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)