sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
983e143ed44a6aa5029e225bcb094844b8f89debfb79fbe6d31fcb3759e5e4de | Python | 8,513 | 339 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 27 17:13:07 2020
@author: baris
"""
gra_spikes = gra_spikes_diff[0]
f=10
n_phase_bins=360
dur_ms=2000
dur_s = dur_ms/1000
T = 1/f
time_bin_size = T
times = np.arange(0, dur_s+time_bin_size, time_bin_size)
n_time_bins = int(dur_s/T)
def mean_phase(... |
b6a0f59322da82d5d456ffe7da1cbaf31c47dbef402f36d1fa94214d63357865 | Python | 8,514 | 218 | """Callback classes to control training."""
import logging
import numpy as np
# to ignore imports for sphix-autoapidoc
__all__ = ['BaseCallback', 'EarlyStopping', 'AnnealHparam', 'PseudoLabels']
class BaseCallback(object):
"""Abstract base class for callbacks."""
def on_epoch_end(self, data_generator, mode... |
69517097e6fcfdaeec968021c74f167d9e5a764b443b8f4484d892f2bbd82119 | Python | 8,515 | 218 | """Callback classes to control training."""
import logging
import numpy as np
# to ignore imports for sphix-autoapidoc
__all__ = ['BaseCallback', 'EarlyStopping', 'AnnealHparam', 'PseudoLabels', 'UPS']
class BaseCallback(object):
"""Abstract base class for callbacks."""
def on_epoch_end(self, data_generato... |
41e670aca8e493b1937bfb29c274fe5a5fe209adebc9306daff081fb273fb486 | Python | 8,516 | 254 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import os.path as osp
import warnings
import numpy as np
import onnx
import torch
from mmcv import Config
from mmcv.tensorrt import is_tensorrt_plugin_loaded, onnx2trt, save_trt_engine
from mmdet.core.export import preprocess_example_input
from... |
854a8cf67924bd7da038d93388cce9e3a03b7033c12d01734ec8da0c28cac6c4 | Python | 8,517 | 254 | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
def bbox_flip(bboxes, img_shape, direction='horizontal'):
"""Flip bboxes horizontally or vertically.
Args:
bboxes (Tensor): Shape (..., 4*k)
img_shape (tuple): Image shape.
direction (str): Flip direction,... |
3a8a7ce0f8bbe6a4c07994141ed578a81a97913da23aba10768a101248d84254 | Python | 8,527 | 193 | """General-purpose test script for image-to-image translation.
Once you have trained your model with train.py, you can use this script to test the model.
It will load a saved model from --checkpoints_dir and save the results to --results_dir.
It first creates model and dataset given the option. It will hard-code some... |
369e31e62f61576a147bc09936db1d5ec46e47b8a8fd0c94358f7fdb5c186c3f | Python | 8,529 | 211 | import matplotlib.pyplot as plt
import numpy as np
import grid_model
import matplotlib.gridspec as gridspec
import matplotlib as mpl
import shelve
import os
from neural_coding import _code_maker, load_spikes, rate_n_phase
import math
from perceptron import run_perceptron
dir_name = os.path.dirname(__file__) # Name of... |
be95d9fe523085d15f008ef7eede94d9409455e1d760962792c1db7961e893c8 | Python | 8,531 | 227 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import warnings
from typing import Dict, Union
import numpy as np
from mmcv import Config, is_seq_of
from mmpose.core.post_processing.temporal_filters import build_filter
class Smoother():
"""Smoother to apply temporal smoothing on pose estimation resu... |
ab69919cc03f60751826176e0bdc37d73bec8039835cb060094b4a34fe74bc4b | Python | 8,535 | 242 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
# code for MMD from:
# https://github.com/mackelab/labproject/blob/main/labproject/metrics/MMD_torch.py
import warnings
from typing import Optional
impo... |
cc6b8a7a9b7a8639b4999f395770b3f13f68cf8d4bdbe7734de5c49130cf4daa | Python | 8,542 | 205 | from __future__ import annotations
import re
from .consts import CUTOFFS, BCONDS
from .tfspline import Bcond
from typing import ItemsView, ValuesView, KeysView, Union, Iterable
from .util import formatZ, padZ, Z2A
import numpy as np
import pickle as pkl
# TODO: support various types of models (current version only... |
83e873f6b942ba4065daf4bd81d909ce83a0dad1cf335078e837b2a4c5f18783 | Python | 8,556 | 221 | import importlib
import os
import logging
from pathlib import Path
from functools import reduce, partial
from operator import getitem
from datetime import datetime
import stringcase
from data_loader.my_transforms.compose import Compose
from logger import setup_logging
from utils import read_json, write_json
class C... |
d28ac4b50d921c26e09a17c6c49faf729d62b047ef9b1db0de4aeda1153b857d | Python | 8,560 | 256 |
from neural_coding import load_spikes, rate_n_phase
from perceptron_new import run_perceptron
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from sklearn import decomposition
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
import pickle
import c... |
2520d5746f4b55f1d9f79f41e877f87a5f9c04f7ef042daa1afaab84829ff8e6 | Python | 8,580 | 240 | import shutil
import sys
from genomad import database, mmseqs2, prodigal, sequence, taxonomy, utils
from genomad._paths import GenomadOutputs
def write_genes_output(genes_output, database_obj, prodigal_obj, mmseqs2_obj):
marker_annotation_dict = database_obj.get_marker_annotation()
gene_match_dict = mmseqs2_... |
d1d0b3b1e331a5445332c5d5b7a33bdec604219f35af9d15bdabb2a53478e658 | Python | 8,584 | 189 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
from typing import Dict, Optional, Union
import torch
from torch import Tensor, nn, ones
from torch.distributions import Distribution
from torch.utils.te... |
421b67e9edbafce62e1a16fca20a44315c6ae3512432947e809b5a30a6deefc6 | Python | 8,585 | 197 | """General-purpose test script for image-to-image translation.
