warp.fixedarray#

class warp.fixedarray(*args, **kwargs)[source]#

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:

__init__(dtype=Any, shape=None)[source]#

Parameters:

Methods

`__init__`([dtype, shape])
`assign`(src)	Wraps `src` in an `warp.array` if it is not already one and copies the contents to `self`.
`contiguous`()	Returns 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`()	Returns 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`()	Returns a flattened list of items in the array as a Python list.
`mark_init`()	Resets this array's read flag
`mark_read`()	Marks 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`()	Converts 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)	Returns a reshaped array.
`to`(device[, requires_grad])	Returns a Warp array with this array's data moved to the specified device, no-op if already on device.
`transpose`([axes])	Returns an zero-copy view of the array with axes transposed.
`view`(dtype)	Returns a zero-copy view of this array's memory with a different data type.
`zero_`()	Zeroes-out the array entries.

Attributes