repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
lunayach/texar-pytorch | [
"ac3e334e491f524dd01654b07af030fa20c88b34",
"ac3e334e491f524dd01654b07af030fa20c88b34",
"ac3e334e491f524dd01654b07af030fa20c88b34"
] | [
"texar/core/optimization_test.py",
"texar/modules/decoders/transformer_decoders.py",
"texar/core/attention_mechanism_test.py"
] | [
"\"\"\"\nUnit tests for various optimization related utilities.\n\"\"\"\n\nimport unittest\n\nimport torch\n\nfrom texar.core.optimization import *\n\n\nclass OptimizationTest(unittest.TestCase):\n r\"\"\"Test optimization.\n \"\"\"\n\n def setUp(self):\n N, D_in, H, D_out = 64, 100, 10, 1\n\n ... | [
[
"torch.nn.Linear",
"torch.nn.MSELoss",
"torch.nn.ReLU",
"torch.tensor",
"torch.randn"
],
[
"torch.zeros",
"torch.nn.Dropout",
"torch.nn.LayerNorm",
"torch.nn.ModuleList",
"torch.ones_like",
"torch.empty",
"torch.argmax",
"torch.where"
],
[
"torch.Siz... |
GeoscienceAustralia/anuga_core | [
"372e21a5c1c88867437374c851f1ff629bd3dab3"
] | [
"anuga/parallel/tests/test_parallel_sw_flow_low_froude_0.py"
] | [
"\"\"\"\nSimple water flow example using ANUGA\n\nWater driven up a linear slope and time varying boundary,\nsimilar to a beach environment\n\nThis is a very simple test of the parallel algorithm using the simplified parallel API\n\"\"\"\nfrom __future__ import print_function\nfrom __future__ import division\n\n\n#... | [
[
"numpy.allclose",
"numpy.array"
]
] |
jkortner/ml-ops | [
"c0b6d4ce76008a325cfb49e87f2be40a22b62b3e"
] | [
"sandbox/ml/train.py"
] | [
"import mlflow\nimport mlflow.sklearn\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import BernoulliNB\nfrom sklearn.metrics import accuracy_score\nimport pandas as pd\n\n\ndef get_X_y(df, target):\n\n # sklearn split\n train, test = train_test_split(df)\n\n # X, y split\n... | [
[
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"sklearn.naive_bayes.BernoulliNB",
"sklearn.metrics.accuracy_score"
]
] |
fossabot/autofocus | [
"45954416011eca7c3f25a548bfe5017a083d7593"
] | [
"autofocus/predict/example_post.py"
] | [
"# Examples of how to make requests agains the image classification endpoints\n# Note:\n# 1. This assumes that the image_classifier_api is running (i.e., using docker compose up)\n# 2. It also assumes that the api address is at 127.0.0.1 (which should be the case)\nimport os\n\nimport pandas as pd\nimport reque... | [
[
"pandas.DataFrame"
]
] |
nirvaank/pyqmc | [
"a92c926d1008e466409cdefaab74d343061a30b4"
] | [
"tests/integration/test_twist.py"
] | [
"import numpy as np\nimport pyqmc.api as pyq\nfrom pyqmc.slater import Slater\nfrom pyqmc.pbc import enforce_pbc\nfrom pyqmc.coord import PeriodicConfigs\n\n\ndef test_cubic_with_ecp(li_cubic_ccecp, kind=1):\n cell, mf = li_cubic_ccecp\n runtest(cell, mf, kind=kind)\n\n\ndef test_noncubic(diamond_primitive, k... | [
[
"numpy.linalg.norm",
"numpy.random.seed",
"numpy.round",
"numpy.einsum",
"numpy.random.randint",
"numpy.abs"
]
] |
PASTAplus/dex | [
"d04fcf756b77856f4be0585dd7f5d38795751247",
"d04fcf756b77856f4be0585dd7f5d38795751247"
] | [
"tools/prepopulate_caches.py",
"dex/util.py"
] | [
"#!/usr/bin/env python\n\n\"\"\"Prepopulate caches\"\"\"\nimport collections\nimport contextlib\nimport csv\nimport logging\nimport os\nimport pathlib\nimport sys\nimport time\nimport unittest.mock\n\nimport pandas as pd\nimport pandas_profiling.model.base\n\nimport pandas_profiling.model.describe\n\n# WALK_ROOT_PA... | [
[
"pandas.read_csv"
],
[
"pandas.option_context"
]
] |
axiezai/complex_laplacian | [
"e84574a7d9c051a95b5d37aa398765aeb5f85fa4"
] | [
"scripts/laplacian_pearson_basinhopping.py"
] | [
"\"\"\"\nUse the basinhopping algorithm to find best alpha, speed, and frequency\nthat produces the best spatial correlation for a given canonical network\n\"\"\"\n\n# number stuff imports\nimport h5py\nimport numpy as np\nimport pandas as pd\nfrom scipy.optimize import basinhopping\nfrom scipy.stats import pearson... | [
[
"numpy.max",
"numpy.array",
"numpy.nan_to_num",
"numpy.zeros",
"numpy.round",
"pandas.DataFrame",
"numpy.load",
"numpy.min",
"numpy.where",
"numpy.argsort",
"numpy.all",
"pandas.read_csv",
"numpy.squeeze"
]
] |
jerryuhoo/PaddleSpeech | [
"1eec7b5e042da294c7524af92f0fae4c32a71aa3",
"1eec7b5e042da294c7524af92f0fae4c32a71aa3"
] | [
"paddlespeech/server/engine/tts/online/onnx/tts_engine.py",
"audio/tests/features/test_log_melspectrogram.py"
] | [
"# Copyright (c) 2021 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 re... | [
[
"numpy.concatenate",
"numpy.load",
"numpy.transpose"
],
[
"numpy.testing.assert_array_almost_equal"
]
] |
spalato/spectro_tools | [
"977dc35dfec35ffbc75cacecdeeda9ed4fdbf0cd"
] | [
"scratch/vibronic.py"
] | [
"import numpy as np\nfrom scipy.special import assoc_laguerre, factorial\nfrom lmfit.lineshapes import voigt\nimport matplotlib.pyplot as plt\n\n# Normally, all these functions are in a module called `spectro.utils`. \n# I would only perform the following import:\n# from spectro.utils import vibronic_emission\n\n\n... | [
[
"numpy.zeros_like",
"numpy.asarray",
"matplotlib.pyplot.savefig",
"numpy.sum",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"numpy.exp",
"matplotlib.pyplot.figure",
"numpy.where",
"numpy.arange",
"scipy.special.factorial",
"numpy.abs",
"numpy.all",
... |
Nickfagiano/SLM-Lab | [
"dddff5e1ce7454c33b45a803dd0c1d8e133c4508",
"dddff5e1ce7454c33b45a803dd0c1d8e133c4508"
] | [
"slm_lab/agent/net/net_util.py",
"test/conftest.py"
] | [
"from functools import partial, wraps\nfrom slm_lab.lib import logger, optimizer, util\nimport os\nimport pydash as ps\nimport torch\nimport torch.nn as nn\n\nlogger = logger.get_logger(__name__)\n\n# register custom torch.optim\nsetattr(torch.optim, 'GlobalAdam', optimizer.GlobalAdam)\nsetattr(torch.optim, 'Global... | [
[
"torch.nn.Linear",
"torch.isnan",
"torch.nn.init.constant_",
"torch.nn.Sequential",
"torch.is_tensor",
"torch.cuda.is_available",
"torch.nn.init.calculate_gain",
"torch.equal"
],
[
"pandas.DataFrame",
"numpy.asarray"
]
] |
yoyonel/DailyCodingProblem | [
"5fb1e844fa975ebc0bd0e2818ea20ed5696170fa"
] | [
"src/coding_interview_preparation/backtracking_algorithm_n_queens/app.py"
] | [
"\"\"\"\n\n\"\"\"\nfrom functools import partial\nfrom itertools import permutations\nfrom matplotlib import pyplot\nimport time\nimport timeit\nfrom typing import Iterator, Tuple\n\n\ndef handle_return(generator, func):\n \"\"\"\n https://stackoverflow.com/questions/34073370/best-way-to-receive-the-return-va... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot"
]
] |
Aethiles/ppo-pytorch | [
"b3fb6bdb466056cf84115ca7b0af21d2b48185ae"
] | [
"test/understanding/test_batches.py"
] | [
"import numpy as np\nimport torch.utils.data.sampler as samplers\nimport unittest\n\n\nclass BatchTest(unittest.TestCase):\n def test_different_batches(self):\n mini_batch_size = 3\n sampler = samplers.BatchSampler(sampler=samplers.SubsetRandomSampler(range(12)),\n ... | [
[
"numpy.array_equal"