Once you have trained your model with train.py, you can use this script to test the model.
It will load a saved model from --checkpoints_dir and save the results to --results_dir.
It first creates model and dataset given the option. It will hard-code some... |
fa0d696123a90b5be4c49b8207dc115ef8ada5609687fb30a66116ff8057deb0 | Python | 8,585 | 201 | import logging
from pprint import pprint
import torch
from pybrid import utils, datasets, optim
from pybrid.models.hybrid import HybridModel
def setup(cfg):
cfg = utils.setup_experiment(cfg)
datasets.download_mnist()
train_dataset_1 = datasets.MNIST(
train=True,
scale=cfg.data.label_scale... |
ed74b8d4390753d1e97f15087d7156b0afef03fdef381995471147708f746b93 | Python | 8,590 | 252 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import unittest.mock as mock
from collections import OrderedDict
from unittest.mock import MagicMock, patch
import pytest
import torch
import torch.nn as nn
from mmcv.runner import EpochBasedRunner, build_optimizer
from mmcv.utils im... |
4837fbee8a80507a647f9c84ab3668fc56c64727320d0baa1691230dac5f84af | Python | 8,591 | 204 | import numpy as np
from tdt import StructType
import pandas as pd
import sys
from copy import deepcopy
import os
def find_options_FED3(inputs):
# Create a list of system variables to exclude from possible TTLMs.
TTLM_exclude = ['PC0_','PC1_','PC2_','PC3_','PC0/','PC1/','PC2/','PC3/',
... |
dbd8eda5aaa81daf8fea3161c4b233a1951ec66f4db6c8c8bf7c13713f92699c | Python | 8,601 | 266 | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmpose.models.detectors import CID, AssociativeEmbedding
def test_ae_forward():
model_cfg = dict(
type='AssociativeEmbedding',
pretrained=None,
backbone=dict(type='ResNet', depth=18),
... |
e9d6bfb76ede7ea4cec3b8f73f139e97b291c0515c5f8fe29730f0dba244a503 | Python | 8,602 | 273 | """Evaluation functions for the daart package."""
import itertools
import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
import seaborn as sns
from sklearn.metrics import recall_score, precision_score
from typeguard import typechecked
from typing import List, Optional, Union
from daart.io i... |
289371c72ecebdff181125f730027e5061848bdd1418212de468b8069f27d9a5 | Python | 8,622 | 256 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os.path as osp
import pickle
from abc import ABCMeta, abstractmethod
import json_tricks as json
import numpy as np
from scipy.io import loadmat
from torch.utils.data import Dataset
from mmpose.datasets import DatasetInfo
from mmpose.datasets.pipelines... |
56f55c5c9ca5dc47301b17eed40c846a0a36c33ddb8b3a51ae0598f03ecee759 | Python | 8,625 | 206 | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch
from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class TBLRBBoxCoder(BaseBBoxCoder):
"""TBLR BBox coder.
Following the practice in `FSAF <https://arxiv.org/abs/1903.00621>`_,
... |
b6f4bebd2b4ea6f47343ce5125ebe93f70c6303aaebd0db8de9af1340591cd68 | Python | 8,630 | 226 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
from __future__ import annotations
from typing import Optional, Tuple, Union
import torch
from torch import Tensor, nn
from torch.distributions import D... |
8b8dc87b356961b02835565df81b94501bf5f94aef2e706f6ad08a4472b618b9 | Python | 8,631 | 212 | # Copyright (c) OpenMMLab. All rights reserved.
# Copyright (c) 2018, Alexander Kirillov
# This file supports `file_client` for `panopticapi`,
# the source code is copied from `panopticapi`,
# only the way to load the gt images is modified.
import multiprocessing
import os
import mmcv
import numpy as np
try:
fro... |
b88831ea8c3c9b6991ae26d13369cb89ba5819e075c9d1cc1f7e581c58db41aa | Python | 8,633 | 280 | # -*- coding: utf-8 -*-
"""
Created on Tue Mar 1 13:33:57 2022
@author: oliver braganza
"""
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from brian2 import (
NeuronGroup,
Synapses,
SpikeGeneratorGroup,
SpikeMonitor,
StateMonitor,
Network,
start_scope,
col... |
75a1a5b8cd19aa785cd1e5a2c92be3762652bec996858f05937c463893fe4073 | Python | 8,651 | 257 | import logging
import torch
from pybrid import utils
from pybrid.models.base import BaseModel
from pybrid.layers import FCLayer
class HybridModel(BaseModel):
def __init__(
self,
nodes,
amort_nodes,
act_fn,
mu_dt=0.01,
use_bias=False,
kaiming_init=False,
... |
1adc538298ff2c684bfd15bd27eeb1fca1bea8392f1c1665fa8007e70dc69d65 | Python | 8,658 | 211 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
import warnings
from typing import Any, ClassVar, Dict, Literal, Optional, Union
from torch.distributions import Distribution
from torch.utils.tensorboa... |
ce97e1623c4c49de1c77ecd8b4c59efcdd10402449894e45cf582e415c31dfd6 | Python | 8,664 | 247 |
#bamToGFF.py
#script to grab reads from a bam that align to a .gff file
import sys
import re
import ROSE_utils
from collections import defaultdict
import os
from string import join,upper,maketrans
#=====================================================================
#====================MAPPING BAM READS TO ... |
993a763bff520c3ff724b1b74c9b3da220f18d2d08cf65bfcf5678ca4bf35c68 | Python | 8,671 | 203 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule, auto_fp16
from ..builder import NECKS
@NECKS.register_module()
class FPN(BaseModule):
r"""Feature Pyramid Network.
