ZigZag - Deep Learning Hardware Design Space Exploration
This repository presents the novel version of our tried-and-tested hardware Architecture-Mapping Design Space Exploration (DSE) Framework for Deep Learning (DL) accelerators. ZigZag bridges the gap between algorithmic DL decisions and their acceleration cost on specialized accelerators through a fast and accurate hardware cost estimation.
LayerAttribute Class Reference

Abstract Base Class to represent any layer attribute. More...

Inheritance diagram for LayerAttribute:
Collaboration diagram for LayerAttribute:

Public Member Functions

def __init__ (self, Any data)
 
int __len__ (self)
 
Iterator[Any] __iter__ (self)
 
def __getitem__ (self, Any key)
 
bool __contains__ (self, Any key)
 
def __str__ (self)
 
def __repr__ (self)
 
Any __jsonrepr__ (self)
 
def __eq__ (self, object other)
 
def __hash__ (self)
 

Public Attributes

 data
 

Detailed Description

Abstract Base Class to represent any layer attribute.

Constructor & Destructor Documentation

◆ __init__()

def __init__ (   self,
Any  data 
)

Member Function Documentation

◆ __contains__()

bool __contains__ (   self,
Any  key 
)

◆ __eq__()

def __eq__ (   self,
object  other 
)

◆ __getitem__()

def __getitem__ (   self,
Any  key 
)

◆ __hash__()

def __hash__ (   self)

Reimplemented in LayerTemporalOrdering, and SpatialMapping.

◆ __iter__()

Iterator[Any] __iter__ (   self)

◆ __jsonrepr__()

Any __jsonrepr__ (   self)
Here is the call graph for this function:

◆ __len__()

int __len__ (   self)

◆ __repr__()

def __repr__ (   self)

◆ __str__()

def __str__ (   self)

Reimplemented in MemoryOperandLinks, and SpatialMapping.

Member Data Documentation

◆ data

data

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