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.
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Operand from the layer definition, e.g. More...
Public Member Functions | |
def | is_output (self) |
def | is_final_output (self) |
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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) |
Operand from the layer definition, e.g.
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def is_final_output | ( | self | ) |
def is_output | ( | self | ) |