repo_name stringlengths 8 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
cnk113/TREX | [
"add83d8108f3602c5bbe7b37f60ff19f89b2236d"
] | [
"src/trex/writers.py"
] | [
"from pathlib import Path\nfrom typing import List\nfrom .cell import Cell\nimport operator\nimport warnings\n\nwith warnings.catch_warnings():\n warnings.filterwarnings(\"ignore\", \"Conversion of the second argument of issubdtype\")\n import loompy\nimport numpy as np\n\n\ndef write_count_matrix(path: Path,... | [
[
"numpy.array"
]
] |
18621579069/PaddleHub-yu | [
"47741382cf15eda852fefdada6ce83ef86350af6",
"15e8bcef2addf239081e235bdcfd039de12330e0"
] | [
"paddlehub/contrib/ppdet/data/source/simple_source.py",
"hub_module/modules/text/semantic_model/slda_news/util.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 re... | [
[
"numpy.array"
],
[
"numpy.random.uniform",
"numpy.random.seed"
]
] |
mcoughlin/PypeIt | [
"9aa1d10633faf3d73135e1a1c94b1cd18c7058e0"
] | [
"pypeit/core/gui/identify.py"
] | [
"import os\nimport copy\nimport numpy as np\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom matplotlib.lines import Line2D\nfrom matplotlib.colors import LinearSegmentedColormap, Normalize\nfrom matplotlib.cm import ScalarMappable\nimport matplotlib.transforms as mtransforms\nfrom matplotlib.widgets impor... | [
[
"matplotlib.widgets.Button",
"numpy.copy",
"matplotlib.colors.LinearSegmentedColormap.from_list",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.subplots_adjust",
"numpy.polyfit",
"numpy.polyval",
"matplotlib.colors.Normalize",
"numpy.argmin",
"numpy.abs",
"numpy.where",
... |
JerBouma/OpenBBTerminal | [
"0c60d70cb29b0a6e4db41d6dd0d34f79a6169b27"
] | [
"openbb_terminal/cryptocurrency/overview/coinpaprika_view.py"
] | [
"\"\"\"CoinPaprika view\"\"\"\n__docformat__ = \"numpy\"\n\nimport logging\nimport os\n\nfrom pandas.plotting import register_matplotlib_converters\n\nimport openbb_terminal.cryptocurrency.overview.coinpaprika_model as paprika\nfrom openbb_terminal.cryptocurrency.dataframe_helpers import (\n lambda_long_number_f... | [
[
"pandas.plotting.register_matplotlib_converters"
]
] |
haesleinhuepf/pyclesperanto_prototype | [
"65bc3035d3b2b61a2722c93b95bae310bfbd190e"
] | [
"pyclesperanto_prototype/_tier8/_affine_transform.py"
] | [
"from typing import Union\n\nfrom .._tier0 import plugin_function\nfrom .._tier0 import Image\nfrom .._tier0 import push\nfrom ._AffineTransform3D import AffineTransform3D\nfrom skimage.transform import AffineTransform\nimport numpy as np\n\n@plugin_function\ndef affine_transform(source : Image, destination : Image... | [
[
"numpy.linalg.inv",
"numpy.asarray"
]
] |
tourdeml/SAM | [
"08cb3cccb39157859a1c77ef1e1852120df4a790"
] | [
"sam/utils.py"
] | [
"from typing import Iterable, Callable\n\nimport torch\nfrom torch.optim import Optimizer\n\n\ndef compute_sam(group: dict, closure: Callable):\n grads = []\n params_with_grads = []\n\n rho = group['rho']\n # update internal_optim's learning rate\n\n for p in group['params']:\n if p.grad is no... | [
[
"torch._foreach_mul_",
"torch._foreach_add_",
"torch._foreach_sub_"
]
] |
andrewor14/benchmarks | [
"cb2457bbda6138b3e0af95a6d50b7d476d52c410"
] | [
"scripts/tf_cnn_benchmarks/models/ssd_model.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 requ... | [
[
"tensorflow.reshape",
"tensorflow.variable_scope",
"tensorflow.squeeze",
"tensorflow.concat",
"tensorflow.nn.softmax",
"tensorflow.reduce_sum",
"tensorflow.split",
"tensorflow.contrib.framework.argsort",
"tensorflow.multiply",
"tensorflow.losses.sparse_softmax_cross_entropy... |
Nagasaki45/deep_disfluency | [
"4c57a194433af9601ebef0e4c9a451cce4c06252"
] | [
"deep_disfluency/rnn/elman.py"
] | [
"import theano\nimport numpy as np\nimport os\n\nfrom theano import tensor as T\nfrom collections import OrderedDict\n\n# nb might be theano.config.floatX\ndtype = T.config.floatX # @UndefinedVariable\n\n\nclass Elman(object):\n\n def __init__(self, ne, de, na, nh, n_out, cs, npos,\n update_embe... | [
[
"numpy.random.uniform",
"numpy.asarray",
"numpy.zeros"
]
] |
mrakitin/xrt | [
"a2d09296860386ed3a83cea45ab43e7959e58f33"
] | [
"xrt/runner.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nModule :mod:`runner` defines the entry point of xrt - :func:`run_ray_tracing`,\ncontainers for job properties and functions for running the processes or\nthreads and accumulating the resulting histograms.\n\"\"\"\n__author__ = \"Konstantin Klementiev, Roman Chernikov\"\n__date__ = ... | [
[
"numpy.concatenate",
"matplotlib.pyplot.show",
"matplotlib.pyplot.get_backend",
"numpy.long"
]
] |
luckykamon/Morpion | [
"a4da849a354c542fc5a79a3742a86b040df7e016"
] | [
"create_image/white.py"
] | [
"import imageio\nimport matplotlib.pyplot as plt\nimport Image\nimport numpy as np\n\nim = Image.new(\"RGB\", (65,65), \"white\")\npic = np.array(im)\nim=pic\nimageio.imsave(\"white.png\", im)\n\n"
] | [
[
"numpy.array"
]
] |
faymek/compression | [
"20c6745b741e266f7118e6b3fc88d22f6179cfdf"
] | [
"examples/varate.py"
] | [
"#%%\n\"\"\"\nbmshj2018\n\n\"\"\"\n\nimport argparse\nimport glob\nimport sys\n\nfrom absl import app\nfrom absl.flags import argparse_flags\nimport numpy as np\nimport tensorflow.compat.v1 as tf\n\nimport tensorflow_compression as tfc\nfrom dynamic import *\n\n\nSCALES_MIN = 0.11\nSCALES_MAX = 256\nSCALES_LEVELS =... | [
[
"tensorflow.compat.v1.train.MonitoredTrainingSession",
"tensorflow.compat.v1.train.StopAtStepHook",
"tensorflow.compat.v1.log",
"tensorflow.compat.v1.train.AdamOptimizer",
"tensorflow.compat.v1.expand_dims",
"numpy.log",
"tensorflow.compat.v1.image.psnr",
"tensorflow.compat.v1.shap... |
szokejokepu/natural-rws | [
"bb1ad4ca3ec714e6bf071d2136593dc853492b68"
] | [
"core/argo/core/network/MultivariateNormalTriL.py"
] | [
"import tensorflow as tf\nfrom tensorflow_probability import distributions as tfd\nfrom functools import partial\nfrom .AbstractGaussianSimple import AbstractGaussianSimple\nimport types\nimport sonnet as snt\n\nclass MultivariateNormalTriL(AbstractGaussianSimple):\n\n def __init__(self,\n output... | [
[
"tensorflow.pad",
"tensorflow.contrib.distributions.fill_triangular",
"tensorflow.layers.flatten",
"tensorflow.multiply",
"tensorflow.initializers.constant",
"tensorflow.linalg.set_diag",
"tensorflow.nn.softplus"
]
] |
cristhiandcl/AD-DL | [
"b7abb3fe619e736b269067033ba4aad1f03cf3b8"
] | [
"clinicadl/clinicadl/tools/tsv/tsv_utils.py"
] | [
"# coding: utf8\n\nfrom copy import copy\nimport numpy as np\nimport pandas as pd\nfrom os import path\n\n\ndef neighbour_session(session, session_list, neighbour):\n if session not in session_list:\n temp_list = session_list + [session]\n temp_list.sort()\n else:\n temp_list = copy(sessi... | [
