commit 530992a3943eb21e12f6d0e638940d7df27a9f51
author Patrik Gustavsson <patrik.gustavsson@arm.com> Wed Sep 30 13:26:59 2020 +0200
committer Patrik Gustavsson <patrik.gustavsson@arm.com> Wed Sep 30 13:26:59 2020 +0200
tree f726ce430b30bbe0c0466f0f06f6586d809e56e4
parent 0f98b361288c71fca327969346db32de098c797b

MLBEDSW-3001 Fix Min Max OPs not properly checked

Min and max operations was not passed through
the checking of elementwize OPs in the supported
operator checking.

Changed so they are passed through this check as well.

Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I358a121de33882802415d97d9ed5dbee53233f77

ethosu/vela/supported_operators.py

diff --git a/ethosu/vela/supported_operators.py b/ethosu/vela/supported_operators.py
index eec1b90..73a4f28 100644
--- a/ethosu/vela/supported_operators.py
+++ b/ethosu/vela/supported_operators.py
@@ -121,9 +121,6 @@
         self.supported_operator_restrictions.update(
             {op: self.check_memory_only_restrictions for op in self.memory_only_ops}
         )
-        self.supported_operator_restrictions.update(
-            {op: self.check_quantization_restrictions_binary_elem_wise for op in self.binary_elem_wise_min_max_ops}
-        )
         self.supported_operator_restrictions.update({op: self.check_activation_ops for op in self.activation_ops})
 
     def is_operator_supported(self, op):
@@ -201,10 +198,12 @@
 
         # check inf values
         for tens in op.get_ifm_ifm2_weights_ofm():
-            if (tens is not None) and (
-                tens.quantization is not None) and (
-                tens.quantization.scale_f32 is not None) and (
-                np.isinf(tens.quantization.scale_f32).any()):
+            if (
+                (tens is not None)
+                and (tens.quantization is not None)
+                and (tens.quantization.scale_f32 is not None)
+                and (np.isinf(tens.quantization.scale_f32).any())
+            ):
                 print("Warning:", op.type, "has inf valued tensor(s), placing on CPU")
                 return False
 
@@ -398,6 +397,11 @@
         if ifm_tensor.shape != ofm_tensor.shape and ifm2_tensor.shape != ofm_tensor.shape:
             return False
 
+        if op.type in self.binary_elem_wise_min_max_ops and not self.check_quantization_restrictions_binary_elem_wise(
+            op
+        ):
+            return False
+
         return True
 
     def check_memory_only_restrictions(self, op):
@@ -470,7 +474,16 @@
                     return False
                 for i in range(ofm_dims):
                     if i != axis and ifm.shape[i] != ofm.shape[i]:
-                        print("Warning:", op.type, "invalid ifm:", ifm.name, ifm.shape, "mismatch in dimension", i, ", placing on CPU")
+                        print(
+                            "Warning:",
+                            op.type,
+                            "invalid ifm:",
+                            ifm.name,
+                            ifm.shape,
+                            "mismatch in dimension",
+                            i,
+                            ", placing on CPU",
+                        )
                         return False
 
         return True