This is an implementati... |
aa35d0705bd5b423b75b508869bfbf6fc51b71b7820a78b3e7b064f1991bbbe7 | Python | 8,674 | 233 | # Marcus Andersson - Percolator Project
# Script that tests the performances of percolator
# Parameters: input-data, number of runs, list of process-IDs, flags
# psutil is imported in the case that the script should wait for other integration-test scripts to finish.
# Note: Relies on the output generated by the C++ so... |
d9766013a1f601dcca68e728c148ce4423922b6345f9d08a844ee9b5833ac243 | Python | 8,676 | 264 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 25 10:21:07 2021
@author: baris
"""
from neural_coding import load_spikes, rate_n_phase
from perceptron_new import run_perceptron
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from sklearn import decom... |
72f6ae53177afaa123d31352efe3b0c1681c30a253f9561eb2ff0ee0f56e21c0 | Python | 8,679 | 218 | # coding=utf-8
# Copyright 2023 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
a1e6ba6f2f9462e79e3203081fb005bd77c207ed20d0b72b6ec923635a16db50 | Python | 8,679 | 281 | import numpy as np
from cell import *
from neuron import h
from commonutils import *
import pdb
import struct
import os
import sys
h.Random().Random123_globalindex(1234)
h.load_file('stdgui.hoc')
pc = h.ParallelContext()
# set number of threads
pc.nthread(1, 0)
def save_and_update_weights(network_list, batch_... |
b7c11a2f9a2a9bbdfa67c0ce9f498e582ebac7f85757d6b7d458e1d49d7926e0 | Python | 8,694 | 241 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet.models import Accuracy, build_loss
def test_ce_loss():
# use_mask and use_sigmoid cannot be true at the same time
with pytest.raises(AssertionError):
loss_cfg = dict(
type='CrossEntropyLoss',
... |
c6ce77e66bba0f2a21fa0394c2b0e115ea35f7e13df806f1f4b16d2754a093e9 | Python | 8,698 | 244 | """
Created on Tue Mar 1 13:33:57 2022
@author: oliver braganza
"""
import pandas as pd
import os
import shelve
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import pickle
from datetime import datetime
#from S12_simulate_ca3_fac_case import get_synapses
mpl.rcParams['pdf.fonttype'] = ... |
a656a9811fb7b20f88f0454a4c0cfc974bb0a865cd4a27bd9c9ce1707bdf83bb | Python | 8,701 | 251 | # Copyright (c) OpenMMLab. All rights reserved.
import json
import os
import os.path as osp
import tarfile
from argparse import ArgumentParser
from glob import glob
from urllib.request import urlretrieve
import cv2
import mmcv
import numpy as np
import torch
from mmcv import Config
from mmcv.parallel import collate, s... |
b386a4d7ee0f269d0a1de3807f074f709fcac6117445d2591c3e9e14f72841bc | Python | 8,702 | 215 | from typing import Any
import torch
import torch.nn as nn
import numpy as np
import time
from sep.Mic_Array import Mic_Array
import sep.helpers.utils as utils
from sep.training.base_network import BaseNetwork
from sep.training.SpeakerLocalization.network import unnormalize_input, normalize_input
def roll_by_gather(ma... |
e5f00fda225a23af2f455fffa54b3df5e397c2502ec11c8951864d101c1ec68b | Python | 8,704 | 280 | import torch
import torch.nn as nn
class SEBlock(nn.Module):
def __init__(self, in_channels, out_channels, net_mode='2d'):
super(SEBlock, self).__init__()
if net_mode == '2d':
self.gap = nn.AdaptiveAvgPool2d(1)
conv = nn.Conv2d
elif net_mode == '3d':
se... |
5da95b5b72553e73a5e61ae68bffcbf6dd855fad6a36834258e6db55c73a54af | Python | 8,726 | 251 | import copy
import numpy as np
import os
import pytest
import torch
from daart.data import split_trials, compute_sequences, compute_sequence_pad, DataGenerator
from daart.utils import build_data_generator
def test_split_trials():
# return correct number of trials 1
splits = split_trials(100, 0, 8, 1, 1, 0)
... |
212a9adc62682b69ed3fa75f84fb3e1de0b06dc928cbea26716a335adcf0cca8 | Python | 8,732 | 270 | import numpy as np
import scipy as sp
import trefide.extras.tools as tools_
# cython
def kurto_one(x):
"""
Computer kurtosis of rows of x with 2D (d x T)
Outputs: idx of components with kurtosis > population mean + std
"""
# Compute kurtosis
kurt = sp.stats.kurtosis(x, axis=1, fisher=True, b... |
