Saravanan666/pypi-org huggingface dataset:
Package: asmai
Asmai: (Al’asma’i) Arabic semantic analysisمكتبة الأصمعي الدلاليةAsmai: (Al’asma’i) Arabic semantic analysis library for Pythonasmai logoPyPI - DownloadsDeveloppers: Taha Zerrouki:http://tahadz.comtaha dot zerrouki at gmail
dot comFeaturesvalueAuthorsAuthors.mdRelease0.1LicenseGPLTrackerlinuxscout/asmai/IssuesSourceGithubFeedbacksCommentsAccounts[@Twitter](https://twitter.com/linuxscout)DescriptionAsmai: (Al’asma’i) Arabic semantic analysis library for Pythonمزايا:استخلاص ثنائيات الكلمات التي تحمل دلالات من نوع : (فاعلية، مفعولية،
إضافة)installpipinstallasmaiUsageimportpipinstallasmaiTestimportasmai.anasemasasmtext=u"يعبد الله منذ أن تطلع الشمس"result=[]anasem=asm.SemanticAnalyzer()result=anasem.analyze_text(text)# the result contains objetsanasem.pprint(result)Extract semantic relation, display only found relations>>>importpprint>>>sem_result=anasem.display_sem(result)>>>pprint.pprint(sem_result)[[['الشَّمْسُ','تَطْلُعَ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلُعُ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلُعْ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلَعَ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلَعُ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلَعْ','شَمْسٌ','طَلَعَ','Subject']]]Extract semantic relation, display all words and tags>>>sem_result=anasem.display_sem(result,all=True)>>>pprint.pprint(sem_result)[('يعبد','O',[]),('الله','O',[]),('منذ','O',[]),('أن','O',[]),('تطلع','B',[]),('الشمس','I',[['الشَّمْسُ','تَطْلُعَ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلُعُ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلُعْ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلَعَ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلَعُ','شَمْسٌ','طَلَعَ','Subject'],['الشَّمْسُ','تَطْلَعْ','شَمْسٌ','طَلَعَ','Subject']])]>>>convert to pandas ```python >>> import pandas as pd >>> >>> #
flatten the result … df = pd.DataFrame(anasem.decode(result)) >>>
print(df.head()) action affix affix_key forced_word_case …
unvocalized unvoriginal vocalized word 0 -ي– -ي–|المضارع
المنصوب:هو:y False … يعبد عبد يُعَبِّدَ يعبد 1 -ي– -ي–|المضارع
المجهول المجزوم:هو:y False … يعبد عبد يُعَبَّدْ يعبد 2 -ي–
-ي–|المضارع المجهول:هو:y False … يعبد عبد يُعَبَّدُ يعبد 3 -ي–
-ي–|المضارع المعلوم:هو:y False … يعبد عبد يُعَبِّدُ يعبد 4 -ي–
-ي–|المضارع المجزوم:هو:y False … يعبد عبد يُعَبِّدْ يعبد[5 rows x 50 columns] >>> df.to_csv(“output/test.csv”, encoding=”utf8”,
sep=”:raw-latex:’t’”)[requirement]1- pyarabic
2. sqlite
3. sylajoneData Structure:Semantic databaseCREATETABLEsqlite_sequence(name,seq);CREATETABLE"derivations"("id"INTEGERPRIMARYKEYAUTOINCREMENTNOTNULLUNIQUE,"verb"varcharNOTNULL,"transitive"BOOLNOTNULLDEFAULT1,"derived"VARCHARNOTNULL,"type"VARCHARNOTNULL);CSV Structure:Derivattionid : id unique in the databaseverb : vocalized collocationtranstive : if the verb is transitivederived : derived word from verb numbertype : typeSemantic relationsCREATETABLE"relations"("id"INTEGERPRIMARYKEYNOTNULL,first" VARCHAR NOT NULL  DEFAULT ('') ,
    "second" VARCHAR NOT NULL  DEFAULT ('') ,
    "rule"VARCHARNOTNULLDEFAULT(0));CSV Structure:id : id unique in the databasefirst: first wordsecond: second wordrule : the extraction rule number :
Package: asm-api
<h1>Alphalogic Service Manager API
<a href=”https://asm_api.readthedocs.io”>
<img src=”https://readthedocs.org/projects/asm_api/badge/?version=latest” alt=”Documentation Status” />
</a>
</h1>
The official API for Alphalogic Service Manager. <a href=”https://asm_api.readthedocs.io”>   Documentation</a>
Package: asmbench
asmbenchA benchmark toolkit for assembly instructions using the LLVM JIT.UsageTo benchmark latency and throughput of a 64bit integer add use the following command:python-masmbench 'add {src:i64:r}, {srcdst:i64:r}'To benchmark two instructions interleaved use this:python-masmbench 'add {src:i64:r}, {srcdst:i64:r}' 'sub {src:i64:r}, {srcdst:i64:r}'To find out more add-hfor help and-vfor verbose mode.
