Uses of Class
org.bytedeco.javacpp.tensorflow.ResourceApplyMomentum.Attrs

Packages that use tensorflow.ResourceApplyMomentum.Attrs

Package	Description
org.bytedeco.javacpp

Uses of tensorflow.ResourceApplyMomentum.Attrs in org.bytedeco.javacpp

Methods in org.bytedeco.javacpp that return tensorflow.ResourceApplyMomentum.Attrs

Modifier and Type	Method and Description
tensorflow.ResourceApplyMomentum.Attrs	tensorflow.ResourceApplyMomentum.Attrs.position(long position)
tensorflow.ResourceApplyMomentum.Attrs	tensorflow.ResourceApplyMomentum.Attrs.use_locking_(boolean use_locking_)
tensorflow.ResourceApplyMomentum.Attrs	tensorflow.ResourceApplyMomentum.Attrs.use_nesterov_(boolean use_nesterov_)
static tensorflow.ResourceApplyMomentum.Attrs	tensorflow.ResourceApplyMomentum.UseLocking(boolean x)
tensorflow.ResourceApplyMomentum.Attrs	tensorflow.ResourceApplyMomentum.Attrs.UseLocking(boolean x) If True, updating of the var and accum tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.
static tensorflow.ResourceApplyMomentum.Attrs	tensorflow.ResourceApplyMomentum.UseNesterov(boolean x)
tensorflow.ResourceApplyMomentum.Attrs	tensorflow.ResourceApplyMomentum.Attrs.UseNesterov(boolean x) If True, the tensor passed to compute grad will be var - lr * momentum * accum, so in the end, the var you get is actually var - lr * momentum * accum.

Constructors in org.bytedeco.javacpp with parameters of type tensorflow.ResourceApplyMomentum.Attrs

Constructor and Description
ResourceApplyMomentum(tensorflow.Scope scope, tensorflow.Input var, tensorflow.Input accum, tensorflow.Input lr, tensorflow.Input grad, tensorflow.Input momentum, tensorflow.ResourceApplyMomentum.Attrs attrs)