repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
klein203/AI-Learning | [
"8db60945f4ea41b891b56e416f3b49a160b046c6"
] | [
"src/resnet_model.py"
] | [
"'''\r\n@author: xusheng\r\n'''\r\nimport tensorflow as tf\r\nfrom model import Model\r\nfrom six.moves import xrange\r\n\r\nclass ResnetModel(Model):\r\n \r\n def _res_block(self, scope_name, x, in_channels, out_channels, stride=1):\r\n # Res: H(x) = F(x) + x\r\n # F(x) = Conv(Relu(BN( Conv(Rel... | [
[
"tensorflow.summary.histogram",
"tensorflow.reshape",
"tensorflow.variable_scope",
"tensorflow.pad",
"tensorflow.reduce_mean",
"tensorflow.nn.avg_pool"
]
] |
jwyles/cudf | [
"1ba84a1354c33aac0a9851e15321c6d9a2fca956"
] | [
"python/cudf/cudf/comm/gpuarrow.py"
] | [
"# Copyright (c) 2019, NVIDIA CORPORATION.\n\nfrom collections import OrderedDict\nfrom collections.abc import Sequence\n\nimport numba.cuda.cudadrv.driver\nimport numpy as np\nimport pandas as pd\nimport pyarrow as pa\n\nimport rmm\n\nfrom cudf._lib.arrow._cuda import CudaBuffer\nfrom cudf._lib.gpuarrow import (\n... | [
[
"numpy.dtype",
"pandas.core.dtypes.dtypes.CategoricalDtype"
]
] |
hhmlai/OpenNMT-tf | [
"f2320fd857f6c76d4f552a10a0a854b8cd8c8c79"
] | [
"opennmt/tests/checkpoint_test.py"
] | [
"import os\n\nimport tensorflow as tf\n\nfrom opennmt.utils import checkpoint as checkpoint_util\n\n\nclass _DummyModel(tf.keras.layers.Layer):\n\n def __init__(self):\n super(_DummyModel, self).__init__()\n self.layers = [tf.keras.layers.Dense(20), tf.keras.layers.Dense(20)]\n\n def call(self, x):\n for... | [
[
"tensorflow.train.latest_checkpoint",
"tensorflow.train.CheckpointManager",
"tensorflow.not_equal",
"tensorflow.ones_like",
"tensorflow.random.uniform",
"tensorflow.keras.layers.Dense",
"tensorflow.train.list_variables",
"tensorflow.test.main",
"tensorflow.reduce_mean",
"te... |
ZJZAC/Passport-aware-Normalization | [
"e2c2b928678188c1b5440f7da2c529ace87f23ac"
] | [
"Image_cls/Baseline/experiments/classification.py"
] | [
"import os\nfrom pprint import pprint\n\nimport torch\nimport torch.optim as optim\n\nimport passport_generator\nfrom dataset import prepare_dataset, prepare_wm\nfrom experiments.base import Experiment\nfrom experiments.trainer import Trainer, Tester\nfrom experiments.trainer_private import TesterPrivate\nfrom expe... | [
[
"torch.tensor",
"torch.load",
"torch.optim.lr_scheduler.MultiStepLR"
]
] |
Tartar-san/montage.ai | [
"c699dfaf300fdca69f3dbc5d63fae9f00a26ca40"
] | [
"libs/librosa/feature/utils.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"Feature manipulation utilities\"\"\"\n\nfrom warnings import warn\n\nimport numpy as np\nimport scipy.signal\n\nfrom .. import cache\nfrom ..util.deprecation import Deprecated\nfrom ..util.exceptions import ParameterError\n\n__all__ = ['delta', 'stack_memory']\... | [
[
"numpy.pad",
"numpy.ascontiguousarray",
"numpy.roll",
"numpy.atleast_1d",
"numpy.mod",
"numpy.atleast_2d"
]
] |
MDiesing/pandapower | [
"02df20351bcc39e074711fa9550acb448a7c522c"
] | [
"pandapower/test/api/test_toolbox.py"
] | [
"# -*- coding: utf-8 -*-\n\n# Copyright (c) 2016-2019 by University of Kassel and Fraunhofer Institute for Energy Economics\n# and Energy System Technology (IEE), Kassel. All rights reserved.\n\n\nimport copy\n\nimport numpy as np\nimport pandas as pd\nimport pytest\n\nimport pandapower as pp\nimport pandapower.net... | [
[
"numpy.array",
"numpy.isnan",
"numpy.isclose",
"numpy.random.seed",
"numpy.allclose",
"numpy.random.randint",
"numpy.append",
"pandas.Series"
]
] |
amitport/grace | [
"b0e442057d2f36f09cd1817a4acb966c6b0b780f"
] | [
"grace_dl/dist/compressor/topk.py"
] | [
"import torch\r\n\r\nfrom grace_dl.dist import Compressor\r\n\r\n\r\ndef sparsify(tensor, compress_ratio):\r\n tensor = tensor.flatten()\r\n k = max(1, int(tensor.numel() * compress_ratio))\r\n _, indices = torch.topk(tensor.abs(), k)\r\n values = tensor[indices]\r\n return values, indices\r\n\r\n\r\... | [
[
"torch.zeros"
]
] |
anjanatiha/Clustering-for-Document-Classification | [
"64ca76609d0b067d4fc7c493a68e42695794a3b9"
] | [
"news_docs_classification.py"
] | [
"\n# coding: utf-8\n\n# In[1]:\n\n\nfrom sklearn.datasets import fetch_20newsgroups\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.cluster import KMeans\nfrom sklearn import mixture\nfrom sklearn.metrics import f1_score\nimport time\n\n\nnewsgroups_train = fetch_20newsgroups(subset='trai... | [
[
"sklearn.datasets.fetch_20newsgroups",
"sklearn.cluster.KMeans",
"sklearn.mixture.GaussianMixture",
"sklearn.feature_extraction.text.TfidfVectorizer",
"sklearn.metrics.f1_score"
]
] |
zhujiagang/realtime-lstm-parallel | [
"afdea3bcfc741ae469808f6238ce76c2dda5246e"
] | [
"train_loglr_multigpu.py"
] | [
"\n\"\"\" Adapted from:\n @longcw faster_rcnn_pytorch: https://github.com/longcw/faster_rcnn_pytorch\n @rbgirshick py-faster-rcnn https://github.com/rbgirshick/py-faster-rcnn\n Which was adopated by: Ellis Brown, Max deGroot\n https://github.com/amdegroot/ssd.pytorch\n\n Further:\n Updated by Gurk... | [
[
"torch.cuda.manual_seed_all",
"torch.cuda.synchronize",
"numpy.asarray",
"numpy.random.seed",
"torch.nn.init.xavier_uniform",
"torch.save",
"torch.optim.SGD",
"torch.set_default_tensor_type",
"torch.autograd.Variable",
"numpy.random.shuffle",
"torch.manual_seed",
"t... |
YueLiu-jina/jina-hub | [
"e0a7dc95dbd69a55468acbf4194ddaf11fd5aa6c"
] | [
"encoders/numeric/random_sparse.py"
] | [
"__copyright__ = \"Copyright (c) 2020 Jina AI Limited. All rights reserved.\"\n__license__ = \"Apache-2.0\"\n\nfrom . import TransformEncoder\n\n\nclass RandomSparseEncoder(TransformEncoder):\n \"\"\"\n :class:`RandomSparseEncoder` encodes data from an ndarray in size `B x T` into an ndarray in size `B x D`\n... | [
[
"sklearn.random_projection.SparseRandomProjection"
]
] |
ashahba/OpenVINO-model-server | [
"feb7d7119f56fa0787b83393e38e8ea36762a34b"
] | [
"ie_serving/server/predict_utils.py"
] | [
"#\r\n# Copyright (c) 2018 Intel Corporation\r\n#\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n#\r\n# http://www.apache.org/licenses/LICENSE-2.0\r\n#\r\n# Unless requi... | [
[
"tensorflow.python.framework.dtypes.as_dtype",
"tensorflow.contrib.util.make_ndarray",
"tensorflow.python.framework.tensor_shape.as_shape"
]
] |
Kisukee/ray | [
"f1a1f9799238c995995f558636a09c2147ecabe6"
] | [
"python/ray/data/dataset.py"
] | [
"import logging\nimport os\nimport time\nfrom typing import (\n List,\n Any,\n Callable,\n Iterator,\n Iterable,\n Generic,\n Dict,\n Optional,\n Union,\n TYPE_CHECKING,\n Tuple,\n)\nfrom uuid import uuid4\n\nif TYPE_CHECKING:\n import pyarrow\n import pandas\n import mars\... | [
[
"tensorflow.data.Dataset.from_generator",
"torch.as_tensor",
"numpy.mean",
"numpy.array_split"
]
] |
kozzion/breaker_audio | [
"0f27b3ae581fbeb8f79d0b8755a139f7438ca02b"
] | [
"breaker_audio/component_cmn/toolbox/ui.py"
] | [
