Deeploy.DeeployTypes.TransientBuffer

class Deeploy.DeeployTypes.TransientBuffer(name: str = '', size=0)

Bases: VariableBuffer

Class to represent memory space required by kernels that is not covered by input and output tensors, e.g. im2col buffers in convolutions

Methods

__init__(name: str = '', size=0)

`__init__`([name, size])
`alloc`()	Return a string representation of the C code required to allocated this memory buffer
`dealloc`()	Return a string representation of the C code to deallocate/free this memory buffer at runtime
`fromNode`(node)
`has_live_aliases`(ctxt)	Checks whether this VariableBuffer has any live ancestors, i.e. buffers that are still live and are aliased by this buffer.
`init`()	Return a string representation of the C code to declare this memory buffer
`sizeInBytes`()	Returns the size of this VariableBuffer in bytes

Attributes

`initTemplate`	Holds the buffer's initialization code
`allocTemplate`	Holds the buffer's allocation code
`deallocTemplate`	Holds the buffer's deallocation code
`name`	Canonical name that this buffer is registered as in the NetworkContext
`shape`	Represents the dimensions of the underlying tensor as a sequence of dimension sizes

sizeInBytes() → int

Returns the size of this VariableBuffer in bytes

Returns:: Size of this VariableBuffer in bytes
Return type:: int

alloc() → str

Return a string representation of the C code required to allocated this memory buffer

Returns:: C Code to allocate this buffer
Return type:: str

dealloc() → str

Return a string representation of the C code to deallocate/free this memory buffer at runtime

Returns:: C Code to free this buffer
Return type:: str

has_live_aliases(ctxt: NetworkContext) → bool

Checks whether this VariableBuffer has any live ancestors, i.e. buffers that are still live and are aliased by this buffer. :param ctxt: Current NetworkContext :type ctxt: NetworkContext