Update Perfetto and fix tests (#378)

Fix for "SWDEV-479652" - Perfetto-based tests are failing.

Updated version of perfetto submodule to v46.0.
Modified Omnitrace code that uses Perfetto, so it can compile.
Modified the testing code, so it can run the version of trace_processor_shell provided (v46.0).

---------

Signed-off-by: Aleksandar Janicijevic <Aleksandar.Janicijevic@amd.com>
Co-authored-by: David Galiffi <David.Galiffi@amd.com>

examples/python/source-numpy.py

@@ -0,0 +1,83 @@
+#!@PYTHON_EXECUTABLE@
+
+import os
+import sys
+import time
+import omnitrace
+from omnitrace.user import region as omni_user_region
+
+_prefix = ""
+
+
+def fib(n):
+    return n if n < 2 else (fib(n - 1) + fib(n - 2))
+
+
+try:
+    import numpy as np
+
+    def inefficient(n):
+        print(f"[{_prefix}] ... running inefficient({n}) (1)")
+        a = 0
+        for i in range(n):
+            a += i
+            for j in range(n):
+                a += j
+        _len = a * n * n
+        _ret = np.random.rand(_len).sum()
+        print(f"[{_prefix}] ... sum of {_len} random elements: {_ret}")
+        return _ret
+
+except ImportError as e:
+    print(f"ImportError: {e}")
+    import random
+
+    def _sum(arr):
+        print(f"----  in _sum")
+        return sum(arr)
+
+    def inefficient(n):
+        print(f"[{_prefix}] ... running inefficient({n})")
+        a = 0
+        for i in range(n):
+            a += i
+            for j in range(n):
+                a += j
+        _len = a * n * n
+        _arr = [random.random() for _ in range(_len)]
+        _ret = _sum(_arr)
+        print(f"[{_prefix}] ... sum of {_len} random elements: {_ret}")
+        return _ret
+
+
+@omnitrace.profile()
+def run(n):
+    _ret = 0
+    _ret += fib(n)
+    _ret += inefficient(n)
+    return _ret
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-n", "--num-iterations", help="Number", type=int, default=3)
+    parser.add_argument("-v", "--value", help="Starting value", type=int, default=20)
+    parser.add_argument(
+        "-s",
+        "--stop-profile",
+        help="Stop tracing after given iterations",
+        type=int,
+        default=0,
+    )
+    args = parser.parse_args()
+
+    _prefix = os.path.basename(__file__)
+    print(f"[{_prefix}] Executing {args.num_iterations} iterations...\n")
+    for i in range(args.num_iterations):
+        with omni_user_region(f"main_loop"):
+            if args.stop_profile > 0 and i == args.stop_profile:
+                omnitrace.user.stop_trace()
+            ans = run(args.value)
+            print(f"[{_prefix}] [{i}] result of run({args.value}) = {ans}\n")

examples/python/source.py

@@ -5,6 +5,7 @@ import sys
 import time
 import omnitrace
 from omnitrace.user import region as omni_user_region
+import random
 
 _prefix = ""
 
@@ -13,39 +14,23 @@ def fib(n):
     return n if n < 2 else (fib(n - 1) + fib(n - 2))
 
 
-try:
-    import numpy as np
+def _sum(arr):
+    print(f"----  in _sum")
+    return sum(arr)
 
-    def inefficient(n):
-        print(f"[{_prefix}] ... running inefficient({n})")
-        a = 0
-        for i in range(n):
-            a += i
-            for j in range(n):
-                a += j
-        _len = a * n * n
-        _ret = np.random.rand(_len).sum()
-        print(f"[{_prefix}] ... sum of {_len} random elements: {_ret}")
-        return _ret
 
-except ImportError:
-    import random
-
-    def _sum(arr):
-        return sum(arr)
-
-    def inefficient(n):
-        print(f"[{_prefix}] ... running inefficient({n})")
-        a = 0
-        for i in range(n):
-            a += i
-            for j in range(n):
-                a += j
-        _len = a * n * n
-        _arr = [random.random() for _ in range(_len)]
-        _ret = _sum(_arr)
-        print(f"[{_prefix}] ... sum of {_len} random elements: {_ret}")
-        return _ret
+def inefficient(n):
+    print(f"[{_prefix}] ... running inefficient({n})")
+    a = 0
+    for i in range(n):
+        a += i
+        for j in range(n):
+            a += j
+    _len = a * n * n
+    _arr = [random.random() for _ in range(_len)]
+    _ret = _sum(_arr)
+    print(f"[{_prefix}] ... sum of {_len} random elements: {_ret}")
+    return _ret
 
 
 @omnitrace.profile()