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Aya 2022-11-21 14:50:07 +00:00
parent 372605180e
commit be0ba934ee
1 changed files with 17 additions and 233 deletions
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notebooks/Tutorial_2_train_your_first_TTS_model.ipynb
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@ -107,19 +107,10 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "b3cb0191-b8fc-4158-bd26-8423c2a8ba66",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/mount-storage/TTS/tts-env/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
}
],
"outputs": [],
"source": [
"import os\n",
"\n",
@ -134,28 +125,10 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "ae6b7019-3685-4b48-8917-c152e288d7e3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2022-11-21 12:03:04-- https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2\n",
"Resolving data.keithito.com (data.keithito.com)... 174.138.79.61\n",
"Connecting to data.keithito.com (data.keithito.com)|174.138.79.61|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 2748572632 (2.6G) [application/octet-stream]\n",
"Saving to: ‘tts_train_dir/LJSpeech-1.1.tar.bz2’\n",
"\n",
"tts_train_dir/LJSpe 100%[===================>] 2.56G 34.3MB/s in 1m 49s \n",
"\n",
"2022-11-21 12:04:53 (24.1 MB/s) - ‘tts_train_dir/LJSpeech-1.1.tar.bz2’ saved [2748572632/2748572632]\n",
"\n"
]
}
],
"outputs": [],
"source": [
"# Download and extract LJSpeech dataset.\n",
"\n",
@ -165,7 +138,7 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"id": "76cd3ab5-6387-45f1-b488-24734cc1beb5",
"metadata": {},
"outputs": [],
@ -198,7 +171,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "5483ca28-39d6-49f8-a18e-4fb53c50ad84",
"metadata": {},
"outputs": [],
@ -236,51 +209,10 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"id": "b1b12f61-f851-4565-84dd-7640947e04ab",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" > Setting up Audio Processor...\n",
" | > sample_rate:22050\n",
" | > resample:False\n",
" | > num_mels:80\n",
" | > log_func:np.log10\n",
" | > min_level_db:-100\n",
" | > frame_shift_ms:None\n",
" | > frame_length_ms:None\n",
" | > ref_level_db:20\n",
" | > fft_size:1024\n",
" | > power:1.5\n",
" | > preemphasis:0.0\n",
" | > griffin_lim_iters:60\n",
" | > signal_norm:True\n",
" | > symmetric_norm:True\n",
" | > mel_fmin:0\n",
" | > mel_fmax:None\n",
" | > pitch_fmin:1.0\n",
" | > pitch_fmax:640.0\n",
" | > spec_gain:20.0\n",
" | > stft_pad_mode:reflect\n",
" | > max_norm:4.0\n",
" | > clip_norm:True\n",
" | > do_trim_silence:True\n",
" | > trim_db:45\n",
" | > do_sound_norm:False\n",
" | > do_amp_to_db_linear:True\n",
" | > do_amp_to_db_mel:True\n",
" | > do_rms_norm:False\n",
" | > db_level:None\n",
" | > stats_path:None\n",
" | > base:10\n",
" | > hop_length:256\n",
" | > win_length:1024\n"
]
}
],
"outputs": [],
"source": [
"from TTS.utils.audio import AudioProcessor\n",
"ap = AudioProcessor.init_from_config(config)\n",
@ -298,7 +230,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"id": "014879b7-f18d-44c0-b24a-e10f8002113a",
"metadata": {},
"outputs": [],
@ -317,18 +249,10 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": null,
"id": "cadd6ada-c8eb-4f79-b8fe-6d72850af5a7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" | > Found 13100 files in /mount-storage/TTS/TTS/notebooks/tts_train_dir/LJSpeech-1.1\n"
]
}
],
"outputs": [],
"source": [
"from TTS.tts.datasets import load_tts_samples\n",
"train_samples, eval_samples = load_tts_samples(\n",
@ -351,19 +275,10 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": null,
"id": "ac2ffe3e-ad0c-443e-800c-9b076ee811b4",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/mount-storage/TTS/tts-env/lib/python3.8/site-packages/torchaudio/backend/utils.py:53: UserWarning: \"sox\" backend is being deprecated. The default backend will be changed to \"sox_io\" backend in 0.8.0 and \"sox\" backend will be removed in 0.9.0. Please migrate to \"sox_io\" backend. Please refer to https://github.com/pytorch/audio/issues/903 for the detail.\n",
" warnings.warn(\n"
]
}
],
"outputs": [],
"source": [
"from TTS.tts.models.glow_tts import GlowTTS\n",
"model = GlowTTS(config, ap, tokenizer, speaker_manager=None)"
@ -379,28 +294,10 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"id": "0f609945-4fe0-4d0d-b95e-11d7bfb63ebe",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
" > Training Environment:\n",
" | > Current device: 0\n",
" | > Num. of GPUs: 1\n",
" | > Num. of CPUs: 256\n",
" | > Num. of Torch Threads: 128\n",
" | > Torch seed: 54321\n",
" | > Torch CUDNN: True\n",
" | > Torch CUDNN deterministic: False\n",