]
] |
SuperSaiyan-God/PhotoMath | [
"58f7d88dde5f1e0ccc3cabc2499520d08705c734"
] | [
"object_detection/xml_to_csv.py"
] | [
"import os\nimport glob\nimport pandas as pd\nimport xml.etree.ElementTree as ET\n\n\ndef xml_to_csv(path):\n xml_list = []\n for xml_file in glob.glob(path + '/*.xml'):\n tree = ET.parse(xml_file)\n root = tree.getroot()\n for member in root.findall('object'):\n value = (root.... | [
[
"pandas.DataFrame"
]
] |
shikanggao/meta-dataset | [
"7b1e99009516eda3bbd5e740e178ebc37e2d6767"
] | [
"meta_dataset/models/functional_backbones.py"
] | [
"# coding=utf-8\n# Copyright 2021 The Meta-Dataset 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 require... | [
[
"tensorflow.compat.v1.initializers.zeros",
"tensorflow.compat.v1.nn.avg_pool",
"tensorflow.compat.v1.assign",
"tensorflow.compat.v1.logging.info",
"tensorflow.compat.v1.reduce_prod",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.equal",
"tensorflow.compat.v1.get_variable_scop... |
jczhao001/winkDetection | [
"a0c298ae2541a6719e09c66e18afb2c87dba0d7c"
] | [
"input1.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport os\nimport cv2\nfrom PIL import Image\nimport matplotlib.pyplot as plt\ntrain_dir_path = \"E:/test/eyeclt/0/test/\"\ndef getFile(fileDir):\n close = []\n lableclose = []\n open = []\n lableopen = []\n for file in os.listdir(fileDir):\n\n nam... | [
[
"numpy.array",
"tensorflow.train.batch",
"tensorflow.train.slice_input_producer",
"tensorflow.read_file",
"numpy.random.shuffle",
"tensorflow.reshape",
"tensorflow.image.resize_image_with_crop_or_pad",
"tensorflow.image.per_image_standardization",
"numpy.hstack",
"tensorflo... |
acatwithacomputer/proteus | [
"80dfad95da6ab4d18a88a035f55c26b03540a864",
"80dfad95da6ab4d18a88a035f55c26b03540a864",
"80dfad95da6ab4d18a88a035f55c26b03540a864"
] | [
"proteus/tests/POD/svd_burgers.py",
"proteus/tests/SWFlow/solitary_reef.py",
"proteus/mprans/NCLS3P.py"
] | [
"#!/usr/bin/env python\n\nfrom __future__ import print_function\nfrom __future__ import division\nfrom past.utils import old_div\nfrom burgers_init import use_deim\nfrom proteus import deim_utils,Archiver\nfrom proteus.deim_utils import read_snapshots\n\nT = 1.0\nnDTout = 100\nDT = old_div(T,float(nDTout))\n\narchi... | [
[
"numpy.savetxt",
"numpy.linalg.svd"
],
[
"numpy.cosh",
"numpy.piecewise",
"numpy.tanh",
"numpy.sqrt",
"numpy.abs",
"numpy.select",
"numpy.maximum"
],
[
"numpy.copy",
"numpy.ones",
"numpy.save",
"numpy.zeros"
]
] |
asellappen/bokeh | [
"e003b82b18c8ee7fb36f23c5f877e5e16b792827"
] | [
"tests/unit/bokeh/core/test_properties.py"
] | [
"#-----------------------------------------------------------------------------\n# Copyright (c) 2012 - 2021, Anaconda, Inc., and Bokeh Contributors.\n# All rights reserved.\n#\n# The full license is in the file LICENSE.txt, distributed with this software.\n#---------------------------------------------------------... | [
[
"numpy.array"
]
] |
edward-io/captum | [
"8f959950baaad00f2f9a3404d583b9f9292e35c7"
] | [
"captum/_utils/models/linear_model/train.py"
] | [
"import time\nfrom typing import Any, Callable, Dict, List, Optional\n\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import DataLoader\n\nfrom captum._utils.models.linear_model.model import LinearModel\n\n\ndef l2_loss(x1, x2, weights=None):\n if weights is None:\n return torch.mean((x1 - x2... | [
[
"numpy.concatenate",
"torch.stack",
"torch.norm",
"torch.FloatTensor",
"torch.no_grad",
"torch.nn.init.xavier_uniform_",
"torch.isclose",
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"torch.mean"
]
] |
ricardoprins/strawberryfields | [
"739ad44950624434375a24693a060e8a5e74c951"
] | [
"strawberryfields/circuitspecs/xunitary.py"
] | [
"# Copyright 2019-2020 Xanadu Quantum Technologies Inc.\n\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n\n# http://www.apache.org/licenses/LICENSE-2.0\n\n# Unless required by ap... | [
[
"numpy.identity",
"numpy.allclose",
"numpy.round"
]
] |
benoitmartin88/pytorchtrainer | [
"7d73acd0802e00c3589d28bce6c42a489dcd46ea"
] | [
"pytorchtrainer/metric/mean_absolute_error.py"
] | [
"import torch\n\nfrom . import Metric\n\n\nclass MeanAbsoluteError(Metric):\n def __init__(self):\n super().__init__(\"mae\", default_value=float('inf'))\n self._absolute_error_sum = 0.\n self._total = 0\n\n def step(self, y: torch.Tensor, y_pred: torch.Tensor):\n absolute_errors =... | [
[
"torch.abs",
"torch.sum"
]
] |
janaSunrise/Fashion-MNIST-Tensorflow | [
"a31d23e8b06ab8b70235d692b458e5a7c14aa2f1"
] | [
"src/train.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom tensorflow import keras\n\nprint(f\"Using tensorflow version: {tf.__version__}\")\n\n# Get the datasets\ndata = keras.datasets.fashion_mnist\n\n(train_images, train_labels), (test_images, test_labels) = data.load_data()\n\n# The cla... | [
[
"tensorflow.keras.layers.Flatten",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.figure",
"tensorflow.keras.layers.Dense",
"matplotlib.pyplot.show",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.xticks",
"matplotlib.py... |
HochulHwang/gc_test | [
"c42e9ec3392bc02eef5e3943ec3bf79456e91bf9"
] | [
"src/inference/train_val.py"
] | [
"from utils.meter import *\nimport time\nimport torch\nimport ipdb\nimport sys\nimport torch.nn as nn\n# from utils.others import *\nimport matplotlib\nfrom utils.loss import *\n\n\ndef make_variable_all_input(dict_input, cuda=False):\n dict_input_var = {}\n for k, v in dict_input.items():\n var = torc... | [
[
"torch.autograd.Variable",
"torch.no_grad"
]
] |
zhaolotelli/FedLearn | [
"b5ddb26acbee3218b11894fb7ca7ce24677c0b50"
] | [
"flearn/utils/sub.py"
] | [
"import copy\r\nimport numpy as np\r\n\r\ndef boot(client_data, sub_rate):\r\n n = len(client_data)\r\n rand_ind = np.random.choice(n, np.int(np.floor(n * sub_rate)))\r\n sub_data = copy.deepcopy(client_data)\r\n X = client_data.X\r\n y = client_data.y\r\n sub_data.X = X[rand_ind]\r\n sub_data.... | [
[
"numpy.floor"
]
] |
karamach/gtsam | [
"5cbb9dfd6c5bc6a38edd230fd0b9d9c7e5006b0b"
] | [
"cython/gtsam/tests/test_SimpleCamera.py"
] | [
"import math\nimport numpy as np\nimport unittest\n\nfrom gtsam import Pose2, Point3, Rot3, Pose3, Cal3_S2, SimpleCamera\n\nK = Cal3_S2(625, 625, 0, 0, 0)\n\nclass TestSimpleCamera(unittest.TestCase):\n\n def test_constructor(self):\n pose1 = Pose3(Rot3(np.diag([1, -1, -1])), Point3(0, 0, 0.5))\n c... | [
[
"numpy.diag"
]
] |
spaicer/explanation-generator-module | [
"9c7c9322ad43a73e452d9063cb3ae6c0a9309237"
] | [
"src/core/aeas.py"
] | [
"# credit https://github.com/ronniemi/explainAnomaliesUsingSHAP\n\nimport numpy as np\nimport pandas as pd\n\nfrom tensorflow.keras.models import Model\nfrom tensorflow.keras.layers import Input, Dense\nfrom tensorflow.keras import regularizers\nfrom tensorflow.keras.callbacks import EarlyStopping\n\nimport shap\ni... | [
[
"numpy.array",
"tensorflow.keras.regularizers.l1",
"tensorflow.keras.layers.Input",
"numpy.median",