"from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas\nfrom matplotlib.figure import Figure\nfrom PyQt5.QtCore import Qt\nfrom PyQt5.QtWidgets import *\nfrom encoder.inference import plot_embedding_as_heatmap\nfrom breaker_audio.data_structure.utterance import Utterance\nfrom pathlib imp... | [
[
"numpy.array",
"matplotlib.pyplot.subplots",
"numpy.arange",
"numpy.unique",
"matplotlib.backends.backend_qt5agg.FigureCanvasQTAgg"
]
] |
lwb0818/DAVANet | [
"8b7afa3df5b66207f28cc66f559ed23bdd7833d3"
] | [
"utils/network_utils.py"
] | [
"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n# \n# Developed by Shangchen Zhou <shangchenzhou@gmail.com>\n\nimport os\nimport sys\nimport torch\nimport numpy as np\nfrom datetime import datetime as dt\nfrom config import cfg\nimport torch.nn.functional as F\n\nimport cv2\n\ndef mkdir(path):\n if not os.path.isdi... | [
[
"torch.zeros",
"torch.stack",
"torch.isnan",
"torch.nn.init.constant_",
"torch.save",
"torch.nn.init.kaiming_normal_",
"torch.nn.init.xavier_uniform_",
"torch.FloatTensor",
"numpy.logical_and",
"torch.nn.init.normal_",
"torch.cuda.is_available",
"torch.isinf",
"... |
PositivePeriod/music_in_python | [
"5b3244fe03530ee9a73bc9689ee47583825fdd60"
] | [
"middle_c.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nMimic a middle C on the piano.\n\n@author: khe\n\"\"\"\nimport numpy as np\nfrom scipy.io import wavfile\nimport matplotlib.pyplot as plt\nplt.style.use('seaborn-dark')\nimport utils\n\n# Get middle C frequency\nnote_freqs = utils.get_piano_notes()\nfrequenc... | [
[
"numpy.max",
"scipy.io.wavfile.read",
"matplotlib.pyplot.xlim",
"numpy.round",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"numpy.sum",
"numpy.where",
"numpy.fft.fft",
"n... |
gwrome/pandas | [
"cb6e47d5a04c89cb6f3564753c43abadbdf81c94"
] | [
"pandas/core/sparse/frame.py"
] | [
"\"\"\"\nData structures for sparse float data. Life is made simpler by dealing only\nwith float64 data\n\"\"\"\nimport warnings\n\nimport numpy as np\n\nfrom pandas._libs.sparse import BlockIndex, get_blocks\nfrom pandas.compat.numpy import function as nv\nfrom pandas.util._decorators import Appender\n\nfrom panda... | [
[
"pandas.compat.numpy.function.validate_cumsum",
"pandas.io.pickle._unpickle_array",
"pandas.core.ops.add_flex_arithmetic_methods",
"pandas.core.internals.create_block_manager_from_arrays",
"pandas.core.arrays.sparse.SparseArray",
"pandas._libs.sparse.get_blocks",
"pandas.concat",
"... |
rao003/ki-in-schulen | [
"ec7e69da6d728ce6480711b45cea0aef7796b14b"
] | [
"Calliope-Rennspiel/Python/ki-rennspiel.py"
] | [
"#\n# ki-rennspiel.py$\n#\n# (C) 2020, Christian A. Schiller, Deutsche Telekom AG\n#\n# Deutsche Telekom AG and all other contributors /\n# copyright owners license this file to you under the\n# MIT License (the \"License\"); you may not use this\n# file except in compliance with the License.\n# You may obtain a co... | [
[
"numpy.median",
"numpy.array",
"numpy.array_str"
]
] |
google-research/nested-transformer | [
"59c0d6aa1a0526fbca15507a172f3dc110f52a3c",
"59c0d6aa1a0526fbca15507a172f3dc110f52a3c"
] | [
"main.py",
"libml/preprocess.py"
] | [
"# coding=utf-8\n# Copyright 2020 The Nested-Transformer 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 r... | [
[
"tensorflow.config.experimental.set_visible_devices"
],
[
"tensorflow.io.decode_jpeg",
"tensorflow.image.stateless_random_crop",
"tensorflow.image.resize_with_crop_or_pad",
"tensorflow.zeros",
"tensorflow.shape",
"tensorflow.minimum",
"tensorflow.image.stateless_random_flip_lef... |
nzare/poliastro | [
"c4d0f80c98fb2a0ec59a07f4664cfebb0b1a6cf9"
] | [
"tests/tests_twobody/test_propagation.py"
] | [
"import numpy as np\nimport pytest\nfrom astropy import time, units as u\nfrom astropy.coordinates import CartesianRepresentation\nfrom astropy.tests.helper import assert_quantity_allclose\nfrom hypothesis import given, settings, strategies as st\nfrom numpy.testing import assert_allclose\nfrom pytest import approx... | [
[
"numpy.deg2rad",
"numpy.array",
"numpy.random.uniform",
"numpy.cos"
]
] |
noushi/pyccel | [
"f20846897ba2418dc0f432e293bcf8b4ddb24915"
] | [
"tests/pyccel/scripts/hope_benchmarks_decorators/hope_pairwise_python.py"
] | [
"# pylint: disable=missing-function-docstring, missing-module-docstring/\nfrom pyccel.decorators import types\n\n@types('double[:,:]','double[:,:]')\ndef pairwise_python (X, D) :\n from numpy import sqrt, shape\n\n M, N = shape( X )\n for i in range (M) :\n for j in range (M) :\n r = 0.0\... | [
[
"numpy.sqrt",
"numpy.shape",
"numpy.zeros"
]
] |
danielism97/FLAVR | [
"17f62c681bb2a5799e3bc23cf60936ac4d2b9407"
] | [
"model/FLAVR_arch.py"
] | [
"import math\nimport numpy as np\nimport importlib\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom .resnet_3D import SEGating\n\ndef joinTensors(X1 , X2 , type=\"concat\"):\n\n if type == \"concat\":\n return torch.cat([X1 , X2] , dim=1)\n elif type == \"add\":\n re... | [
[
"torch.cat",
"torch.stack",
"torch.nn.Sequential",
"torch.unbind",
"torch.nn.LeakyReLU",
"torch.split",
"torch.nn.BatchNorm2d",
"torch.nn.ConvTranspose2d",
"torch.nn.Upsample",
"torch.nn.Conv2d",
"torch.nn.ReflectionPad2d",
"torch.nn.Conv3d",
"torch.nn.functiona... |
robotory/robopilot | [
"e10207b66d06e5d169f890d1d7e57d971ca1eb5d"
] | [
"robopilot/templates/complete.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\nScripts to drive a robopilot 2 car\n\nUsage:\n manage.py (drive) [--model=<model>] [--js] [--type=(linear|categorical)] [--camera=(single|stereo)] [--meta=<key:value> ...] [--myconfig=<filename>]\n manage.py (train) [--tubs=tubs] (--model=<model>) [--type=(linear|inferred|tens... | [
[
"tensorflow.python.keras.models.model_from_json"
]
] |
vischia/madminer | [
"98c2bcfb93d0fd84ff1872b344c4d89adf51217f"
] | [
"madminer/utils/ml/models/base.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import grad\n\n\nclass BaseFlow(nn.Module):\n \"\"\" \"\"\"\n\n def __init__(self, n_inputs, **kwargs):\n super(BaseFlow, self).__init__()\n\n self.n_... | [
[
"torch.ones_like",
"numpy.log",
"torch.sum"
]
] |
zingale/pynucastro | [
"85b027c0d584046e749888e79e78c611bbf69cb4"
] | [
"pynucastro/rates/rate.py"
] | [
"\"\"\"\nClasses and methods to interface with files storing rate data.\n\"\"\"\n\nimport os\nimport re\nimport io\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport numba\n\ntry:\n from numba.experimental import jitclass\nexcept ImportError:\n from numba import jitclass\n\nfrom pynucastro.nucdata i... | [
[
"numpy.array",
"matplotlib.pyplot.colorbar",
"numpy.zeros_like",
"numpy.log",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"numpy.exp",
"matplotlib.pyplot.subplots",
"numpy.where",
"matplotlib.pyplot.ylabel",
"numpy.abs",
"matp... |
ml-research/X-mushroom-rl | [
"ef5f131d3cfa9c229a614c044d8c001afe8812d2"
] | [
"x_mushroom_rl/algorithms/actor_critic/deep_actor_critic/ppo.py"
] | [
"import numpy as np\n\nimport torch\nimport torch.nn.functional as F\n\nfrom x_mushroom_rl.algorithms.agent import Agent\nfrom x_mushroom_rl.approximators import Regressor\nfrom x_mushroom_rl.approximators.parametric import TorchApproximator\nfrom x_mushroom_rl.utils.torch import to_float_tensor, update_optimizer_p... | [
