def get_validation_loss(dataloader: torch.utils.data.DataLoader,
model: AcousticModel, P: k2.Fsa, device: torch.device,
graph_compiler: MmiMbrTrainingGraphCompiler):
total_loss = 0.
total_mmi_loss = 0.
total_mbr_loss = 0.
total_frames = 0. # for display only
total_all_frames = 0. # all frames including those seqs that failed.
model.eval()
for batch_idx, batch in enumerate(dataloader):
mmi_loss, mbr_loss, frames, all_frames = get_loss(
batch=batch,
model=model,
P=P,
device=device,
graph_compiler=graph_compiler,
is_training=False)
cur_loss = mmi_loss + mbr_loss
total_loss += cur_loss
total_mmi_loss += mmi_loss
total_mbr_loss += mbr_loss
total_frames += frames
total_all_frames += all_frames
return total_loss, total_mmi_loss, total_mbr_loss, total_frames, total_all_frames
def get_validation_objf(dataloader: torch.utils.data.DataLoader,
model: AcousticModel,
P: k2.Fsa,
device: torch.device,
graph_compiler: MmiTrainingGraphCompiler,
den_scale: float = 1):
total_objf = 0.
total_frames = 0. # for display only
total_all_frames = 0. # all frames including those seqs that failed.
model.eval()
for batch_idx, batch in enumerate(dataloader):
objf, frames, all_frames = get_objf(batch=batch,
model=model,
P=P,
device=device,
graph_compiler=graph_compiler,
is_training=False,
is_update=False,
den_scale=den_scale)
total_objf += objf
total_frames += frames
total_all_frames += all_frames
return total_objf, total_frames, total_all_frames
def get_validation_objf(
dataloader: torch.utils.data.DataLoader,
model: AcousticModel,
ali_model: Optional[AcousticModel],
P: k2.Fsa,
device: torch.device,
graph_compiler: MmiTrainingGraphCompiler,
scaler: GradScaler,
den_scale: float = 1,
):
total_objf = 0.
total_frames = 0. # for display only
total_all_frames = 0. # all frames including those seqs that failed.
model.eval()
from torchaudio.datasets.utils import bg_iterator
for batch_idx, batch in enumerate(bg_iterator(dataloader, 2)):
objf, frames, all_frames = get_objf(batch=batch,
model=model,
ali_model=ali_model,
P=P,
device=device,
graph_compiler=graph_compiler,
is_training=False,
is_update=False,
den_scale=den_scale,
scaler=scaler)
total_objf += objf
total_frames += frames
total_all_frames += all_frames
return total_objf, total_frames, total_all_frames
def get_validation_objf(
dataloader: torch.utils.data.DataLoader,
model: AcousticModel,
device: torch.device,
):
total_objf = 0.0
total_frames = 0.0 # for display only
model.eval()
for batch_idx, batch in enumerate(dataloader):
objf, frames = get_objf(batch, model, device, False)
total_objf += objf
total_frames += frames
return total_objf, total_frames
def get_validation_objf(dataloader: torch.utils.data.DataLoader,
model: AcousticModel, device: torch.device,
graph_compiler: CtcTrainingGraphCompiler):
total_objf = 0.
total_frames = 0. # for display only
total_all_frames = 0. # all frames including those seqs that failed.
model.eval()
for batch_idx, batch in enumerate(dataloader):
objf, frames, all_frames = get_objf(batch, model, device,
graph_compiler, False)
total_objf += objf
total_frames += frames
total_all_frames += all_frames
return total_objf, total_frames, total_all_frames
