repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
LiangYang666/mmfewshot | [
"ded7c357edcca29a84e61e6ce55ef9dff407d112"
] | [
"tests/test_detection_data/test_datasets/test_query_aware_dataset.py"
] | [
"# Copyright (c) OpenMMLab. All rights reserved.\nimport tempfile\n\nimport numpy as np\nfrom mmdet.apis import set_random_seed\n\nfrom mmfewshot.detection.datasets.builder import build_dataset\n\n\ndef test_query_aware_dataset():\n set_random_seed(0)\n data_config = {\n 'type': 'QueryAwareDataset',\n ... | [
[
"numpy.sum"
]
] |
shikhar-srivastava/hover_net | [
"d4e8e129a4ad72f5d574a78c036449b496421529"
] | [
"misc/viz_utils.py"
] | [
"import cv2\nimport math\nimport random\nimport colorsys\nimport numpy as np\nimport itertools\nimport matplotlib.pyplot as plt\nfrom matplotlib import cm\n\nfrom .utils import get_bounding_box\n\n####\ndef colorize(ch, vmin, vmax):\n \"\"\"Will clamp value value outside the provided range to vmax and vmin.\"\"\... | [
[
"numpy.array",
"numpy.asarray",
"matplotlib.pyplot.get_cmap",
"numpy.copy",
"matplotlib.pyplot.subplots",
"numpy.unique"
]
] |
IsmaelElsharkawi/new_pororo_repo | [
"4617083b420615b8a3eb0f44d02e4e91a8f407f7",
"4617083b420615b8a3eb0f44d02e4e91a8f407f7"
] | [
"dcsgan/layers.py",
"mart/data_loader.py"
] | [
"import numpy as np\r\nimport torch\r\nimport torch.nn as nn\r\nimport torch.nn.functional as F\r\n \r\nclass DynamicFilterLayer(nn.Module): #MergeLayer\r\n def __init__(self, filter_size, stride=(1,1), pad=(0,0), flip_filters=False, grouping=False):\r\n super(DynamicFilterLayer, self).__init__()\r\n ... | [
[
"torch.cat",
"torch.nn.functional.Conv2d",
"torch.nn.functional.conv1d",
"numpy.prod",
"torch.nn.functional.conv2d",
"torch.sum"
],
[
"numpy.array",
"torch.save",
"numpy.load",
"numpy.random.randn",
"torch.nn.Upsample",
"numpy.swapaxes",
"numpy.random.randin... |
MichaelSinsbeck/paper_hyperparameters-without-exploratory-phase | [
"50fee3aaee14748cb1970ae47ed7dc7ebd6098d5",
"50fee3aaee14748cb1970ae47ed7dc7ebd6098d5"
] | [
"experiment 5/bbi/design.py",
"experiment 4/04_1_computation.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nModule sequentialDesign\nContains the following design methods (including some helper functions):\n 1) design_linearized - the normal sequential design as described in my paper\n If used with a FieldColleciton, becomes the linearized version\n 2... | [
[
"numpy.full",
"numpy.array",
"numpy.isnan",
"numpy.random.choice",
"numpy.zeros",
"numpy.sum",
"numpy.ones",
"numpy.exp",
"numpy.prod",
"numpy.argmax",
"numpy.arange",
"numpy.abs",
"numpy.sqrt",
"numpy.average",
"numpy.diag"
],
[
"numpy.array",
... |
zhengmidon/jingju_baseline | [
"4c6ef80ac14b4640efb1f81cde38df2ac35eacd2"
] | [
"uer/utils/adversarial.py"
] | [
"import torch\r\n\r\n\r\nclass FGM(object):\r\n \"\"\"\r\n refer to the paper: FGM(Fast Gradient Method)\r\n Adversarial training methods for semi-supervised text classification\r\n \"\"\"\r\n\r\n def __init__(self, model):\r\n self.model = model\r\n self.backup = {}\r\n\r\n def atta... | [
[
"torch.norm",
"torch.isnan"
]
] |
tonandr/ymc | [
"4d9db086d95fef21fed6891e987873c00539dbfe"
] | [
"src/space/ymc_opt.py"
] | [
"'''\nCreated on Dec. 1, 2018\n\n@author: Inwoo Chung (gutomitai@gmail.com)\n'''\n\nimport sys\nimport numpy as np\nimport os\nimport argparse\n\nimport pandas as pd\nimport time\n\nnum_iter = 1200\n\ndef calProposalDistVal(pre, cur, cov):\n '''\n Calculate a proposal distribution value.\n @param p... | [
[
"numpy.random.rand",
"numpy.zeros",
"pandas.DataFrame",
"numpy.linalg.det",
"numpy.identity",
"numpy.random.multivariate_normal",
"numpy.power",
"numpy.abs",
"pandas.read_csv",
"numpy.linalg.inv"
]
] |
surrealyz/DeepBayes | [
"b9d9e7a3708d1faf7aa918756619d99b0e71ae3e"
] | [
"models/conv_generator_cifar10_F.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\nimport tensorflow as tf\nfrom mlp import mlp_layer\nfrom convnet import ConvNet, construct_filter_shapes\n\n\"\"\"\ngenerator p(z)p(x|z)p(y|z), GBZ\n\"\"\"\n \ndef deconv_layer(output_shape, filter_shape, activation, strides, name):\n scale = 1.0 / ... | [
[
"tensorflow.exp",
"tensorflow.nn.relu",
"tensorflow.random_uniform",
"numpy.prod",
"numpy.random.randint",
"tensorflow.nn.conv2d_transpose",
"tensorflow.nn.sigmoid",
"tensorflow.split"
]
] |
kduy/linde-intel-hackathon | [
"9e1ad5459a607a691b9d280e9b94e0cdf9c3c081"
] | [
"linde_make_features.py"
] | [
"import pandas as pd\nimport numpy as np\nimport os.path\nimport os\nimport argparse\n\nimport extractor\nfrom feeder import VarFeeder\nimport numba\nfrom typing import Tuple, Dict, Collection, List\n\nroot = '/mnt/md0/hackathon/'\ndef read_cached(name=\"linde_sample_5\") -> pd.DataFrame:\n \"\"\"\n Reads csv... | [
[
"pandas.isnull",
"numpy.full",
"pandas.read_pickle",
"numpy.isnan",
"numpy.empty",
"pandas.DatetimeIndex",
"pandas.Timedelta",
"numpy.nan_to_num",
"numpy.sin",
"numpy.sum",
"pandas.date_range",
"numpy.mean",
"pandas.DateOffset",
"numpy.std",
"numpy.cos",... |
anguillanneuf/deep-reinforcement-learning | [
"9284bdfa2ba6cd136536ebd5d04e6c9fb9e492f8"
] | [
"p3_collab-compet/maddpg.py"
] | [
"import numpy as np\nimport torch\n\nfrom ddpg import DDPGAgent\nfrom utilities import soft_update, transpose_to_tensor, transpose_list\n\n\ndevice = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n\n\nclass MADDPG:\n \"\"\"policy + critic updates\"\"\"\n\n def __init__(self, discount_factor... | [
[
"torch.cat",
"torch.no_grad",
"torch.nn.SmoothL1Loss",
"torch.cuda.is_available",
"torch.tensor"
]
] |
roguephysicist/PyPSD | [
"16f96c3d9df99835b3961751ef9ebceac791bb15"
] | [
"pypsd.py"
] | [
"'''\nusage: python pypsd.py [-h] -b BINSFILE -i INPUTFILE [-o OUTPUTDIR]\n\nA Python script for calculating the particle size distribution (PSD) of any\nsample. Please read the adjoining README.md file for more information.\n\nWritten by Sean M. Anderson and Liliana Villafana-Lopez.\n'''\n\nimport os\nimport argpa... | [
[
"matplotlib.pyplot.xlim",
"numpy.cumsum",
"numpy.bincount",
"numpy.argmax",
"numpy.arange",
"numpy.sqrt",
"matplotlib.pyplot.subplot",
"numpy.array",
"numpy.savetxt",
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"numpy.loadt... |
geekmj/fml | [
"ead2c16be7865eda03183b5e11622f64bf81cab7"
] | [
"python-programming/panda/accessing_elements_pandas_dataframes.py"
] | [
"import pandas as pd\n\nitems2 = [{'bikes': 20, 'pants': 30, 'watches': 35},\n {'watches': 10, 'glasses': 50, 'bikes':15,'pants': 5 } \n ]\nstore_items = pd.DataFrame(items2, index = ['Store 1', 'Store 2'])\n\nprint(store_items)\n\n## We can access rows, columns, or individual elements of the DataF... | [
[
"pandas.DataFrame"
]
] |
DataXujing/CornerNet-Lite-Pytorch | [
"35d491b153c715d40174717ccafd89e77e33b743"
] | [
"trainmyData.py"
] | [
"#!/usr/bin/env python\nimport os\nimport sys\nimport json\nimport torch\nimport numpy as np\nimport queue\nimport pprint\nimport random\nimport argparse\nimport importlib\nimport threading\nimport traceback\nimport torch.distributed as dist\nimport torch.multiprocessing as mp\n\nfrom tqdm import tqdm\nfrom torch.m... | [
