repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
Ajithsj96/RealTimeFRuseDeep | [
"a5ebfc1137bc3e8530ffa4423842d3b2ba13954a"
] | [
"model/prediction.py"
] | [
"import argparse\n\nimport feature_utility as fu\nimport myVGG\n\nimport cv2\nimport numpy as np\n\nparser = argparse.ArgumentParser(description=(\"Testing Prediction\"))\nparser.add_argument('--image', help=('Input an image to test model prediction'))\nparser.add_argument('--dataset', help=('Input a directory to t... | [
[
"numpy.expand_dims"
]
] |
ThirstyScholar/trading-bitcoin-with-reinforcement-learning | [
"e2163e954b1f5f656c49fbfb560ddd4635548a91"
] | [
"frl/data.py"
] | [
"import numpy as np\nimport pandas as pd\n\n\nclass Data(object):\n\n def __init__(self, csv_path):\n self.csv_path = csv_path\n self.data = pd.read_csv(csv_path) # read CSV into DataFrame\n self.feat = None\n\n def __len__(self):\n return len(self.data)\n\n def remove_outlier(... | [
[
"pandas.to_datetime",
"pandas.datetime",
"numpy.log",
"pandas.DataFrame",
"pandas.Grouper",
"pandas.read_csv"
]
] |
jabader97/backpack | [
"089daafa0d611e13901fd7ecf8a0d708ce7a5928",
"089daafa0d611e13901fd7ecf8a0d708ce7a5928",
"089daafa0d611e13901fd7ecf8a0d708ce7a5928"
] | [
"test/implementation/implementation_autograd.py",
"backpack/core/derivatives/rnn.py",
"test/core/derivatives/batch_norm_settings.py"
] | [
"import torch\n\nfrom backpack.hessianfree.ggnvp import ggn_vector_product_from_plist\nfrom backpack.hessianfree.hvp import hessian_vector_product\nfrom backpack.hessianfree.rop import R_op\nfrom backpack.utils.convert_parameters import vector_to_parameter_list\n\nfrom .implementation import Implementation\n\n\ncla... | [
[
"torch.zeros_like",
"torch.autograd.grad",
"torch.cat",
"torch.var"
],
[
"torch.zeros",
"torch.cat",
"torch.einsum"
],
[
"torch.rand",
"torch.nn.BatchNorm2d",
"torch.nn.BatchNorm1d",
"torch.nn.BatchNorm3d"
]
] |
josh-gree/NumericalMethods | [
"03cb91114b3f5eb1b56916920ad180d371fe5283"
] | [
"Lectures/tex/codes/lecture9.py"
] | [
"import numpy\n\ndef functional_iteration(f, x0, max_steps=100, tol=1e-10):\n x = numpy.zeros(max_steps+1)\n x[0] = x0\n step = 0\n g = lambda x : x - f(x)\n while abs(f(x[step])) > tol and step < max_steps:\n step = step + 1\n x[step] = g(x[step-1])\n return x[:step+1]\n \nif __n... | [
[
"numpy.zeros"
]
] |
plasmapotential/HEAT | [
"bee84ceffbfc022cdc202ef67c87e469ff6b9e91"
] | [
"source/GUIscripts/plot2DEQ.py"
] | [
"#plotEQ.py\n#Description: Plots Equilibrium (2D) from gfile for pyqt5 application\n#Engineer: T Looby\n#Date: 20190916\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport MDSplus\nimport EFIT.equilParams_class as EP\nfrom scipy import interpolate\nfrom scipy.interpolate import interp1d\n\n... | [
[
"numpy.array",
"matplotlib.pyplot.contourf",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.tick_params",
"matplotlib.pyplot.ylabel",
"numpy.append",
"matplotlib.pyplot.axes",
"numpy.linspace",
"matplotlib.pyplot.con... |
Tarandro/TransTrack | [
"81c12d0737125052f3eb2773ac47be60144f6ccb"
] | [
"datasets/data_prefetcher.py"
] | [
"# ------------------------------------------------------------------------\r\n# Deformable DETR\r\n# Copyright (c) 2020 SenseTime. All Rights Reserved.\r\n# Licensed under the Apache License, Version 2.0 [see LICENSE for details]\r\n# ------------------------------------------------------------------------\r\nimpo... | [
[
"torch.cuda.current_stream",
"torch.cuda.Stream",
"torch.cuda.stream"
]
] |
patrickeganfoley/pyro | [
"3bd5e099e85f3686c66fc3b53476c3b009a77a02",
"3bd5e099e85f3686c66fc3b53476c3b009a77a02"
] | [
"pyro/infer/importance.py",
"pyro/poutine/enum_messenger.py"
] | [
"# Copyright (c) 2017-2019 Uber Technologies, Inc.\n# SPDX-License-Identifier: Apache-2.0\n\nimport math\nimport warnings\n\nimport torch\n\nimport pyro\nimport pyro.poutine as poutine\nfrom pyro.ops.stats import fit_generalized_pareto\n\nfrom .abstract_infer import TracePosterior\nfrom .enum import get_importance_... | [
[
"torch.cat",
"torch.einsum",
"torch.no_grad",
"torch.logsumexp",
"torch.tensor",
"torch.exp",
"torch.sort"
],
[
"torch.zeros",
"torch.arange"
]
] |
shuxiaobo/TextTransferLearning | [
"6fb93bd43dde7012ece1bbe7a5beee0a991ccc43"
] | [
"datasets/binary.py"
] | [
"'''\nBinary classifier and corresponding datasets : MR, CR, SUBJ, MPQA...\n'''\nfrom __future__ import absolute_import, division, unicode_literals\n\nimport io\nimport os\nimport logging\nfrom utils.util import logger\nfrom torch.utils.data import Dataset\nfrom utils.util import prepare_dictionary\nfrom tensorflow... | [
[
"tensorflow.python.keras.preprocessing.sequence.pad_sequences"
]
] |
sanchitvohra/EGVSR | [
"3c0b478179f772d7fe7521655008a2d79a6b6185"
] | [
"codes/torch2onnx.py"
] | [
"import os\nimport os.path as osp\nimport argparse\nimport yaml\nimport time\nimport torch\n\nfrom data import create_dataloader, prepare_data\nfrom models import define_model\nfrom models.networks import define_generator\nfrom utils import base_utils, data_utils\nfrom metrics.model_summary import register, profile... | [
[
"torch.device",
"torch.rand",
"torch.no_grad",
"torch.cuda.empty_cache",
"torch.cuda.is_available"
]
] |
dariaomelkina/UCU-Semester-Homework | [
"c980d467e9eba3ab64c4db36c66c20ac92c7ba00"
] | [
"examples/libs_and_modules_usage_example.py"
] | [
"import json\nimport dash\nimport urllib.request\nimport urllib.parse\nimport dash_core_components as dcc\nimport dash_html_components as html\nimport pandas\nimport plotly.express as px\n\nBASE_URL = \"https://api.nasa.gov/insight_weather/?api_key=DEMO_KEY&feedtype=json&ver=1.0\"\n\n\ndef get_data_from_URL(base_ur... | [
[
"pandas.DataFrame"
]
] |
tpinhoda/Graph-Based_Spatial_Cross_Validation | [
"19300a715d3d03580232926bbc1f6ea8800b23e3"
] | [
"src/paralleling/train_predict/cross_validation.py"
] | [
"import contextlib\nimport os\nimport sys\nimport pandas as pd\nimport geopandas as gpd\nfrom weka.core import jvm\nfrom src import utils\nfrom src.pipeline import Pipeline\nfrom src.visualization.performance import VizMetrics\nfrom src.visualization.dependence import VizDependence\n\n# Set pipeline switchers\nSWIT... | [
[
"pandas.read_csv"
]
] |
jingliinpurdue/Fast-and-Robust-UAV-to-UAV-Detection-and-Tracking | [
"317e85a03f5c374ef8ec53b543208ec36655fa07"
] | [
"util/kalman2d.py"
] | [
"# Opencv 2---Version\n# -*- coding: utf-8 -*-\n'''\n kalman2d - 2D Kalman filter using OpenCV\n \n Based on http://jayrambhia.wordpress.com/2012/07/26/kalman-filter/\n \n Copyright (C) 2014 Simon D. Levy\n \n This code is free software: you can redistribute it and/or modify\n it under the t... | [
[
"numpy.array",
"numpy.float32",
"numpy.zeros"
]
] |
lzamparo/SeqDemote | [
"3eaf18e88c9dc6a3d1a69444ecdba9f9b5d9682a",
"3eaf18e88c9dc6a3d1a69444ecdba9f9b5d9682a"
] | [
"tests/test_train_utils.py",
"src/pytorch_visualize.py"
] | [
"import os \nimport numpy as np\nfrom nose.tools import eq_, ok_\n\nimport torch\nimport utils.train_utils as tr_utils\nimport utils.torch_model_construction_utils as tmu\n\ndef flip_random(data, num_labels):\n ''' return a column of 0,1 labels with num_labels flipped '''\n length = data.shape[0]\n flip_po... | [