"pandas.DataFrame",
"tensorflow.keras.models.Model",
"numpy.mean",
"numpy.fabs",
"numpy.power",
"tensorflow.keras.regularizers.l2",
"pandas.concat",
"tensorflow.keras... |
cgvvxx/Font_Style_Transfer | [
"1ff1e9f7bd1fef8f7736da90f917ad11b8fce964"
] | [
"data_modules/crawling.py"
] | [
"from selenium import webdriver\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.support import expected_conditions as EC\nfrom selenium.webdriver.support.ui import WebDriverWait\nfrom webdriver_manager.chrome import ChromeDriverManager\nimport pandas as pd\nimport warnings\nimport zipfile\nimp... | [
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
interesaaat/onnxconverter-common | [
"5f670d71184abb1f4601193f552bdda6c1f59555"
] | [
"onnxconverter_common/onnx_ops.py"
] | [
"# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License. See License.txt in the project root for\n# license information.\n###############################################################################\n\n# This file contains some high-level APIs for applying operations on var... | [
[
"numpy.array",
"numpy.iinfo"
]
] |
protivinsky/python-utils | [
"145fc8e6385df745c7b73fa0dfbb17abf6f58f82"
] | [
"libs/plots.py"
] | [
"import os\r\nfrom yattag import Doc, indent\r\nfrom libs.utils import create_stamped_temp, slugify\r\nimport matplotlib.pyplot as plt\r\n\r\n# NOTE - Does not work out of the box, needs a fix:\r\n#\r\n# Annoyingly, the js loading of subpages violates Cross-Origin Requests policy in all browsers\r\n# when files are... | [
[
"matplotlib.pyplot.close"
]
] |
xizhihuang/one_model_one_week | [
"a84fecd93a0fd60e1bbb923d78fe47d453938126"
] | [
"linear_regression/regression.py"
] | [
"# -*- coding:utf-8 -*-\nimport numpy as np\nnp.random.seed(1337)\nfrom keras.models import Sequential\nfrom keras.layers import Dense\nimport matplotlib.pyplot as plt\n\nX = np.linspace(-1, 1, 500)\nnp.random.shuffle(X)\nY = 0.5 * X + 0.2 + np.random.normal(0, 0.05, (500,))\n\nX_train, Y_train = X[:400], Y[:400]\n... | [
[
"numpy.random.normal",
"numpy.random.seed",
"matplotlib.pyplot.plot",
"numpy.random.shuffle",
"matplotlib.pyplot.show",
"matplotlib.pyplot.scatter",
"numpy.linspace"
]
] |
Evanc123/chainer | [
"929af7189b1271683200aa9b0ba6da2dd3dee110",
"929af7189b1271683200aa9b0ba6da2dd3dee110"
] | [
"tests/chainer_tests/functions_tests/activation_tests/test_softmax.py",
"tests/chainer_tests/initializer_tests/test_normal.py"
] | [
"import unittest\n\nimport numpy\n\nimport chainer\nfrom chainer.backends import cuda\nfrom chainer import functions\nfrom chainer import gradient_check\nfrom chainer import testing\nfrom chainer.testing import attr\n\n\n@testing.parameterize(*testing.product({\n 'shape_axis':\n [{'shape': None, 'axis': 1... | [
[
"numpy.ndindex",
"numpy.array",
"numpy.rollaxis",
"numpy.exp",
"numpy.random.uniform"
],
[
"numpy.empty"
]
] |
SteveDoyle2/pynastran | [
"14798312ac0419857ce030ee367f924b4924f9fd"
] | [
"pyNastran/op2/tables/ogs_grid_point_stresses/ogs_surface_stresses.py"
] | [
"import warnings\nfrom typing import List\nimport numpy as np\n\nfrom pyNastran.op2.result_objects.op2_objects import ScalarObject, get_times_dtype\nfrom pyNastran.f06.f06_formatting import (\n write_floats_10e, _eigenvalue_header)\nfrom pyNastran.op2.writer.utils import fix_table3_types\nfrom pyNastran.op2.op2_... | [
[
"numpy.isnan",
"numpy.empty",
"numpy.array_equal",
"numpy.zeros",
"numpy.allclose",
"numpy.float32",
"numpy.int32"
]
] |
jmetteUni/CoTeDe-modified | [
"3f1142811f051eb023337b7f80a513ad53866d68",
"3f1142811f051eb023337b7f80a513ad53866d68"
] | [
"cotede/qctests/gradient_depthconditional.py",
"cotede/qctests/morello2014.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# Licensed under a 3-clause BSD style license - see LICENSE.rst\n\n\"\"\"\n\n\"\"\"\n\nimport logging\n\nimport numpy as np\nfrom numpy import ma\n\nfrom .qctests import QCCheckVar\nfrom .gradient import curvature\n\nmodule_logger = logging.getLogger(__name__)\n\n\nc... | [
[
"numpy.ma.getmaskarray",
"numpy.shape",
"numpy.atleast_1d",
"numpy.isfinite",
"numpy.absolute"
],
[
"numpy.all",
"numpy.shape"
]
] |
sparkroy/DAML | [
"8a6d0869771bb35d2084d055123bbe790ecb8cf7"
] | [
"lib/common/utils.py"
] | [
"# -*- coding: utf-8 -*-\n\n\nfrom collections import defaultdict\nimport itertools\nimport os\nimport numpy as np\nimport yaml\nfrom lib.functions.triplet_loss import triplet_loss as F_tloss\nfrom lib.common.evaluation import evaluate_cluster\n\nimport chainer\nimport torch\nimport torch.nn.functional as F\n\n\nim... | [
[
"numpy.random.choice",
"numpy.tile",
"numpy.mean",
"torch.sum",
"numpy.concatenate",
"numpy.log",
"numpy.arange",
"torch.nn.functional.relu",
"numpy.int32",
"numpy.array",
"numpy.delete",
"torch.nn.functional.concat",
"numpy.argsort",
"numpy.array_split",
... |
yougoforward/tensorpackwithmscnn | [
"3c61c31892a1d954678fcef22f1243ab252e0015",
"3c61c31892a1d954678fcef22f1243ab252e0015",
"8d5ae5cc2cfcf2e4e53b4d1064ac9e727f736d09"
] | [
"tensorpack/dataflow/image.py",
"tensorpack/callbacks/param.py",
"examples/SpatialTransformer/mnist-addition.py"
] | [
"# -*- coding: UTF-8 -*-\n# File: image.py\n\n\nimport numpy as np\nimport copy as copy_mod\nfrom contextlib import contextmanager\nfrom .base import RNGDataFlow\nfrom .common import MapDataComponent, MapData\nfrom ..utils import logger\nfrom ..utils.argtools import shape2d\n\n__all__ = ['ImageFromFile', 'AugmentIm... | [
[
"numpy.issubdtype"
],
[
"tensorflow.local_variables",
"tensorflow.global_variables"
],
[
"tensorflow.nn.in_top_k",
"tensorflow.constant_initializer",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.nn.softmax",
"tensorflow.concat",
"tensorflow.transpose",
... |
johannespitz/MNF_VBNN | [
"e274a57cac03282e8ff3181c831e650b024b14a2"
] | [
"mutual_information.py"
] | [
"import sys\nimport numpy as np\nfrom tqdm import tqdm\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n\ndef _compute_mi(model, samples, num_runs):\n predictions_list = []\n for idx in tqdm(range(num_runs), file=sys.stdout):\n predictions_list.append(model.predict(samples, batch_size=10000))... | [
[
"numpy.log",
"matplotlib.pyplot.legend",
"numpy.asarray",
"matplotlib.pyplot.subplots"
]
] |
likith012/distill-grammar | [
"04ff5e07337789edfe57f21f85e30e7992ae90d9"
] | [
"deploy/convert_onnx.py"
] | [
"\"\"\"Convert the model to ONN format\n\"\"\"\n\n__author__ = \"Likith Reddy\"\n__version__ = \"1.0.0\"\n__email__ = \"likith012@gmail.com\"\n\n\nimport torch\nimport torch.nn as nn\nimport torch.onnx\nimport sys, os\n\nsys.path.insert(0, os.path.join(sys.path[0], '../'))\n\nfrom configs import config\nfrom src.da... | [
[
"torch.nn.DataParallel",
"torch.onnx.export",
"torch.cuda.device_count"
]
] |
dsshim0125/grmc | [
"a4d02b66055b33df07a8136cd6b11020b27ac4c5"
] | [
"evaluate_pytorch.py"
] | [
