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| author | Johan Alfven <johan.alfven@arm.com> | 2023-03-09 08:36:10 +0100 |
|---|---|---|
| committer | Fredrik Svedberg <fredrik.svedberg@arm.com> | 2023-03-16 16:12:36 +0000 |
| commit | 126558e26df26830c2d331ec0041dc9a4f1a0d38 (patch) | |
| tree | 597de0b202cfcd3950faf9c7f4e71e56ed0d867d /ethosu/vela/test | |
| parent | a5e1b6224d8436365e7f0bdb0afef060423fba57 (diff) | |
| download | ethos-u-vela-126558e26df26830c2d331ec0041dc9a4f1a0d38.tar.gz | |
MLBEDSW-7352: Refactoring move_constant_data
Refactoring move_constant_data in the scheduler. The use case currently
only work for LUT tensor, so simplifying the logic. In order to make it
work for other tensors one would also have to take into consideration
memory usage when building cascades and also the
use_fast_storage_for_feature_maps would be effected.
Change-Id: Ic8de53b65a2c17d34515002d7f184d0ab1830222
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
Diffstat (limited to 'ethosu/vela/test')
| -rw-r--r-- | ethosu/vela/test/test_lut.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/ethosu/vela/test/test_lut.py b/ethosu/vela/test/test_lut.py index 58e72bbf..e52b4896 100644 --- a/ethosu/vela/test/test_lut.py +++ b/ethosu/vela/test/test_lut.py @@ -36,7 +36,7 @@ def set_256_lut(op, key, arch): random.seed(key) values = random.choices(range(256), k=256) lut_tensor = create_const_tensor(op.name + "_lut", [1, 1, 1, 256], DataType.uint8, values, TensorPurpose.LUT) - scratch_lut_tensor = lut_tensor.clone_into_fast_storage(arch) + scratch_lut_tensor = lut_tensor.clone_into_shram(arch) op.set_activation_lut(scratch_lut_tensor) @@ -44,7 +44,7 @@ def set_1K_lut(op, key, arch): random.seed(key) values = random.choices(range(256), k=256) lut_tensor = create_const_tensor(op.name + "_lut", [1, 1, 1, 256], DataType.int32, values, TensorPurpose.LUT) - scratch_lut_tensor = lut_tensor.clone_into_fast_storage(arch) + scratch_lut_tensor = lut_tensor.clone_into_shram(arch) op.set_activation_lut(scratch_lut_tensor) @@ -52,7 +52,7 @@ def set_2K_lut(op, key, arch): random.seed(key) values = random.choices(range(512), k=512) lut_tensor = create_const_tensor(op.name + "_lut", [1, 1, 1, 512], DataType.int32, values, TensorPurpose.LUT) - scratch_lut_tensor = lut_tensor.clone_into_fast_storage(arch) + scratch_lut_tensor = lut_tensor.clone_into_shram(arch) op.set_activation_lut(scratch_lut_tensor) |