[
"numpy.zeros_like",
"numpy.random.binomial",
"numpy.nditer",
"numpy.random.gamma",
"numpy.alltrue",
"numpy.random.randint",
"torch.tensor"
],
[
"torch.jit.get_trace_graph",
"torch.randn",
"torch.onnx.set_training"
]
] |
albpurpura/PLTR | [
"e21d3eb24fb0d269abd68ba23677501c30bb08eb"
] | [
"main_dasalc.py"
] | [
"import argparse\nimport logging\nimport os\nimport time\nimport uuid\n\nimport numpy as np\nimport pyltr\nimport tensorflow as tf\n\nfrom evaluation import compute_mean_ndcg, compute_perf_metrics, create_trec_eval_format_run_qrels\nfrom lambdamart import compute_lambdamart_preds\n# from model import ReRanker\nfrom... | [
[
"numpy.max",
"tensorflow.set_random_seed",
"numpy.array",
"numpy.zeros",
"tensorflow.get_default_graph",
"numpy.random.seed",
"tensorflow.random.set_random_seed",
"tensorflow.reset_default_graph",
"numpy.mean",
"tensorflow.ConfigProto",
"numpy.argmax",
"numpy.argsor... |
kokeshing/espnet | [
"9e2bfc5cdecbb8846f5c6cb26d22010b06e98c40"
] | [
"espnet/tts/pytorch_backend/tts.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n# Copyright 2018 Nagoya University (Tomoki Hayashi)\n# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)\n\n\"\"\"E2E-TTS training / decoding functions.\"\"\"\n\nimport copy\nimport json\nimport logging\nimport math\nimport os\nimport time\n\nimport chaine... | [
[
"torch.cat",
"torch.cuda.is_available",
"torch.LongTensor",
"matplotlib.pyplot.savefig",
"torch.FloatTensor",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.subplot",
"matplotlib.use",
"torch.device",
"numpy.array",
"matplotlib.pyplot.close",
"matplotlib.pyplo... |
JulianKnodt/nerf_atlas | [
"6866713c498cea026cb215260a779a2c6c13246c"
] | [
"scripts/2d_recon.py"
] | [
"import sys\nsys.path[0] = sys.path[0][:-len(\"scripts/\")] # hacky way to treat it as root directory\n\nimport random\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torchvision as tv\nfrom src.neural_blocks import ( SkipConnMLP, FourierEncoder )\nfrom src.utils import ( fat_sigmoid )... | [
[
"torch.cat",
"torch.save",
"torch.no_grad",
"torch.linspace",
"torch.nn.functional.mse_loss",
"torch.randn",
"torch.tensor",
"torch.load",
"torch.nn.Embedding",
"torch.fft.rfft2"
]
] |
ytian81/CarND-Behavioral-Cloning-P3 | [
"df912ae149035330f4e6be8a6c76a3271d522611"
] | [
"finetune.py"
] | [
"from keras.callbacks import EarlyStopping, ModelCheckpoint\nfrom keras.layers import Activation, Conv2D, Cropping2D, Dense, Dropout, Flatten, Lambda, MaxPool2D\nfrom keras.models import Sequential\nfrom keras.regularizers import l2\nfrom keras.callbacks import EarlyStopping, ModelCheckpoint\nfrom keras.models impo... | [
[
"numpy.array",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"numpy.fliplr",
"matplotlib.pyplot.ylabel",
"scipy.ndimage.imread",
"sklearn.utils.shuffle"
]
] |
agramfort/nilearn | [
"f075440e6d97b5bf359bb25e9197dbcbbc26e5f2",
"f075440e6d97b5bf359bb25e9197dbcbbc26e5f2"
] | [
"nilearn/_utils/niimg_conversions.py",
"nilearn/tests/test_testing.py"
] | [
"\"\"\"\nConversion utilities.\n\"\"\"\n# Author: Gael Varoquaux, Alexandre Abraham, Philippe Gervais\n# License: simplified BSD\nimport warnings\n\nimport numpy as np\nimport itertools\nfrom sklearn.externals.joblib import Memory\n\nfrom .cache_mixin import cache\nfrom .niimg import _safe_get_data, load_niimg, new... | [
[
"sklearn.externals.joblib.Memory"
],
[
"numpy.random.RandomState"
]
] |
Mrrrat/asr_project_template | [
"50d264684d90bc45c59f3e9be5766fabaf090d25"
] | [
"hw_asr/trainer/trainer.py"
] | [
"import random\nfrom random import shuffle\n\nimport PIL\nimport torch\nimport torch.nn.functional as F\nfrom torch.nn.utils import clip_grad_norm_\nfrom torchvision.transforms import ToTensor\nfrom tqdm import tqdm\n\nfrom hw_asr.base import BaseTrainer\nfrom hw_asr.logger.utils import plot_spectrogram_to_buf\nfro... | [
[
"torch.no_grad",
"torch.cuda.empty_cache",
"torch.nn.functional.log_softmax"
]
] |
ahgamut/cliquematch | [
"3065b9edfa8ed3dc9986b7152913436ada26d195"
] | [
"tests/test_align.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n cliquematch.test_align\n ~~~~~~~~~~~~~~~~~~~~~~\n\n testcases for cliquematch.AlignGraph\n\n :copyright: (c) 2020 by Gautham Venkatasubramanian.\n :license: see LICENSE for more details.\n\"\"\"\nimport pytest\nimport numpy as np\nimport cliquematch\nimport random\n... | [
[
"numpy.sin",
"numpy.matmul",
"numpy.random.seed",
"numpy.ones",
"numpy.random.uniform",
"numpy.cos"
]
] |
emorynlp/levi-graph-amr-parser | [
"f71f1056c13181b8db31d6136451fb8d57114819"
] | [
"elit/components/parsers/second_order/tree_crf_dependency_parser.py"
] | [
"# -*- coding:utf-8 -*-\n# Author: hankcs\n# Date: 2020-05-08 20:51\nimport functools\nimport os\nfrom typing import Union, Any, List\n\nimport torch\nfrom alnlp.modules.util import lengths_to_mask\nfrom torch import nn\nfrom torch.optim import Adam\nfrom torch.optim.lr_scheduler import ExponentialLR\nfrom torch.ut... | [
[
"torch.no_grad",
"torch.optim.lr_scheduler.ExponentialLR"
]
] |
UtrechtUniversity/SWORDS-UU | [
"d9b45706566054541625ec363e41bdf97f58c6b1"
] | [
"collect_variables/scripts/download_stats.py"
] | [
"\"\"\"Collect download statistics.\n\"\"\"\nimport re\nimport datetime\nimport argparse\nimport json\n\nimport requests\nimport pandas as pd\n\nPYPI_STATS = \"https://pypistats.org/api/packages/{}/recent\"\nCRAN_STATS = \"https://cranlogs.r-pkg.org/downloads/total/last-month/{}\"\nNPM_STATS = \"https://api.npmjs.o... | [
[
"pandas.DataFrame"
]
] |
krantiparida/beyond-image-to-depth | [
"dcdef5122fa456a92bd58ead4eea0a777158c535"
] | [
"util/util.py"
] | [
"#!/usr/bin/env python\nimport numpy as np\nimport os\n\ndef compute_errors(gt, pred):\n \"\"\"Computation of error metrics between predicted and ground truth depths\n \"\"\"\n # select only the values that are greater than zero\n mask = gt > 0\n pred = pred[mask]\n gt = gt[mask]\n\n thresh = n... | [
[
"numpy.log10",
"numpy.abs",
"numpy.maximum"
]
] |
lucidrains/ddpm-proteins | [
"88bfacbd3cbdc4e38585fab420106f56e890c5f7"
] | [
"ddpm_proteins/utils.py"
] | [
"import os\nfrom PIL import Image\nimport seaborn as sn\nimport matplotlib.pyplot as plt\n\nimport torch\nimport torch.nn.functional as F\n\nfrom sidechainnet.utils.sequence import ProteinVocabulary\nfrom einops import rearrange\n\n# general functions\n\ndef exists(val):\n return val is not None\n\ndef default(v... | [
[
"torch.cat",
"torch.no_grad",
"torch.save",
"torch.load",
"matplotlib.pyplot.clf",
"torch.nn.functional.pad",
"torch.hub.load"
]
] |
HQDragon/pandas | [
"8713f2d1237a471a4f42f3fb547887bc022a5b94",
"8713f2d1237a471a4f42f3fb547887bc022a5b94",
"8713f2d1237a471a4f42f3fb547887bc022a5b94"
] | [
"pandas/tests/indexes/test_numpy_compat.py",
"pandas/core/indexes/timedeltas.py",
"pandas/tests/indexes/datetimes/test_datetimelike.py"
] | [
"import numpy as np\nimport pytest\n\nfrom pandas.compat import np_version_under1p17, np_version_under1p18\n\nfrom pandas import (\n DatetimeIndex,\n Float64Index,\n Index,\n Int64Index,\n PeriodIndex,\n TimedeltaIndex,\n UInt64Index,\n)\nimport pandas._testing as tm\nfrom pandas.core.indexes.d... | [
