vela: Improve the scaling is equal check

 - Fixed and documented both tensor and quant params scaling checks
 - Added quant params validity check and tensor quantisation check
 - Added valid tensor checks to some graph optimisation functions

Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I8d6e8f03a603d28886dde511672c8399c85b794c

1 files changed, 14 insertions, 7 deletions

diff --git a/ethosu/vela/supported_operators.py b/ethosu/vela/supported_operators.py
index f4dd5796..dfb7bc7d 100644
--- a/ethosu/vela/supported_operators.py
+++ b/ethosu/vela/supported_operators.py
@@ -24,6 +24,8 @@ from .data_type import DataType
 from .numeric_util import is_integer
 from .operation import get_slice_offsets
 from .operation import Op
+from .tensor import check_quantized_tens_scaling_equal
+from .tensor import check_tens_quantized
 
 
 # Custom decorator function to allow formatting docstrings containing "{}"
@@ -730,17 +732,22 @@ class SupportedOperators:
 
     @classmethod
     def check_quantization_restrictions_binary_elem_wise(cls, op):
-        # makes sure IFM1, IFM2 and OFM quantization are equal for binary ops
+        # checks that IFM1, IFM2 and OFM quantization are equal for binary ops
+
         assert len(op.inputs) >= 2 and len(op.outputs) == 1
 
         if (
-            op.inputs[0].quantization is None
-            or not op.inputs[0].is_scaling_equal(op.inputs[1])
-            or not op.inputs[0].is_scaling_equal(op.outputs[0])
+            not check_tens_quantized(op.inputs[0])
+            or not check_tens_quantized(op.inputs[1])
+            or not check_tens_quantized(op.outputs[0])
         ):
-            print(
-                "Warning: Input/output tensors with different quantization is unsupported for the", op.type, "operator"
-            )
+            warn_cpu(op, "has non-quantised input and/or output tensors")
+            return False
+
+        if not check_quantized_tens_scaling_equal(op.inputs[0], op.inputs[1]) or not check_quantized_tens_scaling_equal(
+            op.inputs[0], op.outputs[0]
+        ):
+            warn_cpu(op, "has input/output tensors with different quantisation which is illegal")
             return False
 
         return True