,\n efficientnet_params,\n load_pretrained_weights,\n)\n\n... | [
[
"torch.sigmoid",
"torch.nn.functional.dropout",
"torch.nn.ModuleList",
"torch.nn.functional.adaptive_avg_pool2d",
"torch.nn.Linear",
"torch.nn.BatchNorm2d"
]
] |
jlosey513/Binomial | [
"64dbe493132d27b01342911a079d09d59cbc6f6b"
] | [
"binomial_option_model.py"
] | [
"import numpy as np\n\n\ndef binomial_model(N, S0, u, r, K):\n \"\"\"\n N = number of binomial iterations\n S0 = initial stock price\n u = factor change of upstate\n r = risk free interest rate per annum\n K = strike price\n \"\"\"\n d = 1 / u\n p = (1 + r - d) / (u - d)\n q = 1 - p\n\... | [
[
"numpy.zeros"
]
] |
oi-analytics/argentina-transport | [
"f1583b077844e6b20b2c81144dec0872c88bdb80",
"f1583b077844e6b20b2c81144dec0872c88bdb80",
"f1583b077844e6b20b2c81144dec0872c88bdb80",
"f1583b077844e6b20b2c81144dec0872c88bdb80"
] | [
"src/atra/plot/air_network_flows.py",
"src/atra/preprocess/convert_hazard_data.py",
"src/atra/plot/od_commodities_charts.py",
"src/atra/preprocess/road_network_creation.py"
] | [
"\"\"\"air network flows map\n\"\"\"\nimport os\nimport sys\nfrom collections import OrderedDict\n\nimport pandas as pd\nimport geopandas as gpd\nimport cartopy.crs as ccrs\nimport cartopy.io.shapereader as shpreader\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom shapely.geometry import LineString\nfrom... | [
[
"pandas.merge",
"pandas.read_csv",
"matplotlib.pyplot.close"
],
[
"numpy.isnan",
"pandas.DataFrame"
],
[
"pandas.read_csv"
],
[
"pandas.merge",
"numpy.array",
"pandas.DataFrame"
]
] |
hero9968/scikit-neuralnetwork | [
"b7fd0c089bd7c721c4d9cf9ca71eed74c6bafc5e"
] | [
"sknn/backend/lasagne/mlp.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import (absolute_import, division, unicode_literals, print_function)\n\n__all__ = ['MultiLayerPerceptronBackend']\n\nimport os\nimport sys\nimport math\nimport time\nimport types\nimport logging\nimport itertools\n\nlog = logging.getLogger('sknn')\n\n\nimport numpy\nimport ... | [
[
"numpy.arange",
"numpy.zeros",
"numpy.random.shuffle",
"numpy.transpose"
]
] |
gangigammo/deep-learning-1 | [
"3fe803514c3733d8715cf1211a82ffd8ea660af2"
] | [
"common/gradient.py"
] | [
"# coding: utf-8\nimport numpy as np\n\ndef _numerical_gradient_1d(f, x):\n h = 1e-4 # 0.0001\n grad = np.zeros_like(x)\n \n for idx in range(x.size):\n tmp_val = x[idx]\n x[idx] = float(tmp_val) + h\n fxh1 = f(x) # f(x+h)\n \n x[idx] = tmp_val - h \n fxh2 = f(x... | [
[
"numpy.zeros_like",
"numpy.nditer"
]
] |
sonata-nfv/tng-sdk-validation | [
"e20bfa2247c95a82db42a0dd586f76a0c42d059b"
] | [
"non-functional-tests/stat-graph-generation.py"
] | [
"#!/usr/bin/python3\n\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport numpy as np\nimport pandas as pd\n\nresults = pd.read_csv('integrity_2019-07-16_00-20-47_21_iteraciones.csv')\nresults.head()\nresults['Max memory (mb)'] = results['Max memory (kb)'] / 1024\nresults = results.drop('Max memory (kb)... | [
[
"pandas.read_csv",
"matplotlib.pyplot.show"
]
] |
atztogo/niggli | [
"157e3474fc63ef415584e8b5db4483c65c6abf01"
] | [
"python/niggli/niggli.py"
] | [
"# Copyright (C) 2016 Atsushi Togo\n# All rights reserved.\n#\n# This file is part of niggli\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 copyrig... | [
[
"numpy.reshape",
"numpy.ravel"
]
] |
irec-org/irec | [
"a7ec8a53dcb6489c31f64d7192720baca50e0049"
] | [
"irec/offline_experiments/evaluation_policies/limited_interaction.py"
] | [
"from .base import EvaluationPolicy\nfrom threadpoolctl import threadpool_limits\nfrom collections import defaultdict\nimport scipy.sparse\nimport numpy as np\nimport random\n\nclass LimitedInteraction(EvaluationPolicy):\n\n \"\"\"LimitedInteraction\n\n In this evaluation policy, the system will perform new a... | [
[
"numpy.unique",
"numpy.nonzero",
"numpy.ones"
]
] |
sheroze1123/HROM_BIDL | [
"7a7efba71d93fecf9be560e920e71cfa737a384c",
"7a7efba71d93fecf9be560e920e71cfa737a384c"
] | [
"bayesian_inference/muq_old/muq_mod_five_param.py",
"rom/petsc_affine_ROM.py"
] | [
"import sys; sys.path.append('../')\nsys.path.insert(0,'/home/fenics/Installations/MUQ_INSTALL/lib')\nimport pymuqModeling as mm\nimport numpy as np\nfrom tensorflow.keras.optimizers import Adam, RMSprop, Adadelta\nfrom fom.forward_solve import Fin, get_space\nfrom deep_learning.dl_model import load_parametric_mode... | [
[
"numpy.array",
"numpy.loadtxt"
],
[
"numpy.dot",
"numpy.linalg.solve",
"tensorflow.keras.backend.get_session",
"tensorflow.keras.backend.gradients",
"tensorflow.placeholder",
"numpy.linalg.norm",
"tensorflow.square",
"numpy.array",
"numpy.zeros",
"numpy.vstack"
... |
aracoara/price_action_teste | [
"1bfd1e4f2f2446108832f969a038a3616ba13e4a"
] | [
"e_web_app_local_function_final_teste.py"
] | [
"\r\n\r\n## import custom functions\r\nfrom c_price_action_function_teste import pa_long_ativo_func\r\nfrom c_price_action_function_teste import ranking_ativo_func\r\nfrom c_price_action_function_teste import pa_segmentos_temp_func\r\nfrom c_price_action_function_teste import ranking_segmento_func\r\nfrom c_price_a... | [
[
"pandas.merge",
"pandas.read_json"
]
] |
JMichaelStringer/NeMo | [
"b5b29a69ccb0ec3d8c9ace2f33872ee99858a559"
] | [
"nemo/collections/asr/modules/conv_asr.py"
] | [
"# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless re... | [
[
"torch.nn.functional.normalize",
"torch.nn.Sequential",
"torch.nn.functional.softmax",
"torch.nn.AdaptiveMaxPool1d",
"torch.randint",
"torch.nn.BatchNorm1d",
"torch.cat",
"torch.randn",
"torch.nn.ModuleList",
"torch.nn.Linear",
"torch.nn.Conv1d",
"torch.nn.AdaptiveA... |
NicolasISEN/Facial_landmark_emotion_detection | [
"c7b8d7b0ea91a3496e3611bc1aab221709added4"
] | [
"models/model_source/v1.0.0/learning.py"
] | [
"import sys\nfrom dataset import Dataset\nimport tqdm\nimport time\nfrom cnn import Net32, Net256\nimport torch\nimport torch.nn as nn\nimport numpy as np\nimport logging\nimport argparse\nimport torchvision.models as models\nfrom torchvision import datasets\nfrom tensorboardX import SummaryWriter\n\ndevice = torch... | [
[
"torch.nn.CrossEntropyLoss",
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"torch.max",
"torch.no_grad",
"torch.cuda.is_available",
"torch.save"
]
] |
vykimo/twitter_best_date | [
"557c3a1e084633760ceda11ae340a3d2871d7926"
] | [
"train_hashtag.py"
] | [
"#!/usr/bin/env python\n# encoding: utf-8\nimport numpy\nimport random\nimport argparse\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection import cross_val_predict\nfrom sklearn.model_selection import KFold\nfrom sklearn.preproces... | [
[
"sklearn.ensemble.RandomForestRegressor",
"sklearn.model_selection.train_test_split",
"sklearn.metrics.mean_squared_error"
]
] |
riemarc/pyinduct | [
"5c407b6ae301be76639d464d43a20ba3fafd7e66",
"5c407b6ae301be76639d464d43a20ba3fafd7e66"
] | [
"pyinduct/examples/string_with_mass/observer_evp_scripts/modal_approximation.py",
"pyinduct/simulation.py"
] | [
"from pyinduct.examples.string_with_mass.utils import sym, param, obs_gain\nfrom sympy.utilities import lambdify\nfrom scipy.integrate import quad\nimport numpy as np\nimport sympy as sp\n\n\ndef _sum(iterable):\n sum = iterable[0] * 0\n for v in iterable:\n sum += v\n return sum\n\n\ndef _discard_s... | [
[
"numpy.real_if_close",
"numpy.imag",
"numpy.abs",
"numpy.linspace",
"numpy.eye",
"numpy.roots",
"numpy.exp",
"numpy.real",
"numpy.vectorize",
"scipy.integrate.quad",
"numpy.array",
"numpy.testing.assert_array_almost_equal"
],
[
"numpy.linalg.matrix_rank",
... |
Kanikamiglani31/tensorflow | [
"428cdeda09aef81e958eeb274b83d27ad635b57b"
] | [
"tensorflow/python/keras/engine/training.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.keras.distribute.distributed_training_utils.is_tpu_strategy",
"tensorflow.python.keras.saving.saved_model.model_serialization.ModelSavedModelSaver",
"tensorflow.python.eager.context.async_wait",
"tensorflow.python.util.tf_decorator.make_decorator",
"tensorflow.python.distrib... |
NeelayS/realtime_hand | [
"219c772b9b7df60c390edac7da23f9cdddebca4d",
"219c772b9b7df60c390edac7da23f9cdddebca4d"
] | [
"realtime_hand_3d/segmentation/models/espnet.py",
"realtime_hand_3d/segmentation/utils/metrics.py"
] | [
"import torch\nimport torch.nn as nn\n\nfrom .retrieve import SEG_MODELS_REGISTRY\n\n\nclass CBR(nn.Module):\n \"\"\"\n This class defines the convolution layer with batch normalization and PReLU activation\n \"\"\"\n\n def __init__(self, nIn, nOut, kSize, stride=1):\n \"\"\"\n :param nIn:... | [
[
"torch.nn.ConvTranspose2d",
"torch.cat",
"torch.load",
"torch.nn.PReLU",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d"
],
[
"numpy.array",
"torch.nn.functional.interpolate",
"torch.argmax"
]
] |
FrederikWarburg/NLSPN_ECCV20 | [
"2db2d4eb269c7d27e16c8ff4f4fb3331778ef6b6",
"2db2d4eb269c7d27e16c8ff4f4fb3331778ef6b6"
] | [
"src/main.py",
"src/model/unetmodel.py"
] | [
"\"\"\"\n Non-Local Spatial Propagation Network for Depth Completion\n Jinsun Park, Kyungdon Joo, Zhe Hu, Chi-Kuei Liu and In So Kweon\n\n European Conference on Computer Vision (ECCV), Aug 2020\n\n Project Page : https://github.com/zzangjinsun/NLSPN_ECCV20\n Author : Jinsun Park (zzangjinsun@kaist.a... | [
[
"torch.distributed.init_process_group",
"torch.cuda.set_device",
"numpy.random.seed",
"torch.utils.data.distributed.DistributedSampler",
"torch.manual_seed",
"torch.load",
"torch.multiprocessing.spawn",
"torch.utils.data.DataLoader",
"torch.set_grad_enabled",
"torch.no_grad... |
s19282/PAD | [
"ca9fe4e199927db0a62314f7b8464f70c96aacd3"
] | [
"cw05/z1_2_3.py"
] | [
"import pandas as pd\n\ncustomers = pd.read_csv('customers.csv', delimiter=\",\")\norders = pd.read_csv('orders.csv', delimiter=\",\")\n# z1\nprint(orders.describe())\nprint(orders.info())\nprint(orders.head())\n# a\norders['order_date'] = pd.to_datetime(orders['order_date'], format='%Y/%m/%d')\n# b\nprint(orders['... | [
[
"pandas.merge",
"pandas.read_csv",
"pandas.to_datetime"
]
] |
leozhoujf/scikit-plot | [
"2dd3e6a76df77edcbd724c4db25575f70abb57cb",
"2dd3e6a76df77edcbd724c4db25575f70abb57cb"
] | [
"scikitplot/tests/test_decomposition.py",
"scikitplot/metrics.py"
] | [
"from __future__ import absolute_import\nimport unittest\n\nfrom sklearn.datasets import load_iris as load_data\nfrom sklearn.decomposition import PCA\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom scikitplot.decomposition import plot_pca_component_variance\nfrom scikitplot.decomposition import plot... | [
[
"numpy.random.seed",
"sklearn.datasets.load_iris",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.close",
"sklearn.decomposition.PCA"
],
[
"sklearn.metrics.silhouette_samples",
"sklearn.metrics.silhouette_score",
"numpy.asarray",
"numpy.around",
"numpy.in1d",
"skl... |
prOttonicFusion/spectrograph | [
"9ebc1c4b129f9aff6b83024b3d4aa78af556c813"
] | [
"linearSpectrum.py"
] | [
"\"\"\"\nPlot a spectrum from a data file of color codes\n\"\"\"\n\n__author__ = \"prOttonicFusion\"\n__version__ = \"0.1.0\"\n__license__ = \"MIT\"\n\nimport numpy as np\nimport argparse\nfrom math import pi\nfrom bokeh.io import output_file, export_png, show\nfrom bokeh.plotting import figure\n\n\ndef main(color_... | [
[
"numpy.loadtxt"
]
] |
menikhilpandey/AART | [
"4accd3ad777933a46c57caa6e9fc7ac85cb667ee"
] | [
"emotion_detection/realtime_demo.py"
] | [
"import numpy as np\nimport argparse\nimport cv2\nfrom keras.models import Sequential\nfrom keras.layers.core import Dense, Dropout, Flatten\nfrom keras.layers.convolutional import Conv2D\nfrom keras.optimizers import Adam\nfrom keras.layers.pooling import MaxPooling2D\nfrom keras.preprocessing.image import ImageDa... | [
[
"numpy.argmax"
]
] |
Chicco94/breakout-Q-learning | [
"dfb7c1d18c4472f21828f1163641817b6f44d726"
] | [
"model.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.nn.functional as F\nimport os\n\nclass Linear_QNet(nn.Module):\n\tdef __init__(self, input_size, hidden_size, hidden_size2, output_size):\n\t\t# feed forward neural network\n\t\tsuper().__init__()\n\t\tself.linear1 = nn.Linear(input_siz... | [
[
"torch.load",
"torch.argmax",
"torch.unsqueeze",
"torch.tensor",
"torch.nn.Linear",
"torch.nn.MSELoss",
"torch.save"
]
] |
Pangoraw/Deep-SVDD-PyTorch | [
"806f7099cea2013a87ebb32f30a6f4c9595ebbeb"
] | [
"src/datasets/mnist.py"
] | [
"from torch.utils.data import Subset\nfrom PIL import Image\nfrom torchvision.datasets import MNIST\nfrom base.torchvision_dataset import TorchvisionDataset\nfrom .preprocessing import get_target_label_idx, global_contrast_normalization\n\nimport torchvision.transforms as transforms\n\nMNIST.resources = [\n ... | [
[
"torch.utils.data.Subset"
]
] |
liseda-lab/Supervised-SS | [
"62cbea0475fb93693c1edf4f6d1ff1bdaab17265"
] | [
"Regression/gplearn/_program.py"
] | [
"\"\"\"The underlying data structure used in gplearn.\r\n\r\nThe :mod:`gplearn._program` module contains the underlying representation of a\r\ncomputer program. It is used for creating and evolving programs used in the\r\n:mod:`gplearn.genetic` module.\r\n\"\"\"\r\n\r\n# Author: Trevor Stephens <trevorstephens.com>... | [
[
"numpy.repeat",
"numpy.where",
"sklearn.utils.random.sample_without_replacement",
"numpy.bincount"
]
] |
Shivvrat/Machine-Learning-Algorithms | [
"f20503ee513dbd7e51470c464e47358dd6c1e133"
] | [
"Learning-Algorithms-for-Bayesian-Networks/Learning-Algorithms-for-Bayesian-Networks-master/pod_em_learn.py"
] | [
"\"\"\"\r\n\r\n__author__ = \"Shivvrat Arya\"\r\n__version__ = \"Python3.7\"\r\n\"\"\"\r\n\r\nfrom numpy import array, zeros, nan_to_num, divide, product\r\n\r\nimport helper\r\nfrom helper import generate_random_parameters, complete_data\r\n\r\n\r\ndef train(pod_examples, var_in_clique, markov, cardinalit... | [
[
"numpy.product",