Package: asmchip8
asmchip8is an assembler for CHIP-8.  It is free software under the GNU
AGPLv3+ license.The author and maintainer is Mariano Street <mctpyt@proton.me>.DependenciesRuntime dependency: Python 3.10 or later.Install dependency: Flit.Test dependencies: PyTest, PyEnv, Test.DevelopmentHow to run?From the project directory, run:$ ./src/asmchip8/main.py <input>For information on command-line options, seeasmchip8(1)or run with-hor--help.How to install?Part of the project can be installed via Flit:$ flit installHow to run the test suite?From the project directory, run:$ PYTHONPATH=src pytest testsIf you want a more verbose output, add the-voption.PyTest is required to be installed.  One way to handle this is via Tox: see
the next section.How to test different Python versions?Use PyEnv and Tox.For example, to test 3.11:$ pyenv install 3.11-dev
$ PATH=$PATH:$HOME/.pyenv/versions/3.11-dev/bin tox -e py311When testing via Tox, it is not necessary to have PyTest installed on the
system.  Tox installs it automatically in an isolated environment.Additional documentationTwo manpages are provided with the project:asmchip8(1)Located atdoc/asmchip8.1.  It documents theasmchip8command.asmchip8(5)Located atdoc/asmchip8.5.  It documents the assembly language.They can be read without installing like this, from the project directory:$ man -l doc/asmchip8.1
$ man -l doc/asmchip8.5In addition, the source code contains some comments and docstrings.
Package: asm-cli
<h1>Alphalogic Service Manager CLI
<a href=”https://asm_cli.readthedocs.io”>
<img src=”https://readthedocs.org/projects/asm_cli/badge/?version=latest” alt=”Documentation Status” />
</a>
</h1>
The official CLI for Alphalogic Service Manager. <a href=”https://asm_cli.readthedocs.io”>   Documentation</a>
Package: asmclient
An exporter about prometheus, written in Python, mainly provides monitoring of api data functions, as follows:
     1. Request quantity
     2. Request duration per second
     3. The number being requested
     4. The last request took timeFor details, please see:https://github.com/prometheus/client_pythonUsage example:“””from apimon import ApiMonitorapimonitor = ApiMonitor(app_name=”your app name”)
apimonitor.setup_metrics(app)  # your app object instance“””
Package: asmd
Audio-Score Meta-DatasetASMD is a framework for installing, using and creating music multimodal
datasets including (for now) audio and scores.This is the repository for paper [1]Read more in thedocs.To install:pip install asmdTo install datasets:python-masmd.installTo import API:from asmd import asmdOther examples in the paper!ChangelogVersion 0.5Improved inference of misalignmentsImproved the reproducibility of artificial dataImproved the documentationAddedASAPgroup inMaestro: broken backward compatibilityAddedscorefor the original scoreAdded midi note matching based on EITA methodAdded missing and extra notesGeneral refactoringAdded functions for set operations among datasets (union, intersections,
complement and subsampling)Various fixesVersion 0.4# SkippedVersion 0.3Fixed MIDI values ([0, 128) for control changes and pitches)Fixed metadata error while reading audio filesFixed pedaling for tracks that have no pedalingFixed group selectionAddedget_songsImproved initialization ofDatasetobjectsImproved documentationVersion 0.2.2-2Fixed major bug in install scriptFixed bug in conversion toolRemoved TRIOS dataset because no longer availableUpdated ground_truthVersion 0.2.2ImprovedparallelfunctionImproved documentationVarious fixings inget_pedalingVersion 0.2.1Addednframesutility to compute the number of frames in a given time lapseAddedgroupattribute to each track to create splits in a dataset
(supported in only Maestro for now)Changed.pyxto.pywith cython in pure-python modeVersion 0.2Addedparallelutility to run code in parallel over a while datasetAddedget_pianorollutility to get score as pianorollAddedsustain,sostenuto, andsoftto model pedaling informationAdded utilitiesframe2timeandtime2frameto ease the developmentAddedget_audio_datato get data about audio without loading itAddedget_score_durationto get the full duration of a score without
loading itAdded another name for the API:from asmd import asmdDeprecatedfrom asmd import audioscoredatasetChanged thegenerate_ground_truthcommand line optionsEasier to generate misaligned dataImproved documentationRoadmapAdd matching of same music piece among different datasetsAddedtorch.DatasetDumpfor preprocessing datasets and use them in pytorchAdd new modalities (video, images)Add other datasetsRefactoring of thefilterfunction (it’s a bit long now…)Cite us[1]  Simonetta, Federico ; Ntalampiras, Stavros ; Avanzini, Federico:ASMD: an automatic framework for compiling multimodal datasets with audio and scores. In: Proceedings of the 17th Sound and Music Computing Conference. Torino, 2020arXiv:2003.01958—Federico Simonettahttps://federicosimonetta.eu.orghttps://lim.di.unimi.it
Package: asmlib
Tooling package for the computer architecture course (aka Rechnerorganisation) atGraz University of Technology.This package provides utilities and tooling for working with textual and binary assembly variants.
