SGD
Customizes the SGD optimizer.
Prototype
1 | def create_hash_optimizer(learning_rate, use_locking=False, name="GradientDescent", use_fusion_optim=False, weight_decay=None) |
Parameters
Parameter |
Type |
Mandatory/Optional |
Description |
|---|---|---|---|
learning_rate |
float/tf.Tensor |
Mandatory |
Learning rate Value range: [0.0, 10.0] |
use_locking |
bool |
Optional |
Prevents concurrent updates of variables. Default value: False Value range:
|
name |
string |
Optional |
Name of the optimizer Default value: GradientDescent Name length range: [1, 200] |
use_fusion_optim |
bool |
Optional |
Whether to enable operator acceleration. Default value: False Value range:
|
weight_decay |
float |
Optional |
Weight decay coefficient. Default value: None, indicating that weight decay is disabled. Value range: [1e-5, 1e-2] |
Return Value
An instance object of the CustomizedGradientDescent optimizer.
Example
1 2 | from mx_rec.optimizers.gradient_descent import create_hash_optimizer hashtable_optimizer = create_hash_optimizer(0.001) |
Parent topic: Optimizers