def Evaluator(criterion):
loss, metric = Trainer._get_loss_metric(criterion)
parameters = set(loss.parameters)
if metric:
parameters |= set(metric.parameters)
dummy_learner = momentum_sgd(tuple(parameters),
lr = learning_rate_schedule(1, UnitType.minibatch),
momentum = momentum_as_time_constant_schedule(0))
return Trainer(None, (loss, metric), dummy_learner)
def Evaluator(criterion):
loss, metric = Trainer._get_loss_metric(criterion)
parameters = set(loss.parameters)
if metric:
parameters |= set(metric.parameters)
dummy_learner = momentum_sgd(tuple(parameters),
lr=learning_parameter_schedule(1),
momentum=momentum_schedule(0))
return Trainer(None, (loss, metric), dummy_learner)
def Evaluator(model, criterion):
from cntk import Trainer
from cntk.learners import momentum_sgd, momentum_schedule_per_sample
loss, metric = Trainer._get_loss_metric(criterion)
parameters = set(loss.parameters)
if model:
parameters |= set(model.parameters)
if metric:
parameters |= set(metric.parameters)
dummy_learner = momentum_sgd(tuple(parameters),
lr=learning_parameter_schedule(1),
momentum=momentum_schedule_per_sample(0))
return Trainer(model, (loss, metric), dummy_learner)
def Evaluator(model, criterion):
from cntk import Trainer
from cntk.learners import momentum_sgd, learning_rate_schedule, UnitType, momentum_as_time_constant_schedule
loss, metric = Trainer._get_loss_metric(criterion)
parameters = set(loss.parameters)
if model:
parameters |= set(model.parameters)
if metric:
parameters |= set(metric.parameters)
dummy_learner = momentum_sgd(tuple(parameters),
lr = learning_rate_schedule(1, UnitType.minibatch),
momentum = momentum_as_time_constant_schedule(0))
return Trainer(model, (loss, metric), dummy_learner)
def Evaluator(model, criterion):
from cntk import Trainer
from cntk.learners import momentum_sgd, momentum_schedule_per_sample
loss, metric = Trainer._get_loss_metric(criterion)
parameters = set(loss.parameters)
if model:
parameters |= set(model.parameters)
if metric:
parameters |= set(metric.parameters)
dummy_learner = momentum_sgd(tuple(parameters),
lr = learning_parameter_schedule(1),
momentum = momentum_schedule_per_sample(0))
return Trainer(model, (loss, metric), dummy_learner)