repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list | possible_versions list |
|---|---|---|---|---|---|
oldgeeksguide/tensorflow | [
"64b76357c5e9869e461575dbbad38914a8a922dd",
"64b76357c5e9869e461575dbbad38914a8a922dd"
] | [
"tensorflow/python/eager/function.py",
"tensorflow/python/ops/parallel_for/pfor.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.pywrap_tensorflow.TF_GetBuffer",
"tensorflow.python.framework.c_api_util.ScopedTFFunction",
"tensorflow.python.eager.tape.record_operation",
"tensorflow.python.util.tf_decorator.make_decorator",
"tensorflow.python.eager.tape.should_record",
"tensorflow.python.eager.conte... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"2.8",
"1.10",
"2.7",
"1.4",
"2.6",
"2.3",
"2.4",
"2.9",
"1.5",
"1.7",
"2.5",
"2.2",
"2.10"
]
},
{
"matplotlib": [],
"numpy": ... |
xiaoli-chen/courses | [
"f8d3c68ea93397bfc84fe20f92a5f296a547cb7b"
] | [
"deeplearning1/nbs/vgg16.py"
] | [
"from __future__ import division, print_function\n\nimport os, json\nfrom glob import glob\nimport numpy as np\nfrom scipy import misc, ndimage\nfrom scipy.ndimage.interpolation import zoom\n\nfrom keras import backend as K\nfrom keras.layers.normalization import BatchNormalization\nfrom keras.utils.data_utils impo... | [
[
"numpy.array",
"numpy.argmax"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
IBM/gym-constructionworld | [
"2ee21f2f069af7301e2df9659d530c237d7ce3f6"
] | [
"simulators/construct.py"
] | [
"# MIT License\n#\n# Copyright (C) IBM Corporation 2018, 2019\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated\n# documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the\n# rights to use, ... | [
[
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
muma7490/TICLE | [
"bffa64ee488abac17809d02dfc176fe80128541a"
] | [
"ticle/analysis/pdm.py"
] | [
"import numpy as np\nimport logging\nfrom multiprocessing import Pool, cpu_count\n\nlogger = logging.getLogger(__name__)\n\nNCPUS = cpu_count()\n\ndef get_frequency_grid(times,\n samplesperpeak=5,\n nyquistfactor=5,\n minfreq=None,\n ... | [
[
"numpy.isfinite",
"numpy.unique",
"numpy.arange",
"numpy.median",
"numpy.concatenate",
"numpy.ceil",
"numpy.std",
"numpy.argmin",
"numpy.floor",
"numpy.var",
"numpy.argsort",
"numpy.digitize",
"numpy.array",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
dzhurak/maskrcnn-benchmark | [
"d3adae1ffae3d40e58516d53ce6b5af4e8cfc9d3"
] | [
"maskrcnn_benchmark/modeling/rpn/loss.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\n\"\"\"\nThis file contains specific functions for computing losses on the RPN\nfile\n\"\"\"\n\nimport torch\nfrom torch.nn import functional as F\n\nfrom ..balanced_positive_negative_sampler import BalancedPositiveNegativeSampler\nfrom ..util... | [
[
"torch.nn.functional.binary_cross_entropy_with_logits",
"torch.cat"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
DataCanvasIO/tabular-toolbox | [
"c456a2716aaefbba5173f0886be4f9f4487f36a5"
] | [
"tabular_toolbox/tests/data_cleaner_test.py"
] | [
"# -*- coding:utf-8 -*-\n__author__ = 'yangjian'\n\"\"\"\n\n\"\"\"\n\nimport io\n\nimport numpy as np\nimport pandas as pd\nfrom numpy import dtype\nfrom dask import dataframe as dd\n\nfrom tabular_toolbox.data_cleaner import DataCleaner\n\ncsv_str = '''x1_int_nanchar,x2_all_nan,x3_const_str,x4_const_int,x5_dup_1,x... | [
[
"numpy.dtype"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
nzw0301/gpytorch | [
"498a4bc8b9637940577852bb9d529c346c6e9363"
] | [
"gpytorch/optim/ngd.py"
] | [
"#!/usr/bin/env python3\n\nfrom typing import Iterable, Union\n\nimport torch\n\n\nclass NGD(torch.optim.Optimizer):\n r\"\"\"Implements a natural gradient descent step.\n It **can only** be used in conjunction with a :obj:`~gpytorch.variational._NaturalVariationalDistribution`.\n\n Nesterov momentum is ba... | [
[
"torch.no_grad"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
anyoptimization/ezmodel | [
"c6c8779066921359f821963a1e10a98b54f5ac98"
] | [
"tests/test_partitioning.py"
] | [
"import numpy as np\n\nfrom ezmodel.util.partitioning.crossvalidation import CrossvalidationPartitioning\nfrom ezmodel.util.partitioning.random import RandomPartitioning\n\n\ndef test_random_selection():\n X = np.random.random((10000, 1))\n partitions = RandomPartitioning(perc_train=0.01, n_sets=5).do(X)\n\n ... | [
[
"numpy.random.random"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
josephlee222/py-project | [
"affe4e9bbdeeadb1cc96224ed4c2118aa0b6bc6e"
] | [
"grp1_ASP_Project.py"
] | [
"import pandas as pd\nimport matplotlib.pyplot as plt\n\nclass findCountries:\n data = pd.ExcelFile('IMVA.xls')\n df = pd.read_excel(data, 'Sheet1')\n start_year = 1978\n end_year = 1987\n countries = [\"Brunei Darussalam\", \"Indonesia\", \"Malaysia\", \"Myanmar\", \"Philippines\", \"Thailand\", \"V... | [
[
"pandas.read_excel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.gcf",
"pandas.ExcelFile",
"pandas.DataFrame.from_dict",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
emmamcbryde/summer | [
"129176507646f45c054f7bac03628799b06de055"
] | [
"summer_py/parameter_processing.py"
] | [
"import numpy\nfrom scipy.integrate import quad\nfrom summer_py.summer_model import order_dict_by_keys, add_zero_to_age_breakpoints\nfrom copy import copy\n\n\n\"\"\"\npallettes of functions that may be useful for creating parameter values to submit to the SUMMER module\n\"\"\"\n\n\ndef change_parameter_unit(parame... | [
[
"scipy.integrate.quad",
"numpy.exp",
"numpy.cos"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
"1.6",
"1.4",
"1.9",
"1.3",
"1.10",
"0.15",
"0.18",
"0.16"... |
TomasBeuzen/pyguest | [
"a3bef9b7303ff594096fe4bca70ae48cce0bb7b6"
] | [
"tests/test_pyguest.py"
] | [
"import pyguest\nimport numpy as np\n\n\ndef test_simulate():\n np.random.seed(2020)\n x = list(np.random.randint(0, 11, 100) / 10)\n y = pyguest.simulate(x)\n assert y.mean() == 49.47\n assert y.shape[0] == 100\n"
] | [
[
"numpy.random.seed",
"numpy.random.randint"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
arthurprevot/yaetos | [
"5eba59538f8e53c3d7033b0af80a25828c24a43e"
] | [
"yaetos/libs/analysis_toolkit/query_helper.py"
] | [
"import pandas as pd\nimport numpy as np\nimport os\nfrom time import time\nimport hashlib\n\n\ndef query_and_cache(query_str, name, folder, to_csv_args={}, dbargs={}, db_type='oracle', force_rerun=False, show=False):\n (name, fname_base, fname_csv, fname_pykl, fname_sql) = filename_expansion(name, folder)\n ... | [
[
"pandas.merge",
"pandas.util.hash_pandas_object",
"numpy.seterr",
"pandas.isna",
"pandas.read_pickle"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"0.24",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
smsaladi/bebi103_utils | [
"a13fc62efcd695b73dad3ce4941eea28b3c4120d"
] | [
"bebi103/emcee.py"
] | [
"import collections\nimport warnings\n\nimport numpy as np\nimport pandas as pd\n\nimport emcee\nimport ptemcee\n\ndef generic_log_posterior(log_prior, log_likelihood, params, logpargs=(),\n loglargs=()):\n \"\"\"\n Generic log posterior for MCMC calculations\n\n Parameters\n --... | [
[
"pandas.DataFrame",
"numpy.ones",
"numpy.concatenate",
"numpy.diff",
"numpy.any",
"numpy.empty"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
priyaramani/pytorch | [
"a6f767ed3d66b4a01e5b2edead8491dfbca517e6"
] | [
"test/quantization/fx/test_quantize_fx.py"
] | [
