MLBEDSW-8290: MLCE: Add TRANSPOSE support3.10.0.rc1

 - Added graph optimiser function to convert TRANSPOSE op
into an AvgPool op with swapped stride for height and width
 - Added TRANSPOSE supported op check
 - Added unit tests for TRANSPOSE supported op check
 - Updated SUPPORTED_OPS.md
 - Fixed problem in pass packing when optimizing the pass list.
Old problem, but now seen when moving TRANSPOSE from cpu.

Change-Id: I0a0ef420b0fb8241090c2e2434622881105cde15
Signed-off-by: Johan Alfven <johan.alfven@arm.com>

1 files changed, 46 insertions, 1 deletions

diff --git a/ethosu/vela/tflite_supported_operators.py b/ethosu/vela/tflite_supported_operators.py
index 14c22133..45003913 100644
--- a/ethosu/vela/tflite_supported_operators.py
+++ b/ethosu/vela/tflite_supported_operators.py
@@ -109,7 +109,9 @@ class TFLiteSupportedOperators:
     elem_wise_main_ops = binary_elem_wise_main_ops | unary_elem_wise_main_ops | set((Op.SquaredDifference,))
     pad_ops = set((Op.Pad,))
     supported_int32_tensor_ops = (
-        set((Op.ReduceSum, Op.CLZ, Op.Shape, Op.ArgMax)) | binary_elem_wise_add_mul_sub | binary_elem_wise_shift_ops
+        set((Op.ReduceSum, Op.CLZ, Op.Shape, Op.ArgMax, Op.Transpose))
+        | binary_elem_wise_add_mul_sub
+        | binary_elem_wise_shift_ops
     )
 
     relu_ops = set(
@@ -163,6 +165,7 @@ class TFLiteSupportedOperators:
                 Op.QuantizedReshape,
                 Op.Squeeze,
                 Op.ExpandDims,
+                Op.Transpose,
             )
         )
         | concat_ops
@@ -340,6 +343,9 @@ class TFLiteSupportedOperators:
         # Slice specific checks:
         self.specific_constraints[Op.Slice].append(TFLiteSupportedOperators.constraint_slice_inputs_const)
 
+        # Transpose specific checks:
+        self.specific_constraints[Op.Transpose].append(TFLiteSupportedOperators.constraint_transpose)
+
     def is_operator_supported(self, op):
         ext_type = optype_to_builtintype(op.type)
         if op.type not in TFLiteSupportedOperators.supported_operators:
@@ -1027,3 +1033,42 @@ class TFLiteSupportedOperators:
             extra.append(f"Size tensor '{sizes.name}'")
         extra = ", ".join(extra)
         return valid, f"Op has non-constant tensors: {extra}"
+
+    @staticmethod
+    def constraint_transpose(op):
+        """The following shape/permutations are supported for transpose:
+        When ifm rank is 2: WxC -> CxW
+        When ifm rank is 3: HxWxC -> WxHxC, 1xWxC -> 1xCxW, Hx1xC -> Cx1xH
+        When ifm rank is 4: 1xHxWxC -> 1xWxHxC, 1x1xWxC -> 1x1xCxW, 1xHx1xC -> 1xCx1xW"""
+
+        ifm_shape = op.inputs[0].shape
+        perm = op.inputs[1]
+
+        # WxC -> CxW
+        valid = len(ifm_shape) == 2
+
+        # HxWxC -> WxHxC
+        if not valid and perm.shape == [3]:
+            valid = perm.values[0] == 1 and perm.values[1] == 0
+
+        # 1xWxC -> 1xCxW
+        if not valid and perm.shape == [3] and ifm_shape[0] == 1:
+            valid = perm.values[1] == 2 and perm.values[2] == 1
+
+        # Hx1xC -> Cx1xH
+        if not valid and perm.shape == [3] and ifm_shape[1] == 1:
+            valid = perm.values[0] == 2 and perm.values[2] == 0
+
+        # 1xHxWxC -> 1xWxHxC
+        if not valid and perm.shape == [4]:
+            valid = perm.values[0] == 0 and perm.values[1] == 2 and perm.values[2] == 1
+
+        # 1x1xWxC -> 1x1xCxW
+        if not valid and perm.shape == [4] and ifm_shape[1] == 1:
+            valid = perm.values[0] == 0 and perm.values[2] == 3 and perm.values[3] == 2
+
+        # 1xHx1xC -> 1xCx1xH
+        if not valid and perm.shape == [4] and ifm_shape[2] == 1:
+            valid = perm.values[0] == 0 and perm.values[1] == 3 and perm.values[3] == 1
+
+        return valid, f"Op has ifm_shape: {ifm_shape} and permutation is: {perm.values}"