def synthesize(model, step, configs, vocoder, batchs):
preprocess_config, model_config, train_config = configs
for batch in batchs:
batch = to_device(batch, device)
with torch.no_grad():
# Forward
output = model(*(batch[2:]), )
synth_samples(
batch,
output,
vocoder,
model_config,
preprocess_config,
train_config["path"]["result_path"],
)
def synthesize(model, step, configs, vocoder, batchs, control_values):
preprocess_config, model_config, train_config = configs
pitch_control, energy_control, duration_control = control_values
for batch in batchs:
batch = to_device(batch, device)
with torch.no_grad():
# Forward
output = model(*(batch[2:]),
p_control=pitch_control,
e_control=energy_control,
d_control=duration_control)
synth_samples(
batch,
output,
vocoder,
model_config,
preprocess_config,
train_config["path"]["result_path"],
)