[
"torch.multiprocessing.Process",
"torch.distributed.init_process_group",
"torch.multiprocessing.spawn",
"torch.cuda.device_count",
"torch.multiprocessing.Queue"
]
] |
ori-drs/whole_body_state_msgs | [
"1c1dd3395907c344d94515ff4f10a6a06ff30abb"
] | [
"src/whole_body_state_msgs/whole_body_interface.py"
] | [
"from __future__ import print_function, absolute_import\n\nimport rospy\nfrom whole_body_state_msgs.msg import WholeBodyState, ContactState, JointState\nimport pinocchio\nimport numpy as np\nimport copy\n\n__all__ = ['WholeBodyStateInterface']\n\n\nclass WholeBodyStateInterface():\n def __init__(self, model, fra... | [
[
"numpy.array",
"numpy.zeros"
]
] |
NanYoMy/mmregnet | [
"50909d39289733264dce14666e9deeecbe858819"
] | [
"proj/voxelmorph/torch_vm/losses.py"
] | [
"import torch\nimport torch.nn.functional as F\nimport numpy as np\nimport math\n\n\nclass NCC:\n \"\"\"\n Local (over window) normalized cross correlation loss.\n \"\"\"\n\n def __init__(self, win=None):\n self.win = win\n\n def loss(self, y_true, y_pred):\n\n I = y_true\n J = y... | [
[
"torch.abs",
"numpy.prod",
"torch.mean",
"torch.ones"
]
] |
runjerry/alf | [
"38a3621337a030f74bb3944d7695e7642e777e10"
] | [
"alf/algorithms/one_step_loss.py"
] | [
"# Copyright (c) 2019 Horizon Robotics. 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 requi... | [
[
"tensorflow.reduce_mean",
"tensorflow.stop_gradient"
]
] |
mounalab/Multivariate-time-series-forecasting-keras | [
"c9551cf3b88aa5b4257206fb5096716df648d93d"
] | [
"Transformer.py"
] | [
"from datetime import datetime\nfrom time import time\nimport json\nimport logging\n\nimport tensorflow as tf\nimport keras\nfrom keras import layers\nfrom keras.models import Model\nfrom keras.models import load_model\nfrom keras.models import Sequential\nfrom keras.callbacks import EarlyStopping, TensorBoard, Mod... | [
[
"tensorflow.keras.optimizers.Adam"
]
] |
tansyab1/PhD-project | [
"b4815d151ef90cffa1bbc8fbf97cd091a20ce600"
] | [
"2021/src/Classification/Pre-Trained-DenseNet-161/02_medico_2018_method_3_densenet161_split_1.py"
] | [
"# # Developer: Vajira Thambawita\n# # Last modified date: 18/07/2018\n# # ##################################\n\n# # Description ##################\n# # pythroch resnet18 training\n\n\n\n\n\n\n###########################################\n\nfrom __future__ import print_function, division\n\nimport datetime\n\n#... | [
[
"torch.utils.data.ConcatDataset",
"torch.nn.Linear",
"sklearn.metrics.confusion_matrix",
"torch.cat",
"numpy.set_printoptions",
"torch.cuda.is_available",
"matplotlib.pyplot.gcf",
"torch.load",
"sklearn.metrics.f1_score",
"torch.nn.CrossEntropyLoss",
"matplotlib.pyplot.... |
dnadlinger/numba | [
"0d1d778471afd930915d1b0aba1997ddabee5be4"
] | [
"numba/tests/test_array_methods.py"
] | [
"from itertools import product, cycle, permutations\nimport sys\nimport warnings\n\nimport numpy as np\n\nfrom numba import jit, typeof\nfrom numba.core import types\nfrom numba.core.compiler import compile_isolated\nfrom numba.core.errors import TypingError, LoweringError\nfrom numba.np.numpy_support import as_dty... | [
[
"numpy.testing.assert_allclose",
"numpy.int8",
"numpy.copy",
"numpy.asfortranarray",
"numpy.mean",
"numpy.where",
"numpy.frombuffer",
"numpy.imag",
"numpy.random.random",
"numpy.dtype",
"numpy.int16",
"numpy.zeros_like",
"numpy.nonzero",
"numpy.arange",
... |
nacansino/DiscreteTimeVaryingFilter | [
"16f19729dd85cceb25e1f4a382533b0947f584c3"
] | [
"discrete-time-varying-filter/gaussian_fitness_fxn.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Apr 29 16:15:38 2019\n\n@author: jay\n\nCreation of Gaussian fitness function\n\"\"\"\n\nimport numpy as np\n\ntx=np.arange(0,1,0.01)\nty=np.arange(-0.5,0.5,0.00001)\n\nsx=0.4\nsy=0.3\n\nx,y = np.meshgrid(tx,ty,sparse=True)\ngauss=100*np.exp(-... | [
[
"numpy.meshgrid",
"numpy.arange",
"numpy.exp"
]
] |
Haelles/QueryTrack | [
"ea3e5c964788231926a393ba691aa2db7974102c"
] | [
"mmdet/models/roi_heads/mask_heads/dynamic_mask_head.py"
] | [
"import torch\nimport torch.nn as nn\nfrom mmcv import imresize\nfrom mmcv.cnn import (bias_init_with_prob, build_activation_layer,\n build_norm_layer, ConvModule, Conv2d, build_upsample_layer)\nfrom mmcv.runner import auto_fp16, force_fp32\n\nfrom mmdet.core import mask_target\nfrom mmdet.mode... | [
[
"torch.nn.init.xavier_uniform_",
"torch.arange",
"torch.nn.init.constant_"
]
] |
klebster2/inversion_mapping_dissertation | [
"568a043086207d1170410068213179b437b26e80"
] | [
"model1c.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated by Kleber Noel for disseration: \n inversion mapping using a Local Linear embedding\nJune 2019\n\"\"\"\nimport numpy as np \n#import pandas as pd \nimport os, pdb, argparse, re, random\nfrom tqdm import tqdm\nfrom collections import defaultdict, O... | [
[
"torch.nn.Linear",
"torch.mul",
"torch.nn.LSTM",
"torch.nn.MSELoss",
"torch.autograd.Variable",
"torch.nn.utils.rnn.pad_sequence",
"torch.FloatTensor",
"torch.cuda.is_available",
"torch.nn.utils.rnn.pad_packed_sequence",
"torch.load",
"torch.empty",
"torch.randn"
... |
zzzqzhou/Dual-Normalization | [
"b9831b6e2662a950600ba37ada087ba8ce93f60c"
] | [
"utils/loss.py"
] | [
"import torch\nimport torch.nn.functional as F\n\neps = 1e-8\n\ndef dice_loss(input, target, p=2, ignore_index=-100):\n n, c, h, w = input.size()\n prob = F.softmax(input, dim=1)\n prob_flatten = prob.permute(0, 2, 3, 1).contiguous().view(-1, c)\n\n target_flatten = target.view(n * h * w, 1)\n mask =... | [
[
"torch.nn.functional.one_hot",
"torch.mul",
"torch.nn.functional.softmax",
"torch.zeros_like",
"torch.sum"
]
] |
veui/yolo-tf2-py37 | [
"10b841bcb8403c4388f7b877338c7268041cf95e"
] | [
"yolo_tf2/core/evaluator.py"
] | [
"import os\nfrom concurrent.futures import ThreadPoolExecutor, as_completed\n\nimport numpy as np\nimport pandas as pd\nimport tensorflow as tf\nfrom cv2 import cv2\nfrom yolo_tf2.core.models import BaseModel\nfrom yolo_tf2.utils.common import (LOGGER, get_abs_path, get_detection_data,\n ... | [
[
"tensorflow.data.TFRecordDataset",
"pandas.set_option",
"tensorflow.expand_dims",
"pandas.DataFrame",
"numpy.random.default_rng",
"pandas.concat",
"numpy.isin"
]
] |
jonathanvoelkle/twemoji | [
"af7d3779ed7ceb18dbd1543f3d1efd69e573703b"
] | [
"main.py"
] | [
"import os\n\nfrom collections import Counter\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.patches import Rectangle\n\nfrom matplotlib import image as mpimg\n\nimport statistics\n\n\n# 2194\n\n\ndef getColors(img):\n pixels = img.reshape((72*72, 4)) .tolist()\n\n # filter pixels fo... | [
[
"numpy.array",
"matplotlib.pyplot.xlim",
"numpy.median",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.subplots",
"numpy.mean",
"matplotlib.pyplot.show",
"matplotlib.patches.Rectangle"
]
] |
asinghgaba/PyBaMM | [
"2f51eaacbbc6b264fb376a6cef33ff91e99b9f49",
