Caffe2 - Python API
A deep learning, cross platform ML framework
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caffe2.python.optimizer.AdadeltaOptimizer Class Reference
Inheritance diagram for caffe2.python.optimizer.AdadeltaOptimizer:

Public Member Functions

def __init__ (self, alpha=0.01, epsilon=1e-4, decay=0.95, policy="fixed", sparse_dedup_aggregator=None, engine='', kwargs)
def scale_learning_rate (self, scale)
- Public Member Functions inherited from caffe2.python.optimizer.Optimizer
def __init__ (self)
def __call__ (self, net, param_init_net, param, grad=None)
def get_cpu_blob_name (self, base_str, node_name='')
def get_gpu_blob_name (self, base_str, gpu_id, node_name)
def make_unique_blob_name (self, base_str)
def build_lr (self, net, param_init_net, base_learning_rate, learning_rate_blob=None, policy="fixed", iter_val=0, kwargs)
def add_lr_multiplier (self, lr_multiplier)
def get_auxiliary_parameters (self)
def scale_learning_rate (self, args, kwargs)
def create_lars_inputs (self, param_init_net, weight_decay, trust, lr_max)

Public Attributes


Additional Inherited Members

- Static Public Member Functions inherited from caffe2.python.optimizer.Optimizer
def dedup (net, sparse_dedup_aggregator, grad)

Detailed Description

Definition at line 738 of file

Constructor & Destructor Documentation

def caffe2.python.optimizer.AdadeltaOptimizer.__init__ (   self,
  alpha = 0.01,
  epsilon = 1e-4,
  decay = 0.95,
  policy = "fixed",
  sparse_dedup_aggregator = None,
  engine = '',
Constructor function to add Adadelta Optimizer

    alpha: learning rate
    epsilon: attribute of Adadelta to avoid numerical issues
    decay: attribute of Adadelta to decay the squared gradient sum
    policy: specifies how learning rate should be applied, options are
      "fixed", "step", "exp", etc.
    sparse_dedup_aggregator: specifies deduplication strategy for
      gradient slices. Works while using sparse gradients. Options
      include "mean" and "sum".
    engine: the engine used, options include "", "CUDNN", etc.

Definition at line 740 of file

The documentation for this class was generated from the following file: