MLBEDSW-7284: MLCE: Fix assert for faulty Split op

- An assert in Vela is triggered when the number of splits does
not evenly divide the input.shape[axis] value and the split offsets
are calculated wrongly.
- The fix is to add the same constraints as in the reference kernel
and only run the Split op on the NPU when the criterias are fulfilled.
- Modified test to reflect the new constraints
- Updated SUPPORTED_OPS.md

Change-Id: I4103ff4a3fdf9a813f5fcb7f51081b859e611100
Signed-off-by: Johan Alfven <johan.alfven@arm.com>

2 files changed, 62 insertions, 1 deletions

diff --git a/ethosu/vela/test/test_tflite_model_semantic.py b/ethosu/vela/test/test_tflite_model_semantic.py
index 2e0936d0..e26a327f 100644
--- a/ethosu/vela/test/test_tflite_model_semantic.py
+++ b/ethosu/vela/test/test_tflite_model_semantic.py
@@ -191,6 +191,40 @@ def test_constraint_beta_value_range():
     assert semantic_checker.is_operator_semantic_valid(op)
 
 
+def test_constraint_split_axis():
+    # Axis value must be in the range [-<ifm_dimensions>, <ifm_dimensions>)"
+    attrs = {"num_splits": 2}
+    axis = create_const_tensor("axis", [1], DataType.int8, [3])
+    ifm = Tensor([1, 1, 4], DataType.int8, "ifm")
+    ifm.quantization = testutil.default_quant_params()
+    ofm = Tensor([1, 1, 4], DataType.int8, "ofm")
+    ofm.quantization = testutil.default_quant_params()
+    op = testutil.create_op(Op.Split, [axis, ifm], ofm, attrs)
+    # Check invalid axis value
+    assert not semantic_checker.is_operator_semantic_valid(op)
+    # Check valid axis value
+    axis = create_const_tensor("axis", [1], DataType.int8, [-1])
+    op = testutil.create_op(Op.Split, [axis, ifm], ofm, attrs)
+    assert semantic_checker.is_operator_semantic_valid(op)
+
+
+def test_constraint_split_num_splits():
+    # Check that split number is valid"
+    attrs = {"num_splits": 2}
+    axis = create_const_tensor("axis", [1], DataType.int8, [-1])
+    ifm = Tensor([1, 1, 3], DataType.int8, "ifm")
+    ifm.quantization = testutil.default_quant_params()
+    ofm = Tensor([1, 1, 3], DataType.int8, "ofm")
+    ofm.quantization = testutil.default_quant_params()
+    op = testutil.create_op(Op.Split, [axis, ifm], ofm, attrs)
+    # Check invalid split number 2
+    assert not semantic_checker.is_operator_semantic_valid(op)
+    # Check valid split number 3
+    attrs = {"num_splits": 3}
+    op = testutil.create_op(Op.Split, [axis, ifm], ofm, attrs)
+    assert semantic_checker.is_operator_semantic_valid(op)
+
+
 def test_constraint_splitv_inferred():
     # SplitV requires a maximum of one inferred shape (-1)
     qp = testutil.default_quant_params()
diff --git a/ethosu/vela/tflite_model_semantic.py b/ethosu/vela/tflite_model_semantic.py
index dc3b8185..2851ab16 100644
--- a/ethosu/vela/tflite_model_semantic.py
+++ b/ethosu/vela/tflite_model_semantic.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright 2021-2022 Arm Limited and/or its affiliates <open-source-office@arm.com>
+# SPDX-FileCopyrightText: Copyright 2021-2023 Arm Limited and/or its affiliates <open-source-office@arm.com>
 #
 # SPDX-License-Identifier: Apache-2.0
 #
@@ -155,6 +155,10 @@ class TFLiteSemantic:
         self.specific_constraints[Op.Softmax].append(TFLiteSemantic.constraint_matching_in_out_types)
         self.specific_constraints[Op.Softmax].append(TFLiteSemantic.constraint_beta_value_range)
 
+        # Split specific checks:
+        self.specific_constraints[Op.Split].append(TFLiteSemantic.constraint_split_axis)
+        self.specific_constraints[Op.Split].append(TFLiteSemantic.constraint_split_num_splits)
+
         # SplitV specific checks:
         self.specific_constraints[Op.SplitV].append(TFLiteSemantic.constraint_splitv_inferred)
 
@@ -396,6 +400,29 @@ class TFLiteSemantic:
         return valid, f"Op has ifm_shape={ifm_shape} and ofm_shape={ofm_shape}"
 
     @staticmethod
+    def constraint_split_axis(op):
+        "Axis value must be in the range [-RANK(IFM) to +RANK(IFM))"
+        axis_tens = op.inputs[0]
+        input_tens = op.inputs[1]
+        dims = len(input_tens.shape)
+        axis = int(axis_tens.values)
+        axis += dims if axis < 0 else 0
+        valid = 0 <= axis < dims
+        return valid, f"Op has ifm_dimensions={dims} and axis value is: {axis}"
+
+    @staticmethod
+    def constraint_split_num_splits(op):
+        "Axis must be divisible by number of splits"
+        num_splits = op.attrs.get("num_splits")
+        axis_tens = op.inputs[0]
+        input_tens = op.inputs[1]
+        dims = len(input_tens.shape)
+        axis = int(axis_tens.values)
+        axis += dims if axis < 0 else 0
+        valid = input_tens.shape[axis] % num_splits == 0
+        return valid, f"Op has ifm shape={input_tens.shape} axis={axis} num_splits={num_splits}"
+
+    @staticmethod
     def constraint_splitv_inferred(op):
         "Only one size is allowed to be inferred"
         sizes = op.inputs[1].values