[
"scipy.stats.chisquare",
"pandas.DataFrame",
"pandas.concat",
"numpy.array",
"numpy.concatenate",
"numpy.unique"
]
] |
jeetbanik/Corona-Real-Time-Face-Mask-and-Keypoints-Detection | [
"3232f5d7b84fffcc61c2bb84d1b5109154bcc6bb"
] | [
"Testing Model Including Facial Keypoints.py"
] | [
"import numpy as np\nfrom PIL import Image\nimport cv2\nfrom model import Net\nimport torch\nfrom torchvision import transforms\nfrom mtcnn import MTCNN\n\ndef LoadModel(fpath):\n '''\n function to load saved model\n '''\n c = torch.load(fpath, map_location='cpu')\n model = c['model']\n model.load... | [
[
"torch.load",
"torch.cuda.is_available",
"torch.from_numpy",
"torch.max",
"numpy.array"
]
] |
KarthikKothareddy/AirFlow | [
"faaf0b8b4467bcf5bff4a5b49086a9e02cb9c112"
] | [
"tests/core.py"
] | [
"# -*- coding: utf-8 -*-\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in wri... | [
[
"numpy.testing.assert_array_almost_equal"
]
] |
fheyen/ClaVis | [
"528ca85dd05606d39761b5a00d755500cf1cd2f6"
] | [
"backend/modules/classifiers/cifar10_cnn/__init__.py"
] | [
"import numpy\nimport keras\nfrom keras.preprocessing.image import ImageDataGenerator\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Activation, Flatten\nfrom keras.layers import Conv2D, MaxPooling2D\nfrom keras.callbacks import EarlyStopping\nimport os\nfrom ...tools import check_ar... | [
[
"numpy.random.seed"
]
] |
Tianxiaomo/ROI | [
"8422716605f846c6f4276051a9738cb6c162611d"
] | [
"roi/layers/nms.py"
] | [
"# -*- coding: utf-8 -*-\n# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\nimport torch\nfrom torchvision.ops import boxes as box_ops\nfrom torchvision.ops import nms # BC-compat\n\n\ndef batched_nms(boxes, scores, idxs, iou_threshold):\n \"\"\"\n Same as torchvision.ops.boxes.batche... | [
[
"torch.empty",
"torch.min",
"torch.unique",
"torch.max"
]
] |
xmengxin/MFGR | [
"ba807d0f52c0eb00d330eaa9bcef56c1343d2588"
] | [
"models/dcgan_conv.py"
] | [
"import torch\nimport torch.nn as nn\n\n\n# custom weights initialization called on netG and netD\ndef weights_init(m):\n classname = m.__class__.__name__\n if classname.find('Conv') != -1:\n nn.init.normal_(m.weight.data, 0.0, 0.02)\n elif classname.find('BatchNorm') != -1:\n nn.init.normal_... | [
[
"torch.nn.BatchNorm2d",
"torch.nn.Linear",
"torch.randint",
"torch.nn.init.constant_",
"torch.nn.Dropout2d",
"torch.randn",
"torch.flatten",
"torch.nn.init.normal_",
"torch.nn.Tanh",
"torch.nn.Upsample",
"torch.nn.Conv2d",
"torch.nn.Sigmoid",
"torch.nn.LeakyReLU... |
hiagopinacio/ross | [
"1bc84061f23df455d9e37cb11b244ac795c836ad"
] | [
"ross/api_report.py"
] | [
"# fmt: off\nfrom copy import copy, deepcopy\n\nimport numpy as np\nimport pandas as pd\nfrom plotly import express as px\nfrom plotly import graph_objects as go\nfrom plotly.subplots import make_subplots\nfrom scipy.interpolate import interp1d\nfrom scipy.signal import argrelextrema\n\nfrom ross.bearing_seal_eleme... | [
[
"numpy.sum",
"scipy.interpolate.interp1d",
"scipy.signal.argrelextrema",
"numpy.transpose",
"numpy.append",
"numpy.argmin",
"numpy.cos",
"numpy.log10",
"numpy.delete",
"numpy.where",
"numpy.round",
"numpy.linspace",
"numpy.mean",
"numpy.argmax",
"pandas.... |
dimitymiller/cac-openset | [
"b07dadbb8caa5d7430c403734f6543ff17e2ae11"
] | [
"datasets/generate_trainval_splits.py"
] | [
"\"\"\"\n\tRandomly select train and validation subsets from training datasets.\n\t80/20 split ratio used for all datasets except TinyImageNet, which will use 90/10.\n\n\tDimity Miller, 2020\n\"\"\"\n\nimport json\nimport random\nimport torchvision\nimport numpy as np\n\nrandom.seed(1000)\n\ndef save_trainval_split... | [
[
"numpy.unique"
]
] |
Pandinosaurus/depthai | [
"a46ad95744d8175f1c87bf8cd92c7423a84b8607"
] | [
"depthai_profiler.py"
] | [
"#!/usr/bin/env python3\n\n#depthai function profiler\nimport subprocess\nimport sys\nimport numpy as np\n\n#this is a debugging tool, that's why it's not added to requirements.txt\ntry:\n import snakeviz\nexcept ImportError:\n raise ImportError('\\033[1;5;31m snakeviz module not found, run: \\033[0m python3 ... | [
[
"numpy.concatenate"
]
] |
IJSComplexMatter/cddm | [
"f4d7521ad88271027c61743b2e8a2355a40cb117"
] | [
"examples/paper/plot_error.py"
] | [
"\"\"\"Plots fig 3. and fig 4. from the paper.\n\nYou must first create data calling the following scripts:\n \n$ python auto_correlate_random_error.py\n$ python auto_correlate_standard_error.py\n$ python auto_correlate_fast_error.py\n$ python cross_correlate_error.py\n\n\"\"\"\n\nfrom cddm.sim import random_tim... | [
[
"matplotlib.pyplot.figure",
"matplotlib.pyplot.tight_layout",
"numpy.arange",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.show",
"numpy.sqrt"
]
] |
panpanyunshi/rlkit | [
"e1f6c9e59ab2baab93d35385cdc43ab3632b2b65"
] | [
"rlkit/torch/core.py"
] | [
"import numpy as np\nimport torch\n\nfrom rlkit.torch import pytorch_util as ptu\n\n\ndef eval_np(module, *args, **kwargs):\n \"\"\"\n Eval this module with a numpy interface, 返回numpy类型变量\n\n Same as a call to __call__ except all Variable input/outputs are\n replaced with numpy equivalents.\n\n Assum... | [
[
"numpy.dtype"
]
] |
asaran/decision-transformer | [
"f6f8bf283256d616d213ac5bd07cb7f3efb101b3"
] | [
"gym/decision_transformer/models/decision_transformer.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\n\nimport transformers\n\nfrom decision_transformer.models.model import TrajectoryModel\nfrom decision_transformer.models.trajectory_gpt2 import GPT2Model\n\n\nclass DecisionTransformer(TrajectoryModel):\n\n \"\"\"\n This model uses GPT to model (Return... | [
[
"torch.ones",
"torch.stack",
"torch.nn.Linear",
"torch.nn.Embedding",
"torch.nn.Tanh",
"torch.nn.LayerNorm",
"torch.zeros"
]
] |
elwintay/clearml_test | [
"c87985303e69490e83ec779d098570bc505f80ae"
] | [
"model_gtt/run_pl_gtt.py"
] | [
"import argparse\nimport glob\nimport pandas as pd\nimport logging\nimport os\nimport json\nfrom collections import OrderedDict\nfrom eval import eval_tf\n\nimport numpy as np\nimport torch\nfrom seqeval.metrics import f1_score, precision_score, recall_score, accuracy_score\nfrom torch.nn import CrossEntropyLoss\nf... | [
[
"torch.stack",
"torch.load",
"torch.nn.Softmax",
"torch.save",
"torch.tensor",
"numpy.argmax",
"torch.nn.CrossEntropyLoss",
"torch.utils.data.TensorDataset",
"torch.topk",
"torch.cuda.is_available",
"torch.index_select",
"numpy.concatenate",
"torch.bmm",
"to... |
simonsimon006/tensorflow-wavelets | [
"21a095bf0048ae2488ca5ae4961d2cbfe94263a9"
] | [
"Development/models/DWT2.py"
] | [
