import json
from typing import Dict, List

# Load the ID mapping
with open("training/datasets/speaker_id_mapping_libri.json") as f:
    id_mapping = json.load(f)

# Create a reverse mapping
reverse_mapping: Dict[int, int] = {int(v): int(k) for k, v in id_mapping.items()}

# Selected for the fine-tuning
# train-960 subset of LibriTTS
selected_speakers = [
    574,  # Daniel Shorten 	M 	train-clean-100
    242,  # J. Hall 	M 	train-other-500
    536,  # Robert Flach 	M 	train-other-500
    82,  # Andy Minter 	M 	train-other-500
    672,  # Stuart Bell 	M 	train-other-500
    315,  # Jean Crevier 	M 	train-other-500
    628,  # Bryan Ness 	M 	train-clean-100
    61,  # John Greenman 	M 	train-other-500
    649,  # Scarlett! 	F 	train-clean-360
    105,  # Marian Brown 	F 	train-clean-360
    399,  # entada 	F 	train-clean-360
    89,  # 	Paula Berinstein 	F 	train-clean-360
    502,  # Lee Elliott 	F 	train-other-500
    102,  # Maureen S. O'Brien 	F 	train-clean-100
    544,  # Miranda Stinson 	F 	train-clean-360
    653,  # cucciasv 	F 	train-other-500
    465,  # Leonie Rose 	F 	train-clean-100
    96,  # Kymm Zuckert 	F 	train-other-500
    447,  # Lee Ann Howlett 	F 	train-clean-360
    165,  # 	Elisabeth Shields 	F 	train-clean-100
    430,  # 	Millbeach 	F 	train-other-500
    214,  # Scott Splavec 	M 	train-clean-100
    666,  # Kelly Dougherty 	M 	train-clean-360
    481,  # Scott Sherris 	M 	train-clean-360
    463,  # Chris Hughes 	M 	train-other-500
    273,  # Andrew Lebrun 	M 	train-other-500
    172,  # Harvey Chinn 	M 	train-other-500
    83,  # Graham Williams 	M 	train-other-500
    523,  # Michael Loftus 	M 	train-clean-360
    38,  # Kurt Copeland 	M 	train-clean-360
    248,  # fieldsofgold 	M 	train-other-500
    234,  # Menno 	M 	train-other-500
    145,  # Mr. Baby Man 	M 	train-clean-360
    250,  # Quentin 	M 	train-clean-360
    498,  # Chris Gladis 	M 	train-clean-100
    123,  # Sean McGaughey 	M 	train-clean-360
    171,  # Paul Harvey 	M 	train-clean-360
    49,  # 	Kristen McQuillin 	F 	train-clean-100
    588,  # 	Kalynda 	F 	train-clean-360
    117,  # 	Caitlin Kelly 	F 	train-clean-360
    657,  # Shannon 	F 	train-other-500
    275,  # Zale Schafer (Rose May Chamberlin Memorial Foundat 	F 	train-clean-360
    604,  # Anne-Marie 	F 	train-other-500
    64,  # Christiane Levesque 	F 	train-clean-360
    685,  # Nikki Sullivan 	F 	train-clean-100
    355,  # Lana Taylor 	F 	train-clean-100
    185,  # Kim Braun 	F 	train-clean-360
    52,  # Cori Samuel 	F 	train-other-500
    218,  # Joy Chan 	F 	train-other-500
    549,  # AmyAG 	F 	train-other-500
    617,  # PJ 	F 	train-other-500
    414,  # Christabel 	F 	train-clean-100
    382,  # Kelli Robinson 	F 	train-clean-360
    76,  # 	ML Cohen 	M 	train-other-500
    176,  # Micah Sheppard 	M 	train-clean-360
    233,  # mikenkat 	M 	train-clean-360
    390,  # JimmyLogan 	M 	train-clean-360
    393,  # 	Tim Lundeen 	M 	train-clean-360
    425,  # RedToby 	M 	train-clean-360
    398,  # Sam Fold 	M 	train-other-500
    372,  # Jim Mullins 	M 	train-clean-360
    99,  # Stewart Wills 	M 	train-clean-100
    340,  # 	Nick Gallant 	M 	train-clean-100
    40,  # JemmaBlythe 	F 	train-other-500
    118,  # 	Brenda Dayne 	F 	train-clean-360
    640,  # David A. Stokely 	M 	train-other-500
