sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
3c5e98479bf838ee909bce4c9f2072f7cc3059c3540cb44b6fd7241303f6e2c9 | Python | 1,220 | 37 | # 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.
import torch.nn as nn
class LSTMCellWithZoneOut(nn.Module):
"""
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations... |
0a9a423a4ef2c707d5d5abf02237efd28ebb904c87d7824ef771b7a844e15e95 | Python | 1,221 | 37 | # encoding: utf-8
"""
@author: Jiayang Chen
@contact: yjcmydkzgj@gmail.com
"""
from torch.utils.data.distributed import DistributedSampler
from torch.utils.data.sampler import SequentialSampler
from torch.utils.data.sampler import RandomSampler
def build_sampler(sampler_name, data_source, is_train=True, distributed_... |
26ba882984495f6745a7a825b058ee7a97c3e4db58da4b619f934b1022bf4bd9 | Python | 1,221 | 38 | from __future__ import annotations
from typing import TYPE_CHECKING
import torch
from scvi import REGISTRY_KEYS
from scvi.module.base import EmbeddingModuleMixin
if TYPE_CHECKING:
import numpy as np
from anndata import AnnData
class EmbeddingMixin:
"""Mixin class for initializing and using embeddings ... |
58def0d1d9c51bae57d86ef1a0932dfebb5613bb130c8995310a6ad88aa58ae3 | Python | 1,221 | 41 | #!/usr/bin/python3
# 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.
import argparse
import fileinput
import hashlib
import sys
from multiprocessing import Pool
def get_hashes_and_lines(raw_... |
ea6e9e1b8a877f0c24754b00bc023548ed7be849605122eae78e80d546fe75e5 | Python | 1,221 | 35 | import numpy as np
class Material:
def __init__(self, material_name):
"""
Material of optical elements and its refractive index.
Args:
material name: name of the material. So far, we provide PDMS, FUSED_SILICA, VACCUM.
"""
self.material_name = material_name
... |
c81b3fadf4ddf9e0190bd32086fa56e344e2b99fd5dda6d725a74821043929dc | Python | 1,222 | 21 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_bal_nnunet_aug_TIME(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: int, dat... |
deb7967c45c477a7e15f18ba83ffc307a9c6409ecbf10403e888b04645d109e9 | Python | 1,222 | 21 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_wei_nnunet_aug_TIME(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: int, dat... |
eb1ff68278ba6bf7807af12ef3f6a3c7632114cbd8334c8ada5e102cfd629673 | Python | 1,222 | 33 | import jax
import jax.numpy as jnp
from folx import forward_laplacian, register_function
from folx.api import FwdJacobian, FwdLaplArray
@jax.jit
def custom_logsumexp(log_determinants, sign_determinants):
return jax.nn.logsumexp(log_determinants, b=sign_determinants, return_sign=True)
def custom_logsumexp_forwar... |
5eb8dc25ae7a162df091a8fe3703a39522d49b181906958772c50bd8bbac4815 | Python | 1,223 | 42 | #!/usr/bin/env python
# PYTHON_ARGCOMPLETE_OK
"""This script prints a list of all the models MDT can find in your home directory."""
import argparse
import mdt
import mdt.utils
from mdt.lib.shell_utils import BasicShellApplication
__author__ = 'Robbert Harms'
__date__ = "2015-08-18"
__maintainer__ = "Robbert Harms"
__... |
e64ec392a2be1c706afee0eee41cfbe39c2b7fa1dad864c364fbe3be3689cfdc | Python | 1,223 | 40 | # Copyright 2021 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
111676582f6b1d93e0e2fca5037209a46eb352108d07cfd17daaf6877ad1fb29 | Python | 1,224 | 21 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_wei_i0_nnunet_aug_TIME(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: int, ... |
5b6ac4466d196dd6fc9483032e89a46227a367cad12ea89b04aa5787487f510c | Python | 1,224 | 37 | # encoding: utf-8
"""
@author: chenjiayang
@contact: sychenjiayang@163.com
"""
from PIL import Image
#import torchvision.transforms as T
from . import cla_transforms as CT
def build_transforms(dataset_type, cfg, is_train=True):
if dataset_type == "sequence-classification":
transforms = build_transforms_se... |
f6c1324b561ea98aebd00ae20bcf183aa67e9072685f37fe447aa7fdf2cbf207 | Python | 1,224 | 33 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from dataclasses import dataclass, field
from typing import Any
@dataclass
class Config:
# This is for CLI applications that need to reuse a CLI parameter in multiple places
# in the config file. The idea is that you use `my_cli params... |
1a21f37fdaad6bd6de0e101d8dc8b6945b557fd763c8eb4d5c099055154f343e | Python | 1,225 | 28 | import argparse
from msi_visual.extract.bruker_tsf_to_numpy import BrukerTsfToNumpy
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument('--start_mz', type=int, default=300)
parser.add_argument('--id', type=str, required=True)
parser.add_argument('--end_mz', type=int, default=1... |
5cbbb2791a6c02cc90c2fae03d78371d7c84f1cf7e83f7f64bf04078b455818c | Python | 1,226 | 33 | """GO-DAG constants."""