"import os\nimport cv2\nimport math\nimport pywt\nimport numpy as np\nfrom utils import mse\nimport tensorflow as tf\nfrom tensorflow import keras\nfrom tensorflow.keras import layers\nfrom tensorflow.keras.datasets import mnist, cifar10\n\n# os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # for tensor flow warning\n# os... | [
[
"tensorflow.pad",
"tensorflow.stack",
"tensorflow.add_n",
"tensorflow.reshape",
"tensorflow.keras.Sequential",
"tensorflow.expand_dims",
"tensorflow.zeros_like",
"tensorflow.nn.conv2d",
"numpy.int32",
"tensorflow.repeat",
"numpy.expand_dims",
"tensorflow.keras.layer... |
chetansurwade/great_expectations | [
"f488d861f3c00c73a6181d6bd5788fb8895079d9"
] | [
"tests/conftest.py"
] | [
"import datetime\nimport locale\nimport logging\nimport os\nimport random\nimport shutil\nimport sys\nimport warnings\nfrom typing import Dict, List, Optional\n\nimport numpy as np\nimport pandas as pd\nimport pytest\nfrom freezegun import freeze_time\nfrom ruamel.yaml import YAML\n\nimport great_expectations as ge... | [
[
"pandas.read_csv",
"pandas.DataFrame",
"numpy.random.normal"
]
] |
drudd/pandas | [
"99922b9175c4ca6acb0f42dd17c01c507cbd94d6"
] | [
"pandas/core/algorithms.py"
] | [
"\"\"\"\nGeneric data algorithms. This module is experimental at the moment and not\nintended for public consumption\n\"\"\"\nfrom __future__ import division\nfrom warnings import warn\nimport numpy as np\n\nimport pandas.core.common as com\nimport pandas.algos as algos\nimport pandas.hashtable as htable\nimport pa... | [
[
"pandas.hashtable.value_count_int64",
"pandas.core.common.isnull",
"pandas.hashtable.mode_int64",
"numpy.asarray",
"pandas.hashtable.mode_object",
"pandas.core.common._asarray_tuplesafe",
"numpy.isscalar",
"pandas.core.common.is_float_dtype",
"pandas.algos.arrmap_float64",
... |
flaght/zipline | [
"15b8832421e2b1ba98ec9938ceb794f64ad581b5",
"0848a8a4862fd8bbe7ba64654e6bc731b4b622b7"
] | [
"tests/test_perf_tracking.py",
"tests/test_api_shim.py"
] | [
"#\n# Copyright 2016 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 required by applicable law or... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"pandas.Timestamp",
"numpy.float64",
"pandas.DataFrame.from_dict"
],
[
"numpy.arange",
"pandas.Timestamp",
"numpy.testing.assert_array_equal"
]
] |
steven-murray/powerbox | [
"09809f3fe9e2b25dfb2f956ca4c2d4d40a0ac693"
] | [
"tests/test_power.py"
] | [
"import numpy as np\nimport os\nimport inspect\nimport sys\n\nLOCATION = \"/\".join(os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))).split(\"/\")[:-1])\nsys.path.insert(0, LOCATION)\n\nfrom powerbox import PowerBox, get_power\n\n\ndef test_power1d():\n p = [0] * 40\n for i in range(40... | [
[
"numpy.array",
"numpy.allclose",
"numpy.all",
"numpy.ones_like"
]
] |
jesserobertson/cogj | [
"25f1d85023764ef0cc459a8a715b1b678f971858"
] | [
"setup_extensions.py"
] | [
"\"\"\" file: setup_extensions.py (cogj)\n author: Jess Robertson, @jesserobertson\n date: Saturday, 16 March 2019\n\n description: Set up Cython extensions for CO-GJ\n\"\"\"\n\nfrom pathlib import Path\nfrom logging import getLogger\nfrom multiprocessing import cpu_count\n\nimport numpy\nfrom setup... | [
[
"numpy.get_include"
]
] |
CAVED123/Tensorforce | [
"823177f77f9047b1e71eccfffc08315ed1636878"
] | [
"tensorforce/core/optimizers/solvers/line_search.py"
] | [
"# Copyright 2018 Tensorforce Team. 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 b... | [
[
"tensorflow.abs",
"tensorflow.maximum",
"tensorflow.control_dependencies",
"tensorflow.math.logical_and"
]
] |
spirit-code/aiida-spirit | [
"7a0c0ca7406f958599b691a410201137f9fb94e9"
] | [
"tests/test_calculations.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\" Tests for calculations\n\n\"\"\"\nimport os\nimport numpy as np\nfrom aiida.plugins import CalculationFactory\nfrom aiida.orm import Dict\nfrom aiida.engine import run, run_get_node\nfrom aiida_spirit.tools.helpers import prepare_test_inputs\n\nfrom . import TEST_DIR\n\n\ndef test_i... | [
[
"numpy.std",
"numpy.mean"
]
] |
heather999/lenstronomy | [
"8102fe026c1f3ba6e81d8a1f59cceb90e68430b4"
] | [
"lenstronomy/ImSim/differential_extinction.py"
] | [
"from lenstronomy.LightModel.light_model import LightModel\nimport numpy as np\n\n__all__ = ['DifferentialExtinction']\n\n\nclass DifferentialExtinction(object):\n \"\"\"\n class to compute an extinction (for a specific band/wavelength). This class uses the functionality available in\n the LightModel modul... | [
[
"numpy.exp"
]
] |
forestriveral/floris | [
"02c31e121283ad6ccae987cfa3aa1bf1e4b43014"
] | [
"examples/visualization/subtract_inflow.py"
] | [
"# Copyright 2021 NREL\n\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may not\n# use this file except in compliance with the License. You may obtain a copy of\n# the License at http://www.apache.org/licenses/LICENSE-2.0\n\n# Unless required by applicable law or agreed to in writing, soft... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
]
] |
ConsenSys/handel | [
"bc3f6f8194db140a1067ab157fc6bb1fb53a0144"
] | [
"simul/plots/failing_time.py"
] | [
"#!/usr/bin/env python\n\n## This script generate the graphs that compares handel signature \n## generation with different number of failing nodes for a fixed \n## number of total nodes, and a fixed threshold 51%\n##\nimport sys\n\nimport matplotlib.pyplot as plt\nimport pandas as pd\nplt.figure(figsize=(4,2))\nfro... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.xlabel"
]
] |
sakibguy/models | [
"7214e17eb425963ec3d0295be215d5d26deaeb32"
] | [
"official/nlp/tools/export_tfhub_lib_test.py"
] | [
"# Copyright 2022 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.io.gfile.GFile",
"numpy.ones_like",
"tensorflow.executing_eagerly",
"tensorflow.RaggedTensorSpec",
"tensorflow.ragged.constant",
"tensorflow.Graph",
"tensorflow.constant",
"tensorflow.test.main",
"tensorflow.saved_model.load",
"tensorflow.compat.v1.Session",
... |
good5dog5/Speaker-Diarization | [
"4cc38f77a2f2c24ce086323aa37098f6cd0f7f10"
] | [
"ghostvlad/generate_embeddings.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import print_function\nimport os\nimport sys\nimport numpy as np\nimport librosa\n\nimport toolkits\nimport random\n\n# ===========================================\n# Parse the argument\n# ===========================================\nimport argparse\np... | [
[
"numpy.savez",
"numpy.expand_dims",
"numpy.array",
"numpy.std",
"numpy.concatenate",
"numpy.random.randint",
"numpy.linalg.norm",
"numpy.unique",
"numpy.mean"
]
] |
fzyzcjy/ncnn | [
"42e71609508fde1bd54d9d9de6ca5522ee3bcf37"
] | [
"tools/pnnx/tests/test_nn_BatchNorm2d.py"
] | [