[
"torch.min",
"numpy.mean",
"torch.nn.functional.mse_loss",
"numpy.std",
"torch.distributions.kl.kl_divergence",
"torch.tensor"
]
] |
trevordavid/rossby-ridge | [
"fb25a8ccf49bec42c440c17d82e56c3ee999f9de"
] | [
"src/scripts/percentiles.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\nimport paths\nimport numpy as np\nimport pandas as pd\n\nfrom astropy.table import Table\n\nimport matplotlib.pyplot as plt\nimport matplotlib as mpl\n\nmpl.rcParams[\"figure.dpi\"] = 100\nmpl.rcParams[\"savefig.bbox\"] = \"tight\"\nmpl.rcParams[\"savefig.dpi\"] = 300\n\ni... | [
[
"matplotlib.pyplot.xlim",
"numpy.median",
"numpy.exp",
"numpy.mean",
"pandas.read_hdf",
"pandas.concat",
"numpy.nanpercentile",
"matplotlib.pyplot.savefig",
"numpy.arange",
"numpy.array",
"numpy.std",
"matplotlib.pyplot.xlabel",
"numpy.sum",
"matplotlib.pypl... |
NagisaZj/pytorch-soft-actor-critic | [
"7f219269356b11273e873a9f4d3ac7b86fe317cb"
] | [
"main.py"
] | [
"import argparse\nimport datetime\nimport gym\nimport numpy as np\nimport itertools\nimport torch\nfrom sac import SAC\nfrom torch.utils.tensorboard import SummaryWriter\nfrom replay_memory import ReplayMemory\nimport json\nimport metaworld, random\n\nparser = argparse.ArgumentParser(description='PyTorch Soft Actor... | [
[
"numpy.random.seed",
"torch.save",
"torch.manual_seed",
"torch.load",
"torch.utils.tensorboard.SummaryWriter"
]
] |
fronovics/AI_playground | [
"ac302c0694fa2182af343c257b28a033bc4cf5b9"
] | [
"dasem/models.py"
] | [
"\"\"\"models.\n\nUsage:\n dasem.models\n\n\"\"\"\n\n\nfrom __future__ import absolute_import, division, print_function\n\nfrom abc import ABCMeta\n\nimport logging\n\nimport gensim\n\nfrom os.path import join, sep\n\nfrom numpy import argsort, array, dot, newaxis, sqrt, zeros\n\nfrom six import with_metaclass\n\n... | [
[
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.argsort"
]
] |
lisabang/basenji | [
"f91bb195b4062c55e487a4091e13a0e813ef07d6"
] | [
"bin/basenji_annot_chr.py"
] | [
"#!/usr/bin/env python\nfrom __future__ import print_function\nfrom optparse import OptionParser\n\nimport gc\nimport joblib\nimport multiprocessing\nimport pdb\nimport os\nimport subprocess\nimport sys\n\nimport h5py\nimport numpy as np\nimport pandas as pd\nfrom sklearn.decomposition import NMF, PCA\n\n# import z... | [
[
"numpy.concatenate",
"numpy.array",
"pandas.read_table",
"numpy.random.choice",
"sklearn.decomposition.NMF",
"numpy.arange",
"numpy.abs",
"sklearn.decomposition.PCA"
]
] |
lupoglaz/GodotGymAI | [
"2c06f0ab14a4f8e804791324793ae46e668540ee"
] | [
"Tutorials/Lander/main.py"
] | [
"import torch\nimport gym\nfrom stable_baselines3 import DDPG\nfrom LanderEnv import LanderEnv\n\nfrom stable_baselines3.common.callbacks import BaseCallback\nfrom stable_baselines3.common.noise import OrnsteinUhlenbeckActionNoise\nimport numpy as np\n\nclass NormalizedEnvironment(gym.ActionWrapper):\n def actio... | [
[
"numpy.ones",
"numpy.zeros",
"torch.jit.trace",
"torch.from_numpy"
]
] |
ManuelFritsche/flow-consistency | [
"90625fe25855aa11c6245ca242ab8d66c41f4726"
] | [
"semseg/models/icnet.py"
] | [
"import torch\r\nimport numpy as np\r\nimport torch.nn as nn\r\n\r\nfrom math import ceil\r\nfrom torch.autograd import Variable\r\n\r\nfrom semseg import caffe_pb2\r\nfrom semseg.models.utils import *\r\nfrom semseg.loss import *\r\n\r\nicnet_specs = {\r\n \"cityscapes\": {\r\n \"n_classes\": 19,\r\n ... | [
[
"numpy.array",
"numpy.zeros",
"torch.autograd.Variable",
"numpy.copy",
"scipy.misc.imresize",
"torch.from_numpy",
"torch.cuda.device_count",
"torch.nn.Conv2d",
"numpy.argmax",
"scipy.misc.imsave"
]
] |
qrebjock/fanok | [
"5c3b95ca5f2ec90af7060c21409a11130bd350bd"
] | [
"fanok/sdp/sdp.py"
] | [
"import warnings\n\nimport numpy as np\nfrom scipy.linalg import eigh\nfrom scipy.spatial.distance import pdist\nfrom scipy.cluster.hierarchy import linkage, cut_tree\n\nfrom fanok.sdp._full_rank import _full_rank\nfrom fanok.sdp._low_rank import _sdp_low_rank\n\ntry:\n import cvxpy as cp\nexcept ImportError:\n ... | [
[
"scipy.cluster.hierarchy.linkage",
"scipy.spatial.distance.pdist",
"scipy.cluster.hierarchy.cut_tree",
"numpy.zeros",
"scipy.linalg.eigh",
"numpy.sum",
"numpy.ones",
"numpy.ix_",
"numpy.where",
"numpy.sqrt",
"numpy.clip",
"numpy.diag"
]
] |
LeBronLiHD/ZJU2021_MedicineAI_CourseProject | [
"d19253ace2725545b8eff02ccae957278d6a3402"
] | [
"j_CAE_binary_classification.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"\ngenerate more '1' data in Convolutional auto-encoder\n\"\"\"\n\nimport numpy as np\nimport f_parameters\nimport f_preprocess\nimport f_load_data\nfrom keras.callbacks import EarlyStopping\nfrom keras.layers import Conv2D, MaxPooling2D, UpSampling2D, Dense\nimport os\nimport matpl... | [
[
"numpy.array",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"numpy.shape",
"numpy.mean",
"numpy.std",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"sklearn.metrics.roc_auc_score",
"sklearn.metr... |
mz71/manim | [
"08678f7b3edc376932493f53e416d310666ed3b7"
] | [
"manim/camera/three_d_camera.py"
] | [
"import numpy as np\n\nfrom ..camera.camera import Camera\nfrom ..constants import *\nfrom ..config import config\nfrom ..mobject.three_d_utils import get_3d_vmob_end_corner\nfrom ..mobject.three_d_utils import get_3d_vmob_end_corner_unit_normal\nfrom ..mobject.three_d_utils import get_3d_vmob_start_corner\nfrom ..... | [
[
"numpy.identity",
"numpy.array",
"numpy.dot",
"numpy.exp"
]
] |
AZMAG/urbansim_templates | [
"723b83b4187da53a50ee03fdba4842a464f68240"
] | [
"urbansim_templates/models/binary_logit.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\nimport pandas as pd\nimport patsy\nfrom datetime import datetime as dt\nfrom statsmodels.api import Logit\n\nimport orca\n\nfrom .. import modelmanager\nfrom ..utils import get_data\nfrom .shared import TemplateStep\n\n\n@modelmanager.template\nclass Bin... | [
[
"scipy.stats.chi2.sf",
"numpy.less",
"numpy.dot",
"numpy.exp"
]
] |
nickpoerio/CarND-Capstone | [
"439bcc4574d6e7a684250c8a86928c3767c68fff"
] | [
"ros/src/waypoint_updater/waypoint_updater_partial.py"
] | [
"#!/usr/bin/env python\n\nimport rospy\nfrom geometry_msgs.msg import PoseStamped\nfrom styx_msgs.msg import Lane, Waypoint\nfrom scipy.spatial import KDTree\nimport numpy as np\n\nimport math\n\n'''\nThis node will publish waypoints from the car's current position to some `x` distance ahead.\n\nAs mentioned in the... | [
[
"scipy.spatial.KDTree",
"numpy.array",
"numpy.dot"
]
] |
AhmedHathout/mathematics_dataset | [
"4fd371919d57258dcdedaa21b111fa61ee0a771f"
] | [
"mathematics_dataset/sample/polynomials.py"
] | [
"# Copyright 2018 DeepMind Technologies Limited.\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 appli... | [
[
"numpy.random.dirichlet",
"numpy.array",
"numpy.pad",
"numpy.empty",
"numpy.asarray",
"numpy.zeros",
"numpy.reshape",
"numpy.not_equal",