"import os\r\nimport glob\r\nimport time\r\nimport argparse\r\nimport torch\r\nfrom torch import nn\r\nfrom model.densedepth import Model\r\nfrom model.fcrn import ResNet\r\nfrom utils import evaluate\r\nfrom matplotlib import pyplot as plt\r\n\r\n\r\n# Argument Parser\r\nparser = argparse.ArgumentParser(descriptio... | [
[
"torch.load"
]
] |
evhub/compiled-cocotest | [
"7bfb1c92ec1f1cea48f12280faf95d3c7ed8b8e0"
] | [
"dest/extras.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# __coconut_hash__ = 0x58bfe0d3\n\n# Compiled with Coconut version 1.4.1 [Ernest Scribbler]\n\n# Coconut Header: -------------------------------------------------------------\n\nfrom __future__ import print_function, absolute_import, unicode_literals, division\nimpor... | [
[
"numpy.array",
"numpy.arange",
"numpy.vectorize"
]
] |
brandontrabucco/cs285 | [
"0ed5fca1d897bf197a43e2be14b204606ae4c36c"
] | [
"cs285/distributions/continuous/tanh_gaussian.py"
] | [
"\"\"\"Author: Brandon Trabucco, Copyright 2019, MIT License\"\"\"\n\n\nfrom cs285.distributions.continuous.gaussian import Gaussian\nimport tensorflow as tf\nimport math\n\n\nclass TanhGaussian(Gaussian):\n\n def __init__(\n self,\n *args,\n std=None,\n **kwargs\n ):\n Gaus... | [
[
"tensorflow.tanh",
"tensorflow.clip_by_value",
"tensorflow.keras.models.clone_model",
"tensorflow.math.softplus"
]
] |
Pgaskins/mycode.py | [
"ba5bbe5a6bb727d535ff5c984f7e6ac9429bbf24"
] | [
"graphing/graphmaker-csvreader.py"
] | [
"#!/usr/bin/python3\n\n# from python std library\nimport csv\n\n# python3 -m pip install np\nimport numpy as np\n# python3 -m pip install matplotlib\nimport matplotlib\nmatplotlib.use('Agg')\n# sudo apt install python3-tk\nimport matplotlib.pyplot as plt\n\ndef parsecsvdata():\n \"\"\"returns a list. [0] is LAN ... | [
[
"matplotlib.use",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.xticks"
]
] |
grebtsew/Object-and-Facial-detection-in-python | [
"57c4bf8d934cc8d6dbaa0cfc56b2b343795ceef1"
] | [
"tensorflow/multi threaded implementation/utils/detect_and_align.py"
] | [
"from six import string_types, iteritems\nfrom scipy import misc\nimport tensorflow as tf\nimport numpy as np\nimport os\nimport cv2\n\n\ndef align_image(img, pnet, rnet, onet):\n margin = 44\n image_size = 160\n\n img_size = np.asarray(img.shape)[0:2]\n bounding_boxes, landmarks, accur = detect_face(im... | [
[
"tensorflow.exp",
"tensorflow.nn.conv2d",
"numpy.minimum",
"numpy.tile",
"numpy.load",
"numpy.mean",
"scipy.misc.imresize",
"tensorflow.reshape",
"numpy.where",
"numpy.zeros_like",
"numpy.empty",
"numpy.flipud",
"tensorflow.variable_scope",
"numpy.transpose"... |
ejmichaud/torch-foresight | [
"e36a8fdd65f0432b9fa25a5127412b081159956b"
] | [
"tests/test_ei.py"
] | [
"import pytest\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom foresight import ei\n\n\n##################################\n#### H ####\n##################################\n\ndef test_H_0():\n x = torch.zeros((4,))\n x[1] = 1\n assert ei.H(x).item() ==... | [
[
"torch.zeros",
"torch.nn.Linear",
"torch.nn.AvgPool2d",
"torch.ones",
"torch.nn.Conv2d",
"torch.tensor",
"torch.flatten",
"torch.randn"
]
] |
HoseungCha/mist-rnns | [
"523d1fa769a7ed29fce22138d1993a8acca28c41"
] | [
"mnist_train.py"
] | [
"import os\nimport sys\nimport argparse\nimport shutil\nimport time\n\nimport numpy as np\nimport tensorflow as tf\n\nimport models\nimport optimizers\nimport utils\n\nimport mnist\n\nINPUT_SIZE = 1\nTARGET_SIZE = 10\nBATCH_SIZE = 100\nVAL_BATCH_SIZE = 100\nNUM_OPT_STEPS = 15000\nNUM_STEPS_PER_TRAIN_SUMMARY = 10\nN... | [
[
"numpy.pad",
"tensorflow.summary.scalar",
"tensorflow.argmax",
"tensorflow.Session",
"tensorflow.train.Saver",
"numpy.mean",
"tensorflow.ConfigProto",
"tensorflow.placeholder",
"numpy.arange",
"tensorflow.to_float",
"numpy.argmax",
"tensorflow.summary.merge_all",
... |
slac-lcls/ami | [
"0feb89248350b80a85689d8230277cea5bf4d470"
] | [
"ami/graph_nodes.py"
] | [
"import abc\nimport operator\nimport numpy as np\nfrom networkfox import operation\n\n\nclass Transformation(abc.ABC):\n\n def __init__(self, **kwargs):\n \"\"\"\n Keyword Arguments:\n name (str): Name of node\n inputs (list): List of inputs\n outputs (list): List o... | [
[
"numpy.roll",
"numpy.zeros"
]
] |
headrockz/data-analysis-challenge | [
"a0bec70654c58698648fd7c7179dd2d451d33f58"
] | [
"utils/load_idh.py"
] | [
"import sqlite3\nimport pandas as pd\n\n\nclass LoadIDH:\n def __init__(self, file):\n self.conn = sqlite3.connect(file)\n self.cursor = self.conn.cursor()\n\n def select(self, municipio):\n consult = 'select id_municipio from municipios where municipio like ?'\n self.cursor.execut... | [
[
"pandas.read_excel"
]
] |
kdatta/tensorpack | [
"963e5100aa2f91d3a4b02f809b2cfbb50be9094e"
] | [
"tensorpack/input_source/input_source_base.py"
] | [
"# -*- coding: utf-8 -*-\n# File: input_source_base.py\n\nimport copy\nfrom abc import ABCMeta, abstractmethod\nfrom contextlib import contextmanager\nimport six\nimport tensorflow as tf\n\nfrom ..callbacks.base import CallbackFactory\nfrom ..tfutils.common import get_op_tensor_name\nfrom ..utils import logger\nfro... | [
[
"tensorflow.name_scope"
]
] |
sharma-arjun/gym | [
"e689f93a425d97489e590bba0a7d4518de0dcc03"
] | [
"gym/envs/classic_control/cartpole.py"
] | [
"\"\"\"\nClassic cart-pole system implemented by Rich Sutton et al.\nCopied from http://incompleteideas.net/sutton/book/code/pole.c\npermalink: https://perma.cc/C9ZM-652R\n\"\"\"\n\nimport math\nimport gym\nfrom gym import spaces, logger\nfrom gym.utils import seeding\nimport numpy as np\n\nclass CartPoleEnv(gym.En... | [
[
"numpy.finfo",
"numpy.array"
]
] |
airqj/maskrcnn-benchmark | [
"210d1abf24d0edf8ee43c3a49c3da9cde6dddad7",
"210d1abf24d0edf8ee43c3a49c3da9cde6dddad7"
] | [
"tools/train_net.py",
"maskrcnn_benchmark/engine/MyInference.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\nr\"\"\"\nBasic training script for PyTorch\n\"\"\"\n\n# Set up custom environment before nearly anything else is imported\n# NOTE: this should be the first import (no not reorder)\nfrom maskrcnn_benchmark.utils.env import setup_environment #... | [
[
"torch.device",
"torch.distributed.init_process_group",
"torch.nn.parallel.DistributedDataParallel",
"torch.cuda.set_device",
"torch.cuda.empty_cache"
],
[
"torch.device",
"torch.no_grad",
"torch.distributed.is_initialized",
"torch.distributed.get_world_size"
]
] |
WolfNiu/AdversarialDialogue | [
"de406d3b624f9500e79bef7c5bc10e24376fefa8"
] | [
"src/basic/ubuntu_data_generator.py"
] | [
"\n# coding: utf-8\n\n# In[1]:\n\n\n\"\"\"\nTodo: combine read_lines, load_pickle, etc... to one single function load_file(),\n and use if statement to see which suffix the file has. Also keep an optional param\n suffix=None just in case we want to force it to load with a certain format\n\n\"\"\"\nfrom random... | [
[
"numpy.percentile"
]
] |
vipermu/dgl | [
"c9ac6c9889423019977e431c8b74a7b6c70cdc01",
"c9ac6c9889423019977e431c8b74a7b6c70cdc01"
] | [
"examples/pytorch/rgcn/link_predict.py",
"examples/pytorch/rgcn/entity_classify.py"
] | [
