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.
LayerOperand Class Reference

Operand from the layer definition, e.g. More...

Inheritance diagram for LayerOperand:
Collaboration diagram for LayerOperand:

Public Member Functions

def is_output (self)
 
def is_final_output (self)
 
- Public Member Functions inherited from OperandABC
def __init__ (self, str name)
 
def name (self)
 Protect the class variable from reassignment (as this would invalidate the stored hash value) More...
 
def __eq__ (self, "OperandABC" other)
 
def __hash__ (self)
 Optimize performance by statically storing the hash. More...
 
def __str__ (self)
 
def __repr__ (self)
 
def __lt__ (self, "OperandABC" other)
 
def __ge__ (self, "OperandABC" other)
 
def __jsonrepr__ (self)
 

Detailed Description

Operand from the layer definition, e.g.

I, W, O.

Member Function Documentation

◆ is_final_output()

def is_final_output (   self)

◆ is_output()

def is_output (   self)

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