"2f51eaacbbc6b264fb376a6cef33ff91e99b9f49"
] | [
"pybamm/parameters/parameter_values.py",
"pybamm/solvers/base_solver.py"
] | [
"#\n# Dimensional and dimensionless parameter values, and scales\n#\nimport pybamm\nimport pandas as pd\nimport os\nimport numbers\nimport warnings\nfrom pprint import pformat\nfrom collections import defaultdict\n\n\nclass ParameterValues:\n \"\"\"\n The parameter values for a simulation.\n\n Note that th... | [
[
"pandas.DataFrame",
"pandas.read_csv"
],
[
"numpy.array",
"numpy.zeros",
"numpy.diff",
"numpy.arange",
"numpy.searchsorted",
"numpy.linspace",
"numpy.insert"
]
] |
xiayzh/MH-MDGM | [
"203fb463ac968d1c566073111ff42ca55e7ea085",
"203fb463ac968d1c566073111ff42ca55e7ea085",
"203fb463ac968d1c566073111ff42ca55e7ea085"
] | [
"inversion/Channel/simulation.py",
"inversion/Gaussian/inversion_16_64.py",
"MDGM/Channel/VAE_train_16.py"
] | [
"from dolfin import *\nimport matplotlib.pyplot as plt\nimport fenics\nimport numpy as np\nimport os\nimport property_field as property_field\nimport scipy.misc as misc\nimport scipy.io\nimport scenarios as scenarios\nfrom matplotlib import ticker,cm\nimport time\n\n\nclass simulation:\n def __init__(self):\n ... | [
[
"numpy.full",
"numpy.random.normal",
"numpy.savetxt",
"numpy.log",
"numpy.zeros",
"matplotlib.pyplot.savefig",
"numpy.copy",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots",
"numpy.loadtxt",
"numpy.amax",
"numpy.abs",
"numpy.amin",
"matplotlib.ticker... |
moloney/nipype | [
"a7a9c85c79cb1412ba03406074f83200447ef50b"
] | [
"nipype/workflows/rsfmri/fsl/tests/test_resting.py"
] | [
"# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n\nimport pytest\nimport os\nimport mock\nimport numpy as np\n\nfrom .....testing import utils\nfrom .....interfaces import IdentityInterface\nfrom .....pipeline.engine import Node, Workflow\n\nfrom .... | [
[
"numpy.array",
"numpy.zeros"
]
] |
er1ca/Gesture-Generation-from-Trimodal-Context | [
"6d988a7211a4d8294e1ef4b45c45ee25d12455d2",
"6d988a7211a4d8294e1ef4b45c45ee25d12455d2"
] | [
"scripts/utils/data_utils.py",
"scripts/train_eval/train_seq2seq.py"
] | [
"import re\n\nimport librosa\nimport numpy as np\nimport torch\nfrom scipy.interpolate import interp1d\nfrom sklearn.preprocessing import normalize\n\ndevice = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n\n\nskeleton_line_pairs = [(0, 1, 'b'), (1, 2, 'darkred'), (2, 3, 'r'), (3, 4, 'orange')... | [
[
"numpy.array",
"scipy.interpolate.interp1d",
"numpy.pad",
"numpy.zeros",
"torch.cuda.is_available",
"numpy.arange",
"sklearn.preprocessing.normalize"
],
[
"torch.nn.functional.mse_loss",
"torch.norm",
"torch.stack",
"torch.sum"
]
] |
ljrprocc/Motif-Removal | [
"8979ca91398212248a2be61345c99bdec53ae37e"
] | [
"networks/unet_components.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as f\n\n\ndef weight_init(m):\n if isinstance(m, nn.Conv2d):\n nn.init.xavier_normal_(m.weight)\n nn.init.constant_(m.bias, 0)\n\n\ndef reset_params(model):\n for i, m in enumerate(model.modules()):\n weight_init(m)\n\n\ndef... | [
[
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.init.constant_",
"torch.nn.MaxPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ConvTranspose2d",
"torch.nn.ReLU",
"torch.nn.Upsample",
"torch.nn.Conv2d",
"torch.nn.functional.relu",
"torch.nn.init.xavier_normal_"
]
] |
cseed/hail | [
"425e779c0bde619bcf96838c09cc834de3c182fd"
] | [
"hail/python/test/hail/expr/test_ndarrays.py"
] | [
"import numpy as np\nfrom ..helpers import *\nimport tempfile\nimport pytest\n\nfrom hail.utils.java import FatalError, HailUserError\n\n\ndef assert_ndarrays(asserter, exprs_and_expecteds):\n exprs, expecteds = zip(*exprs_and_expecteds)\n\n expr_tuple = hl.tuple(exprs)\n evaled_exprs = hl.eval(expr_tuple)... | [
[
"numpy.array_equal",
"numpy.asfortranarray",
"numpy.load",
"numpy.linalg.qr",
"numpy.concatenate",
"numpy.full",
"numpy.linalg.matrix_rank",
"numpy.eye",
"numpy.testing.assert_array_almost_equal",
"numpy.arange",
"numpy.linalg.inv",
"numpy.vstack",
"numpy.array"... |
Open-Speech-EkStep/ekstep-gender-classification | [
"7af5b5c24c6a7d37dc84afbaf76efcaf38e941e5"
] | [
"tests/test_create_embeddings.py"
] | [
"import unittest\nfrom scripts.create_embeddings import encoder\nfrom os import path\nfrom glob import glob\nimport numpy as np\n\n\nclass EmbeddingsTests(unittest.TestCase):\n def test_should_create_embeddings_for_clean_test_files(self):\n source_dir = '../resources/test_data/'\n source_dir_patter... | [
[
"numpy.load"
]
] |
nbokulich/genome-sampler | [
"5a37b74fcb21cdaf2c7a437f015eda14ce02590d"
] | [
"genome_sampler/subsample_diversity.py"
] | [
"import tempfile\n\nimport pandas as pd\n\nimport qiime2\nfrom q2_types.feature_data import DNAFASTAFormat\n\nfrom genome_sampler.common import IDSelection, run_command, ids_from_fasta\n\n\n# According to the vsearch 2.14.2 documentation, percent_id is defined as:\n# (matching columns) / (alignment length - termin... | [
[
"pandas.read_csv",
"pandas.Index",
"pandas.Series"
]
] |
Powahowa/CSML1020-Project---UrbanSound-8K | [
"94c44f453aa275471e3d951bdbe72ec5e4bc878f"
] | [
"data-exploration_parallel.py"
] | [
"# %% [markdown] \n# # Data Exploration\n\n# ## Imports\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport librosa\n\n# Import custom module containing useful functions\nimport sonicboom\n\n# Parallelization libraries\nfrom joblib import Parallel, delayed\n\n# %% [markdown]\n# ## R... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.style.use",
"matplotlib.pyplot.specgram",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplot"
]
] |
lhmtriet/DeepCVA | [
"92c352a0ae11fc7d69497308f690dcca73eb50b0"
] | [
"infer_features/infer_features_ast.py"
] | [
"import sys\n\nsys.path.append(\"../\")\nimport helpers.feature_model_helpers as fmh\nimport pandas as pd\nimport pickle\nfrom gensim.models import Word2Vec\nfrom importlib import reload\nfrom pathlib import Path\nimport pickle as pkl\nimport numpy as np\nfrom scipy.sparse import coo_matrix\n\nreload(fmh)\n\n# %% G... | [
[
"scipy.sparse.coo_matrix"
]
] |
ezanardi/phonopy | [
"ea701805638113e697b0f1743c5ab8eaaa15dceb"
] | [
"phonopy/unfolding/core.py"
] | [
"# Copyright (C) 2015 Atsushi Togo\n# All rights reserved.\n#\n# This file is part of phonopy.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions\n# are met:\n#\n# * Redistributions of source code must retain the above copyr... | [
[
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.rint",
"numpy.linalg.inv",
"numpy.where",
"numpy.abs",
"numpy.repeat",
"numpy.diag",
"numpy.dtype"
]
] |
LinacCoherentLightSource/psgeom | [
"1c31208d861755fc76074c1032ec24d0058a96bf"
] | [
"test/test_reciprocal.py"
] | [
"# --- reciprocal.py -----------------------------------------------------------\n# + basisgrid.py\n\nimport numpy as np\nimport os\nimport unittest\nimport h5py\n\nfrom psgeom import basisgrid\nfrom psgeom import reciprocal\nfrom psgeom import camera\nfrom psgeom import sensors\nfrom psgeom import fitting\n\n\nd... | [