"numpy.count_nonzero",
"numpy.ones",
"numpy.prod",
"numpy.all",
"numpy.indices",
"numpy.maximum"
]
] |
ffffconf1/anon | [
"4359ee496b85d7c5037a488b72b0bc34e7df88a5"
] | [
"quant_eval/scripts/eurecom/evaluation_psnr_ssim.py"
] | [
"from PIL import Image\nimport numpy as np\nfrom PIL import Image\nimport pandas as pd\nimport argparse\nimport os\nfrom os import listdir,makedirs\nfrom os.path import isfile,join\nimport cv2\nimport os,glob\nfrom skimage.measure import compare_ssim\nimport re\nimport itertools\n\n\"\"\"\nScript to convert real an... | [
[
"numpy.array",
"numpy.asarray",
"pandas.DataFrame",
"numpy.sqrt",
"pandas.concat",
"pandas.read_csv"
]
] |
lsst-dm/Spectractor | [
"4ed1bf75d6bf970fd28308da30754485722835a8"
] | [
"tests/test_extractor.py"
] | [
"from numpy.testing import run_module_suite\n\nfrom spectractor import parameters\nfrom spectractor.extractor.extractor import Spectractor\nfrom spectractor.logbook import LogBook\nfrom spectractor.config import load_config\nimport os\nimport numpy as np\n\n\ndef test_logbook():\n logbook = LogBook('./ctiofulllo... | [
[
"numpy.sum",
"numpy.testing.run_module_suite",
"numpy.isclose",
"numpy.mean"
]
] |
Andrew-VanIderstine/RNN-and-DNN-from-scratch | [
"61331277245ca5892c6ece8138a5a2c825565b08"
] | [
"RNN and DNN from scratch.py"
] | [
"from math import exp\r\nfrom random import random\r\nfrom sklearn.model_selection import train_test_split\r\nfrom sklearn import metrics\r\nimport numpy as np\r\nimport librosa\r\nimport tensorflow as tf\r\nimport torch\r\nfrom keras.models import Sequential\r\nfrom keras.layers import Dense\r\nfrom keras.layers i... | [
[
"numpy.full",
"numpy.array",
"tensorflow.convert_to_tensor",
"numpy.asarray",
"tensorflow.keras.losses.MeanSquaredError",
"sklearn.model_selection.train_test_split",
"tensorflow.keras.Input"
]
] |
GuanLab/sepsis | [
"2476d894926f5676ef6376746c47b4c1b1111128"
] | [
"evaluation/evaluation_bootstrap_arg.py"
] | [
"from sklearn.metrics import auc\nimport numpy as np\nfrom sklearn.metrics import precision_recall_curve\nimport sklearn.metrics as metrics\nimport sys\n\nthe_list=['0','1','2','3','4']\ny_long=np.zeros(0)\npred_long=np.zeros(0)\nfor the_id in the_list:\n y=np.genfromtxt((sys.argv[1]+'.'+the_id),delimiter='\\t')... | [
[
"numpy.random.choice",
"numpy.zeros",
"numpy.genfromtxt",
"sklearn.metrics.auc",
"numpy.hstack",
"sklearn.metrics.roc_curve"
]
] |
nishio/atcoder | [
"8db36537b5d8580745d5f98312162506ad7d7ab4"
] | [
"agc047/a.py"
] | [
"#!/usr/bin/env python3\nimport sys\nsys.setrecursionlimit(10**6)\nINF = 10 ** 9 + 1 # sys.maxsize # float(\"inf\")\nMOD = 10 ** 9 + 7\n\n\ndef debug(*x):\n print(*x, file=sys.stderr)\n\n\ndef solve0(N, AS):\n ret = 0\n for i in range(N):\n for j in range(i + 1, N):\n if AS[i] * AS[j] % ... | [
[
"numpy.zeros"
]
] |
jason9693/ModelWriter | [
"ab80ba154ed862ac32e20b9cd1c6ee7aecec8388"
] | [
"model_writer.py"
] | [
"import pandas as pd\nfrom tabulate import tabulate\n\nclass ModelValue:\n '''\n Model Value class contain model name and some values for during training time.\n '''\n def __init__(self, model_name: str, values: dict):\n self.model_name = model_name\n self.values = values\n\n def set_va... | [
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
prography/ddeep_KYJ_JSY | [
"2da506cfd9e792a2d391de6f390b8b3b509b6c54"
] | [
"mtcnn_pytorch/src/detector.py"
] | [
"import numpy as np\r\nimport torch\r\nfrom torch.autograd import Variable\r\nfrom .get_nets import PNet, RNet, ONet\r\nfrom .box_utils import nms, calibrate_box, get_image_boxes, convert_to_square\r\nfrom .first_stage import run_first_stage\r\n\r\n\r\ndef detect_faces(image, min_face_size=20.0,\r\n ... | [
[
"numpy.round",
"torch.FloatTensor",
"numpy.where",
"numpy.vstack",
"numpy.expand_dims"
]
] |
plant99/MSS | [
"4d1cef8d3822000d8f5a1a88bdeec714fda70adb"
] | [
"mslib/retriever.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n\n mslib.retriever\n ~~~~~~~~~~~~~~~~~~~~\n\n automation within mss to create for instance a number of the same plots\n for several flights or several forecast steps\n\n This file is part of mss.\n\n :copyright: Copyright 2020 Joern Ungermann\n :license: APACHE... | [
[
"matplotlib.pyplot.text",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.gca"
]
] |
aditagrawal/Azure_ML | [
"30d7021c19aef8f56b05580cba25d38a5bc0b24e"
] | [
"1_Train_model_AML/1_Run_training_script.py"
] | [
"### Writing a script to train a model\n\nfrom azureml.core import Run\nimport pandas as pd\nimport numpy as np\nimport joblib\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LogisticRegression\n\n# Get the experiment run context\nrun = Run.get_context()\n\n# Prepare the data... | [
[
"numpy.float",
"sklearn.linear_model.LogisticRegression",
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"numpy.average"
]
] |
BadDevCode/lumberyard | [
"3d688932f919dbf5821f0cb8a210ce24abe39e9e"
] | [
"dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/tests/test_dictobject.py"
] | [
"\"\"\"\nTesting numba implementation of the numba dictionary.\n\nThe tests here only check that the numba typing and codegen are working\ncorrectly. Detailed testing of the underlying dictionary operations is done\nin test_dictimpl.py.\n\"\"\"\nfrom __future__ import print_function, absolute_import, division\n\ni... | [
[
"numpy.int8",
"numpy.random.seed",
"numpy.arange",
"numpy.intp",
"numpy.uint64",
"numpy.random.random",
"numpy.int32"
]
] |
lyakaap/ISC21-Descriptor-Track-1st | [
"843e28d55b32ae179acc2526aa59ee2f052e310f"
] | [
"exp/v98.py"
] | [
"import argparse\nimport builtins\nimport os\nimport pickle\nimport random\nimport shutil\nimport subprocess\nimport warnings\nfrom pathlib import Path\nfrom typing import Any, Dict, List, Optional\n\nimport h5py\nimport numpy as np\nimport timm\nimport torch\nimport torch.backends.cudnn as cudnn\nimport torch.dist... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.cuda.amp.autocast",
"torch.tile",
"torch.multiprocessing.spawn",
"torch.load",
"torch.nn.DataParallel",
"numpy.concatenate",
"torch.nn.SyncBatchNorm.convert_sync_batchnorm",
"torch.nn.init.constant_",
"torch.distributed.init_proces... |
aak65/glue | [
"7f03fe5dac4add2cb0d7347832cb9d1850f73440"
] | [
"glue/core/data_factories.py"
] | [
"\"\"\" Factory methods to build Data objects from files\n\nImplementation notes:\n\nEach factory method conforms to the folowing structure, which\nhelps the GUI Frontend easily load data:\n\n1) The first argument is a file name to open\n\n2) The return value is a Data object\n\n3) The function has a .label attribu... | [
[
"numpy.flipud",
"pandas.read_excel",
"pandas.read_csv"
]
] |
ADS-Group-15/Data-Preparation | [
"c7173af6da22c35067cafd88775a17817f81e599"
] | [
"Merge_Data.py"
] | [
"import pandas as pd\nimport csv\n\nhour_filename = 'LPPH.csv'\nperson_filename = 'LPPP.csv'\nsource_filename = 'Data.csv'\n\ndef merge_csv(file1, file2, file3):\n dfH = pd.read_csv(file1, sep=\",\", header=0)\n dfP = pd.read_csv(file2, sep=\",\", header=0)\n dfS = pd.read_csv(file3, sep=\",\", header=0)\n... | [