"import os\nimport torch\nimport torch.nn.functional as F\nimport torch.nn as nn\nimport torch.nn.quantized as nnq\nimport torch.nn.quantized.dynamic as nnqd\nimport torch.nn.intrinsic as nni\nimport torch.nn.intrinsic.quantized as nniq\nimport torch.multiprocessing as mp\n\n# graph mode quantization based on fx\nf... | [
[
"torch.randint",
"torch.max",
"torch.zeros",
"torch.nn.functional.dropout",
"torch.quantization.FakeQuantize.with_args",
"torch.device",
"torch.testing._internal.common_quantized.override_quantized_engine",
"torch.nn.EmbeddingBag",
"torch.quantization.prepare",
"torch.randn... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
jrmejansen/scipy | [
"77f4f5172f8e718de96b89bf3f015a8729a7613c"
] | [
"DDEs_models_test/gurney.py"
] | [
"from scipy.integrate import solve_dde\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom scipy.interpolate import CubicHermiteSpline\nfrom jitcdde import jitcdde\nfrom jitcdde import y as y_jit\nfrom jitcdde import t as t_jit\n\n\"\"\"\nThe revisited blowflies problem (from Gurney 1980, \nNicholson's blowf... | [
[
"matplotlib.pyplot.legend",
"scipy.integrate.solve_dde",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"numpy.exp",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ctava/CapsNet-Tensorflow | [
"69f049b92dd5f409ac4a26107a8af640f6c99652"
] | [
"capsNet.py"
] | [
"\"\"\"\nLicense: Apache-2.0\nAuthor: Huadong Liao\nE-mail: naturomics.liao@gmail.com\n\"\"\"\n\nimport tensorflow as tf\n\nfrom config import cfg\nfrom utils import get_batch_data\nfrom utils import softmax\nfrom utils import reduce_sum\nfrom capsLayer import CapsLayer\n\n\nepsilon = 1e-9\n\n\nclass CapsNet(object... | [
[
"tensorflow.concat",
"tensorflow.reduce_sum",
"tensorflow.cast",
"tensorflow.train.AdamOptimizer",
"tensorflow.to_int32",
"tensorflow.summary.scalar",
"tensorflow.Graph",
"tensorflow.Variable",
"tensorflow.summary.image",
"tensorflow.squeeze",
"tensorflow.square",
"... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
EPAENERGYSTAR/epathermostat | [
"98aaf571fe8e15e1a372567776081fd9dae7e872",
"98aaf571fe8e15e1a372567776081fd9dae7e872"
] | [
"tests/test_metrics.py",
"tests/test_stats.py"
] | [
"from thermostat.exporters import metrics_to_csv\nfrom thermostat.multiple import multiple_thermostat_calculate_epa_field_savings_metrics\n\nimport pandas as pd\nimport numpy as np\nfrom numpy.testing import assert_allclose\n\nimport tempfile\n\nimport pytest\n\nfrom .fixtures.thermostats import thermostat_type_1\n... | [
[
"numpy.testing.assert_allclose"
],
[
"pandas.read_csv",
"numpy.isnan",
"pandas.DataFrame",
"scipy.stats.norm.rvs",
"scipy.stats.randint.rvs"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
CheerfulUser/tesstpfreduction | [
"dee13fdbec16e41ca73d18fffdbf8eb8cbee65d4",
"dee13fdbec16e41ca73d18fffdbf8eb8cbee65d4"
] | [
"tessreduce/tessreduce.py",
"tessreduce/calibration_tools.py"
] | [
"\"\"\"\nImport packages!\n\"\"\"\nimport os\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nimport lightkurve as lk\n\nfrom copy import deepcopy\n\nfrom scipy.ndimage.filters import convolve\nfrom scipy.ndimage import shift\nfrom scipy.ndimage import gaussian_filter\nfrom scipy.ndimage... | [
[
"numpy.nanmax",
"matplotlib.pyplot.legend",
"numpy.nanmedian",
"numpy.sqrt",
"matplotlib.pyplot.MaxNLocator",
"numpy.nanmin",
"matplotlib.pyplot.plot",
"numpy.round",
"numpy.nanargmin",
"numpy.zeros_like",
"sklearn.cluster.OPTICS",
"numpy.argmin",
"numpy.average... | [
{
"matplotlib": [],
"numpy": [
"1.10",
"1.12",
"1.11",
"1.19",
"1.13",
"1.16",
"1.9",
"1.18",
"1.20",
"1.7",
"1.15",
"1.14",
"1.17",
"1.8"
],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2... |
simplezhang57/QUANTAXIS | [
"0fab23ee3cc4048a30b5eed3c311a5c9cdce8110"
] | [
"QUANTAXIS/QAFetch/QAQuery_Advance.py"
] | [
"# coding: utf-8\n#\n# The MIT License (MIT)\n#\n# Copyright (c) 2016-2018 yutiansut/QUANTAXIS\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 witho... | [
[
"pandas.to_datetime",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
maru-n/alife_book_src | [
"13b4502ad42b12f543d2ed42588596de1540f1ba"
] | [
"chap02/gray_scott.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport sys, os\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\nfrom alifebook_lib.visualizers import MatrixVisualizer\n\n# visualizerの初期化 (Appendix参照)\nvisualizer = MatrixVisualizer()\n\n# シミュレーションの各パラメタ\nSPACE_GRID_SIZE = 256\ndx = 0.... | [
[
"numpy.roll",
"numpy.zeros",
"numpy.random.rand",
"numpy.ones"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
dougscohen/DS-Unit-3-Sprint-1-Software-Engineering | [
"9618aaa2913a4c10a064d346320e69d09483e31b"
] | [
"module2-oop-code-style-and-reviews/Assignment/dc_lambdata/mod2.py"
] | [
"# dc_lambdata\\mod2.py\n\nimport pandas as pd\n\n\ndef split_date(df):\n \"\"\"\n Creates 3 new columns with year, month, and day\n\n Params: dataframe with column called \"date\" which has the date in the\n format \"MM/DD/YYYY\"\n \"\"\"\n\n df = df.copy()\n df['date'] = pd.to_datetime(df['da... | [
[
"pandas.to_datetime",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
kinnala/pymor | [
"9d2a8ee5f7a71482e62952257332d269d50678e9"
] | [
"src/pymor/models/neural_network.py"
] | [
"# This file is part of the pyMOR project (https://www.pymor.org).\n# Copyright pyMOR developers and contributors. All rights reserved.\n# License: BSD 2-Clause License (https://opensource.org/licenses/BSD-2-Clause)\n\n\"\"\"Remark on the documentation:\n\nDue to an issue in autoapi, the classes `NeuralNetworkState... | [
[
"torch.nn.ModuleList",
"numpy.linspace"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
YasserZhang/emotion-detection-in-dialogues | [
"783cc0a360a880f48fcb516cf93a27e9d74f5295"
] | [
"vanilla/cnn.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Sun Apr 1 13:04:09 2018\r\n\r\n@author: flyin\r\n\"\"\"\r\n\r\nimport tensorflow as tf\r\n\r\nclass TextCNN:\r\n def __init__(self, sequence_length, num_classes, vocab_size,\r\n embedding_size, filter_sizes, num_filters, l2_reg_lambda=0.0):\r\n ... | [
[
"tensorflow.device",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.concat",
"tensorflow.nn.max_pool",
"tensorflow.cast",
"tensorflow.nn.l2_loss",
"tensorflow.nn.conv2d",
"tensorflow.name_scope",
"tensorflow.argmax",
"tensorflow.nn.dropout",
"tensorflow.... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
hummat/DISN | [
"b48a9c31d54211681996faaf9fca996be703ff84"
] | [
"test/create_sdf.py"
] | [
"import argparse\nimport os\nimport random\nimport socket\nimport struct\nimport sys\nfrom datetime import datetime\n\nimport h5py\nimport numpy as np\nimport tensorflow as tf\n\nBASE_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))\nsys.path.append(BASE_DIR) # model\nsys.path.append... | [
[
"tensorflow.train.get_checkpoint_state",
"numpy.swapaxes",
"numpy.expand_dims",
"tensorflow.Variable",
"numpy.linspace",
"tensorflow.get_collection_ref",
"numpy.meshgrid",
"tensorflow.placeholder",
"tensorflow.ConfigProto",
"numpy.ceil",
"tensorflow.global_variables_ini... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"1.12",
"1.4",
"1.13",
"1.5",
"1.7",
"0.12",
"1.0",
"1.2"
]
}
] |
cottrell/tf-quant-finance | [
"5aba5ddab3a4dd1efa87d5a12fec403315d2ac98"
] | [
"tf_quant_finance/math/pde/grids/grids_test.py"
] | [
"# Copyright 2019 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.log",
"tensorflow.constant",
"numpy.linspace",