"# Tencent is pleased to support the open source community by making ncnn available.\n#\n# Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.\n#\n# Licensed under the BSD 3-Clause License (the \"License\"); you may not use this file except\n# in compliance with the License. You may obtain a... | [
[
"torch.nn.BatchNorm2d",
"torch.manual_seed",
"torch.rand",
"torch.equal",
"torch.jit.trace"
]
] |
ofgulban/iphigen | [
"47c972a5852677e01ab0b120f69d004abc57e478"
] | [
"iphigen/iphigen_nifti.py"
] | [
"\"\"\"MRI data processing with retinex and balance methods.\"\"\"\n\nfrom __future__ import division\nimport os\nimport numpy as np\nimport nibabel as nb\nfrom iphigen import core, utils\nfrom iphigen.ui import user_interface, display_welcome_message\nimport iphigen.config as cfg\n\n\ndef main():\n \"\"\"Iphige... | [
[
"numpy.sum",
"numpy.asarray"
]
] |
johnruth96/privacy-justifiable-fairness | [
"3f5ae92d791df1827cbc8720cf5e7aa33ceed7aa"
] | [
"experiments/evaluate.py"
] | [
"import os\n\nimport pandas as pd\n\nfrom experiments.conf import Config\nfrom fairness import measure_fairness\nfrom privacy.models import get_l_distinct, get_k\n\n\ndef evaluate_experiment(conf: Config):\n # Load setup\n setup = conf.get_setup()\n A = setup[\"A\"]\n I = setup[\"I\"]\n O = setup[\"O... | [
[
"pandas.read_csv",
"pandas.MultiIndex.from_tuples"
]
] |
Yidansong/SchNet | [
"49a1e6031f50d79a83ea21148b8e8cbcabdaabb7"
] | [
"src/schnet/nn/utils.py"
] | [
"import numpy as np\nimport tensorflow as tf\nfrom tensorflow.python.ops.array_grad import _TileGrad\nfrom tensorflow.python.framework import ops\n\n\ndef shape(x):\n if isinstance(x, tf.Tensor):\n return x.get_shape().as_list()\n return np.shape(x)\n\n\n@ops.RegisterGradient(\"TileDense\")\ndef tile_g... | [
[
"tensorflow.python.ops.array_grad._TileGrad",
"numpy.shape",
"tensorflow.python.framework.ops.RegisterGradient",
"tensorflow.convert_to_tensor"
]
] |
Banconxuan/RTS3D | [
"6d2738501eaf90f019eeaa22254cd9756f8d3364"
] | [
"src/lib/models/embedding_space_generater.py"
] | [
"# ------------------------------------------------------------------------------\n# Copyright (c) Microsoft\n# Licensed under the MIT License.\n# Written by Bin Xiao (Bin.Xiao@microsoft.com)\n# Modified by Xingyi Zhou\n# ------------------------------------------------------------------------------\n\nfrom __futur... | [
[
"torch.stack",
"torch.nonzero",
"torch.linspace",
"torch.exp",
"torch.norm",
"torch.nn.functional.grid_sample",
"torch.meshgrid",
"torch.cat"
]
] |
FelixNeutatz/auto-sklearn | [
"b5d141603332041475ed746aa1640334f5561aea"
] | [
"autosklearn/pipeline/components/data_preprocessing/imputation/categorical_imputation.py"
] | [
"from ConfigSpace.configuration_space import ConfigurationSpace\nfrom autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm\nfrom autosklearn.pipeline.constants import DENSE, SPARSE, UNSIGNED_DATA, INPUT\nfrom ConfigSpace.hyperparameters import CategoricalHyperparameter, UniformIntegerHyperp... | [
[
"numpy.unique",
"sklearn.model_selection.train_test_split"
]
] |
helloworldpark/PyEMD | [
"d28481b3244f317c196dbfe92af7e2d776b64382"
] | [
"PyEMD/EMD_matlab.py"
] | [
"#!/usr/bin/python\r\n# coding: UTF-8\r\n#\r\n# Author: Dawid Laszuk\r\n# Contact: laszukdawid@gmail.com\r\n#\r\n# Edited: 11/05/2017\r\n#\r\n# Feel free to contact for any information.\r\n\r\nfrom __future__ import division, print_function\r\n\r\nimport logging\r\nimport numpy as np\r\nimport time\r\n\r\nfrom... | [
[
"numpy.save",
"scipy.interpolate.interp1d",
"numpy.diff",
"numpy.any",
"numpy.append",
"numpy.abs",
"numpy.cos",
"numpy.where",
"numpy.round",
"numpy.nonzero",
"numpy.linspace",
"numpy.mean",
"numpy.ceil",
"numpy.zeros",
"numpy.array",
"numpy.linalg.... |
simpla-fusion/spdb | [
"be6667eb6c7d464f68b0fd51ca2a8f021581eb84"
] | [
"examples/obsolete/putslice_eq.py"
] | [
"# Definition of the class structures in file imas.py\nimport imas\nimport numpy\nimport sys\nimport os\n\n'''\nThis sample program will create a pulse file (shot 13, run 1) and will\nput an example of equilibirium IDS using put_slice methods.\n'''\n\n# This routine reads an array of pfsystems IDSs in the database,... | [
[
"numpy.empty",
"numpy.zeros"
]
] |
ChuanTianML/learn_gnmt | [
"19e97e04feaecd7682abaf6247a0f9e3f37f9892"
] | [
"nmt/utils/common_test_utils.py"
] | [
"# Copyright 2017 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.python.ops.lookup_ops.index_table_from_tensor",
"tensorflow.constant",
"tensorflow.python.ops.lookup_ops.index_to_string_table_from_tensor"
]
] |
floyebolu/GPy | [
"d493b200642196c6d211ea1bcb052f3fbf396f24"
] | [
"GPy/plotting/gpy_plot/latent_plots.py"
] | [
"#===============================================================================\n# Copyright (c) 2015, Max Zwiessele\n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions are met:\n#\n# * Redistributio... | [
[
"numpy.ones",
"numpy.zeros",
"numpy.argmax",
"numpy.log",
"numpy.array",
"numpy.unique"
]
] |
swpucwf/Deeplearning | [
"be19885d52b7ce8782949d931a1b2994de36679f"
] | [
"OpenCV/video_flow.py"
] | [
"import numpy as np\nimport cv2\n\ncap = cv2.VideoCapture('car.mp4')\n\n# params for ShiTomasi corner detection\nfeature_params = dict(maxCorners=100,\n qualityLevel=0.3,\n minDistance=7,\n blockSize=7)\n\n# Parameters for lucas kanade optical flow\nlk_... | [
[
"numpy.zeros_like",
"numpy.random.randint"
]
] |
vita-epfl/pedestrian-transition-dataset | [
"7e1b723a37289850b5ef8628e6881845a24912f9"
] | [
"src/dataset/loader.py"
] | [
"import os\nimport copy\nimport PIL\nimport torch\nimport torchvision\nimport numpy as np\nimport math\n\nimport logging\nfrom typing import List\n\nLOG = logging.getLogger(__name__)\n\n\ndef define_path(use_jaad=True, use_pie=True, use_titan=True):\n \"\"\"\n Define the correct paths to datasets'annotations ... | [
[
"torch.zeros",
"torch.rand",
"torch.stack",
"torch.tensor"
]
] |
mizolotu/DonkeyCarExperiments | [
"3d6be742915efe51c0f5abda4c69a4349a555373"
] | [
"reinforcement_learning/her/utils.py"
] | [
"from collections import OrderedDict\n\nimport numpy as np\nfrom reinforcement_learning.gym import spaces\n\n# Important: gym mixes up ordered and unordered keys\n# and the Dict space may return a different order of keys that the actual one\nKEY_ORDER = ['observation', 'achieved_goal', 'desired_goal']\n\n\nclass HE... | [
[
"numpy.concatenate"
]
] |
JuliaChae/faster-rcnn.pytorch | [
"220005b5dbed1dd7e5abcfb85eee9f976a8a5f58"
] | [
"lib/detection_metric/Evaluator.py"
] | [
"###########################################################################################\n# #\n# Evaluator class: Implements the most popular metrics for object detection #\n# ... | [
[
"numpy.sum",