7970a6ebd6a9434c43b00ac7d5859b57dd2148f74100946bb3f3f6d5da312d6e | Python | 8,743 | 241 | #### ADAPTED FROM https://github.com/githubharald/CTCDecoder/blob/master/src/BeamSearch.py
from __future__ import division
from __future__ import print_function
import numpy as np
import pathlib
from .lm import LanguageModel
from operator import itemgetter
class BeamEntry:
"information about one single beam at sp... |
a7291be4aee8f35fdbab34ce8a3f7be3197f237247d1f816390cdcdf6d25805f | Python | 8,748 | 246 | # adapted from https://github.com/Oafish1/WR2MD/blob/main/mmd_wrapper/algs/source/maninetcluster/alignment.py
# Align data sets
import numpy as np
import scipy as sp
from scipy.sparse.linalg import eigs, eigsh
from .maninetcluster.util import pairwise_error, block_antidiag
from .maninetcluster.neighborhood import neig... |
82d96f1fd3adc996925f46fbb990e8739d32c7571b2c82c3a582e9b2d4bda46a | Python | 8,750 | 210 | from typing import Optional, Type
import jax
import jax.numpy as jnp
import numpy as np
from functools import partial, cache
import utils
from flax import linen as nn
import transformer_flax as transformer
from transformer_flax import translate_config
from einshape import jax_einshape as einshape
import jax.tree_util a... |
9233a3d8b5dda409097e372f8602e0fc871be64bf94914dc6f90ab0fc458358c | Python | 8,756 | 205 | #!/usr/bin/env python
from __future__ import division
from __future__ import print_function
import sys
import argparse
import vcf
FORMAT_FIELDS = ["GT", "AD", "DP"]
FORMAT = ":".join(FORMAT_FIELDS)
CALL_DATA_FORMAT = vcf.model.make_calldata_tuple(FORMAT_FIELDS)
def melt_somatic_vcf(in_vcf_path, remove_filtered, tu... |
2f9e78edd3ce8daee8cc327164a715a77875f02cc766c8ba607e6096f87f6478 | Python | 8,764 | 222 | import numpy as np
import os
import pickle
import json
import pandas as pd
import matplotlib.pyplot as plt
os.chdir('/home/mathilde.lapoix/PycharmProjects/SCAPE/')
import utils.import_data as load
# %% Initialise
def fix_lustre_name(df):
return df.replace('iss01', 'iss02', regex=True)
def fix_lustre_name_Exp... |
9b561ec4bc9e909d40c724c7277cb56cd90a2d8d1c9cf3c7795d34ba882947e2 | Python | 8,765 | 246 | '''
ResNet for CIFAR-10/100 Dataset.
Reference:
1. https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py
2. https://github.com/facebook/fb.resnet.torch/blob/master/models/resnet.lua
3. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Deep Residual Learning for Image Recognition. https://arxiv.org... |
e249c4f24299d985774b029f071974385e08e1fe3621fc8619dbeca5c5b8b302 | Python | 8,766 | 188 | # -*- coding: utf-8 -*-
"""
Created on Mon Jun 7 19:00:06 2021
@author: fhu14
"""
#%% Imports, definitions
from MasterConstants import Model, RawData
from typing import List, Dict
import numpy as np
Array = np.ndarray
from Spline import SplineModel, get_dftb_vals, fit_linear_model
import torch
Tensor = torch.Tensor
i... |
6353c8ff96d65cdac7b05a18913874f3747e91bc934938659f5f0bb77eaf0271 | Python | 8,767 | 198 | import torch as th
import torch.nn as nn
from latentvelo.dataloader import Dataset
from latentvelo.utils import normalize, sparse_mx_to_torch_sparse_tensor
import os
import numpy as np
import matplotlib.pyplot as plt
from latentvelo.utils import batch_func
# setup adjacency matrix
def set_adj(adata):
import scipy ... |
d733de8b29e761ee7b44eb18cc7e820f48e32cb2205bfaa74946a8a59c9762e1 | Python | 8,772 | 262 | import json
import os
from collections import OrderedDict
from itertools import repeat
from pathlib import Path
import numpy as np
import pandas as pd
import re
from functools import singledispatch
import scipy
from scipy.ndimage.filters import gaussian_filter
from types import SimpleNamespace
from scipy.ndimage impo... |
e57d9490664f950ac16fb5628c50a6e292ca5f0eb5d1bfa5659912a2f8477b97 | Python | 8,778 | 193 | #!/usr/bin/env python3
"""
svaba_cloud_serve.py -- tiny local backend for docs/svaba_cloud_launcher.html.
Serves the launcher and a few JSON endpoints that shell out to your *existing*
gcloud/gsutil auth, turning the static page into a live dashboard:
GET / -> the launcher (token injected so it... |
15ddc8b61791c1811fe4f74c093442c7b51beca96a5da2caa9c3a3540d2ba0f0 | Python | 8,784 | 221 | """Compute statistical analysis from autocorrelation metrics.
