sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1eaea54365aa3121dd4c7595c4973778c5948509cb0a3664c7a0c324bcaf5425 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_lmda_03_1"] = lambda: ModelCommitment(
identifier="eSimCLR_lmda_03_1",
activations_model=get_model("eSimCLR_lmda_03_1"),... |
247dacd530d390b68f4415721fb35c9b4a222a5bf3e21a109a71fa06a83a58e9 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-Barlow_lmda_03"] = lambda: ModelCommitment(
identifier="CE-Barlow_lmda_03",
activations_model=get_model("CE-Barlow_lmda_03"),... |
39b26fa513f34b4aaa18078672b09a9d0c1499da189bc24d8b99b71a5b75c22a | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_Vanilla_1"] = lambda: ModelCommitment(
identifier="eBarlow_Vanilla_1",
activations_model=get_model("eBarlow_Vanilla_1"),... |
49b591bb025da4f9a3867a6af936c8c9dde69466499f11c897f3c8e2e8768261 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_Vanilla_2"] = lambda: ModelCommitment(
identifier="eSimCLR_Vanilla_2",
activations_model=get_model("eSimCLR_Vanilla_2"),... |
5245b561e8eb544e4d768db910ceb895f2a968c1783b14d1394add951a3a70dc | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-Barlow_lmda_05"] = lambda: ModelCommitment(
identifier="CE-Barlow_lmda_05",
activations_model=get_model("CE-Barlow_lmda_05"),... |
573acf8b9f7461d450e4f43d4ae9cf37da223b8a880058682502bd5f01582a45 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_lmda_02_1"] = lambda: ModelCommitment(
identifier="eSimCLR_lmda_02_1",
activations_model=get_model("eSimCLR_lmda_02_1"),... |
57d2037a0b35516dc0f9357b58fe6700278aef3db0ed68732015e017f1e3e3e7 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-SimCLR_lmda_03"] = lambda: ModelCommitment(
identifier="CE-SimCLR_lmda_03",
activations_model=get_model("CE-SimCLR_lmda_03"),... |
58ef9d1ae57476bea1db9d71146ff85083d214417cb0d72edc9a05c603822f70 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-SimCLR_lmda_04"] = lambda: ModelCommitment(
identifier="CE-SimCLR_lmda_04",
activations_model=get_model("CE-SimCLR_lmda_04"),... |
5f0aa3d40f3a7be899b2cc3b892006a7f8ff60930a001f673587de8ac9f22108 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-SimCLR_lmda_01"] = lambda: ModelCommitment(
identifier="CE-SimCLR_lmda_01",
activations_model=get_model("CE-SimCLR_lmda_01"),... |
671b376cf67433a708595668f27647ebab1e9c408a0e9ecae1d39b649b7d4a19 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_lmda_02_1"] = lambda: ModelCommitment(
identifier="eBarlow_lmda_02_1",
activations_model=get_model("eBarlow_lmda_02_1"),... |
689f5d5f7c917578a620611069afdf453687899fec2f3d9166be1d449cc5df8e | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_lmda_01_2"] = lambda: ModelCommitment(
identifier="eBarlow_lmda_01_2",
activations_model=get_model("eBarlow_lmda_01_2"),... |
71e6e7404e1625d1b539607e37475cad8cf0c962fcdca640583272e5034b9038 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-Barlow_lmda_01"] = lambda: ModelCommitment(
identifier="CE-Barlow_lmda_01",
activations_model=get_model("CE-Barlow_lmda_01"),... |
751ad91463d92b258a79a97c44d9b684ee26c9f31751380807200262992a681b | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-Barlow_lmda_02"] = lambda: ModelCommitment(
identifier="CE-Barlow_lmda_02",
activations_model=get_model("CE-Barlow_lmda_02"),... |
816d97e198f9bcbb382cfd4faa886d7e74e4dafc41fc08a8467aa96d84104d55 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-SimCLR_lmda_00"] = lambda: ModelCommitment(
identifier="CE-SimCLR_lmda_00",
activations_model=get_model("CE-SimCLR_lmda_00"),... |