"matplotlib.pyplot.legend",
"numpy.cumsum",
"numpy.divide",
"numpy.argwhere",
"numpy.zeros",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.close",
"matplotlib.pyplot.plot",
... |
mindspore-ai/models | [
"9127b128e2961fd698977e918861dadfad00a44c",
"9127b128e2961fd698977e918861dadfad00a44c",
"9127b128e2961fd698977e918861dadfad00a44c"
] | [
"official/nlp/transformer/export.py",
"research/cv/meta-baseline/preprocess.py",
"research/cv/ras/src/resnet50.py"
] | [
"# Copyright 2020-2022 Huawei Technologies Co., Ltd\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 applica... | [
[
"numpy.ones"
],
[
"numpy.save",
"numpy.random.seed"
],
[
"numpy.sqrt",
"numpy.ones",
"numpy.zeros"
]
] |
PPACI/Devoxx19-TensorflowJS | [
"4096c8ea460af8a9f8a36df01e88309568318ab8"
] | [
"python/02_train.py"
] | [
"from PIL import Image\nimport numpy\nfrom tensorflow.python.keras.preprocessing.image import ImageDataGenerator\nfrom tensorflow.python.keras.applications.mobilenet import MobileNet\nfrom tensorflow.python.keras.models import Model\nfrom tensorflow.python.keras.layers import Dense, Dropout, BatchNormalization\nfro... | [
[
"tensorflow.python.keras.layers.Dense",
"tensorflow.python.keras.applications.mobilenet.MobileNet",
"tensorflow.python.keras.models.Model",
"tensorflow.python.keras.optimizers.Adam",
"tensorflow.python.keras.preprocessing.image.ImageDataGenerator",
"tensorflow.python.keras.layers.Dropout"
... |
fbrundu/scCODA | [
"5508a0419d4a46e33897a5df69ba6d4e1753fadd"
] | [
"sccoda/model/dirichlet_models.py"
] | [
"\"\"\"\nDirichlet-multinomial models for statistical analysis of compositional changes in single-cell data.\n\nFor further reference, see:\nBüttner, Ostner et al.: scCODA: A Bayesian model for compositional single-cell data analysis\n\n:authors: Johannes Ostner\n\"\"\"\nimport numpy as np\nimport time\nimport warn... | [
[
"numpy.sum",
"tensorflow.zeros",
"numpy.matmul",
"numpy.zeros",
"tensorflow.ones",
"numpy.exp",
"numpy.count_nonzero",
"numpy.size",
"tensorflow.cast",
"tensorflow.exp",
"tensorflow.matmul",
"tensorflow.convert_to_tensor",
"tensorflow.random.normal",
"numpy.... |
ylimit/ModelDiff | [
"f509bd2a1de20138aeb5cf105f99597a279f6f0b"
] | [
"utils.py"
] | [
"import os\nimport os.path as osp\nimport sys\nimport time\nimport argparse\nfrom pdb import set_trace as st\nimport json\nimport functools\n\nimport torch\nimport numpy as np\nimport torchvision\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\n\nfrom torchvision import transfor... | [
[
"torch.utils.data.DataLoader",
"torch.load",
"torch.zeros_like",
"torch.nn.LogSoftmax",
"numpy.linalg.norm"
]
] |
TomLiu59/AI-Final-Project | [
"160cb39f7a6c2d51a5f131c70a2ef4677a6d554e"
] | [
"main.py"
] | [
"import numpy as np\nimport pprint\nimport tensorflow as tf\nimport os\nfrom datetime import datetime\n\nfrom model import AlternatingAttention\nimport data_helper\nimport train\nimport test1\nimport sys\n\nflags = tf.app.flags;\n\nflags.DEFINE_integer(\"embedding_dim\", 384, \"Dimensionality of character embedding... | [
[
"tensorflow.app.run",
"tensorflow.device",
"numpy.max",
"tensorflow.train.Saver",
"tensorflow.ConfigProto"
]
] |
ShuoZ9379/Integration_SIL_and_MBL | [
"d7df6501a665d65eb791f7fd9b8e85fd660e6320"
] | [
"algos/mbl_copos2_sil/run.py"
] | [
"import multiprocessing\nimport os.path as osp\nimport gym,sys\nfrom collections import defaultdict\nimport tensorflow as tf\nimport numpy as np\nimport pickle\nfrom baselines.common.vec_env import VecFrameStack,VecEnv, VecNormalize\nfrom baselines.run import parse_cmdline_kwargs, build_env, configure_logger, get_d... | [
[
"tensorflow.variable_scope",
"numpy.zeros",
"tensorflow.global_variables_initializer"
]
] |
mrtucar/keras-unet-collection | [
"38ac652f33799502df1933c805c04e366ee05c3d"
] | [
"keras_unet_collection/_model_swin_unet_2d.py"
] | [
"\nfrom __future__ import absolute_import\n\nfrom keras_unet_collection.layer_utils import *\nfrom keras_unet_collection.transformer_layers import patch_extract, patch_embedding, SwinTransformerBlock, patch_merging, patch_expanding\n\nfrom tensorflow.keras.layers import Input, Dense\nfrom tensorflow.keras.models im... | [
[
"tensorflow.keras.layers.Input"
]
] |
warcraft12321/Hyperfoods | [
"b995cd7afe10fcbd338158c80f53ce637bfffc0c",
"b995cd7afe10fcbd338158c80f53ce637bfffc0c"
] | [
"src/torch/nn/grad.py",
"src/torch/utils/data/distributed.py"
] | [
"\"\"\"Gradient interface\"\"\"\n\nimport torch\nfrom .modules.utils import _single, _pair, _triple\n\n\ndef _grad_input_padding(grad_output, input_size, stride, padding, kernel_size):\n input_size = list(input_size)\n k = grad_output.dim() - 2\n\n if len(input_size) == k + 2:\n input_size = input_s... | [
[
"torch.conv_transpose2d",
"torch.conv1d",
"torch.conv_transpose3d",
"torch.conv2d",
"torch.conv3d",
"torch.conv_transpose1d"
],
[
"torch.distributed.get_rank",
"torch.Generator",
"torch.distributed.get_world_size"
]
] |
vonkaenelerik/self-supervised-poisson-gaussian | [
"7ebb4527fa79ace7d5de8c28fb484ef1a5cd1c96"
] | [
"test_mydat.py"
] | [
"import numpy as np\nfrom skimage.metrics import peak_signal_noise_ratio\nfrom nets import *\nfrom scipy.optimize import minimize\n\nimport os\nfrom os import listdir\nfrom os.path import join\nfrom imageio import imread, imwrite\nimport glob\nfrom tqdm import trange\n\nimport argparse\nparser = argparse.ArgumentPa... | [
[
"numpy.squeeze",
"numpy.quantile",
"numpy.stack",
"numpy.log",
"numpy.maximum",
"numpy.mean"
]
] |
ryanjmccall/sb_ml_eng_capstone | [
"dfa87dcbd741c6f502b6cd0eb8f31203568c09a2"
] | [
"modules/module_5_3_2/data/population.py"
] | [
"#!/usr/bin/env python\n\nimport numpy as np\nimport pandas as pd\nimport os\n\ndata_file = os.path.join(os.path.dirname(__file__),'Top5000population.csv')\n\ndata = pd.read_csv(data_file, header=None, thousands=',',sep=',',\n names=['city','state','pop'],\n encoding='iso-8859-1')\n\ndata['city'] = da... | [
[
"pandas.read_csv"
]
] |
kovenock/FATES_Parameter_Selection | [
"eb38cc96b3cb6c02ae71426b6351e60b16ed8a56"
] | [
"psfxns/annmeans.py"
] | [
"import netCDF4 as nc4\nimport numpy as np\n\n\ndef annual_mean_model(filepath, var, varfiletype, nyrs, conv_factor):\n \"\"\"Calculate time series of model annual means for one variable.\n \n :param filepath (str): the file path and name for the data file\n :param var (str): the name of the variable to... | [
[
"numpy.reshape"
]
] |
DFNaiff/BVBQ | [
"48f0eb624483f67b748d791efc0c06ddfb6e0646"
] | [
"bvbq/interface.py"
] | [
"# -*- coding: utf-8 -*-\n# pylint: disable=E1101\n\"\"\"\n Deprecated. Use named_interface.BVBQMixMVN.\n Won't be documented due to this\n\"\"\"\nimport torch\n\nfrom . import utils\nfrom . import bvbq\nfrom . import distributions\nfrom . import gp\nfrom . import acquisition\nfrom . import metrics\n\n\nclass... | [