" | > Torch CUDNN benchmark: False\n",
"\n",
" > Model has 28610257 parameters\n"
]
}
],
"outputs": [],
"source": [
"from trainer import Trainer, TrainerArgs\n",
"trainer = Trainer(\n",
@ -418,123 +315,10 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": null,
"id": "d4c07f99-3d1d-4bea-801e-9f33bbff0e9f",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"\u001b[4m\u001b[1m > EPOCH: 0/100\u001b[0m\n",
" --> tts_train_dir/run-November-21-2022_12+44PM-bc6120c3\n",
"\n",
"\u001b[1m > TRAINING (2022-11-21 12:44:16) \u001b[0m\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"> DataLoader initialization\n",
"| > Tokenizer:\n",
"\t| > add_blank: False\n",
"\t| > use_eos_bos: False\n",
"\t| > use_phonemes: True\n",
"\t| > phonemizer:\n",
"\t\t| > phoneme language: en-us\n",
"\t\t| > phoneme backend: espeak\n",
"| > Number of instances : 12969\n",
" | > Preprocessing samples\n",
" | > Max text length: 188\n",
" | > Min text length: 13\n",
" | > Avg text length: 100.90014650319993\n",
" | \n",
" | > Max audio length: 222643.0\n",
" | > Min audio length: 24499.0\n",
" | > Avg audio length: 144984.29755570978\n",
" | > Num. instances discarded samples: 0\n",
" | > Batch group size: 0.\n",
"æt ðə lˈæst mˈoʊmənt pˈɑːmɚ tˈɔst ɐ bˈɪt ʌv pˈeɪpɚɹ ˌoʊvɚ tə hɪz kˈaʊnsəl, ˌɔn wˌɪtʃ hiː hæd ɹˈɪʔn̩, kwˈoʊt, aɪ θˈɪŋk ðɛɹ wɪl biː ɐ vˈɜːdɪkt ʌv nˌɑːt ɡˈɪlti, ˈɛnd kwˈoʊt.\n",
" [!] Character '̩' not found in the vocabulary. Discarding it.\n",
"ðeɪ ɹˈæn tə ðə dˈoːɹ ɪn tˈaɪm tə sˈiː ɐ mˈæn wɪð ɐ ɹᵻvˈɑːlvɚ kˈʌt əkɹˌɑːs ðɛɹ lˈɔːn ænd dˌɪsɐpˈɪɹ ɚɹˈaʊnd ɐ kˈɔːɹnɚɹ ʌvðə hˈaʊs ˌɑːntʊ pˈæʔn̩.\n",
" [!] Character '̩' not found in the vocabulary. Discarding it.\n",
"mˈɪstɚ dʒˈiː, ʌv bˈɪʃəp stˈɔːɹtfɚd, hˌuː ɐdmˈɪnɪstɚd ðɪ ᵻstˈeɪt əvə sˈɜːʔn̩ mˈɪstɚ kˈænɪŋ, dᵻsˈiːst.\n",
" [!] Character '̩' not found in the vocabulary. Discarding it.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" ! Run is removed from tts_train_dir/run-November-21-2022_12+44PM-bc6120c3\n",
"Traceback (most recent call last):\n",
" File \"/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py\", line 1569, in fit\n",
" self._fit()\n",
" File \"/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py\", line 1523, in _fit\n",
" self.train_epoch()\n",
" File \"/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py\", line 1288, in train_epoch\n",
" _, _ = self.train_step(batch, batch_num_steps, cur_step, loader_start_time)\n",
" File \"/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py\", line 1120, in train_step\n",
" outputs, loss_dict_new, step_time = self._optimize(\n",
" File \"/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py\", line 1004, in _optimize\n",
" outputs, loss_dict = self._model_train_step(batch, model, criterion)\n",
" File \"/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py\", line 960, in _model_train_step\n",
" return model.train_step(*input_args)\n",
" File \"/mount-storage/TTS/TTS/TTS/tts/models/glow_tts.py\", line 396, in train_step\n",
" _ = self.forward(\n",
" File \"/mount-storage/TTS/TTS/TTS/tts/models/glow_tts.py\", line 234, in forward\n",
" y, y_lengths, y_max_length, attn = self.preprocess(y, y_lengths, y_max_length, None)\n",
" File \"/mount-storage/TTS/TTS/TTS/tts/models/glow_tts.py\", line 517, in preprocess\n",
" y_lengths = torch.div(y_lengths, self.num_squeeze, rounding_mode=\"floor\") * self.num_squeeze\n",
"TypeError: div() got an unexpected keyword argument 'rounding_mode'\n"
]
},
{
"ename": "AssertionError",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py:1569\u001b[0m, in \u001b[0;36mTrainer.fit\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1568\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1569\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_fit\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1570\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs\u001b[38;5;241m.\u001b[39mrank \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py:1523\u001b[0m, in \u001b[0;36mTrainer._fit\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mskip_train_epoch:\n\u001b[0;32m-> 1523\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_epoch\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39mrun_eval:\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py:1288\u001b[0m, in \u001b[0;36mTrainer.train_epoch\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1287\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m cur_step, batch \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtrain_loader):\n\u001b[0;32m-> 1288\u001b[0m _, _ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_step\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_num_steps\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcur_step\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mloader_start_time\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1289\u001b[0m loader_start_time \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py:1120\u001b[0m, in \u001b[0;36mTrainer.train_step\u001b[0;34m(self, batch, batch_n_steps, step, loader_start_time)\u001b[0m\n\u001b[1;32m 1118\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moptimizer, \u001b[38;5;28mlist\u001b[39m):\n\u001b[1;32m 1119\u001b[0m \u001b[38;5;66;03m# training with a single optimizer\u001b[39;00m\n\u001b[0;32m-> 1120\u001b[0m outputs, loss_dict_new, step_time \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_optimize\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1121\u001b[0m \u001b[43m \u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1122\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1123\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptimizer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1124\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mscaler\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1125\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcriterion\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1126\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mscheduler\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1127\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1128\u001b[0m \u001b[43m \u001b[49m\u001b[43mstep_optimizer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstep_optimizer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1129\u001b[0m \u001b[43m \u001b[49m\u001b[43mnum_optimizers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1130\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1131\u001b[0m loss_dict\u001b[38;5;241m.\u001b[39mupdate(loss_dict_new)\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py:1004\u001b[0m, in \u001b[0;36mTrainer._optimize\u001b[0;34m(self, batch, model, optimizer, scaler, criterion, scheduler, config, optimizer_idx, step_optimizer, num_optimizers)\u001b[0m\n\u001b[1;32m 1003\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1004\u001b[0m outputs, loss_dict \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_model_train_step\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcriterion\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1006\u001b[0m \u001b[38;5;66;03m# skip the rest\u001b[39;00m\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py:960\u001b[0m, in \u001b[0;36mTrainer._model_train_step\u001b[0;34m(batch, model, criterion, optimizer_idx)\u001b[0m\n\u001b[1;32m 959\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m model\u001b[38;5;241m.\u001b[39mmodule\u001b[38;5;241m.\u001b[39mtrain_step(\u001b[38;5;241m*\u001b[39minput_args)\n\u001b[0;32m--> 960\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_step\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minput_args\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/mount-storage/TTS/TTS/TTS/tts/models/glow_tts.py:396\u001b[0m, in \u001b[0;36mGlowTTS.train_step\u001b[0;34m(self, batch, criterion)\u001b[0m\n\u001b[1;32m 395\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mno_grad():\n\u001b[0;32m--> 396\u001b[0m _ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mforward\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 397\u001b[0m \u001b[43m \u001b[49m\u001b[43mtext_input\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 398\u001b[0m \u001b[43m \u001b[49m\u001b[43mtext_lengths\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 399\u001b[0m \u001b[43m \u001b[49m\u001b[43mmel_input\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 400\u001b[0m \u001b[43m \u001b[49m\u001b[43mmel_lengths\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 401\u001b[0m \u001b[43m \u001b[49m\u001b[43maux_input\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43md_vectors\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43md_vectors\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mspeaker_ids\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mspeaker_ids\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 402\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 403\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