"numpy.meshgrid",
"numpy.squeeze",
"tensorflow.test.main",
"numpy.testing.assert_almost_equal",
"numpy.exp",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
iverxin/Paddle | [
"2b8fd704d0ec555b5b27d50fca261741a7fbbf28"
] | [
"python/paddle/fluid/tests/unittests/test_seed_op.py"
] | [
"# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless ... | [
[
"numpy.asarray"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
pkuyym/Paddle | [
"728621e57b98c8b36e1c118e1d0f9cd51a3baafb"
] | [
"python/paddle/fluid/tests/unittests/test_dist_train.py"
] | [
"# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless ... | [
[
"numpy.allclose"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
NwekeChidi/Flask_Dog_Breed_Classifier_App | [
"73e51b5f4601fda2e1289a933c2d3216cf89073b"
] | [
"transformers.py"
] | [
"# Importing Libraries\r\nimport torch\r\nimport numpy\r\n\r\n# Defining the transforms\r\nclass ToTensor(object):\r\n\r\n def __call__(self, image):\r\n # imagem numpy: C x H x W\r\n # imagem torch: C X H X W\r\n \r\n image = image.transpose((0, 1, 2))\r\n retu... | [
[
"torch.from_numpy"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
cmitash/bin_packing_simulation | [
"09a96a32e21d5e8ddb0d626ad765bfd550318bbe"
] | [
"Label.py"
] | [
"import cv2\nfrom PIL import Image, ImageDraw\nimport os.path as osp\nimport os\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport random\nimport OpenEXR, Imath\nimport open3d as o3d\nimport matplotlib.pyplot as plt\nfrom mathutils import Vector, Matrix, Quaternion\n\nclass Label:\n def draw_bboxes(sel... | [
[
"numpy.nonzero",
"numpy.uint8",
"numpy.ones",
"numpy.max",
"numpy.fromstring",
"numpy.zeros",
"numpy.hypot"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Richardhongyu/attack_code | [
"b331b3a9a47bd70578842db5df0535620b9ed367"
] | [
"random_generate.py"
] | [
"import random\nimport numpy as np\ndef Random_Attack(pixel_count):\n random_attack_results=[]\n for i in range(pixel_count):\n x = random.randint(0,27)\n y = random.randint(0,27)\n grey_value = random.randint(0,255)\n random_attack_results.append(x)\n ... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
HYUNMIN-HWANG/fairseq | [
"8094376456f586f119ffe5b83d7af5979066197d"
] | [
"examples/data2vec/models/data2vec_audio.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport logging\nimport math\nfrom dataclasses import dataclass, field\nfrom typing import Optional\n\nfrom omegaconf import II\n\nim... | [
[
"torch.nn.Dropout",
"torch.floor",
"torch.zeros",
"torch.sqrt",
"torch.distributed.is_initialized",
"torch.from_numpy",
"torch.nn.Linear",
"torch.no_grad",
"torch.FloatTensor",
"torch.arange",
"torch.distributed.all_reduce"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
dallaval5u/COMET | [
"8c5793faafe2797dd4100507aa0fe1e71cf9f6c0"
] | [
"COMET/measurement_plugins/QTCTESTSYSTEM.py"
] | [
"# This file conducts a full test on the KIT Test Card nearly automatically\n\nimport logging\nimport sys\n\nsys.path.append(\"../COMET\")\nfrom time import time, sleep\nimport time\nfrom ..utilities import transformation, force_plot_update\nfrom .forge_tools import tools\nimport numpy as np\n\n\nclass QTCTESTSYSTE... | [
[
"numpy.random.normal",
"numpy.array",
"numpy.zeros",
"numpy.mean"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Data-to-Knowledge/water-use-advice | [
"b0541f47ee6bf2aff4774a6c9fdcb034aa74586e"
] | [
"2020-09-15/CRC020199.1.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Jul 2 09:25:41 2019\n\n@author: michaelek\n\"\"\"\nimport os\nimport pandas as pd\nfrom pdsql import mssql\nfrom matplotlib.pyplot import show\n\npd.options.display.max_columns = 10\n\ndate_col = 'Date_Time_Readings'\n\noutput_path = r'C:\\ecan\\git\\water-use-advic... | [
[
"pandas.to_datetime",
"matplotlib.pyplot.show"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
mac-wang/DEGBM | [
"55dd37b87edc0922d617dd9ddc1cf4553a807c84",
"55dd37b87edc0922d617dd9ddc1cf4553a807c84"
] | [
"kdd99/train.py",
"talking data/test.py"
] | [
"import os\nimport time\nimport pickle\nimport numpy as np\nimport tensorflow as tf\nimport sys\nfrom build_dataset import build_dataset\nfrom model import BiWGAN\nfrom utils import DataInput, calc_metric, calc_auc, create_logdir, _shuffle\n\n\n# hyper parameters\nbase_dir = os.path.dirname(os.path.realpath(__file_... | [
[
"tensorflow.global_variables_initializer",
"numpy.array",
"tensorflow.local_variables_initializer",
"tensorflow.Session"
],
[
"tensorflow.local_variables_initializer",
"numpy.concatenate",
"tensorflow.global_variables_initializer",
"tensorflow.Session",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"1.12",
"1.4",
"1.13",
"1.5",
"1.7",
"0.12",
"1.0",
"1.2"
]
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensor... |
deeplearning-project/pytorch-YOLOv4 | [
"75b27f4df2a1f21d16ce4a87c00ac09e6d948838"
] | [
"tool/torch_utils.py"
] | [
"import sys\nimport os\nimport time\nimport math\nimport torch\nimport numpy as np\nfrom PIL import Image, ImageDraw, ImageFont\nfrom torch.autograd import Variable\n\nimport itertools\nimport struct # get_image_size\nimport imghdr # get_image_size\n\nfrom tool import utils \n\n\ndef bbox_ious(boxes1, boxes2, x1y... | [
[
"torch.nn.Softmax",
"torch.sigmoid",
"torch.max",
"numpy.linspace",
"torch.cat",
"torch.min",
"torch.tensor",
"torch.exp",
"torch.sort",
"torch.autograd.Variable"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
PPiacek/Class-5---Homework | [
"54a2637e690afaad9728b794c2063950a97a858f"
] | [
"dataset-processor.py"
] | [
"import pandas as pd\nimport os\nimport matplotlib.pyplot as plt\n\n# Creating Dataframe from Files\nhousing_df = pd.read_csv(filepath_or_buffer='~/Desktop/housing.csv',\n sep='\\s+',\n header=None)\n\n#Adding Header\nhousing_df.columns = ['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX'... | [
[
"pandas.read_csv",
"matplotlib.pyplot.title",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.close",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylabel"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
naykun/guided-diffusion | [
"dab7b2b4240db9b41c1b0518eac6bd92e4e1f832"
] | [
"guided_diffusion/dist_util.py"
] | [
"\"\"\"\nHelpers for distributed training.\n\"\"\"\n\nimport io\nimport os\nimport socket\n\nimport blobfile as bf\nfrom mpi4py import MPI\nimport torch as th\nimport torch.distributed as dist\n\n# Change this to reflect your cluster layout.\n# The GPU for a given rank is (rank % GPUS_PER_NODE).\nGPUS_PER_NODE = 16... | [
[
"torch.distributed.broadcast",
"torch.distributed.init_process_group",
"torch.load",
"torch.distributed.is_initialized",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
itec-hust/MusicYOLO | [
"d980a0c0a3723a6c25772c2f7150a82baa1a4ec3"
] | [
"tools/train.py"
] | [
"#!/usr/bin/env python3\r\n# -*- coding:utf-8 -*-\r\n# Copyright (c) Megvii, Inc. and its affiliates.\r\n\r\nimport argparse\r\nimport os\r\nimport random\r\nimport warnings\r\nfrom loguru import logger\r\n\r\nimport torch\r\nimport torch.backends.cudnn as cudnn\r\n\r\nfrom yolox.core import Trainer, launch\r\nfrom... | [
[
"torch.cuda.FloatTensor",
"torch.manual_seed",
"torch.cuda.device_count"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mhardcastle/reproject | [
"4746c7897240013b8805030c898b29f3a090349f"
] | [
"reproject/tests/test_utils.py"
] | [