[
"pandas.read_csv"
]
] |
Alexfm101/Smartbots | [
"4dcd422b15ba84584c4e0991e21d0c6e5fbdb289"
] | [
"smartbots/enviroments/driving_0.py"
] | [
"'''\nDriving-v0 environment. Target with no obstacles.\n'''\n# OpenAI gym library imports\nimport gym\n# External libraries\nimport pybullet as p\nimport numpy as np\n# Local resources\nfrom smartbots.enviroments.driving_env import DrivingEnv\nimport smartbots.assets._car as car\nfrom smartbots.assets._cube import... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.linalg.norm"
]
] |
Jjthemoviestar/mr-data-likes-py | [
"93578ac4d989eef9d52fc6938c03e71dc575e662"
] | [
"unused code.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Mon Oct 8 15:20:20 2018\r\n\r\n@author: joshcole\r\n\"\"\"\r\nimport matplotlib.pyplot as plt\r\nimport F1_import as f1\r\n\r\n\r\naskcredloan_credhistnum = f1.loan_data['Credit_History_Num'] #see AskCreditLoans_Regression Analysis for more info\r\naskcredloan_lnsta... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.scatter"
]
] |
metya/Sun_Project | [
"799cbda66f7d898a39438daa9c16bf124562395a"
] | [
"utils.py"
] | [
"import copy\nimport os\nimport pickle\nimport time\nimport urllib\nimport warnings\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n# import pretrainedmodels\n\nfrom astropy.io import fits\n# from PIL import Image\nfrom skimage.transform import rescale, resize\n# from sklearn.metrics import f1_score\n# from... | [
[
"numpy.max",
"torch.utils.data.random_split",
"numpy.sign",
"numpy.abs",
"matplotlib.pyplot.axes",
"numpy.floor"
]
] |
baowj-678/TC | [
"4c9bf6bf2202c9930616259d3f3e1a2b0529a6e6"
] | [
"ALBERT/dataset/dataloader.py"
] | [
"\"\"\" 数据集加载器\r\n@Author: Bao Wenjie\r\n@Email: bwj_678@qq.com\r\n@Date: 2020/10/31\r\n\"\"\"\r\nfrom torch.utils.data import DataLoader\r\nfrom torch.nn.utils.rnn import pack_padded_sequence\r\nimport torch\r\n\r\ndef collate_func(X):\r\n \"\"\" batch数据处理 (snntence, length, label)\r\n @param:\r\n :pre_X ... | [
[
"torch.tensor",
"torch.sort"
]
] |
ac-optimus/pymc3 | [
"4759797bb2b8f4998f47f32c3fd8cd355529add8"
] | [
"pymc3/model.py"
] | [
"import collections\nimport functools\nimport itertools\nimport threading\nimport warnings\nfrom typing import Optional, TypeVar, Type, List, Union, TYPE_CHECKING, Any, cast\nfrom sys import modules\n\nimport numpy as np\nfrom pandas import Series\nimport scipy.sparse as sps\nimport theano.sparse as sparse\nfrom th... | [
[
"scipy.sparse.issparse",
"numpy.array",
"numpy.copyto",
"numpy.empty",
"numpy.asarray",
"numpy.zeros",
"numpy.ones",
"numpy.can_cast",
"numpy.prod",
"numpy.issubdtype",
"numpy.empty_like"
]
] |
mikezsx/dlstudy | [
"9eb7ecd3e525c9cff31ebd59a96794f212ca5e1e"
] | [
"tests/keras/preprocessing/image_test.py"
] | [
"import pytest\nfrom keras.preprocessing import image\nfrom PIL import Image\nimport numpy as np\nimport os\nimport shutil\nimport tempfile\n\n\nclass TestImage:\n\n def setup_class(cls):\n img_w = img_h = 20\n rgb_images = []\n gray_images = []\n for n in range(8):\n bias ... | [
[
"numpy.random.random",
"numpy.arange",
"numpy.random.rand",
"numpy.vstack"
]
] |
giladElichai/public | [
"1c86379f54999ca941eeb2199cc37a60f7939097"
] | [
"CnnArchitecture/VGG/VGGModel.py"
] | [
"\nfrom tensorflow.keras.layers import Input, Conv2D, MaxPooling2D, BatchNormalization, Activation, Dropout, Dense, Flatten\nfrom tensorflow.keras.models import Model\n\ndef conv_block(input_tensor, filters, n_blocks=2, kernel_size=3, padding='same'):\n\n x = input_tensor\n for _ in range(n_blocks):\n ... | [
[
"tensorflow.keras.layers.Input",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Dropout",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.layers.MaxPooling2D",
... |
Hertz-and-Alpha/zipline-reloaded | [
"eea4a2ccfc03d7fa4946defcb3cdf23469e4ae39"
] | [
"src/zipline/examples/buy_and_hold.py"
] | [
"#!/usr/bin/env python\n#\n# Copyright 2015 Quantopian, 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 requir... | [
[
"pandas.Timestamp"
]
] |
MEDCOMP/SC2_ACME | [
"511f5c4388ad4b8ef157e46678cc22bb0a199ad4",
"511f5c4388ad4b8ef157e46678cc22bb0a199ad4"
] | [
"acme/agents/tf/actors.py",
"acme/tf/networks/stochastic.py"
] | [
"# python3\n# Copyright 2018 DeepMind Technologies Limited. 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... | [
[
"tensorflow.function"
],
[
"tensorflow.zeros",
"tensorflow.range",
"tensorflow.gather_nd",
"tensorflow.transpose",
"tensorflow.debugging.assert_equal",
"tensorflow.nn.softmax"
]
] |
twicki/dace | [
"75619ef87396c9e48b877ac4a12b333b528abd7c"
] | [
"tests/numpy/array_creation_test.py"
] | [
"# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.\nimport dace\nimport numpy as np\nfrom common import compare_numpy_output\n\n# M = dace.symbol('M')\n# N = dace.symbol('N')\n\nM = 10\nN = 20\n\n\n@dace.program\ndef empty():\n return np.empty([M, N], dtype=np.uint32)\n\n\ndef test_empt... | [
[
"numpy.zeros_like",
"numpy.ones_like",
"numpy.empty",
"numpy.zeros",
"numpy.copy",
"numpy.ones",
"numpy.complex32",
"numpy.identity",
"numpy.ndarray",
"numpy.empty_like",
"numpy.full_like"
]
] |
karan-w/WebScraping | [
"1d8de647df689f46b97be8084e9f15bddfa658eb"
] | [
"google-news-scraping/scraper.py"
] | [
"import requests\nfrom bs4 import BeautifulSoup\nimport pickle \nimport csv \nimport urllib.request \nimport json\nfrom vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer \nfrom selenium import webdriver\nfrom webdriver_manager.chrome import ChromeDriverManager\nimport datetime\nimport time\nimport arg... | [
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
GH-Jo/PROFIT | [
"7a42553c2d1291200b5b01942791113332252829"
] | [
"quant_op/softlsq.py"
] | [
"from __future__ import absolute_import\r\nfrom __future__ import division\r\nfrom __future__ import print_function\r\nfrom __future__ import unicode_literals\r\n\r\nimport torch \r\nimport torch.nn as nn \r\nimport torch.nn.functional as F\r\nfrom torch.nn.parameter import Parameter\r\nimport numpy as np \r\nfrom ... | [
[
"torch.nn.functional.softplus",
"torch.no_grad",
"numpy.exp",
"torch.nn.functional.linear",
"torch.nn.functional.hardtanh",
"numpy.sort",
"numpy.abs",
"torch.nn.functional.relu",
"torch.nn.functional.pad",
"torch.Tensor",
"torch.nn.functional.conv2d"
]
] |
wwhio/awesome-DeepLearning | [
"2cc92edcf0c22bdfc670c537cc819c8fadf33fac",
"2cc92edcf0c22bdfc670c537cc819c8fadf33fac"
] | [
"transformer_courses/BERT_distillation/PaddleSlim-develop/paddleslim/nas/darts/search_space/conv_bert/reader/cls.py",
"transformer_courses/BERT_distillation/PaddleSlim-develop/paddleslim/common/rl_controller/ddpg/ddpg_controller.py"
] | [
"# Copyright (c) 2019 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.random.seed",
"numpy.random.shuffle"
],
[
"numpy.random.normal",
"numpy.abs",
"numpy.asarray",
"numpy.expand_dims"
]
] |
junmuz/pandapower | [
"24ed3056558887cc89f67d15b5527523990ae9a1"
] | [
"pandapower/control/util/auxiliary.py"
