tf.raw_ops.SparseApplyAdagradDA
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Update entries in 'var' and 'accum' according to the proximal adagrad scheme.
tf.raw_ops.SparseApplyAdagradDA(
var,
gradient_accumulator,
gradient_squared_accumulator,
grad,
indices,
lr,
l1,
l2,
global_step,
use_locking=False,
name=None
)
Args |
|---|
var
|
A mutable Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, qint16, quint16, uint16, complex128, half, uint32, uint64.
Should be from a Variable().
|
gradient_accumulator
|
A mutable Tensor. Must have the same type as var.
Should be from a Variable().
|
gradient_squared_accumulator
|
A mutable Tensor. Must have the same type as var.
Should be from a Variable().
|
grad
|
A Tensor. Must have the same type as var. The gradient.
|
indices
|
A Tensor. Must be one of the following types: int32, int64.
A vector of indices into the first dimension of var and accum.
|
lr
|
A Tensor. Must have the same type as var.
Learning rate. Must be a scalar.
|
l1
|
A Tensor. Must have the same type as var.
L1 regularization. Must be a scalar.
|
l2
|
A Tensor. Must have the same type as var.
L2 regularization. Must be a scalar.
|
global_step
|
A Tensor of type int64.
Training step number. Must be a scalar.
|
use_locking
|
An optional bool. Defaults to False.
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.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A mutable Tensor. Has the same type as var.
|
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.raw_ops.SparseApplyAdagradDA\n\n\u003cbr /\u003e\n\nUpdate entries in '*var' and '*accum' according to the proximal adagrad scheme.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.SparseApplyAdagradDA`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SparseApplyAdagradDA)\n\n\u003cbr /\u003e\n\n tf.raw_ops.SparseApplyAdagradDA(\n var,\n gradient_accumulator,\n gradient_squared_accumulator,\n grad,\n indices,\n lr,\n l1,\n l2,\n global_step,\n use_locking=False,\n name=None\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `var` | A mutable `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `qint16`, `quint16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`. Should be from a Variable(). |\n| `gradient_accumulator` | A mutable `Tensor`. Must have the same type as `var`. Should be from a Variable(). |\n| `gradient_squared_accumulator` | A mutable `Tensor`. Must have the same type as `var`. Should be from a Variable(). |\n| `grad` | A `Tensor`. Must have the same type as `var`. The gradient. |\n| `indices` | A `Tensor`. Must be one of the following types: `int32`, `int64`. A vector of indices into the first dimension of var and accum. |\n| `lr` | A `Tensor`. Must have the same type as `var`. Learning rate. Must be a scalar. |\n| `l1` | A `Tensor`. Must have the same type as `var`. L1 regularization. Must be a scalar. |\n| `l2` | A `Tensor`. Must have the same type as `var`. L2 regularization. Must be a scalar. |\n| `global_step` | A `Tensor` of type `int64`. Training step number. Must be a scalar. |\n| `use_locking` | An optional `bool`. Defaults to `False`. 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. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A mutable `Tensor`. Has the same type as `var`. ||\n\n\u003cbr /\u003e"]]