"numpy.nan_to_num",
"numpy.array",
"numpy.zeros",
"numpy.divide"
]
] |
achang67/pyGSM-1 | [
"ba7a1a1563a0d7765999e6683a93236571e6a470"
] | [
"pygsm/coordinate_systems/internal_coordinates.py"
] | [
"#!/usr/bin/env python\n\n# standard library imports\nimport time\n\n# third party\nfrom collections import OrderedDict\nimport numpy as np\nfrom numpy.linalg import multi_dot\n\nfrom utilities import elements, options, nifty, block_matrix\n\nELEMENT_TABLE = elements.ElementData()\n\nCacheWarning = False\n\n\nclass... | [
[
"numpy.diag",
"numpy.dot",
"numpy.linalg.svd",
"numpy.random.random",
"numpy.abs",
"numpy.einsum",
"numpy.linalg.inv",
"numpy.linalg.multi_dot",
"numpy.linalg.norm",
"numpy.zeros_like",
"numpy.array"
]
] |
chriscab83/CarND-Semantic-Segmentation | [
"8fcfa05dfe22ac9fcbabe2ee4a7889b61c9d58b4"
] | [
"main.py"
] | [
"import os.path\nimport tensorflow as tf\nimport helper\nimport warnings\nfrom distutils.version import LooseVersion\nimport project_tests as tests\n\n\n# Check TensorFlow Version\nassert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf._... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.test.gpu_device_name",
"tensorflow.reshape",
"tensorflow.placeholder",
"tensorflow.contrib.layers.l2_regularizer",
"tensorflow.global_variables_initializer",
"tensorflow.add",
"tensorflow.train.AdamOptimizer",
"tens... |
math2peters/CastleSerialLink | [
"70d4792b9555df52f5d1237b7a0c9f2f0bed7a53"
] | [
"CastleSerialLinkControl.py"
] | [
"import numpy as np\n\nclass SerialLink():\n \"\"\"\n Class to communicate with castle serial link, takes Pyserial Serial class in constructor\n \"\"\"\n\n\n def __init__(self, serial, device_id=0):\n \"\"\"\n :param serial: Pyserial Serial class\n :param device_id: number between 0... | [
[
"numpy.sum"
]
] |
Binjie-Qin/SVS-net | [
"00ae880143f2c84e600ce1638d2c2fa5e892e24d"
] | [
"src/data_feed.py"
] | [
"\r\nimport time\r\nimport numpy as np\r\nimport random\r\nimport scipy as sp\r\nimport scipy.interpolate\r\nimport scipy.ndimage\r\nimport scipy.ndimage.interpolation\r\nimport random\r\nimport h5py\r\nimport pylab as py\r\nimport matplotlib.pyplot as plt\r\nfrom skimage import transform\r\nimport random\r\nimport... | [
[
"numpy.rollaxis",
"numpy.dot",
"numpy.asarray",
"numpy.max",
"numpy.random.randint",
"numpy.clip",
"numpy.reshape",
"numpy.stack",
"numpy.sin",
"numpy.float32",
"scipy.ndimage.interpolation.affine_transform",
"numpy.min",
"matplotlib.pyplot.switch_backend",
... |
nadegeguiglielmoni/HapPy | [
"fec797800157acda4d501dc60d890b5b0bbb6bee"
] | [
"happy/estimate.py"
] | [
"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n\n# General\nimport os, sys, math\n\n# Happy\nfrom happy.utils import *\nfrom happy.plot import *\n\n# Stats\nfrom scipy.signal import savgol_filter # SmoothingAUC\nfrom scipy.signal import find_peaks # Finding peaks\nfrom scipy.signal import peak_widths\n\ndef estimat... | [
[
"scipy.signal.find_peaks",
"scipy.signal.savgol_filter",
"scipy.signal.peak_widths"
]
] |
Flobian/DSAMaterialNetworks | [
"e9628e9e72ec63ca0d228af552c6a679faf72543"
] | [
"worksheets_English/sheet1/code/pathgraph.py"
] | [
"# -*- coding: utf-8 -*-\r\n\r\n# import necessary library\r\nimport numpy as np\r\n\r\n# define a function \r\ndef path_graph( n ):\r\n \"\"\"\r\n Returns the (n x n) adjacency matrix \r\n of a path graph with n nodes.\r\n \"\"\"\r\n\r\n # empty adjacency matrix of shape (n x n)\r\n A = n... | [
[
"numpy.zeros",
"numpy.transpose"
]
] |
ppruthi/SynapseML | [
"d38c82455b28585cb35f6f4386a508ff4026f1d3"
] | [
"core/src/main/python/synapse/ml/cyber/anomaly/collaborative_filtering.py"
] | [
"__author__ = \"rolevin\"\n\nimport os\nfrom typing import List, Optional, Tuple\n\nfrom synapse.ml.cyber.anomaly.complement_access import ComplementAccessTransformer\nfrom synapse.ml.cyber.feature import indexers, scalers\nfrom synapse.ml.cyber.utils import spark_utils\n\nimport numpy as np\n\nfrom pyspark import ... | [
[
"numpy.array"
]
] |
moondaiy/TensorFlowTutorials | [
"c7f0255e3704c5a40f72ac0707684fb201123c1c",
"c7f0255e3704c5a40f72ac0707684fb201123c1c",
"c7f0255e3704c5a40f72ac0707684fb201123c1c"
] | [
"TensorFlowBasic/convNet.py",
"TensorFlowBasic/tensorBoard.py",
"TensorFlowBasic/tensor_create.py"
] | [
"\"\"\"\n卷积神经网络\n两个卷积层，两个全连接层\n输入 [sample * 28 * 28 * 1 ] (灰度图)\n[ 28 * 28 *1 ] --> (32个卷积核，每个大小5*5*1,sample方式卷积) --> [ 28 * 28 * 32] --> (池化 2*2 ，步长2)--> [14 *14 *32]\n[ 14 * 14 *32] --> (64个卷积核，每个大小 5 * 5 * 32,sample方式卷积) --> [14 * 14 *64] --> (池化 2*2 ，步长2)--> [7 * 7 *64] \n[ 7 * 7 * 64] --> reshape 成列向量 --> ... | [
[
"tensorflow.matmul",
"tensorflow.__version__.split",
"tensorflow.truncated_normal",
"tensorflow.constant",
"tensorflow.Variable",
"tensorflow.nn.max_pool",
"tensorflow.reshape",
"tensorflow.cast",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"ten... |
sadicLiu/mask_rcnn_code | [
"a8878f81f6bbfa63b5a4b7ca2bfb80673e4febfd",
"a8878f81f6bbfa63b5a4b7ca2bfb80673e4febfd"
] | [
"maskrcnn_benchmark/engine/trainer.py",
"maskrcnn_benchmark/layers/misc.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\nimport datetime\nimport logging\nimport time\n\nimport torch\nimport torch.distributed as dist\n\nfrom maskrcnn_benchmark.utils.comm import get_world_size\nfrom maskrcnn_benchmark.utils.metric_logger import MetricLogger\n\n\ndef reduce_loss_d... | [
[
"torch.cuda.max_memory_allocated",
"torch.distributed.reduce",
"torch.no_grad",
"torch.stack",
"torch.distributed.get_rank"
],
[
"torch.nn.modules.utils._ntuple",
"torch.nn.functional.interpolate"
]
] |
SaibheMcC/ARC | [
"52ba259c29443f1671cdf583889e31445694fe69"
] | [
"src/solution_017c7c7b.py"
] | [
"import json #import the json module\nimport sys #import the sys module\nimport numpy as np #import the numpy module\n\n\n#solve function\ndef solve():\n\n #set datalocation to the argument passed in from the command line\n datalocation = sys.argv[1]\n\n #open datalocation, and load it into variable data\n... | [
[
"numpy.array"
]
] |
arengela/AngelaUCSFCodeAll | [
"aeacf478bae7fbddfe6903c963fb9a08b0f0aecc"
] | [
"koepsell-phase-coupling-estimation-271441c/python/phasemodel/setup.py"
] | [
"def configuration(parent_package='',top_path=None):\n from numpy.distutils.misc_util import Configuration\n config = Configuration('phasemodel', parent_package, top_path)\n\n config.add_data_dir('tests')\n config.add_data_files('*.pyx')\n\n return config\n\nif __name__ == '__main__':\n from numpy... | [
[
"numpy.distutils.misc_util.Configuration"
]
] |
clw5180/yolact_notes | [
"c59fbb9cb49e1008a00a17e599014f9bd8337100"
] | [
"eval.py"
] | [
"from data import COCODetection, get_label_map, MEANS, COLORS\nfrom yolact import Yolact\nfrom utils.augmentations import BaseTransform, FastBaseTransform, Resize\nfrom utils.functions import MovingAverage, ProgressBar\nfrom layers.box_utils import jaccard, center_size, mask_iou\nfrom utils import timer\nfrom utils... | [
