tf.raw_ops.ResourceSparseApplyAdagradDA
Update entries in 'var' and 'accum' according to the proximal adagrad scheme.
tf.raw_ops.ResourceSparseApplyAdagradDA(
var, gradient_accumulator, gradient_squared_accumulator, grad, indices, lr, l1,
l2, global_step, use_locking=False, name=None
)
| Args | |
|---|---|
var |
A Tensor of type resource. Should be from a Variable(). |
gradient_accumulator |
A Tensor of type resource. Should be from a Variable(). |
gradient_squared_accumulator |
A Tensor of type resource. Should be from a Variable(). |
grad |
A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64. 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 grad. Learning rate. Must be a scalar. |
l1 |
A Tensor. Must have the same type as grad. L1 regularization. Must be a scalar. |
l2 |
A Tensor. Must have the same type as grad. 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 | |
|---|---|
| The created Operation. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/ResourceSparseApplyAdagradDA