Update '*var' according to the Adam algorithm.
tf.raw_ops.ResourceApplyAdamWithAmsgrad( var, m, v, vhat, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad, use_locking=False, name=None )
Args | |
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var | A Tensor of type resource . Should be from a Variable(). |
m | A Tensor of type resource . Should be from a Variable(). |
v | A Tensor of type resource . Should be from a Variable(). |
vhat | A Tensor of type resource . Should be from a Variable(). |
beta1_power | A Tensor . Must be one of the following types: float32 , float64 , int32 , uint8 , int16 , int8 , complex64 , int64 , qint8 , quint8 , qint32 , bfloat16 , uint16 , complex128 , half , uint32 , uint64 . Must be a scalar. |
beta2_power | A Tensor . Must have the same type as beta1_power . Must be a scalar. |
lr | A Tensor . Must have the same type as beta1_power . Scaling factor. Must be a scalar. |
beta1 | A Tensor . Must have the same type as beta1_power . Momentum factor. Must be a scalar. |
beta2 | A Tensor . Must have the same type as beta1_power . Momentum factor. Must be a scalar. |
epsilon | A Tensor . Must have the same type as beta1_power . Ridge term. Must be a scalar. |
grad | A Tensor . Must have the same type as beta1_power . The gradient. |
use_locking | An optional bool . Defaults to False . If True , updating of the var, m, and v tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention. |
name | A name for the operation (optional). |
Returns | |
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The created Operation. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/ResourceApplyAdamWithAmsgrad