"File \u001b[0;32m/mount-storage/TTS/TTS/TTS/tts/models/glow_tts.py:234\u001b[0m, in \u001b[0;36mGlowTTS.forward\u001b[0;34m(self, x, x_lengths, y, y_lengths, aux_input)\u001b[0m\n\u001b[1;32m 233\u001b[0m \u001b[38;5;66;03m# drop redisual frames wrt num_squeeze and set y_lengths.\u001b[39;00m\n\u001b[0;32m--> 234\u001b[0m y, y_lengths, y_max_length, attn \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpreprocess\u001b[49m\u001b[43m(\u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_lengths\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_max_length\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 235\u001b[0m \u001b[38;5;66;03m# create masks\u001b[39;00m\n",
"File \u001b[0;32m/mount-storage/TTS/TTS/TTS/tts/models/glow_tts.py:517\u001b[0m, in \u001b[0;36mGlowTTS.preprocess\u001b[0;34m(self, y, y_lengths, y_max_length, attn)\u001b[0m\n\u001b[1;32m 516\u001b[0m attn \u001b[38;5;241m=\u001b[39m attn[:, :, :, :y_max_length]\n\u001b[0;32m--> 517\u001b[0m y_lengths \u001b[38;5;241m=\u001b[39m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdiv\u001b[49m\u001b[43m(\u001b[49m\u001b[43my_lengths\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnum_squeeze\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrounding_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfloor\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnum_squeeze\n\u001b[1;32m 518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m y, y_lengths, y_max_length, attn\n",
"\u001b[0;31mTypeError\u001b[0m: div() got an unexpected keyword argument 'rounding_mode'",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mSystemExit\u001b[0m Traceback (most recent call last)",
" \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
"Cell \u001b[0;32mIn [10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mtrainer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/trainer/trainer.py:1590\u001b[0m, in \u001b[0;36mTrainer.fit\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1589\u001b[0m traceback\u001b[38;5;241m.\u001b[39mprint_exc()\n\u001b[0;32m-> 1590\u001b[0m \u001b[43msys\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexit\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
"\u001b[0;31mSystemExit\u001b[0m: 1",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)",
" \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/IPython/core/interactiveshell.py:2042\u001b[0m, in \u001b[0;36mInteractiveShell.showtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m 2039\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m exception_only:\n\u001b[1;32m 2040\u001b[0m stb \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mAn exception has occurred, use \u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mtb to see \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 2041\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mthe full traceback.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m-> 2042\u001b[0m stb\u001b[38;5;241m.\u001b[39mextend(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mInteractiveTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_exception_only\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2043\u001b[0m \u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 2044\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 2045\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 2046\u001b[0m \u001b[38;5;66;03m# Exception classes can customise their traceback - we\u001b[39;00m\n\u001b[1;32m 2047\u001b[0m \u001b[38;5;66;03m# use this in IPython.parallel for exceptions occurring\u001b[39;00m\n\u001b[1;32m 2048\u001b[0m \u001b[38;5;66;03m# in the engines. This should return a list of strings.\u001b[39;00m\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/IPython/core/ultratb.py:579\u001b[0m, in \u001b[0;36mListTB.get_exception_only\u001b[0;34m(self, etype, value)\u001b[0m\n\u001b[1;32m 571\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_exception_only\u001b[39m(\u001b[38;5;28mself\u001b[39m, etype, value):\n\u001b[1;32m 572\u001b[0m \u001b[38;5;124;03m\"\"\"Only print the exception type and message, without a traceback.\u001b[39;00m\n\u001b[1;32m 573\u001b[0m \n\u001b[1;32m 574\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 577\u001b[0m \u001b[38;5;124;03m value : exception value\u001b[39;00m\n\u001b[1;32m 578\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 579\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mListTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/IPython/core/ultratb.py:446\u001b[0m, in \u001b[0;36mListTB.structured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, context)\u001b[0m\n\u001b[1;32m 443\u001b[0m chained_exc_ids\u001b[38;5;241m.