[
"torch.set_default_tensor_type",
"torch.cuda.synchronize",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.title",
"torch.Tensor",
"torch.from_numpy",
"numpy.save",
"torch.no_grad",
"numpy.searchsorted",
"torch.stack",
"numpy.array",
"matplotlib.pyplot.show"
]
] |
RiceAstroparticleLab/strax | [
"38a7fcb58e92e20a3441ba008b7598de65068ed0"
] | [
"strax/dtypes.py"
] | [
"\"\"\"Fundamental dtypes for use in strax.\n\nNote that if you change the dtype titles (comments), numba will crash if\nthere is an existing numba cache. Clear __pycache__ and restart.\nTODO: file numba issue.\n\"\"\"\nimport numpy as np\nimport typing as ty\nimport numba\n\n\n__all__ = ('interval_dtype raw_record... | [
[
"numpy.shape"
]
] |
disc5/DyraLib | [
"74045c5e7cadb1b6469fb0bbccd96d8ff7b0d47b"
] | [
"Matlab/PLNet/python_tensorflow/dypy/utils.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nUtility functions for dyad ranking / PyDR\r\n\r\n(2017/1)\r\n@author: Dirk Schaefer\r\n\"\"\"\r\n#%%\r\nfrom __future__ import division\r\nimport numpy as np\r\n#%%\r\ndef convert_orderingvec_to_rankingvec(ordering):\r\n '''\r\n Converts an ordering vector to a rankin... | [
[
"numpy.kron",
"numpy.zeros",
"numpy.ones"
]
] |
yohai/pde-superresolution | [
"5ed0d4c4d039c9a8ed2b197a07839c83fea89251",
"5ed0d4c4d039c9a8ed2b197a07839c83fea89251"
] | [
"pde_superresolution/scripts/create_training_data.py",
"pde_superresolution/duckarray.py"
] | [
"# Copyright 2018 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.arange"
],
[
"tensorflow.concat",
"numpy.minimum",
"tensorflow.reduce_sum",
"tensorflow.minimum",
"numpy.concatenate",
"numpy.mean",
"numpy.exp",
"tensorflow.spectral.irfft",
"numpy.fft.rfftfreq",
"numpy.reshape",
"numpy.arange",
"numpy.sin",
"num... |
xinyufei/Quantum-Control-qutip | [
"bd8a119b9ff8ac0929ffb1f706328759d89fcb5e",
"bd8a119b9ff8ac0929ffb1f706328759d89fcb5e"
] | [
"qutip/tests/test_states.py",
"qutip/floquet.py"
] | [
"# This file is part of QuTiP: Quantum Toolbox in Python.\r\n#\r\n# Copyright (c) 2011 and later, Paul D. Nation and Robert J. Johansson.\r\n# All rights reserved.\r\n#\r\n# Redistribution and use in source and binary forms, with or without\r\n# modification, are permitted provided that the following co... | [
[
"numpy.testing.run_module_suite",
"numpy.zeros",
"numpy.testing.assert_"
],
[
"numpy.array",
"numpy.sqrt",
"numpy.linspace",
"numpy.arange",
"numpy.sign",
"numpy.shape",
"numpy.argsort",
"numpy.angle",
"numpy.exp",
"numpy.zeros",
"numpy.where",
"scip... |
evidation-health/bokeh | [
"2c580d93419033b962d36e3c46d7606cc2f24606"
] | [
"bokeh/_legacy_charts/builder/tests/test_step_builder.py"
] | [
"\"\"\" This is the Bokeh charts testing interface.\n\n\"\"\"\n#-----------------------------------------------------------------------------\n# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.\n#\n# Powered by the Bokeh Development Team.\n#\n# The full license is in the file LICENSE.txt, d... | [
[
"numpy.testing.assert_array_equal",
"numpy.array",
"pandas.DataFrame"
]
] |
hanlinxuy/HASCO | [
"f7c3ac51817b2550f1dcfe7c9a79f81fd15f232c"
] | [
"src/codesign/ax_extend.py"
] | [
"import inspect\r\nfrom typing import Any, Callable, Dict, List, Optional\r\n\r\nimport numpy as np\r\nfrom ax.core.arm import Arm\r\nfrom ax.core.base_trial import BaseTrial, TrialStatus\r\nfrom ax.core.batch_trial import BatchTrial\r\nfrom ax.core.data import Data\r\nfrom ax.core.experiment import Experiment\r\nf... | [
[
"numpy.minimum.accumulate",
"numpy.maximum.accumulate"
]
] |
eozd/probability | [
"2b866780982182fe0bf4e5336ee09fdb74cc2b03"
] | [
"tensorflow_probability/python/distributions/autoregressive.py"
] | [
"# Copyright 2018 The TensorFlow Probability Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by a... | [
[
"tensorflow.compat.v1.name_scope"
]
] |
meyer-lab/bi-cytok | [
"34bac90b88d53c02e742dec3a5f663734e860f1b"
] | [
"genFigures.py"
] | [
"#!/usr/bin/env python3\n\nimport sys\nimport logging\nimport time\nimport matplotlib\nmatplotlib.use('AGG')\n\nfdir = './output/'\n\nlogging.basicConfig(format='%(levelname)s:%(message)s', level=logging.INFO)\n\nif __name__ == '__main__':\n start = time.time()\n nameOut = 'figure' + sys.argv[1]\n\n exec('... | [
[
"matplotlib.use"
]
] |
kprokofi/ML_Decoder | [
"c01c50e0165e607afbebd8d615708ef9c084dd5b"
] | [
"src_files/models/timm_wrapper.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.nn import Module as Module\nimport timm\nfrom torch.nn import Parameter\nimport torch.nn.functional as F\n\nclass AngleSimpleLinear(nn.Module):\n \"\"\"Computes cos of angles between input vectors and weights vectors\"\"\"\n\n def __init__(self, in_features, ou... | [
[
"torch.nn.functional.normalize",
"torch.Tensor",
"torch.nn.PReLU",
"torch.nn.Identity",
"torch.t"
]
] |
TMB-CSB/HDXer | [
"6ad1d73931f6a53922c3c960e6c3f67ebcbd7161"
] | [
"HDXer/dfpred.py"
] | [
"# Superclass for HDX deuterated fraction prediction method objects\n#\n\nimport mdtraj as md\nimport numpy as np\nimport os, glob, pickle\nfrom .functions import list_prolines\nfrom .errors import HDX_Error\n\n\nclass DfPredictor(object):\n \"\"\"Superclass for all methods that use the general rate equation:\n\... | [
[
"numpy.log",
"numpy.array_equal",
"numpy.logical_and",
"numpy.asarray",
"numpy.stack",
"numpy.ones",
"numpy.concatenate",
"numpy.max",
"numpy.delete",
"numpy.std",
"numpy.mean",
"numpy.insert",
"numpy.exp",
"numpy.where",
"numpy.isinf"
]
] |
flyinslowly/flyinnlp | [
"328e45d2952da6cdebbc1cccbb6a0aa9972859df"
] | [
"allennlp/models/reading_comprehension/bidaf.py"
] | [
"import logging\nfrom typing import Any, Dict, List, Optional\n\nimport torch\nfrom torch.nn.functional import nll_loss, binary_cross_entropy_with_logits, sigmoid\n\nfrom allennlp.common.checks import check_dimensions_match\nfrom allennlp.data import Vocabulary\nfrom allennlp.models.model import Model\nfrom allennl... | [
[
"torch.nn.Dropout",
"torch.sigmoid",
"torch.cat",
"torch.nn.functional.binary_cross_entropy_with_logits",
"torch.zeros_like",
"torch.nn.Linear",
"torch.ones_like"
]
] |
CaoZhongZ/inference | [
"58025f8fde679ea864d34f96ecc9f14bf70ece53",
"58025f8fde679ea864d34f96ecc9f14bf70ece53",
"58025f8fde679ea864d34f96ecc9f14bf70ece53"
] | [
"speech_recognition/rnnt/pytorch/utils/download_librispeech.py",
"recommendation/dlrm/pytorch/python/backend_onnxruntime.py",
"speech_recognition/rnnt/pytorch/parts/segment.py"
] | [
"#!/usr/bin/env python\n# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICEN... | [
[
"pandas.read_csv"
],
[
"torch.is_tensor",
"torch.tensor"
],
[
"numpy.pad",
"numpy.log10",
"numpy.mean",
"numpy.any",
"numpy.iinfo"
]
] |
qq2016/kubeflow_learning | [
"c93b792d67c8c52bc91d4ccf5fbaead4e2324331"
] | [
"github_issue_summarization/pipelines/components/kubeflow-resources/tf-serving-gh/deploy-tf-serve.py"