"""
import json
import numpy as np
import matplotlib.pyplot as plt
import os
from scipy.optimize import curve_fit
import scipy.stats
def analyze_autocorrelation():
# First, load relevant data
AUTOCORR_RESULTFOLDER = '../results/intermediate/fig6'
... |
0abc18890789762921fd2443752e3cb9017ea797366c973d38a27e4821598922 | Python | 8,787 | 295 | '''Some helper functions for PyTorch, including:
- get_mean_and_std: calculate the mean and std value of dataset.
- msr_init: net parameter initialization.
- progress_bar: progress bar mimic xlua.progress.
'''
import os
import sys
import time
import math
import torch
import torch.nn as nn
import torch.nn.i... |
9c927b1d97fb43d75d3e1250bb3f800c307b278d43614a780c274368ad4491a9 | Python | 8,792 | 207 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, xavier_init
from mmcv.runner import auto_fp16
from ..builder import NECKS
@NECKS.register_module()
class FPN(nn.Module):
r"""Feature Pyramid Network.
This is an implementati... |
ecc8f9559938bd1edc2a33376c64329340d503ed3935e18555b3e814e548515f | Python | 8,796 | 254 | import math
import numpy as np
class Point:
"""Simple class for representing points in a uniform, image (row, col) manner"""
def __init__(self, row, col):
self.row = int(row)
self.col = int(col)
def __eq__(self, other):
if isinstance(other, Point):
return self.row == ... |
57f93b017aefd35a2c6e64d758f2759d298719827f67520e35d610f36cd87829 | Python | 8,800 | 235 | import torch
from torch.nn.functional import multi_head_attention_forward
import torch.testing as testing
from selbstaufsicht.modules import AxialSelfAttention2d, MultiHeadSelfAttention2d, TiedAxialSelfAttention2d
def test_MultiHeadAttention2d():
num_heads = 2
dim_head = 3
bs = 1
embed_dim = num_head... |
610b9c4d8f49043a91ac555f2e24be3397797d15509e47dd94747621c7590303 | Python | 8,803 | 208 | # training surv-based network with pretrained model
# Created: 5/21/2021
# Status: OK
# Consider merge into 1 main file
# CUBLAS_WORKSPACE_CONFIG=:4096:8 python transfer_main.py
# import torch.nn as nn
import sys
import torch
import numpy as np
import pandas as pd
sys.path.insert(1, '../plot/')
from networks import CN... |
2d758468f2b78ff62018c40737dcd09ead21b2483feb306b7049cf0fcfe44c68 | Python | 8,805 | 245 | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch
from mmdet.models.dense_heads import PISARetinaHead, PISASSDHead
from mmdet.models.roi_heads import PISARoIHead
def test_pisa_retinanet_head_loss():
"""Tests pisa retinanet head loss when truth is empty and non-empty."""
s = 256
img... |
3624d1ddae901ef748b3c7b2ffd8556c49d1615ac71694917ab37ea226f4efd2 | Python | 8,808 | 233 | # -*- coding: utf-8 -*-
"""
Created on Mon Jan 24 20:31:08 2022
@author: Daniel
"""
import sqlite3
import os
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from scipy.stats import ttest_rel, ttest_ind
import numpy as np
import scipy.optimize
from statsmodels.formula.api import ols
from stat... |
5e991a4a17ec1391ddaae79c772ed760ef1c5ef377e65b0007d1a05969dd042b | Python | 8,808 | 338 | import os
import pickle
import copy
import json
from collections import defaultdict
import numpy as np
import random
import torch
from rdkit import Chem
import networkx as nx
import imp
import h5py
from tqdm import tqdm
import hashlib
import torch as pt
from glob import glob
import pandas as pd
import ase.units as unit... |
795647d961f9e8970f1b46a06aa91db67130d92a2de5f2c6d3b8a3ba093423bc | Python | 8,814 | 217 | import numpy as np
from nengo.exceptions import ValidationError
from nengo.processes import Process
from nengo.params import (EnumParam, NdarrayParam, Parameter, TupleParam,
Unconfigurable)
from nengo.utils.compat import is_iterable, range
class ShapeParam(TupleParam):
"""A parameter wh... |
669d6400d3779ac990218638b1117d90c50296b71e5c7531f587c97eab70c7c2 | Python | 8,821 | 271 | ########
#
# This code generates a shorter version of figure 8A in Eyal et al 2017
# It simulates synchronous activation of synapses and the probability to spike as function of the number of activated synapses.
# Two cases are shown, the case of distributed activation and the case of clustered activation
# This is a sh... |
0913802af81a19890d2c855ea65e4e3d6c3f03a8f1ce93c17314be29649a0587 | Python | 8,832 | 258 | # -*- coding: utf-8 -*-
"""Residual block modules.
References:
- https://github.com/r9y9/wavenet_vocoder
- https://github.com/jik876/hifi-gan
"""
import math
import torch
import torch.nn.functional as F
from parallel_wavegan.layers.causal_conv import CausalConv1d
class Conv1d(torch.nn.Conv1d):
"""Co... |
44b65ae9eaeed4d4ef752d83109711d28f43e9a9dcd71d872288ddfc5d4155ad | Python | 8,836 | 259 | import sys
sys.path.append('..')