[
"pandas._testing.assert_index_equal",
"pandas._testing.external_error_raised",
"numpy.errstate"
],
[
"pandas.core.indexes.base.maybe_extract_name",
"pandas.core.indexes.base.Index.get_loc",
"pandas._libs.tslibs.to_offset",
"pandas.core.dtypes.common.is_scalar",
"pandas.core.ind... |
maxwellzh/ST-NAS | [
"67d1b91cdc42a30a38fb540922b49c02a3b9c74e"
] | [
"ASR/scripts/toolkit/dataset_pickle.py"
] | [
"'''\nCopyright 2020 SPMI-CAT\nModified by Zheng Huahuan\n'''\nfrom torch.utils.data import Dataset\nimport kaldi_io\nimport numpy as np\nimport torch\nimport sys\nimport pickle\nsys.path.append('./ctc-crf')\n\n\nclass SpeechDataset(Dataset):\n def __init__(self, pickle_path):\n with open(pickle_path, 'rb... | [
[
"torch.IntTensor",
"torch.FloatTensor",
"torch.stack",
"torch.zeros"
]
] |
DiegoHidalgoS/Kats | [
"48f95d141a6241f26f2fdac84418dba430407fb6"
] | [
"kats/detectors/prophet_detector.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\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\n\"\"\"\nThis module contains code to implement the Prophet algorithm\nas a Detector Model.\n\"\"\"\n\nfrom enum import Enum\nfrom typin... | [
[
"pandas.DataFrame",
"pandas.Series",
"numpy.maximum"
]
] |
MrHakimov/toy-store | [
"89b944d86273fe41215f4667d4ac6e9ea4566322"
] | [
"app.py"
] | [
"import datetime, json, re, numpy as np, simplejson, time\nfrom collections import defaultdict\nfrom sqlalchemy.ext.hybrid import hybrid_property\nfrom sqlalchemy.ext.mutable import Mutable\nfrom flask import Flask, request, jsonify\nfrom flask_sqlalchemy import SQLAlchemy\nfrom flask_marshmallow import Marshmallow... | [
[
"numpy.percentile"
]
] |
JungHunOh/liif | [
"c4445bf4b4adf25cae66d760fc590b80e627f0d7"
] | [
"train_liif.py"
] | [
"\"\"\" Train for generating LIIF, from image to implicit representation.\r\n\r\n Config:\r\n train_dataset:\r\n dataset: $spec; wrapper: $spec; batch_size:\r\n val_dataset:\r\n dataset: $spec; wrapper: $spec; batch_size:\r\n (data_norm):\r\n inp: {sub: []; div: ... | [
[
"torch.FloatTensor",
"torch.optim.lr_scheduler.MultiStepLR",
"torch.nn.L1Loss",
"torch.utils.data.DataLoader",
"torch.load",
"torch.nn.parallel.DataParallel"
]
] |
vandbt/pyblur | [
"5a31b6ced59a4cdef30eafebf0f7c27135d19d34"
] | [
"LinearMotionBlur.py"
] | [
"# -*- coding: utf-8 -*-\r\nimport math\r\nimport numpy as np\r\nfrom PIL import Image\r\nfrom scipy.signal import convolve2d\r\nfrom skimage.draw import line\r\n\r\nfrom LineDictionary import LineDictionary\r\n\r\nlineLengths =[3,5,7,9]\r\nlineTypes = [\"full\", \"right\", \"left\"]\r\n\r\nlineDict = LineDictionar... | [
[
"numpy.array",
"numpy.count_nonzero",
"numpy.zeros",
"numpy.abs",
"numpy.linspace",
"scipy.signal.convolve2d"
]
] |
ScriptBox99/deepmind-sonnet | [
"5cbfdc356962d9b6198d5b63f0826a80acfdf35b"
] | [
"sonnet/src/conformance/pickle_test.py"
] | [
"# Copyright 2019 The Sonnet 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 required ... | [
[
"tensorflow.test.main"
]
] |
Mandorath/analyze_ais | [
"335a5185a588f99a8151ea77e2406e8cec43ffcb"
] | [
"stats_ais.py"
] | [
"import pandas as pd\nimport numpy as np\n\n\ndef calc_stats(df, col_ais, col_spd, col_zn, unique_col, date, df_out, ship_count):\n '''\n Statistics calculation function.\n '''\n # df = pd.read_csv(file, delimiter=\",\")\n # the percentage of \"True\" in AIS gaps\n df['spd_and_gap'] = pd.np.where(... | [
[
"pandas.DataFrame"
]
] |
Heron-Repositories/Transfer-Learning-In-Animals | [
"96a49f1ca27c62defaf3ea90f0dd6640034c8541"
] | [
"Transforms/Transfer_Learning/TL_Experiment_Phase_2/tl_experiment_phase_2_worker.py"
] | [
"\r\nimport sys\r\nfrom os import path\r\n\r\ncurrent_dir = path.dirname(path.abspath(__file__))\r\nwhile path.split(current_dir)[-1] != r'Heron':\r\n current_dir = path.dirname(current_dir)\r\nsys.path.insert(0, path.dirname(current_dir))\r\n\r\nimport copy\r\nimport numpy as np\r\nfrom enum import Enum\r\nfrom... | [
[
"numpy.max",
"numpy.array",
"numpy.random.binomial",
"numpy.empty",
"numpy.min",
"numpy.random.randint"
]
] |
iamxiaodong/Kats | [
"31df55acc22797ce06330586542fe6e5f315e574"
] | [
"kats/models/metalearner/metalearner_modelselect.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\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\n# pyre-unsafe\n\n\"\"\"A module for meta-learner model selection.\n\nThis module contains:\n - :class:`MetaLearnModelSelect` for met... | [
[
"numpy.random.choice",
"pandas.concat",
"pandas.DataFrame",
"matplotlib.pyplot.subplots",
"sklearn.metrics.accuracy_score",
"sklearn.svm.SVC",
"numpy.arange",
"numpy.array",
"sklearn.ensemble.RandomForestClassifier",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.na... |
amsword/maskrcnn-benchmark | [
"660457d5f28c5d7d7887829486a20c60976b1dd8"
] | [
"maskrcnn_benchmark/modeling/backbone/resnet_fast.py"
] | [
"# This file cames from Xiyang Dai\n\nimport torch.nn as nn\nfrom torch.nn import BatchNorm2d\nfrom maskrcnn_benchmark.modeling.make_layers import frozen_batch_norm\nfrom maskrcnn_benchmark.layers.batch_norm import FrozenBatchNorm2d\n\ndef conv3x3(in_planes, out_planes, stride=1):\n \"\"\"3x3 convolution with pa... | [
[
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.Sequential",
"torch.nn.MaxPool2d"
]
] |
FloCF/pytorch | [
"383a33a0eb28ae454c0c8965650aea8ce1608943"
] | [
"test/distributed/test_c10d_nccl.py"
] | [
"import copy\nimport math\nimport os\nimport random\nimport signal\nimport sys\nimport tempfile\nimport threading\nimport time\nfrom contextlib import contextmanager\nfrom datetime import timedelta\nfrom itertools import product\nfrom unittest import mock\n\nimport torch\nimport torch.distributed as c10d\n\nif not ... | [
[
"torch.nn.Linear",
"torch.distributed.rendezvous",
"torch.distributed.get_world_size",
"torch.distributed._get_debug_mode",
"torch.testing._internal.common_utils.find_free_port",
"torch.randperm",
"torch.distributed._broadcast_coalesced",
"torch.ones",
"torch.cuda.FloatTensor",... |
disanda/MSV | [
"066ed236a4c5df8b4b5e366020fe2954b7a6915a"
] | [
"ablation-study/1.E_align_z.py"
] | [
"import sys\nsys.path.append(\"..\")\nimport os\nimport math\nimport torch\nimport torchvision\nimport model.E.Ablation_Study.E_Blur_Z as BE\nfrom model.utils.custom_adam import LREQAdam\nimport metric.pytorch_ssim as pytorch_ssim\nimport lpips\nimport numpy as np\nimport tensorboardX\nimport argparse\nfrom model.s... | [
[
"torch.device",
"torch.cat",
"torch.arange",
"torch.ones",
"torch.load",
"torch.randn",
"torch.where"
]
] |
jcharlong/scipy | [
"153467a9174b0c6f4b90ffeed5871e5018658108",
"153467a9174b0c6f4b90ffeed5871e5018658108",
"153467a9174b0c6f4b90ffeed5871e5018658108",
"153467a9174b0c6f4b90ffeed5871e5018658108"
] | [
"benchmarks/benchmarks/linalg.py",
"scipy/stats/tests/test_mstats_basic.py",
"scipy/optimize/tests/test_optimize.py",
"scipy/fft/__init__.py"
] | [
"import math\n\nimport numpy.linalg as nl\n\nimport numpy as np\nfrom numpy.testing import assert_\nfrom numpy.random import rand\n\nfrom .common import Benchmark, safe_import\n\nwith safe_import():\n import scipy.linalg as sl\n\n\ndef random(size):\n return rand(*size)\n\n\nclass Bench(Benchmark):\n param... | [
