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.
LayerOperandPrecision Class Reference

Contains the bit precision of each layer operand. More...

Inheritance diagram for LayerOperandPrecision:
Collaboration diagram for LayerOperandPrecision:

Public Member Functions

def __init__ (self, dict[LayerOperand, int] data)
 
def __getitem__ (self, LayerOperand layer_op)
 
int final_output_precision (self)
 Return the precision of either the final output (if defined by user) or the intermediate output. More...
 
- Public Member Functions inherited from LayerAttribute
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
 
- Public Attributes inherited from LayerAttribute
 data
 

Detailed Description

Contains the bit precision of each layer operand.

Constructor & Destructor Documentation

◆ __init__()

def __init__ (   self,
dict[LayerOperand, int]  data 
)

Member Function Documentation

◆ __getitem__()

def __getitem__ (   self,
LayerOperand  layer_op 
)

◆ final_output_precision()

int final_output_precision (   self)

Return the precision of either the final output (if defined by user) or the intermediate output.

Member Data Documentation

◆ data

data

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