__copyright__ = "Copyright (C) 2010-2019, DV Klopfenstein, H Tang, All rights reserved."
__author__ = "DV Klopfenstein"
NAMESPACE2NS = {
'biological_process' : 'BP',
'molecular_function' : 'MF',
'cellular_component' : 'CC'}
NS2NAMESPACE = {
'BP': 'biological_process',
'MF... |
7ebeb9e3b181eddd57b2a0f33d3f1830fefda353fe43ee42df2c75dc09353224 | Python | 1,226 | 41 | # 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.
import logging
from fairseq.tasks import register_task
from fairseq.tasks.speech_to_text import SpeechToTextTask
from fairseq.tasks.translatio... |
bb5660926ac740e9444f3b6b8fb7e9171a89149bdca17202830636ccc3d65918 | Python | 1,228 | 21 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_wei_nnunet_aug_json(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: int, dat... |
bbfab4535afd72e18482c2379989fcb8ee0f59f153b91e21d9e13c433fef7f19 | Python | 1,229 | 32 | import torch
def broadcast_labels(o, n_broadcast=-1):
"""Utility for the semi-supervised setting.
If y is defined(labelled batch) then one-hot encode the labels (no broadcasting needed)
If y is undefined (unlabelled batch) then generate all possible labels (and broadcast other
arguments if not None)
... |
e8df1d0a6e14c931aa65e88d0759996084233870a582dcbd07a917ce4cc9ed5b | Python | 1,229 | 47 | import matplotlib.pyplot as plt
import numpy as np
# 设置全局字体为新罗马字体
plt.rcParams['font.family'] = 'serif'
plt.rcParams['font.serif'] = 'Times New Roman'
# 设置全局字体大小
plt.rcParams.update({'font.size': 12})
# Data
scenarios = ['Playground', 'City', 'Canyon']
methods = ['SAC+RAE', 'SAC+CFS', 'Our method']
succes... |
3cdb51bd3d44fab602b82d0514a5338483b271ccab6613448a791719bc1ff00b | Python | 1,230 | 21 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_wei_i0_nnunet_aug_json(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: int, ... |
4c1c7363b09ae61b105f313b528e7b04a4a2ef5ab5918f05c94945d8bdcc7205 | Python | 1,230 | 44 | from __future__ import annotations
from types import MappingProxyType
import pytest
from scvi.train._config import TrainerConfig, TrainingPlanConfig, merge_kwargs
def test_merge_kwargs_prefers_overrides():
config = TrainingPlanConfig(lr=1e-3, weight_decay=1e-2, loss_kwargs={"foo": "bar"})
overrides = {"lr"... |
cf53e995df971cea54d4a0c4771bee302fe329a586aa8861a345700c636e703e | Python | 1,230 | 28 | from nnunetv2.training.nnUNetTrainer.nnUNetTrainer import nnUNetTrainer
class nnUNetTrainerNoMirroring(nnUNetTrainer):
def configure_rotation_dummyDA_mirroring_and_inital_patch_size(self):
rotation_for_DA, do_dummy_2d_data_aug, initial_patch_size, mirror_axes = \
super().configure_rotation_dum... |
28e14ba8203aad41737cf976b70a7f07da5477cd723c47faced72813271bd82d | Python | 1,231 | 34 |
import torch
import numpy as np
from torch.utils.data import Dataset
import skimage.io as skio
class BatchDatasetFromTIFFAndZernike(Dataset):
def __init__(self, tif_path, coeff_path, device='cuda'):
self.device = device
super().__init__()
# === Load raw intensity images
phase_adde... |
29b81a5130ece743b6b325e0b3549a952fa723fb1010ee54038e8e7db651a540 | Python | 1,231 | 37 | __author__ = 'Robbert Harms'
__date__ = "2016-06-25"
__maintainer__ = "Robbert Harms"
__email__ = "robbert@xkls.nl"
class ProtocolIOError(Exception):
"""Custom exception class for protocol input output errors.