[
"scipy.linalg.toeplitz",
"numpy.random.rand",
"scipy.linalg.svd",
"scipy.linalg.tri",
"numpy.finfo",
"scipy.linalg.cholesky",
"scipy.linalg.solve_triangular",
"scipy.linalg.solve",
"scipy.linalg.eigvals",
"scipy.linalg.dft",
"numpy.linalg.norm",
"scipy.linalg.block_... |
jimgoo/metaflow-tabular | [
"66b02c1d53b1a64d19b4fc2f7f4a5f9a5ab1b422"
] | [
"metaflow_tabular/forecasting_flow.py"
] | [
"\"\"\"\nTo run this flow:\n```python forecasting_flow.py --environment=conda run```\n\"\"\"\n\nfrom functools import partial\n\nfrom metaflow import (\n Flow,\n FlowSpec,\n IncludeFile,\n Parameter,\n batch,\n conda,\n conda_base,\n get_metadata,\n parallel_map,\n step,\n)\n\nfrom pip... | [
[
"pandas.to_datetime",
"pandas.DataFrame",
"numpy.mean",
"pandas.read_csv",
"pandas.infer_freq"
]
] |
axdahl/SC-MMGP | [
"c6cd9d9de66bb7074925a4b6485f10a74bdd9f68"
] | [
"examples/flight_delays/logcox_implicit_scmmgp.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nScript to execute example implicit sparse covarying MMGP with Poisson likelihood.\r\nThe model invokes the 'implicit' sparse model class and accepts a degenerate kernel\r\nthat is optionally corrected within the model class with diagonal correction.\r\n\r\nInputs: Data training... | [
[
"numpy.concatenate",
"tensorflow.train.AdamOptimizer",
"numpy.savetxt",
"numpy.mean",
"pandas.read_csv"
]
] |
opplatek/fivepseq | [
"9a531520e29aa9b3edbf1823c6cfd249f97bba9b"
] | [
"fivepseq/logic/structures/fivepseq_counts.py"
] | [
"import collections\nimport logging\nimport os\nfrom math import floor\n\nimport numpy as np\nimport pandas as pd\nimport plastid\nfrom preconditions import preconditions\nfrom scipy import stats\n\nfrom fivepseq import config\nfrom fivepseq.logic.structures import codons\nfrom fivepseq.logic.structures.codons impo... | [
[
"numpy.count_nonzero",
"numpy.asarray",
"pandas.DataFrame",
"numpy.sum",
"numpy.mean",
"numpy.argmax",
"numpy.arange",
"numpy.floor",
"pandas.Series",
"pandas.read_csv",
"numpy.vstack",
"scipy.stats.poisson.cdf"
]
] |
junkilee/simple_baselines | [
"cc5cc4b8d83119bf144abb08900762b76b1a33ac"
] | [
"baselines/deepq/build_graph.py"
] | [
"\"\"\"Deep Q learning graph\n\nThe functions in this file can are used to create the following functions:\n\n======= act ========\n\n Function to chose an action given an observation\n\n Parameters\n ----------\n observation: object\n Observation that can be feed into the output of make_obs_ph\n... | [
[
"tensorflow.constant_initializer",
"tensorflow.group",
"tensorflow.stack",
"tensorflow.control_dependencies",
"tensorflow.nn.softmax",
"tensorflow.one_hot",
"tensorflow.trainable_variables",
"tensorflow.shape",
"tensorflow.argmax",
"tensorflow.Variable",
"tensorflow.var... |
tkuri/pytorch-CycleGAN-and-pix2pix | [
"b00b3f0bcebfb12d3f026c2a61c98ff63175a583"
] | [
"data/aligned3_tm_max_dataset.py"
] | [
"import os.path\nfrom data.base_dataset import BaseDataset, get_params, get_transform\nfrom data.image_folder import make_dataset\nfrom PIL import Image, ImageOps\nimport torch\n\nclass Aligned3TmMaxDataset(BaseDataset):\n \"\"\"A dataset class for paired image dataset.\n\n It assumes that the directory '/pat... | [
[
"torch.unsqueeze"
]
] |
alat-rights/pytorch-lightning | [
"a4f1f3dc28982eb6578df62ca92b93f83a2defcc"
] | [
"pytorch_lightning/strategies/ddp.py"
] | [
"# Copyright The PyTorch Lightning team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager",
"torch.distributed.optim.PostLocalSGDOptimizer",
"torch.distributed.broadcast_object_list",
"torch.nn.parallel.distributed.DistributedDataParallel",
"torch.distributed.get_backend",
"torch.cuda.empty_cache",
... |
vonguyenleduy/dnn_representation_selective_inference | [
"ea9924950441d30d2619a235551673f089f5a54f"
] | [
"ex3_len_interval_proposed_oc.py"
] | [
"import numpy as np\r\nfrom tensorflow.keras.models import load_model\r\nimport tensorflow as tf\r\nimport time\r\n\r\nimport gen_data\r\nimport util\r\n\r\n\r\ndef run():\r\n d = 8\r\n IMG_WIDTH = d\r\n IMG_HEIGHT = d\r\n IMG_CHANNELS = 1\r\n mu_1 = 0\r\n mu_2 = 2\r\n\r\n global_list_ineq = []... | [
[
"numpy.dot"
]
] |
tommccoy1/copynet | [
"6bc6f3a81a4922d06bdd9e86dcd7125251282076"
] | [
"transformer.py"
] | [
"\n# From https://github.com/ischlag/TP-Transformer\n\nimport math\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\ndef build_transformer(input_dim=None, hidden=None, dropout=None, max_length=None, n_layers=None, n_heads=None, myfilter=None, pad_idx=None):\n\n embedding = TokenEmbedding... | [
[
"torch.zeros",
"torch.cos",
"torch.nn.Dropout",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.argmax",
"torch.sin",
"torch.einsum",
"torch.cat",
"torch.arange",
"torch.FloatTensor",
"torch.nn.init.xavier_uniform_",
"torch.ones",
"torch.nn.functional.softma... |
anonymous191116/S3ED | [
"250b3e39db7dfa9d2212795b6d9ea428acfa907b",
"250b3e39db7dfa9d2212795b6d9ea428acfa907b"
] | [
"datasets/helper functions/combine_A_and_B.py",
"data/extrac_features.py"
] | [
"from pdb import set_trace as st\nimport os\nimport numpy as np\nimport cv2\nimport argparse\n\nparser = argparse.ArgumentParser('create image pairs')\nparser.add_argument('--fold_A', dest='fold_A', help='input directory for image A', type=str,\n default='/media/disk2/daic/blur_data/3_14GAN/GAN_G... | [
[
"numpy.concatenate"
],
[
"numpy.concatenate",
"torch.no_grad"
]
] |
pjgrandinetti/mrsimulator | [
"01b447239d9f469df62b7293a74a3d0c34500a19",
"01b447239d9f469df62b7293a74a3d0c34500a19"
] | [
"examples_source/1D_simulation(crystalline)/plot_6_coupled_spin_system.py",
"tests/2D_spectrum_tests/test_ssb.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\nCoupled spins 5/2-9/2 (Quad + J-coupling)\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n²⁷Al-⁹³Nb spin system spectrum.\n\"\"\"\n# %%\nimport matplotlib.pyplot as plt\n\nfrom mrsimulator import Simulator, SpinSystem\nfrom mrsimulator.methods import BlochDecay... | [
[
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.show",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.figure"
],
[
"numpy.testing.assert_almost_equal",
"numpy.where"
]
] |
csm-adapt/karon | [
"988ef07eb9339b6dea3babd4f31337bce7b5d5e4"
] | [
"src/karon/tree/build.py"
] | [
"__all__ = [\"generate_tree\", \"from_parent\"]\n\n\nimport warnings\nimport numpy as np\n\n\ndef generate_tree(get_nodeid, get_parent, cmp=None):\n \"\"\"\n Defines the functions required to (a) extract a field from a\n node, (b) extract a field from a prospective parent node, and (c)\n compare the res... | [
[
"numpy.isnan"
]
] |
Qottmann/pennylane | [
"ba7cb0d27965bdb642d29648d70dd8246432eec0"
] | [
"pennylane/_qubit_device.py"
] | [
"# Copyright 2018-2021 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.array",
"numpy.empty",
"numpy.random.choice",
"numpy.zeros",
"numpy.mean",
"numpy.prod",
"numpy.arange",
"numpy.var",
"numpy.argsort",
"numpy.unique"
]
] |
HappyBall/asr_guided_tacotron | [
"be36f0895b81e338c5c51a7ab6d421fbf3aa055b"
