From c21436bcea8617a0e0bfd27eab2364c597020a5e Mon Sep 17 00:00:00 2001
From: Stephan Seitz <stephan.seitz@fau.de>
Date: Wed, 14 Aug 2019 07:57:05 +0200
Subject: [PATCH] Fixup: also accept non-array parameters for OpenCL jit
arguments
---
pystencils/opencl/opencljit.py | 2 +-
pystencils_tests/test_opencl.py | 53 +++++++++++++++++++++++++++++++++
2 files changed, 54 insertions(+), 1 deletion(-)
diff --git a/pystencils/opencl/opencljit.py b/pystencils/opencl/opencljit.py
index dd06606..a681749 100644
--- a/pystencils/opencl/opencljit.py
+++ b/pystencils/opencl/opencljit.py
@@ -64,7 +64,7 @@ def make_python_function(kernel_function_node, opencl_queue, opencl_ctx, argumen
block_and_thread_numbers['grid']))
args = _build_numpy_argument_list(parameters, full_arguments)
- args = [a.data for a in args if hasattr(a, 'data')]
+ args = [a.data if hasattr(a, 'data') else a for a in args]
cache[key] = (args, block_and_thread_numbers)
cache_values.append(kwargs) # keep objects alive such that ids remain unique
func(opencl_queue, block_and_thread_numbers['grid'], block_and_thread_numbers['block'], *args)
diff --git a/pystencils_tests/test_opencl.py b/pystencils_tests/test_opencl.py
index 5aa6185..24ef56f 100644
--- a/pystencils_tests/test_opencl.py
+++ b/pystencils_tests/test_opencl.py
@@ -142,5 +142,58 @@ def test_opencl_jit():
assert np.allclose(result_cuda, result_opencl)
+@pytest.mark.skipif(not HAS_OPENCL, reason="Test requires pyopencl")
+def test_opencl_jit_with_parameter():
+ z, y, x = pystencils.fields("z, y, x: [2d]")
+
+ a = sp.Symbol('a')
+ assignments = pystencils.AssignmentCollection({
+ z[0, 0]: x[0, 0] * sp.log(x[0, 0] * y[0, 0]) + a
+ })
+
+ print(assignments)
+
+ ast = pystencils.create_kernel(assignments, target='gpu')
+
+ print(ast)
+
+ code = pystencils.show_code(ast, custom_backend=CudaBackend())
+ print(code)
+ opencl_code = pystencils.show_code(ast, custom_backend=OpenClBackend())
+ print(opencl_code)
+
+ cuda_kernel = ast.compile()
+ assert cuda_kernel is not None
+
+ import pycuda.gpuarray as gpuarray
+
+ x_cpu = np.random.rand(20, 30)
+ y_cpu = np.random.rand(20, 30)
+ z_cpu = np.random.rand(20, 30)
+
+ x = gpuarray.to_gpu(x_cpu)
+ y = gpuarray.to_gpu(y_cpu)
+ z = gpuarray.to_gpu(z_cpu)
+ cuda_kernel(x=x, y=y, z=z, a=5.)
+
+ result_cuda = z.get()
+
+ import pyopencl.array as array
+ ctx = cl.create_some_context(0)
+ queue = cl.CommandQueue(ctx)
+
+ x = array.to_device(queue, x_cpu)
+ y = array.to_device(queue, y_cpu)
+ z = array.to_device(queue, z_cpu)
+
+ opencl_kernel = make_python_function(ast, queue, ctx)
+ assert opencl_kernel is not None
+ opencl_kernel(x=x, y=y, z=z, a=5.)
+
+ result_opencl = z.get(queue)
+
+ assert np.allclose(result_cuda, result_opencl)
+
+
if __name__ == '__main__':
test_opencl_jit()
--
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