This can be raised if a protocol is inconsistent or incomplete. It should not be raised for general... |
74587490deeac9cb0b8b26f4c64f890e7dcdfdf5895d4e25682cedb23055baaf | Python | 1,231 | 37 | # Do this here to suppress warnings before we import vak
import logging
import warnings
from numba.core.errors import NumbaDeprecationWarning
warnings.simplefilter('ignore', category=NumbaDeprecationWarning)
import vak
from . import constants
logger = logging.getLogger(__name__)
def run_prep():
"""Run ``vak ... |
624c28916ae265e85acd9931d25d6b2539fc13b1cbd096b767abbc831a3c1c90 | Python | 1,232 | 28 | from argschema import ArgSchema, ArgSchemaParser
from argschema.schemas import DefaultSchema
from argschema.fields import Nested, InputDir, String, Float, Dict, Int
from ...common.schemas import EphysParams, Directories
class PostprocessingParams(DefaultSchema):
within_unit_overlap_window = Float(required=False,... |
b486229fa64d8b1cf4a7c91f473c836bc31970746246461d9ddf333571133e00 | Python | 1,232 | 21 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_wei_nnunet_aug_json_TIME(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: int... |
8d6067eb59f95bce5392946bdc53c58c68928850717224baf52fdce0add903bf | Python | 1,234 | 21 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_wei_i0_nnunet_aug_json_TIME(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: ... |
52c5caab4426bbb86f3b7d7c9816d3aacd178cc6401acd6b79a956a5dd426f0a | Python | 1,235 | 51 | from pathlib import Path
import pytest
HERE = Path(__file__).parent
TEST_DATA_ROOT = HERE.joinpath("..", "data_for_tests")
@pytest.fixture
def test_data_root():
"""Path that points to root of data_for_tests directory"""
return TEST_DATA_ROOT
SOURCE_TEST_DATA_ROOT = TEST_DATA_ROOT.joinpath("source")
@p... |
9f6b050eef5592dee7fe4e36779316d69e7c448b363c8564d78edcf323b5d53e | Python | 1,235 | 43 |
def cli_main():
pl.seed_everything(1234)
# ------------
# args
# ------------
parser = ArgumentParser()
parser.add_argument('--batch_size', default=32, type=int)
parser = pl.Trainer.add_argparse_args(parser)
parser = LitClassifier.add_model_specific_args(parser)
args = parser.parse... |
61c03c6b2abb1d996d1f50dee39d2cfe6debafc1656eccdbb3f532ea47eac4b3 | Python | 1,236 | 40 | import torch
from torch.linalg import svdvals
def old_topk(similarities, labels, k=5):
if k > similarities.shape[0]:
k = similarities.shape[0]
topsum = 0
for i in range(k):
topsum += torch.sum(
torch.argsort(similarities, axis=1)[:, -(i + 1)] == labels
) / len(labels)
... |
200ec0b3a0f67a1a0d30516cee53f1e9e6b4174897e73ba256d0134941d7311a | Python | 1,238 | 41 | import torch
from torch.distributions.constraints import Constraint
class _Optional(Constraint):
def __init__(self, constraint: Constraint):
self.constraint = constraint
def check(self, value: torch.Tensor) -> torch.Tensor:
if value is None:
return torch.ones(1, dtype=torch.bool)
... |
8fe35807e846e682a12bd382b28dc53bae8aa8d80fda9b0bf4d625c561cfd47a | Python | 1,238 | 52 | import numpy as np
import pandas as pd
import pytest
from pgmpy.estimators import MmhcEstimator
@pytest.fixture
def mmhc_estimator():
data = pd.DataFrame(np.random.randint(0, 2, size=(int(1e5), 3)), columns=list("XYZ"))
data["sum"] = data.sum(axis=1)
est = MmhcEstimator(data)
return est
def test_es... |
9e42d06ea12b47683e5cf84f4e9ebcd072b70762b009429bb745e15aa27c6bf5 | Python | 1,238 | 35 | # 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.
"""
Layer norm done in fp32 (for fp16 training)
"""
import torch.nn as nn
import torch.nn.functional as F
class Fp32InstanceNorm(nn.Instance... |
29f84feb2c193e9e9e101be02db7a7c76e09d1631306cbca95a7a693dd3c5331 | Python | 1,240 | 49 | from importlib.metadata import metadata
import pytest
import scvi
from scvi.hub._url import validate_colab_notebook, validate_url
info = metadata("scvi-tools")
@pytest.mark.internet
def test_validate_homepage_url():
valid = "https://scvi-tools.org/"
assert validate_url(valid)
invalid = "scvi-tools.org... |
e0bce3d81dd3be511bcb9ee1dbfc052a8f4e79eccaa0fa38b5a07c9e9a59d8ba | Python | 1,241 | 40 | import torch
import torch.nn as nn
class ConvMLP(nn.Module):
def __init__(self, input_size=256):
super(ConvMLP, self).__init__()
self.audio_encoder = nn.Sequential(
nn.Conv1d(1, 16, kernel_size=3, stride=2, padding=1),
nn.ReLU(),
nn.Conv1d(16, ... |
85b2e909eb22143bd28f92950e57ae124f57d43b0f104063636369d21d8388a6 | Python | 1,242 | 43 | from typing import Union, NamedTuple, Optional
from pathlib import Path
import torch
PathLike = Union[str, Path]
class NamedTensorTuple(NamedTuple):
def to(self, *args, **kwargs) -> "NamedTensorTuple":
return self.__class__(
*(tensor.to(*args, **kwargs) for tensor in self) # type: ignore
... |
49f2b1c7ca20a33667808d37f336ba428812c64fc7830442b753c05ebc4ee961 | Python | 1,243 | 43 | import unittest
class TestInstalledModules(unittest.TestCase):
# GPU dependent library installations:
def test_opencv(self):
try:
import cv2
except ImportError:
self.fail('OpenCV not installed')
try:
_ = cv2.__version__
except Exception as e:
... |
c379d225c01ac2e00b0e514ce4c6837f5202587de9289ef0a96bfc0a2a631ea1 | Python | 1,245 | 32 | import os
from pathlib import Path
def find_project_root(marker_file_or_dir="setup.py"):
"""
Finds the project root by searching for a marker file/directory
up the directory tree from the current file's location.
