mirror of
https://github.com/storytold/torchscript-models.git
synced 2026-10-19 07:42:59 +00:00
Brandon Thomas
44 lines
1.9 KiB
Python
Executable File
44 lines
1.9 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
# From: https://github.com/pytorch/pytorch/issues/20356#issuecomment-545572400
|
|
import torch
|
|
|
|
from collections import OrderedDict
|
|
import re
|
|
import yaml
|
|
|
|
from model_melgan.generator import load_melgan
|
|
|
|
#torch.set_default_tensor_type('torch.DoubleTensor')
|
|
|
|
#model_checkpoint_path = '/home/bt/models/melgan-swpark/trumptxlearn183_fa14347_7675.pt'
|
|
model_checkpoint_path = '/home/bt/models/melgan-swpark/ljs-high-pitch_8741385_6975.pt'
|
|
model_checkpoint_path = '/home/bt/models/melgan-swpark/trump-txlearn-2020.05.05_8741385_7525.pt'
|
|
model_checkpoint_path = '/home/bt/models/melgan-swpark/trump-txlearn-2020.05.05_8741385_13675.pt'
|
|
model_checkpoint_path = '/home/bt/models/melgan-swpark/melgan_trump_txlearn_2020-05-30_steno_chkpt9800.pt'
|
|
|
|
melgan_model = load_melgan(model_checkpoint_path)
|
|
|
|
#output_filename = 'shared_melgan_container2.pt'
|
|
#output_filename = 'melgan_ljs-high-pitch_container.pt'
|
|
output_filename = 'melgan_trump-txlearn-2020.05.05.jit'
|
|
output_filename = 'melgan_trump-txlearn-2020.05.05_13675.jit'
|
|
output_filename = 'melgan_trump_txlearn_2020-05-30_steno_chkpt9800.torchjit'
|
|
|
|
# NB: Tracing evaluates the model on input and unrolls and hardcodes branching
|
|
# and loops. Scripting allows these to remain by converting the entire program
|
|
# to TorchScript. Scripting seems MUCH faster, is also harder get working.
|
|
trace_model = True
|
|
if trace_model:
|
|
print('Tracing model and saving as: {}'.format(output_filename))
|
|
mel_file = './sample/LJ002-0320.mel'
|
|
mel = torch.load(mel_file, map_location=torch.device('cpu'))
|
|
# NB: Getting `Tracing failed sanity checks! Graphs differed across invocations!`
|
|
traced_script_module = torch.jit.trace(melgan_model, mel, check_trace=True)
|
|
traced_script_module.save(output_filename)
|
|
else:
|
|
print('Saving script model as: {}'.format(output_filename))
|
|
container = torch.jit.script(melgan_model)
|
|
container.save(output_filename)
|
|
|
|
|