[
"numpy.max",
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.linalg.norm",
"numpy.sin",
"numpy.zeros",
"numpy.squeeze",
"numpy.testing.assert_almost_equal",
"numpy.random.randn",
"numpy.logical_and",
"numpy.testing.assert_array_almost_equal",
"numpy.arange",
... |
226wyj/R-BERT | [
"c94daf7b72b2d70f7883f9e646825ab1a6c149a1"
] | [
"utils.py"
] | [
"import sys\nsys.path.append('.')\n\nimport os\nimport random\nimport logging\nimport collections\nimport csv\nfrom copy import deepcopy\n\nimport torch\nimport numpy as np\nfrom sklearn.metrics import f1_score\nfrom transformers.tokenization_bert import BertTokenizer\n\nimport matplotlib\nmatplotlib.use('TkAgg')\n... | [
[
"matplotlib.use",
"torch.cuda.manual_seed_all",
"numpy.zeros",
"numpy.random.seed",
"pandas.DataFrame",
"torch.manual_seed",
"numpy.loadtxt",
"torch.cuda.is_available",
"matplotlib.pyplot.show",
"sklearn.metrics.f1_score"
]
] |
Kirndohyeon/deeplearning_from_scratch | [
"4bbb640b42bddc136abd88b8caa66e874b8a1935"
] | [
"ch7.CNN/simple_convnet.py"
] | [
"# coding: utf-8\nimport sys, os\nsys.path.append(os.pardir) # 부모 디렉터리의 파일을 가져올 수 있도록 설정\nimport pickle\nimport numpy as np\nfrom collections import OrderedDict\nfrom common.layers import *\nfrom common.gradient import numerical_gradient\n\n\nclass SimpleConvNet:\n \"\"\"단순한 합성곱 신경망\n \n conv - relu - poo... | [
[
"numpy.sum",
"numpy.random.randn",
"numpy.argmax",
"numpy.zeros"
]
] |
dlsaavedra/Detector_GDXray | [
"1e120f8fa548819eef1b86ccfbbe306b44405b6f"
] | [
"keras-yolo2-master/frontend.py"
] | [
"from keras.models import Model\nfrom keras.layers import Reshape, Activation, Conv2D, Input, MaxPooling2D, BatchNormalization, Flatten, Dense, Lambda\nfrom keras.layers.advanced_activations import LeakyReLU\nimport tensorflow as tf\nimport numpy as np\nimport os\nimport cv2\nfrom utils import decode_netout, comput... | [
[
"tensorflow.exp",
"tensorflow.ones_like",
"tensorflow.assign_add",
"numpy.finfo",
"tensorflow.to_float",
"numpy.cumsum",
"numpy.random.normal",
"tensorflow.shape",
"tensorflow.concat",
"tensorflow.less",
"tensorflow.sigmoid",
"tensorflow.argmax",
"tensorflow.Var... |
Doodleverse/Segmentation_Gym | [
"df8818b70b650d6390e5b70db2cdd65837a7d474"
] | [
"make_nd_dataset.py"
] | [
"# Written by Dr Daniel Buscombe, Marda Science LLC\n# for the USGS Coastal Change Hazards Program\n#\n# MIT License\n#\n# Copyright (c) 2020-22, Marda Science LLC\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Softwar... | [
[
"numpy.full",
"numpy.array",
"numpy.zeros",
"numpy.round",
"numpy.ones",
"numpy.savez_compressed",
"numpy.all",
"numpy.unique",
"numpy.arange",
"numpy.dstack",
"numpy.squeeze",
"numpy.vstack",
"numpy.maximum"
]
] |
gitter-badger/scvi-tools | [
"8948405f6b393baede73ccd6a0a5ac0824e16c0d"
] | [
"scvi/utils/_differential.py"
] | [
"import inspect\nimport logging\nimport warnings\nfrom typing import Callable, Dict, List, Optional, Sequence, Union\n\nimport numpy as np\nimport pandas as pd\nimport torch\n\nfrom scvi._compat import Literal\n\nlogger = logging.getLogger(__name__)\n\nNumber = Union[int, float]\n\n\nclass DifferentialComputation:\... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.random.choice",
"numpy.asarray",
"numpy.argmin",
"numpy.log",
"numpy.median",
"torch.no_grad",
"numpy.mean",
"numpy.where",
"numpy.arange",
"numpy.sort",
"numpy.abs",
"pandas.ExcelWriter",
"numpy.log2",
"num... |
HiteshMah-Jan/Quantdom | [
"e05304006d3805f941d5f1033135730287b447e6"
] | [
"quantdom/lib/portfolio.py"
] | [
"\"\"\"Portfolio.\"\"\"\n\nimport itertools\nfrom contextlib import contextmanager\nfrom enum import Enum, auto\n\nimport numpy as np\n\nfrom .base import Quotes\nfrom .performance import BriefPerformance, Performance, Stats\nfrom .utils import fromtimestamp, timeit\n\n__all__ = ('Portfolio', 'Position', 'Order')\n... | [
[
"numpy.zeros_like",
"numpy.sum",
"numpy.maximum.accumulate",
"numpy.where",
"numpy.cumsum"
]
] |
JishinMaster/scientific_benchmarks | [
"1ec81d2475a857fbb81474036af98080b5c1875e"
] | [
"tests/resources/covmat_test_data.py"
] | [
"import numpy as np\n\nnp.random.seed(0)\n\ndef generate(size):\n (m_real, m_imag) = np.random.randn(size, size), np.random.randn(size, size)\n\n m_complex = m_real + 1j * m_imag\n\n m_covmat = np.cov(m_complex)\n\n output_file_name = \"tests/resources/data/testcovmat_sp_out_{}_{}\".format(size, size)\n... | [
[
"numpy.cov",
"numpy.random.seed",
"numpy.random.randn",
"numpy.real",
"numpy.imag"
]
] |
AntixK/PyTorch-Model-Compare | [
"869d3ecd0b9a0b9ceca51f84f4eedcce1fdd392f"
] | [
"torch_cka/utils.py"
] | [
"from mpl_toolkits import axes_grid1\nimport matplotlib.pyplot as plt\n\ndef add_colorbar(im, aspect=10, pad_fraction=0.5, **kwargs):\n \"\"\"Add a vertical color bar to an image plot.\"\"\"\n divider = axes_grid1.make_axes_locatable(im.axes)\n width = axes_grid1.axes_size.AxesY(im.axes, aspect=1./aspect)\... | [
[
"matplotlib.pyplot.gca",
"matplotlib.pyplot.sca"
]
] |
jorgemauricio/get_forecast_from_conagua | [
"7124041cd061134feb37afa11e70aabd68495153"
] | [
"algoritmo_diario.py"
] | [
"# /usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n# Script que permite insertar el pronóstico de CONAGUA a una base de datos\n# Author: Jorge Mauricio\n# Email: jorge.ernesto.mauricio@gmail.com\n# Date: Created on Thu... | [
[
"pandas.to_datetime"
]
] |
alanoooaao/FoolNLTK | [
"1344c5aa1c2aabc1f4f6f2a492e1663928836325"
] | [
"train/export_model.py"
] | [
"#!/usr/bin/env python\n#-*-coding:utf-8-*-\n\n\nimport tensorflow as tf\nfrom tensorflow.contrib.crf import viterbi_decode\nimport numpy as np\n\ndef decode(logits, trans, sequence_lengths, tag_num):\n viterbi_sequences = []\n small = -1000.0\n start = np.asarray([[small] * tag_num + [0]])\n for logit,... | [
[
"numpy.concatenate",
"numpy.array",
"tensorflow.train.latest_checkpoint",
"numpy.asarray",
"tensorflow.get_default_graph",
"tensorflow.contrib.crf.viterbi_decode",
"tensorflow.Graph",
"tensorflow.Session",
"tensorflow.GraphDef",
"tensorflow.import_graph_def",
"numpy.one... |
fixedchaos/delfem2 | [
"c8a7a000ec6a51c44bc45bc6ad0d0106d9315ade"
] | [
"test_py/test_fem.py"
] | [
"####################################################################\n# Copyright (c) 2019 Nobuyuki Umetani #\n# #\n# This source code is licensed under the MIT license found in the #\n# LICENSE file in the root director... | [
[
"numpy.where",
"numpy.array",
"numpy.random.uniform",
"numpy.zeros"
]
] |
gregbugaj/marie-ai | [
"f51a74f19ab5d7231c9f8a426284feff1671b974"
] | [
"src/models/icr/test.py"
] | [
"import argparse\nimport os\nimport re\nimport string\nimport time\n\nimport numpy as np\nimport torch\nimport torch.backends.cudnn as cudnn\nimport torch.nn.functional as F\nimport torch.utils.data\nfrom nltk.metrics.distance import edit_distance\n\nfrom dataset import AlignCollate, hierarchical_dataset\nfrom mode... | [
[
"torch.IntTensor",
"torch.no_grad",
"torch.nn.CTCLoss",
"torch.cuda.device_count",
"torch.cuda.is_available",