] | [
"# Copyright 2018 Google Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by app... | [
[
"tensorflow.python.lib.io.file_io.list_directory"
]
] |
BrookPurdueUniversity/CarND-Capstone | [
"9e226ffacee49c545fbbfcecf3a47ab6f66302ef"
] | [
"ros/src/tl_detector/tl_detector.py"
] | [
"#!/usr/bin/env python\nimport rospy\nfrom std_msgs.msg import Int32\nfrom geometry_msgs.msg import PoseStamped, Pose\nfrom styx_msgs.msg import TrafficLightArray, TrafficLight\nfrom styx_msgs.msg import Lane\nfrom sensor_msgs.msg import Image\nfrom cv_bridge import CvBridge\nfrom light_classification.tl_classifier... | [
[
"scipy.spatial.KDTree"
]
] |
5-pankajkr/ga-learner-dsmp-repo | [
"11d091877169c48516308a1ca3e7a5e7abf649a7"
] | [
"Human-activity-recognition-with-smartphones/code.py"
] | [
"# --------------\nimport pandas as pd\nfrom collections import Counter\n\n# Load dataset\ndata = pd.read_csv(path)\nprint(data.isnull().sum())\n\nprint(data.describe())\n\n\n# --------------\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\nsns.set_style(style='darkgrid')\n\n# Store the label values \n... | [
[
"pandas.read_csv",
"pandas.Series",
"sklearn.metrics.accuracy_score",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"sklearn.preprocessing.LabelEncoder",
"sklearn.metrics.precision_recall_fscore_support",
"sklearn.svm.SVC",
"sklearn.svm.LinearSVC",
"sklear... |
nimu77/lambdata-nirmal | [
"bc69505aada975c8056fefa06b510d276ce9fd50"
] | [
"my_lambdata/my_mod_one.py"
] | [
"import pandas as pd\n\n\ndef checks_null(a):\n '''checks to see if dataframe has null values'''\n a = pd.DataFrame(a)\n\n if a.isnull().values.any():\n print(f'DataFrame has some null values, please replace it or drop it.')\n else:\n print(f'DataFrame is good to go. No null values.')\n\n\... | [
[
"pandas.DataFrame"
]
] |
link-kut/deeplink_public | [
"688c379bfeb63156e865d78d0428f97d7d203cc1",
"688c379bfeb63156e865d78d0428f97d7d203cc1",
"688c379bfeb63156e865d78d0428f97d7d203cc1"
] | [
"1.DeepLearning/01.Multiple_Neurons/or_gate_three_neurons_target_learning.py",
"1.DeepLearning/deeplink/optimizers.py",
"2.ReinforcementLearning/FrozenLake/FrozenLake-1.py"
] | [
"from __future__ import print_function\nimport numpy as np\nimport random\nimport math\n\nclass Neuron1:\n def __init__(self):\n self.w1 = np.array([random.random(), random.random()]) # weight of one input\n self.b1 = random.random() # bias\n print(\"Neuron1 - Initial w1: {0}, b1: {1}\".... | [
[
"numpy.dot",
"numpy.array"
],
[
"numpy.zeros_like",
"numpy.sqrt"
],
[
"numpy.amax",
"numpy.nonzero",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"numpy.max",
"matplotlib.pyplot.show",
"numpy.zeros"
]
] |
3DAlgoLab/vispy | [
"91972307cf336674aad58198fb26b9e46f8f9ca1",
"91972307cf336674aad58198fb26b9e46f8f9ca1",
"91972307cf336674aad58198fb26b9e46f8f9ca1",
"91972307cf336674aad58198fb26b9e46f8f9ca1",
"91972307cf336674aad58198fb26b9e46f8f9ca1"
] | [
"vispy/visuals/histogram.py",
"vispy/visuals/tests/test_image.py",
"vispy/app/tests/test_ipython.py",
"examples/demo/gloo/camera.py",
"examples/demo/gloo/galaxy.py"
] | [
"# -*- coding: utf-8 -*-\n# -----------------------------------------------------------------------------\n# Copyright (c) Vispy Development Team. All Rights Reserved.\n# Distributed under the (new) BSD License. See LICENSE.txt for more info.\n# ----------------------------------------------------------------------... | [
[
"numpy.asarray",
"numpy.repeat",
"numpy.array",
"numpy.histogram"
],
[
"numpy.random.seed",
"numpy.clip",
"numpy.issubdtype",
"numpy.random.random_sample",
"numpy.stack",
"numpy.dtype",
"numpy.ones",
"numpy.zeros_like",
"numpy.random.rand",
"numpy.iinfo"... |
TrainingByPackt/Beginning-Python-AI | [
"b1e68d892e65b1f7b347330ef2a90a1b546bdd25",
"b1e68d892e65b1f7b347330ef2a90a1b546bdd25",
"b1e68d892e65b1f7b347330ef2a90a1b546bdd25",
"b1e68d892e65b1f7b347330ef2a90a1b546bdd25"
] | [
"Lesson04/Activity 08 Increasing the Accuracy of Credit Scoring/credit_scoring.py",
"Lesson03/polynomial_prediction.py",
"Lesson03/first.py",
"Lesson03/support_vector_regression_degree_3_polynomial_kernel.py"
] | [
"import pandas\nimport numpy as np\nfrom sklearn import model_selection\nfrom sklearn import preprocessing\nfrom sklearn import neighbors\n\n# 1. Loading data\ndata_frame = pandas.read_csv('german.data', sep=' ')\ndata_frame.replace('NA', -1000000, inplace=True)\n\n# 2. Label encoding\nlabels = {\n 'CheckingAcco... | [
[
"pandas.read_csv",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.preprocessing.LabelEncoder",
"numpy.array",
"sklearn.preprocessing.MinMaxScaler"
],
[
"matplotlib.pyplot.scatter",
"sklearn.model_selection.... |
firasm/pysketcher | [
"ef0c25b11b739197e254d714c69c86e107059be3"
] | [
"tests/test_point.py"
] | [
"from math import inf\n\nfrom conftest import isclose\nfrom hypothesis import assume, HealthCheck, note, settings\nimport numpy as np\nimport pytest\n\nfrom pysketcher import Angle, Point\nfrom tests.utils import given_inferred\n\n\nclass TestPoint:\n @given_inferred\n def test_coordinates(self, x: float, y: ... | [
[
"numpy.hypot"
]
] |
manusimidt/deep-reinforcement-learning | [
"814f83b162c445744874be56e6bc4e84aba2a207"
] | [
"dqn/exercise/dqn_agent.py"
] | [
"import numpy as np\nimport random\nfrom collections import namedtuple, deque\n\nfrom model import QNetwork\n\nimport torch\nimport torch.nn.functional as F\nimport torch.optim as optim\n\nBUFFER_SIZE = int(1e5) # replay buffer size\nBATCH_SIZE = 64 # minibatch size\nGAMMA = 0.99 # discount factor\nTAU = 1e-3 #... | [
[
"numpy.arange",
"torch.from_numpy",
"torch.nn.functional.mse_loss",
"torch.no_grad",
"torch.cuda.is_available",
"numpy.vstack"
]
] |
mpes-kit/pesfit | [
"d7a0a4d0ee3cc35d9c9ffb87e156bb5ad2802f81"
] | [
"pesfit/metrics.py"
] | [
"#! /usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport pandas as pd\nimport numpy as np\n\n\nclass GroupMetrics(object):\n \"\"\" Group-wise evaluation metrics calculator.\n \"\"\"\n \n def __init__(self, fres, nband):\n self.fres = fres\n self.nband = nband\n \n @property\n ... | [
[
"numpy.var",
"pandas.read_hdf",
"numpy.array",
"numpy.linalg.norm"
]
] |
zhxtu/ours_video | [
"2762501e4d3795872ffabc49fa3c73fdde10af8b",
"2762501e4d3795872ffabc49fa3c73fdde10af8b",
"2762501e4d3795872ffabc49fa3c73fdde10af8b",
"2762501e4d3795872ffabc49fa3c73fdde10af8b",
"2762501e4d3795872ffabc49fa3c73fdde10af8b"
] | [
"models/modeling/net_utils.py",
"models/model_vid_re.py",
"train_vid.py",
"models/backbones/resnet_models.py",
"test_vid.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nimport pdb\n\nclass LayerNorm(nn.Module):\n\tdef __init__(self, eps=1e-5):\n\t\tsuper().__init__()\n\t\tself.register_parameter('gamma', None)\n\t\tself.register_parameter('beta', None)\n\t\tself.eps = eps\n\n\tdef forward(self, x):\n\t\tif se... | [
[
"torch.div",
"torch.nn.Softmax",