"""
current_path = Path(os.path.abspath(os.path.dirname(__file__)))
for parent in ... |
19e545ba339df5c977cd87973c95273eafc3bed883bc6d3a3bb82a388d5b1be6 | Python | 1,246 | 39 | import argparse
import webbrowser
import neuroglancer
import neuroglancer.cli
if __name__ == "__main__":
ap = argparse.ArgumentParser()
neuroglancer.cli.add_server_arguments(ap)
args = ap.parse_args()
neuroglancer.cli.handle_server_arguments(args)
viewer = neuroglancer.Viewer()
with viewer.tx... |
ba45435300a029b73043cf0b5ea59753e908e9f4b6a44fde8a8ff39410684137 | Python | 1,246 | 53 | import os
from fairseq.data.audio import (
AudioTransform,
CompositeAudioTransform,
import_transforms,
register_audio_transform,
)
class AudioDatasetTransform(AudioTransform):
pass
AUDIO_DATASET_TRANSFORM_REGISTRY = {}
AUDIO_DATASET_TRANSFORM_CLASS_NAMES = set()
def get_audio_dataset_transform... |
ebec1387fee6e5d491a9e9b2ede397d726e711f2cc884a08a793d6914fa58e19 | Python | 1,246 | 35 | from typing import Tuple
import numpy as np
import loompy
from cytograph.species import Species
class CellCycleAnnotator:
def __init__(self, species: Species) -> None:
self.species = species
def fit(self, ds: loompy.LoomConnection) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
g1_indices = np.isin(ds.ra.Gene... |
10eeebaf11a9ab1b2006906fba6a67e9703b713fabdb9158a1a94215aa7ee853 | Python | 1,247 | 29 | """The process-wide CPU embeddings cache must not leak across tests.
`base.cpu_embeddings_cache` is module state keyed by base model and document
id, and fixtures across the suite reuse small integer pmids for unrelated
documents — so on a machine whose `config.toml` enables the cache, one test's
entry could be read b... |
1c0bd8e74d966cf9418d2cbdb615b4417bd278dbbe425543d88f51d1feb7d78b | Python | 1,248 | 29 | from dataclasses import dataclass, field
@dataclass
class LossData:
"""Dataclass to store loss values for training, validation, and testing from different loss functions."""
losses_train: dict[str, list[float]] = field(default_factory=dict)
losses_val: dict[str, list[float]] = field(default_factory=dict)... |
d27d1e01427e32c7dc71c89335f913de75fe0f5a669a31f39efef97af93f206d | Python | 1,248 | 39 | import pytest
from pymatgen.core import Element
from pymatgen.entries.computed_entries import ComputedEntry, EnergyAdjustment
from mattergen.evaluation.reference.correction_schemes import TRI110Compatibility2024
def test_tri_pbe_correction_uses_uncorrected_energy() -> None:
entry = ComputedEntry(
composi... |
206697b88fb7eb088f8aded04db9c9518ab8668849c0352e925dc08b512e4fdb | Python | 1,249 | 39 | import os
import pandas as pd
def get_git_directory(config):
if config.get("GIT_DIR") is not None:
git_dir = config["GIT_DIR"]
else:
# Should change the SpaceHack directory.
git_dir = os.getenv("GIT_DIR", "/home/ubuntu/workspace/SpaceHack2023")
if not git_dir.endswith("/"):
... |
364ce654af07329c224f8316f444eb79f63cba6fd5a0cb42f7b992d7a37bbde6 | Python | 1,250 | 46 | # Copyright 2021 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
57e055a1b96c9a42a08f0006408914e1eda3a74d1e741313e3fa25f78a53e435 | Python | 1,250 | 30 | from argparse import ArgumentParser
from transformers.commands import BaseTransformersCLICommand
def download_command_factory(args):
return DownloadCommand(args.model, args.cache_dir, args.force)
class DownloadCommand(BaseTransformersCLICommand):
@staticmethod
def register_subcommand(parser: ArgumentPa... |
750795eff57a78098e868022b02500b64f5f6c9fc4ca404848378343126d1c61 | Python | 1,251 | 41 | """Single-image inference script."""
import argparse
import torch
from PIL import Image
from torchvision import transforms
from configs.config import Config
from models.hybrid_model import HybridTransformerModel
from utils.checkpoints import load_checkpoint
def predict_image(image_path: str):
config = Config()
... |
bb7aa8f184dd61da00d2bd6523a220c6bcb6a60030287597a09d4510e4e47bc0 | Python | 1,251 | 29 | # Generate sql script to extract patient followup for each condition
# Requires tables containing patients for inclusion
from A0_global_vars_py import *
s = ''
for pln in ['gold', 'aurum']:
s += f'--- {pln.upper()}\n'
for condition in conditions:
s += f'-- {condition.upper()} {pln}\n'
s += f''... |
3be37c408053c734ba6e23163fb9af2bbfdd1e08e188404ec28cf71dcff1820b | Python | 1,252 | 40 | """Smoke test for scripts/ssn/train_bm.py.
Uses tests/fixtures/ssn_smoke.yaml: 11 epochs, dur=100 (vs 1000 in the
minimal_working_example), to keep runtime well under the 60 s timeout.