896de54e917f0cc1d00bb788cb509e1063afe0ab4fa3bcb658b240852bfa247f | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_Vanilla_1"] = lambda: ModelCommitment(
identifier="eSimCLR_Vanilla_1",
activations_model=get_model("eSimCLR_Vanilla_1"),... |
8b8fbc51ed28f0dfa2215880c969e8e1ddaba749f4d29081e2b6f470f49b8854 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_lmda_03_1"] = lambda: ModelCommitment(
identifier="eBarlow_lmda_03_1",
activations_model=get_model("eBarlow_lmda_03_1"),... |
94a438d23fbe4c90bc64296d3b3ba884e61cf0a1372cc3102c992b7f4c2c0d29 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-SimCLR_lmda_02"] = lambda: ModelCommitment(
identifier="CE-SimCLR_lmda_02",
activations_model=get_model("CE-SimCLR_lmda_02"),... |
9a04f52a8bf95c0b2583f60109c4b8affa63a20204ce1ce0ba298b29786a3109 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-SimCLR_lmda_05"] = lambda: ModelCommitment(
identifier="CE-SimCLR_lmda_05",
activations_model=get_model("CE-SimCLR_lmda_05"),... |
9ac3b769c28e3ce2182b8f735411feb33fd074f32fefd2112b2cd9c852f83e92 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_lmda_01_1"] = lambda: ModelCommitment(
identifier="eBarlow_lmda_01_1",
activations_model=get_model("eBarlow_lmda_01_1"),... |
b02fd31429a20f82af834b39ad6653659b22113d579a476f19c6a935db750cd0 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-Barlow_lmda_00"] = lambda: ModelCommitment(
identifier="CE-Barlow_lmda_00",
activations_model=get_model("CE-Barlow_lmda_00"),... |
bb3883685ccbbc192458e32f4ab2b150f0117e8dfef43c851947c47de443d5bd | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_lmda_04_1"] = lambda: ModelCommitment(
identifier="eBarlow_lmda_04_1",
activations_model=get_model("eBarlow_lmda_04_1"),... |
bc3471dc477871d3b03fff8eaf556957ffea67a8ea5eac4d48edf6176448f956 | Python | 367 | 15 | try:
from brainways.ui._version import version as __version__
except ImportError:
__version__ = "unknown"
from brainways.ui._sample_project import (
load_sample_project,
load_sample_project_annotated,
)
from brainways.ui.brainways_ui import BrainwaysUI
__all__ = (
"load_sample_project",
"load_s... |
c18b6739e5c8b090f618ad81a36fb071d052bd50006d64d002b299329e11e177 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_lmda_01_1"] = lambda: ModelCommitment(
identifier="eSimCLR_lmda_01_1",
activations_model=get_model("eSimCLR_lmda_01_1"),... |
dc68e972048dfb254b3d0b31a902b96f22aeb4dbed48749e3b9012a8d7b761d9 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-Barlow_lmda_04"] = lambda: ModelCommitment(
identifier="CE-Barlow_lmda_04",
activations_model=get_model("CE-Barlow_lmda_04"),... |
f6c382aaecf85937b417f710dcbbaa4fbe655f79f49b438983e4eb9ed19c9b04 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-MMCR_lmda_0001"] = lambda: ModelCommitment(
identifier="CE-MMCR_lmda_0001",
activations_model=get_model("CE-MMCR_lmda_0001"),... |
f7bb6271766409b21bc132c9a3fad73761f0bdba1922c69e150cf14ed8816997 | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_lmda_01_2"] = lambda: ModelCommitment(
identifier="eSimCLR_lmda_01_2",
activations_model=get_model("eSimCLR_lmda_01_2"),... |
faec60ade882f7724d96fbcc0ab1cd94afaaf20db53f2ed7a7bc127211643b6d | Python | 367 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_Vanilla_2"] = lambda: ModelCommitment(
identifier="eBarlow_Vanilla_2",
activations_model=get_model("eBarlow_Vanilla_2"),... |
ff414f5f0f8f4489428dabce1335925f5bb3347d7db8dbded4c3fafaf7d253a7 | Python | 367 | 12 | import mido
def midi_target(midi_file, chunksize=4):
target_midi = mido.MidiFile(midi_file)
target_notes = []
for message in target_midi.tracks[0]:
if message.type == "note_on":
target_notes.append(message.note)
split_list = [target_notes[i:i + chunksize] for i in range(0, len(ta... |
66c76bc8cb1090b2143789bceb1a93af30a6e2629e02f317be1fe0426f8bc1ac | Python | 368 | 17 | from rscvp.util.util_demo import run_demo
from rscvp.visual.main_polar import VisualPolarOptions
class ExampleRun(VisualPolarOptions):
exp_date = '210315'
animal_id = 'YW006'
plane_index = 0
neuron_id = 2
signal_type = 'df_f'
use_default = True
debug_mode = True
if __name__ == '__main__... |
310bac716de9087588b8e4350332e11312f5548afed7a9f26277b3c5e19b01bf | Python | 369 | 15 | # Pretty colours
colors = {
'c_darkblue': '#2F7194',
'c_red': '#ec7070',
'c_darkgreen': '#48675A',
'c_lightblue': '#97c3d0',
'c_lightgreen': '#AFD8BC',
'c_lightbrown': '#C6BFA2',
'c_orange': '#EC9F7E',
'c_yellow': '#F5DDA9',
'c_darkgrey': '#3D4244',
'c_pink': '#F8A6A6',
'c_pu... |
abfe8448e2b3b51e27b4c09dcd2e03af2363b9397f5426146e14532dab4989cc | Python | 369 | 7 | from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision import model_registry
from .model import get_layers,get_model
model_registry['mobilenet_v2_1_0_128'] = \
lambda: ModelCommitment(identifier='mobilenet_v2_1_0_128', activations_model=get_model('mobilenet_v2_1_0_... |
c366fa7acf350d014a0065945e5c8a239e9fbb05a12c28b60714d12cff43a31c | Python | 369 | 7 | from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision import model_registry
from .model import get_layers,get_model
model_registry['mobilenet_v2_1_0_160'] = \
lambda: ModelCommitment(identifier='mobilenet_v2_1_0_160', activations_model=get_model('mobilenet_v2_1_0_... |
0160dc9553601576c7a6346bd20ddc14e233a0a7fbf5c74a513f9563a78cb059 | Python | 370 | 11 | import logging
import sys
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
ch = logging.StreamHandler(sys.stdout)
ch.setLevel(logging.INFO)
formatter = logging.Formatter('%(asctime)s %(levelname)-8s %(filename)-20s%(lineno)4d:\t %(message)s',
datefmt='%d-%m-%Y:%H:%M:%S')... |
1db085bde9cc8628f0ad5919f1ded5b8095fcfae6ce335f18f791db68b3adbf1 | Python | 370 | 7 | from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision import model_registry
from .model import get_layers,get_model
model_registry['mobilenet_v2_1_0_192'] = \
lambda: ModelCommitment(identifier='mobilenet_v2_1_0_192', activations_model=get_model('mobilenet_v2_1_0_... |
43ec2ad4a24ebbdde020d1674df5db89bdf8c7df2514759764b592edb6f3253f | Python | 370 | 17 | import unittest
import sys
class OpenCVTest(unittest.TestCase):
""" Simple functionality tests. """
def test_import(self):
""" Test that the cv2 module can be imported. """
import cv2
def test_video_capture(self):
import cv2
cap = cv2.VideoCapture("SampleVideo_1280x720_... |
7156d581aee9ac1f3fc18156d2c8cbfbddfd4e562a9f754512a20e4971382723 | Python | 370 | 7 | from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision import model_registry
from .model import get_layers,get_model
model_registry['mobilenet_v2_1_3_224'] = \
lambda: ModelCommitment(identifier='mobilenet_v2_1_3_224', activations_model=get_model('mobilenet_v2_1_3_... |
90c670d3677473e09331fde5fb78949d4b393fbbc57761e74b2434bfd6900a66 | Python | 370 | 7 | from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision import model_registry
from .model import get_layers,get_model
model_registry['mobilenet_v2_0_5_192'] = \
lambda: ModelCommitment(identifier='mobilenet_v2_0_5_192', activations_model=get_model('mobilenet_v2_0_5_... |
c271c60cae945945ded955bc3aa8b554dbf67e3cad72cdb8f6ccf693f15e3461 | Python | 370 | 19 | """Make a list of the data files we want to train on.