] | [
"# -*- coding: utf-8 -*-\n\n# Copyright (c) 2016-2021 by University of Kassel and Fraunhofer Institute for Energy Economics\n# and Energy System Technology (IEE), Kassel. All rights reserved.\nimport csv\nimport random\nfrom functools import reduce\nfrom pandapower.auxiliary import ADict\n\nimport numpy as np\nimpo... | [
[
"numpy.asarray",
"pandas.Int64Index",
"matplotlib.pyplot.plot",
"numpy.isscalar",
"numpy.ndim",
"numpy.linspace"
]
] |
Jade-flow/manim | [
"e359f520bc7010d4ce9c3ffa3668049b0d512b1d"
] | [
"manimlib/mobject/mobject.py"
] | [
"import copy\nimport itertools as it\nimport random\nimport sys\nimport moderngl\nfrom functools import wraps\n\nimport numpy as np\n\nfrom manimlib.constants import *\nfrom manimlib.utils.color import color_gradient\nfrom manimlib.utils.color import get_colormap_list\nfrom manimlib.utils.color import rgb_to_hex\nf... | [
[
"numpy.repeat",
"numpy.array",
"numpy.linalg.norm",
"numpy.dot",
"numpy.zeros",
"numpy.identity",
"numpy.sign",
"numpy.transpose",
"numpy.arange",
"numpy.abs",
"numpy.all",
"numpy.linspace",
"numpy.vstack"
]
] |
solomon-han/convince | [
"8d32118b3339fc9820aa59af4815f87eaca95f24"
] | [
"ParlAI/parlai/core/pytorch_data_teacher.py"
] | [
"#!/usr/bin/env python3\n\n# 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 (NOTE: To use this class, please follow the tutorial here:\n http://parl.ai/static/docs/tutorial... | [
[
"torch.utils.data.sampler.RandomSampler",
"torch.version.__version__.startswith",
"torch.multiprocessing.Lock",
"torch.multiprocessing.Value",
"torch.utils.data.sampler.SequentialSampler",
"torch.utils.data.DataLoader",
"torch.as_tensor"
]
] |
murali1996/ConMask | [
"3e16e35309ca73e4010533d6af7a82f84e3e8079"
] | [
"ndkgc/utils/__init__.py"
] | [
"import numpy as np\n\nimport tensorflow as tf\n\n\ndef count_line(file_path):\n counter = 0\n with open(file_path, 'r', encoding='utf8') as f:\n for _ in f:\n counter += 1\n return counter\n\n\ndef valid_vocab_file(file_path):\n with open(file_path, 'r', encoding='utf8') as f:\n ... | [
[
"tensorflow.logging.info",
"numpy.sqrt"
]
] |
thomasvrussell/snlstm | [
"8d7f6e2fa03b2486b8297641a430e1ca8172e6df",
"8d7f6e2fa03b2486b8297641a430e1ca8172e6df"
] | [
"snail/utils/GPLightCurve.py",
"snail/SpecProc.py"
] | [
"import warnings\nimport numpy as np\nfrom sklearn.gaussian_process import GaussianProcessRegressor\nfrom sklearn.gaussian_process.kernels import RBF, ConstantKernel as CK\n\ndef GP_Interpolator(X, Y, eY, X_q, NaN_fill=0.1):\n # * nan-correction\n Avmask = ~np.isnan(Y)\n X, Y, eY = X[Avmask], Y[Avmask], eY... | [
[
"numpy.max",
"numpy.isnan",
"numpy.atleast_2d",
"numpy.min",
"sklearn.gaussian_process.kernels.RBF",
"numpy.sqrt",
"sklearn.gaussian_process.GaussianProcessRegressor",
"sklearn.gaussian_process.kernels.ConstantKernel"
],
[
"numpy.max",
"scipy.interpolate.interp1d",
... |
ravipatelxyz/kbc-meta | [
"ff60a159d7d9917f4357c8663974410e4c901531",
"ff60a159d7d9917f4357c8663974410e4c901531"
] | [
"toymeta/kbc-cli-toymeta2_higher_sqrdL2norm_multidim_noiseinject.py",
"tools/results-cli.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n# %%\nimport argparse\nimport sys\nimport os\n\nimport multiprocessing\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom copy import deepcopy\n\nimport pandas as pd\nimport torch\nfrom torch import nn, optim\n\nimport higher\nimport wandb\n\ntorch.set_num... | [
[
"torch.optim.Adagrad",
"torch.ones",
"pandas.DataFrame",
"torch.norm",
"matplotlib.pyplot.savefig",
"torch.manual_seed",
"torch.tensor",
"matplotlib.pyplot.tight_layout",
"torch.device",
"numpy.array",
"numpy.percentile",
"matplotlib.pyplot.title",
"torch.optim.... |
Superuserjoy/Yolov4-Deepsort-for-google-colab | [
"1261dc3c8bd2d390eb95ddb3dc2f46fedd3b5243"
] | [
"object_tracker.py"
] | [
"import os\n# comment out below line to enable tensorflow logging outputs\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\nimport time\nimport tensorflow as tf\nphysical_devices = tf.config.experimental.list_physical_devices('GPU')\nif len(physical_devices) > 0:\n tf.config.experimental.set_memory_growth(physical_devi... | [
[
"numpy.array",
"numpy.delete",
"tensorflow.shape",
"numpy.asarray",
"tensorflow.compat.v1.ConfigProto",
"tensorflow.compat.v1.InteractiveSession",
"tensorflow.config.experimental.set_memory_growth",
"tensorflow.lite.Interpreter",
"matplotlib.pyplot.get_cmap",
"numpy.linspac... |
83286415/DeepLearningWithPythonKeras | [
"d3e7dd3b206d3d22a45ad4967a00edd26c4cbe75"
] | [
"6.3.5-a-first-recurrent-baseline.py"
] | [
"# FROM 6.3py\n# 6.3.1 prepare the climate data\n\nimport keras\nprint(keras.__version__) # 2.1.6\nimport os\n\n\n# prepare the climate data\nbase_dir = 'D:/AI/deep-learning-with-python-notebooks-master'\nclimate_dir = os.path.join(base_dir, 'jena_climate')\nfname = os.path.join(climate_dir, 'jena_climate_2009_201... | [
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"numpy.random.randint",
"matplotlib.pyplot.show"
]
] |
waffoo/accel | [
"7aaa45af2d120f9ed49d10f8654ff5af03feb705"
] | [
"examples/atari_cql.py"
] | [
"import os\nfrom logging import DEBUG, getLogger\nfrom time import time\n\nfrom comet_ml import Experiment # isort: split\nimport gym\nimport hydra\nimport numpy as np\n# from gym.utils.play import play import random\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim... | [
[
"torch.nn.Linear",
"numpy.round",
"numpy.load",
"torch.nn.Conv2d",
"torch.cuda.is_available"
]
] |
databricks-academy/scalable-machine-learning-with-apache-spark | [
"2b560dea766e2e6589defaaf6d9d15f361ce6db6",
"2b560dea766e2e6589defaaf6d9d15f361ce6db6"
] | [
"Scalable-Machine-Learning-with-Apache-Spark/ML 13 - Training with Pandas Function API.py",
"Scalable-Machine-Learning-with-Apache-Spark/Solutions/Labs/ML 08L - Hyperopt Lab.py"
] | [
"# Databricks notebook source\n# MAGIC %md-sandbox\n# MAGIC \n# MAGIC <div style=\"text-align: center; line-height: 0; padding-top: 9px;\">\n# MAGIC <img src=\"https://databricks.com/wp-content/uploads/2018/03/db-academy-rgb-1200px.png\" alt=\"Databricks Learning\" style=\"width: 600px\">\n# MAGIC </div>\n\n# COM... | [
[
"pandas.DataFrame",
"sklearn.metrics.mean_squared_error",
"sklearn.ensemble.RandomForestRegressor"
],
[
"numpy.random.default_rng",
"sklearn.ensemble.RandomForestRegressor",
"sklearn.model_selection.cross_val_score"
]
] |
sheikhahnaf/upho | [
"c658538093d471eb20accc4028406034cb223ecc"
] | [
"upho/harmonic/dynamical_matrix.py"
] | [
"import numpy as np\nfrom phonopy.structure.cells import get_reduced_bases\nfrom phonopy.harmonic.dynamical_matrix import DynamicalMatrix\n\n\nclass UnfolderDynamicalMatrix(DynamicalMatrix):\n \"\"\"Dynamical matrix class\n\n When prmitive and supercell lattices are L_p and L_s, respectively,\n frame F is ... | [
[
"numpy.array",
"numpy.dot",
"numpy.linalg.norm",
"numpy.zeros",
"numpy.rint",
"numpy.min",
"numpy.abs",
"numpy.linalg.inv"
]
] |
skw32/CoFFEE_PoissonSolver_KO_pa | [
"27a0ec8021ffefda1a4a4aa3d8086ac7d5561559"