import os
import torch
import numpy as np
import torch.nn as nn
from torch.nn import functional as F
import data
import utils
import metrics
from main_bayesian import getModel as getBayesianModel
from main_frequentist import getModel as getFrequentistModel
import config_mixtures as cf... |
c130294daf5a62cb309988b358d5f83f2bc86be28ba8ffb5e17cf4b129906183 | Python | 8,844 | 227 | import logging
import torch.utils.data as data
import numpy as np
import h5py
import os
from skimage.transform import resize
from .data_utility import init_transform, count_samples, mr_normalization, merge_brain_mask_brats, merge_skull_brats
logging.basicConfig()
logger = logging.getLogger()
logger.setLevel(logging.... |
4118cb19aaa86aaeea2cf531955771097d0fc310f2713e9c06beffb19dec50e9 | Python | 8,849 | 255 | # Acquired from https://github.com/pytorch/vision/tree/master/references/detection
import copy
import os
import torch
import torch.utils.data
import torchvision
import torchvision.transforms as T
from pycocotools import mask as coco_mask
from pycocotools.coco import COCO
class FilterAndRemapCocoCategories(object):
... |
6b041b3e9f04855862b2a2c1093d631450a3e232799db65225d76a6c1019cdb8 | Python | 8,850 | 169 | import torch
from models.perception_loss import vgg16_feat, perceptual_loss
from . import networks
from .base_model import BaseModel
class Pix2PixModel(BaseModel):
""" This class implements the pix2pix model, for learning a mapping from input images to output images given paired data.
The model training req... |
f649dc5c2d77a30ec9f34d3bbaf516a403c95a1c1b29059168f81558d4347fd7 | Python | 8,850 | 221 | import os.path
import random
import sys
import cv2
import h5py
import numpy as np
import scipy.ndimage as ndimage
from PIL import Image
from data.base_dataset import BaseDataset, get_params, get_transform
class BratsDataset(BaseDataset):
"""A dataset class for paired image dataset.
It assumes that the dire... |
60ec12b07d018830675d186f462f310eb3da831e2ec3d9d3160b319e4e6b3421 | Python | 8,857 | 154 | import argparse
import os
import torch
from exp.exp_main import Exp_Main
import random
import numpy as np
def main():
fix_seed = 2021
random.seed(fix_seed)
torch.manual_seed(fix_seed)
np.random.seed(fix_seed)
parser = argparse.ArgumentParser(description='Autoformer & Transformer family for Time S... |
2ae5fd03aec67a2e7bbd3536159e901afc76f2c5d5f9c025624f788451e72912 | Python | 8,870 | 243 | from __future__ import annotations
from typing import Union
import numpy as np
from scipy.linalg import block_diag
from .dataset import Dataset, Gammas
from .generator import Generator
from .options import Options
from .shifter import Shifter
from .skf import SKFSet
from .solver import Solver
from .spline import BSp... |
90a37de58e8aa776092236a4e3e127c73dae360f5a6cce95116f0bf114d4ca27 | Python | 8,880 | 286 | # Acquired from https://github.com/pytorch/vision/tree/master/references/detection
import datetime
import pathlib
import pickle
import time
from collections import defaultdict, deque
import torch
import torch.distributed as dist
class SmoothedValue(object):
"""Track a series of values and provide access to smoot... |
8e049790889dec58e7716521f6e893b1829c2c94603a1f5d0862acc87012afda | Python | 8,889 | 222 | # ----------------------------------------------------------------------- #
# Copyright (c) 2023, UChicago Argonne, LLC. All rights reserved. #
# #
# Software Name: Fast Autonomous Scanning Toolkit (FAST) #
# By: Argonne Na... |
e013f2e91332ac589a8aa5f90ddd503d09ba730de547ca766e7ac3d790221643 | Python | 8,894 | 271 | # Copyright (c) OpenMMLab. All rights reserved.
import os
import warnings
import numpy as np
from mmcv import Config
from xtcocotools.cocoeval import COCOeval
from ...builder import DATASETS
from .topdown_coco_dataset import TopDownCocoDataset
@DATASETS.register_module()
class TopDownCocoWholeBodyDataset(TopDownCoc... |
db8656f1b703967dbc1855830b9c415b9812eb12fea8a0d2bb438e489ca8e8da | Python | 8,904 | 253 | ## Acquired from https://github.com/pytorch/vision/tree/master/references/detection
import copy
import os
from PIL import Image
import torch
import torch.utils.data
import torchvision
from pycocotools import mask as coco_mask
from pycocotools.coco import COCO
import torchvision.transforms as T
class FilterAndRemap... |
65826b301dc4083898ee42bbd5bdb5a7f93fa7c1197bc448294fae044603cc4b | Python | 8,907 | 196 | import logging
import torch.utils.data as data
import numpy as np
import h5py
import os
from .data_utility import init_transform, count_samples, get_img_list_h5
logging.basicConfig()
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def get_transforms():
transforms_train = ["FilterLabel", "Resize", "... |
262d9ba622485afe7532bd897faf3479c589d597ff0754a74aee49852372cd01 | Python | 8,911 | 262 | import torch
import torch.optim as optim
import numpy as np
import copy
from ... import sync
from ...cfg_holder import cfg_unique_holder as cfguh
def singleton(class_):
instances = {}
def getinstance(*args, **kwargs):
if class_ not in instances:
instances[class_] = class_(*args, **kwargs)
... |
1bfd05ee9b3ca4f4e1f3b4bd1022c08746eb1bf6dfe30ef26869a98df084788b | Python | 8,924 | 213 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
from typing import Tuple
import torch
from torch import Tensor, nn
from sbi.neural_nets.estimators.base import ConditionalDensityEstimator
from sbi.neur... |
d3b23f5314988a89d9b8319ef1ee224a8df62844acd749bdbdb66adaefc90c28 | Python | 8,931 | 259 | """
AnySleep: Attention-based U-Sleep for variable channel sleep staging.