"torch.LongTensor",
"torch.load",
"torch.nn.functional.softmax",
"torch.nn.CrossEntropyLoss",
"torch.nn.DataParallel"
]
] |
dojoteef/storium-gpt2 | [
"ce8e3fa330b203068e9572417c8f40366ca131d5"
] | [
"dae/world_vis.py"
] | [
"import sys\n\nprint(sys.path)\n# import matplotlib\n# import matplotlib.pyplot as plt\nimport random\nimport torch\nfrom torch import nn, optim\nfrom torch.autograd import Function\nimport numpy as np\nimport os\nimport pickle\nimport data_analysis_utils\nfrom data_analysis_utils import (prepare_text_for_lda, buil... | [
[
"numpy.delete",
"numpy.zeros",
"numpy.sum",
"numpy.where",
"numpy.argsort",
"numpy.around"
]
] |
Jimmy-INL/jax | [
"ef4debcaad5a5ac5182899e385f45ca64f5ce600"
] | [
"jax/lib/xla_bridge.py"
] | [
"# Copyright 2018 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.equal",
"numpy.array",
"numpy.not_equal",
"numpy.take",
"numpy.isscalar"
]
] |
jbsantos/api-grafico | [
"42f98cafecd9fc9e04292e99e15b44c400c86e8c"
] | [
"treinamento.py"
] | [
"from sklearn.cluster import KMeans\n\ndef objGrafico():\n import numpy as np\n import json\n\n class NumpyEncoder(json.JSONEncoder):\n def default(self, obj):\n if isinstance(obj, np.ndarray):\n return obj.tolist()\n return json.JSONEncoder.default(self, obj)\n\... | [
[
"pandas.DataFrame",
"sklearn.cluster.KMeans",
"matplotlib.pyplot.title",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.scatter",
"pandas.read_csv"
]
] |
Mriana-Yadkoo/Plutinos32-Fall2020 | [
"6e5678275ff5439c32e1140f55e99c590b308b1b"
] | [
"ReboundCode.py"
] | [
"# ---- Author/Instructor: Samantha Lawler ---- #\n# ---- CoAuthor/Student: Mriana Yadkoo ---- #\n# ---- Student Email: mriana.saeed1997@gmail.com / May99@uregina.ca ---- #\n# ---- Copyrights: Fall 2020 ---- #\n\n# Used Modulars\nimport numpy as np\nimport rebound\nimport sys\n\n# Conversion tools\ndeg2rad = np.pi/... | [
[
"numpy.linspace",
"numpy.arange"
]
] |
howieraem/KinectActionDetection | [
"ff64030e9fa2eb3d512b5cc1dae79e6a07ab8e5c"
] | [
"utils/pytorch.py"
] | [
"import torch\nimport copy\nfrom utils.misc import deprecated\n\n\ndef unprocessed_collate(batch):\n \"\"\"\n A dummy function to prevent Pytorch's data loader from converting and stacking batch data.\n :param batch:\n :return:\n \"\"\"\n return batch # List of data tuples (sequence, timeline, ... | [
[
"torch.zeros",
"torch.LongTensor",
"torch.clamp",
"torch.pow"
]
] |
pySTEPS/pySTEPS | [
"99c79d8dd10ec9e0b61b59eb9f2b3ff73d0ed0df"
] | [
"pysteps/scripts/run_vel_pert_analysis.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Analyze uncertainty of motion field with increasing lead time. The analyses\nare done by comparing initial motion fields to those estimated in the future.\nFor a description of the method, see :cite:`BPS2006`.\"\"\"\n\nimport argparse\nfrom datetime import datetime, timedelta\nimport... | [
[
"numpy.linalg.norm",
"numpy.sum",
"numpy.ones",
"numpy.any",
"numpy.stack",
"numpy.isfinite",
"scipy.linalg.norm"
]
] |
OH-Seoyoung/People_Counter_using_Object_Detection | [
"ec0e75ea4a820466d1e98b842731fe21221b59ea"
] | [
"YOLO-v3_test/yolo_opencv.py"
] | [
"import cv2\nimport argparse\nimport numpy as np\n\nap = argparse.ArgumentParser()\nap.add_argument('-i', '--image', required=True,\n help = 'path to input image')\nap.add_argument('-c', '--config', required=True,\n help = 'path to yolo config file')\nap.add_argument('-w', '--weights',... | [
[
"numpy.argmax"
]
] |
darsh8200/tensorflow | [
"a21ecf40d7be6b877e673f6360cda3dfc70ef6ff"
] | [
"tensorflow/python/keras/engine/training_v2_utils.py"
] | [
"# Copyright 2019 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.keras.engine.training_utils.cast_to_model_input_dtypes",
"tensorflow.python.framework.tensor_util.constant_value",
"tensorflow.python.ops.math_ops.cast",
"tensorflow.python.keras.engine.training_utils.ModelInputs",
"tensorflow.python.keras.distribute.distributed_training_uti... |
lutsker/simple-autodiff | [
"3eaecbae7e46566a51f12c923d72af305d39b4ee"
] | [
"autodiff/ops.py"
] | [
"from .numtor import Numtor\nimport numpy as np\n\n\ndef np_exp(arg: Numtor):\n return Numtor(np.exp(arg.value), op='exp', parents=[arg])\n\ndef np_log(arg: Numtor):\n return Numtor(np.log(arg.value), op='log', parents=[arg])\n\ndef np_sigmoid(arg: Numtor):\n return Numtor(1/(1+np.exp(-arg.value)), op='sig... | [
[
"numpy.exp",
"numpy.log"
]
] |
pthomson88/drug_design | [
"d92ed4c06cd036c83fe60ada05b493f4581d24d6"
] | [
"drug_design/similarity.py"
] | [
"\n#this approach was taken from: https://stackabuse.com/levenshtein-distance-and-text-similarity-in-python/\nimport numpy as np\nimport pandas as pd\nimport pathos.multiprocessing as mp\nfrom functools import partial\nfrom itertools import repeat, starmap\nimport settings\nimport datetime\n\ndef parallelize_datafr... | [
[
"pandas.Series"
]
] |
diffiii/DF8 | [
"bd4ef60944a39fedef222c98e27ec61269278cdc"
] | [
"DF8.py"
] | [
"import time\nimport numpy as np\nfrom typing import Literal, Optional\nfrom DF8Converter import convert\n\n\ndef ROM(filename: Optional[str]='ROM'):\n ROM = []\n with open(filename) as file:\n contents = file.read().replace(' ', '').replace('\\n', '')\n for i in range(256):\n ROM.append(cont... | [
[
"numpy.zeros",
"numpy.ubyte"
]
] |
SteveCruz/icpr2022-autoencoder-attractors | [
"0935179b514fd49e1d2410005d91ff49db9978ac"
] | [
"dataset.py"
] | [
"####################################################################################################################################################\n####################################################################################################################################################\n\"\"\"\nDataloa... | [
[
"numpy.array",
"numpy.random.choice",
"numpy.random.seed",
"torch.initial_seed",
"torch.Generator",
"numpy.min",
"numpy.transpose",
"torch.utils.data.DataLoader",
"numpy.unique"
]
] |
JunLi-Galios/unsup_temp_embed_alternating | [
"1b054fd82aadcfe1aa219be17beb77c89efd974e"
] | [
"data_utils/BF_utils/update_argpars.py"
] | [
"#!/usr/bin/env python\n\n\"\"\"Update parameters which directly depends on the dataset.\n\"\"\"\n\n__author__ = 'Anna Kukleva'\n__date__ = 'November 2018'\n\nimport os\nimport os.path as ops\n\nfrom ute.utils.arg_pars import opt\nfrom ute.utils.util_functions import update_opt_str, dir_check\nfrom ute.utils.loggin... | [
[
"torch.cuda.is_available"
]
] |
TSummersLab/polgrad-multinoise | [
"c51a81212bc648256976a4696807f7bd2828baa0"
] | [
"polgrad_multinoise/ltimult.py"
] | [
"import numpy as np\nfrom numpy import linalg as la\nfrom matrixmath import is_pos_def, vec, sympart, kron, randn, dlyap, dare, mdot\n\nimport warnings\nfrom warnings import warn\nfrom copy import copy\n\n\n###############################################################################\n# Developer notes\n#########... | [
[
"numpy.isinf",
"numpy.dot",
"numpy.linalg.norm",
"numpy.reshape",
"numpy.zeros",
"numpy.isnan",
"numpy.copy",
"numpy.ones",
"numpy.eye",
"numpy.linalg.solve",
"numpy.abs",
