E2-F5-TTS / src /f5_tts /scripts /count_params_gflops.py
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import sys
import os
sys.path.append(os.getcwd())
from f5_tts.model import CFM, DiT
import torch
import thop
""" ~155M """
# transformer = UNetT(dim = 768, depth = 20, heads = 12, ff_mult = 4)
# transformer = UNetT(dim = 768, depth = 20, heads = 12, ff_mult = 4, text_dim = 512, conv_layers = 4)
# transformer = DiT(dim = 768, depth = 18, heads = 12, ff_mult = 2)
# transformer = DiT(dim = 768, depth = 18, heads = 12, ff_mult = 2, text_dim = 512, conv_layers = 4)
# transformer = DiT(dim = 768, depth = 18, heads = 12, ff_mult = 2, text_dim = 512, conv_layers = 4, long_skip_connection = True)
# transformer = MMDiT(dim = 512, depth = 16, heads = 16, ff_mult = 2)
""" ~335M """
# FLOPs: 622.1 G, Params: 333.2 M
# transformer = UNetT(dim = 1024, depth = 24, heads = 16, ff_mult = 4)
# FLOPs: 363.4 G, Params: 335.8 M
transformer = DiT(dim=1024, depth=22, heads=16, ff_mult=2, text_dim=512, conv_layers=4)
model = CFM(transformer=transformer)
target_sample_rate = 24000
n_mel_channels = 100
hop_length = 256
duration = 20
frame_length = int(duration * target_sample_rate / hop_length)
text_length = 150
flops, params = thop.profile(
model, inputs=(torch.randn(1, frame_length, n_mel_channels), torch.zeros(1, text_length, dtype=torch.long))
)
print(f"FLOPs: {flops / 1e9} G")
print(f"Params: {params / 1e6} M")