This module implements AnySleep, an extension of U-Sleep that uses attention
mechanisms to combine information from multiple input channels. Unlike the
standard U-Sleep which uses exactly 2 channels, AnySleep can process any
number of EEG and EO... |
5561f803ded3b6c154d1a766873ab7c774e50f61b8448692c6abd0a5ad3cc9f2 | Python | 8,936 | 260 | """
Early fusion AnySleep variant (AnySleepEF).
This module implements an attention-based sleep staging architecture where
channel attention is applied BEFORE the U-Net encoder. The attention mechanism
learns to weight and combine multiple input channels into a fixed number of
"virtual channels" before any feature ext... |
85ea82d4b565c0b87dee6fabac248a29178c69cd84dba45f0e304a33fcc3bc74 | Python | 8,941 | 226 | import torch
import tensorflow as tf
import os
os.environ['XLA_PYTHON_CLIENT_PREALLOCATE'] = 'false'
tf.config.set_visible_devices([], device_type='GPU')
from pprint import pprint
import jax.numpy as jnp
import jax.tree_util as tree
import numpy as np
from functools import partial
import haiku as hk
import optax
impor... |
84843d84219feb9470d21284b981cc72cbedc9b0dd6c68abe923d4d6d4ef05e7 | Python | 8,946 | 271 | from typing import Tuple, Any
import pytest
import eagerpy as ep
import numpy as np
import copy
import foolbox as fbn
ModelAndData = Tuple[fbn.Model, ep.Tensor, ep.Tensor]
def test_bounds(fmodel_and_data: ModelAndData) -> None:
fmodel, x, y = fmodel_and_data
min_, max_ = fmodel.bounds
assert min_ < max_... |
801daeb03fecf24ab86261267d371fd0baf4d7200061cf123591d1ecb9746e60 | Python | 8,947 | 202 | import copy
import logging
import random
import time
import numpy as np
import torch
import wandb
from .optrepo import OptRepo
from .utils import transform_list_to_tensor
class FedOptAggregator(object):
def __init__(self, train_global, test_global, all_train_data_num,
train_data_local_dict, te... |
541a098364e93bd3c161a6e4e38c9275272580b8804dcce1514f2851dbedf634 | Python | 8,961 | 202 | import torch as th
import torch.nn as nn
from latentvelo.anvi_dataloader import ANVIDataset
from latentvelo.utils import normalize, sparse_mx_to_torch_sparse_tensor
import os
import numpy as np
import matplotlib.pyplot as plt
from latentvelo.utils import batch_func
def set_adj(adata):
import scipy as scp
adata... |
18a6f97cc49103605bdf87c7773e4add8d9f2d81d0fa7596135ffd8621f7056a | Python | 8,967 | 236 | import os
import csv
import shutil
import hashlib
import tempfile
import numpy as np
import pandas as pd
from rdkit import Chem
from rdkit.Chem import AllChem, MACCSkeys
from rdkit.Chem import MolFromSmiles
from padelpy import padeldescriptor # required to calculate KlekotaRothFingerPrint
from metstab_shap.config imp... |
3ef74a8a4a01c92557b08f6663856f0079864463bf7add82c3f84f6befc09526 | Python | 8,967 | 192 | # Copyright Universitat Pompeu Fabra 2020-2023 https://www.compscience.org
# Distributed under the MIT License.
# (See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
import glob
import numpy as np
import torch
from torch_geometric.data import Dataset, Data
__all__ = ["Custom"]
clas... |
026b3fc5367e3d6e4e22ae48419e3a6eab1212425988f8b7bb1835b33d064cca | Python | 8,969 | 186 | from models.med import BertConfig, BertModel, BertLMHeadModel
from models.blip import create_vit, init_tokenizer, load_checkpoint
import torch
from torch import nn
import torch.nn.functional as F
from transformers import BertTokenizer
import numpy as np
class BLIP_VQA(nn.Module):
def __init__(self, ... |
7c5718a06b4060333f4f413da1ce879e1b12e9c237dcfdd80780533fda7ecfc9 | Python | 8,991 | 231 | import logging
import math
import os
import time
from copy import deepcopy
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
import torch.nn.functional as F
import torchvision.models as models
logger = logging.getLogger(__name__)
def init_seeds(seed=0):
torch.manual_seed(seed)
# Speed... |
a9c209c94a52f55e7181d2bdbb0149d4cafb8ee84be7dbd5fd11705e95e61dda | Python | 8,997 | 210 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Sep 22 16:10:46 2020
@author: bariskuru
"""
import seaborn as sns, numpy as np
import matplotlib.pyplot as plt
sns.set(context='paper',style='whitegrid',palette='colorblind', font='Arial',font_scale=1.5,color_codes=True)
load = np.load('rate_n_pha... |
ad8b58653961028b1bb030b1cd3441623f4d1254f7b67c424a484e1df6a5d840 | Python | 9,002 | 222 | import numpy as np
import sklearn
import sklearn.metrics as sk_metrics
from sklearn.model_selection import (
BaseCrossValidator,
cross_val_score,
LeaveOneOut)
from copy import deepcopy
from . import base as pea2_base
from . import validation as pea2_valid
def aucScore(y_pred: np.ndarray, y_t... |
6edf7712594293141bbcd2905ed0fd7927dc2dc162f34b1910472455bb9885cf | Python | 9,003 | 255 | import numpy as np
from importlib import reload
import sys
sys.path.insert(2,'support')
import functions
reload(functions)
import functions as f
import parameters
reload(parameters)
import parameters as p
import matplotlib
import matplotlib.pyplot as plt
matplotlib.rcParams.update({'font.size': p.fontsize})
plasticity... |
3fe798d4b4ba63f0c0d4aed4d4d15f5927d1facf1a15100f91765b613fed523b | Python | 9,004 | 308 | import torch
import numpy as np
import logging
logger = logging.getLogger(__name__)
def minimize_bfgs(system, forces, fmax=0.5, steps=1000):
from scipy.optimize import minimize
if steps == 0:
return
if system.pos.shape[0] != 1:
raise RuntimeError(
"System minimization curren... |
742f41b28aa236ab44e2475137702ca746b00ee07d1a88abbdbd08ada7330f0e | Python | 9,010 | 251 | '''
ResNet for CIFAR-10/100 Dataset.
