def test_ifmap_size(self):
''' Get ifmap size. '''
clayer = ConvLayer(3, 64, [28, 14], 3, strd=2)
self.assertEqual(clayer.ifmap_size(2),
((28 - 1) * 2 + 3) * ((14 - 1) * 2 + 3) * 2,
'ConvLayer: ifmap_size')
self.assertEqual(clayer.total_ifmap_size(2),
((28 - 1) * 2 + 3) * ((14 - 1) * 2 + 3) * 3 * 2,
'ConvLayer: total_ifmap_size')
llayer = LocalRegionLayer(64, 28, 1, 3, strd=2)
self.assertEqual(llayer.ifmap_size(2), ((28 - 1) * 2 + 3)**2 * 2,
'LocalRegionLayer: ifmap_size')
self.assertEqual(llayer.total_ifmap_size(2),
((28 - 1) * 2 + 3)**2 * 64 * 2,
'LocalRegionLayer: total_ifmap_size')
def test_nested_loop_desc_fold_w(self):
''' Generated nested loop description when folding width. '''
layer = self.convlayers['conv1']
batch_size = 4
occ = 1
ms = MapStrategyEyeriss(layer, batch_size, occ, self.dim_array)
self.assertTupleEqual(ms.repl, (1, 1))
self.assertEqual(ms.fold.h, 1)
self.assertGreater(ms.fold.w, 1)
# Only 1 possible nld.
nld_list = list(ms.gen_nested_loop_desc())
self.assertEqual(len(nld_list), 1)
nld = nld_list[0]
# Fold to batch size.
fold_w = ms.fold.w
folded_layer = ConvLayer(layer.nifm,
layer.nofm,
(util.idivc(layer.hofm, fold_w), layer.wofm),
(layer.hfil, layer.wfil),
strd=(layer.htrd, layer.wtrd))
folded_batch_size = batch_size * fold_w
locc = layer.total_ops(batch_size) \
/ folded_layer.total_ops(folded_batch_size)
self.assertLessEqual(locc, 1)
self.assertEqual(nld.loopcnt[le.IFM], folded_layer.nifm)
self.assertEqual(nld.loopcnt[le.OFM], folded_layer.nofm)
self.assertEqual(nld.loopcnt[le.BAT], folded_batch_size)
self.assertEqual(nld.usize_gbuf[de.FIL], folded_layer.filter_size())
self.assertEqual(nld.usize_gbuf[de.IFM], folded_layer.ifmap_size())
self.assertEqual(nld.usize_gbuf[de.OFM], folded_layer.ofmap_size())
# DRAM and GBUF accesses are equal.
self.assertTupleEqual(nld.unit_access[me.DRAM],
nld.unit_access[me.GBUF])