In more detail, we provide comparable simple implementations of standard tools (e.g., assemblers,
instruction set simulators) that are required for experimenting with self-written processors.
Given that the tools are used for teaching, the focus of the package is correctness and
extensibility. As instruction set architecture, Princeton’sTOY, incl. various extensions, and a subset of theRISC-V RV32Iare currently supported.Quick and Dirty Usage of the ToolsFor fast experimentation, executable entry points for the most important tools liketoyasm-ng.pyandtoysim-ng.pyare provided next to this README. Subsequently, it is possible to directly
use these applications like in one of the following examples:$python3./relative/pkg_path/toyasm-ng.pysome_input_file.asm$python3/absolute/pkg_path/toyasm-ng.pysome_input_file.asmGiven that the entry points are marked as executable (i.e.,chmod +x ...) and have a propershebang, on unix-like systems, also direct
execution is possible:$./relative/pkg_path/toyasm-ng.pysome_input_file.asm$/absolute/pkg_path/toyasm-ng.pysome_input_file.asmFinally, when the root directory of this package is part of thePATH(e.g.,exportPATH=/absolute/pkg_path:$PATH) environment variable, execution of the tools
simply by name is working too.$toyasm-ng.pysome_input_file.asmProper Installation and Usage of the Packageasmlibis a proper python package and can also be installed via the standard package manager
(e.g.,pip3 install--user/absolute/pkg_path). Note that, when development on to the package is
planned, installing the package as editable by adding the-ecommand line flag is recommended.
Additionally,virtual environments(e.g.,python3-mvenv _venv && source_venv/bin/activate) can be used too.Either way, this automatically installs the entry points into the correct directories and the tools
can directly be used on the command line (i.e.,toyasm-ng.pysome_input_file.asm).Building the Sphinx DocumentationWhen Sphinx is installed (i.e.,pip3 install sphinxsphinx-autodoc-typehints), the HTML API
documentation for this package can be built via the followingsphinx-buildinvocation:$sphinx-builddocdoc/_build/htmlAlternatively, thesphinxcommand on the setup.py file can be used.$python3./setup.pysphinxEither way, the API documentation gets automatically generated by executingsphinx-apidocfirst.
The resulting HTML output can be found in thedoc/_build/htmldirectory.
Package: asmog
Python Client for interacting withAmpio Smog SensorsThis module is not officially developed nor surrported by Ampio.InstallationThis module is available from thePython Package Index.$pip3installasmogUsageThe fileexample.pycontains an example about how to use this module.DevelopmentFor development is recommended to use avenv.$python3.6-mvenv.$sourcebin/activate$python3setup.pydevelopLicenseasmogis licensed under Apache 2.0, for more details check LICENSE.
Package: asmpy
ASMpy is a python backend for nasm or yasm.
It makes easy to writing operating systems.I renamed these instructions:jmp - jump
mov - move
hlt - halt
int - interrupt
cmp - compareAnd added functions:mkboot - alias for “times 510-($-$$) db 0” and “dw 0xAA55” (makes bootloader)
printchar - prints a one symbol
printchar_f - prints a one symbol without “mov AH, 0x0e” (before it you must call initvideo())
initvideo - alias for “mov AH, 0x0e” (tty mode)
printtext - prints a text
printtext_f - same as printtextcmd - is a bufferExample:import asmpyasmpy.printtext(“Hello world!!!”);
asmpy.mkboot()open(“hello_world.asm”,”w”).write(asmpy.cmd)And you get a hello_world.asm file.