Reference:
1. https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py
2. https://github.com/facebook/fb.resnet.torch/blob/master/models/resnet.lua
3. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Deep Residual Learning for Image Recognition. https://arxiv.org... |
5d86b8b4f94aec4f1178be7fd38f22064d1baa444896c7e93d3efa6f1d6a25cd | Python | 9,012 | 267 | from os.path import join, exists
from file_browser import get_models
from config_path import PLOTS_PATH, TEST_RESULTS_PATH
import pandas as pd
from matplotlib import pyplot as plt
import os
base_dir = os.path.dirname(__file__)
all_files= get_models()
# number_patients= [884,592,214,103,68, 35]
# number_patients= [884... |
f6949dc971501d7584b006a64b33b4830472d85010db077dd2c3c217377eccd2 | Python | 9,012 | 260 | # -*- coding: utf-8 -*-
"""
Functions for computing various metrics to aid interpretation of similarity
network fusion outputs.
"""
import numpy as np
from sklearn.cluster import spectral_clustering
from sklearn.metrics import v_measure_score
from sklearn.utils.validation import check_random_state
from . import comput... |
f35dce13b3a3a5133d9860460de6241ae4889db8520e6ecca7e12efb5f2b821d | Python | 9,016 | 197 | import argparse
import logging
import os
import socket
import sys
import numpy as np
import psutil
import setproctitle
import torch
import wandb
# https://nyu-cds.github.io/python-mpi/05-collectives/
from mpi4py import MPI
# add the FedML root directory to the python path
from torch import nn
sys.path.insert(0, os.pa... |
ebd537ec36bc355028013dc849bcfb22ed737b9562c408baceea5b72d4e4e0b1 | Python | 9,020 | 190 | import numpy as np
from torch import nn
class CRNN(nn.Module):
def __init__(
self,
configuration=None,
input_channels=3,
output_classes=22,
convolution_layers=4,
cnn_kernel_size=(3, 3),
in_channels=None,
max_pooling=None,
batch_normalization=... |
ed451d01e32e0e6d3d65cf3bfe6b097c723b212b3fb9c4ee860fbe32cb6d553e | Python | 9,031 | 297 | import spacy, utils
from semquery import SemEHRES
import re
from os import listdir
from os.path import isdir, isfile, join
class StreamedDocs(object):
"""
effectively an abstract class for doing streaming docs
"""
_spacy_instance = None
def get_doc_by_id(self, doc_id):
pass
def __ite... |
c009395f870a0d4588c4231f54837253384982c3cef32a0a55876cb975a300e3 | Python | 9,041 | 222 | # -*- coding: utf-8 -*-
"""CT dataset"""
__author__ = "Sean Benson"
__copyright__ = "MIT"
import os
from torch.utils.data import Dataset
import pathlib
import numpy as np
from dtor.utilities.utils import cutup, pad_nd_image, expand_image,removeOutliers
from dtor.utilities.utils import bbox3d, crop3d
from tqdm import ... |
dc089644d093d1812e5d59057c60f5fb26663b53c1d8c2749582617d4693c42f | Python | 9,041 | 220 | # -*- coding: utf-8 -*-
"""
Created on Fri Jun 4 16:35:35 2021
@author: fhu14
"""
import json
import os
from InputParser import (collapse_to_master_settings,
construct_final_settings_dict,
parse_input_dictionaries)
from .helpers import test_data_dir
def test_excep... |
0bc318e18a24b6ec44cfb8ad910e67cb6f53ef51bb4d7d19b1608a9ac3e284c5 | Python | 9,045 | 251 | '''
ResNet for CIFAR-10/100 Dataset.
Reference:
1. https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py
2. https://github.com/facebook/fb.resnet.torch/blob/master/models/resnet.lua
3. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Deep Residual Learning for Image Recognition. https://arxiv.org... |
ad76cff65e3ccc675c449d5332ed0e0310ba6fa475cc6f91cb3a3a529fa22f40 | Python | 9,067 | 240 | from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras import Model
import tensorflow as tf
from tensorflow.keras.applications.xception import Xception
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from glob import glob
import pa... |
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