[
"torch.ones",
"torch.vstack"
]
] |
YoNyeoSeok/refinenet-pytorch | [
"34dfa49a141630247aef1d5d2424c823ecba46c7"
] | [
"train/training.py"
] | [
"import sys\nsys.path.append('/home/user/research/refinenet-pytorch')\nimport os\nimport numpy as np\nimport tqdm\nimport argparse\nimport math\nimport random\nfrom PIL import Image\n\nimport torch\nimport torch.nn as nn\nimport datasets as ds\nfrom torchvision import transforms as trf\nfrom models.refinenet_resnet... | [
[
"torch.utils.data.DataLoader",
"numpy.vectorize",
"torch.no_grad",
"torch.nn.CrossEntropyLoss",
"torch.from_numpy",
"numpy.array",
"torch.nn.functional.interpolate"
]
] |
alexanderkell/temporal_granularity | [
"f29b294beb360d8d66c6fedf78bbf9ae84055b24"
] | [
"test/test_metrics/test_multi_year_metrics.py"
] | [
"from pathlib import Path\nimport pandas as pd\nfrom src.metrics.multi_year_metrics import MultiYearMetrics\nimport pytest\nimport logging\n\nlogging.basicConfig(level=logging.DEBUG)\nlogger = logging.getLogger(__name__)\n\nproject_dir = Path(\"__file__\").resolve().parents[1]\n\n\n@pytest.fixture\ndef define_multi... | [
[
"pandas.to_datetime"
]
] |
Frognar/Super-Resolution | [
"406b909d71e156aa11ee589698744e3ad9abfee7"
] | [
"nn/block/upsample_blocks.py"
] | [
"import torch.nn as nn\nfrom torch.nn.functional import interpolate\n\n\nclass PixelShuffleUpscaleBlock(nn.Module):\n def __init__(self, in_channels=64, kernel_size=3, upscale_factor=2):\n super().__init__()\n\n self.block = nn.Sequential(\n nn.Conv2d(in_channels=in_channels,\n ... | [
[
"torch.nn.PixelShuffle",
"torch.nn.PReLU",
"torch.nn.Conv2d",
"torch.nn.functional.interpolate",
"torch.nn.LeakyReLU"
]
] |
TannerGilbert/Machine-Learning-Explained | [
"5309f44a38ce862f3f177e8d5de2e60eea44637b"
] | [
"Optimizers/adam/code/adam.py"
] | [
"# based on https://ruder.io/optimizing-gradient-descent/#adam\n# and https://github.com/eriklindernoren/ML-From-Scratch/blob/master/mlfromscratch/deep_learning/optimizers.py#L106\n\nimport numpy as np\n\n\nclass Adam:\n \"\"\"Adam - Adaptive Moment Estimation\n Parameters:\n -----------\n learning_rate... | [
[
"numpy.sqrt",
"numpy.power",
"numpy.shape"
]
] |
mustelideos/td-opswtw-competition-rl | [
"afbd6603b74f09c133d5d68e587fc93387ca93ba"
] | [
"models/neural_net.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.init as init\nimport torch.nn.functional as F\nfrom torch.utils.checkpoint import checkpoint\n\nimport math\nimport numpy as np\n\n# ------------------------------------------------------------------------------\n# Transformer model from: https://github.com/JayP... | [
[
"torch.ones",
"torch.FloatTensor",
"torch.nn.Linear",
"torch.load",
"torch.nn.Dropout",
"torch.split",
"torch.utils.checkpoint.checkpoint",
"torch.nn.init.xavier_uniform_",
"torch.nn.Softmax",
"torch.nn.functional.softmax",
"torch.zeros",
"torch.nn.LSTMCell",
"t... |
michelebucelli/cardioemulator | [
"0ce8d5fce017a7251865ab01fdf3d0653490b60f"
] | [
"example/circulation_closed_loop.py"
] | [
"import numpy as np\nimport pandas as pd\nimport json\nimport csv\nimport time\nfrom scipy.integrate import RK45, solve_ivp\n\nclass circulation_closed_loop:\n \"\"\"\n Closed loop circulation model.\n\n References\n ----------\n F. Regazzoni, M. Salvador, P. C. Africa, M. Fedele, L. Dede', A. Quarte... | [
[
"numpy.arctan",
"pandas.DataFrame",
"numpy.mod",
"numpy.arange",
"numpy.log10",
"numpy.round"
]
] |
kim95175/detr | [
"342947185153e1f599b47da423a0c49329bbe055"
] | [
"main.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport argparse\nimport datetime\nimport json\nimport random\nimport time\nfrom pathlib import Path\n\nimport numpy as np\nimport torch\nfrom torch.utils.data import DataLoader, DistributedSampler\n\nimport datasets\nimport util.misc as utils\... | [
[
"torch.utils.data.DataLoader",
"torch.hub.load_state_dict_from_url",
"torch.load",
"torch.utils.data.BatchSampler",
"torch.manual_seed",
"torch.utils.data.DistributedSampler",
"numpy.random.seed",
"torch.utils.data.SequentialSampler",
"torch.nn.parallel.DistributedDataParallel"... |
oguzhangur96/automl-benchmark | [
"785b4d762164dd251b7c5e63131579113c2dc2c2"
] | [
"autogluon/taxi_trip_duration.py"
] | [
"# %% [markdown]\n# This is a simple notebook for Autogluon AutoMl prediction.\n# MLflow used as tracking tool since experiments take long time complete\n# and it is hard to manage too many experiments.\n#%%\n# Importing necessary libraries\nimport os\nimport re\nimport random\nimport string\nimport math\nimport pa... | [
[
"numpy.sqrt",
"pandas.read_pickle",
"sklearn.model_selection.train_test_split",
"sklearn.metrics.mean_squared_log_error"
]
] |
lebrice/continuum | [
"7fa9048361b5821b61fa8ec1ac535c2438329626"
] | [
"continuum/task_set.py"
] | [
"from typing import Tuple, Union\n\nimport numpy as np\nfrom PIL import Image\nfrom torch.utils.data import Dataset as TorchDataset\nfrom torchvision import transforms\n\nfrom continuum.viz import plot\n\n\nclass TaskSet(TorchDataset):\n \"\"\"A task dataset returned by the CLLoader.\n\n :param x: The data, e... | [
[
"numpy.random.RandomState",
"numpy.concatenate",
"numpy.unique"
]
] |
FerdinandEiteneuer/ReinforcementLearning | [
"15c75d7f984bd0a8a25b9df822113d8837aa4a93"
] | [
"utils/memory.py"
] | [
"\"\"\"\nMemory\n\"\"\"\nimport numpy as np\nimport os\n\nfrom utils import export\n\n\n@export\nclass NumpyArrayMemory:\n \"\"\"\n Datastructure for all the experiences (states, actions, rewards, next_states)\n the agent saw.\n \"\"\"\n def __init__(self, size, input_shape, nb_actions, data_dir):\n\... | [
[
"numpy.save",
"numpy.any",
"numpy.load",
"numpy.zeros"
]
] |
KEVINYZY/python-tutorial | [
"d0f7348e1da4ff954e3add66e1aae55d599283ee"
] | [
"17tensorflow/mnist/__init__.py"
] | [
"# -*- coding: utf-8 -*-\n# Author: XuMing <shibing624@126.com>\n# Data: 17/10/10\n# Brief: \nimport tensorflow as tf\nimport numpy as np\n\n# 使用 NumPy 生成假数据(phony data), 总共 100 个点.\nx_data = np.float32(np.random.rand(2, 100)) # 随机输入\ny_data = np.dot([0.100, 0.200], x_data) + 0.300\n\n# 构造一个线性模型\n#\nb = tf.Variable... | [
[
"tensorflow.zeros",
"tensorflow.global_variables_initializer",
"tensorflow.matmul",
"tensorflow.random_uniform",
"numpy.random.rand",
"tensorflow.train.GradientDescentOptimizer",
"tensorflow.Session",
"tensorflow.square",
"numpy.dot"
]
] |
joybhallaa/pandas | [
"1779155552631a30d4bb176dec70b8cc477defd7"
] | [
"pandas/core/internals/concat.py"
] | [