"import numpy as np\n\nfrom astropy.tests.helper import pytest\nfrom astropy.coordinates import FK5, Galactic, ICRS\nfrom astropy.io import fits\nfrom astropy.wcs import WCS\nfrom astropy.utils.data import get_pkg_data_filename\n\nfrom ..utils import parse_input_data, parse_output_projection\n\n\ndef test_parse_inp... | [
[
"numpy.arange",
"numpy.testing.assert_allclose"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
zitkat/bag-of-local-features-models | [
"0e38d26cf6e082baf4de89d0cdfece6ba15573eb"
] | [
"bagnets/pytorchnet.py"
] | [
"import torch.nn as nn\nimport math\nimport torch\nfrom collections import OrderedDict\nfrom torch.utils import model_zoo\n\nimport os \ndir_path = os.path.dirname(os.path.realpath(__file__))\n\n__all__ = ['bagnet9', 'bagnet17', 'bagnet33']\n\nmodel_urls = {\n 'bagnet9': 'https://bitbucket.org/wielandbre... | [
[
"torch.nn.Sequential",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.utils.model_zoo.load_url"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
binglel/mnist_bp | [
"3ce345558a5dd7a10014915c5b451585299fc829"
] | [
"train.py"
] | [
"# encoding: utf-8\n# ******************************************************\n# requirement:python3\n# Author: chyb\n# Last modified: 20181023 14:00\n# Email:chyb3.14@gmail.com\n# Filename:train.py\n# Description:\n# ******************************************************\nimport numpy as np\nimport math\nfrom input... | [
[
"numpy.dot",
"numpy.random.random",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"numpy.argmax",
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
kenoss/HandyRL | [
"5f132d382f551eea08e6c2387251f99943eab779"
] | [
"handyrl/evaluation.py"
] | [
"# Copyright (c) 2020 DeNA Co., Ltd.\n# Licensed under The MIT License [see LICENSE for details]\n\n# evaluation of policies or planning algorithms\n\nimport random\nimport time\nimport multiprocessing as mp\n\nimport numpy as np\n\nfrom .environment import prepare_env, make_env\nfrom .connection import send_recv, ... | [
[
"numpy.ones_like",
"numpy.mean",
"torch.load"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
IouJenLiu/HTS-RL | [
"7972340c765ef45d2bda353a197b78e0b844f2bd"
] | [
"a2c_ppo_acktr/storage_ma.py"
] | [
"import torch\nfrom torch.utils.data.sampler import BatchSampler, SubsetRandomSampler\nfrom a2c_ppo_acktr.storage import RolloutStorage\nimport time\n\n\ndef _flatten_helper(T, N, _tensor):\n return _tensor.view(T * N, *_tensor.size()[2:])\n\n\nclass RolloutStorageMA(object):\n def __init__(self, num_steps, n... | [
[
"torch.ones",
"torch.zeros",
"torch.randperm",
"torch.cat",
"torch.narrow",
"torch.stack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
alexsah-ece/avt-2019 | [
"4015ac11599fc4216dde04c9c791af2646df087c"
] | [
"AdvancedEAST/predict.py"
] | [
"import argparse\n\nimport numpy as np\nfrom PIL import Image, ImageDraw\nfrom keras.preprocessing import image\nfrom keras.applications.vgg16 import preprocess_input\n\nimport cfg\n\nfrom label import point_inside_of_quad\nfrom network import East\nfrom preprocess import resize_image\nfrom nms import nms\n\n\ndef ... | [
[
"numpy.amax",
"numpy.expand_dims",
"numpy.amin",
"numpy.reshape",
"numpy.squeeze",
"numpy.greater_equal",
"numpy.exp",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ehsanfar/Network_Auctioneer | [
"802f10b27d4f6f5fd9d5434f30814f2175236479"
] | [
"resources/auction.py"
] | [
"\"\"\"\nCopyright 2018, Abbas Ehsanfar, Stevens Institute of Technology\nLicensed 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 Unle... | [
[
"numpy.mean"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
liisaratsep/nmt_service | [
"51b0d1aa1e115ceb72f5fdb07fe8b6d08eacf431"
] | [
"interface.py"
] | [
"import logging\nimport copy\nfrom typing import Dict, List, Iterator, Any, Optional\n\nfrom fairseq.data import Dictionary, LanguagePairDataset, FairseqDataset\nfrom fairseq import utils, search, hub_utils\nfrom fairseq.models.multilingual_transformer import MultilingualTransformerModel\nfrom fairseq.tasks.multili... | [
[
"torch.nn.ModuleList",
"torch.tensor"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
rodney-wang/deeplab-pytorch | [
"cfb586ba220603031aefab005cc90ef799b32c84"
] | [
"draw_model.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n#\n# Author: Kazuto Nakashima\n# URL: http://kazuto1011.github.io\n# Created: 2017-11-06\n\nimport torch\nimport yaml\nfrom tensorboardX import SummaryWriter\nfrom torch.autograd import Variable\n\nfrom libs.models import *\n\ninput = torch.randn(1, 3, 513, 513).cuda... | [
[
"torch.randn"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
sparsh-ai/recsys-colab | [
"c0aa0dceca5a4d8ecd42b61c4e906035fe1614f3"
] | [
"data/preprocess_retailrocket.py"
] | [
"import numpy as np\nimport pandas as pd\nfrom datetime import datetime, timezone, timedelta\n\n#data config (all methods)\nDATA_PATH = '../data/retailrocket/raw/'\nDATA_PATH_PROCESSED = '../data/retailrocket/prepared/'\nDATA_FILE = 'events'\nSESSION_LENGTH = 30 * 60 #30 minutes\n\n#filtering config (all methods)\n... | [
[
"numpy.in1d",
"pandas.read_csv",
"pandas.to_datetime"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
devinbalkind/greppo | [
"817644fa5328259d6a0141c781db22dbb9f0650f"
] | [
"library/src/greppo/layers/vector_layer.py"
] | [
"from dataclasses import dataclass\nfrom typing import List, Union\nimport uuid\nfrom click import style\nfrom geopandas import GeoDataFrame as gdf\nfrom numpy import arange\nfrom ..colorbrewer import get_palette\n\n\n@dataclass\nclass VectorLayerComponent:\n def __init__(\n self,\n data: gdf,\n ... | [
[
"numpy.arange"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
koulakis/stable-baselines3 | [
"08e7519381e800edc6bbd09577f14381b7341873"
] | [
"stable_baselines3/dqn/dqn.py"
] | [
"from typing import List, Tuple, Type, Union, Callable, Optional, Dict, Any\n\nimport numpy as np\nimport torch as th\nimport torch.nn.functional as F\n\nfrom stable_baselines3.common import logger\nfrom stable_baselines3.common.off_policy_algorithm import OffPolicyAlgorithm\nfrom stable_baselines3.common.type_alia... | [
[
"torch.no_grad",
"numpy.random.rand",
"torch.nn.functional.smooth_l1_loss"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
MishaLaskin/dm_control | [
"846e4b6e87448d17d006f9fc159ce20406f051a5"
] | [
"dm_control/rl/specs_test.py"
] | [
"# Copyright 2017 The dm_control Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
yangece/thrive | [
"483ede1dd9d4629674e5621ff47aef7d4c1ce06f"
] | [
"algorithms/CellDIVE_Seg.py"
] | [
"import numpy as np\nimport os\nimport cv2\nimport json\nimport pickle\nfrom learning_helpers import Traditional_ML\nimport subprocess\n\n\n\nclass CellDIVESeg:\n def __init__(self):\n self.tissueSegModel = None\n self.DLFeats = False\n self.learningMethod = Traditional_ML()\n\n\n def loa... | [
[
"numpy.unique",
"scipy.ndimage.distance_transform_edt",
"numpy.ones",
"numpy.concatenate",
"scipy.ndimage.label",
"numpy.max",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
"1.6",
"1.4",
"1.9",
"1.3",
"1.10",
"0.15",
"0.18",
"0.16"... |
NeoExtended/gym-gathering | [
"71a75eab5d08e9705f5e5dd491b6d97ba0ffdf4b"
] | [
"gym_gathering/steps/basic_modifiers.py"
] | [
"from typing import Dict, Tuple\n\nimport numpy as np\n\nfrom gym_gathering.steps.base_step_modifier import StepModifier\n\n\nclass SimpleMovementModifier(StepModifier):\n def _step(\n self, action: int, locations: np.ndarray, update: np.ndarray\n ) -> np.ndarray:\n dy, dx = self.action_map[acti... | [