\u001b[39madd(\u001b[38;5;28mid\u001b[39m(exception[\u001b[38;5;241m1\u001b[39m]))\n\u001b[1;32m 444\u001b[0m chained_exceptions_tb_offset \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m 445\u001b[0m out_list \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 446\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 447\u001b[0m \u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mchained_exc_ids\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 448\u001b[0m \u001b[43m \u001b[49m\u001b[43mchained_exceptions_tb_offset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 449\u001b[0m \u001b[38;5;241m+\u001b[39m chained_exception_message\n\u001b[1;32m 450\u001b[0m \u001b[38;5;241m+\u001b[39m out_list)\n\u001b[1;32m 452\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out_list\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/IPython/core/ultratb.py:1112\u001b[0m, in \u001b[0;36mAutoFormattedTB.structured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1110\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1111\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtb \u001b[38;5;241m=\u001b[39m tb\n\u001b[0;32m-> 1112\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mFormattedTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1113\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/IPython/core/ultratb.py:1006\u001b[0m, in \u001b[0;36mFormattedTB.structured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1003\u001b[0m mode \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmode\n\u001b[1;32m 1004\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mode \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mverbose_modes:\n\u001b[1;32m 1005\u001b[0m \u001b[38;5;66;03m# Verbose modes need a full traceback\u001b[39;00m\n\u001b[0;32m-> 1006\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mVerboseTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1007\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\n\u001b[1;32m 1008\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1009\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMinimal\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 1010\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ListTB\u001b[38;5;241m.\u001b[39mget_exception_only(\u001b[38;5;28mself\u001b[39m, etype, value)\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/IPython/core/ultratb.py:859\u001b[0m, in \u001b[0;36mVerboseTB.structured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 850\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstructured_traceback\u001b[39m(\n\u001b[1;32m 851\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 852\u001b[0m etype: \u001b[38;5;28mtype\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 856\u001b[0m number_of_lines_of_context: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m5\u001b[39m,\n\u001b[1;32m 857\u001b[0m ):\n\u001b[1;32m 858\u001b[0m \u001b[38;5;124;03m\"\"\"Return a nice text document describing the traceback.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 859\u001b[0m formatted_exception \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mformat_exception_as_a_whole\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 860\u001b[0m \u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 862\u001b[0m colors \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mColors \u001b[38;5;66;03m# just a shorthand + quicker name lookup\u001b[39;00m\n\u001b[1;32m 863\u001b[0m colorsnormal \u001b[38;5;241m=\u001b[39m colors\u001b[38;5;241m.\u001b[39mNormal \u001b[38;5;66;03m# used a lot\u001b[39;00m\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/IPython/core/ultratb.py:793\u001b[0m, in \u001b[0;36mVerboseTB.format_exception_as_a_whole\u001b[0;34m(self, etype, evalue, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m 790\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(tb_offset, \u001b[38;5;28mint\u001b[39m)\n\u001b[1;32m 791\u001b[0m head \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprepare_header(etype, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlong_header)\n\u001b[1;32m 792\u001b[0m records \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 793\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_records\u001b[49m\u001b[43m(\u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mif\u001b[39;00m etb \u001b[38;5;28;01melse\u001b[39;00m []\n\u001b[1;32m 794\u001b[0m )\n\u001b[1;32m 796\u001b[0m frames \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 797\u001b[0m skipped \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/IPython/core/ultratb.py:848\u001b[0m, in \u001b[0;36mVerboseTB.get_records\u001b[0;34m(self, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m 842\u001b[0m formatter \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 843\u001b[0m options \u001b[38;5;241m=\u001b[39m stack_data\u001b[38;5;241m.