"\"\"\"\nModeling Relational Data with Graph Convolutional Networks\nPaper: https://arxiv.org/abs/1703.06103\nCode: https://github.com/MichSchli/RelationPrediction\n\nDifference compared to MichSchli/RelationPrediction\n* Report raw metrics instead of filtered metrics.\n* By default, we use uniform edge sampling in... | [
[
"torch.nn.functional.binary_cross_entropy_with_logits",
"torch.arange",
"numpy.mean",
"torch.from_numpy",
"torch.cuda.set_device",
"torch.cuda.is_available",
"torch.LongTensor",
"torch.load",
"torch.nn.init.calculate_gain",
"torch.Tensor",
"torch.nn.Embedding",
"tor... |
Qin-J/Multi-site-transfer-classification-of-major-depressive-disorder | [
"f6af292388ec83a9851a2254f38e8d90adfe4e6c"
] | [
"graph.py"
] | [
"# Copyright (c) 2016 Michaël Defferrard\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitation the rights\n# to use, copy, modify, merg... | [
[
"numpy.array",
"numpy.empty",
"numpy.random.permutation",
"numpy.exp",
"numpy.mean",
"numpy.random.uniform",
"numpy.random.randint",
"numpy.arange",
"numpy.argsort",
"numpy.sqrt",
"numpy.abs",
"numpy.linspace",
"numpy.meshgrid"
]
] |
happy-jihye/alias-free-gan-encoder | [
"d54df2fc1ee57b2d3259e7f64a79b7fbdc6a4631"
] | [
"model.py"
] | [
"import math\r\n\r\nimport torch\r\nfrom torch import nn\r\nfrom torch.nn import functional as F\r\n\r\nfrom stylegan2.model import PixelNorm, EqualLinear, EqualConv2d, ConvLayer, ResBlock\r\nfrom stylegan2.op import conv2d_gradfix, upfirdn2d, fused_leaky_relu\r\n\r\n\r\ndef polyval(coef, x):\r\n res = 0\r\n\r\n... | [
[
"torch.ger",
"torch.cos",
"torch.cat",
"torch.sqrt",
"torch.zeros",
"torch.sinc",
"torch.arange",
"torch.nn.ModuleList",
"torch.nn.Sequential",
"torch.sin",
"torch.norm",
"torch.linspace",
"torch.abs",
"torch.tensor",
"torch.as_tensor",
"torch.randn"... |
cutz-j/AR-project | [
"50d4f407a4f2c42e12bf2bcd54c436df6fa3c9fa",
"50d4f407a4f2c42e12bf2bcd54c436df6fa3c9fa"
] | [
"MobileNetSSD/realsense_ssd.py",
"RealSenseSDK/API_test.py"
] | [
"### TENSORFLOW API: MobilnetV2_SSD ###\n## Import packages ##\nimport numpy as np\nimport os\nimport six.moves.urllib as urllib\nimport sys\nimport tensorflow as tf\nfrom distutils.version import StrictVersion\nfrom collections import defaultdict\nfrom io import StringIO\n## 시각화 Tool ##\nfrom matplotlib import pyp... | [
[
"numpy.zeros_like",
"numpy.zeros",
"tensorflow.Graph",
"tensorflow.Session",
"tensorflow.GraphDef",
"tensorflow.import_graph_def",
"tensorflow.gfile.GFile",
"numpy.frombuffer",
"numpy.squeeze",
"numpy.expand_dims"
],
[
"numpy.asanyarray",
"matplotlib.pyplot.imsh... |
beAWARE-project/crisis-classification | [
"2061a2ee57fd502bd973fdfcffc6d7098049b5ed"
] | [
"main/src/CRCL/FloodCRisisCLassification/CRCL_FLOOD_Forecast_v15.py"
] | [
"# Created Date: 11/09/2018\n# Modified Date: 12/09/2018\n#\n# Implements the 1st algorithm of Crisis Classification module\n# based on the predicted water levels from AMICO for particular 60\n# river sections in the next 54h starting at a specific date/time or\n# the last execution of AMICO module.\n#\n# Groups of... | [
[
"numpy.array",
"pandas.ExcelWriter",
"pandas.DataFrame.from_dict",
"pandas.DataFrame",
"pandas.concat",
"pandas.read_csv"
]
] |
yanxu55/sasoptpy | [
"17006707212c87fdf90ee18b9d23a2c35eae421c",
"17006707212c87fdf90ee18b9d23a2c35eae421c"
] | [
"sasoptpy/utils.py",
"examples/mining_optimization.py"
] | [
"#!/usr/bin/env python\n# encoding: utf-8\n#\n# Copyright SAS Institute\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# U... | [
[
"pandas.set_option",
"pandas.DataFrame.from_dict",
"pandas.DataFrame",
"pandas.MultiIndex.from_tuples",
"pandas.option_context"
],
[
"pandas.DataFrame"
]
] |
Sha-Lab/SynPo | [
"8ac35a01d2c810187b9c14b914bcb792ed73caa9"
] | [
"train_gridworld.py"
] | [
"import logging\nimport argparse\nimport ipdb\nimport random\nfrom datetime import datetime\nfrom itertools import product\nfrom tqdm import tqdm\nimport numpy as np\nimport pickle\nfrom IPython import embed\nfrom ipdb import slaunch_ipdb_on_exception\n\nfrom synpo.agent import *\nfrom synpo.component import *\nfro... | [
[
"numpy.random.randint",
"numpy.mean"
]
] |
Highroad-Consulting/keras-yolo3 | [
"52323cfd21040e96e53ae106a979841c2252a05b"
] | [
"yolo3/model.py"
] | [
"\"\"\"YOLO_v3 Model Defined in Keras.\"\"\"\n\nfrom functools import wraps\n\nimport numpy as np\nimport tensorflow as tf\nfrom keras import backend as K\nfrom keras.layers import Conv2D, Add, ZeroPadding2D, UpSampling2D, Concatenate, MaxPooling2D\nfrom keras.layers.advanced_activations import LeakyReLU\nfrom kera... | [
[
"numpy.array",
"tensorflow.image.non_max_suppression",
"numpy.minimum",
"numpy.argmax",
"numpy.floor",
"tensorflow.boolean_mask",
"numpy.expand_dims",
"numpy.maximum"
]
] |
ayan-iiitd/scikit-learn | [
"02dcedf9ad553a85f43570e78ccbdbb1cea46ef8"
] | [
"sklearn/utils/estimator_checks.py"
] | [
"import types\nimport warnings\nimport pickle\nimport re\nfrom copy import deepcopy\nfrom functools import partial, wraps\nfrom inspect import signature\n\nimport numpy as np\nfrom scipy import sparse\nfrom scipy.stats import rankdata\nimport joblib\n\nfrom . import IS_PYPY\nfrom .. import config_context\nfrom ._te... | [
[
"numpy.mean",
"numpy.where",
"numpy.finfo",
"numpy.sort",
"scipy.stats.rankdata",
"numpy.issubdtype",
"numpy.dtype",
"numpy.full",
"numpy.empty",
"numpy.log",
"pandas.DataFrame",
"numpy.core.numerictypes.allTypes.values",
"numpy.take",
"numpy.arange",
"n... |
Sirius207/Reinforcement-Learning-Algorithms | [
"85a1297c6a03fa8316f53ccee4ad477684f00ef4"
] | [
"dqnSample.py"
] | [
"# From https://towardsdatascience.com/reinforcement-learning-w-keras-openai-dqns-1eed3a5338c\n\nimport gym\nimport numpy as np\nimport random\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout\nfrom keras.optimizers import Adam\n\nfrom collections import deque\n\nclass DQN:\n def __in... | [
[
"numpy.random.random"
]
] |
AmedeoSapio/tensorflow | [
"38e0922d1e2dcd572379af4496f878492e9f689a"
] | [
"tensorflow/python/kernel_tests/lookup_ops_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.ops.lookup_ops.TextFileStringTableInitializer",
"tensorflow.python.ops.lookup_ops.TextFileInitializer",
"tensorflow.python.framework.test_util.assert_ops_in_graph",
"tensorflow.python.framework.ops.get_collection",
"tensorflow.python.platform.test.main",
"tensorflow.pyth... |
goel96vibhor/semisup-adv | [
"30576066663e999d6ae9cc06fd5016d5886dd0b2"
] | [
"ti_cifar_dataset.py"
] | [
"\"\"\"\nDatasets with unlabeled (or pseudo-labeled) data\n\"\"\"\n\nfrom torchvision.datasets import CIFAR10, SVHN, MNIST\nfrom torch.utils.data import Sampler, Dataset\nimport torch\nimport numpy as np# from PIL import Image\nimport cifar_own\nimport qmnist_own\nimport os\nfrom PIL import Image\nimport pickle\n# ... | [
[
"numpy.array",
"torch.Tensor"
]
] |
janismdhanbad/PointCNN | [
"23b7f1873b607ebeb5d63e466a65565405a4909a"
] | [
"data_conversions/prepare_s3dis_data.py"
] | [