] | [
"Examples/1D/NanoRibbon_BN/Model_Scaling/plot_fit.py"
] | [
"#!/usr/bin/env python\n\nimport sys,string\nimport matplotlib.pyplot as plt\nfrom matplotlib.ticker import AutoMinorLocator\nimport matplotlib.gridspec as gridspec\nimport numpy as np\n\nfig, ax = plt.subplots()\n\n# Values of alpha:\nalpha = np.array([6,8,10,15,20,30])\n\n# Corresponding model energies:\nEn = np.... | [
[
"numpy.array",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots",
"numpy.arange",
"numpy.polyfit",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.show"
]
] |
KansKim/oneplus | [
"df6aad250dba9bc36a0eccfe960026e3e240f057"
] | [
"selfdrive/ntune.py"
] | [
"import os\nimport fcntl\nimport signal\nimport json\nimport numpy as np\n\nfrom selfdrive.hardware import TICI\n\nCONF_PATH = '/data/ntune/'\nCONF_LQR_FILE = '/data/ntune/lat_lqr.json'\n\nntunes = {}\n\ndef file_watch_handler(signum, frame):\n global ntunes\n for ntune in ntunes.values():\n ntune.handle()\n\n... | [
[
"numpy.array"
]
] |
jankukacka/lwnet | [
"5b91c1897e68021c1dac263645d1d3050190ab35"
] | [
"analyze_results.py"
] | [
"import argparse\nfrom PIL import Image\nimport os, sys\nimport os.path as osp\nimport pandas as pd\nfrom tqdm import tqdm\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import roc_curve, auc, confusion_matrix, accuracy_score\nfrom sklearn.metrics import matthews_corrcoef\nfrom utils.eva... | [
[
"numpy.array",
"sklearn.metrics.confusion_matrix",
"pandas.DataFrame",
"matplotlib.pyplot.plot",
"numpy.hstack",
"matplotlib.pyplot.legend",
"numpy.linspace",
"sklearn.metrics.accuracy_score",
"matplotlib.pyplot.figure",
"numpy.argmax",
"sklearn.metrics.auc",
"panda... |
ndlrf-rnd/sgpt | [
"de45632cc6e12612771146725a0f6fc4ff42555c"
] | [
"biencoder/nli_msmarco/sentence-transformers/examples/training/ms_marco/train_bi-encoder_mnrl.py"
] | [
"\"\"\"\nThis examples show how to train a Bi-Encoder for the MS Marco dataset (https://github.com/microsoft/MSMARCO-Passage-Ranking).\n\nThe queries and passages are passed independently to the transformer network to produce fixed sized embeddings.\nThese embeddings can then be compared using cosine-similarity to ... | [
[
"numpy.random.seed",
"torch.utils.data.DataLoader"
]
] |
joshuagornall/jax | [
"c97cd0a526c12ad81988fd58c1c66df4ddd71813"
] | [
"jax/experimental/jax2tf/tests/shape_poly_test.py"
] | [
"# 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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"tensorflow.TensorSpec",
"numpy.array",
"numpy.random.rand",
"tensorflow.GradientTape",
"numpy.ones",
"tensorflow.Variable",
"tensorflow.function",
"numpy.shape",
"numpy.float32",
"numpy.stack",
"numpy.arange",
"numpy.prod"
]
] |
DominiqueMaciejewski/asreview | [
"eb1066074613a5f6f930ff610ff92184e9244f4f",
"eb1066074613a5f6f930ff610ff92184e9244f4f"
] | [
"asreview/io/ris_writer.py",
"asreview/batch.py"
] | [
"# Copyright 2019-2021 The ASReview 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 r... | [
[
"pandas.isnull"
],
[
"numpy.random.RandomState"
]
] |
HASTE-project/desktop-agent | [
"71a3d0d69b5a6660d63158897a53d1a65aba49ba"
] | [
"scrap/plot-queue.py"
] | [
"import matplotlib.pyplot as plt\n\nLOG_FILE_NAME = '2019_03_22__11_40_21_trash'\n\ntimestamps = []\npre_processeds = []\nnot_pre_processeds = []\ntotal = []\n\nlines = []\n\nwith open('../../logs/log_%s.log' % LOG_FILE_NAME, 'r') as f:\n for line in f:\n if 'PLOT' not in line:\n continue\n ... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.show",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.clf"
]
] |
sugartom/TF-Serving-Downloads | [
"4bf8eeacafd3a58bc701c23bb31b73463704cedd",
"4bf8eeacafd3a58bc701c23bb31b73463704cedd"
] | [
"tensorflow_serving/example/tf_openpose_client.py",
"tensorflow_serving/example/inception_client_master_version_v2.py"
] | [
"# Copyright 2016 Google Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appl... | [
[
"tensorflow.contrib.util.make_tensor_proto",
"tensorflow.app.run",
"numpy.expand_dims",
"tensorflow.app.flags.DEFINE_string"
],
[
"tensorflow.app.run",
"tensorflow.python.framework.tensor_util.MakeNdarray"
]
] |
inXS212/Saltie | [
"78224ecdcbe049c9a798c5cfac12c223efc0596f"
] | [
"bot_code/models/actor_critic/base_actor_critic.py"
] | [
"from bot_code.models import base_reinforcement\r\nimport numpy as np\r\nimport tensorflow as tf\r\nimport random\r\nimport bot_code.livedata.live_data_util as live_data_util\r\nimport collections\r\n\r\n\r\nclass BaseActorCritic(base_reinforcement.BaseReinforcement):\r\n frames_since_last_random_action = 0\r\n ... | [
[
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.multinomial",
"tensorflow.matmul",
"tensorflow.greater",
"tensorflow.stack",
"tensorflow.nn.softmax",
"tensorflow.identity",
"tensorflow.cast",
"tensorflow.train.GradientDescentOptimizer",
"tensorflow.random_normal_i... |
mawanda-jun/TReNDS-neuroimaging | [
"8075f4196e7eb812ce96b5a10b18d13c293ce727"
] | [
"training_net_info/PlainResNet3D50_numInitFeatures.64_lr.0.0001_drop.0.4_batchsize.34_loss.metric_optimizer.adamw_patience.10_other_net.32outputfeatures/train.py"
] | [
"from model import Model\nfrom dataset import TReNDS_dataset, ToTensor, AugmentDataset, fMRI_Aumentation, Normalize, RandomCropToDim, ResizeToDim\nimport shutil\nfrom torch.utils.data import DataLoader, random_split\nfrom torchvision import transforms\nimport os\n\nos.setgid(1000), os.setuid(1000)\n\n\ndef clean_fo... | [
[
"torch.utils.data.random_split",
"torch.utils.data.DataLoader"
]
] |
wallacegferreira/PythonML_Study | [
"151e96ba4019dc03a8b4fb1cab7d9b0e637f7905"
] | [
"BasicPython/lin_regress_multiv_poly.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Apr 8 15:05:29 2020\n\n@author: Wallace\n\nExamples based on https://realpython.com/linear-regression-in-python/\n\"\"\"\n\n\n\n# Step 1: Import packages\nimport numpy as np\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.preprocessing import Polyno... | [
[
"numpy.array",
"sklearn.linear_model.LinearRegression",
"sklearn.preprocessing.PolynomialFeatures",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show"
]
] |
Wenyuan-Vincent-Li/pixpixHD | [
"7553e0f9bb23b453a476404f00607bd8f75854a9"
] | [
"precompute_feature_maps.py"
] | [
"from options.train_options import TrainOptions\nfrom data.data_loader import CreateDataLoader\nfrom models.models import create_model\nimport os\nimport util.util as util\nfrom torch.autograd import Variable\nimport torch.nn as nn\n\nopt = TrainOptions().parse()\nopt.nThreads = 1\nopt.batchSize = 1 \nopt.serial_ba... | [
[
"torch.nn.Upsample"
]
] |
linyang23/AI-Python-Code-Implementations-with-Notes | [
"af729c652a301b199d568d5989adc5ed6413dcf9"
] | [
"numpy_test/numpy_c.py"
] | [
"# coding=utf-8\nimport numpy as np\nnd5=np.random.random([3,3]) #生成3行3列的矩阵\nprint(nd5)\nprint(type(nd5))\n\n'''输出 \n[[0.30996243 0.70525938 0.23778251]\n [0.36607574 0.07691564 0.25879282]\n [0.78231402 0.64058363 0.44167507]]\n<class 'numpy.ndarray'>\n'''"
] | [