"torch.nn.functional.softmax",
"torch.ones",
"torch.max",
"torch.zeros",
"torch.min",
"torch.pow",
"torch.bmm",
"torch.nn.L1Loss",
"torch.diag",
"torch.nn.MSELoss"
],
[
"torch.mean",
"torch.nn.functional.softmax",
"to... |
duncanriach-nvidia/tensorflow-models | [
"f95f014e6192434f405b7d6209c885072a3f6b6d",
"f95f014e6192434f405b7d6209c885072a3f6b6d",
"f95f014e6192434f405b7d6209c885072a3f6b6d",
"f95f014e6192434f405b7d6209c885072a3f6b6d",
"f95f014e6192434f405b7d6209c885072a3f6b6d",
"f95f014e6192434f405b7d6209c885072a3f6b6d",
"f95f014e6192434f405b7d6209c885072a3f6b6... | [
"research/object_detection/tpu_exporters/utils_test.py",
"official/projects/deepmac_maskrcnn/configs/deep_mask_head_rcnn_config_test.py",
"official/projects/vit/modeling/vit.py",
"official/vision/serving/detection_test.py",
"official/vision/beta/projects/centernet/modeling/centernet_model_test.py",
"offic... | [
"# 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.compat.v1.ones",
"tensorflow.compat.v1.random.uniform",
"tensorflow.compat.v1.test.main"
],
[
"tensorflow.test.main"
],
[
"tensorflow.concat",
"tensorflow.keras.Input",
"tensorflow.keras.backend.image_data_format",
"tensorflow.transpose",
"tensorflow.reduce_... |
jbgh2/speech-denoising-wavenet | [
"386662527b8da69fb3314531a2a7cff087eac557"
] | [
"util.py"
] | [
"# A Wavenet For Speech Denoising - Dario Rethage - 19.05.2017\n# Util.py\n# Utility functions for dealing with audio signals and training a Denoising Wavenet\nimport os\nimport numpy as np\nimport json\nimport warnings\nimport scipy.signal\nimport scipy.stats\nimport soundfile as sf\nimport tensorflow.keras as ker... | [
[
"tensorflow.keras.backend.sign",
"numpy.max",
"numpy.mean",
"numpy.iinfo",
"tensorflow.keras.backend.log",
"numpy.square",
"numpy.arange",
"numpy.eye",
"numpy.finfo",
"numpy.argmax",
"numpy.log",
"tensorflow.keras.backend.abs",
"numpy.append",
"numpy.log10",... |
wkentaro/cupy | [
"1d072d0b3cb2780c0874201c0222d46fa8e7797d",
"1d072d0b3cb2780c0874201c0222d46fa8e7797d"
] | [
"cupy/linalg/product.py",
"cupy/indexing/generate.py"
] | [
"import collections\n\nimport numpy\nimport six\n\nimport cupy\nfrom cupy import core\nfrom cupy import internal\n\n\nmatmul = core.matmul\n\n\ndef dot(a, b, out=None):\n \"\"\"Returns a dot product of two arrays.\n\n For arrays with more than one axis, it computes the dot product along the\n last axis of ... | [
[
"numpy.isscalar"
],
[
"numpy.find_common_type"
]
] |
kh296/InnerEye-DeepLearning | [
"917f8d0b30c4ecfa9198cf55b17b87f359fbbbe9"
] | [
"InnerEye/ML/metrics_dict.py"
] | [
"# ------------------------------------------------------------------------------------------\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.\n# -----------------------------------------------------------... | [
[
"sklearn.metrics.roc_auc_score",
"numpy.expand_dims",
"numpy.unique",
"sklearn.metrics.precision_recall_curve",
"pandas.DataFrame",
"numpy.concatenate",
"sklearn.metrics.log_loss",
"numpy.argmax",
"numpy.mean",
"numpy.nanmean",
"pandas.DataFrame.from_records",
"skle... |
bradyneal/rl-width | [
"9720ccd8bfc9fa29ffa14b9afa6b70d34199292c",
"9720ccd8bfc9fa29ffa14b9afa6b70d34199292c"
] | [
"SAC/main.py",
"DDPG/main.py"
] | [
"import argparse\nimport os\nimport random\nimport time\n\nimport gym\nimport imageio\nimport numpy as np\nimport torch\n\nimport SAC\nimport utils\n\nfrom utils import Logger\nfrom utils import create_folder\n\n\n# Runs policy for X episodes and returns average reward\ndef evaluate_policy(policy,\n ... | [
[
"torch.cuda.synchronize",
"numpy.random.seed",
"torch.manual_seed",
"torch.set_num_threads",
"torch.cuda.manual_seed_all",
"torch.cuda.is_available",
"numpy.array",
"numpy.random.randint"
],
[
"numpy.random.seed",
"torch.manual_seed",
"numpy.save",
"numpy.random... |
kylebarron/geopandas | [
"22b5a0dc23be8876a3270d0c009db5bd765fabf3"
] | [
"geopandas/io/file.py"
] | [
"from distutils.version import LooseVersion\n\nimport numpy as np\n\nimport fiona\n\nfrom geopandas import GeoDataFrame, GeoSeries\n\ntry:\n from fiona import Env as fiona_env\nexcept ImportError:\n from fiona import drivers as fiona_env\n# Adapted from pandas.io.common\nfrom urllib.request import urlopen as ... | [
[
"numpy.zeros"
]
] |
zehuilu/DrMaMP-Distributed-Real-time-Multi-agent-Mission-Planning-Algorithm | [
"894875ebddf7d1f6bbf7a47ce82f05d7be2bafdc",
"894875ebddf7d1f6bbf7a47ce82f05d7be2bafdc"
] | [
"src/PathPlanner.py",
"test/single_compare_MissionPlanning_with_legacy.py"
] | [
"#!/usr/bin/env python3\nimport asyncio\nimport time\nfrom itertools import chain\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pathmagic\nwith pathmagic.context():\n import DrMaMP\n from discrete_path_to_time_traj import discrete_path_to_time_traj\n from interpolate_traj import interpolate_... | [
[
"numpy.array",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.gcf"
],
[
"matplotlib.pyplot.show"
]
] |
crmauceri/pytorch-deeplab-xception | [
"aec2cb7b0c09c346519c6bf22c2cbf419021fdc7"
] | [
"deeplab3/doc/deeplab_xception.py"
] | [
"import math\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.utils.model_zoo as model_zoo\nfrom deeplab3.modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d\n\nBatchNorm2d = SynchronizedBatchNorm2d\n\nclass SeparableConv2d(nn.Module):\n def __init__(self, inplanes... | [
[
"torch.nn.Sequential",
"torch.cat",
"torch.randn",
"torch.nn.Conv2d",
"torch.no_grad",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.ReLU",
"torch.utils.model_zoo.load_url",
"torch.nn.functional.pad"
]
] |
ZuhongLi/tensorflow | [
"d8717a34799b3a70170caec38c39ed4fe893003d"
] | [
"Linear regression/utils.py"
] | [
"import os\nimport gzip\nimport shutil\nimport struct\nimport urllib\n\nos.environ['TF_CPP_MIN_LOG_LEVEL']='2'\n\nfrom matplotlib import pyplot as plt\nimport numpy as np\nimport tensorflow as tf\n\ndef huber_loss(labels, predictions, delta=14.0):\n residual = tf.abs(labels - predictions)\n def f1(): return 0... | [
[
"tensorflow.cond",
"matplotlib.pyplot.imshow",
"numpy.fromfile",
"numpy.asarray",
"numpy.arange",
"tensorflow.data.Dataset.from_tensor_slices",
"numpy.random.permutation",
"tensorflow.square",
"matplotlib.pyplot.show",
"numpy.zeros",
"tensorflow.abs"
]
] |
yizx-1017/modin | [
"2eee697135b30a9694c202456db0635c52c9e6c9"
] | [
"modin/experimental/core/execution/native/implementations/omnisci_on_native/exchange/dataframe_protocol/column.py"
] | [
"# Licensed to Modin Development Team under one or more contributor license agreements.\n# See the NOTICE file distributed with this work for additional information regarding\n# copyright ownership. The Modin Development Team licenses this file to you under the\n# Apache License, Version 2.0 (the \"License\"); you... | [
[
"pandas.api.types.is_categorical_dtype",
"pandas.api.types.is_datetime64_dtype",
"numpy.dtype",
"pandas.api.types.is_string_dtype",
