commit 4a434cba156cdfb2613b7ebe4d4a4ec9f85ba616
author Fredrik Svedberg <fredrik.svedberg@arm.com> Tue Sep 27 14:13:01 2022 +0200
committer Fredrik Svedberg <fredrik.svedberg@arm.com> Tue Oct 04 09:20:33 2022 +0000
tree 47ebce38221b92b8eeb34e8b5f558223dcd4d3e3
parent dda4caed56d2cd3a9d5927bf405859c1777ac909

MLBEDSW-6969 Remove RescaleAdd and RescaleMul operators

Removed RescaleAdd and RescaleMul operators in favour of
Operation.explicit_scale and removed Operation.rescale.

Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: Idccd8851731d4bb8d4e84970e0fd6b409d7d4e45

ethosu/vela/tflite_graph_optimiser.py

diff --git a/ethosu/vela/tflite_graph_optimiser.py b/ethosu/vela/tflite_graph_optimiser.py
index 5d6d707..f3ca1b6 100644
--- a/ethosu/vela/tflite_graph_optimiser.py
+++ b/ethosu/vela/tflite_graph_optimiser.py
@@ -871,7 +871,7 @@
             # Add explicit rescaling
             rescale = ifm.quantization.scale_f32 / ofm.quantization.scale_f32
             multiplier, shift = scaling.quantise_scale(rescale)
-            relu_fused_op.rescale = ExplicitScaling(False, [shift], [multiplier])
+            relu_fused_op.explicit_scaling = ExplicitScaling(False, [shift], [multiplier])
             # Tidy up and assign the ifm and ofm to the new op
             ifm.consumer_list.remove(op)
 
@@ -991,8 +991,8 @@
         DebugDatabase.add_optimised(op, relu_op)
 
         # Add scaled and alpha multiplied values (without scaling)
-        add_op = Operation(Op.RescaleAdd, op.name + "_add")
-        add_op.rescale = (1, 0)  # No scale or shift
+        add_op = Operation(Op.Add, op.name + "_add")
+        add_op.explicit_scaling = ExplicitScaling(False, shift=[0], multiplier=[1])  # No scaling
         add_op.add_input_tensor(fm_alpha)
         add_op.add_input_tensor(fm_scaled)
         add_op.set_output_tensor(ofm)
@@ -1180,8 +1180,8 @@
             mul_ifm.dtype = DataType.int32
         min_op.set_output_tensor(mul_ifm)
         min_op.set_ifm_ofm_shapes()
-        new_op = Op.RescaleAdd
-        op.rescale = (1, 0)  # No scale or shift
+        new_op = Op.Add
+        op.explicit_scaling = ExplicitScaling(False, shift=[0], multiplier=[1])  # No scaling
         DebugDatabase.add_optimised(op, min_op)
 
     # Add multiplication with alpha
@@ -1196,8 +1196,7 @@
     if is_converted_prelu:
         # The LeakyRelu was the result from convert_prelu and the scaling is provided
         scalar, alpha_scale, alpha_shift = op.attrs["alpha_scaling"]
-        mul_alpha.type = Op.RescaleMul
-        mul_alpha.rescale = [alpha_scale, alpha_shift]
+        mul_alpha.explicit_scaling = ExplicitScaling(False, [alpha_shift], [alpha_scale])
     elif alpha == 0 or np.isinf(1 / alpha):
         # Handling of alpha near or at zero
         quantization.scale_f32 = np.float32(1)