"#!/usr/bin/python3\n'''Prepare Data for S3DIS Segmentation Task.'''\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport os\nimport sys\nimport math\nimport h5py\nimport argparse\nimport numpy as np\nfrom datetime import datetime\n\nsys.path.ap... | [
[
"numpy.concatenate",
"numpy.repeat",
"numpy.array",
"numpy.zeros",
"numpy.load",
"numpy.split",
"numpy.random.shuffle",
"numpy.amax",
"numpy.argsort",
"numpy.amin",
"numpy.cumsum",
"numpy.average",
"numpy.unique",
"numpy.floor"
]
] |
hellock/mmaction2 | [
"def3b651ab7818ece637d8637dddacbca027910c"
] | [
"tests/test_dataset.py"
] | [
"import os\nimport os.path as osp\nimport tempfile\n\nimport mmcv\nimport numpy as np\nimport pytest\nfrom numpy.testing import assert_array_equal\n\nfrom mmaction.datasets import (ActivityNetDataset, RawframeDataset,\n RepeatDataset, VideoDataset)\n\n\nclass TestDataset(object):\n\n ... | [
[
"numpy.equal",
"numpy.array",
"numpy.array_equal"
]
] |
zhihansh/federated-oss | [
"38cfcb05702ff7297db76d3ccb5f5afef53ca09b"
] | [
"tensorflow_federated/python/learning/federated_sgd_test.py"
] | [
"# Copyright 2018, The TensorFlow Federated 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.constant",
"tensorflow.keras.layers.Dense"
]
] |
stenczelt/pyGSM | [
"48e7a710744ec768e2c4a0f4d8dc1f9ffd948ce1"
] | [
"pygsm/optimizers/lbfgs.py"
] | [
"\n\n# standard library imports\nimport os\nimport sys\nfrom io import StringIO\n\n# third party\nimport numpy as np\nfrom scipy.optimize.lbfgsb import LbfgsInvHessProduct\n\n# local application imports\nfrom pygsm import utilities\n\nfrom .base_optimizer import base_optimizer\n\n\nclass iterationData:\n \"\"\"d... | [
[
"numpy.zeros_like",
"numpy.linalg.norm",
"numpy.dot",
"numpy.reshape",
"numpy.copy",
"scipy.optimize.lbfgsb.LbfgsInvHessProduct",
"numpy.absolute"
]
] |
MC-kit/mckit-meshes | [
"8aa06ff95ffd1dabac95f399d45047325c265f78"
] | [
"src/mckit_meshes/mesh/geometry_spec.py"
] | [
"\"\"\"Common mesh geometry specification classes and functions.\n\n## Relative or absolute coordinates\n\n There are variations when coordinates are presented as relative to origin\n or absolute. This depends on is output for specification, or input/output\n to Weight of Meshtal files and is it cartesian ... | [
[
"numpy.dot",
"numpy.array_equal",
"numpy.cos",
"numpy.max",
"numpy.sin",
"numpy.linalg.norm",
"numpy.arcsin",
"numpy.logical_and",
"numpy.eye",
"numpy.sqrt",
"numpy.cross",
"numpy.vstack",
"numpy.square",
"numpy.array",
"numpy.zeros",
"numpy.isscalar... |
crcresearch/GOS | [
"a359f54f9477c1785501bd07a05ccbb8d122a0c0"
] | [
"examples/migration/migration.py"
] | [
"import numpy as np\nimport pandas as pd\nimport data as data\nfrom constants import POPULATION_SCALE, MIGRATION_THRESHOLD, PROCESSES, SPLITS, BRAIN_DRAIN_THRESHOLD\nfrom gos import Globe\nimport sys\n\n# The attributes for each agent.\nworld_columns = [\"Country\", \"Income\", \"High Income\", \"Employed\", \"Atta... | [
[
"numpy.random.choice",
"numpy.empty",
"numpy.random.seed",
"numpy.random.mtrand.RandomState",
"numpy.random.randint",
"numpy.dtype"
]
] |
JinheonBaek/pytorch_geometric | [
"dfd32d08a3d8191d6290e53458d4eda515d04fd6"
] | [
"torch_geometric/utils/convert.py"
] | [
"from typing import Optional, Union, Tuple, List\n\nfrom collections import defaultdict\n\nimport torch\nimport scipy.sparse\nfrom torch import Tensor\nfrom torch.utils.dlpack import to_dlpack, from_dlpack\n\nimport torch_geometric.data\n\nfrom .num_nodes import maybe_num_nodes\n\n\ndef to_scipy_sparse_matrix(edge_... | [
[
"torch.utils.dlpack.to_dlpack",
"torch.cat",
"torch.stack",
"torch.is_tensor",
"torch.from_numpy",
"torch.tensor"
]
] |
zhubonan/parsevasp | [
"ac929f324f33e03543f0b4cb4b11eb426aab2199"
] | [
"parsevasp/vasprun.py"
] | [
"#!/usr/bin/python\nimport sys\nimport os\nimport numpy as np\nimport logging\nimport mmap\nimport copy\n\nfrom parsevasp import constants\nfrom parsevasp import utils\nfrom parsevasp.base import BaseParser\n\nfrom lxml import etree\n\n# Try to import lxml, if not present fall back to\n# intrinsic ElementTree\nlxml... | [
[
"numpy.array",
"numpy.asarray",
"numpy.ascontiguousarray",
"numpy.split",
"numpy.swapaxes",
"numpy.append",
"numpy.fromstring"
]
] |
pdxgx/immunorx_response_pipeline | [
"5a3faa72370e96545b46caa790090d022eaa5ece"
] | [
"scripts/process_netctlpan_results.py"
] | [
"#!/usr/bin/env python\n\nfrom __future__ import print_function\nfrom collections import defaultdict\nfrom numpy import median\nimport argparse\nimport glob\nimport os\nimport pickle\n\nif __name__ == \"__main__\":\n\n\t# Parse command line options\n\tparser = argparse.ArgumentParser()\n\tparser.add_argument('-m', ... | [
[
"numpy.median"
]
] |
MW55/ChimeraMATE | [
"0af276fb7c89f529b18348d52d3738bcf84d671e"
] | [
"setup.py"
] | [
"from distutils.core import setup\nfrom Cython.Build import cythonize\nimport numpy\n\nsetup(ext_modules = cythonize('chimeramate_main.pyx'),include_dirs=[numpy.get_include()])\n"
] | [
[
"numpy.get_include"
]
] |
travc/ddtool | [
"33ef02afb4ebf62823f285d1dc6ead125f39bf54"
] | [
"temps2daily_gui.py"
] | [
"#!/usr/bin/env python3\nimport os\nimport tkinter as tk\nfrom tkinter import ttk\nfrom tkinter.scrolledtext import ScrolledText\nimport tkinter.filedialog\nfrom multicolumn_listbox import Multicolumn_Listbox\n\nimport numpy as np\nimport pandas as pd\nfrom collections import OrderedDict as ordereddict\n\nclass App... | [
[
"pandas.read_csv"
]
] |
Nintendofan885/wiki-detox | [
"571a3e4ae13ecf7a564a01bcf16507f0a87351a4"
] | [
"src/analysis/load_utils.py"
] | [
"import os\nimport pandas as pd\nimport re\n\n\ndef load_diffs(keep_diff = False):\n \n nick_map = {\n 'talk_diff_no_admin_sample.tsv': 'sample',\n 'talk_diff_no_admin_2015.tsv': '2015',\n 'all_blocked_user.tsv': 'blocked',\n 'd_annotated.tsv': 'annotated',\n }\n\n base = '..... | [
[
"pandas.to_datetime",
"pandas.read_csv",
"pandas.concat"
]
] |
anisotropi4/goldfinch | [
"eb0f3c76f193e548bbd3b37f3223002431f1cc92"
] | [
"xl2tsv/xl2ndjson.py"
] | [
"#!/usr/bin/env python3\n\nimport pandas as pd\nimport argparse\nimport os\nimport sys\n\nparser = argparse.ArgumentParser(description='Dump xls(x) files tab(s) to .tsv files, to the (default output) path')\n\nparser.add_argument('inputfiles', type=str, nargs='*', help='name of xls-file to process')\n\ntabgroup = p... | [
[
"pandas.read_excel"
]
] |
priyamDalmia/predator-prey | [
"0902e305f029d164966c4c65cf1498d5406fe3ab"
] | [
"data/replay_buffer.py"
] | [
"import random\nimport numpy as np\nimport pdb\nimport gc\n\nclass ReplayBuffer():\n def __init__(self, buffer_size, batch_size, state_size):\n self.buffer_size = buffer_size\n self.batch_size = batch_size\n self.state_size = state_size\n self.counter = 0\n # memory \n s... | [
[
"numpy.random.choice",
"numpy.zeros"
]
] |
YB27/GPy | [
"abef7b3deec593f02cfbed81929b21c660e7069c"
] | [
"GPy/examples/regressionCensored.py"
] | [
