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tensorflow :: ops :: ApplyFtrl

#include <training_ops.h>

Update '* var' sesuai dengan skema Ftrl-proksimal.

Ringkasan

accum_new = accum + grad * grad linear + = grad - (accum_new ^ (- lr_power) - accum ^ (- lr_power)) / lr * var kuadrat = 1.0 / (accum_new ^ (lr_power) * lr) + 2 * l2 var = (tanda (linear) * l1 - linear) / kuadrat jika | linear | > L1 lain 0.0 accum = accum_new

argumen:

  • Ruang lingkup: Sebuah Ruang Lingkup objek
  • var: Harus dari Variable a ().
  • accum: Harus dari Variable a ().
  • linear: Harus dari Variable a ().
  • grad: gradien The.
  • lr: Scaling faktor. Harus skalar.
  • l1: L1 regularisasi. Harus skalar.
  • l2: L2 regularisasi. Harus skalar.
  • lr_power: faktor Scaling. Harus skalar.

Atribut opsional (lihat Attrs ):

  • use_locking: Jika True , pemutakhiran var dan accum tensor akan dilindungi oleh kunci; jika perilaku tidak terdefinisi, tapi mungkin menunjukkan kurang pertentangan.

Pengembalian:

  • Output : Sama seperti "var".

Konstruktor dan Destructors

ApplyFtrl (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input linear, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input lr_power)
ApplyFtrl (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input linear, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input lr_power, const ApplyFtrl::Attrs & attrs)

atribut umum

operation
out

fungsi publik

node () const
::tensorflow::Node *
operator::tensorflow::Input () const
operator::tensorflow::Output () const

fungsi public static

MultiplyLinearByLr (bool x)
UseLocking (bool x)

struct

tensorflow :: ops :: ApplyFtrl :: attrs

Setter atribut opsional untuk ApplyFtrl .

atribut umum

operasi

 Operation operation

di luar

:: tensorflow::Output out

fungsi publik

ApplyFtrl

 ApplyFtrl(
  const :: tensorflow::Scope & scope,
  :: tensorflow::Input var,
  :: tensorflow::Input accum,
  :: tensorflow::Input linear,
  :: tensorflow::Input grad,
  :: tensorflow::Input lr,
  :: tensorflow::Input l1,
  :: tensorflow::Input l2,
  :: tensorflow::Input lr_power
)

ApplyFtrl

 ApplyFtrl(
  const :: tensorflow::Scope & scope,
  :: tensorflow::Input var,
  :: tensorflow::Input accum,
  :: tensorflow::Input linear,
  :: tensorflow::Input grad,
  :: tensorflow::Input lr,
  :: tensorflow::Input l1,
  :: tensorflow::Input l2,
  :: tensorflow::Input lr_power,
  const ApplyFtrl::Attrs & attrs
)

simpul

::tensorflow::Node * node() const 

Operator :: tensorflow :: Masukan

 operator::tensorflow::Input() const 

Operator :: tensorflow :: Keluaran

 operator::tensorflow::Output() const 

fungsi public static

MultiplyLinearByLr

 Attrs MultiplyLinearByLr(
  bool x
)

UseLocking

 Attrs UseLocking(
  bool x
)