\u001b[39mOptions(\n\u001b[1;32m 844\u001b[0m before\u001b[38;5;241m=\u001b[39mbefore,\n\u001b[1;32m 845\u001b[0m after\u001b[38;5;241m=\u001b[39mafter,\n\u001b[1;32m 846\u001b[0m pygments_formatter\u001b[38;5;241m=\u001b[39mformatter,\n\u001b[1;32m 847\u001b[0m )\n\u001b[0;32m--> 848\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mstack_data\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mFrameInfo\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstack_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m[tb_offset:]\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/stack_data/core.py:564\u001b[0m, in \u001b[0;36mFrameInfo.stack_data\u001b[0;34m(cls, frame_or_tb, options, collapse_repeated_frames)\u001b[0m\n\u001b[1;32m 548\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m 549\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstack_data\u001b[39m(\n\u001b[1;32m 550\u001b[0m \u001b[38;5;28mcls\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 554\u001b[0m collapse_repeated_frames: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 555\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Union[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mFrameInfo\u001b[39m\u001b[38;5;124m'\u001b[39m, RepeatedFrames]]:\n\u001b[1;32m 556\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 557\u001b[0m \u001b[38;5;124;03m An iterator of FrameInfo and RepeatedFrames objects representing\u001b[39;00m\n\u001b[1;32m 558\u001b[0m \u001b[38;5;124;03m a full traceback or stack. Similar consecutive frames are collapsed into RepeatedFrames\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 562\u001b[0m \u001b[38;5;124;03m and optionally an Options object to configure.\u001b[39;00m\n\u001b[1;32m 563\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 564\u001b[0m stack \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43miter_stack\u001b[49m\u001b[43m(\u001b[49m\u001b[43mframe_or_tb\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 566\u001b[0m \u001b[38;5;66;03m# Reverse the stack from a frame so that it's in the same order\u001b[39;00m\n\u001b[1;32m 567\u001b[0m \u001b[38;5;66;03m# as the order from a traceback, which is the order of a printed\u001b[39;00m\n\u001b[1;32m 568\u001b[0m \u001b[38;5;66;03m# traceback when read top to bottom (most recent call last)\u001b[39;00m\n\u001b[1;32m 569\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_frame(frame_or_tb):\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/stack_data/utils.py:97\u001b[0m, in \u001b[0;36miter_stack\u001b[0;34m(frame_or_tb)\u001b[0m\n\u001b[1;32m 95\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m frame_or_tb:\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m frame_or_tb\n\u001b[0;32m---> 97\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43mis_frame\u001b[49m\u001b[43m(\u001b[49m\u001b[43mframe_or_tb\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 98\u001b[0m frame_or_tb \u001b[38;5;241m=\u001b[39m frame_or_tb\u001b[38;5;241m.\u001b[39mf_back\n\u001b[1;32m 99\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/stack_data/utils.py:90\u001b[0m, in \u001b[0;36mis_frame\u001b[0;34m(frame_or_tb)\u001b[0m\n\u001b[1;32m 89\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mis_frame\u001b[39m(frame_or_tb: Union[FrameType, TracebackType]) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mbool\u001b[39m:\n\u001b[0;32m---> 90\u001b[0m \u001b[43massert_\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43misinstance\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mframe_or_tb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mtypes\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mFrameType\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtypes\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTracebackType\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 91\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(frame_or_tb, (types\u001b[38;5;241m.\u001b[39mFrameType,))\n",
"File \u001b[0;32m/mount-storage/TTS/tts-env/lib/python3.8/site-packages/stack_data/utils.py:176\u001b[0m, in \u001b[0;36massert_\u001b[0;34m(condition, error)\u001b[0m\n\u001b[1;32m 174\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(error, \u001b[38;5;28mstr\u001b[39m):\n\u001b[1;32m 175\u001b[0m error \u001b[38;5;241m=\u001b[39m \u001b[38;5;167;01mAssertionError\u001b[39;00m(error)\n\u001b[0;32m--> 176\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m error\n",
"\u001b[0;31mAssertionError\u001b[0m: "
]
}
],
"outputs": [],
"source": [
"trainer.fit()"
]