"""
import os
from glob import glob
paths = sorted(
glob(
"/gpfs3/well/win-hcp/HCP-YA/HCP_PTN1200/node_timeseries"
"/3T_HCP1200_MSMAll_d50_ts2/*.txt"
)
)
print("Found", len(paths), "files")
with open("data_files.txt", "w") as file:
f... |
ce1503d87a28f52e8cbdc156890e1a5595fb0a91e94f7638e5fd9b210bf3382a | Python | 370 | 7 | from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision import model_registry
from .model import get_layers,get_model
model_registry['mobilenet_v2_0_5_224'] = \
lambda: ModelCommitment(identifier='mobilenet_v2_0_5_224', activations_model=get_model('mobilenet_v2_0_5_... |
19b9167c5a6e3b78188df6a5e8cde226f3abc57ec932cc3755fbe96e5091a482 | Python | 371 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_lmda_001_3"] = lambda: ModelCommitment(
identifier="eBarlow_lmda_001_3",
activations_model=get_model("eBarlow_lmda_001_3... |
1c6ae56c6408fd28929d132dcf3a50b65f82f906bc23cad7f315a06fb2b9c1c8 | Python | 371 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['convnext_base_fb_in1k'] = lambda: ModelCommitment(identifier='convnext_base_fb_in1k', activations_model=get_model('convnext_base_fb_... |
3a25e71ed4f51cb6618bceb5397122e836e24c108cb884032b85be2a924c0086 | Python | 371 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_lmda_001_1"] = lambda: ModelCommitment(
identifier="eBarlow_lmda_001_1",
activations_model=get_model("eBarlow_lmda_001_1... |
79929851b6b35cf66479f662318b41da7db4dadb5153b00ec3bf0e24454ce260 | Python | 371 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_lmda_001_1"] = lambda: ModelCommitment(
identifier="eSimCLR_lmda_001_1",
activations_model=get_model("eSimCLR_lmda_001_1... |
c3faef5286624f755fbe200ab214eb12f652a2f1e969d3c3b2f29ae1e8409b4f | Python | 371 | 12 | import logging
import sys
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
ch = logging.StreamHandler(sys.stdout)
ch.setLevel(logging.INFO)
formatter = logging.Formatter('%(asctime)s %(levelname)-8s %(filename)-20s%(lineno)4d:\t %(message)s',
datefmt='%d-%m-%Y:%H:%M:%S'... |
d1b88d477ad64b62c29d55a7261506d1d41a5ad495a584f07fe28797f34462db | Python | 371 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_lmda_001_2"] = lambda: ModelCommitment(
identifier="eBarlow_lmda_001_2",
activations_model=get_model("eBarlow_lmda_001_2... |
424f9c6c0740768390e63bf1939ea6c68dc68039d86e5b81a3e612dc99130103 | Python | 372 | 18 | import sys, os, glob
def fullpath( p ):
return os.path.abspath( os.path.expanduser(p) ) if len(p.strip())>0 else ''
def fileparts( fname ):
p, n = os.path.split( fname )
n, e = os.path.splitext( n )
return p, n, e
def dirsort( filt ):
flist = glob.glob( filt )
flist.sort()
return flist
d... |
447202bcbd158adc19cb925cd63fa30ab86c215baac94f166de124f6aea69706 | Python | 372 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['alexnet_7be5be79_convs'] = lambda: ModelCommitment(identifier='alexnet_7be5be79_convs', activations_model=get_model('alexnet_7be5be79_co... |
54c6055d6da67af24a84a93c28cf5e2a99b0c2b1c4637e09e28854553d0826e1 | Python | 372 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['focalnet_tiny_lrf_in1k'] = lambda: ModelCommitment(identifier='focalnet_tiny_lrf_in1k', activations_model=get_model('focalnet_tiny_lrf_i... |
cedb373fd90decbacb60b91aaac3698ec669765656cede4513566c3c75de4c09 | Python | 372 | 9 | # Copyright (c) OpenMMLab. All rights reserved.
from .inference import inference_depther, init_depther
from .test import multi_gpu_test, single_gpu_test
from .train import get_root_logger, set_random_seed, train_depther
__all__ = [
'get_root_logger', 'set_random_seed', 'train_depther', 'init_depther',
'inferen... |
f288a509dba172597a876308e17c139b96099d921c23e8c14ecdbf15fc294fa0 | Python | 372 | 10 | from brainscore_vision import benchmark_registry
from .benchmarks.benchmark import DicarloRajalingham2018I2n
benchmark_registry['Rajalingham2018-i2n'] = DicarloRajalingham2018I2n
# public benchmark
from.benchmarks.public_benchmark import RajalinghamMatchtosamplePublicBenchmark
benchmark_registry['Rajalingham2018pub... |
ff54fb89b1ea3544536e866a820174fd0e9bf14f0c2b57409e5786680db6764c | Python | 372 | 12 | from __future__ import annotations