[
"numpy.array",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
gbodra/bovespa-recommendations | [
"c45a198bd5e24a99a1937d69f456aabdb64d00c9"
] | [
"tf-stock-prediction.py"
] | [
"from __future__ import absolute_import, division, print_function\nimport sys\nimport pathlib\nimport pandas as pd\nimport seaborn as sns\nimport tensorflow as tf\nfrom tensorflow import keras\nfrom tensorflow.keras import layers\nimport matplotlib.pyplot as plt\n\ncolspecs = [(2,10),(12,24),(56,69),(108,121)]\n\nn... | [
[
"pandas.concat",
"pandas.to_datetime",
"pandas.read_fwf",
"tensorflow.train.RMSPropOptimizer",
"tensorflow.keras.layers.Dense",
"pandas.DataFrame",
"tensorflow.keras.callbacks.EarlyStopping"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
roy881020/v-coco | [
"f41b55139d0ec23b76c1934d51bffddb9289fe09"
] | [
"vsrl_utils.py"
] | [
"# AUTORIGHTS\n# ---------------------------------------------------------\n# Copyright (c) 2016, Saurabh Gupta\n# \n# This file is part of the VCOCO dataset hooks and is available \n# under the terms of the Simplified BSD License provided in \n# LICENSE. Please retain this notice and LICENSE if you use \n# this fi... | [
[
"numpy.unique",
"numpy.ones",
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
chrishhx/Course_ComplexDataAnalyse | [
"fc34ef471b9daadce1f6ea760c5a3e8fd2b6aa19",
"fc34ef471b9daadce1f6ea760c5a3e8fd2b6aa19"
] | [
"Bighw/project/SingleTrial_Hetero.py",
"Bighw/project/MultiTrial_Hetero.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Sun Dec 24 08:51:24 2017\r\n\r\n@author: chris\r\n\"\"\"\r\nimport os\r\nos.chdir(\"E:\\\\workspace\\\\project\")\r\n\r\nfrom mymodule.GMM import GMM\r\nimport numpy as np\r\nfrom scipy import stats\r\nfrom matplotlib import pyplot as plt\r\n\r\ndef mixture(x,p,mu,si... | [
[
"numpy.random.seed",
"matplotlib.pyplot.scatter",
"numpy.random.multivariate_normal",
"matplotlib.pyplot.figure",
"numpy.random.multinomial",
"matplotlib.pyplot.contour",
"scipy.stats.multivariate_normal.pdf"
],
[
"numpy.random.multivariate_normal",
"numpy.random.multinomia... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
senti-ESES/ESES | [
"c95523a10710978f8d25d0199ee69108b91094fd",
"c95523a10710978f8d25d0199ee69108b91094fd"
] | [
"code/SEntiMoji_script/DeepMoji/deepmoji/filter_utils.py",
"code/SEntiMoji_script/DeepMoji/deepmoji/sentence_tokenizer.py"
] | [
"\nfrom __future__ import print_function, division\nimport sys\nimport numpy as np\nimport re\nimport string\nimport emoji\nfrom tokenizer import RE_MENTION, RE_URL\nfrom global_variables import SPECIAL_TOKENS\nfrom itertools import groupby\n\nAtMentionRegex = re.compile(RE_MENTION)\nurlRegex = re.compile(RE_URL)\n... | [
[
"numpy.load"
],
[
"sklearn.model_selection.train_test_split",
"numpy.ones",
"numpy.iinfo",
"numpy.count_nonzero",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
tingofurro/summac | [
"53fae37bbdd3995c50b50a2713d196680966c765"
] | [
"train_summac.py"
] | [
"import utils_misc\n\nutils_misc.select_freer_gpu()\nimport torch, tqdm, nltk, numpy as np, argparse, json\nfrom torch.utils.data import DataLoader, RandomSampler\nimport utils_optim, os, time\nfrom utils_summac_benchmark import SummaCBenchmark, load_factcc\nfrom model_summac import SummaCConv, model_map\n\ndef tra... | [
[
"torch.LongTensor",
"torch.nn.CrossEntropyLoss",
"numpy.array",
"torch.utils.data.RandomSampler"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
wesleyhuang2014/benchmarks | [
"fe410cb77e9d7956226b16dc72ed5a75bd456dfc",
"fe410cb77e9d7956226b16dc72ed5a75bd456dfc"
] | [
"scripts/tf_cnn_benchmarks/benchmark_cnn.py",
"scripts/tf_cnn_benchmarks/ssd_dataloader.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.convert_to_tensor",
"tensorflow.control_dependencies",
"tensorflow.reduce_sum",
"tensorflow.python.client.timeline.Timeline",
"tensorflow.train.get_global_step",
"tensorflow.train.get_or_create_global_step",
"tensorflow.FIFOQueue",
"numpy.median",
"numpy.array",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.13",
"1.12"
]
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
ReykCS/navrep | [
"22ee4727268188414a8121f069e45c2ab798ca19",
"22ee4727268188414a8121f069e45c2ab798ca19"
] | [
"navrep/scripts/check_imrnn.py",
"navrep/envs/rosnavtrainencodedenv.py"
] | [
"from __future__ import print_function\nimport numpy as np\nimport os\n\nfrom navrep.models.rnn import reset_graph, sample_hps_params, MDNRNN, get_pi_idx\nfrom navrep.models.vae2d import ConvVAE\n\n# parameters\nTEMPERATURE = 0.5\n_Z = 32\n\nsequence_z_path = os.path.expanduser(\n \"~/navrep/datasets/M/im/corrid... | [
[
"numpy.sqrt",
"numpy.reshape",
"matplotlib.pyplot.subplots",
"numpy.copy",
"matplotlib.pyplot.clf",
"numpy.random.randn",
"numpy.random.rand",
"numpy.load",
"numpy.array",
"numpy.exp",
"numpy.zeros",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.ion",
"matpl... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
lynnbwilsoniii/Wind_Decom_Code | [
"ef596644fe0ed3df5ff3b462602e7550a04323e2"
] | [
"Wind_SMS_software/MFI_data/read_wind_mfi_w_orbit_data.py"
] | [
"''' \r\nThis script will read in the Wind MFI data w/ orbital information\r\n\r\n'''\r\n\r\n#import the requisite library modules\r\nimport numpy as np\r\nimport pandas as pd\r\nimport time as tm\r\nimport matplotlib\r\nimport matplotlib.pyplot as plt\r\nimport os\r\nimport glob\r\nimport datetime\r\nimport calend... | [
[
"numpy.loadtxt",
"matplotlib.mlab.rec_append_fields",
"numpy.dtype"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ericmjl/nxviz | [
"e338a1de5e94f08009297ac06907d37729828e7b"
] | [
"nxviz/api.py"
] | [
"\"\"\"High level nxviz plotting API.\"\"\"\n\n\nfrom functools import partial, update_wrapper\nfrom typing import Callable, Dict, Hashable\n\nimport matplotlib.pyplot as plt\nimport networkx as nx\nimport numpy as np\n\nfrom nxviz import edges, nodes\nfrom nxviz.plots import aspect_equal, despine\n\n# This docstri... | [
[
"matplotlib.pyplot.gca",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
danielsto/nba-talent-scraper | [
"3b1e417b2b35059aa5af9e63976ffb9a8613e1ca"
] | [
"tests/test_scraper.py"
] | [
"import src.scraper as scraper\r\nimport pandas as pd\r\n\r\n\r\nclass TestRetrieveData:\r\n \"\"\"Test the retrieve_data function\"\"\"\r\n\r\n def test_retrieve_data_league_options(self):\r\n \"\"\"Test league options only retrieves indicated league\"\"\"\r\n res = scraper.retrieve_data_league... | [
[
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
ksackvil/NeuralNarrator | [
"257ab8bc23e54242a8c6d66cd88ccb093bc01ed3"
] | [
"word-rnn-tf/sample.py"
] | [
"from __future__ import print_function\nimport numpy as np\nimport tensorflow as tf\n\nimport argparse\nimport time\nimport os\nfrom six.moves import cPickle\n\nfrom utils import TextLoader\nfrom model import Model\n\ndef main():\n parser = argparse.ArgumentParser()\n parser.add_argument('--save_dir', type=st... | [
[
"tensorflow.compat.v1.Session",
"tensorflow.compat.v1.global_variables",
"tensorflow.train.get_checkpoint_state",
"tensorflow.compat.v1.global_variables_initializer"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
aiologybay/NumberClassification | [
"2c9649973b540c5a8d48e7aa359e4aa6c6632803"
] | [
"train.py"
] | [