    50,  # Dan Threetrees 	M 	train-clean-360
    373,  # Brooks Seveer 	M 	train-clean-360
    124,  # Steve Karafit 	M 	train-clean-100
    314,  # Carl Vonnoh, III 	M 	train-clean-360
    531,  # Fr. Richard Zeile of Detroit 	M 	train-other-500
    383,  # Mike Roop 	M 	train-other-500
    710,  # Sheila Morton 	F 	train-clean-100
    450,  # Heather Duncan 	F 	train-clean-360
    645,  # Micah 	M 	train-other-500
    517,  # Madame Tusk 	F 	train-other-500
    479,  # Wina Hathaway 	F 	train-other-500
    30,  # Ophelia Darcy 	F 	train-other-500
    220,  # Tina Tilney 	F 	train-clean-360
    63,  # Linda Wilcox 	F 	train-other-500
    283,  # Bethany Simpson 	F 	train-clean-360
    644,  # Cynthia Zocca 	F 	train-clean-360
    677,  # Allyson Hester 	F 	train-other-500
    21,  # Kelly Bescherer 	F 	train-other-500
    552,  # Mim Ritty 	F 	train-clean-100
    80,  # 	Fox in the Stars 	F 	train-clean-100
    394,  # swroot 	F 	train-clean-360
    426,  # Megan Stemm-Wade 	F 	train-clean-100
    91,  # Chris Goringe 	M 	train-other-500
    108,  # Kevin McAsh 	M 	train-clean-360
    130,  # 	Peter of Buckinghamshire England 	M 	train-other-500
    661,  # James Gladwin 	M 	train-other-500
    216,  # Dave Ranson 	M 	train-clean-100
    164,  # Ed Good 	M 	train-other-500
    308,  # Eric Connover 	M 	train-other-500
    569,  # Arouet 	M 	train-clean-360
    313,  # Tim Bulkeley 	M 	train-other-500
    212,  # Glen Hallstrom 	M 	train-other-500
    15,  # 	Chip 	M 	train-other-500
    469,  # Christian Pecaut 	M 	train-clean-360
    294,  # 	Diana Kiesners 	F 	train-clean-360
    192,  # Nocturna 	F 	train-clean-100
    73,  # Claire Goget 	F 	train-clean-100
    417,  # Kiki Baessell 	F 	train-clean-360
    636,  # Matthew Howell 	F 	train-other-500
    36,  # chriss the girl 	F 	train-other-500
    668,  # Jan Baxter 	F 	train-clean-360
    403,  # Igor Teaforay 	F 	train-clean-360
    618,  # Linnea 	F 	train-other-500
    596,  # Jo 	F 	train-other-500
    499,  # Tammy Sanders 	F 	train-clean-100
    207,  # Sage Tyrtle 	F 	train-other-500
    1346,  # Jeanie 	F 	train-other-500
    1109,  # Martin Geeson 	M 	train-other-500
    770,  # Pete Williams, Pittsburgh, PA 	M 	train-clean-360
    1247,  # Sarah LuAnn 	F 	train-clean-100
    1526,  # 	Mike Harris 	M 	train-other-500
    908,  # Quentin Manuel 	M 	train-clean-360
    1183,  # 	Evelyn Clarke 	F 	train-other-500
    1438,  # Tom Barron 	M 	train-other-500
    1022,  # 	peac 	M 	train-clean-100
    1603,  # 	Christine Rodriguez 	F 	train-clean-360
    1425,  # 	Jonah Cummings 	M 	train-clean-360
    731,  # 	Priya, India 	F 	train-other-500
    782,  # Alec Daitsman 	M 	train-clean-360
    1090,  # Termin Dyan 	M 	train-other-500
    995,  # Parrot 	M 	train-other-500
    923,  # Jane Greensmith 	F 	train-clean-360
    766,  # Clive Catterall 	M 	train-other-500
    822,  # kristiface 	F 	train-clean-360
    897,  # Jan Dawn Doronila 	F 	train-clean-360
    1579,  # Linda Velwest 	F 	train-clean-360
    964,  # Utek 	M 	train-clean-360
    1414,  # 	Preston Scrape 	M 	train-other-500
    834,  # Serin 	F 	train-other-500
    1302,  # davidb 	M 	train-clean-360
    1135,  # Linda Andrus 	F 	train-clean-360
    1440,  # 	P Moscato 	F 	train-clean-360
    870,  # Barbara Bulkeley 	F 	train-clean-360