Compile it with nasm or yasm:nasm hello_world.asmRun your program with qemu:qemu-system-x86_64 hello_worldYou get a Hello world on BIOS!
Package: asmr-spider
ASMR-Spider本项目改编自DiheChen/go-asmr-spider一个简单的https://asmr.one爬虫。使用Install:pipinstall-Uasmr-spiderRun:asmrRJ373001RJ385913# `asmr` 后面接RJ号, 可输入多个, 使用空格隔开配置文件asmr_spider.yml和 音频目录Voice保存在命令执行时所在的路径Importfromasmr_spiderimportdloadasyncdefdemo():args=['RJ373001','RJ385913']awaitdload(args)asmr_spider.yml和Voice将保存在你自己的项目根路径致谢感谢地河酱, 地河酱yyds🤗感谢https://asmr.one, 现在每天都有不同的女孩子陪我睡觉。
Package: asmscan-lstm
ASMscan-LSTMBidirectional LSTM model for detection of amyloid signaling motifs (ASMs).Installationpipinstallasmscan-lstmUsagefromasmscanlstmimportASMscanLSTMaa_seqs=["MEGRASGSARIYQAGGDQYIEE","VSLRAGAHDGGRIYQAVGDQYIYE","HASGHGRVFQSAGDQHITEH"]model=ASMscanLSTM()pred,frags=model.predict(aa_seqs)ReferencesASMscan-LSTM model is part of theASMscanproject:Not yet published.ASMscan project is an extension of the ASMs analysis conducted with thePCFG-CMmodel:W. Dyrka, M. Gąsior-Głogowska, M. Szefczyk, N. Szulc, "Searching for universal model of amyloid signaling motifs using probabilistic context-free grammars",BMC Bioinformatics, 22, 222, 2021.W. Dyrka, M. Pyzik, F. Coste, H. Talibart, "Estimating probabilistic context-free grammars for proteins using contact map constraints",PeerJ, 7, e6559, 2019.
Package: asmysql
asmysqlIntroductionasmysql is a library for using the MySQL asynchronous client, which is a wrapper for aiomysql.FeaturesCode supports type annotations.Very easy to use, simply inherit the AsMysql class for logical development.Supports automatic management of the MySQL connection pool and reconnection mechanism.Automatically captures and handles MysqlError errors globally.Separates statement execution from data retrieval.Install# Python3.11+pipinstallasmysqlDocumentationQuick StartimportasynciofromasmysqlimportAsMysqlclassTestAsMysql(AsMysql):host='127.0.0.1'port=3306user='root'password='pass'asyncdefget_users(self):result=awaitself.client.execute('select user,authentication_string,host from mysql.user')ifresult.err:print(result.err)else:asyncforiteminresult.iterate():print(item)asyncdefmain():mysql=awaitTestAsMysql()awaitmysql.get_users()asyncio.run(main())More UsageimportasynciofromasmysqlimportAsMysqlclassTestAsMysql(AsMysql):asyncdefget_users(self):result=awaitself.client.execute('select user,authentication_string,host from mysql.user')ifresult.err:print(result.err)else:returnawaitresult.fetch_all()mysql=TestAsMysql(host='192.168.1.192',port=3306)asyncdefmain():awaitmysql.connect()# or: await mysqlprint(awaitmysql.get_users())asyncio.run(main())
Package: asn1vnparser
asn1vnparserParses ASN.1 value notation into a Python object or JSON without requiring its ASN.1 schema.Free software: ISC licenseDocumentation:https://asn1vnparser.readthedocs.io.FeaturesParsing ASN.1 value notation into a Python object, or a JSON stringNo ASN.1 Schema RequiredLimitationsSince Knowledge of schema is not used, misdetection of ASN.1 types can occur; see Type Translations section.Some ASN.1 types and grammars are not supported; see grammar.py.Type Translationsasn1vnparserperforms the following type translations:ASN.1 TypePython TypeJSON TypeExample (ASN.1 -> Python)NULLNonenullNULL -> NoneBOOLEANboolTrue/FalseTRUE -> TrueINTEGERintnumber (int)3 -> 3REALfloatnumber (real)0.1 -> 0.1BIT STRING (^1)bitarray.bitarraystring (e.g. “010101”)‘010101’B -> bitarray.bitarray(‘010101’)OCTET