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# Sample source code from the Tutorial Introduction in the documentation.

from __future__ import annotations

import numpy

import pycuda.autoinit # ruff:ignore[unused-import]

import pycuda.driver as cuda

from pycuda.compiler import SourceModule

a = numpy.random.randn(4, 4)

a = a.astype(numpy.float32)

a_gpu = cuda.mem_alloc(a.size * a.dtype.itemsize)

cuda.memcpy_htod(a_gpu, a)

mod = SourceModule("""

__global__ void doublify(float *a)

{

int idx = threadIdx.x + threadIdx.y*4;

a[idx] *= 2;

}

""")

func = mod.get_function("doublify")

func(a_gpu, block=(4, 4, 1), grid=(1, 1), shared=0)

a_doubled = numpy.empty_like(a)

cuda.memcpy_dtoh(a_doubled, a_gpu)

print("original array:")

print(a)

print("doubled with kernel:")

print(a_doubled)

# alternate kernel invocation -------------------------------------------------

func(cuda.InOut(a), block=(4, 4, 1))

print("doubled with InOut:")

print(a)

# part 2 ----------------------------------------------------------------------

from pycuda import gpuarray

a_gpu = gpuarray.to_gpu(numpy.random.randn(4, 4).astype(numpy.float32))

a_doubled = (2*a_gpu).get()

print("original array:")

print(a_gpu)

print("doubled with gpuarray:")

print(a_doubled)