    1256,  # Graeme Dunlop 	M 	train-other-500
    1255,  # Daniel Paashaus 	M 	train-other-500
    1157,  # Bev J Stevens 	F 	train-clean-360
    934,  # Darla 	F 	train-other-500
    1281,  # garbageman99 	M 	train-clean-360
    819,  # n8evv 	M 	train-clean-360
    1041,  # mjbrichant 	F 	train-other-500
    863,  # K Hindall 	F 	train-clean-360
    1303,  # kiwafruit 	F 	train-clean-100
    1115,  # Rachel Gatwood 	F 	train-clean-360
    1539,  # Nathan Jordan 	M 	train-other-500
    1428,  # Gary Dzierlenga 	M 	train-other-500
    1049,  # Diana Solomon 	F 	train-other-500
    1546,  # Carrie Heyes 	F 	train-other-500
    1089,  # Bill Ruhsam 	M 	train-clean-360
    1142,  # Jonathan Burchard 	M 	train-other-500
    1375,  # Frank Adams 	M 	train-clean-360
    881,  # mpetranech 	M 	train-other-500
    798,  # Wyatt 	M 	train-other-500
    1647,  # 	Patrick Reinhart 	M 	train-clean-360
    1587,  # Claudia Wilson 	F 	train-clean-360
    830,  # musici123 	F 	train-other-500
    1592,  # jerryB 	M 	train-other-500
    839,  # Ben Dutton 	M 	train-other-500
    835,  # Rachel Lintern 	F 	train-other-500
    1273,  # gmiteva 	F 	train-other-500
    932,  # Raerity 	F 	train-other-500
    1108,  # Paul McCartan 	M 	train-other-500
    732,  # Tysto 	M 	train-clean-360
    781,  # Megan Kunkel 	F 	train-other-500
    1555,  # Andrew Nelson 	M 	train-clean-360
    1437,  # Charles RUHE 	M 	train-clean-360
    1402,  # Angel5 	F 	train-other-500
    963,  # MichelleHarris 	F 	train-clean-360
    1181,  # J. Rebecca Franklin 	F 	train-clean-360
    818,  # Matt Warzel 	F 	train-clean-360
    1285,  # Ric F 	M 	train-clean-100
    797,  # Chris Jones 	F 	train-other-500
    1505,  # Rom Maczka 	M 	train-clean-360
    1214,  # David Baldwin 	M 	train-clean-360
    1636,  # jessecoy 	M 	train-other-500
    929,  # Petra 	F 	train-other-500
    1171,  # 	Roberta Carlisle 	F 	train-other-500
    817,  # texttalker 	M 	train-clean-360
    1433,  # browneyedgirl32382 	F 	train-clean-360
    1158,  # StarrDog 	M 	train-other-500
    1000,  # artos 	M 	train-other-500
    848,  # senshisteph 	F 	train-other-500
    1596,  # Joyce Couch 	F 	train-other-500
    757,  # Roger Melin 	M 	train-clean-360
    1168,  # Epistomolus 	M 	train-clean-100
    741,  # Nick Marsh 	M 	train-other-500
    1649,  # Phineas Redux 	M 	train-other-500
    851,  # Jennifer Lott 	F 	train-clean-360
    808,  # M. J. Boyle 	F 	train-other-500
    1595,  # Matthew Reece 	M 	train-clean-360
    1370,  # Savanna Herrold 	F 	train-other-500
    1565,  # bryan.peterson 	M 	train-other-500
    944,  # Sarafina Suransky 	F 	train-other-500
    1268,  # A. Janelle Risa 	F 	train-clean-100
    771,  # Isosceles 	F 	train-clean-360
    752,  # Cat Schirf 	F 	train-other-500
    800,  # Jack Farrell 	M 	train-clean-360
    1005,  # Beatrice 	F 	train-other-500
    1229,  # RoseA 	F 	train-clean-360
    943,  # Matthew C. Heckel 	M 	train-clean-360
    891,  # anoldfashiongirl 	F 	train-other-500
    1226,  # serenitylee 	F 	train-clean-360
    1253,  # Caroline Shapiro 	F 	train-other-500
    1204,  # Dale A. Bade 	F 	train-clean-360
    1230,  # Troy Bond 	M 	train-other-500
    791,  # David Kleparek 	M 	train-clean-100
    1184,  # Joseph Couves 	F 	train-other-500