"# coding:utf-8\nimport matplotlib.pyplot as plt\nimport torch\nimport torch.nn.functional as F\n\nn_data = torch.ones(100, 2) # 100个具有2个属性的数据 shape=(100,2)\nx0 = torch.normal(2 * n_data, 1) # 根据原始数据生成随机数据，第一个参数是均值，第二个是方差，这里设置为1了，shape=(100,2)\ny0 = torch.zeros(100) # 100个0作为第一类数据的标签，shape=(100,1)\nx1 = torch.no... | [
[
"torch.normal",
"torch.nn.CrossEntropyLoss",
"torch.ones",
"torch.max",
"torch.zeros",
"torch.cat",
"matplotlib.pyplot.cla",
"torch.nn.Linear",
"matplotlib.pyplot.text",
"matplotlib.pyplot.show",
"matplotlib.pyplot.pause"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
pat-phattharaporn/qiskit-aqua | [
"fb7f24d45769ed5152e589b0f9d84ea90618d052"
] | [
"qiskit/aqua/operators/evolutions/evolved_op.py"
] | [
"# This code is part of Qiskit.\n#\n# (C) Copyright IBM 2020.\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.\n#\n# Any modifications or ... | [
[
"numpy.conj",
"scipy.linalg.expm"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"0.13",
"0.12",
"0.14",
"0.15"
],
"tensorflow": []
}
] |
jinshisai/Imfits | [
"5c5c86238785e1bc6faf33b13a4a2b846648fc90"
] | [
"imfits/au.py"
] | [
"'''\nAnalysis utilities for Imfits.\n'''\n\n\nimport numpy as np\nimport scipy.optimize\nimport matplotlib.pyplot as plt\n\nfrom imfits import Imfits\n\n\n\n# constant\nclight = 2.99792458e10 # light speed [cm s^-1]\nauTOkm = 1.495978707e8 # AU --> km\nauTOcm = 1.495978707e13 # AU --> cm\nauTOpc = 4.85e-6 ... | [
[
"numpy.diag",
"numpy.radians",
"numpy.sqrt",
"numpy.abs",
"numpy.isnan",
"numpy.cos",
"numpy.sin",
"numpy.arctan2",
"numpy.exp",
"numpy.where",
"numpy.vstack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
neuralbotnetworks/ncappzoo | [
"b63b650e6525cf869d0c7e09ce2168371c020ad4",
"b63b650e6525cf869d0c7e09ce2168371c020ad4"
] | [
"networks/tiny_yolo_v3/tiny_yolo_v3.py",
"networks/mnist/mnist.py"
] | [
"\n# Copyright(c) 2017 Intel Corporation. \n# License: MIT See LICENSE file in root directory.\n\n\nGREEN = '\\033[1;32m'\nRED = '\\033[1;31m'\nNOCOLOR = '\\033[0m'\nYELLOW = '\\033[1;33m'\nDEVICE = \"MYRIAD\"\n\ntry:\n from openvino.inference_engine import IENetwork, IECore\nexcept:\n print(RED + '\\nPlease ... | [
[
"numpy.exp",
"numpy.array",
"numpy.transpose"
],
[
"numpy.argsort"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
hql1234/mne-python | [
"14fe4fa5e92884dcf665fd96a71ec5bb49e4da96"
] | [
"mne/stats/tests/test_permutations.py"
] | [
"# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>\n#\n# License: BSD (3-clause)\n\nfrom numpy.testing import assert_array_equal, assert_allclose\nimport numpy as np\nfrom scipy import stats, sparse\n\nfrom mne.stats import permutation_cluster_1samp_test\nfrom mne.stats.permutations import per... | [
[
"scipy.stats.ttest_1samp",
"numpy.random.seed",
"numpy.linspace",
"scipy.sparse.eye",
"numpy.testing.assert_array_equal",
"numpy.random.randn",
"numpy.testing.assert_allclose",
"numpy.random.default_rng"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"0.13",
"1.6",
"0.14",
"1.10",
"0.15",
"1.4",
"1.3",
"1.9",
"0.19",
"1.5",
"0.18",
"1.2",
"1.7",
"0.12",
"1.0",
"0.17",
"0.16",
"1.8"
... |
chameleonTK/misspelling-semantics | [
"a51e372d8c43551ce3f41c69deb34a5998b0dec1",
"a51e372d8c43551ce3f41c69deb34a5998b0dec1"
] | [
"few-shot_WangchanBERTa_MST.py",
"MAEClassifier.py"
] | [
"\nfrom WangchanBERTaArgs import parser\nimport os\nimport numpy as np\nimport random\nimport torch\nfrom WangchanBERTaModel import WangchanBERTaModel\nfrom WangchanBERTaDataset import WangchanBERTaDataset\n\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n\ndef set_random_seed(seed=0):\n os.environ['PYTHO... | [
[
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.manual_seed",
"torch.cuda.manual_seed_all",
"numpy.random.RandomState"
],
[
"torch.cat"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
may3rd/pid_detector | [
"c5f84c0d1cbf7c5598f44819b279a066dea0e5b8"
] | [
"text_detection/EAST-Detector/opencv_text_detection_image.py"
] | [
"# USAGE\n# python3 opencv_text_detection_image.py --image images/lebron_james.jpg --east frozen_east_text_detection.pb\n\n# import the necessary packages\nfrom imutils.object_detection import non_max_suppression\nimport numpy as np\nimport argparse\nimport time\nimport cv2\n\n# construct the argument parser and pa... | [
[
"numpy.array",
"numpy.cos",
"numpy.sin"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
INFINITSY/darts | [
"684f97e407ee044a14c375f4a3078398a4b802bc"
] | [
"cnn/analyze.py"
] | [
"import torch\nimport numpy as np\nimport torch.nn as nn\nfrom numpy.linalg import eigvals\nfrom torch.autograd import Variable\nfrom copy import deepcopy\nimport logging\n\n\ndef _concat(xs):\n return torch.cat([x.view(-1) for x in xs])\n\n\nclass Analyzer(object):\n def __init__(self, model, args):\n ... | [
[
"torch.zeros",
"torch.zeros_like",
"torch.is_tensor",
"torch.autograd.grad",
"torch.autograd.Variable"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
HofmannCh/MzbCreator | [
"481086c898f1189b785f959012bb477bca476b1c"
] | [
"window.py"
] | [
"import tkinter.filedialog\nfrom tkinter.messagebox import showerror\nimport tkinter as tk\n\nfrom route import Route\n\nimport matplotlib\nfrom matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk\n\n# Implement the default Matplotlib key bindings.\nfrom matplotlib.backend_bases import ... | [
[
"matplotlib.backends.backend_tkagg.NavigationToolbar2Tk",
"matplotlib.backend_bases.key_press_handler",
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg",
"matplotlib.figure.Figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Phellox/bert2punc | [
"4a260893ec93f6e73da6c800f140f005ed295853"
] | [
"tests/test_model.py"
] | [
"import torch\nfrom variables import PROJECT_PATH\nfrom src.models import train_model\nfrom src.data.load_data import load_dataset\n\ndef test_model_output(i=5):\n model = train_model.TrainModel().model\n data = load_dataset(set_type = 'val', dir_path=PROJECT_PATH / \"data\" / \"processed\")\n with torch.n... | [
[
"torch.no_grad",
"torch.argmax"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
vfdev-5/learn2learn | [
"a1da2c755856505556241809bba9b150f36850c2"
] | [
"examples/vision/protonet_omniglot.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# The code is adapted from Oscar Knagg\n# https://github.com/oscarknagg/few-shot\n# and he has a great set of medium articles around it.\n\nimport argparse\n\nimport numpy as np\nimport torch\nfrom PIL.Image import LANCZOS\nfrom torch.nn import Module\nfrom torch.optim imp... | [
[
"torch.nn.NLLLoss",
"torch.LongTensor",
"torch.cat",
"numpy.less",
"torch.cuda.is_available",
"torch.device",
"torch.stack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
georghess/fastmurty | [
"ec9f862268b8cee3dd7d3c229b5901a137e692f1"
] | [
"otherimplementations/slowmurty.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\ngithub.com/motrom/fastmurty last modified 5/17/19\r\na simple but inefficient implementation of HOMHT data association\r\nused for testing the validity of the main code\r\nvery slow - don't use on anything bigger than 50x50!\r\nAlso, this code doesn't correctly handle the corne... | [
[
"scipy.optimize.linear_sum_assignment"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.6",
"1.4",
"0.19",
"1.5",
"0.18",
"1.2",
"1.7",
"1.0",
"0.17",
"1.3",
"1.8"
],
"tensorflow": []
}
] |
jit9/simonsobs-sotodlib | [
"ee7c187c1266d14f2fc3447e83d8ac65a021a6c6"
] | [
"sotodlib/data/toast_load.py"