"\n''' temporary : Use this to use the forked version of GPy'''\nimport sys\nsys.path.insert(1, '/home/breux/GPy')\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport GPy\n'''\nGaussian Processes regression with censored data example using artificial data as in \n\"Gaussian Process Regression with Censor... | [
[
"numpy.delete",
"numpy.sin",
"matplotlib.pyplot.xlim",
"numpy.ndenumerate",
"numpy.zeros",
"numpy.random.seed",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplots",
"numpy.sqrt",
"numpy.put",
"matplotlib.pyplot.show",
"numpy.linspac... |
flowersteam/TeachMyAgent | [
"a8f71cbfce4cb8ca6da24d00ea690495e3afbd2e",
"a8f71cbfce4cb8ca6da24d00ea690495e3afbd2e",
"a8f71cbfce4cb8ca6da24d00ea690495e3afbd2e"
] | [
"TeachMyAgent/students/openai_baselines/ppo2/model.py",
"TeachMyAgent/students/openai_baselines/common/plot_util.py",
"TeachMyAgent/teachers/utils/torch.py"
] | [
"import tensorflow as tf\nimport functools\n\nfrom TeachMyAgent.students.openai_baselines.common.tf_util import get_session, save_variables, load_variables\nfrom TeachMyAgent.students.openai_baselines.common.tf_util import initialize\n\ntry:\n from TeachMyAgent.students.openai_baselines.common.mpi_adam_optimizer... | [
[
"tensorflow.exp",
"tensorflow.trainable_variables",
"tensorflow.abs",
"tensorflow.train.AdamOptimizer",
"tensorflow.global_variables_initializer",
"tensorflow.variable_scope",
"tensorflow.placeholder",
"tensorflow.clip_by_value",
"tensorflow.maximum",
"tensorflow.clip_by_gl... |
Shafaq-Siddiqi/systemml | [
"5cc523971854cdf4f22e6199987a86e213fae4e2"
] | [
"src/main/python/tests/frame/test_transform_apply.py"
] | [
"# -------------------------------------------------------------\n#\n# 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# ... | [
[
"numpy.isreal"
]
] |
wenshuin/mkpy | [
"52d22b9bac50eede794bacd756869b1600b71ec0"
] | [
"mkpy/events.py"
] | [
"import re\nimport yaml\nimport h5py\nimport numpy as np\nimport pandas as pd\nfrom . import h5tools, mkh5\n\n\ndef read_excel_codemap(file, sheet_name=0):\n \"\"\"Read Excel .xlsx file, return codemap pandas DataFrame.\"\"\"\n\n codemap = pd.read_excel(file, sheet_name=sheet_name, index_col=\"Index\")\n i... | [
[
"pandas.DataFrame",
"pandas.read_excel",
"pandas.read_table",
"pandas.concat"
]
] |
sandialabs/slycat | [
"690e1cb07a6fa990d7206265e18edb22ae3f62e7"
] | [
"web-client/slycat/web/client/cca_random.py"
] | [
"#!/bin/env python\n# Copyright (c) 2013, 2018 National Technology and Engineering Solutions of Sandia, LLC . Under the terms of Contract\n# DE-NA0003525 with National Technology and Engineering Solutions of Sandia, LLC, the U.S. Government\n# retains certain rights in this software.\n\n\"\"\"Demonstrates uploading... | [
[
"numpy.random.seed",
"numpy.random.normal"
]
] |
ZhaoyangLyu/Point_Diffusion_Refinement | [
"9747265a5f141e5546fd4f862bfa66aa59f1bd33"
] | [
"pointnet2/models/pvd/modules/pointnet.py"
] | [
"import torch\nimport torch.nn as nn\n\nimport modules.functional as F\nfrom modules.ball_query import BallQuery\nfrom modules.shared_mlp import SharedMLP\n\n__all__ = ['PointNetAModule', 'PointNetSAModule', 'PointNetFPModule']\n\n\nclass PointNetAModule(nn.Module):\n def __init__(self, in_channels, out_channels... | [
[
"torch.cat",
"torch.nn.ModuleList"
]
] |
cabrittin/volumetric_analysis | [
"82004378abae963ef02858bf4711786dad76f133",
"82004378abae963ef02858bf4711786dad76f133"
] | [
"scripts/varshney_hierarchy.py",
"scripts/logistic_test.py"
] | [
"\"\"\"\nvarshney_hierarchy.py\n\n\n\n\n\"\"\"\n\nimport matplotlib.pyplot as plt\n\nfrom connectome.load import load_lite\nimport networks.hierarchy as hierarchy\nfrom figures.hierarchy import plot_varshney\nimport aux\n\nDB = 'N2U'\nGROUP = './mat/n2u_class_group.txt'\nREMOVE = './mat/n2u_remove.txt'\nTHRESH = 0.... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
],
[
"numpy.log",
"numpy.zeros",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots",
"sklearn.linear_model.LogisticRegression",
"numpy.ravel",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.show",
"... |
pawandeep2155/FixMatch-pytorch | [
"d86dc6d85d3d69518c100edb93b2fc13354191cb"
] | [
"train.py"
] | [
"import argparse\nimport logging\nimport math\nimport os\nimport random\nimport shutil\nimport time\nfrom collections import OrderedDict\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom torch.optim.lr_scheduler import LambdaLR\nfrom torch.utils.data import Data... | [
[
"torch.distributed.get_world_size",
"torch.cat",
"numpy.mean",
"torch.nn.functional.cross_entropy",
"torch.load",
"torch.distributed.init_process_group",
"torch.manual_seed",
"torch.utils.tensorboard.SummaryWriter",
"torch.device",
"torch.cuda.manual_seed_all",
"torch.m... |
sandutsar/jax | [
"409684f9c2d72a93b0d242afde79fc424ede5250"
] | [
"jax/_src/numpy/lax_numpy.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.multiply",
"numpy.sign",
"numpy.where",
"numpy.issubdtype",
"numpy.broadcast_to",
"numpy.dtype",
"numpy.concatenate",
"numpy.iscomplex",
"numpy.uint8",
"numpy.empty",
"numpy.log",
"numpy.arange",
"numpy.ndim",
"numpy.array",
"numpy.delete",
"n... |
AlamiMejjati/controllable_image_synthesis | [
"06f81359d5f10854af275cd313023d9f1e0afd4c"
] | [
"controllable_gan/datasets.py"
] | [
"import os\nimport numpy as np\nimport torchvision\nfrom torchvision.datasets.vision import VisionDataset\nfrom PIL import Image\nimport glob\nfrom collections import Counter\n\n\nclass ObjectDataset(VisionDataset):\n \"\"\"\n Multiple data directories for varying number of objects per scene.\n Folder structure:... | [
[
"numpy.array",
"numpy.random.choice",
"numpy.sum",
"numpy.any",
"numpy.where",
"numpy.expand_dims"
]
] |
rgalhama/wordrep_cmcl2020 | [
"074c268314f94f9eaa02b8a4352608a520447f42"
] | [
"src/evaluation/stats/corr_freq_aoa.py"
] | [
"import statsmodels.api as sm\nimport statsmodels.formula.api as smf\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom scipy.stats import pearsonr\n\ndef plot_with_category(df, title):\n\n fig, ax = plt.subplots()\n sns.scatterplot(x=\"logfreq\", y=\"aoa\",... | [
[
"numpy.log",
"pandas.merge",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots",
"numpy.eye",
"scipy.stats.pearsonr",
"pandas.read_csv"
]
] |
ikervazquezlopez/Pylearn2 | [
"2971e8f64374ffde572d4cf967aad5342beaf5e0",
"2971e8f64374ffde572d4cf967aad5342beaf5e0",
"2971e8f64374ffde572d4cf967aad5342beaf5e0",
"2971e8f64374ffde572d4cf967aad5342beaf5e0"
] | [
"pylearn2/datasets/tests/test_cifar10.py",
"pylearn2/train_extensions/window_flip.py",
"pylearn2/costs/tests/test_term_1_0_l1_penalty.py",
"pylearn2/expr/tests/test_probabilistic_max_pooling.py"
] | [
"import unittest\nimport numpy as np\nfrom pylearn2.datasets.cifar10 import CIFAR10\nfrom pylearn2.space import Conv2DSpace\nfrom pylearn2.testing.skip import skip_if_no_data\n\n\nclass TestCIFAR10(unittest.TestCase):\n\n def setUp(self):\n skip_if_no_data()\n self.test = CIFAR10(which_set='test')\... | [
[
"numpy.all"
],
[
"numpy.zeros"
],
[
"numpy.array"
],
[
"numpy.random.RandomState",