"from __future__ import annotations\n\nfrom collections import defaultdict\nimport copy\nimport itertools\nfrom typing import TYPE_CHECKING, Dict, List, Sequence, cast\n\nimport numpy as np\n\nfrom pandas._libs import internals as libinternals\nfrom pandas._typing import ArrayLike, DtypeObj, Manager, Shape\nfrom pa... | [
[
"pandas.core.dtypes.cast.ensure_dtype_can_hold_na",
"numpy.ones",
"numpy.find_common_type",
"numpy.diff",
"numpy.dtype",
"pandas.core.arrays.DatetimeArray",
"pandas.core.internals.managers.BlockManager",
"pandas.core.dtypes.common.is_float_dtype",
"pandas.core.internals.array_m... |
ankitshaw/DenGa | [
"92dfb0f3760c30dd9a32d650da92d5c3276099d1"
] | [
"denga/genda.py"
] | [
"\nimport denga.augment as au\nimport pandas as pd\n\nclass Genda():\n\n\tdef __init__(self,filepath): \n\t\tself.filepath = filepath\n\t\tself.dataset = None\n\t\ttry:\n\t\t\tself.dataset = pd.read_csv(self.filepath, header= None, error_bad_lines=False)\n\t\texcept:\n\t\t\traise Exception(\"ERROR: File Missing\")... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
ABernard27/PROJET-groupe-3 | [
"a9ab9d80c10724ded9e20751fda018a7ed05589b"
] | [
"Coberny/graph_min_cost/best_price_path.py"
] | [
"import pandas as pd\nimport networkx as nx\nfrom networkx.algorithms import dijkstra_path\nimport itertools\nimport time\nimport datetime as dt\n# import matplotlib.pyplot as plt\n\n\n# Retourne la liste de toutes les villes du dataframe\ndef GetListOfcolnames(data):\n listofColnames = list(data.columns)[1:]\n ... | [
[
"pandas.read_csv"
]
] |
sdementen/pandas | [
"e23e6f164209167c0fba0d32c862c5e75e6d4a8a"
] | [
"pandas/io/pytables.py"
] | [
"\"\"\"\nHigh level interface to PyTables for reading and writing pandas data structures\nto disk\n\"\"\"\n\n# pylint: disable-msg=E1101,W0613,W0603\nfrom datetime import datetime, date\nimport time\nimport re\nimport copy\nimport itertools\nimport warnings\nimport os\n\nfrom pandas.types.common import (is_list_lik... | [
[
"pandas.types.common.is_categorical_dtype",
"pandas.types.common._ensure_int64",
"pandas.Series",
"pandas.compat.iteritems",
"pandas.formats.printing.adjoin",
"pandas.core.algorithms.unique",
"pandas.compat.u_safe",
"numpy.asarray",
"pandas.tslib.get_timezone",
"pandas.io.c... |
BioinfoTongLI/deepBlink | [
"aa819b71f380507f9fcfa0664ab0f5a8eca4b209"
] | [
"tests/test_augment.py"
] | [
"\"\"\"Unittests for the deepblink.augment module.\"\"\"\n# pylint: disable=missing-function-docstring\n\nfrom hypothesis import given\nfrom hypothesis.extra.numpy import arrays\nimport numpy as np\nimport pytest\n\nfrom deepblink.augment import augment_batch_baseline\nfrom deepblink.augment import flip\nfrom deepb... | [
[
"numpy.sum",
"numpy.zeros"
]
] |
ethz-asl/data-driven-dynamics | [
"decf4bec19c9fc4a1789f5eb4d6e6003774c75d6"
] | [
"Tools/parametric_model/src/models/multirotor_model.py"
] | [
"\"\"\"\n *\n * Copyright (c) 2021 Manuel Yves Galliker\n * 2021 Autonomous Systems Lab ETH Zurich\n * All rights reserved.\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 * 1. Redistributi... | [
[
"numpy.diag"
]
] |
rhoposit/tacotron2 | [
"2dad8df5ea50459789e16d9effb83fc2a25e42ed"
] | [
"tacotron/models.py"
] | [
"# ==============================================================================\n# Copyright (c) 2018, Yamagishi Laboratory, National Institute of Informatics\n# Author: Yusuke Yasuda (yasuda@nii.ac.jp)\n# All rights reserved.\n# ==============================================================================\n\"\"... | [
[
"tensorflow.metrics.mean",
"tensorflow.summary.scalar",
"tensorflow.minimum",
"tensorflow.summary.merge_all",
"tensorflow.clip_by_global_norm",
"tensorflow.get_collection",
"tensorflow.to_float",
"tensorflow.train.AdamOptimizer",
"tensorflow.expand_dims",
"tensorflow.estima... |
ChristopherChudzicki/mitx-grading-library | [
"1d9a7107f26b5e0ebe24deb552cf943779693e18"
] | [
"mitxgraders/helpers/calc/mathfuncs.py"
] | [
"\"\"\"\nmathfuncs.py\n\nContains mathematical functions for use in interpreting formulas.\n\nContains some helper functions used in grading formulae:\n* within_tolerance\n\nDefines:\n* DEFAULT_FUNCTIONS\n* DEFAULT_VARIABLES\n* DEFAULT_SUFFIXES\n* METRIC_SUFFIXES\n\"\"\"\nfrom __future__ import print_function, divi... | [
[
"numpy.arctanh",
"scipy.special.gamma",
"numpy.tanh",
"numpy.transpose",
"numpy.arccosh",
"numpy.arcsinh",
"numpy.arccos",
"numpy.cos",
"numpy.complex",
"numpy.sinh",
"numpy.tan",
"numpy.linalg.norm",
"numpy.arctan2",
"numpy.cosh",
"numpy.arcsin",
"n... |
Moetaz-M-Mokhtar/ITIintake40_FaceRecognition | [
"570ceb5d1353efa8b8754243ee8d5db36a951998"
] | [
"detection/docker/model_handler_cpu.py"
] | [
"# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.\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# A copy of the License is located at\n# http://www.apache.org/licenses/LICENSE-2.0\n# or in the \"... | [
[
"numpy.round",
"numpy.max",
"numpy.min",
"numpy.frombuffer"
]
] |
zxc1342802/leijmtrader | [
"f24d5593d8708e48f2a9180d9469a6c2af93a08d"
] | [
"examples/strategies/king_keltner_strategy.py"
] | [
"from jiamtrader.app.cta_strategy import (\n CtaTemplate,\n StopOrder,\n TickData,\n BarData,\n TradeData,\n OrderData,\n BarGenerator,\n ArrayManager,\n)\n\nimport pandas_ta as ta\nimport pandas as pd\n\nclass KingKeltnerStrategy(CtaTemplate):\n \"\"\"\"\"\"\n\n author = \"用Python的交易员... | [
[
"pandas.Series"
]
] |
abhishekmaha23/synthetic_data_generation_attempt | [
"99ee858cdf405641fd0e2797bfc14c1a736547eb"
] | [
"util/utils.py"
] | [
"import matplotlib.pyplot as plt\nfrom datetime import datetime\nimport numpy as np\nimport torch\nimport os\nimport time\nfrom scipy.ndimage.filters import gaussian_filter1d\nfrom itertools import repeat\nimport copy\nimport gym\n# import torch.multiprocessing as multiprocessing\nimport multiprocessing\nimport pic... | [
[
"torch.no_grad",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.plot",
"scipy.ndimage.filters.gaussian_filter1d",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"matplotlib.use",
"... |
ngbsLab/Korean-Speech-Recognition | [
"3867bf7d23222da6812c9b98a93d3c6f7b3c80fc"
] | [
"package/loss.py"
] | [
"import torch\nimport torch.nn as nn\n\nclass LabelSmoothingLoss(nn.Module):\n \"\"\"\n Provides Label-Smoothing loss.\n\n Args:\n class_num (int): the number of classfication\n ignore_index (int): Indexes that are ignored when calculating loss\n smoothing (float): ratio of smoothing (... | [
[
"torch.sum",
"torch.zeros_like",
"torch.no_grad"
]
] |
bhevencious/EvalNE | [
"a62bd11901ea891535f6cb2a05e7abb65b1f3e6f"
] | [
