MLBEDSW-2528: MLCE-219: Custom operator pass through

 - Fixed custom operator pass through
 - Added error printing functions for operators and tensor
 - Minor cleanup of custom exception handling

Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: Idf295df1e4c544381dc480244d880c32fb285e38

1 files changed, 25 insertions, 6 deletions

diff --git a/ethosu/vela/tflite_reader.py b/ethosu/vela/tflite_reader.py
index 5667aff5..9d312e52 100644
--- a/ethosu/vela/tflite_reader.py
+++ b/ethosu/vela/tflite_reader.py
@@ -20,6 +20,7 @@ import os.path
 import numpy as np
 
 from .errors import InputFileError
+from .errors import TensorError
 from .nn_graph import Graph
 from .nn_graph import Subgraph
 from .operation import Operation
@@ -69,14 +70,16 @@ class TFLiteSubgraph:
             self.tensors.append(self.parse_tensor(subgraph.Tensors(idx)))
 
         for idx in range(subgraph.OperatorsLength()):
-            self.parse_operator(subgraph.Operators(idx))
+            self.parse_operator(idx, subgraph.Operators(idx))
 
-        self.outputs = [self.tensors[idx] for idx in subgraph.OutputsAsNumpy()]
-        self.inputs = [self.tensors[idx] for idx in subgraph.InputsAsNumpy()]
+        self.outputs = self.get_tensors_from_indices_remove_duplicates(subgraph.OutputsAsNumpy(), "output")
+        self.inputs = self.get_tensors_from_indices_remove_duplicates(subgraph.InputsAsNumpy(), "input")
 
         # Fix up tensors without operations. Generate either Placeholder or Constant ops
         for tens in self.inputs:
-            assert not tens.ops
+            if tens.ops != []:
+                TensorError(tens, "This subgraph input tensor has unexpected driving operators.")
+
             op = Operation("Placeholder", tens.name)
             op.outputs = [tens]
             tens.ops = [op]
@@ -87,6 +90,21 @@ class TFLiteSubgraph:
                 op.outputs = [tens]
                 tens.ops = [op]
 
+    def get_tensors_from_indices_remove_duplicates(self, indices, warning_str):
+        tensors = []
+        for idx in indices:
+            tensor = self.tensors[idx]
+            if tensor not in tensors:
+                tensors.append(tensor)
+            else:
+                print(
+                    "Warning: Subgraph {0} tensor ({1}) with idx = {2} already seen. Removing the duplicate.".format(
+                        warning_str, tensor, idx
+                    )
+                )
+
+        return tensors
+
     def parse_tensor(self, tens_data):
         np_shape = tens_data.ShapeAsNumpy()
         shape = list(np_shape) if type(np_shape) is np.ndarray else []
@@ -121,7 +139,7 @@ class TFLiteSubgraph:
                 tens.values = tens.quantization.dequantize(tens.quant_values)
         return tens
 
-    def parse_operator(self, op_data):
+    def parse_operator(self, op_index, op_data):
         op_type, opt_serializer = self.graph.operator_codes[op_data.OpcodeIndex()]
         inputs = [self.tensors[idx] for idx in op_data.InputsAsNumpy()]
         outputs = [self.tensors[idx] for idx in op_data.OutputsAsNumpy()]
@@ -129,6 +147,7 @@ class TFLiteSubgraph:
         if len(outputs):
             name = outputs[0].name
         op = Operation(op_type, name)
+        op.op_index = op_index
         op.inputs = inputs
         op.outputs = outputs
         for out in op.outputs:
@@ -143,7 +162,7 @@ class TFLiteSubgraph:
             inputs[1] = clone_and_reshape_tensor(inputs[1], (1, 0))
 
         if opt_serializer is not None:
-            op.attrs = opt_serializer.deserialize(op_data.BuiltinOptions(), op_data.CustomOptionsAsNumpy())
+            op.attrs = opt_serializer.deserialize(op_data)
 
             if "stride_w" in op.attrs:
                 op.attrs["strides"] = (1, op.attrs["stride_h"], op.attrs["stride_w"], 1)