"pandas.api.types.is_bool_dtype"
]
] |
michiboo/HARK | [
"de2aab467de19da2ce76de1b58fb420f421bc85b"
] | [
"HARK/utilities.py"
] | [
"'''\nGeneral purpose / miscellaneous functions. Includes functions to approximate\ncontinuous distributions with discrete ones, utility functions (and their\nderivatives), manipulation of discrete distributions, and basic plotting tools.\n'''\n\nfrom __future__ import division # Import Python 3.x division fu... | [
[
"numpy.dot",
"matplotlib.pyplot.legend",
"scipy.stats.norm.cdf",
"numpy.linspace",
"numpy.sqrt",
"matplotlib.pyplot.rc",
"numpy.cumsum",
"numpy.all",
"numpy.max",
"matplotlib.pyplot.plot",
"numpy.mean",
"numpy.argmin",
"numpy.searchsorted",
"numpy.zeros_like... |
tridao/metal | [
"a077d52d42453be9ca345db73281fb3dc198399c"
] | [
"tests/metal/tuners/test_random_search_tuner.py"
] | [
"import unittest\n\nimport numpy as np\n\nfrom metal.tuners.random_tuner import RandomSearchTuner\n\n\nclass RandomSearchModelTunerTest(unittest.TestCase):\n def test_config_constant(self):\n search_space = {\"a\": 1}\n tuner = RandomSearchTuner(None, None, seed=123)\n configs = list(tuner.c... | [
[
"numpy.mean"
]
] |
fkhiro/kws-ode | [
"5751f9b665511908b26e77f6ea5a97bf87823aab"
] | [
"src/train.py"
] | [
"from collections import ChainMap\nimport argparse\nimport os\nimport random\nimport sys\n\nfrom torch.autograd import Variable\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.utils.data as data\n\nfrom . import model_ode as mod\nfrom .manage_audio import AudioPreprocessor\n\nimport pickle\n\... | [
[
"torch.nn.CrossEntropyLoss",
"torch.max",
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.cuda.set_device",
"torch.manual_seed",
"torch.utils.data.DataLoader",
"numpy.mean",
"torch.autograd.Variable"
]
] |
matpompili/Cirq | [
"b9ce387a7fc1f571b3d6e903c46543c3578677cb",
"b9ce387a7fc1f571b3d6e903c46543c3578677cb"
] | [
"cirq/ion/convert_to_ion_gates_test.py",
"cirq/ops/common_channels_test.py"
] | [
"# Copyright 2018 The Cirq Developers\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law o... | [
[
"numpy.array"
],
[
"numpy.sqrt",
"numpy.eye",
"numpy.testing.assert_almost_equal",
"numpy.array",
"numpy.random.RandomState",
"numpy.empty"
]
] |
ikanher/numpy-MNIST | [
"f41daa6181a04d82667ba4e3f694afcd4b291845"
] | [
"taivasnet/taivasnet/dataloaders.py"
] | [
"\"\"\"\nContains different dataloaders\n\"\"\"\n\n__author__ = 'Aki Rehn'\n__project__ = 'taivasnet'\n\nimport numpy as np\nimport pickle\nimport gzip\n\nclass MNISTDataLoader():\n \"\"\"\n Loads the MNIST training, validation and testing data.\n\n Data from http://deeplearning.net/data/mnist/mnist.pkl.gz... | [
[
"numpy.array",
"numpy.multiply",
"numpy.random.randint"
]
] |
Nebula4869/real-time-object-detection-YOLOv3 | [
"37a36a822840ffa160fc707b570ec279fbdcce34"
] | [
"realtime_detection.py"
] | [
"from yolo_v3 import *\nimport tensorflow as tf\nimport time\nimport cv2\n\n\nINPUT_SIZE = 416\n\n\ndef load_coco_names(file_name):\n names = {}\n with open(file_name) as f:\n for id_, name in enumerate(f):\n names[id_] = name.split('\\n')[0]\n return names\n\n\ndef detect_from_image(imag... | [
[
"tensorflow.placeholder",
"tensorflow.reset_default_graph",
"tensorflow.variable_scope",
"tensorflow.Session",
"tensorflow.train.Saver"
]
] |
jieming2002/models-quiz8 | [
"421dc407a10444cab4bd88c25599077acca96bdb",
"421dc407a10444cab4bd88c25599077acca96bdb",
"421dc407a10444cab4bd88c25599077acca96bdb"
] | [
"official/resnet/resnet_run_loop.py",
"official/resnet/cifar10_test.py",
"official/utils/logging/hooks_helper_test.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.client.device_lib.list_local_devices",
"tensorflow.zeros",
"tensorflow.cast",
"tensorflow.contrib.estimator.TowerOptimizer",
"tensorflow.nn.l2_loss",
"tensorflow.estimator.RunConfig",
"tensorflow.summary.scalar",
"tensorflow.get_collection",
"tensorflow.summa... |
ArgonneCPAC/diffstar | [
"4d15a5b2fd2faa86311c543a151fee73a14bd7f1"
] | [
"scripts/load_smah_data.py"
] | [
"\"\"\"\n\"\"\"\nimport numpy as np\nimport os\nimport h5py\nimport warnings\nfrom diffstar.utils import _get_dt_array\n\n\nTASSO = \"/Users/aphearin/work/DATA/diffmah_data\"\nBEBOP = \"/lcrc/project/halotools/diffmah_data\"\nLAPTOP = \"/Users/alarcon/Documents/diffmah_data\"\n\nH_BPL = 0.678\nH_TNG = 0.6774\nH_MDP... | [
[
"numpy.load",
"numpy.log10",
"numpy.array",
"numpy.cumsum"
]
] |
kshen6/byol-pytorch | [
"49e303adf89ed3d990025262fd30226a00a98d45"
] | [
"examples/lightning/train.py"
] | [
"import os\nimport argparse\nimport multiprocessing\nfrom pathlib import Path\nfrom PIL import Image\n\nimport torch\nfrom torchvision import models, transforms\nfrom torch.utils.data import DataLoader, Dataset\n\nfrom byol_pytorch import BYOL\nimport pytorch_lightning as pl\n\n# test model, a resnet 50\n\nresnet =... | [
[
"torch.utils.data.DataLoader"
]
] |
arjunsinghrathore/routing-transformer | [
"999c611dddf4aa8d45ad3e5063406b24cd450757"
] | [
"routing_transformer/reversible.py"
] | [
"import torch\nimport torch.nn as nn\nfrom operator import itemgetter\nfrom torch.autograd.function import Function\nfrom torch.utils.checkpoint import get_device_states, set_device_states\n\n# for routing arguments into the functions of the reversible layer\n\ndef route_args(router, args, depth):\n routed_args ... | [
[
"torch.set_rng_state",
"torch.enable_grad",
"torch.zeros",
"torch.cat",
"torch.random.fork_rng",
"torch.autograd.backward",
"torch.utils.checkpoint.set_device_states",
"torch.tensor",
"torch.get_rng_state",
"torch.utils.checkpoint.get_device_states",
"torch.no_grad",
... |
AlexRogalskiy/DevArtifacts | [
"931aabb8cbf27656151c54856eb2ea7d1153203a"
] | [
"master/Impractical_Python_Projects-master/Impractical_Python_Projects-master/Chapter_16/benford.py"
] | [
"\"\"\"Check conformance of numerical data to Benford's Law.\"\"\"\nimport sys\nimport math\nfrom collections import defaultdict\nimport matplotlib.pyplot as plt\n\n# Benford's Law percentages for leading digits 1-9\nBENFORD = [30.1, 17.6, 12.5, 9.7, 7.9, 6.7, 5.8, 5.1, 4.6]\n\ndef load_data(filename):\n \"\"\"O... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
]
] |
NERSC/atlas_dl_benchmark | [
"290ed4a5ec19384e1af31b06d15e335bd3df9b27"
] | [
"slurm_tf_helper/setup_clusters.py"
] | [
"#*** License Agreement ***\n#\n#High Energy Physics Deep Learning Convolutional Neural Network Benchmark (HEPCNNB) Copyright (c) 2017, The Regents of the University of California, \n#through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All righ... | [
[
"tensorflow.train.Server",
"tensorflow.train.ClusterSpec"
]
] |
flyslowly/PIEPredict | [
"f6d6770858fc50290665fbcc363b7e474712328f"
] | [
"extract_dataset.py"
] | [
"\"\"\"\nThe code implementation of the paper:\n\nA. Rasouli, I. Kotseruba, T. Kunic, and J. Tsotsos, \"PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and\nTrajectory Prediction\", ICCV 2019.\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file e... | [