Note: first run includes numba JIT compilation (~10-15 s overhead).
"""
import shutil
import subprocess
import sys
from pathlib impor... |
65d801bdfa0a37ca654ba1dcdea5e39122fdaa25033bac38bacc4bdb551ab9f8 | Python | 1,253 | 28 | import argparse
from msi_visual.extract.pymzml_to_numpy import PymzmlToNumpy
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument('--start_mz', type=int, default=None)
parser.add_argument('--id', type=str, required=True)
parser.add_argument('--end_mz', type=int, default=None)
... |
a8b301d8ac6894730a5a07bdc49033555d722ae6c4b197339fe391ae4bdad762 | Python | 1,254 | 40 | import torch.nn as nn
import math
import torch
class GhostModule(nn.Module):
def __init__(self, inp, oup, kernel_size=1, ratio=2, dw_size=3, stride=1, relu=True):
super(GhostModule, self).__init__()
self.oup = oup
init_channels = math.ceil(oup / ratio)
new_channels = init_channels*(... |
ff6017bcbd920f8c8e6e4fc1b5a357130ae1ccd7679782c26c488263bba87f5c | Python | 1,256 | 36 | """module for functions that deal with vector of times from a spectrogram,
i.e. where elements are the times at bin centers"""
import numpy as np
def timebin_dur_from_vec(time_bins, n_decimals_trunc=5):
"""compute duration of a time bin, given the
vector of time bin centers associated with a spectrogram
... |
e3be15d704da345680f8c519184bf28e59e57cb98b5da8a6d0b4b147abde9ab5 | Python | 1,257 | 34 | """Checkpoint resume must not graft cached accuracies onto the wrong rows."""
import numpy as np
from crossda.core.method_bank import generate_method_bank
from crossda.core import workers as W
def test_checkpoint_resumes_when_method_bank_matches(tmp_path):
mb = generate_method_bank("smoke")
cached = mb.copy... |
ec2362ea49568650d0bb2ff08cbb5925cb6813a69ad71eb1082e31c121f13223 | Python | 1,257 | 40 | import argparse
import copy
import time
import neuroglancer
import neuroglancer.cli
from example import add_example_layers
if __name__ == "__main__":
ap = argparse.ArgumentParser()
neuroglancer.cli.add_server_arguments(ap)
args = ap.parse_args()
neuroglancer.cli.handle_server_arguments(args)
view... |
6ee7e33c7f0392073ecd5cf43765492d2be44683238e8e4d3ecdef8fe1dc2836 | Python | 1,262 | 32 | import torch
from pathlib import Path
import gdown
import json
from rinalmo.data.alphabet import Alphabet
from rinalmo.model.model import RiNALMo
from rinalmo.config import model_config
DEFAULT_CACHE_DIR = Path.home() / ".cache" / "rinalmo_pretrained"
with open(Path(__file__).parent / "resources" / "model2gdisk.json... |
d1dccc88b7c55a19312a0b55b180848e5dbd35cb978a2e3e33d0ad57a8b9ea07 | Python | 1,262 | 49 | #!/usr/bin/env python3
import argparse
import os
import shutil
import subprocess
import sys
script_dir = os.path.dirname(sys.argv[0])
src_dir = os.path.join(script_dir, "ext/src")
dest_openmesh_dir = os.path.join(script_dir, "ext/third_party/openmesh/OpenMesh")
ap = argparse.ArgumentParser()
ap.add_argument("openmes... |
1f9eab770ba5c6fc1193be4c3af039d71300706693e0e16883a27b7cda31a068 | Python | 1,263 | 37 | import numpy as np
import scipy
class ObjectDetector:
def __init__(self, size=3, peak_multiply=1000):
self.size = size
self.peak_multiply = peak_multiply
print(self.size, self.peak_multiply)
def get_mask(self, img):
img = np.float32(img)
normalized = img ... |
4d09a9e2d9d7bb04918f32c6ace625d83b251273f04766e7490014d7a7915c4b | Python | 1,263 | 30 | """
Function to compute spatial weights for the neighborhood extensions.