] | [
"synthesize.py"
] | [
"'''\nmodified from\nhttps://www.github.com/kyubyong/tacotron\n'''\n\nfrom hyperparams import Hyperparams as hp\nimport tqdm\nfrom data_load import load_data\nimport tensorflow as tf\nfrom train import Graph\nfrom utils import spectrogram2wav\nfrom scipy.io.wavfile import write\nimport os\nimport numpy as np\n\n\nd... | [
[
"tensorflow.train.latest_checkpoint",
"tensorflow.Session",
"numpy.tile",
"tensorflow.train.Saver"
]
] |
amir-rahim/BookClubSocialNetwork | [
"b69a07cd33592f700214252a64c7c1c53845625d"
] | [
"BookClub/management/commands/importuserstargeted.py"
] | [
"from django.core.management.base import BaseCommand\nimport random\nfrom faker import Faker\nimport pandas as pd\nfrom pandas import DataFrame\nimport time\nfrom BookClub.management.commands.helper import get_top_n_books, get_top_n_users_who_have_rated_xyz_books, get_top_n_books_shifted\n\nfrom BookClub.models.use... | [
[
"pandas.read_csv"
]
] |
openghg/openghg | [
"9a05dd6fe3cee6123898b8f390cfaded08dbb408"
] | [
"tests/standardise/surface/test_glasgow_licor.py"
] | [
"from helpers import get_mobile_datapath\nfrom openghg.standardise.surface import parse_glasow_licor\nfrom pandas import Timestamp\nimport pytest\n\n\ndef test_glasgow_licor_read():\n test_data = get_mobile_datapath(filename=\"glasgow_licor_sample.txt\")\n data = parse_glasow_licor(filepath=test_data)\n\n ... | [
[
"pandas.Timestamp"
]
] |
hwangoh/uq-vae | [
"24a3d26987e2ec807d57601b14c68b22f3652a18",
"24a3d26987e2ec807d57601b14c68b22f3652a18",
"24a3d26987e2ec807d57601b14c68b22f3652a18"
] | [
"codes/projects/test_continuous_parameter/utils_project/prediction_and_plotting_routine_vaeiaf.py",
"codes/projects/test_continuous_parameter/utils_project/training_routine_vae_full_model_aware.py",
"codes/projects/advection_diffusion_2d/utils_project/construct_prior_dict.py"
] | [
"'''Prediction and plotting routine\n\nIn preparation for prediction and plotting, this script will:\n 1) Load the obs_dimensions\n 2) Specify the input_dimensions and latent_dimensions\n 3) Instantiate the DataHandler class\n 4) Instantiate the neural network\n 5) Load the trained neural network wei... | [
[
"numpy.log",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.close",
"numpy.linspace",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.ioff",
"pandas.read_csv",
... |
ajspera/pandas | [
"f38020f33052ea9029b410d7fae79bc8f249c0ac",
"f38020f33052ea9029b410d7fae79bc8f249c0ac"
] | [
"pandas/tests/arithmetic/test_object.py",
"pandas/tests/groupby/aggregate/test_other.py"
] | [
"# Arithmetic tests for DataFrame/Series/Index/Array classes that should\n# behave identically.\n# Specifically for object dtype\nfrom decimal import Decimal\nimport operator\n\nimport numpy as np\nimport pytest\n\nimport pandas as pd\nfrom pandas import Series, Timestamp\nfrom pandas.core import ops\nimport pandas... | [
[
"pandas.Index",
"numpy.array",
"pandas.Timedelta",
"pandas.util.testing.box_expected",
"pandas.util.testing.makeObjectSeries",
"pandas.util.testing.assert_index_equal",
"numpy.random.randn",
"pandas.util.testing.assert_series_equal",
"pandas.Timestamp.now",
"pandas.Timestam... |
AndrewWangJZ/pyfem | [
"8e7df6aa69c1c761bb8ec67302847e30a83190b4"
] | [
"1D_example.py"
] | [
"import numpy as np\nimport scipy.integrate.quadrature as integrator\n\n\"\"\"\n An 1-dimensional linear problem is used to describe the FEM process\n \n reference:\n [1] https://www.youtube.com/watch?v=rdaZuKFK-4k\n \n\"\"\"\n\n\nclass OneDimensionalProblem:\n def __init__... | [
[
"numpy.zeros_like",
"numpy.array",
"numpy.linspace",
"numpy.sqrt"
]
] |
cookish/deeptile | [
"159275b4d63286dd6ad08010a4e457ba9af9ae2d"
] | [
"python/check_docker.py"
] | [
"import requests\nimport numpy as np\nimport json\n\nimport include.board_utilities as board_utilities\n\nhost = 'localhost'\nport = '8503'\n\ntest_boards = np.empty(shape=1000, dtype=\"uint64\")\nfor i in range(1000):\n test_boards[i] = 0xfedcba9876543210 + i\n\ntest_board_arr = board_utilities.int_to_arr(test_... | [
[
"numpy.empty"
]
] |
shanaxel42/napari | [
"d182b3694deb185afcf8b6ae2e87cccb78d7f82b"
] | [
"napari/layers/image/image.py"
] | [
"import types\nimport warnings\nfrom base64 import b64encode\nfrom xml.etree.ElementTree import Element\n\nimport numpy as np\nfrom imageio import imwrite\nfrom scipy import ndimage as ndi\n\nfrom ...utils.colormaps import AVAILABLE_COLORMAPS\nfrom ...utils.event import Event\nfrom ...utils.status_messages import f... | [
[
"numpy.divide",
"numpy.max",
"numpy.array",
"numpy.concatenate",
"numpy.full",
"numpy.asarray",
"numpy.zeros",
"numpy.round",
"numpy.copy",
"numpy.ones",
"numpy.any",
"numpy.clip",
"numpy.all",
"scipy.ndimage.zoom",
"numpy.dtype"
]
] |
Strabes/h2o-prod | [
"2bfd4c87302c2ca3219b0bc313f13c9e787d84ad"
] | [
"_build/jupyter_execute/Score_LendingClub.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# # MOJO Scoring: Two Approaches\n# \n# Now we will use the model we built on the Lending Club data to score the test cases we pickled. To mimick the scoring performance we would experience if the model were implemented in a real-time environment, we will score the records... | [
[
"pandas.read_pickle",
"pandas.DataFrame",
"pandas.concat"
]
] |
radiasoft/rs_synergia | [
"b43509de7f4a938354dc127762d8e723463e0e95"
] | [
"rssynergia/base_diagnostics/write_bunch.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"?\n\n:copyright: Copyright (c) 2020 RadiaSoft LLC. All Rights Reserved.\n:license: http://www.apache.org/licenses/LICENSE-2.0.html\n\"\"\"\nfrom __future__ import absolute_import, division, print_function\nimport synergia\nimport numpy as np\nimport h5py\n\ndef write_bunch(bunch, f... | [
[
"numpy.savetxt"
]
] |
marcovarrone/squidpy | [
"fb68a913db0e0daaabeab69df308461ecaba1268"
] | [
"squidpy/im/_process.py"
] | [
"from types import MappingProxyType\nfrom typing import Any, Union, Mapping, Callable, Optional, Sequence\n\nfrom scanpy import logging as logg\n\nfrom dask import delayed\nfrom scipy.ndimage.filters import gaussian_filter as scipy_gf\nimport numpy as np\nimport dask.array as da\n\nfrom skimage.color import rgb2gra... | [
[
"numpy.array"
]
] |
Jovioluiz/IA | [
"35247c782747a972e73a723608e71faa70cb6916"
] | [
"Trabalho LSTM/trabalho_LSTM.py"
] | [
"import pandas as pd\r\nfrom tensorflow import keras\r\nfrom keras.models import Sequential\r\nfrom keras.layers import Dense, Dropout, LSTM\r\nimport plotly.graph_objects as go\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport seaborn as sns\r\n# %matplotlib inline\r\n\r\nDataSet=pd.read_csv('cota... | [
[
"numpy.array",
"numpy.reshape",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"numpy.roll",
"matplotlib.pyplot.show",
"sklearn.preprocessing.MinMaxScaler",
"pandas.concat",
"matplotlib.pyplot.ylabel",
"m... |
donproc/Paddle | [
"75dadd586996c71cf5b088b6141b94705561773f"
] | [
"python/paddle/fluid/tests/unittests/test_multiply.py"
] | [
"# Copyright (c) 2020 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.random.rand",
"numpy.random.seed",
"numpy.random.randn",
"numpy.multiply",