"numpy.full_like"
]
] |
mariogeiger/se3cnn | [
"afd027c72e87f2c390e0a2e7c6cfc8deea34b0cf"
] | [
"tests/point/periodic_convolution_tests.py"
] | [
"# pylint: disable=C,E1101,E1102\nimport unittest\n\nimport torch\nfrom functools import partial\nfrom se3cnn.point.operations import PeriodicConvolution\nfrom se3cnn.point.kernel import Kernel\nfrom se3cnn.point.radial import ConstantRadialModel\n\n\nclass Tests(unittest.TestCase):\n def test1(self):\n t... | [
[
"torch.set_default_dtype",
"torch.randn"
]
] |
AnonymousCIKM2021-2518/SAEDS | [
"9aa156956a3da28b2d275016b899ed77c8c54005"
] | [
"dialog_fairseq/fairseq/hub_utils.py"
] | [
"#!/usr/bin/env python3 -u\n# 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 argparse\nimport copy\nimport logging\nimport os\nfrom typing import Any, Dict, Iterator, List, Tu... | [
[
"torch.is_tensor",
"torch.tensor",
"torch.nn.ModuleList"
]
] |
sji15/oneflow | [
"523888bc251920c39021e7a0e063118d53c4cfd1",
"523888bc251920c39021e7a0e063118d53c4cfd1"
] | [
"oneflow/python/test/modules/test_repeat.py",
"oneflow/python/test/tensor/test_tensor.py"
] | [
"\"\"\"\nCopyright 2020 The OneFlow Authors. All rights reserved.\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by ap... | [
[
"numpy.random.randn",
"numpy.tile"
],
[
"numpy.array",
"numpy.random.rand",
"numpy.zeros",
"numpy.ones",
"numpy.random.randn",
"numpy.random.randint"
]
] |
YangHu-yh/Extrasensory_Data_Mining | [
"37586a31e1532631432fada148df5723a4d7e5c3"
] | [
"utilize/test.py"
] | [
"from sklearn.metrics import multilabel_confusion_matrix, confusion_matrix\r\nfrom sklearn.metrics import accuracy_score\r\nimport numpy as np \r\n\r\ndef evaluate_model(model, X_test, y_test, W_test = None, report = True):\r\n\t'''\r\n\tEstimate a model\r\n\tKeyword Arguments:\r\n\t\tmodel: model to be estimated\r... | [
[
"numpy.concatenate",
"numpy.sum",
"sklearn.metrics.confusion_matrix",
"numpy.expand_dims"
]
] |
dargueso/IceVarFigs | [
"d9b1bb3ac09a9dfd097e72b0dba78276b7e251e4"
] | [
"Scripts/SeaIce/NSIDCseaice_Antarctic_quartiles.py"
] | [
"\"\"\"\nReads in current year's Antarctic sea ice extent from Sea Ice Index 3 (NSIDC)\n\nWebsite : ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/daily/data/\nAuthor : Zachary M. Labe\nDate : 5 September 2016\n\"\"\"\n\n### Import modules\nimport numpy as np\nimport urllib as UL\nimport datetime\ni... | [
[
"matplotlib.pyplot.text",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.ylim",
"numpy.genfromtxt",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.rc",
"numpy.whe... |
m-guggenmos/remeta | [
"d074d87cb45ae83cd0213ffbecbb3d85036f8cd2"
] | [
"remeta/modelspec.py"
] | [
"from dataclasses import make_dataclass\n\nimport numpy as np\nfrom scipy.optimize import OptimizeResult\n\nfrom .util import TAB, ReprMixin, spearman2d, pearson2d\n\n\nclass Parameter(ReprMixin):\n def __init__(self, guess, bounds, grid_range=None):\n \"\"\"\n Class that defines the fitting charac... | [
[
"numpy.array",
"numpy.isnan",
"numpy.nansum",
"numpy.tile",
"numpy.sign",
"numpy.abs",
"numpy.mod",
"numpy.maximum"
]
] |
rangwani-harsh/char-cnn-char-rnn-sentiment-analysis | [
"48238232ba053f8c12e66383fd65fc075c532dad"
] | [
"predict.py"
] | [
"import os\nimport sys\nimport torch\nimport mydatasets\nimport torch.autograd as autograd\nimport argparse\nimport torchtext.data as data\ntorch.manual_seed(3)\n\nparser = argparse.ArgumentParser(description='Predictor api')\nparser.add_argument('--snapshot', type=str, default='saved-models/best-cnn.pt', help='fil... | [
[
"torch.max",
"torch.autograd.Variable",
"torch.manual_seed",
"torch.tensor",
"torch.load"
]
] |
leoatchina/MachineLearning | [
"071f2c0fc6f5af3d9550cfbeafe8d537c35a76d3"
] | [
"h_RNN/RNN.py"
] | [
"import os\r\nimport sys\r\nroot_path = os.path.abspath(\"../\")\r\nif root_path not in sys.path:\r\n sys.path.append(root_path)\r\n\r\nimport random\r\nimport numpy as np\r\nimport tensorflow as tf\r\nimport matplotlib.pyplot as plt\r\nimport tensorflow.contrib.layers as layers\r\n\r\nfrom g_CNN.Optimizers impo... | [
[
"tensorflow.contrib.layers.fully_connected",
"numpy.mean",
"tensorflow.nn.tanh",
"tensorflow.global_variables_initializer",
"tensorflow.shape",
"numpy.empty",
"tensorflow.concat",
"tensorflow.variable_scope",
"numpy.prod",
"numpy.argmax",
"tensorflow.nn.dynamic_rnn",
... |
andres-fm/tensorflow-clone | [
"bd9db7eb5dc589a620999800ba96a8182c6b624a"
] | [
"tensorflow/python/ops/io_ops.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.ops.gen_io_ops._fixed_length_record_reader",
"tensorflow.python.ops.gen_io_ops._reader_serialize_state",
"tensorflow.python.framework.tensor_shape.vector",
"tensorflow.python.ops.gen_io_ops._save",
"tensorflow.python.framework.ops.RegisterShape",
"tensorflow.python.ops.g... |
pyoung2778/models | [
"45fd9249893b07b73447cf849a770891734c7e3a"
] | [
"official/vision/image_classification/efficientnet/efficientnet_model.py"
] | [
"# Copyright 2021 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.keras.layers.Permute",
"tensorflow.keras.layers.add",
"tensorflow.keras.layers.Input",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.backend.image_data_format",
"tensorflow.keras.layers.multiply",
"tensorflow.keras.layers.Reshape",
"tensorflow.keras.layers.Dro... |
JvPy/PlasmaPy | [
"9ba3f4eb5dbbb1a3d7b25527e0d5eb62c5086edf"
] | [
"plasmapy/utils/decorators/tests/test_checks.py"
] | [
"\"\"\"\nTests for 'check` decorators (i.e. decorators that only check objects but do not\nchange them).\n\"\"\"\nimport inspect\nimport numpy as np\nimport pytest\n\nfrom astropy import units as u\nfrom astropy.constants import c\nfrom plasmapy.utils.decorators.checks import (\n _check_relativistic,\n check_... | [
[
"numpy.array",
"numpy.complex"
]
] |
jkleve/Optimization-Algoirthms | [
"dec1edd0cd12569b3732d5a7b4bfbcdced9b1568"
] | [
"tests/ga_graph.py"
] | [
"import matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom matplotlib import cm\nimport numpy as np\nimport sys\nsys.path.append(\"../utils\")\n\nfrom oa_utils import read_xy_data\nfrom test_helpers import gen_filename\nfrom regression_utils import get_regression_coef\n\ninput_loc = '../data/ga... | [
[
"matplotlib.pyplot.show",
"numpy.arange",
"numpy.meshgrid",
"matplotlib.pyplot.figure"
]
] |
mekan841/urgent-pathology-routing | [
"a0a7ba17e3f831c51f177c390c283939762da7a2"
] | [
"distances.py"
] | [
"\nimport sys\nimport os\nimport re\nimport json\nimport numpy as np\nimport pandas as pd\nfrom datetime import datetime\nimport random\nimport itertools\nimport math\nfrom collections import defaultdict\nfrom collections import Counter\nimport time\nimport copy\n\nfrom sklearn.preprocessing import OneHotEncoder\nf... | [
[
"pandas.to_datetime",
"numpy.array",
"sklearn.linear_model.LinearRegression",
"pandas.read_csv",
"pandas.Series.unique",
"pandas.get_dummies"
]
] |
DyegoPimentel/PI5A | [
"361d7b1ba3576aa83e14f8d3a177ad2daa4b0ab7"
] | [
"analise de sentimentos.py"
] | [