"numpy.allclose",
"numpy.any",
"numpy.abs",
"numpy.all"
]
] |
Chandy002/PySyncObj | [
"aeda3d264aef80e1310aacf770c696e53545b4bd"
] | [
"cs598_benchmarks/plot_cdf_latencies.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport sys\nimport os\nimport json\n\ndef plot_cdf(directory):\n colors = ['#ffc406', 'green', 'blue', 'red']\n i = 0\n for file in os.listdir(directory):\n filename = os.fsdecode(file)\n filepath = os.path.join(directory, filename)\n ... | [
[
"numpy.histogram",
"numpy.array",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.ylabel",
"numpy.append",
"numpy.cumsum",
"matplotlib.pyplot.axis"
]
] |
Linzee/datacatalog-connectors-rdbms | [
"f66072732d3eaec8b982a4e389ba29947c5b6c3d"
] | [
"google-datacatalog-rdbms-connector/src/google/datacatalog_connectors/rdbms/scrape/metadata_scraper.py"
] | [
"#!/usr/bin/python\n#\n# Copyright 2020 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by app... | [
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
Mathiasn21/household_object_detection | [
"4c8a22070fae5e516bce4b704102ae42ae40c3b1"
] | [
"code/resize_images.py"
] | [
"import os\n\nimport cv2\n\nfrom tools.tools import load_json_data, load_image, save_json_data, load_config_file\nimport numpy as np\n\n\ndef calc_new_dimensions(max_size: int, width, height):\n \"\"\"\n Calculate new minimum dimensions and corresponding scalar\n :param max_size: int\n :param width: int... | [
[
"numpy.array"
]
] |
rackerlabs/mlflow | [
"8607e630b77e139756923c7bf513ea6a300acd10"
] | [
"mlflow/pyfunc/scoring_server/__init__.py"
] | [
"\"\"\"\nScoring server for python model format.\nThe passed int model is expected to have function:\n predict(pandas.Dataframe) -> pandas.DataFrame\n\nInput, expected intext/csv or application/json format,\nis parsed into pandas.DataFrame and passed to the model.\n\nDefines two endpoints:\n /ping used for hea... | [
[
"numpy.array",
"pandas.DataFrame",
"pandas.read_json",
"numpy.asscalar",
"pandas.read_csv"
]
] |
asfadmin/hyp3-geocode | [
"aaee8866b8ee0a27203d20e605ada6608f26a392"
] | [
"hyp3_geocode/sentinel.py"
] | [
"\"\"\"Geocode a sentinel-1 granule using Gamma software\"\"\"\n\nimport argparse\nimport datetime\nimport glob\nimport logging\nimport math\nimport os\nimport shutil\nimport zipfile\n\nimport numpy as np\nfrom hyp3lib.asf_geometry import geometry_geo2proj\nfrom hyp3lib.byteSigmaScale import byteSigmaScale\nfrom hy... | [
[
"numpy.reshape",
"numpy.fromfile",
"numpy.floor"
]
] |
thu-spmi/semi-EBM | [
"393e3ea3566dd60c48872a5c573a335e8e802707",
"393e3ea3566dd60c48872a5c573a335e8e802707"
] | [
"train/run_trf_pretrain.py",
"hrf/trfx_semi.py"
] | [
"# Copyright 2020 Tsinghua University, Author: Yunfu Song\n# Apache 2.0.\n# This script contrains TRF unsupervised training experiments.\n\nimport tensorflow as tf\nimport numpy as np\nimport json\nimport os\n\nfrom base import *\nimport trf_uns, nce_net_uns\nimport argparse\n\npaser = argparse.ArgumentParser()\npa... | [
[
"tensorflow.set_random_seed",
"tensorflow.ConfigProto",
"tensorflow.get_default_graph",
"numpy.random.seed"
],
[
"numpy.concatenate",
"numpy.array",
"numpy.linalg.norm",
"numpy.dot",
"numpy.sum",
"numpy.mean"
]
] |
dineshrajdhanapathyDD/selenium-youtube-scraper-live | [
"a0f1f3278165e62a7cf7e26d5f8c099102ea7039"
] | [
"scraper.py"
] | [
"import pandas as pd\nfrom selenium import webdriver\nfrom selenium.webdriver.chrome.options import Options\nfrom selenium.webdriver.common.by import By\n\n\nYOUTUBE_TRENDING_URL = 'https://www.youtube.com/feed/trending'\n\n\ndef get_driver():\n chrome_options = Options()\n chrome_options.add_argument('--no-sandb... | [
[
"pandas.DataFrame"
]
] |
ABohynDOE/mldoe | [
"0987df34a219b07488647ea3434e81cd07da9687"
] | [
"src/mldoe/design.py"
] | [
"# Packages\r\nfrom math import log2\r\nfrom mldoe.matrix import bmat, gmat\r\nfrom mldoe.wlp import wlp\r\nfrom itertools import chain\r\nimport oapackage as oa\r\nfrom typing import List\r\nimport numpy as np\r\n\r\n\r\nclass Design:\r\n \"\"\"\r\n Private meta-class for two-level design (TLD) and mixed-lev... | [
[
"numpy.concatenate",
"numpy.count_nonzero",
"numpy.dot",
"numpy.zeros",
"numpy.eye"
]
] |
812610357/Optics | [
"713759a95f442f2f7f6efb75bbf15d5836029fac"
] | [
"FraunDiffraRecAper.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom math import pi\n\nLambda = 0.5\na = 20\nb = 20\nsintheta1 = np.linspace(-0.12, 0.12, 1201)\nsintheta2 = np.linspace(-0.12, 0.12, 1201)\n\nalpha = pi*a*sintheta1/Lambda\nbeta = pi*b*sintheta2/Lambda\nia = (np.sin(alpha)/alpha)**2\nib = (np.sin(beta)/beta)**2... | [
[
"numpy.sin",
"numpy.dot",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"numpy.sqrt",
"matplotlib.pyplot.show",
"numpy.linspace",
"matplotlib.pyplot.subplot"
... |
manoloesparta/stuff | [
"3cd3c5b6d76593ee3ccad9334f567b68853de9e1"
] | [
"poketsp/main.py"
] | [
"import numpy as np\nimport pandas as pd\n\n\ndef solve(adj):\n visited = {}\n \n start = adj.iloc[0]\n for index, row in adj.iterrows():\n print(\"INDEX: \", index)\n print(\"ROW: \", row)\n\n\ndef main():\n adj = pd.read_csv('adjacency.csv', index_col='compared')\n solve(adj)\n\n\n... | [
[
"pandas.read_csv"
]
] |
dingdingdingyinyinyin/text-cnn | [
"652e69b01bfb6569fb282571d1e446f1087d1c1e"
] | [
"text_test.py"
] | [
"#encoding:utf-8\nfrom __future__ import print_function\nfrom text_model import *\nfrom loader import *\nfrom sklearn import metrics\nimport sys\nimport os\nimport time\nfrom datetime import timedelta\n\n\ndef evaluate(sess, x_, y_):\n data_len = len(x_)\n batch_eval = batch_iter(x_, y_, 128)\n total_loss ... | [
[
"sklearn.metrics.classification_report",
"sklearn.metrics.confusion_matrix"
]
] |
laurencer/recipes | [
"60b7c5f0304c7eb44a39295eba78da02608ae858"
] | [
"torchrecipes/core/base_train_app.py"
] | [
"# Copyright (c) Meta Platforms, Inc. and affiliates.\n#\n# This source code is licensed under the BSD-style license found in the\n# LICENSE file in the root directory of this source tree.\n\n\n#!/usr/bin/env python3\n\n# pyre-strict\n\nimport os\nimport time\nimport traceback\nfrom dataclasses import dataclass\nfr... | [
[
"torch._C._log_api_usage_once"
]
] |
allenai/learning_from_interaction | [
"a266bc16d682832aa854348fa557a30d86b84674",
"a266bc16d682832aa854348fa557a30d86b84674"
] | [
"source/models/poke_rcnn.py",
"source/losses/fgbg_losses.py"
] | [
"import torch\nimport numpy as np\nfrom torch import nn\nfrom random import sample\nfrom detectron2.modeling.meta_arch.rcnn import GeneralizedRCNN\nfrom detectron2.modeling.postprocessing import detector_postprocess\nfrom detectron2.structures import Instances, Boxes, BitMasks\nfrom detectron2.utils.events import E... | [
[
"torch.zeros",
"torch.cat",
"torch.stack",
"torch.no_grad",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"numpy.any",
"torch.nn.Conv2d",
"torch.tensor",
"torch.zeros_like",
"torch.where"
],
[
"torch.stack",
"numpy.zeros"
]
] |
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