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	Operation
out	:: tensorflow::Output

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

Fungsi statis publik
UseLocking (bool x)	Attrs

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
)