from typing import IO
from typing import Any
from ruamel.yaml import YAML
def safe_load(stream: str | IO[str], /) -> Any: # noqa: ANN401
# A fresh instance per call, not a shared one: ruamel's load() appends to
# YAML().doc_infos and never clears it, so a long-lived insta... |
6fe17a6c351bc2670f3abe8c0648100c23399be6923f365d068ed6fb097139b6 | Python | 373 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['aughost_fair_resnet18'] = lambda: ModelCommitment(identifier='aughost_fair_resnet18', activations_model=get_model('aughost_fair_resn... |
7cd15d01720a3ca3e1102c29af1ba798729119bb1322361022c87b9d5662349e | Python | 373 | 15 | """ Fill holes in a surface """
import SVMTK as svm
from pathlib import Path
if __name__ == "__main__":
print("Start ",__file__)
outdir = Path("../results")
outdir.mkdir(exist_ok=True)
mech_shark = svm.Surface("../Data/mech-holes-shark.off")
mech_shark.fill_holes()
mech_shark.save(str(outdir/"mech... |
c0c8869a96edb2b8a9e56d2b2aebb1f222fc8e6c465d14524c03c5c356b3ac34 | Python | 373 | 7 | from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision import model_registry
from .model import get_layers,get_model
model_registry['mobilenet_v2_0_75_224'] = \
lambda: ModelCommitment(identifier='mobilenet_v2_0_75_224', activations_model=get_model('mobilenet_v2_0_... |
c16ef1987998531432e25f23c6336b94fdefaf53b1ca7c90df45e2e77840d2eb | Python | 373 | 7 | from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision import model_registry
from .model import get_layers,get_model
model_registry['mobilenet_v2_0_75_192'] = \
lambda: ModelCommitment(identifier='mobilenet_v2_0_75_192', activations_model=get_model('mobilenet_v2_0_... |
ce50412d67f8960a6d723fc3a702b28da273df8ba139f65f206b26669c71949f | Python | 373 | 7 | from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision import model_registry
from .model import get_layers,get_model
model_registry['mobilenet_v2_0_75_160'] = \
lambda: ModelCommitment(identifier='mobilenet_v2_0_75_160', activations_model=get_model('mobilenet_v2_0_... |
05284220f73e887a74fe6e7bb3cafd4ee6800f063bf0a19dfd4d90a88c24358c | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eMMCR_Mom_lmda_03_1"] = lambda: ModelCommitment(
identifier="eMMCR_Mom_lmda_03_1",
activations_model=get_model("eMMCR_Mom_lmda_0... |
075ce1b017910a113c22d8a9af13b7929f72cf38b248a38a14ec1dd547a6ab1c | Python | 375 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['AdvProp_efficientnet-b4'] = lambda: ModelCommitment(identifier='AdvProp_efficientnet-b4', activations_model=get_model('AdvProp_efficient... |
105f96752ccf1a6e9f63d6fd4571d1dfc010cb7140cfc5f7184ceb4785de3b25 | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eMMCR_Mom_lmda_01_2"] = lambda: ModelCommitment(
identifier="eMMCR_Mom_lmda_01_2",
activations_model=get_model("eMMCR_Mom_lmda_0... |
19ae0d7bf8e58eeb1db4357bf6fa957777822b578baeadd094cf50fd06b1ae31 | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eMMCR_Mom_lmda_01_1"] = lambda: ModelCommitment(
identifier="eMMCR_Mom_lmda_01_1",
activations_model=get_model("eMMCR_Mom_lmda_0... |
2245ad6493792bc8d7ba5d867f5fee750b0f724b5ea2fd27a1cf74fee44cecfd | Python | 375 | 15 | import warnings
import torch
try:
import pytorch_lightning as pl
LightningModule = pl.LightningModule
Callback = pl.Callback
except ImportError:
pl = object
LightningModule = torch.nn.Module
Callback = object
warnings.warn("Please install 'pytorch_lightning' via "
"'pip... |
2354dca613f31cf57f2457c80eb1c45d02b27a9ae6dc39a737b8e22c68269138 | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_lmda_02_1_1"] = lambda: ModelCommitment(
identifier="eSimCLR_lmda_02_1_1",
activations_model=get_model("eSimCLR_lmda_02_... |
23c800fd38b34cb53dc513600656f85817f2360fc23cfe4e7df51543fc043dd0 | Python | 375 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['AdvProp_efficientnet-b7'] = lambda: ModelCommitment(identifier='AdvProp_efficientnet-b7', activations_model=get_model('AdvProp_efficient... |
5833015790453426c251d80b46168312ef4367f0d5dcdee10fb48e0f823f133b | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eMMCR_Mom_lmda_05_1"] = lambda: ModelCommitment(