"# ################################\n# #\n# PROJETO INTEGRADOR 5-A #\n# #\n##################################\n### Alunos: ###\n##################################\n# ANGELUS VICTOR SARAIVA BORGES #\n# DIEGO DE MEDEIROS ... | [
[
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.imshow"
]
] |
xr-Yang/CycleGAN-VAE | [
"951d45c5762f92efdea87a9723ed9deabd16c063"
] | [
"util/visualizer.py"
] | [
"import numpy as np\nimport os\nimport ntpath\nimport time\nfrom . import util\nfrom . import html\nfrom scipy.misc import imresize\nimport errno\n\n\n# mkdir\ndef mkdir_if_missing(dir_path):\n try:\n os.makedirs(dir_path)\n except OSError as e:\n if e.errno != errno.EEXIST:\n raise\n... | [
[
"numpy.array"
]
] |
ratuagga/curation | [
"047b984f20643e21bf3ab1e309903abaf816ecd5"
] | [
"tests/unit_tests/data_steward/cdr_cleaner/cleaning_rules/remove_participant_data_past_deactivation_date_test.py"
] | [
"\"\"\"\nUnit test for the remove_ehr_data_past_deactivation_date module\n\nOriginal Issue: DC-686\n\nThe intent is to sandbox and drop records dated after the date of deactivation for participants\nwho have deactivated from the Program.\n\"\"\"\n\n# Python imports\nimport unittest\nimport mock\n\n# Third Party imp... | [
[
"pandas.DataFrame"
]
] |
FraPorta/pepper_openpose_teloperation | [
"e31bc0b12bd8511dbce9e4449610a08ebe32c184"
] | [
"openpose_wrap/get_and_plot_3Dkeypoints.py"
] | [
"import sys\n\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\n\nfrom socket_receive import SocketReceive\n\nimport numpy as np\n\n\ntry:\n # Init dictionary\n wp_dict = {}\n\n # initialize socket for receiving the 3D keypoints\n sr = SocketReceive()\n\n # Create matplotlib ... | [
[
"numpy.array",
"matplotlib.pyplot.ion",
"matplotlib.pyplot.cla",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show"
]
] |
Opty1337/AI | [
"5f58b72dfece423f150aabb57587b9c6896fddbd"
] | [
"Project_1/Resources/Mark.py"
] | [
"import pickle\r\nimport copy\r\nimport matplotlib.pyplot as plt\r\nimport time\r\nimport imp\r\n\r\nwith open(\"coords.pickle\", \"rb\") as fp: # Unpickling\r\n coords = pickle.load(fp)\r\n \r\nwith open(\"mapasgraph.pickle\", \"rb\") as fp: #Unpickling\r\n AA = pickle.load(fp)\r\nU = AA[1]\r\n\r\ndef... | [
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.imread",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.show",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.imshow"
]
] |
jiabinnn/faster-rcnn-pytorch | [
"3192e6a2353f0e290372f9ecddaaa22fdd626695"
] | [
"nets/classifier.py"
] | [
"import warnings\r\nfrom collections import namedtuple\r\nfrom string import Template\r\n\r\nimport torch\r\nfrom torch import nn\r\nfrom torch.autograd import Function\r\nfrom torchvision.ops import RoIPool\r\nimport numpy as np\r\nwarnings.filterwarnings(\"ignore\")\r\n\r\nclass VGG16RoIHead(nn.Module):\r\n de... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.Tensor"
]
] |
pykeen/pykeen | [
"049ab51669e75dc464549611c845381677884247"
] | [
"src/pykeen/nn/emb.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"Embedding modules.\"\"\"\n\nfrom __future__ import annotations\n\nimport functools\nimport itertools\nimport logging\nimport warnings\nfrom abc import ABC, abstractmethod\nfrom dataclasses import dataclass\nfrom typing import Any, Callable, Mapping, Optional, Sequence, Tuple, TypeV... | [
[
"torch.nn.Linear",
"torch.get_default_dtype",
"torch.nn.Dropout",
"torch.rand",
"torch.nn.ModuleList",
"torch.nn.init.xavier_uniform_",
"torch.nn.BatchNorm1d",
"numpy.prod",
"torch.empty",
"torch.nn.Embedding",
"torch.empty_like"
]
] |
martinmcbride/python-projects-for-gcse | [
"cdf4696650b641657e116a3307d4271a114b80df"
] | [
"fractals/iterate-henon.py"
] | [
"import matplotlib.pyplot as plt\n\nxvalues = []\nyvalues = []\nx = 1.12\ny = 0.09\n\nfor i in range(10):\n xvalues.append(x)\n yvalues.append(y)\n print(x, y)\n x, y = y+1-1.4*x*x, 0.3*x\n\nplt.plot(xvalues, yvalues)\nplt.plot(xvalues, yvalues, 'bo')\nplt.show()"
] | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot"
]
] |
stxinsite/wepy | [
"352d4c1316b20e839aae8824eedd66f0f2d0b456"
] | [
"src/wepy/resampling/resamplers/revo.py"
] | [
"import multiprocessing as mulproc\nimport random as rand\nimport itertools as it\n\nimport logging\nfrom eliot import start_action, log_call\n\nimport numpy as np\n\nfrom wepy.resampling.resamplers.resampler import Resampler\nfrom wepy.resampling.resamplers.clone_merge import CloneMergeResampler\nfrom wepy.resamp... | [
[
"numpy.array",
"numpy.zeros",
"numpy.log"
]
] |
c60evaporator/seaborn-analyzer | [
"af1088dffa7d4afb1061a9b3ed220c9fc0ed6a71"
] | [
"seaborn_analyzer/custom_hist_plot.py"
] | [
"from typing import Dict\nimport seaborn as sns\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom scipy import stats\nfrom scipy.stats import distributions\nimport decimal\n\nclass hist():\n # 分布フィッティング線のデフォルトカラーマップ\n _DEFAULT_LINECOLORS = ['red', 'darkmagenta', 'mediumblue', 'da... | [
[
"numpy.histogram",
"scipy.stats.norm",
"numpy.log",
"numpy.roll",
"matplotlib.pyplot.subplots",
"numpy.mean",
"scipy.stats.probplot",
"numpy.std",
"numpy.amax",
"numpy.power",
"numpy.amin",
"scipy.stats.shapiro",
"matplotlib.pyplot.gca"
]
] |
berquist/pyresponse | [
"3267b0ca1e5b2e638cd2388532897f2749af8397"
] | [
"pyresponse/tests/properties/test_quadratic_psi4numpy.py"
] | [
"from itertools import permutations, product\n\nimport numpy as np\n\nimport pyscf\n\nfrom pyresponse import cphf, solvers, utils\nfrom pyresponse.core import Hamiltonian, Program, Spin\nfrom pyresponse.properties import electric\nfrom pyresponse.pyscf.molecules import (\n molecule_physicists_water_augccpvdz,\n ... | [
[
"numpy.array",
"numpy.dot",
"numpy.trace",
"numpy.zeros",
"numpy.testing.assert_almost_equal",
"numpy.set_printoptions",
"numpy.allclose",
"numpy.abs",
"numpy.all",
"numpy.diag",
"numpy.empty_like"
]
] |
denglixi/faster-rcnn.pytorch | [
"12158fa2ec998ba3733a4696b7a4e08a35c157e3"
] | [
"lib/datasets/food_meta_data.py"
] | [
"from __future__ import print_function\nfrom __future__ import absolute_import\n# --------------------------------------------------------\n# Fast R-CNN\n# Copyright (c) 2015 Microsoft\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Ross Girshick\n# ----------------------------------------... | [
[
"numpy.mean",
"scipy.io.loadmat",
"numpy.zeros"
]
] |
PauliKarl/RotationDetection | [
"84bbfe5b1a3ee36e8ad66fd0f36a5ef7b9b0019e",
"84bbfe5b1a3ee36e8ad66fd0f36a5ef7b9b0019e"
] | [
"utils/order_points.py",
"tools/test_dota_base_q.py"
] | [
"# some code from https://github.com/ming71/toolbox/blob/master/rotation/order_points.py\n\nimport os\nimport math\nimport cv2\nimport numpy as np\n\n\n# this function is confined to rectangle\n# clockwise, write by ming71\ndef order_points(pts):\n # sort the points based on their x-coordinates\n xSorted = pt... | [
[
"numpy.array",
"numpy.arccos",
"numpy.zeros",
"numpy.mean",
"numpy.where",
"numpy.sqrt",
"numpy.argsort",
"numpy.iinfo",
"scipy.spatial.distance.cdist",