[
"tensorflow.reset_default_graph"
]
] |
vene/seqlearn | [
"e429de64499be5e763b5d10a8e305002a50fa746"
] | [
"seqlearn/datasets/tests/test_conll.py"
] | [
"from nose.tools import assert_equal, assert_less, assert_true\nfrom numpy.testing import assert_array_equal\n\nfrom StringIO import StringIO\n\nimport scipy.sparse as sp\n\nfrom seqlearn.datasets import load_conll\n\n\nTEST_FILE = \"\"\"\n\nThe Det\ncat N\nis V\non Pre\nthe Det\n mat N\n. Punc\n\n\nReally Adv... | [
[
"numpy.testing.assert_array_equal",
"scipy.sparse.isspmatrix"
]
] |
Jimmy2027/MoPoE-MIMIC | [
"d167719b0dc7ba002b7421eb82a83e47d2437795",
"d167719b0dc7ba002b7421eb82a83e47d2437795"
] | [
"mimic/evaluation/divergence_measures/mm_div.py",
"mimic/networks/ConvNetworksTextMimic.py"
] | [
"import torch\n\nfrom mimic.evaluation.divergence_measures.kl_div import calc_entropy_gauss\nfrom mimic.evaluation.divergence_measures.kl_div import calc_kl_divergence\nfrom mimic.evaluation.divergence_measures.kl_div import calc_kl_divergence_lb_gauss_mixture\nfrom mimic.evaluation.divergence_measures.kl_div impor... | [
[
"torch.Tensor",
"torch.zeros",
"torch.sum",
"torch.exp",
"torch.log"
],
[
"torch.nn.Linear",
"torch.utils.data.DataLoader",
"torch.Tensor",
"torch.cat"
]
] |
hbrunie/tvm_ttile | [
"35de098ef637b501b96a8a4455d8deae052e0268"
] | [
"python/tvm/relay/frontend/tensorflow2.py"
] | [
"# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); y... | [
[
"tensorflow.python.framework.tensor_util.MakeNdarray",
"numpy.dtype",
"tensorflow.python.framework.dtypes.as_dtype",
"tensorflow.python.framework.function_def_to_graph.function_def_to_graph_def",
"tensorflow.python.framework.tensor_util.TensorShapeProtoToList"
]
] |
kuielab/mdx-net | [
"bbd46dbf2ceb26c3fbfbe412b5159bce2366c9c0"
] | [
"src/datamodules/musdb_datamodule.py"
] | [
"import os\nfrom os.path import exists, join\nfrom pathlib import Path\nfrom typing import Optional, Tuple\n\nfrom pytorch_lightning import LightningDataModule\nfrom torch.utils.data import ConcatDataset, DataLoader, Dataset, random_split\n\nfrom src.datamodules.datasets.musdb import MusdbTrainDataset, MusdbValidDa... | [
[
"torch.utils.data.DataLoader"
]
] |
hengwei-chan/rmsd-to-calculate-structural-difference-between-2-cmps | [
"55eebc390458307c548b45adfeb84d9f194c4344"
] | [
"tests/test_kabsch_weighted.py"
] | [
"import pathlib\n\nimport numpy as np\nfrom context import RESOURCE_PATH\n\nimport rmsd\n\n\ndef test_kabash_fit_pdb():\n\n filename_p = pathlib.PurePath(RESOURCE_PATH, \"ci2_1r+t.pdb\")\n filename_q = pathlib.PurePath(RESOURCE_PATH, \"ci2_1.pdb\")\n\n p_atoms, p_coord = rmsd.get_coordinates_pdb(filename_p... | [
[
"numpy.testing.assert_array_almost_equal"
]
] |
fjcu-ee-islab/Sideoutput_U2 | [
"dcec844e5fcb428771142d9d78ca85a4e3c4f694"
] | [
"eval_other.py"
] | [
"#!/usr/bin/env python3\r\n# *****************************************************************************\r\n# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.\r\n#\r\n# Redistribution and use in source and binary forms, with or without\r\n# modification, are permitted provided that the following c... | [
[
"torch.load",
"torch.cat",
"torch.manual_seed",
"torch.utils.data.DataLoader",
"torch.cuda.empty_cache",
"torch.no_grad",
"numpy.nanmean",
"torch.cuda.is_available",
"torch.split",
"torch.cuda.device_count",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] |
qq456cvb/KeypointNet | [
"814a9320d0bd53df47c2a655da55377f714351f2"
] | [
"benchmark_scripts/models/pointnet.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.parallel\nimport torch.utils.data\nfrom torch.autograd import Variable\nimport numpy as np\nimport torch.nn.functional as F\n\n\nclass STN3d(nn.Module):\n def __init__(self):\n super(STN3d, self).__init__()\n self.conv1 = torch.nn.Conv1d(3, 64, ... | [
[
"torch.nn.BatchNorm1d",
"torch.nn.Dropout",
"torch.max",
"torch.cat",
"numpy.eye",
"torch.eye",
"torch.nn.Sigmoid",
"torch.nn.Linear",
"torch.bmm",
"torch.rand",
"torch.nn.Conv1d",
"torch.nn.ReLU",
"numpy.array"
]
] |
andresdelarosa1887/Public-Projects | [
"db8d8e0c0f5f0f7326346462fcdfe21ce8142a12"
] | [
"OCDS API- Dominican Republic/04_tagInformation.py"
] | [
"import pandas as pd\nimport numpy as np\nimport datetime as dt\nimport concurrent.futures\nimport threading\nfrom unidecode import unidecode\n\n\n\ndef mapeo_procesos_final(): \n contratos= get_mapeo_contratosPT()\n procesos= get_mapeo_procesosPT()\n data_fortag= pd.merge(procesos, contratos, left_on='id'... | [
[
"pandas.merge",
"pandas.isna"
]
] |
ptrckhmmr/ChatBotforCulturalInstitutions | [
"c3da1a6d142e306c2e3183ba5609553e15a0e124"
] | [
"Chatbot_DebuggingVersion/app/__init__.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"This module contains the MindMeld application\"\"\"\nfrom mindmeld import Application\nfrom mindmeld.components import QuestionAnswerer\n\n# suggestions\nfrom fuzzywuzzy import process\n\n# data import\nimport pandas as pd\n\nimport os\napp_path = os.path.dirname(__file__)\n\n# setti... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
gsajko/QLD_fuel_scraping | [
"325351adc958c5e490626cd37672e07ff4b00c47"
] | [
"daily_scrape.py"
] | [
"# %%\nimport os\nfrom datetime import datetime\n\nimport pandas as pd\nimport requests\n\n# %%\n# import json\n# auth_path: str = \"config/auth.json\"\n# auth = json.load(open(auth_path))\n# TOKEN = auth[\"token\"]\nTOKEN = os.environ[\"TOKEN\"]\nfileList = os.listdir(\"data/week/\")\nweek_of_year = datetime.now()... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
Husky22/threeML | [
"2ef3401e3edf82ceffd85ad0a9ea9e8b2bba3520",
"2ef3401e3edf82ceffd85ad0a9ea9e8b2bba3520"
] | [
"threeML/minimizer/pagmo_minimizer.py",
"threeML/utils/statistics/likelihood_functions.py"
] | [
"from __future__ import print_function\nfrom builtins import range\nfrom builtins import object\nimport numpy as np\nimport os\nfrom threeML.minimizer.minimization import GlobalMinimizer\nfrom threeML.io.progress_bar import progress_bar\nfrom threeML.parallel.parallel_client import is_parallel_computation_active\n\... | [
[
"numpy.array",
"numpy.zeros"
],
[
"numpy.empty_like",
"numpy.log",
"numpy.sqrt"
]
] |
srt19/manga-ocr | [
"1eb03fd542496eeeac07deb2d88a1fa41850cd7b"
] | [
"manga_ocr_dev/synthetic_data_generator/run_generate.py"
] | [
"import traceback\nfrom pathlib import Path\n\nimport cv2\nimport fire\nimport pandas as pd\nfrom tqdm.contrib.concurrent import thread_map\n\nfrom manga_ocr_dev.env import FONTS_ROOT, DATA_SYNTHETIC_ROOT\nfrom manga_ocr_dev.synthetic_data_generator.generator import SyntheticDataGenerator\n\ngenerator = SyntheticDa... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.DataFrame"
]
] |
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