"""
def spatial_weights(adata_sp, standardized, self_inclusion):
import collections
import sklearn
import libpysal
import numpy as np
if not set(["spatial_connectivities", "spatial_distances"]).issubset(set(adata_sp.obsp.keys... |
64d7641e9e7371331fe33405e2c8c112daf12d59bd760bb23292ad642520f0fc | Python | 1,263 | 34 | from __future__ import annotations
from typing import TYPE_CHECKING
from scvi.utils import error_on_missing_dependencies
if TYPE_CHECKING:
from ._experiment import AutotuneExperiment, ScibTuneReportCheckpointCallback
from ._tune import run_autotune
__all__ = ["AutotuneExperiment", "ScibTuneReportCheckpointC... |
9230f2e20a50eaa087b588aef8576017d4ffe7b2c720d390775ec05b64d5ba14 | Python | 1,263 | 47 | import os
import tarfile
import pytest
import scanpy as sc
from scvi.data import dataset_10x, organize_cite_seq_10x
from .utils import unsupervised_training_one_epoch
def test_populate_and_train_one_v1(save_path):
sp = os.path.join(save_path, "10X")
dataset = dataset_10x(
dataset_name="cd4_t_helper... |
2462097bd840dde601f48e2c2b1bb3c553189061d81f44e374036cfd31150d01 | Python | 1,268 | 42 | from argparse import ArgumentParser
from pathlib import Path
import nibabel as nib
import numpy as np
import pandas as pd
def parse_args():
parser = ArgumentParser()
parser.add_argument("residual_dir", type=Path)
parser.add_argument("atlas", type=Path)
parser.add_argument("output", type=Path)
par... |
6c09c225f3e306affaf5afb332f18c05e52360ffd85885440c56c9ce99fbb2cf | Python | 1,268 | 51 | import warnings
from scvi import settings
from scvi.utils import error_on_missing_dependencies
from . import utils
from ._amortizedlda import AmortizedLDA
from ._autozi import AUTOZI
from ._condscvi import CondSCVI
from ._destvi import DestVI
from ._linear_scvi import LinearSCVI
from ._multivi import MULTIVI
from ._p... |
9dd631f3a9facd23af916dfeadb8cb7ae130e3742515b2296ae6bcda8bf93fb6 | Python | 1,271 | 53 | from __future__ import annotations
import os
from pathlib import Path
from PySide6.QtGui import QFont, QFontDatabase
from src.gui.framework.qt_view_styles import (
APP_FONT_FAMILY,
APP_FONT_POINT_SIZE,
MONO_FONT_FAMILY,
)
FONT_FILES = (
"DejaVuSans.ttf",
"DejaVuSans-Bold.ttf",
"DejaVuSansMon... |
66fd51a56431e64cecd63c4a53f790002a4ca87534b91fc91f44f3f133f82dcf | Python | 1,272 | 32 | from argparse import ArgumentParser
from transformers.commands import BaseTransformersCLICommand
def download_command_factory(args):
return DownloadCommand(args.model, args.cache_dir, args.force)
class DownloadCommand(BaseTransformersCLICommand):
@staticmethod
def register_subcommand(parser: ArgumentPa... |
cdd1a5820cc879943352edd7a69d66a29e3ba5ee9c25dd344c72017188c53f23 | Python | 1,272 | 55 | import anndata
import numpy as np
import pandas as pd
from anndata import AnnData
import novae
domains = [
["D1", "D2", "D3", "D4", "D5"],
["D1", "D1", "D2", "D2", "D3"],
["D1", "D1", "D1", "D2", np.nan],
]
spatial_coords = np.array([
[[0, 0], [0, 1], [0, 2], [3, 3], [1, 1]],
[[0, 0], [0, 1], [0,... |
66071efe0e12f5432f9f590ba9395bd997a64fdd85067dfd139bc0bd43a32517 | Python | 1,273 | 42 | import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
def plot_prob_density_func(csv_path, col_name, out_path):
# Load the CSV file
data = pd.read_csv(csv_path) # Replace with your file path
# Assuming the predicted probabilities are in a column called 'predicted_probability'
pred... |
b5f5f262492f9dc297c467e33a50bdb14257e54e52b7e195e0e1ac5ca5c9da53 | Python | 1,273 | 35 | """Used to operate on a sub-graph of a larger GO DAG."""
from collections import defaultdict
__copyright__ = "Copyright (C) 2016-2018, DV Klopfenstein, H Tang, All rights reserved."
__author__ = "DV Klopfenstein"
class GODagSmall(object):
"""Contains a sub-graph of the original obo from geneontology.org."""
... |
3edc6b0e5c09797480e321bd9b2d1fb2aeb7f71aa79a5732564b1893f54770ac | Python | 1,274 | 44 | import os
import re
import pandas as pd
import requests
from bs4 import BeautifulSoup
from tqdm import tqdm
import config
import enzymes
with open(config.species_list) as species_list:
bacteria = set(s.strip() for s in species_list.readlines())
for enzyme in tqdm(enzymes.enzymes):
references = []
url =... |
e7c5264163ba16dd818266e390dcd114ef01043911dff379165f89a1ee51deba | Python | 1,275 | 33 | # Shared Config class
class Config(object):
"""
A shared configuration class for managing device settings, data paths,
and training parameters in SemanticST.
Attributes:
use_cuda (bool): Whether to use CUDA (GPU) acceleration. Default is True.
device (str): The computing device to be ... |
9079eb45c796c9120b2c6b5f0b027f308cbb87e1baa698f53a39664ed50c4952 | Python | 1,276 | 63 | """
Neural Network Models for Medical Imaging
Core model architectures including transformers, MIL pooling, projection heads,
and positional encodings for 3D medical imaging.