[
"numpy.random.random"
]
] |
Muxelmann/animlib | [
"f85c13ecdc98b49aae64c7cb02e5dccc2dbecfd7"
] | [
"animlib/animations/unveil.py"
] | [
"from animlib.animations.animation import Animation, AnimationOut\nfrom animlib.geometies.base import Base\n\ntry:\n import cairo\nexcept:\n import cairocffi as cairo\nimport numpy as np\nfrom enum import Enum\n\nclass UnveilDirections(Enum):\n LEFT = ( 1.0, 0.0, 1.0, 0.0)\n TOP_LEFT = ... | [
[
"numpy.concatenate",
"numpy.array"
]
] |
OpenSourceEconomics/tespy | [
"2bf3e6dda867514a04d5816609010bf09e436d44"
] | [
"docs/_static/codes/fig-gaussian-peak.py"
] | [
"\"\"\"Figure of the Gaussian Peak Integrand function in 3D.\n\nx1 is evaluated on [0, 1]\nx2 is evaluated on [0, 1]\ny is the result of applying the Gaussian Peak Integrand function on\neach combination of x1 and x2 and u1,u2 = 0.5\n\n\"\"\"\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom mpl_toolkits.m... | [
[
"numpy.array",
"numpy.linspace",
"matplotlib.pyplot.figure"
]
] |
JoeshpCheung/trans_emotion | [
"5909611c1ae65f9e4e64e5584008d731ca4b7eb9"
] | [
"test_transformers.py"
] | [
"#! /usr/bin/env python\n# -*- coding: utf-8 -*-\n# vim:fenc=utf-8\n#\n# Copyright © 2021 jasoncheung <jasoncheung@iZwz95ffbqqbe9pkek5f3tZ>\n#\n# Distributed under terms of the MIT license.\n\n\"\"\"\n\n\"\"\"\nimport os\n\nos.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"1\"\nimport tensorflow as tf\n\nfrom transformers i... | [
[
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"sklearn.metrics.accuracy_score",
"sklearn.metrics.precision_recall_fscore_support"
]
] |
Jun1453/tomofilter | [
"efd8db983c92386ae93a4544e057d61b2d38b89c"
] | [
"blockmodel.py"
] | [
"import numpy as np\n\nRADIUS1 = [3484.3,3661.0,3861.0,4061.0,4261.0,4461.0,4861.0,5061.0,5261.0,5411.0,5561.0,5711.0,5841.0,5971.0,6071.0,6171.0,6260.0,6349.0]\nRADIUS2 = [3661.0,3861.0,4061.0,4261.0,4461.0,4861.0,5061.0,5261.0,5411.0,5561.0,5711.0,5841.0,5971.0,6071.0,6171.0,6260.0,6349.0,6371.0]\n\nclass Model(l... | [
[
"numpy.round",
"numpy.deg2rad",
"numpy.mean",
"numpy.zeros"
]
] |
takat0m0/test_code | [
"1cd90f8a97bf3d2417319bc48284d7d4be331c94"
] | [
"tf_rnn/rnn_layer.py"
] | [
"# -*- coding:utf-8 -*-\n\nimport os\nimport sys\n\nimport numpy as np\nimport tensorflow as tf\n\nfrom tf_util import Layers\n\nclass RNNLayers(Layers):\n def __init__(self, name_scopes, hidden_dims):\n assert(len(name_scopes) == 1)\n super().__init__(name_scopes)\n self.hidden_dims = hidde... | [
[
"tensorflow.shape",
"tensorflow.nn.rnn_cell.GRUCell",
"tensorflow.variable_scope",
"tensorflow.placeholder",
"tensorflow.nn.dynamic_rnn"
]
] |
karencfisher/deskbot | [
"655caef26bc7e943976b75ff0c6a597c42610f2d"
] | [
"face_track_backup.py"
] | [
"import cv2\nimport numpy as np\nimport picamera, picamera.array\nimport time\nimport haar_detect\nimport dnn_detect as dn\nimport talker \nfrom adafruit_servokit import ServoKit\nimport pid\n\n# define pan function\nprev_x = 0\nprev_y = 0\n\nclass facetrack():\n \n def __init__(self):\n \n # se... | [
[
"numpy.arctan"
]
] |
dionis/ABSA-DeepMultidomain | [
"36371065e15f01e5dd2ebaaf9f39abf8b6282de7"
] | [
"approaches/random.py"
] | [
"import sys\nimport numpy as np\nimport torch\n\nimport utils\n\nclass Appr(object):\n\n def __init__(self,model,nepochs=0,sbatch=0,lr=0,lr_min=1e-4,lr_factor=3,lr_patience=5,clipgrad=10000,args=None):\n self.model=model\n\n self.criterion=None\n self.optimizer=None\n\n return\n\n ... | [
[
"torch.LongTensor",
"numpy.random.shuffle"
]
] |
awais307/message-ix-models | [
"560b5ae6d7ecde42be8d90cbcbd4bbd14ca1cb1d"
] | [
"message_ix_models/testing.py"
] | [
"import logging\nfrom copy import deepcopy\nfrom pathlib import Path\n\nimport click.testing\nimport message_ix\nimport pandas as pd\nimport pytest\nfrom ixmp import Platform\nfrom ixmp import config as ixmp_config\n\nfrom message_ix_models import cli, util\nfrom message_ix_models.util._logging import mark_time, pr... | [
[
"pandas.ExcelFile",
"pandas.ExcelWriter"
]
] |
dashee87/blogScripts | [
"526bca57777258e55a140e557e3fa3b813441780"
] | [
"Python/2018-09-13-dixon-coles-and-time-weighting/dixon_coles_decay_xi_5season.py"
] | [
"import pandas as pd\r\nimport numpy as np\r\nimport pickle\r\nfrom scipy.stats import poisson,skellam\r\nfrom scipy.optimize import minimize, fmin\r\nfrom multiprocessing import Pool\r\n\r\ndef calc_means(param_dict, homeTeam, awayTeam):\r\n return [np.exp(param_dict['attack_'+homeTeam] + param_dict['defence_'+... | [
[
"pandas.to_datetime",
"numpy.array",
"numpy.array_equal",
"pandas.DataFrame",
"scipy.stats.poisson.pmf",
"numpy.exp",
"numpy.triu",
"numpy.random.uniform",
"numpy.diag",
"scipy.optimize.minimize",
"numpy.tril"
]
] |
entn-at/voxceleb_trainer | [
"b288f2a2175ff772647343567395db3b645a2124"
] | [
"models/ResNetSE34.py"
] | [
"#! /usr/bin/python\n# -*- encoding: utf-8 -*-\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.nn import Parameter\nfrom models.ResNetBlocks import *\n\nclass ResNetSE(nn.Module):\n def __init__(self, block, layers, num_filters, nOut, encoder_type='SAP', **kwargs):\n\n ... | [
[
"torch.nn.InstanceNorm1d",
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.FloatTensor",
"torch.nn.init.kaiming_normal_",
"torch.nn.init.constant_",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.fu... |
vineeths96/Pattern-Recognition-2 | [
"8691c4fe658028bc9d4a06eb17c216eaa5193df9"
] | [
"problem_4/linear_regression_train.py"
] | [
"from sklearn.linear_model import LinearRegression\nfrom sklearn.utils import shuffle\n\n\n# Trains linear regression model\ndef linear_regression_train(X_train, Y_train):\n X_train, Y_train = shuffle(X_train, Y_train, random_state=0)\n\n linear_reg_model = LinearRegression()\n linear_reg_model.fit(X_train... | [
[
"sklearn.linear_model.LinearRegression",
"sklearn.utils.shuffle"
]
] |
PolaeCo/restyle-encoder | [
"ca30e5655314b59962cc630745934a17ff717039"
] | [
"cloneGAN.py"
] | [
"import argparse\r\nfrom argparse import Namespace\r\nimport time\r\nimport os\r\nimport sys\r\nimport pprint\r\nimport numpy as np\r\nfrom PIL import Image\r\nimport torch\r\nimport torchvision.transforms as transforms\r\n\r\nsys.path.append(\".\")\r\nsys.path.append(\"..\")\r\n\r\nfrom utils.common import tensor2... | [
[
"torch.no_grad",
"torch.load"
]
] |
WangShaoSUN/LWDRLD | [
"bc71c2588fb8c65076b8353bb0c9e8f1040db4e6"
] | [
"DQN_Zoo/DQN_per.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n# Implementation of Deep Q-Network (DQN)\n# Paper: https://www.nature.com/articles/nature14236\n# And implementation of Prioritized Experience Replay (PER)\n# Paper: https://arxiv.org/abs/1511.05952\n\ndevice = torch.device... | [
[
"torch.nn.Linear",
"torch.arange",
"torch.max",
"torch.no_grad",
"torch.nn.Conv2d",
"torch.cuda.is_available",
"numpy.random.uniform",
"torch.squeeze",
"torch.load",
"torch.as_tensor",
"torch.nn.init.calculate_gain",
"torch.nn.init.orthogonal_",
"torch.argmax"
... |
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