identifier="eMMCR_Mom_lmda_05_1",
activations_model=get_model("eMMCR_Mom_lmda_0... |
58c5debf764c091609844452888af6b713d73876b58c90c318d006eb90899e2a | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-SimCLR_lmda_0001"] = lambda: ModelCommitment(
identifier="CE-SimCLR_lmda_0001",
activations_model=get_model("CE-SimCLR_lmda_0... |
7183fed8009b59b8c2a02c521d99b9c5fb689e51bde3568b9fb71b40d06ca770 | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_lmda_0001_1"] = lambda: ModelCommitment(
identifier="eSimCLR_lmda_0001_1",
activations_model=get_model("eSimCLR_lmda_000... |
7e6e570bb0c9f564997fcf8e4c8d3d7a008d9fe115bb0019fe3f58b5eb8b36a1 | Python | 375 | 15 | """
AVPENet: Audio-Visual Pain Estimation Network
Official implementation of:
"AVPENet: Pain Estimation from Audio-Visual Fusion of Non-Speech Sounds"
PLOS Digital Health, 2026
Authors: Sami Naouali, Oussama El Othmani
"""
from avpenet.models.avpenet import AVPENet
from avpenet.inference import PainEstimator
__vers... |
97fb4efb9594be476497377c99ce019bc6cb0daa321d1cd82ced7b1d56e5119a | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eSimCLR_lmda_04_1_1"] = lambda: ModelCommitment(
identifier="eSimCLR_lmda_04_1_1",
activations_model=get_model("eSimCLR_lmda_04_... |
9e2cc84647a4ea31178b91ea168cd776de86a1c88230342c4d2a3416f5cafd6f | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eBarlow_lmda_0001_1"] = lambda: ModelCommitment(
identifier="eBarlow_lmda_0001_1",
activations_model=get_model("eBarlow_lmda_000... |
c67124ccf32ad78411be77870db2ec39e65f4f54a60a1993d2cf508c019ce311 | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eMMCR_Mom_Vanilla_2"] = lambda: ModelCommitment(
identifier="eMMCR_Mom_Vanilla_2",
activations_model=get_model("eMMCR_Mom_Vanill... |
cc1d3f09928678fc7823b473d93081d1e0084d0593a4da15eacb153c2ada00eb | Python | 375 | 17 | from setuptools import setup, find_packages
setup(
name='stim-opt',
version='1.0',
description='Methods for optimizing two-photon optogenetic photostimulation patterns',
author='Marcus Triplett',
author_email='marcus.triplett@columbia.edu',
packages=find_packages(),
install_requires=[
'numpy>=1.26',
'scipy>... |
cd7e46a0816dbcbd5251c89baf7293d73a2600ffe30074136cbe08a1051ae597 | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eMMCR_Mom_Vanilla_1"] = lambda: ModelCommitment(
identifier="eMMCR_Mom_Vanilla_1",
activations_model=get_model("eMMCR_Mom_Vanill... |
d381b25d893506cb90c8ae99f063c222a83b64684869005fb6d97251d052108d | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eMMCR_Mom_lmda_04_1"] = lambda: ModelCommitment(
identifier="eMMCR_Mom_lmda_04_1",
activations_model=get_model("eMMCR_Mom_lmda_0... |
d39c2574a65c6fc1be7b340d036eba1104ca5ce6f8e373ab74994c85d1c546f1 | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["CE-Barlow_lmda_0001"] = lambda: ModelCommitment(
identifier="CE-Barlow_lmda_0001",
activations_model=get_model("CE-Barlow_lmda_0... |
e11d9e2be4e3aaebb6fa6036fbdf62dfbcffed1b62e6d040d5bb612179b747f8 | Python | 375 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eMMCR_Mom_lmda_02_1"] = lambda: ModelCommitment(
identifier="eMMCR_Mom_lmda_02_1",
activations_model=get_model("eMMCR_Mom_lmda_0... |
ecb1f542ae290743d02d296abf6fd5f6a929021b93a3d38afc7ad7ae14df97a8 | Python | 375 | 12 | from distances import SNRDistance
from utils import common_functions as c_f
from losses.contrastive_loss import ContrastiveLoss
class SignalToNoiseRatioContrastiveLoss(ContrastiveLoss):
def __init__(self, **kwargs):
super().__init__(**kwargs)
c_f.assert_distance_type(self, SNRDistance)
def ge... |
24812318a8bfba3d3b48911712c728f7085ea0032570570db6a5aed6691c1f61 | Python | 376 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['AdvProp_efficientnet-b6'] = lambda: ModelCommitment(identifier='AdvProp_efficientnet-b6', activations_model=get_model('AdvProp_efficient... |
5c3d94e4f48e02b37f91334114d185ea78848f440b170bc610af664e04fe748b | Python | 376 | 19 | """# File dialog widget
A dialog to select a file.
"""
from pathlib import Path
from magicgui import magicgui
@magicgui(filename={"mode": "r"})
def filepicker(filename=Path("~")) -> Path:
"""Take a filename and do something with it."""