"""
# Transformer Components
from .vit import (
SelfAttention,
CrossAttention,
Block,
TransformerEncoder,
VisionPredictor,
... |
cbee68e094dd27c7cd5f1baf79daa4883af7a50a9ba2f6d190e183281804909a | Python | 1,276 | 47 | # Copyright 2021 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
e76029c065a5982cb5f260984025b53efef4f44040ea6674d4b2417cde0ba2b7 | Python | 1,276 | 49 | """Classes to deal with codon sequences."""
import abc
from Bio.Seq import Seq
from typing import Union, List
def _split_into_codons(seq: str):
"""Yield successive 3-letter chunks of a string/sequence."""
for i in range(0, len(seq), 3):
yield seq[i:i + 3]
class Sequence(abc.ABC):
"""Abstract bas... |
e2bad14912c674071d25cd91dce1b42b1a17898e85b56fe133182838ee3b18cc | Python | 1,279 | 40 | # 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.
import torch.optim
from . import LegacyFairseqOptimizer, register_optimizer
@register_optimizer("adagrad")
class Adagrad(LegacyFairseqOptim... |
425dce87ccb86db760e331053d355b09a820219a8eb6a0d2a97c00089dde77e2 | Python | 1,280 | 50 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import ClassVar
from cleo.helpers import argument
from tomlkit.items import AoT
from poetry.console.commands.command import Command
if TYPE_CHECKING:
from cleo.io.inputs.argument import Argument
class SourceRemoveCommand(Command)... |
fddbfdd111c8e3cf9892c002234aa2ee78380f1075700b1bf05ff167ee61ba53 | Python | 1,281 | 35 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from typing import Any, Dict, Type
import pytest
import torch
from mattergen.diffusion.corruption.multi_corruption import MultiCorruption
from mattergen.diffusion.corruption.sde_lib import SDE
from mattergen.diffusion.tests.conftest import SDE_... |
ed7d013ccca3a83dc32ccdb03d6f034ba64a627dc9eb240df94520005f19f711 | Python | 1,283 | 38 | import math
import unittest
from unittest.mock import patch
from pyecharts import options as opts
from pyecharts.charts import Line3D
from pyecharts.faker import Faker
class TestLine3DChart(unittest.TestCase):
@patch("pyecharts.render.engine.write_utf8_html_file")
def test_line3d_base(self, fake_writer):
... |
ab0efeb6a5bcdbfdea1f4c0842b5bc18ba48bb93f0bb79868e3352711ffbf9eb | Python | 1,284 | 35 | import importlib
import os
from beartype.typing import Any
from omegaconf import OmegaConf
def resolve_omegaconf_variable(variable_path: str) -> Any:
"""Resolve an OmegaConf variable path to its value."""
# split the string into parts using the dot separator
parts = variable_path.rsplit(".", 1)
# ge... |
bd7c581eda6ffceee4bae55a09cde3b6edce3431a5083c91b700575874cbabbc | Python | 1,284 | 28 | from argschema import ArgSchema, ArgSchemaParser
from argschema.schemas import DefaultSchema
from argschema.fields import Nested, InputDir, String, Float, Dict, Int
from ...common.schemas import EphysParams, Directories, CommonFiles
class ExtractFromNpxParams(DefaultSchema):
npx_directory = String(help='Path to N... |
0c00f22e51d312dd115c5460b42700a1153a0cec70e0c5d4d108b6d1b28cccad | Python | 1,285 | 46 | import argparse
from gsMap import __version__
from gsMap.config import cli_function_registry
def main():
parser = create_parser()
try:
import argcomplete
argcomplete.autocomplete(parser)
except ImportError:
pass
args = parser.parse_args()
if args.subcommand is None:
... |
6fcce53559f49dd9d85d8e1f2b9542433d19b530ec5620df7db9b3c8f97a3639 | Python | 1,285 | 48 | #!/usr/bin/env python
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_fu... |
78f83d69c4b7ce2a499d77c19e04cf0a3aa17257c347c886d4cf534249983b4a | Python | 1,285 | 43 | # 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.
import torch
from torch import nn
from fairseq.distributed import utils
class TPUDistributedDataParallel(nn.Module):
def __init__(self,... |
e90be7bf695fef64133aace60830f9aef4366bf2986475e858ae75e482f21b87 | Python | 1,286 | 45 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from cleo.exceptions import CleoNoSuchOptionError
from poetry.console.commands.sync import SyncCommand
# import all tests from the install command
# and run them for sync by overriding the command fixture
from tests.console.commands.... |
16bb95bbaf2a6fbfc1d99d1ac988066b22ec7fe8c5506ed6c90fef572b87f26d | Python | 1,287 | 23 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_bal_i0_alb_aug_TIME(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: int, dat... |
2f34061291bb9aa169b007dacad5743185461dcbc6adde0a7907b962dc2c4c22 | Python | 1,287 | 30 | #!/usr/bin/env python3
# MIT License
#
# Copyright 2023 Broad Institute
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use... |
4b1ee80a0872010ea1d00aabc7b72cad46351c4408fa4b52bfa7a6c27187f36d | Python | 1,287 | 23 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_bal_i0_nnunet_aug(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: int, datas... |