"numpy.allclose"
]
] |
Derek-Wds/MAD-VAE | [
"267ce6ca98f1b1ecc8ebec22ddeca32e2c502d5b"
] | [
"experiments/gen_white_table.py"
] | [
"import json\nimport numpy as np\n\nif __name__ == \"__main__\":\n models = {'vanilla': 0, 'classification': 0, 'proxi_dist': 0, 'combined': 0}\n models_list = ['vanilla', 'classification', 'proxi_dist', 'combined'] # for consistency in older versions\n\n for flavor in models_list:\n with open(f'./a... | [
[
"numpy.argmax"
]
] |
zx-sdu/NodeFinder | [
"edaeeba8fb5a1ca28222313f6de7a6dfa8253093"
] | [
"tests/search/test_nodal_surface.py"
] | [
"# -*- coding: utf-8 -*-\n\n# © 2017-2019, ETH Zurich, Institut für Theoretische Physik\n# Author: Dominik Gresch <greschd@gmx.ch>\n\"\"\"\nTests with a nodal line.\n\"\"\"\n\nimport numpy as np\nimport pytest\n\nfrom nodefinder.search import run\nfrom nodefinder.search.refinement_stencil import get_mesh_stencil\n\... | [
[
"numpy.array"
]
] |
gicsaw/ARAE_SMILES | [
"05cd508be0450ad0e8944e6280b8fa2863cc8dd0"
] | [
"gen_CARAE_con_logP_SAS_TPSA.py"
] | [
"from model.CARAE import ARAE\n#from utils.utils import *\nimport numpy as np\nimport os, sys\nimport time\nimport tensorflow as tf\nimport collections\nimport copy\nfrom six.moves import cPickle\n#os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"\n\ndef convert_to_smiles(vector, char):\n smiles=\"\"\n for i in vec... | [
[
"numpy.random.normal",
"numpy.array",
"numpy.array_equal",
"numpy.reshape",
"numpy.empty",
"numpy.save",
"numpy.argmax"
]
] |
BolachasDaAvo/PyTorch-StudioGAN | [
"21d0f1d976d0c5c3d240295e9efa83c105e40ac7",
"21d0f1d976d0c5c3d240295e9efa83c105e40ac7"
] | [
"src/utils/resize.py",
"src/utils/style_ops/filtered_lrelu.py"
] | [
"\"\"\"\nMIT License\n\nCopyright (c) 2021 Gaurav Parmar\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modif... | [
[
"numpy.concatenate",
"torch.nn.functional.interpolate",
"numpy.asarray"
],
[
"torch.zeros",
"torch.cuda.current_stream",
"torch.ones",
"torch.cuda.default_stream",
"numpy.sqrt",
"torch.empty"
]
] |
SeanNaren/aitextgen | [
"12a647cd6e8f2a9f8b0dfa5e380ad50d10a527cd"
] | [
"aitextgen/train.py"
] | [
"import pytorch_lightning as pl\nfrom pytorch_lightning.callbacks.progress import ProgressBarBase\nfrom tqdm.auto import tqdm\nimport sys\nimport torch\nfrom torch.optim import AdamW\nfrom torch.utils.data import DataLoader\nfrom transformers import get_linear_schedule_with_warmup\nimport os\nimport shutil\nimport ... | [
[
"torch.as_tensor",
"torch.cuda.empty_cache",
"torch.optim.AdamW",
"torch.utils.data.DataLoader"
]
] |
urasakikeisuke/segmenter | [
"69ff016e621b7d1e4b8573a8b150e80dbc70cf84"
] | [
"segm/utils/torch.py"
] | [
"import os\nimport torch\n\n\n\"\"\"\nGPU wrappers\n\"\"\"\n\nuse_gpu = False\ngpu_id = 0\ndevice = None\n\ndistributed = False\ndist_rank = 0\nworld_size = 1\n\n\ndef set_gpu_mode(mode):\n global use_gpu\n global device\n global gpu_id\n global distributed\n global dist_rank\n global world_size\n... | [
[
"torch.device"
]
] |
anton-buyskikh/QuSpin | [
"4e46b495e399414d9361d659e186492a1ac5b511"
] | [
"quspin/tools/expm_multiply_parallel_core/expm_multiply_parallel_core.py"
] | [
"from scipy.sparse.linalg import LinearOperator,onenormest,aslinearoperator\nfrom .expm_multiply_parallel_wrapper import _wrapper_expm_multiply,_wrapper_csr_trace\nimport scipy.sparse as _sp\nimport numpy as _np\n\nclass expm_multiply_parallel(object):\n\t\"\"\"Implements `scipy.sparse.linalg.expm_multiply()` for *... | [
[
"numpy.result_type",
"numpy.array",
"numpy.ceil",
"numpy.asarray",
"numpy.zeros",
"numpy.ascontiguousarray",
"numpy.finfo",
"scipy.sparse.linalg.aslinearoperator",
"scipy.sparse.identity",
"numpy.sqrt",
"numpy.abs",
"scipy.sparse.csr_matrix",
"numpy.floor"
]
] |
mlilab/Mixed-Effect-Composite-RNN-Gaussian-Process | [
"dd7da89ce3c41d459a26ad1ce5ed2f40ab4ca85d"
] | [
"GPflow/testing/test_triang.py"
] | [
"import unittest\nfrom gpflow.tf_wraps import vec_to_tri\nimport tensorflow as tf\nimport numpy as np\n\nfrom testing.gpflow_testcase import GPflowTestCase\nfrom gpflow.tf_wraps import vec_to_tri\n\n\nclass TestVecToTri(GPflowTestCase):\n def referenceInverse(self, matrices):\n\t\t#this is the inverse operation ... | [
[
"numpy.ones_like",
"numpy.zeros",
"numpy.random.RandomState",
"tensorflow.gradients",
"numpy.testing.assert_array_almost_equal",
"tensorflow.constant",
"numpy.tril_indices",
"tensorflow.reduce_sum"
]
] |
jordan-owen/tpqoa | [
"7f75b3399ec5b05ad8c543e95c815a76372db98d"
] | [
"tpqoa/tpqoa.py"
] | [
"#\n# tpqoa is a wrapper class for the\n# Oanda v20 API (RESTful & streaming)\n# making use of the v20 Python package\n#\n# (c) Dr. Yves J. Hilpisch\n# The Python Quants GmbH\n#\n#\n# Trading forex/CFDs on margin carries a high level of risk and may\n# not be suitable for all investors as you could sustain losses\n... | [
[
"pandas.to_datetime",
"pandas.DatetimeIndex",
"pandas.DataFrame",
"pandas.date_range",
"pandas.Timestamp"
]
] |
FarCaptain/MyUnet | [
"a02516a7ffa9e6fd5730e05fb5f95386bbb4b3d6"
] | [
"models/unet_original_dice&BCE.py"
] | [
"\n# coding: utf-8\n\n# In[1]:\n\nimport matplotlib as mpl\nimport matplotlib.pyplot as plt\n#get_ipython().magic('matplotlib inline')\nimport numpy as np\nimport sklearn\nfrom sklearn.model_selection import train_test_split\nimport pandas as pd\nimport os\nimport sys\nimport time\n#import keras\n#from keras.layers... | [
[
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.keras.layers.Activation",
"numpy.min",
"tensorflow.enable_eager_execution",
"tensorflow.keras.Model",
"tensorflow.keras.layers.BatchNormalization",
"numpy.max",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.Input",... |
ChristineBasta/fairseq | [
"c349ec3ec7fa0da7306c91769fbdc6146569a0ee"
] | [
"longformer_scripts/sequence_encoder.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 math\nfrom typing import Dict, List, Optional\n\nimport torch\nimport torch.nn as nn\nfrom fairseq import search, utils\nfrom... | [
[
"torch.jit.annotate",
"torch.no_grad",
"torch.stack",
"torch.nn.ModuleList"
]
] |
rishavpramanik/mealpy | [
"d4a4d5810f15837764e4ee61517350fef3dc92b3",
"d4a4d5810f15837764e4ee61517350fef3dc92b3"
] | [
"mealpy/swarm_based/SSpiderO.py",
"tests/physics_based/test_NRO.py"
] | [
"# !/usr/bin/env python\n# Created by \"Thieu\" at 12:00, 17/03/2020 ----------%\n# Email: nguyenthieu2102@gmail.com %\n# Github: https://github.com/thieu1995 %\n# --------------------------------------------------%\n\nimport numpy as np\nfrom copy import deepcopy\nfrom mealpy.optimize... | [
[
"numpy.max",
"numpy.array",
"numpy.linalg.norm",
"numpy.zeros",
"numpy.median",
"numpy.sum",
"numpy.min",
"numpy.logical_and",
"numpy.mean",
"numpy.multiply",
"numpy.random.uniform"
],
[
"numpy.sum"
]
] |
yueqiw/ml-agents | [
"499120a45c6a0203ff39770ded9a9dc6069ffa46"
] | [
"ml-agents/mlagents/trainers/ppo/trainer.py"
] | [
"# # Unity ML-Agents Toolkit\n# ## ML-Agent Learning (PPO)\n# Contains an implementation of PPO as described (https://arxiv.org/abs/1707.06347).\n\nimport logging\nimport os\nfrom collections import deque\n\nimport numpy as np\nimport tensorflow as tf\n\nfrom mlagents.envs import AllBrainInfo, BrainInfo\nfrom mlage... | [