    1001,  # TriciaG 	F 	train-clean-360
    804,  # FirstKnight 	F 	train-other-500
    1641,  # Kirsten Wever 	F 	train-clean-100
    1259,  # 	Megan Argo 	F 	train-other-500
    1231,  # Abigail Bartels 	F 	train-other-500
    1410,  # 	Zachary Johnson 	M 	train-other-500
    1030,  # Ancient mariner 	M 	train-other-500
    1093,  # Katie Riley 	F 	train-clean-360
    1254,  # Rosie 	F 	train-clean-100
    1365,  # Eric Leach 	M 	train-clean-360
    831,  # David Federman 	M 	train-other-500
    1989,  # 	Joannemmp 	F 	train-clean-100
    1707,  # David Olson 	M 	train-other-500
    1849,  # Fred DeBerardinis 	M 	train-clean-100
    1808,  # Rebecca King 	F 	train-clean-360
    2292,  # Arnold 	M 	train-clean-100
    2415,  # Patrick Eaton 	M 	train-other-500
    1656,  # Sharon Omi 	F 	train-clean-100
    1676,  # Gargoyle 	M 	train-clean-360
    1881,  # Julienne 	F 	train-other-500
    2036,  # T.K. Kirven 	F 	train-other-500
    1761,  # EliMarieHK 	F 	train-other-500
    2115,  # Pete Milan 	M 	train-other-500
    1803,  # Susan Hanfield 	F 	train-clean-360
    1798,  # C. L. W. Rollins 	F 	train-other-500
    1723,  # Rachel Bossier 	F 	train-other-500
    2341,  # Haili 	F 	train-other-500
    2468,  # Erin Schellhase 	F 	train-clean-360
    1725,  # Ruth Kidson 	F 	train-other-500
    2010,  # Peggy 	F 	train-other-500
    1853,  # Ron Altman 	M 	train-other-500
    2359,  # Doug Reed 	M 	train-other-500
    2422,  # Jude Somers 	F 	train-clean-360
    2234,  # Coreena 	F 	train-other-500
    2156,  # 	C F de Rosset 	F 	train-other-500
    2483,  # Tammy Porter 	F 	train-clean-360
    1781,  # humanode 	M 	train-clean-360
    2275,  # NatalieOram 	F 	train-other-500
    2390,  # sdaeley17 	M 	train-clean-360
    2314,  # Cheri Jordan 	F 	train-clean-360
    2413,  # Joanne Rochon 	F 	train-clean-360
    1697,  # 	Lonelle Yoder 	F 	train-other-500
    1718,  # 	Caroline Driggs 	F 	train-other-500
    2387,  # Brett G. Hirsch 	M 	train-other-500
    2331,  # Madam Fickle 	F 	train-clean-100
    1783,  # Sarah Crampton 	F 	train-clean-360
    2397,  # Rebecca Braunert-Plunkett 	F 	train-other-500
    2357,  # William Gavula 	M 	train-other-500
    1670,  # dmbrought 	M 	train-other-500
    1987,  # Andrew White 	M 	train-clean-360
    1755,  # 	Yvonne Smith 	F 	train-clean-360
    2192,  # Sammy Bean 	M 	train-other-500
    1716,  # EyeBones 	F 	train-clean-360
    1828,  # David Wales 	M 	train-clean-100
    2251,  # Wiley Combs 	M 	train-clean-360
    2065,  # Muriel 	F 	train-clean-360
    2017,  # CaprishaPage 	F 	train-other-500
    1947,  # Barbara Edelman 	F 	train-other-500
    1738,  # Lois C. Johnson 	F 	train-clean-360
    1791,  # David Cummings 	M 	train-clean-360
    2045,  # Linda Ciano 	F 	train-clean-360
    2452,  # 	Walt Allan 	M 	train-other-500
    2040,  # MJ Franck 	F 	train-other-500
    1831,  # Nigel Boydell 	M 	train-other-500
    2371,  # Alexander Hatton 	M 	train-clean-360
    1954,  # Szindbad 	M 	train-other-500
    1836,  # Kendall Ashyby 	F 	train-other-500
    2436,  # 	josembi 	M 	train-other-500
    2383,  # 	Emma Joyce 	F 	train-other-500
    2278,  # Jake Woldstad 	M 	train-clean-360
    1741,  # 	anjieliu 	F 	train-other-500
    1857,  # Amanda Friday 	F 	train-clean-360
    2370,  # 	gloriousjob 	M 	train-clean-360