a59d7f0dcd6314a9fae9fb3492fb72a10c554ad5d9f72c1d3d47658c97da33b0 | Python | 1,287 | 27 | import os
import random
# dior
# input_folder_path = r'D:\FangX24\code\LO-Det-main\mnt\Datasets\DIOR\ImageSets\train_s1_cat\novel_all'
# output_folder_path = r'D:\FangX24\code\LO-Det-main\mnt\Datasets\DIOR\ImageSets\random4\novel10'
# nwpu
input_folder_path = r'D:\Projects\LFODet-main\mnt\Datasets\NWPU\ImageSet... |
e4358a80d685e14f7c1bd81e2c593b8f2ae0af92c022a4e230c8deef245134df | Python | 1,287 | 48 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import
from __future__ import division
from _... |
363491f7f10b3f672d2fe4d8b3f882bdd3036bd3d689c8aa1445b1dcfb4c1aca | Python | 1,288 | 33 | import pytest
import torch
import scvi.model.base._rnamixin as rnamixin_module
from scvi.data import synthetic_iid
from scvi.model import SCVI
def _make_trained_model(gene_likelihood: str = "nb"):
adata = synthetic_iid()
SCVI.setup_anndata(adata, batch_key="batch")
model = SCVI(adata, gene_likelihood=gen... |
abf1d38146b0896095d72cdb0a3301cdb0ad835bcdf4bdff33f6ed80d16bbd52 | Python | 1,289 | 45 | #!/usr/bin/env python
# Author_and_contribution: Jieran Sun & Mark Robinson; implmented method
# Author_and_contribution: Peiying Cai; created template
# Author_and_contribution: ENTER YOUR NAME AND CONTRIBUTION HERE
import argparse
import pandas as pd
from pathlib import Path
# TODO adjust description
description =... |
49e0365fe13db91892e805923a24efc529f6667d5ad1b81874fc6a228c4031fe | Python | 1,290 | 40 | import sys
import argparse
from tqdm import tqdm
from build_emov_translation_manifests import dedup, remove_under_k
if __name__ == "__main__":
"""
this is a standalone script to process a km file
specifically, to dedup or remove tokens that repeat less
than k times in a row
"""
parser = argpar... |
a35e674a597482428cb695fa6d207b3fea69091def9539b5d9f9f08c275f7c5e | Python | 1,290 | 40 | """TensorBoard scalar logging for manual training loops (DLBase-style train/*, val/* names)."""
from __future__ import annotations
import os
from typing import Any, Dict, Optional
try:
from torch.utils.tensorboard import SummaryWriter
except ImportError: # pragma: no cover
SummaryWriter = None # ... |
8f367a2951fd8cfd61bdfb13890bb26754e98744e274347539f3f20487e2e691 | Python | 1,291 | 23 | import os
import torch
from nnunetv2.training.nnUNetTrainer.variants.pathology.nnUNetTrainer_WSD_undefined_dataloader import nnUNetTrainer_WSD_undefined_dataloader
class nnUNetTrainer_WSD_bal_i0_nnunet_aug_TIME(nnUNetTrainer_WSD_undefined_dataloader):
def __init__(self, plans: dict, configuration: str, fold: int, ... |
872630230a38fad409b3e2cebb402957a28a7298c11db91728754b4ff860688f | Python | 1,293 | 35 | # 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.
import torch.nn as nn
from .learned_positional_embedding import LearnedPositionalEmbedding
from .sinusoidal_positional_embedding import Sinus... |
3fc74c92ba6b11ea853ca9837f314a89c97a7d0536d087f3065d54d79b92c723 | Python | 1,294 | 50 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import Any
from typing import ClassVar
from cleo.commands.command import Command as BaseCommand
from cleo.exceptions import CleoValueError
if TYPE_CHECKING:
from poetry.console.application import Application
from poetry.poetry i... |
4e9613684a3ea5377db00446ed868887d41f8fc476921050385927cad5aa9a21 | Python | 1,294 | 39 | # 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 dataclasses import dataclass
from fairseq.data.legacy.masked_lm_dictionary import MaskedLMDictionary
from fairseq.tasks.translation impor... |
b834b6c9655f135bd9efaed5e8fdd9ef8f41a67d3fca9137d286c52de5a92670 | Python | 1,294 | 33 | import argparse
import json
from collections import defaultdict
import os
import soundfile as sf
from tqdm import tqdm
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Example argument parser')
parser.add_argument('--exp', type=str)
parser.add_argument('--dump', type=str)
args =... |
9a1b4f418fa3967d5aefc2435d1da9d7eb028a867e881df6bf388b8181f2f29f | Python | 1,295 | 34 | import torch.nn as nn
import torch
# using in EffcientDet
class WeightedFeatureFusion(nn.Module): # weighted sum of 2 or more layers https://arxiv.org/abs/1911.09070
def __init__(self, layers, weight=False):
super(WeightedFeatureFusion, self).__init__()
self.layers = layers # layer indices
... |
3542ca5fbae580769b12704af87b347f0b28806d961810d1b12f0eb33aa0166c | Python | 1,296 | 26 | import matplotlib.pyplot as plt
import numpy as np
plt.style.use(['science','nature'])
x_ax = np.array([0.00,0.01,0.05,0.10,0.15,0.20,0.25])
y_ax = np.array([[0.9566, 0.9566, 0.9566, 0.9566, 0.9566, 0.9566, 0.9566, 0.9566, 0.9566, 0.9566],
[0.957, 0.9578, 0.9568, 0.9554, 0.9576, 0.957, 0.956, 0.9556,... |
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