STRING (^1)bytesstring (e.g. “0123ab”)‘0123AB’H -> b’x01x23xab’cstring(PrintableString, etc.)strstring“foobar” -> ‘foobar’ENUMERATEDstrstringany-identifier -> ‘any-identifier’CHOICEDict[str, Any]{“string”: (any JSON object)}alt1 : 123 -> {‘alt1’: 123}Open Type  (e.g. type field)Dict[str, Any]{“String”: (any JSON object)}Type1 : 123 -> {‘Type1’: 123}empty SEQUENCE or SEQUENCE OF{} (empty dict){} (empty object){} -> {}, [] -> {}SEQUENCEdictobject{f1 val, f2 1} -> {‘f1’: ‘val’, ‘f2’: 1}SEQUENCE OFlistarray[1, 2, 3] -> [1, 2, 3]OBJECT IDENTIFIERList[int]array of number (int){1 2 3} -> [1, 2, 3](^1)CONTAINING (some_value)is interpreted as simply(some_value), e.g.:{
    field1 123,
    field2 CONTAINING {
        field2-1 TRUE,
        field2-2 FALSE
    }
}is parsed into following Python object:{
    "field1": 123,
    "field2": {
        "field2-1": True,
        "field2-2": False
    }
}CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.2.1 (2021-11-14)Disable pyparsing v3, which breaks testsUpdate license to ISC0.2.0 (2019-10-02)New FeaturesPartial parsing of a value or a value assignment (parse_alloption)>>>parse_asn1_value(..."alt1: enum1\n---this is remaining string---",...as_json=True,...parse_all=False)# as_json('{"alt1": "enum1"}','\n---this is remaining string---')Parsing multiple value assignments>>>parse_asn1_value_assignments(...'value1 INTEGER ::= 1\nvalue2 Type2 ::= the-value')[{'value_name':'value1','type_name':'INTEGER','value':1},{'value_name':'value2','type_name':'Type2','value':'the-value'}]Bug FixesCLI no longer crashes when given--jsonoption.0.1.0 (2019-09-29)First release on PyPI.
Package: asn-check
ASN CheckGiven a list of IPs the tool returns their AS numbers and names.Data sources:ASN ranges IPv4- Thyme APNIC,ASN ranges IPv6- Thyme APNIC,AS names - ripe.net.Features:Caching the data from sources - first run may take a long time,Binary IP network search for high throughput,Returns AS Number, AS Name and a country code for each IP address.Supports both IPv4 and IPv6Also available as a lib!Installationpip install asn-checkOptions--input-file FILENAME           Input file with one IPv4 per line  [default:STDIN]
  --output-file FILENAME          Output file - csv, header: ip,asn,name,country_code  [default: STDOUT]
  --log-level [DEBUG|INFO|WARNING|ERROR|CRITICAL] Set logging level.  [default: WARNING]
  --help                          Show this message and exit.Example CLI$ echo '250.254.147.119
    12.154.0.67
    41.13.122.240
    176.218.30.1078
    128.105.177.84
    85.227.158.196
    74.74.207.74
    2a03:2880:f077::1' | asn-checkOutput:ip,asn,name,country_code
250.254.147.119,,,
12.154.0.67,7018,ATT-INTERNET4,US
41.13.122.240,29975,VODACOM-,ZA
128.105.177.84,59,WISC-MADISON-AS,US
85.227.158.196,2119,TELENOR-NEXTEL Telenor Norge AS,NO
74.74.207.74,11351,TWC-11351-NORTHEAST,US
2a03:2880:f077::1,32934,FACEBOOK,USExample Lib Usagefrom ipaddress import ip_address
from asn_check import ASNChecker

checker = ASNChecker() 
print(checker.search(ip_address("12.154.0.67")))Output:{'ip': IPv4Address('12.154.0.67'), 'asn': '7018', 'name': 'ATT-INTERNET4', 'country_code': 'US'}Note: If you'd like to use your own data sources, theoretically you can, but they need to follow the same format as the APNIC sources (and the format is not consistent!) - check out the constructor optionsasn_routes_url_v4, asn_routes_url_v6, asn_names_url. I'd recommend sticking to the defaults.