print("The filename is:", filename)
return filename
filepicker.fi... |
7ce317ae27c9201f1a8dfed989f00f2adb89c523dca4214f93649939e584dd08 | Python | 376 | 16 | #!/usr/bin/env python3
import glob, sys, os
def main():
files = glob.glob('*/outs/molecule_info.h5')
aggrFile = open('AggregatedDatasets.csv', 'w')
aggrFile.write('sample_id,molecule_h5\n')
files.sort()
for i in files:
aggrFile.write('%s,%s\n' % (i.split('/')[0], os.path.abspath(i)))
... |
2c1833d96f15f3250b5682f996379a2823ca3ada96460ba825bb17993cb6464f | Python | 377 | 16 | from rscvp.util.util_demo import run_demo
from rscvp.visual.main_sftf_pref import VisualSFTFPrefOptions
class ExampleRun(VisualSFTFPrefOptions):
exp_date = '210315'
animal_id = 'YW006'
plane_index = 0
neuron_id = 2
signal_type = 'df_f'
use_default = True
debug_mode = True
if __name__ == ... |
58ffd5a7dda4b474b049e8bd4865d6422fcae8fdbe32cda017e14da94d3f751f | Python | 377 | 9 | def test_qtwebsockets():
"""Test the qtpy.QtWebSockets namespace"""
from qtpy import QtWebSockets
assert QtWebSockets.QMaskGenerator is not None
assert QtWebSockets.QWebSocket is not None
assert QtWebSockets.QWebSocketCorsAuthenticator is not None
assert QtWebSockets.QWebSocketProtocol is not N... |
86d2a649c4eaa18977509d6ac16c087e7e80a4bbc09de2d7a9e0c87cde292b1d | Python | 378 | 14 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from typing import ClassVar
from cvat.apps.redis_handler.rq import RequestId
class ConsensusRequestId(RequestId):
ACTION_DEFAULT_VALUE: ClassVar[str] = "merge"
ACTION_ALLOWED_VALUES: ClassVar[tuple[str]] = (ACTION_DEFAULT_VALUE,)
QUEU... |
e8eb5b897d661453b3ebcccd90024c104d9ba9f749d53685cb10cf56359a9f4c | Python | 378 | 17 | try:
from .pcqm4m import PCQM4MDataset, PCQM4MEvaluator
except ImportError:
pass
try:
from .pcqm4m_pyg import PygPCQM4MDataset
except ImportError:
pass
try:
from .pcqm4m_dgl import DglPCQM4MDataset
except (ImportError, OSError):
pass
from .mag240m import MAG240MDataset, MAG240MEvaluator
fr... |
13d41b2def720b6a782f417587490895681052effb86841e3bf78314d26d161d | Python | 379 | 12 | # Copyright (c) DP Technology.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from .module_proxy_wrapper import ModuleProxyWrapper
from .legacy_distributed_data_parallel import LegacyDistri... |
82839d6cf289cc7655dd78555299eedb06fc19d6a8dde9ced12dab6c7094a72c | Python | 379 | 12 | from pathlib import Path
from typing import Union
from brainways.utils.io_utils.file_iterators.path import PathFileIterator
from brainways.utils.io_utils.file_iterators.qupath import QuPathFileIterator
def get_file_iterator(path: Union[str, Path]):
if Path(path).suffix == ".qpproj":
return QuPathFileIter... |
9a9f8ea037ae008f44b9617214ac506f43f82af20c29c05cc03ffbedf6811a8f | Python | 379 | 12 | """Public analysis utilities for Waven.
The implementation currently lives in :mod:`Waven.Analysis_Utils` for
historical reasons. This wrapper gives users the lowercase package import:
from waven import analysis_utils as au
from waven.analysis_utils import PlotTuningCurve
"""
from __future__ import annotatio... |
9edabb27b9eb8a11d571c8c75dfe711cd8af8780bfa2acf88d3f666264caaa76 | Python | 379 | 13 | from avpenet.models.audio_encoder import AudioEncoder
from avpenet.models.visual_encoder import VisualEncoder
from avpenet.models.fusion import CrossModalFusion
from avpenet.models.regression_head import RegressionHead
from avpenet.models.avpenet import AVPENet
__all__ = [
"AudioEncoder",
"VisualEncoder",
... |
cfe10ddf84eda5260b90dc8e7e3831efd13728d6291ed6f3d5f5659c8d3ea957 | Python | 379 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry["eMMCR_Mom_lmda_001_1"] = lambda: ModelCommitment(
identifier="eMMCR_Mom_lmda_001_1",
activations_model=get_model("eMMCR_Mom_lmda... |
062c5729df83f537734ded95eb4a29cf6c542bc1da7a7488f6c7269ecda5c08d | Python | 380 | 16 | #!/bin/env python
import numpy as np
import sys
inp1 = sys.argv[1]
inp2 = sys.argv[2]
lines1 = np.loadtxt(inp1, dtype=np.float, usecols=(0,1,2,3),unpack=False)
lines2 = np.loadtxt(inp2, dtype=np.int, usecols=(1,),unpack=False)
n = len(lines1)
for i in range(n):
x, y, z, d = lines1[i]
a = lines2[i]
if a != 0:
... |
c6de14de7a67e9a37b8e49094899a9fe112666ad809ed367ef2264e75e46b299 | Python | 380 | 15 | from zigzag.classes.mapping.loop import Loop
class TemporalLoop(Loop):
"""Class that represents a temporal loop."""