"evalne/evaluation/pipeline.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# Author: Mara Alexandru Cristian\n# Contact: alexandru.mara@ugent.be\n# Date: 18/12/2018\n\n# The manager module contains functions and classes for reading, parsing and using a configuration file to\n# run a complete evaluation of network embedding methods.\n\nfrom ... | [
[
"sklearn.tree.DecisionTreeClassifier",
"sklearn.linear_model.LogisticRegressionCV",
"sklearn.svm.LinearSVC",
"sklearn.linear_model.LogisticRegression"
]
] |
GiovanniCalore/BigGAN-Tensorflow-master | [
"1fcf72fc8b9cbfdd047b9641f656afcfd0972604"
] | [
"metrics/perceptual_path_length.py"
] | [
"# Copyright (c) 2019, NVIDIA Corporation. All rights reserved.\n#\n# This work is made available under the Nvidia Source Code License-NC.\n# To view a copy of this license, visit\n# https://nvlabs.github.io/stylegan2/license.html\n\n\"\"\"Perceptual Path Length (PPL).\"\"\"\n\nimport numpy as np\nimport tensorflow... | [
[
"tensorflow.math.acos",
"numpy.logical_and",
"tensorflow.device",
"tensorflow.math.cos",
"tensorflow.math.sin",
"tensorflow.square",
"numpy.concatenate",
"tensorflow.transpose",
"tensorflow.reduce_sum",
"numpy.percentile",
"numpy.mean"
]
] |
rupei/probability | [
"4aa1ee652853a19c4e80d39216c3fa535ed3e589"
] | [
"tensorflow_probability/python/internal/backend/numpy/numpy_array.py"
] | [
"# Copyright 2018 The TensorFlow Probability Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by a... | [
[
"numpy.sum",
"numpy.take",
"numpy.issubdtype",
"numpy.moveaxis",
"numpy.ndindex",
"numpy.transpose",
"numpy.reshape",
"numpy.expand_dims",
"numpy.where",
"numpy.linspace",
"numpy.repeat",
"numpy.arange",
"numpy.roll",
"numpy.squeeze",
"numpy.conjugate",
... |
foobug/suzieq | [
"c5927616a0e1a1fd9283f2a3eeb120d24ff0f2b5"
] | [
"suzieq/poller/services/evpnVni.py"
] | [
"import re\nimport numpy as np\n\nfrom suzieq.poller.services.service import Service\nfrom suzieq.utils import (convert_rangestring_to_list,\n convert_macaddr_format_to_colon)\n\n\nclass EvpnVniService(Service):\n \"\"\"evpnVni service. Different class because output needs to be munged\"... | [
[
"numpy.delete"
]
] |
PriyankaH21/astropy | [
"159fb9637ce4acdc60329d20517ed3dc7ba79581"
] | [
"astropy/nddata/tests/test_utils.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\n\nimport pytest\nimport numpy as np\nfrom numpy.testing import assert_allclose\n\nfrom ...tests.helper import assert_quantity_allclose\nfrom ..utils import (extract_array, add_array, subpixel_indices,\n block_reduce, block_replica... | [
[
"numpy.ones",
"numpy.zeros",
"numpy.cos",
"numpy.copy",
"numpy.arange",
"numpy.all",
"numpy.isnan",
"numpy.array",
"numpy.sin",
"numpy.testing.assert_allclose"
]
] |
mateussangalli/SE2DINNets | [
"c4d9b6d2577a5044c243d0eb80ebe5879a7673c9"
] | [
"train_SE2DINNet.py"
] | [
"import tensorflow as tf\nimport numpy as np\nfrom tensorflow.keras import layers, regularizers\nfrom tensorflow.keras.utils import to_categorical\nimport matplotlib.pyplot as plt\nimport os\nimport argparse\n\nfrom SE2DIN import *\n\n\nfrom load_data import load_data\n\n\nmnist_rot_dir = 'mnist_rot'\nmnist_12k_dir... | [
[
"tensorflow.keras.models.Sequential",
"tensorflow.keras.optimizers.Adam",
"tensorflow.keras.layers.Dropout",
"tensorflow.keras.losses.SparseCategoricalCrossentropy",
"tensorflow.keras.layers.ReLU",
"tensorflow.keras.regularizers.l2",
"tensorflow.keras.layers.GlobalMaxPooling2D",
"t... |
Ayon134/code_for_Kids | [
"d90698bb38efe5e26c31f02bd129bfdadea158e2"
] | [
"lst.py"
] | [
"import cv2\nimport io\nfrom PIL import Image, ImageEnhance\nimport pytesseract\nfrom wand.image import Image as wi\nimport re\nimport pandas as pd\nfrom PyPDF2 import PdfFileWriter, PdfFileReader\nfrom pdf2image import convert_from_path\n\n\nclaim = '15232353'\nfile = \"a.pdf\"\npages_to_keep = [0]\ninfile = PdfFi... | [
[
"pandas.DataFrame"
]
] |
giangtranml/framgia-training | [
"c7fb343bd43b1bceb241b447ff956febb99c94a8"
] | [
"decision_tree/decision_tree.py"
] | [
"\"\"\"\nAuthor: Giang Tran.\n\"\"\"\n\nimport numpy as np\nfrom math import log2\n\n\nclass NodeDT:\n \"\"\"\n Class Node represents in Decision Tree\n \"\"\"\n\n def __init__(self, X, y, feature_name):\n self.feature_name = feature_name\n self.X = X\n self.y = y\n self.is_l... | [
[
"pandas.read_csv",
"sklearn.tree.DecisionTreeClassifier",
"numpy.logical_and",
"numpy.asarray",
"numpy.unique"
]
] |
mnemocron/TelegramChatStats | [
"10b9ebb97bfb28f835fd05050f03dcb10525f7a3"
] | [
"telegram-statistics.py"
] | [
"#! /usr/bin/python3\n\n#_*_ coding: utf-8 _*_\n\n'''\n@file \t\ttelegram-statistics.py\n@author \tSimon Burkhardt - github.com/mnemocron\n@date \t\t2018.10.01\n\nPost about this code:\nhttps://www.reddit.com/r/LongDistance/comments/9mgcol/oc_chat_statistics_from_telegram_using_python/\n\nInspiration:\nhttps://www.... | [
[
"pandas.DataFrame.from_dict"
]
] |
bentzinir/ray | [
"39b84166f88e271b279bd0b3ce56f81d24a1852c"
] | [
"rllib/agents/sac/sac_ensemble_tf_model_unstack.py"
] | [
"from gym.spaces import MultiDiscrete\nimport numpy as np\n\nfrom ray.rllib.models.tf.tf_modelv2 import TFModelV2\nfrom ray.rllib.utils.framework import try_import_tf\n\ntf = try_import_tf()\n\n\nclass SACEnsembleTFModel(TFModelV2):\n \"\"\"Extension of standard TFModel for SAC.\n\n Data flow:\n obs ->... | [
[
"numpy.log",
"numpy.expand_dims",
"numpy.product",
"numpy.prod"
]
] |
TamasFlorin/YOLO3-4-Py | [
"d7cc4d67c7eb9168a30ce9716ed64024fc1e1f8f"
] | [
"setup.py"
] | [
"import tempfile\nfrom distutils.command.build import build\nfrom distutils.command.clean import clean\nimport sys\nimport numpy as np # TODO: Need a mechanism to ensure numpy is already installed\nimport shutil\n\n# Compile using .cpp files if cython is not present\ntry:\n from Cython.Distutils import build_ext... | [
[
"numpy.get_include"
]
] |
sheepolata/GraphEngine | [
"853447e42dcd09154cdc5ac0b8e00c493445a389"
] | [
"ggraph.py"
] | [
"# import the pygame module, so you can use it\nimport pygame\nfrom pygame.locals import *\nimport warnings\nimport random\nimport numpy as np\nimport math\nfrom scipy.spatial import Delaunay\n\nimport delaunaytriangulation as dt\nimport graphmodel as gm\nimport drawer\nimport utils\n\nclass gNode(gm.Node):\n\n ... | [
[
"numpy.array"
]
] |
inesnolas/Rank-based-loss_ICASSP22 | [
"3ebe7345dc26b8fa74543725a51b43b7170c58cc"
] | [
"run_example.py"
] | [
"import models.SingleLayer_net as single_layer\nimport loss_functions.rank_based_loss as rbl\n# import wandb\nimport torch\nimport utils.data_functions as df\nimport os\nimport json\nimport pandas as pd\nimport csv\n\n\nos.environ['CUDA_VISIBLE_DEVICES'] = '3'\n# wandb.init(project='example')\n\nexp_name = 'example... | [
[
"torch.utils.data.DataLoader",
"torch.load"
]
] |
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