Package: asn-info
ASN InfoA python library providing information about ASNs (AS Name, Country and MANRS membership)This library downloads the Autonomous System list and information from RIPE NCC and provides its contents as objects.There are three data points:Autonomous System Name:get_as_name()Autonomous System Country:get_as_country()Wether an ASN is a MANRS Participant:is_manrs_participant()MANRS Data is not loaded by default, since it requires an API key.  In case you want to load it, you will have to prepare a .env file containing a line like this:MANRS_API_KEY=ad83444d-4c68-4727-9ff6-ce2df6649c05You can obtain an API keyhereExample use:importasn_infoasn_data=asn_info.Asns()h=asn_data.load_asn_data(add_manrs_data=True)print(asn_data.get_as_name(58280))print(asn_data.get_as_country(58280))print(asn_data.is_manrs_participant(58280))Result:STUCCHIMAX-ASMassimilianoAndreaStucchi
CH
FalseYou can also filter the ASNs per country, as follows:switzerland=asn_data.asns_per_country("CH")forasninswitzerland:print("{}has{}".format(asn,switzerland[asn]))Output:...
58280 has {'country': 'CH', 'as_name': 'STUCCHIMAX-AS Massimiliano Andrea Stucchi'}
...
Package: asn-nmap
asn_nmapLibrary created with the aim of facilitating the obtaining of ips service status by asnDescription.The package asn_nmap is used to:Asn:get_ipsNmap:mainRequirementspython3.9 or highernmapInstallationUse the package managerpipto install asn_nmapapt-getinstallnmap-y
pipinstallasn-nmapUsageGet information from a asnfromasn_nmap.asnimportAsnfromasn_nmap.exportimportExportfromasn_nmap.nmapimportNmaplist_asns=[1251]ports=[80,443]asn=Asn()data=asn.get_ips_by_asns(list_asns)data={'1251':['200.136.0.0/32']}# Subscribing the data manually to testnmap=Nmap()nmap.run_nmap(asn_info=data,port_list=ports,threads_count=1)Export().to_xlsx(destination_file_name='teste')an file will be automatically generatedDocumentationProject documented withmkdocs# Run the command in the root of the projectmkdocsserveAuthorEdgar ReisLicenseMIT
Package: asociita
Setting ConfigurationIn order to run the simulation, theOrchestratorinstance must receive asettingsobject that contains all the necessary parameters. It is possible to store those parameters in aJSONformat and load them as the Python dictionary by usingasociita.utils.helper.load_from_jsonfunction. Below is an exemplary settings object embedded as ajsonfile. All the elements are necessary unless stated otherwise.{
    "orchestrator":{
        "iterations": int,
        "number_of_nodes": int,
        "local_warm_start": bool,
        "sample_size": int,
        "evaluation": "none" | "full"
        "save_metrics": bool,
	"save_models": bool,
	"save_path": str
	"nodes": [0,
	1,
	2]
    },
    "nodes":{
    "local_epochs": int,
    "model_settings": {
        "optimizer": "RMS",
        "batch_size": int,
        "learning_rate": float}
        }
}Thesettingscontains two dictionaries:orchestratorandnodes.orchestratorcontains all the settings necessary details of the training:iterationsis the number of rounds to be performed. Example:iterations:12number_of_nodesis the number of nodes that will be included in the training. Example:number_of_nodes: 10local_warm_startallows to distribute various pre-trained weights to different local clients. Not implemeneted yet. Example:local_warm_start: false.sample_sizeis the size of the sample that will be taken each round. Example:sample_size : 4.evaluationallows to control the evaluation procedure across the clients.  Currently, onlynoneorfullare supported. Setting the evaluation to full will perform a full evaluation of every client included in the training. Example:evaluation: fullsave_metricsallows to control whether the metrics should be saved in a csv file. Example:save_metrics: true.save_modelsallows to control whether the models should be saved. Not implemeneted yet. Example:save_metrics: false.save_pathis the system path that will be used when saving the model. It is possible to define a saving_path in a method call.nodesis the list containing the ids of all the nodes participating in the training. Length ofnodesmust be equalnumber_of_nodes.nodescontains all the necessary configuration for nodes."local_epochs":the number of local epochs to be performed on the local nodes."model_settings"is a dictionary containing all the parameters for training the model.optimizeris an optimizer that will be used during the training. Example:optimizer: "RMS"batch_sizeis the batch size that will be used during the training. Example:batch_size: 32learning_rateis the learning rate that will be used during the training. Example:learning_rate: 0.001