def __init__(self,
learning_rate=0.001,
beta1=0.9,
beta2=0.999,
dtype=bb.DType.FP32):
core_optimizer = bb.search_core_object(
'OptimizerAdam', [dtype]).create(learning_rate=learning_rate,
beta1=beta1,
beta2=beta2)
super(OptimizerAdam, self).__init__(core_optimizer=core_optimizer)
def __init__(self, dtype=bb.DType.FP32):
core_loss = bb.search_core_object('LossSoftmaxCrossEntropy',
[dtype]).create()
super(LossSoftmaxCrossEntropy, self).__init__(core_loss=core_loss)
def __init__(self, reduction="mean", dtype=bb.DType.FP32):
core_loss = bb.search_core_object('LossMeanSquaredError',
[dtype]).create(reduction=reduction)
super(LossMeanSquaredError, self).__init__(core_loss=core_loss)
def __init__(self, dtype=bb.DType.FP32):
core_metrics = bb.search_core_object(
'MetricsBinaryCategoricalAccuracy', [dtype]).create()
super(MetricsBinaryCategoricalAccuracy,
self).__init__(core_metrics=core_metrics)
def __init__(self, dtype=bb.DType.FP32):
core_metrics = bb.search_core_object('MetricsMeanSquaredError',
[dtype]).create()
super(MetricsMeanSquaredError,
self).__init__(core_metrics=core_metrics)
def __init__(self, learning_rate=0.01, dtype=bb.DType.FP32):
core_optimizer = bb.search_core_object(
'OptimizerAdaGrad', [dtype]).create(learning_rate=learning_rate)
super(OptimizerAdaGrad, self).__init__(core_optimizer=core_optimizer)