[
"numpy.zeros_like",
"numpy.mean",
"numpy.abs",
"tensorflow.summary.FileWriter",
"numpy.vstack"
]
] |
AideenByrne/python-project | [
"90100295360db810d49cda3f0377fcca3866e33a"
] | [
"project1.py"
] | [
"\n#Aideen Byrne 26th March 2018 \n#Code for investigating Iris Data Set for Programming & Scripting module project \n\n#Select only the rows of the Virginica flowers and assign it to virginica \nimport pandas as pd #import pandas library \ndf1 = pd.read_csv(\"data/iris.csv\") #label contents of iris.csv file as d... | [
[
"pandas.read_csv"
]
] |
andreaconti/torch_k | [
"a5bf09b22d3bef9092d7313dda529af83da15dc6"
] | [
"integration_tests/test_transforms_torchvision.py"
] | [
"\"\"\"\ntesting integration between torchvision and transformations\n\"\"\"\n\nimport torch\nimport torchvision.transforms as V\n\nimport torch_kitti.transforms as K\n\n\ndef test_random_crop():\n\n # simulate input\n fake_img_1 = torch.randn(1, 600, 600)\n fake_img_2 = fake_img_1.clone()\n x = {\"img_... | [
[
"torch.all",
"torch.randn"
]
] |
pierreandrieu/corankcolight | [
"dce9d05c62f25faae5f73f150f44cc20bfa87b33",
"dce9d05c62f25faae5f73f150f44cc20bfa87b33"
] | [
"corankco/experiments/stats/bootstrap_experiment.py",
"corankco/partitioning/parfront.py"
] | [
"from corankco.algorithms.median_ranking import MedianRanking\nfrom corankco.dataset import DatasetSelector, Dataset\nfrom corankco.scoringscheme import ScoringScheme\nfrom corankco.experiments.experiment import ExperimentFromDataset, ExperimentFromOrphanetDataset\nfrom corankco.experiments.stats.bootstrap import b... | [
[
"numpy.quantile",
"numpy.isnan",
"matplotlib.pyplot.xlim",
"numpy.asarray",
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"numpy.mean",
"numpy.std",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.clf",
"numpy.fromstring"
],
[
"nump... |
QUVA-Lab/lang-tracker | [
"6cb3630471765565b6f2d34a160f0cd51d95a082"
] | [
"util/eval_tools.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nimport numpy as np\nimport pyximport; pyximport.install()\nfrom util.nms import cpu_nms as nms\n\n# all boxes are [xmin, ymin, xmax, ymax] format, 0-indexed, including xmax and ymax\ndef compute_bbox_iou(bboxes, target):\n if isinstance(bboxes,... | [
[
"numpy.logical_or",
"numpy.array",
"numpy.minimum",
"numpy.logical_and",
"numpy.all",
"numpy.maximum"
]
] |
katsugeneration/ml-project-template | [
"fe68c2f3fa6b6e51cc29b340cb2a1aeeca221322"
] | [
"model/utils/losses.py"
] | [
"# Copyright 2020 Katsuya Shimabukuro. All rights reserved.\n# Licensed under the MIT License.\nimport tensorflow as tf\n\n\nclass MaskedSparseCategoricalCrossentropy():\n \"\"\"SparseCategoricalCrossentropy without padding mask.\"\"\"\n\n def __call__(self, label, pred, **kwargs):\n \"\"\"Calculate lo... | [
[
"tensorflow.reduce_sum",
"tensorflow.keras.losses.sparse_categorical_crossentropy",
"tensorflow.math.equal",
"tensorflow.cast"
]
] |
Liyulingyue/Paddle | [
"f3f0824df52b6051ac365268a3a8cd2682c6c8d5"
] | [
"python/paddle/tensor/search.py"
] | [
"# Copyright (c) 2020 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.array",
"numpy.isscalar"
]
] |
liguowang/epage | [
"2ce60ddbcd23f06dc4d635681e8e52b66ba519f9",
"2ce60ddbcd23f06dc4d635681e8e52b66ba519f9"
] | [
"bin/gComposite.py",
"lib/pacmodule/iMatrix.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Aug 30 10:04:05 2019\n\n@author: m102324\n\nDescription\n-----------\nThis program Calculates the Composite Expression Scores:\n\t* Gene Set Variation Analysis (GSVA). (Hänzelmann et al, 2013)\n\t* Single Sample GSEA (ssGSEA). (Barbie et al, ... | [
[
"pandas.read_csv",
"pandas.concat"
],
[
"scipy.stats.zscore"
]
] |
lifehouse11amber2/Machine-Learning-A-Z-hands-on-Python-And-R-in-data-Science | [
"d804e7eeace1e5187b156b2fa3e71125b2a3448a",
"d804e7eeace1e5187b156b2fa3e71125b2a3448a"
] | [
"Machine Learning A-Z/Part 7 - Natural Language Processing/Section 36 - Natural Language Processing/natural_language_processing.py",
"Machine Learning A-Z/keras-fire-detection/pyimagesearch/learningratefinder.py"
] | [
"# Natural Language Processing\n\n# Importing the libraries\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# Importing the dataset\ndataset = pd.read_csv('Restaurant_Reviews.tsv', delimiter = '\\t', quoting = 3)\n\n# Cleaning the texts\nimport re\nimport nltk\nnltk.download('stopwords'... | [
[
"sklearn.metrics.confusion_matrix",
"sklearn.naive_bayes.GaussianNB",
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.model_selection.train_test_split",
"pandas.read_csv"
],
[
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"ten... |
Emmyphung/flexible-input-slu | [
"a2c7fff640b2b4aec830f3ca1b447c28dc506bb4"
] | [
"experiments/experiment_base_original.py"
] | [
"# Copyright Amazon.com, Inc. or its affiliates. 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# Unle... | [
[
"torch.cat",
"torch.no_grad",
"torch.nn.CrossEntropyLoss",
"numpy.savez_compressed",
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"torch.load",
"torch.utils.tensorboard.SummaryWriter"
]
] |
Monster880/pytorch_py | [
"9c5ac5974f48edb5ea3d897a1100a63d488c61d9"
] | [
"load_cifar10.py"
] | [
"import glob\n\nfrom torchvision import transforms\nfrom torch.utils.data import DataLoader, Dataset\nimport os\nfrom PIL import Image\nimport numpy as np\n\nlabel_name = [\n \"airplane\",\n \"automobile\",\n \"bird\",\n \"cat\",\n \"deer\",\n \"dog\",\n \"frog\",\n \"horse\",\n \"ship\",... | [
[
"torch.utils.data.DataLoader"
]
] |
svenvanderburg/EEG_age_prediction | [
"958e8d6445bf277a445608e05d779315dbd9b376",
"958e8d6445bf277a445608e05d779315dbd9b376"
] | [
"scripts/DL_final_Encoder_regressor.py",
"scripts/DL_final_InceptionTime_regressor.py"
] | [
"#!/usr/bin/env python\n\n# ================ IMPORT LIBRARIES ================ #\nimport sys, os, fnmatch, time\nimport numpy as np\nimport pandas as pd\n\nfrom sklearn.model_selection import train_test_split\n\nsys.path.insert(0, os.path.dirname(os.getcwd()))\n\nfrom dataset_generator import DataGenerator\n\nimpor... | [
[
"tensorflow.keras.layers.Conv1D",
"tensorflow.keras.metrics.MeanAbsoluteError",
"tensorflow.keras.layers.Lambda",
"tensorflow.keras.layers.Input",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Softmax",
"tensorflow.keras.models.Model",
"tensorflow.keras.callbacks.Mode... |
qw85639229/hardest | [
"ef86536dbbe1089248e34afbbb7bb513f97f58f1",
"ef86536dbbe1089248e34afbbb7bb513f97f58f1"
] | [
"torchreid/data/datasets/video/mars.py",
"torchreid/models/inceptionresnetv2.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import print_function\nfrom __future__ import division\n\nimport sys\nimport os\nimport os.path as osp\nfrom scipy.io import loadmat\nimport warnings\n\nfrom torchreid.data.datasets import VideoDataset\n\n\nclass Mars(VideoDataset):\n \"\"\"MARS.\n\n Re... | [
[
"scipy.io.loadmat"
],
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.MaxPool2d",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.utils.model_zoo.load_url",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.AdaptiveAvgPool2d"
