MLBEDSW-2663: Handle optional tensors

Includes a number of changes:
  * Handle non-existing optional inputs
  * Handle disabled optional inputs (-1 indexed)
  * Added unit tests for parsing operators
  * Add bias tensor to the different Convolutions + FullyConnected if
    it's missing.

Signed-off-by: Jacob Bohlin <jacob.bohlin@arm.com>
Change-Id: Ib88d2b610314b1c886fc0aef4f9da87430ce6ae5

1 files changed, 43 insertions, 0 deletions

diff --git a/ethosu/vela/test/test_tflite_reader.py b/ethosu/vela/test/test_tflite_reader.py
index 1ba07423..d63c0007 100644
--- a/ethosu/vela/test/test_tflite_reader.py
+++ b/ethosu/vela/test/test_tflite_reader.py
@@ -15,6 +15,9 @@
 # limitations under the License.
 # Description:
 # Contains unit tests for tflite_reader
+from unittest.mock import MagicMock
+from unittest.mock import patch
+
 import pytest
 
 from ethosu.vela.tflite_reader import TFLiteSubgraph
@@ -35,3 +38,43 @@ class TestTFLiteSubgraph:
     def test_len1_array_to_scalar(self, test_input, expected):
         output = TFLiteSubgraph.len1_array_to_scalar(test_input)
         assert output == expected
+
+    parse_op_testdata = [
+        # op_type, opt_serializer, inputs, output, expected
+        ("FullyConnected", None, [0, 1, 2], 3, 3),  # FC
+        ("FullyConnected", None, [0, 1, -1], 3, 3),  # FC disabled Bias
+        ("FullyConnected", None, [0, 1], 3, 3),  # FC no Bias
+        ("Conv2D", None, [2, 1, 3], 0, 3),  # Conv2D
+        ("Conv2DBackprop", None, [0, 1, 2, 3], 4, 4),  # TransposeConv
+        ("Conv2DBackprop", None, [0, 1, 2], 4, 4),  # TransposeConv no Bias
+        pytest.param("Conv2D", None, [0, -1, 1], 3, 3, marks=pytest.mark.xfail),  # Conv2D no Weights
+    ]
+
+    @pytest.mark.parametrize("op_type, opt_serializer, inputs, output, expected", parse_op_testdata)
+    def test_parse_operator(self, op_type, opt_serializer, inputs, output, expected):
+        with patch.object(TFLiteSubgraph, "__init__", lambda self, graph, subraph: None):
+            # Mock a TFLiteSubGraph
+            sg = TFLiteSubgraph(None, None)
+            sg.graph = MagicMock()
+            sg.graph.operator_codes = [(op_type, opt_serializer)]
+
+            # Mock a couple of tensors
+            sg.tensors = [MagicMock() for _ in range(5)]
+            for i, tens in enumerate(sg.tensors):
+                tens.name = "tensor_{}".format(i)
+                tens.ops = []
+
+            # Mock op data
+            op_data = MagicMock()
+            op_data.OpcodeIndex.return_value = 0
+            op_data.InputsAsNumpy.return_value = inputs
+            op_data.OutputsAsNumpy.return_value = [output]
+
+            sg.parse_operator(0, op_data)
+
+            # Verify the created Operation
+            created_op = sg.tensors[output].ops[0]
+            assert created_op.type == op_type
+            assert len(created_op.inputs) == expected
+            assert created_op.outputs[0].name == "tensor_{}".format(output)
+            assert inputs[-1] != -1 or not created_op.inputs[-1]