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import torch x = torch.load("protein_dictionary_prose.pt")
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from .cli import main if __name__ == "__main__": main()
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from ray.train._internal.session import * # noqa: F401,F403
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from .transforms_wav import * from .transforms_stft import *
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from .pipeline_dance_diffusion import DanceDiffusionPipeline
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from .fmm3d import hfmm3d,lfmm3d,h3ddir,l3ddir,comperr,Output
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from typing import TypeVar InputSplit = TypeVar("InputSplit")
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from ldctinv.pretrained.load_pretrained import load_pretrained
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from .datahub import DataHub from .dictionary import Dictionary
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from .equiformer_v2.equiformer_v2_oc20 import EquiformerV2_OC20
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# ruff: noqa: F401 from . import eval_utils from . import utils
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try: import unittest2 as unittest except: import unittest
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r"""Bulk omics I/O helpers (placeholder namespace).""" __all__ = []
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__all__ = ["BUM", "cluster", "neuropowermodels", "peakdistribution"]
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from .articulation import PreferenceArticulator, load_demonstrations
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from .decoder import * from .gcn import * from .imrpoved_gcn import *
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from .merge_det_results import merge_preds __all__ = ['merge_preds']
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from .decoder import * from .tasks import * from .objectives import *
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from setuptools import setup setup(setup_requires=["pbr"], pbr=True)
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r""" Graph convolution network """ from .combnet import CombUnweighted
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from lisa.cli.cli import main if __name__=="__main__": main()
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# Copyright (c) 2021 Qualcomm Technologies, Inc. # All Rights Reserved.
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from ci.raydepsets.cli import cli if __name__ == "__main__": cli()
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from .heart import HeartDataset dataset_dict = {'heart': HeartDataset}
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from ci.ray_ci.tester import main if __name__ == "__main__": main()
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from ci.ray_ci.builder import main if __name__ == "__main__": main()
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from . import predictPeak from . import allocation __version__ = '1.2.0'
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from .tabular import TabularDataset __all__ = [ "TabularDataset", ]
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from .batch_pixel_data import BatchPixelData __all__ = ['BatchPixelData']
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""" This package implements the data storage and manipulation framework. """
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from .dffpn import DFFPN from .ufpn import UFPN __all__ = ['DFFPN', 'UFPN']
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from hic3defdr.analysis.constructor import HiC3DeFDR __all__ = ['HiC3DeFDR']
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from .TxData import TxData from .TxGNN import TxGNN from .TxEval import TxEval
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#from samri.examples import functional_connectivity #functional_connectivity()
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from .auxiliaries import * from .metrics import * from .training_utils import *
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from .config import Config from .core import from_dict from .exceptions import *
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AGGREGATOR_AGENT_METRIC_PREFIX = "aggregator_agent" CONSUMER_TAG_KEY = "consumer"
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import rlexp.exp.continual import rlexp.exp.core from .core import run_training
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def unique(list1): unique_list = (list(set(list1))) return unique_list
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from .gene_graph import gene_graph from .adjacency_matrix import adjacency_matrix
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from .mel import Mel from .pipeline_audio_diffusion import AudioDiffusionPipeline
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import warnings warnings.filterwarnings('ignore') from . import tl from . import pl
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from .NER_processing import nlp, disease_service, chemical_service, genetic_service
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from ._plotting import plot_differentially_flowing_signals, plot_intercellular_flows
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from .up_sample import UpConvBlock, Upsample __all__ = ['Upsample', 'UpConvBlock']
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from .detectors import * # noqa: F401,F403 from .necks import * # noqa: F401,F403
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from .basic_image_dataset import BasicImageDataset __all__ = ['BasicImageDataset']
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# -*- coding: utf-8 -*- """ Created on Mon Jun 3 12:47:13 2024 @author: jpv88 """
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from palmnet.cli import main if __name__ == "__main__": raise SystemExit(main())
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import os ROOT_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir))
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from .base import * from .impulse import impulse, impulse_tests from .simulate import *
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from .charmm import EndstateCorrectionCHARMM from .amber import EndstateCorrectionAMBER
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#!/usr/bin/env python from .create_gt import create from .comparison import Comparison
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r""" This package contains a collection of low level tools used throughout *mozaik*. """
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from imports import * class Base(BaseTester): modulepath = 'ngs_mapper.graph_times'