] | [
"# Copyright (c) 2018-2019 Simons Observatory.\n# Full license can be found in the top level \"LICENSE\" file.\n\"\"\"TOAST interface tools.\n\nThis module contains code for interfacing with TOAST data representations.\n\n\"\"\"\nimport os\nimport sys\nimport re\n\nimport traceback\n\nimport numpy as np\n\n# Import... | [
[
"numpy.amin",
"numpy.amax",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
aymen-mouelhi/glyphreader | [
"3c6c05a999aa700fea8bba4224b95c57a413e3e4"
] | [
"src/imageLoader.py"
] | [
"'''\nCreated on 25 Dec 2016\n\n@author: Morris Franken\nLoads a batch of images and prepares them for forwarding into a keras deep net.\n'''\nimport numpy as np\nfrom multiprocessing.pool import Pool\nfrom keras.preprocessing import image\nfrom keras.applications.inception_v3 import preprocess_input\n\ndef loadIm... | [
[
"numpy.expand_dims",
"numpy.vstack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Akshaykumarcp/explore-hugging-face | [
"3d7f9359354938a792d84de8c3bbc59f2606c38e"
] | [
"gpu_test.py"
] | [
"# CREDITS: https://www.tensorflow.org/guide/gpu\r\n\r\nimport tensorflow as tf\r\n\r\n# check tf version\r\ntf.__version__\r\n\r\n# is cuda installed ?\r\ntf.test.is_built_with_cuda()\r\n\r\n# test whether GPU is available\r\ntf.test.is_gpu_available(cuda_only=False, min_cuda_compute_capability=None)\r\n\r\n# phys... | [
[
"tensorflow.test.is_gpu_available",
"tensorflow.test.is_built_with_cuda",
"tensorflow.config.list_physical_devices",
"tensorflow.config.experimental.list_physical_devices"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Rocketbase-AI/rockets-mobilepose | [
"be7273dff7fcf7d1023f431f4b63ac8d82978182"
] | [
"cocoapi/PythonAPI/pycocotools/coco.py"
] | [
"__author__ = 'tylin'\n__version__ = '2.0'\n# Interface for accessing the Microsoft COCO dataset.\n\n# Microsoft COCO is a large image dataset designed for object detection,\n# segmentation, and caption generation. pycocotools is a Python API that\n# assists in loading, parsing and visualizing the annotations in CO... | [
[
"matplotlib.pyplot.gca",
"numpy.random.random",
"numpy.min",
"numpy.dstack",
"numpy.ones",
"matplotlib.pyplot.plot",
"numpy.all",
"numpy.max",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mriverrose/SEC10KTables | [
"00f53b34176303b2d3276347d3397a0f3d57c8ec"
] | [
"statement_functions.py"
] | [
"from bs4 import BeautifulSoup\nimport numpy as np\nimport pandas as pd\nimport requests\n\n\n# Display entire pandas dataframe in the interpreter window:\n#pd.set_option('display.max_colwidth', -1) \n\n\ndef create_statement_data(statementUrl):\n \"\"\"Once we have valid table_urls from our StatementUrls functi... | [
[
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
JamesZhutheThird/Rb-PaStaNet | [
"2f42841621d4a83b1186a6e9bb1f96d8e05e5ae6"
] | [
"tools/Test_pasta_AVA.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport _init_paths\nimport tensorflow as tf\nimport numpy as np\nimport argparse\nimport cPickle as pickle\nimport os\n\nfrom ult.config import cfg\nfrom models.test_Solver_AVA_pasta import test_net\nf... | [
[
"tensorflow.ConfigProto",
"tensorflow.Session",
"tensorflow.train.Saver",
"numpy.random.seed"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
clasp-developers/cl-bqplot | [
"b8fecbb5fa8e59ea94e0cec5b4d2a2e54e926e8c"
] | [
"bqplot/pyplot.py"
] | [
"# Copyright 2015 Bloomberg Finance L.P.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"numpy.arange",
"numpy.issubdtype",
"numpy.shape",
"numpy.column_stack",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
bluerobe25/maxentropy | [
"ce5a005127d929e66d7b715278d3505e3ee4e545"
] | [
"examples/conditional_example1.py"
] | [
"from __future__ import print_function\n# Test for conditional models\n# Ed Schofield, 2006\n\nfrom builtins import str\nfrom builtins import range\nimport numpy as np\nimport maxentropy\n\n# Two contexts W, four labels x\n# E_p f_0(W, X) = 0.4\n# where f_0(w, x) = indicator func \"is the label x=0 and is the conte... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
master-hzz/tensorflow | [
"4b4b51cdd9e8c3c748b76dd8649bcd5556e84d76"
] | [
"tensorflow/contrib/estimator/python/estimator/replicate_model_fn.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.ops.array_ops.shape",
"tensorflow.python.client.device_lib.list_local_devices",
"tensorflow.python.ops.array_ops.split",
"tensorflow.python.framework.device.DeviceSpec.from_string",
"tensorflow.python.ops.variables.trainable_variables",
"tensorflow.python.framework.ops.d... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.5",
"1.7",
"1.4"
]
}
] |
hansheng0512/LateTemporalModeling3DCNN | [
"71c1d3fae9781c55059f0518e0b39781a535e153",
"71c1d3fae9781c55059f0518e0b39781a535e153"
] | [
"models/BERT/transformer.py",
"utils/video_transforms.py"
] | [
"import torch.nn as nn\n\nfrom .attention import MultiHeadedAttention, MultiHeadedAttention2\nfrom .utils import SublayerConnection, PositionwiseFeedForward, SublayerConnection2\n\n\nclass TransformerBlock(nn.Module):\n \"\"\"\n Bidirectional Encoder = Transformer (self-attention)\n Transformer = MultiHead... | [
[
"torch.nn.Dropout"
],
[
"numpy.expand_dims",
"numpy.absolute",
"numpy.abs",
"numpy.min",
"numpy.fliplr",
"numpy.ascontiguousarray",
"numpy.isnan",
"numpy.flipud",
"torch.tensor",
"numpy.concatenate",
"numpy.logical_or",
"numpy.floor",
"numpy.random.binom... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Shipilin/specqp | [
"c96c6f9476d871d73f7aa1fb7aeb3a435c9013a9"
] | [
"specqp/gui.py"
] | [
"import os\nimport copy\nfrom shutil import copyfile\nimport re\nimport datetime\nimport ntpath\nimport logging\nimport webbrowser\n\nimport pandas as pd\nimport numpy as np\n\nimport tkinter as tk\nfrom tkinter import ttk\nfrom tkinter import filedialog, simpledialog, messagebox\n\nimport matplotlib\nfrom matplotl... | [
[
"numpy.log",
"numpy.absolute",
"matplotlib.style.use",
"matplotlib.use",
"pandas.DataFrame",
"matplotlib.image.imread",
"numpy.max",
"numpy.mean",
"matplotlib.backends.backend_tkagg.NavigationToolbar2Tk",
"numpy.array",
"matplotlib.cm.get_cmap",
"matplotlib.backends... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
gdalessi/clustering | [
"79988ee565c9d1b00bbcd3c1dbd9a69d9c1c80f1",
"79988ee565c9d1b00bbcd3c1dbd9a69d9c1c80f1"
] | [
"examples/dimensionality_reduction/pcaFeatureExtraction.py",
"examples/model_order_reduction/MGPCA.py"
] | [
"import OpenMORe.model_order_reduction as model_order_reduction\nfrom OpenMORe.utilities import *\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport os\n\n############################################################################\n# In this example it's shown how to perform dimensionality reduction an... | [
[
"matplotlib.pyplot.figure",
"matplotlib.pyplot.rcParams.update",
"matplotlib.pyplot.show",
"numpy.genfromtxt"
],
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.title",
"numpy.min",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.savefig",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
jesnyder/plastic_bio | [
"883d1b1333f13ef1e723dea4367a34c22bda767a"
] | [
"code/python/a0200_aggregate_info.py"
] | [
"from bs4 import BeautifulSoup\r\nimport datetime\r\nimport json\r\nimport lxml\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nimport os\r\nimport pandas as pd\r\nfrom serpapi import GoogleSearch\r\nimport shutil\r\nimport re\r\nimport requests\r\nimport time\r\n\r\n\r\nfrom a0001_admin import clean_da... | [
