warp.fixedarray

class warp.fixedarray(*args, **kwargs)

A fixed-size, stack allocated, array containing values of the same type.

Only used during codegen, and for type hints, but otherwise not intended to be used at the Python scope.

Parameters:

• dtype (Any)

• shape (int | tuple[int, ...] | list[int] | None)

__init__(dtype=Any, shape=None)

Parameters:

• dtype (Any)

• shape (int | tuple[int, ...] | list[int] | None)

Methods

__init__([dtype, shape])
assign(src)	Wrap src in an warp.array if it is not already one and copy the contents to self.
contiguous()	Return a contiguous array with this array's data.
cptr()	Return a ctypes cast of the array address.
fill_(value)	Set all array entries to value
flatten()	Return a zero-copy view of the array collapsed to 1-D.
ipc_handle()	Return an IPC handle of the array as a 64-byte bytes object
list()	Return a flattened list of items in the array as a Python list.
mark_init()	Reset this array's read flag.
mark_read()	Mark this array as having been read from in a kernel or recorded function on the tape.
mark_write(**kwargs)	Detect if we are writing to an array that has already been read from.
numpy()	Convert the array to a numpy.ndarray (aliasing memory through the array interface protocol) If the array is on the GPU, a synchronous device-to-host copy (on the CUDA default stream) will be automatically performed to ensure that any outstanding work is completed.
reshape(shape)	Return a reshaped array.
to(device[, requires_grad])	Return a Warp array with this array's data moved to the specified device, no-op if already on device.
transpose([axes])	Return a zero-copy view of the array with axes transposed.
view(dtype)	Return a zero-copy view of this array's memory with a different data type.
zero_()	Zero out the array entries.

Attributes

grad
requires_grad
vars

property vars