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#!/usr/bin/env ipython from caiman.tests.comparison import create_gt create_gt.create()
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from .wgcna import * from .utils import * from .geneExp import * from .comparison import *
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from django.apps import AppConfig class AnnotateConfig(AppConfig): name = 'annotate'
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from .alif import alif_forward, alif_recurrent from .lif import lif_forward, lif_recurrent
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# Ultralytics YOLO 🚀, GPL-3.0 license from . import v8 __all__ = 'v8', # tuple or list
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from .ase_dataset import AseReadDataset from .ase_dataset_attribute import AseReadDatasetAttr
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from .edit_data_preprocessor import EditDataPreprocessor __all__ = ['EditDataPreprocessor']
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from .train import MolTrain from .predict import MolPredict from .predictor import UniMolRepr
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"""A file dependency for testing working_dir behavior with Ray Tune.""" def foo(): pass
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from .random_forest import RandomForest, rf_classify from .adjudicate_sv import adjudicate_SV
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TEST_MODULE_ENVIRONMENT_KEY = "RAY_DASHBOARD_MODULE_TEST" if __name__ == "__main__": pass
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from ._utils import get_top_gem_genes,get_top_pyliger_genes,get_top_nmf_genes,get_top_nsf_genes
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import ray NIL_NODE_ID = ray.NodeID.nil().hex() RETRY_GET_ALL_ACTOR_INFO_INTERVAL_SECONDS = 1
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# define the bids root only once in the config bids_root = '/data/raw/hirsch/RestHoldMove_anon/'
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"""Join subcellular Visium HD bins into cells""" __version__ = "0.3.3" from .bin2cell import *
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# test_main.py import data_assimilation as da def test_hello(capfd): x=2 assert x==2
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from .state import State, DenseState from .variational import Variational, Functional, CombineVs
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from .dataset_wrappers import DatasetWithGTImageWrapper __all__ = ['DatasetWithGTImageWrapper']
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# Sample Test passing with nose and pytest def test_pass(): assert True, "dummy sample test"
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from .tags import TAGS from .descriptions import DESCRIPTIONS __all__ = ["TAGS", "DESCRIPTIONS"]
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# Version of deepinterpolation package. Should match the version in setup.py __version__ = "0.2.0"
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from .external import lack logger_manager = lack.LoggerManager("Spaco", "Spaco-temp-timer-logger")
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from ray._private.thirdparty.pynvml.pynvml import * # nvdia-ml-py version __version__ = "13.580.65"
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"""The controller module handles all user interaction with the package (console, jupyter, etc.)."""
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threshold = "100" SEQ_LEN="800" QUARTER_SEQ_LEN = int(SEQ_LEN) // 4 HALF_SEQ_LEN = int(SEQ_LEN) // 2
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""" Provides Operators working on single tensors. """ from .tensor import np_one_hot, torch_one_hot
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r""" SLAT (Spatial-Linked Alignment Tool) """ from . import viz from . import model name = "scSLAT"
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from ray.data._internal.block_batching.block_batching import batch_blocks __all__ = ["batch_blocks"]
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from .visualization_hook import EnhanceDetVisualizationHook __all__ = ['EnhanceDetVisualizationHook']
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def run(): raise Exception("Script failed with exception !") if __name__ == "__main__": run()
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"""Python port of the MetaboLiteLearner repository.""" __all__ = ["__version__"] __version__ = "0.1.0"
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# -*- coding: utf-8 -*- __version__ = '2.1.1' __version_info__ = tuple(map(int, __version__.split(".")))
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from setuptools import find_packages, setup setup( name="m2snn", packages=find_packages(), )
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import torch class Squeezer(torch.nn.Module): def forward(self, x): return x.squeeze(dim=-1)
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from .harmony import Harmony, run_harmony, get_device from .lisi import compute_lisi __version__ = '0.2.0'
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from .nec_network import NEC from .sf_nec_network import SFNEC from .replay_buffer import ExperienceReplay
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__version__ = "1.3.2" __author__ = "Palantir development team" __author_email__ = "manu.talanki@gmail.com"
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from .wavimgprm import WavimgPrm from .msaprm import MsaPrm from .commands import * __version__ = '0.1.25'
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from .deconvolution import Deconvolution,ScadenDeconvolution from .simulation import generate_simulated_data
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import abc class ModelDef: @abc.abstractmethod def get_model(self, *args, **kwargs): pass
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QUALITATIVE_COLORSET = ["#000000", "#E69F00", "#56B4E9", "#009E73","#F0E442", "#0072B2", "#D55E00", "#CC79A7"]
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from ._highly_variable_genes import highly_variable_genes from ._normalization import normalize_pearson_residuals
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from .lark_hook import LarkHook from .summarize_hook import SummarizeHook __all__ = ['LarkHook', 'SummarizeHook']
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from .datasets import * from .flashes import * from .moving_bar import * from .dots import * from .sintel import *
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""" scoreCT: Automated cell type annotation in scRNA-seq data """ from .scorect_api import * __version__ = '0.0.2'