"numpy.maximum"
],
[
"numpy.array",
"numpy.random.rand",
"numpy.zeros",
"tensorflow.expand_dims",
... |
heytanay/pyprobml | [
"f1856d70d0cbc32f22ed623b881b1801d0015d8f"
] | [
"scripts/kalman_filter_spiral_demo.py"
] | [
"# This demo exemplifies the use of the Kalman Filter\n# algorithm when the linear dynamical system induced by the\n# matrix A has imaginary eigenvalues\n# Author: Gerardo Duran-Martin (@gerdm)\n\nimport jax.numpy as jnp\nimport numpy as np\nimport linear_dynamical_systems_lib as lds\nimport matplotlib.pyplot as pl... | [
[
"matplotlib.pyplot.show",
"numpy.isclose",
"numpy.sqrt",
"matplotlib.pyplot.subplots"
]
] |
sumanthratna/tune-sklearn | [
"5e8db24724b99c16b660dbdb0f3f54bfa1ecfb81"
] | [
"examples/discrete_bayesian.py"
] | [
"from tune_sklearn import TuneSearchCV\nfrom sklearn import datasets\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.ensemble import RandomForestClassifier\nfrom skopt.space.space import Real\n\ndigits = datasets.load_digits()\nX = digits.data\ny = digits.target\n\nX_train, X_test, y_train, y_te... | [
[
"sklearn.model_selection.train_test_split",
"sklearn.datasets.load_digits",
"sklearn.ensemble.RandomForestClassifier"
]
] |
agemor/pytorch-project-template | [
"9b43db0578d6ea0aa40d2fec577cb50e86e57c7d"
] | [
"evaluate.py"
] | [
"import argparse\n\nimport torch\nimport torch.nn as nn\nimport torch.utils.data as data\n\nimport torchvision\nfrom tqdm import tqdm\n\nimport utils\nfrom model import DummyModel\n\n\ndef main():\n parser = argparse.ArgumentParser(fromfile_prefix_chars='@')\n\n # Type of experiment\n parser.add_argument('... | [
[
"torch.max",
"torch.nn.CrossEntropyLoss",
"torch.load",
"torch.utils.data.DataLoader"
]
] |
0316038/tf_models | [
"3ff83c663125aa55e61e996ceee7b6456a47b2d6"
] | [
"research/deeplab/vis.py"
] | [
"# Copyright 2018 The TensorFlow Authors All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requi... | [
[
"tensorflow.logging.set_verbosity",
"tensorflow.shape",
"tensorflow.expand_dims",
"tensorflow.Graph",
"tensorflow.Session",
"tensorflow.train.ChiefSessionCreator",
"tensorflow.logging.info",
"tensorflow.global_variables_initializer",
"tensorflow.ConfigProto",
"tensorflow.gf... |
likun-stat/nonstat_model | [
"01a4b210ccabe446bdde36a213407e5813e5ef80"
] | [
"generic_samplers.py"
] | [
"from __future__ import print_function\n# from scipy.stats import norm\n# from scipy.stats import uniform\nimport numpy as np\n\n## --------------------------------------------------------------------- ##\n# A generic Metropolis sampler. You have to supply the log likelihood #\n# function, which need not reall... | [
[
"numpy.array",
"numpy.isnan",
"numpy.cov",
"numpy.zeros",
"numpy.log",
"numpy.exp",
"numpy.eye",
"numpy.std",
"numpy.arange",
"numpy.linalg.cholesky"
]
] |
sophiaandaloro/flamedisx | [
"3b55f2d4e63a8e05acc372a998cce7315facb665"
] | [
"tests/test_likelihood.py"
] | [
"import numpy as np\nimport pandas as pd\nimport pytest\nimport tensorflow as tf\n\nimport flamedisx as fd\nfrom flamedisx.likelihood import DEFAULT_DSETNAME\n\n\nn_events = 2\n\n@pytest.fixture(params=[\"ER\", \"NR\"])\ndef xes(request):\n # warnings.filterwarnings(\"error\")\n data = pd.DataFrame([dict(s1=5... | [
[
"tensorflow.exp",
"numpy.log",
"numpy.testing.assert_almost_equal",
"tensorflow.constant",
"pandas.concat"
]
] |
DomainGroupOSS/ml-recsys-tools | [
"5cf0e360d712c5a0e52f55f20215bf1bd7af672b"
] | [
"ml_recsys_tools/utils/parallelism.py"
] | [
"from multiprocessing import Process, Queue\n\nimport numpy as np\nimport pandas as pd\nfrom itertools import islice\nimport multiprocessing\nfrom multiprocessing.pool import ThreadPool, Pool\n\nfrom ml_recsys_tools.utils.logger import simple_logger as logger\n\n\nN_CPUS = multiprocessing.cpu_count()\n\n\ndef batch... | [
[
"pandas.concat",
"numpy.concatenate",
"numpy.array_split"
]
] |
Trass3r/Halide | [
"7a1fbc464919fd0861c8e18ff2961aa3cb13125d"
] | [
"python_bindings/tutorial/lesson_07_multi_stage_pipelines.py"
] | [
"#!/usr/bin/python3\n# Halide tutorial lesson 7\n\n# This lesson demonstrates how express multi-stage pipelines.\n\n# This lesson can be built by invoking the command:\n# make tutorial_lesson_07_multi_stage_pipelines\n# in a shell with the current directory at the top of the halide source tree.\n# Otherwise, see th... | [
[
"scipy.misc.imread",
"scipy.misc.imsave"
]
] |
Finasty-lab/IA-Python | [
"286113504906fec11a5aa5fd1d12e38536b1c859",
"286113504906fec11a5aa5fd1d12e38536b1c859"
] | [
"CodeIA/venv/Lib/site-packages/imblearn/ensemble/_bagging.py",
"CodeIA/Training.py"
] | [
"\"\"\"Bagging classifier trained on balanced bootstrap samples.\"\"\"\n\n# Authors: Guillaume Lemaitre <g.lemaitre58@gmail.com>\n# Christos Aridas\n# License: MIT\n\nimport numbers\n\nimport numpy as np\n\nfrom sklearn.base import clone\nfrom sklearn.ensemble import BaggingClassifier\nfrom sklearn.tree im... | [
[
"numpy.where",
"sklearn.base.clone",
"sklearn.tree.DecisionTreeClassifier"
],
[
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.figure",
"sklearn.preprocessing.MinMaxScaler",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.show",
"pandas.read_csv",
"sklea... |
shanest/tensorflow | [
"dcb10b1d557168646204239bea6ca5bf1abc40a3",
"8e8a8a574020227889b08778f57bfe004d2d5ff5",
"dcb10b1d557168646204239bea6ca5bf1abc40a3"
] | [
"tensorflow/contrib/distributions/python/ops/mvn_linear_operator.py",
"tensorflow/python/kernel_tests/scatter_nd_ops_test.py",
"tensorflow/python/ops/distributions/multinomial.py"
] | [
"# Copyright 2016 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.contrib.distributions.python.ops.distribution_util.shapes_from_loc_and_scale",
"tensorflow.python.ops.array_ops.identity",
"tensorflow.contrib.distributions.python.ops.distribution_util.parent_frame_arguments",
"tensorflow.python.ops.distributions.kullback_leibler.RegisterKL",
"ten... |
jfrob27/pywavan | [
"78b3a2aa60fc0110c205dc6bc29098b2c7f5cdd2"
] | [
"pywavan/halo_transform.py"
] | [
"import numpy as np\nfrom .wavan import uv_plane\n\ndef halo_transform(image):\n\t'''\n\tPerforms halo wavelet transform on image.\n\tReturns wavelets wt as image cube\n\t'''\n\n\tna = image.shape[1]\n\tnb = image.shape[0]\n\tko = 5.336\n\tdelta = (2.*np.sqrt(-2.*np.log(.75)))/ko\n\n\tx, y, shiftx, shifty, ishiftx,... | [
[
"numpy.max",
"numpy.fft.ifft2",
"numpy.fft.fft2",
"numpy.log",
"numpy.zeros",
"numpy.exp",
"numpy.sqrt"
]
] |
ZhiquanW/CS231n-Coursework | [
"286089692561c12a82724487ea27db68920fc1f3"
] | [
"assignment2/cs231n/classifiers/fc_net.py"
] | [
"from builtins import range\nfrom builtins import object\nimport numpy as np\n\nfrom cs231n.layers import *\nfrom cs231n.layer_utils import *\n\n\nclass TwoLayerNet(object):\n \"\"\"\n A two-layer fully-connected neural network with ReLU nonlinearity and\n softmax loss that uses a modular layer design. We ... | [
[
"numpy.random.normal",
"numpy.ones",
"numpy.sum",
"numpy.zeros"
]
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.