commit 3b1578e44b4c6a8c8c9a8e0891d3866a89bd66af
author Tim Hall <tim.hall@arm.com> Fri Jan 13 17:57:25 2023 +0000
committer tim.hall <tim.hall@arm.com> Fri Jan 20 14:07:21 2023 +0000
tree 491c337bc854d435b80f0a535496084ea9ebc9ac
parent f34904717f643499f3ea6210322bbe1b635db088

MLBEDSW-7151: MLCE: Difference in model output between x86 & aarch64

 - The issue is due to undefined behaviour when casting a NumPy float
to a NumPy unsigned integer which occurs in create_const_tensor()
 - The fix is to make sure that the values are first cast to a Python
float
 - In addition, the values datatype argument has been removed from
create_const_tensor() to stop the tensor and values datatypes getting
out of sync

Change-Id: I134b9be8c941b361929a5ae7db8cb35f2e9728f2
Signed-off-by: Tim Hall <tim.hall@arm.com>

ethosu/vela/test/test_lut.py

diff --git a/ethosu/vela/test/test_lut.py b/ethosu/vela/test/test_lut.py
index 9073270..712be7a 100644
--- a/ethosu/vela/test/test_lut.py
+++ b/ethosu/vela/test/test_lut.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright 2020-2021 Arm Limited and/or its affiliates <open-source-office@arm.com>
+# SPDX-FileCopyrightText: Copyright 2020-2021, 2023 Arm Limited and/or its affiliates <open-source-office@arm.com>
 #
 # SPDX-License-Identifier: Apache-2.0
 #
@@ -18,8 +18,6 @@
 # Unit tests for LUT support
 import random
 
-import numpy as np
-
 from ethosu.vela import lut
 from ethosu.vela import mark_tensors
 from ethosu.vela import pass_packing
@@ -37,9 +35,7 @@
 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.int8, values, np.uint8, TensorPurpose.LUT
-    )
+    lut_tensor = create_const_tensor(op.name + "_lut", [1, 1, 1, 256], DataType.int8, values, TensorPurpose.LUT)
     scratch_lut_tensor = lut_tensor.clone_into_fast_storage(arch)
     op.set_activation_lut(scratch_lut_tensor)
 
@@ -47,9 +43,7 @@
 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, np.uint32, TensorPurpose.LUT
-    )
+    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)
     op.set_activation_lut(scratch_lut_tensor)
 
@@ -57,9 +51,7 @@
 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, np.uint32, TensorPurpose.LUT
-    )
+    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)
     op.set_activation_lut(scratch_lut_tensor)