]
] |
paperclip/tf2-eager-yolo3 | [
"7f6b137c50525f91ed5026c6cb1d556e9b6d9bed"
] | [
"predRoC.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport tensorflow as tf\nimport argparse\nimport cv2\nimport matplotlib.pyplot as plt\nimport glob\nimport json\nimport sys\nimport os\n\nfrom yolo.utils.box import visualize_boxes\nfrom yolo.config import ConfigParser\n\nif tf.executing_eagerly():\n print(\"Executing eargerly\")\nels... | [
[
"tensorflow.executing_eagerly",
"tensorflow.enable_eager_execution"
]
] |
fol21/domain-adaptation-in-deforestation | [
"ae1c37b1634f54230f1d2217c209dabd6780568a",
"ae1c37b1634f54230f1d2217c209dabd6780568a"
] | [
"src/ADDA/Networks.py",
"src/CycleGAN/CycleGAN_DN/util/remote_sensing_visualizer.py"
] | [
"import os\nimport numpy as np\nimport tensorflow as tf\n\n\n\nclass Networks():\n def __init__(self, args):\n super(Networks, self).__init__()\n self.args = args\n \n # Wittich design\n def VNET_16L(self, I, is_train, reuse_unet=False, reuse_ada=False, adaption_net=False):\n\n def ... | [
[
"tensorflow.constant_initializer",
"tensorflow.nn.conv2d",
"tensorflow.ones",
"tensorflow.clip_by_value",
"tensorflow.nn.softmax",
"tensorflow.nn.leaky_relu",
"tensorflow.concat",
"tensorflow.contrib.layers.variance_scaling_initializer",
"tensorflow.layers.batch_normalization",... |
KazMorita/pydefect | [
"31e5ad774845f436554ef15000b8eba3b168a65c"
] | [
"pydefect/tests/cli/vasp/test_main_function.py"
] | [
"# -*- coding: utf-8 -*-\n# Copyright (c) 2020. Distributed under the terms of the MIT License.\nfrom argparse import Namespace\nfrom pathlib import Path\n\nimport numpy as np\nimport pytest\nfrom monty.serialization import loadfn\nfrom pydefect.analyzer.band_edge_states import EdgeCharacters, BandEdgeStates\nfrom... | [
[
"numpy.eye"
]
] |
lxh5147/Text-Classification-Pytorch | [
"51f9189aad62051127c5a537c72ab3a8b0f97c60"
] | [
"models/LSTM_Attn.py"
] | [
"# _*_ coding: utf-8 _*_\n\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\nfrom torch.nn import functional as F\n\n\nclass AttentionModel(torch.nn.Module):\n def __init__(self, batch_size, output_size, hidden_size, vocab_size, embedding_length, weights):\n super(AttentionModel, ... | [
[
"torch.nn.Linear",
"torch.zeros",
"torch.nn.LSTM",
"torch.nn.Parameter",
"torch.cuda.is_available",
"torch.nn.functional.softmax",
"torch.nn.Embedding"
]
] |
MinnDevelopment/robosat.pink | [
"0e4b88a7b1fc91e2a20e5e3bf0c4f742be9ea2c5"
] | [
"robosat_pink/tools/rasterize.py"
] | [
"import os\nimport sys\nimport json\nimport collections\n\nimport numpy as np\nfrom tqdm import tqdm\n\nimport mercantile\nfrom rasterio.crs import CRS\nfrom rasterio.transform import from_bounds\nfrom rasterio.features import rasterize\nfrom rasterio.warp import transform\nfrom supermercado import burntiles\n\nimp... | [
[
"numpy.zeros"
]
] |
CCH852573130/3DPrinting10 | [
"ca843d728bd7501f332a7946976c40d86b362930"
] | [
"app/src/main/python/image.py"
] | [
"# coding=utf-8\nimport numpy\nimport time\nimport struct\nfrom PIL import Image\nfrom MeshBuilder import MeshBuilder\nfrom Vector import Vector\nfrom CuraSceneNode import CuraSceneNode as SceneNode\n\ndef generateSceneNode(file_name, xz_size, peak_height, base_height, blur_iterations, max_size,lighter_is_higher,fi... | [
[
"numpy.array",
"numpy.pad",
"numpy.zeros"
]
] |
sdevenes/M05_MiniProject | [
"38f81c6cc0b0d8f777c51609118b160c010c5590"
] | [
"rr/experiment/database.py"
] | [
"import numpy as np\nimport csv\nfrom sklearn.model_selection import train_test_split\n\nPROTOCOLS = {\n \"proto1\": {\"train\": 0.8, \"test\": 0.2, \"random\": 1},\n \"proto2\": {\"train\": 0.8, \"test\": 0.2, \"random\": 2},\n}\n\nSUBSETS = [\"train\", \"validation\", \"test\"]\n\nCLASSES = [\n \"Other_A... | [
[
"sklearn.model_selection.train_test_split",
"numpy.array",
"numpy.isin"
]
] |
IvanaEscobar/xgcm | [
"95f4f33d72d2add00136e27f6b3bedecb97d4d77"
] | [
"xgcm/test/test_autogenerate.py"
] | [
"import numpy as np\nimport pytest\nimport xarray as xr\nfrom xarray.testing import assert_allclose, assert_equal\n\nfrom xgcm.autogenerate import (\n _fill_attrs,\n _parse_boundary_params,\n _parse_position,\n _position_to_relative,\n generate_axis,\n generate_grid_ds,\n)\n\n# create test dataset... | [
[
"numpy.hstack",
"numpy.array",
"numpy.arange",
"numpy.meshgrid"
]
] |
ignacia-fp/bempp-cl | [
"a65232558826e51e624b1a4f649b6a0ed5a7f551"
] | [
"bempp/api/external/fenicsx.py"
] | [
"\"\"\"Interface to DOLFINX for FEM-BEM coupling.\"\"\"\n\n\ndef boundary_grid_from_fenics_mesh(fenics_mesh):\n \"\"\"\n Create a Bempp boundary grid from a FEniCS Mesh.\n\n Return the Bempp grid and a map from the node numberings of the FEniCS\n mesh to the node numbers of the boundary grid.\n \"\"\... | [
[
"scipy.sparse.csr_matrix",
"numpy.arange",
"numpy.zeros",
"numpy.ones"
]
] |
jostl/masters-thesis | [
"211e1f12a07428d37507e2bddc808f6da1149efb",
"211e1f12a07428d37507e2bddc808f6da1149efb"
] | [
"bird_view/models/birdview.py",
"perception/training/train_depth.py"
] | [
"import cv2\nimport numpy as np\n\nimport torch\nimport torch.nn as nn\n\nfrom . import common\nfrom .agent import Agent\nfrom .controller import PIDController, CustomController\nfrom .controller import ls_circle\n\n\nSTEPS = 5\nSPEED_STEPS = 3\nCOMMANDS = 4\nDT = 0.1\nCROP_SIZE = 192\nPIXELS_PER_METER = 5\n\n\ndef... | [
[
"numpy.concatenate",
"torch.cat",
"numpy.linalg.norm",
"torch.stack",
"numpy.sin",
"torch.nn.BatchNorm2d",
"torch.nn.ConvTranspose2d",
"torch.no_grad",
"torch.FloatTensor",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"numpy.arctan2",
"numpy.cos"
],
[
"torch.util... |
abramhindle/mne-python | [
"989390a484cba219aae74c778b71568586f9edb2"
] | [
"tutorials/stats-sensor-space/plot_stats_cluster_1samp_test_time_frequency.py"
] | [
"\"\"\"\n===============================================================\nNon-parametric 1 sample cluster statistic on single trial power\n===============================================================\n\nThis script shows how to estimate significant clusters\nin time-frequency power estimates. It uses a non-param... | [
[
"matplotlib.pyplot.colorbar",
"numpy.ones_like",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"numpy.abs",
"matplotlib.pyplot.show",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.subplots... |
LinghengMeng/openai_baselines_extension | [
"65ec57a71be77b6cfd92defd070d76ae225a92e7"
] | [
"baselines/deepq_n_step/build_graph.py"
] | [
"\"\"\"Deep Q learning graph\n\nThe functions in this file can are used to create the following functions:\n\n======= act ========\n\n Function to chose an action given an observation\n\n Parameters\n ----------\n observation: object\n Observation that can be feed into the output of make_obs_ph\n... | [
[
"tensorflow.constant_initializer",
"tensorflow.group",
"tensorflow.clip_by_norm",
"tensorflow.stack",
"tensorflow.control_dependencies",
"tensorflow.nn.softmax",
"tensorflow.one_hot",
"tensorflow.trainable_variables",
"tensorflow.shape",
"tensorflow.argmax",
"tensorflow... |
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