    1907,  # 	Snapdragon 	F 	train-other-500
    2225,  # 	nomorejeffs 	M 	train-clean-360
    2439,  # KHand 	F 	train-clean-360
    2239,  # amaskill 	M 	train-other-500
    2007,  # Art Leung 	F 	train-clean-360
    2283,  # Tim Cote 	M 	train-clean-360
    1712,  # 	Steve Belleguelle 	M 	train-other-500
    2094,  # Meg Cowan 	F 	train-clean-360
    1772,  # 	haggisreflux 	M 	train-clean-360
    2317,  # 	helengraves 	F 	train-clean-360
    2241,  # 	Steven Reynolds 	M 	train-clean-360
    2011,  # 	pekein 	M 	train-clean-360
    1826,  # 	John Hoerr 	M 	train-clean-100
    1695,  # Tina Nuzzi 	F 	train-clean-360
    2451,  # DeanOBuchanan 	M 	train-clean-100
    1771,  # Chelsea S. 	F 	train-other-500
    2441,  # Alison Stewart 	F 	train-clean-360
    1745,  # Janet 	F 	train-clean-360
    2358,  # 	Betty Perry 	F 	train-clean-360
    2197,  # Mike Nelson 	M 	train-other-500
    2014,  # 	Eden Rea-Hedrick 	F 	train-other-500
    1672,  # 	Mike Wajda 	M 	train-clean-360
    2394,  # TinaNygard2 	F 	train-clean-100
    1657,  # alwpoe 	M 	train-clean-360
    1728,  # Vinnie Tesla 	M 	train-clean-360
    1805,  # 	Vince Dee 	M 	train-clean-100
    2143,  # 	Suebee 	F 	train-clean-360
    2084,  # Eberle Thomas 	M 	train-other-500
    2479,  # Daisy Flaim 	F 	train-clean-100
    2152,  # Kristel Tretter 	F 	train-clean-360
    2268,  # Greg Giordano 	M 	train-clean-360
    1839,  # James E. Carson 	M 	train-clean-360
    2056,  # 	acloward 	M 	train-clean-360
    1814,  # polkadotish 	F 	train-other-500
    2127,  # Ron Lockhart 	M 	train-clean-100
    2114,  # Larry Beasley 	M 	train-clean-360
    2469,  # 	Kevin Owens 	M 	train-clean-100
    2447,  # Deena Rhoads 	F 	train-clean-360
    1724,  # Juliana M. 	F 	train-clean-360
    1869,  # 	NastassiaS 	F 	train-other-500
    2209,  # Samantha J Gubitz 	F 	train-clean-360
    2171,  # 	Carolyne 	F 	train-other-500
    2403,  # Ian Quinlan 	M 	train-clean-360
    2032,  # 	doonaboon 	M 	train-other-500
    2075,  # Joy S Grape 	F 	train-clean-360
]

# Convert the model speaker IDs back to the dataset speaker IDs
# dataset_speaker_ids: List[int] = [
#     reverse_mapping.get(int(speaker_id)) for speaker_id in selected_speakers
# ]  # type: ignore

# Save the selected speaker IDs
latest_selection: List[int] = [
    574,
    649,
    102,
    544,
    653,
    666,
    481,
    248,
    123,
    171,
    604,
    64,
    685,
    52,
    218,
    617,
    414,
    425,
    118,
    50,
    373,
    314,
    710,
    450,
    645,
    517,
    63,
    644,
    80,
    394,
    91,
    108,
    661,
    164,
    308,
    469,
    192,
    417,
    668,
    596,
    1109,
    770,
    1247,
    908,
    782,
    995,
    923,
    822,
    1414,
    1302,
    1135,
    1440,
    1281,
    1041,
    1142,
    881,
    835,
    932,
    732,
    1402,
    929,
    817,
    1433,
    1596,
    851,
    1370,
    1204,
    1230,
    791,
    804,
    1808,
    1656,
    2115,
    2341,
    2468,
    1718,
    1783,
    1755,
    2192,
    2371,
    1836,
    1741,
    2439,
    1712,
    2197,
    1728,
    1805,
    2143,
    2084,
    2056,
    2114,
    2447,
    1869,
    2209,
]

dataset_speaker_ids: List[int] = [
    reverse_mapping.get(int(speaker_id)) for speaker_id in latest_selection
]  # type: ignore