def compute_loss(self, hidden_outputs, targets, loss_fn, updates):
if loss_fn == 'memory':
return models.memory_efficiency_cross_entropy_loss(hidden_outputs, self.decoder, targets, self.criterion, self.config)
elif loss_fn == 'emb':
return models.prior_knowledge_loss(hidden_outputs, self.decoder, targets, self.criterion, self.config, updates)
else:
return models.cross_entropy_loss(hidden_outputs, self.decoder, targets, self.criterion, self.config)
def compute_loss(self, hidden_outputs, targets, memory_efficiency):
if memory_efficiency:
return models.memory_efficiency_cross_entropy_loss(
hidden_outputs, self.decoder, targets, self.criterion,
self.config)
else:
return models.cross_entropy_loss(hidden_outputs, self.decoder,
targets, self.criterion,
self.config)
def compute_loss(self, hidden_outputs, targets):
# print('-'*20)
# print('hidden_outputs.shape: ',hidden_outputs.shape)
# print('hidden_outputs: ', hidden_outputs)
# print('targets.shape: ', targets.shape)
# print('targets: ', targets)
return models.cross_entropy_loss(hidden_outputs, targets,
self.criterion)
def compute_loss(self, hidden_outputs, hidden_outputs_dir, targets,
targets_dir, memory_efficiency):
if memory_efficiency:
return models.memory_efficiency_cross_entropy_loss(
hidden_outputs, self.decoder, targets, self.criterion,
self.config)
else:
sgm_loss_speaker, num_total, num_correct = models.cross_entropy_loss(
hidden_outputs, self.decoder, targets, self.criterion,
self.config)
#sgm_loss_direction = models.mmse_loss2(hidden_outputs_dir, self.decoder, targets_dir, self.loss_for_dir)
sgm_loss_direction, num_total_dir, num_correct_dir = models.cross_entropy_loss_dir(
hidden_outputs_dir, self.decoder, targets_dir,
self.criterion_dir, self.config)
print("sgm_loss_speaker:", sgm_loss_speaker)
print("sgm_loss_direction:", sgm_loss_direction)
sgm_loss = sgm_loss_speaker + sgm_loss_direction
return sgm_loss, num_total, num_correct, num_total_dir, num_correct_dir
def compute_loss(self, outputs, tgt):
return models.cross_entropy_loss(outputs, tgt, self.criterion)
def compute_loss(self, hidden_outputs, targets):
return models.cross_entropy_loss(hidden_outputs, targets,
self.criterion)
def compute_loss(self, hidden_outputs, decoder, targets, criterion,
loss_fn, updates):
return models.cross_entropy_loss(hidden_outputs, decoder, targets,
criterion, self.config)
