aliran tensor:: operasi:: TerapkanAdagradDA

#include <training_ops.h>

Perbarui '*var' sesuai dengan skema adagrad proksimal.

Ringkasan

Argumen:

  • ruang lingkup: Objek Lingkup
  • var: Harus dari Variabel().
  • gradien_akumulator: Harus dari Variabel().
  • gradien_squared_accumulator: Harus dari Variabel().
  • lulusan: Gradien.
  • lr: Faktor penskalaan. Pasti skalar.
  • l1: Regularisasi L1. Pasti skalar.
  • l2: Regularisasi L2. Pasti skalar.
  • global_step: Nomor langkah pelatihan. Pasti skalar.

Atribut opsional (lihat Attrs ):

  • use_locking: Jika Benar, pembaruan tensor var dan accum akan dilindungi oleh kunci; jika tidak, perilaku tersebut tidak terdefinisikan, namun mungkin menunjukkan lebih sedikit pertentangan.

Pengembalian:

  • Output : Sama seperti "var".

Konstruktor dan Destruktor

ApplyAdagradDA (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input gradient_accumulator, :: tensorflow::Input gradient_squared_accumulator, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input global_step)
ApplyAdagradDA (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input gradient_accumulator, :: tensorflow::Input gradient_squared_accumulator, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input global_step, const ApplyAdagradDA::Attrs & attrs)

Atribut publik

operation
out

Fungsi publik

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

Fungsi statis publik

UseLocking (bool x)

Struktur

tensorflow:: ops:: TerapkanAdagradDA:: Attrs

Penyetel atribut opsional untuk ApplyAdagradDA .

Atribut publik

operasi

Operation operation

keluar

::tensorflow::Output out

Fungsi publik

TerapkanAdagradDA

 ApplyAdagradDA(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input gradient_accumulator,
  ::tensorflow::Input gradient_squared_accumulator,
  ::tensorflow::Input grad,
  ::tensorflow::Input lr,
  ::tensorflow::Input l1,
  ::tensorflow::Input l2,
  ::tensorflow::Input global_step
)

TerapkanAdagradDA

 ApplyAdagradDA(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input gradient_accumulator,
  ::tensorflow::Input gradient_squared_accumulator,
  ::tensorflow::Input grad,
  ::tensorflow::Input lr,
  ::tensorflow::Input l1,
  ::tensorflow::Input l2,
  ::tensorflow::Input global_step,
  const ApplyAdagradDA::Attrs & attrs
)

simpul

::tensorflow::Node * node() const 

operator::tensorflow::Masukan

 operator::tensorflow::Input() const 

operator::tensorflow::Keluaran

 operator::tensorflow::Output() const 

Fungsi statis publik

Gunakan Penguncian

Attrs UseLocking(
  bool x
)