def test_sizes(ctx_with_gs_limits, gl_size, gs_is_multiple):
"""
Test that virtual sizes are correct.
"""
ctx = ctx_with_gs_limits
grid_size, local_size = gl_size
ref = ReferenceIds(grid_size, local_size, gs_is_multiple)
get_sizes = ctx.compile_static("""
KERNEL void get_sizes(GLOBAL_MEM int *sizes)
{
if (virtual_global_flat_id() > 0) return;
for (int i = 0; i < 3; i++)
{
sizes[i] = virtual_local_size(i);
sizes[i + 3] = virtual_num_groups(i);
sizes[i + 6] = virtual_global_size(i);
}
sizes[9] = virtual_global_flat_size();
}
""", 'get_sizes', ref.global_size, local_size=ref.local_size)
sizes = ctx.allocate(10, numpy.int32)
get_sizes(sizes)
gls = list(ref.global_size) + [1] * (3 - len(ref.global_size))
ls = list(ref.local_size) + [1] * (3 - len(ref.local_size))
gs = [min_blocks(g, l) for g, l in zip(gls, ls)]
ref_sizes = numpy.array(ls + gs + gls + [product(gls)]).astype(numpy.int32)
assert diff_is_negligible(sizes.get(), ref_sizes)
def predict_local_ids(self, dim):
if dim > len(self.global_size) - 1:
return numpy.zeros(self.np_global_size, dtype=numpy.int32)
np_dim = len(self.global_size) - dim - 1
global_len = self.np_global_size[np_dim]
local_len = self.np_local_size[np_dim]
repetitions = min_blocks(global_len, local_len)
pattern = numpy.tile(numpy.arange(local_len), repetitions)[:global_len]
pattern_shape = [x if i == np_dim else 1 for i, x in enumerate(self.np_global_size)]
pattern = pattern.reshape(*pattern_shape)
tile_shape = [x if i != np_dim else 1 for i, x in enumerate(self.np_global_size)]
pattern = numpy.tile(pattern, tile_shape)
return pattern.astype(numpy.int32)