[
"pandas.read_csv",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.title",
"numpy.arange",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.close",
"matplotlib.pyplot.xlabel",
"matplotlib.pypl... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
mk37972/PASCAPE | [
"1fc7c0b17b7313dd13ceb93ed2c8e37b206ece87"
] | [
"baselines/her/rollout_NuFingers.py"
] | [
"from collections import deque\n\nimport numpy as np\nimport pickle\n\nfrom baselines.her.util import convert_episode_to_batch_major, store_args\n\nfrom nifpga import Session\nimport time\nimport click\n\nclass RolloutWorker:\n\n @store_args\n def __init__(self, policy, dims, logger, T, rollout_batch_size=1,\... | [
[
"numpy.matrix",
"numpy.random.random",
"numpy.sqrt",
"numpy.clip",
"numpy.linalg.inv",
"numpy.cos",
"numpy.linalg.norm",
"numpy.sin",
"numpy.arctan2",
"numpy.max",
"numpy.mean",
"numpy.float32",
"numpy.transpose",
"numpy.array",
"numpy.zeros",
"numpy... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Shanthika/TerrainAuthoring-Pytorch | [
"54ad87abbfeb7f4ce0b0130e295c4469e45d42a5"
] | [
"experiments/vae_pix2pix_exp.py"
] | [
"import math\nimport torch\nimport numpy as np\nfrom torch import optim\nfrom models import *\nfrom models.types_ import Tensor\nfrom utils import data_loader\nimport pytorch_lightning as pl\nfrom torchvision import transforms\nimport torchvision.utils as vutils \nfrom torch.utils.data import DataLoader\nfrom terra... | [
[
"torch.stack",
"torch.no_grad",
"torch.utils.data.DataLoader",
"torch.optim.lr_scheduler.ExponentialLR"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Pandinosaurus/models-intelai | [
"60f5712d79a363bdb7624e3116a66a4f1a7fe208",
"60f5712d79a363bdb7624e3116a66a4f1a7fe208"
] | [
"models/image_recognition/pytorch/common/main.py",
"models/language_modeling/tensorflow/bert_large/inference/run_squad.py"
] | [
"#\n# -*- coding: utf-8 -*-\n#\n# Copyright (c) 2019-2021 Intel Corporation\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n#... | [
[
"torch.set_flush_denormal",
"torch.multiprocessing.spawn",
"torch.load",
"torch.utils.data.DataLoader",
"torch.fx.experimental.optimization.fuse",
"torch.no_grad",
"torch.cuda.is_available",
"torch.save",
"torch.nn.CrossEntropyLoss",
"torch.jit.trace",
"torch.distribute... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"2.7",
"1.12",
"2.6",
"2.2",
"1.13",
"2.3",
"2.4",
"1.... |
StijnVerdenius/SNIP-it | [
"fec11fcda3038d9ad7246ddb1ee9889049f03fc8"
] | [
"models/criterions/GRASP.py"
] | [
"import copy\n\nimport torch\nimport torch.autograd as autograd\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom models.criterions.SNIP import SNIP\nfrom utils.constants import SNIP_BATCH_ITERATIONS\n\n\nclass GRASP(SNIP):\n\n \"\"\"\n Adapted implementation of GraSP from the paper:\n Pickin... | [
[
"torch.nn.functional.cross_entropy",
"torch.autograd.grad",
"torch.flatten"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
totoyoyo/deformable-template-capstone | [
"bf3a26e1d5781fc2d8a7680c0ad21d982d82d363"
] | [
"complete_workflow/classifier.py"
] | [
"import numpy as np\nfrom typing import List\nimport functions_maker as func\nimport constants_maker as const\nimport time\nimport pandas as pd\nimport save\nfrom pathlib import Path\nimport load\nimport scipy.stats as stat\n\"\"\"\nTakes a list of images:\n\nreturns\n\n\"\"\"\n\nloaded_image = {\n \"name\": \"s... | [
[
"numpy.log",
"numpy.random.multivariate_normal",
"pandas.DataFrame",
"numpy.shape",
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
gwjensen/Theano | [
"cd79b906b7cf1688326304d849f7a3d58d2e5ac5"
] | [
"theano/sandbox/cuda/nvcc_compiler.py"
] | [
"from __future__ import print_function\nimport distutils\nimport logging\nimport os\nimport subprocess\nimport sys\nimport warnings\n\nimport numpy\n\nfrom theano import config\nfrom theano.compat import decode, decode_iter\nfrom theano.configdefaults import local_bitwidth\nfrom theano.gof.utils import hash_from_fi... | [
[
"numpy.__version__.split"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
STHSF/DeepLearning | [
"af91fced5af87f69915bb2674229d5f6461f553d"
] | [
"insurance_qa/cnn.py"
] | [
"# coding=utf-8\n\nimport tensorflow as tf\nimport numpy as np\n\n##########################################################################\n# embedding_lookup + cnn + cosine margine , batch\n##########################################################################\n\n\nclass InsQACNN(object):\n\n def __init... | [
[
"tensorflow.nn.bias_add",
"tensorflow.device",
"tensorflow.constant",
"tensorflow.concat",
"tensorflow.nn.conv2d",
"tensorflow.truncated_normal",
"tensorflow.nn.max_pool",
"tensorflow.reduce_sum",
"tensorflow.sub",
"tensorflow.equal",
"tensorflow.cast",
"tensorflow.... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
uzumaxy/pyvalid | [
"38f1d19b612fc67a2877d6b2e637c971e2ceea77"
] | [
"tests/test_tensor_validator.py"
] | [
"import unittest\n\nimport numpy as np\n\nimport torch\n\nfrom pyvalid.validators import TensorValidator\n\n\nclass TensorValidatorTestCase(unittest.TestCase):\n\n def setUp(self) -> None:\n self.t = torch.Tensor([[0.0688, 0.0843, 0.0000],\n [0.1810, 0.0000, 0.1470]])\n\n ... | [
[
"torch.Tensor"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
fossabot/PyNumDiff | [
"dccad2ad7a875f2ecccb0db2bb6e2afa392916d1"
] | [
"pynumdiff/nnet/__nnet__.py"
] | [
"import numpy as np \nimport os\nimport logging\n\nlogging.basicConfig(\n level=logging.INFO,\n format=\"%(asctime)s [%(levelname)s] %(message)s\",\n handlers=[\n logging.FileHandler(\"debug.log\"),\n logging.StreamHandler()\n ]\n)\n\n# optional packages\ntry:\n import tensorflow as tf\... | [
[
"numpy.product",
"tensorflow.reduce_sum",
"tensorflow.nn.l2_loss",
"tensorflow.train.AdamOptimizer",
"numpy.exp",
"tensorflow.gradients",
"tensorflow.reset_default_graph",
"tensorflow.add",
"tensorflow.logging.set_verbosity",
"tensorflow.contrib.layers.xavier_initializer",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
rpetit3/anthrax-metagenome-study | [
"b4a6f2c4d49b57aeae898afd6a95c8f6cb437945"
] | [
"scripts/subsample-lethal-factor.py"
] | [
"#! /usr/bin/env python3\n\"\"\"Create random subsampels of input sequences.\"\"\"\nimport argparse as ap\nfrom decimal import Decimal\nfrom multiprocessing import Pool\nimport os\nimport glob\nimport random\nimport subprocess\nimport numpy as np\nGENOME_SIZE = None\nLENGTH = None\nSEQUENCES = None\nTOTAL = None\nB... | [
[
"numpy.median",
"numpy.array",
"numpy.mean"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
riccardo-seppi/HMF_seppi20 | [
"f901a51d57a8c21a3a82b62cd821a771dd5cc1da"
] | [
"python/cosmo_params_trends.py"
] | [
"import sys\nimport os, glob\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom colossus.cosmology import cosmology\nfrom colossus.lss import peaks\nfrom colossus.lss import bias\n\noutdir = os.path.join('/home/rseppi/HMF_seppi20','figures','cosmo_trends')\ncosmo = cosmology.setCosmology('multidark-planck')... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.tight_layout",
"numpy.linspace",
"matplotlib.pyplot.savefig",
"numpy.geomspace",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.close",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.tick_params",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.