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Evaluation
import torch
from parler_tts import ParlerTTSForConditionalGeneration
from transformers import AutoTokenizer
import soundfile as sf
device = "cuda:0" if torch.cuda.is_available() else "cpu"
model = ParlerTTSForConditionalGeneration.from_pretrained('./parler-tts/output_dir_training/').to(device)
tokenizer = AutoTokenizer.from_pretrained("ai4bharat/indic-parler-tts")
description_tokenizer = AutoTokenizer.from_pretrained(model.config.text_encoder._name_or_path)
prompt = "ಸರಸ್ವತಿ ಹಿಂದೂ ಧರ್ಮದಲ್ಲಿ ಜ್ಞಾನ ಮತ್ತು ಕಲೆಗಳ ದೇವತೆ. ಸರಸ್ವತಿಯನ್ನು ಬ್ರಹ್ಮದೇವರ ಪತ್ನಿಯೆಂದೂ, ಶ್ವೇತವಸ್ತ್ರಗಳನ್ನು ಧರಿಸಿದವಳೆಂದೂ ಪೂಜಿಸುವರು."
description = "Saraswathi speaks Kannada in a natural tone"
description_input_ids = description_tokenizer(description, return_tensors="pt").to(device)
prompt_input_ids = tokenizer(prompt, return_tensors="pt").to(device)
generation = model.generate(input_ids=description_input_ids.input_ids, attention_mask=description_input_ids.attention_mask, prompt_input_ids=prompt_input_ids.input_ids, prompt_attention_mask=prompt_input_ids.attention_mask)
audio_arr = generation.cpu().numpy().squeeze()
sf.write("indic_tts_out_july31.wav", audio_arr, model.config.sampling_rate)