def __init__(self, dimension, size) -> None:
super().__init__(dimension, size)
self.type = "temporal"
def __str__(self):
return f"TemporalLoop({self.dimension},{sel... |
dccaa8b7a07827ddb35c488d4cb149599cd5872c29907f3ad81c9e2ae308d365 | Python | 380 | 15 | """Shared application-cache locations."""
from pathlib import Path
from platformdirs import user_cache_path
APP_NAME = "napari-dmc-brainmap"
def app_cache_root() -> Path:
"""Return the application-owned platform cache directory."""
cache_root = Path(user_cache_path(APP_NAME, appauthor=False))
cache_ro... |
f796f17c97f2abfbf7dbccfe4a5f312ce1881ab4fd1067e241b90bdac4b8be44 | Python | 380 | 6 | # aliases
from cardiac_models.electrophysio.data_processing import EPDataProcessor, load_dataprocessor
from cardiac_models.electrophysio.GINO.model import initialize_GINO_model
from cardiac_models.electrophysio.raw_data_handling import single_case_handling
from cardiac_models.electrophysio import data_processing
from... |
0565b4276f44b58cd83f1b47010c1a06035dc1ac724d9f1c5ffd03e131a480f3 | Python | 382 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['jem_imagenet_p0p9_s1'] = lambda: ModelCommitment(identifier='jem_imagenet_p0p9_s1', activations_model=get_model('jem_imagenet_p0p9_s1'),... |
2a7862434263389698e741b537ceeffc8af4a78c1f158ecd29a4335d5d13c604 | Python | 382 | 16 | from .vgg import *
from .dpn import *
from .lenet import *
from .senet import *
from .pnasnet import *
from .densenet import *
from .googlenet import *
from .shufflenet import *
from .shufflenetv2 import *
from .resnet import *
from .resnext import *
from .preact_resnet import *
from .mobilenet import *
from .mobilenet... |
5cb0139dcf5d27ad271007c1e8fb127fe8ac38b11f836daf25a022b005e1ad81 | Python | 382 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['jem_imagenet_p0p0_s1'] = lambda: ModelCommitment(identifier='jem_imagenet_p0p0_s1', activations_model=get_model('jem_imagenet_p0p0_s1'),... |
6228f6ac974c9cbb095d644e0bfaad92be6b59c835ec2ba967752cafd226e43f | Python | 382 | 17 | # trial codes
TRIAL_MT_PRACTICE: int = 0
TRIAL_MT_CONTROL: int = 1
TRIAL_MT_MAIN: int = 2
TRIAL_PL1: int = 3
TRIAL_PL2: int = 4
TRIAL_ET_GOOD: int = 5
TRIAL_ET_BAD: int = 6
TRIAL_SURVEY: int = 7
# trigger codes
TRIGGER_FIXATION: str = '1'
TRIGGER_CUE: str = '2'
TRIGGER_AUDIO_ON: str = '3'
TRIGGER_AUDIO_OFF: str = '4'
... |
71a501b67b5779da93b7475250a1bf206dc3f597f0d3d1b70d1f99444a540f41 | Python | 382 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['jem_imagenet_p0p5_s1'] = lambda: ModelCommitment(identifier='jem_imagenet_p0p5_s1', activations_model=get_model('jem_imagenet_p0p5_s1'),... |
9e086af6143fee00758173cc64bc28cdedee1607d5a17f5c3a741dfaad4ee8f3 | Python | 382 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['jem_imagenet_p0p3_s1'] = lambda: ModelCommitment(identifier='jem_imagenet_p0p3_s1', activations_model=get_model('jem_imagenet_p0p3_s1'),... |
b4b551750813be18d0fabfb8762be6154d663231245a4c5c3c9c5252324841fb | Python | 382 | 15 | import requests
def send_request(url: str, payload: list[dict]) -> list[dict]:
response = requests.post(url, json=payload)
response.raise_for_status()
return response.json()
payload = [
{"proteins_tabular": {"classification": "HYDROLASE"}, "protein_sequence": ""},
]
response = send_request(url="htt... |
cf5254c0d2a3c64d391b8578315ab8e344f1ad930ebb129a7416e38b588e614a | Python | 382 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['jem_imagenet_p0p1_s1'] = lambda: ModelCommitment(identifier='jem_imagenet_p0p1_s1', activations_model=get_model('jem_imagenet_p0p1_s1'),... |
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