MLBEDSW-7020: TRANSPOSE_CONV stride documentation is confusing

 - The op contained supported operator checks for both the stride being
in the range 1 to 3, and being equal to 2. Whilst both are correct, only
the later is needed
 - Removed the stride in the range 1 to 3 check for TRANSPOSE_CONV
 - Regenerated the documentation

Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I9789cdbd3ed65ce310f1529036abbac62296d2ca
diff --git a/ethosu/vela/tflite_supported_operators.py b/ethosu/vela/tflite_supported_operators.py
index 23bbac2..b8fe4b6 100644
--- a/ethosu/vela/tflite_supported_operators.py
+++ b/ethosu/vela/tflite_supported_operators.py
@@ -235,14 +235,17 @@
             self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_weights_limit)
             self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_bias_type)
             self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_bias_40bit)
-        # Depthwise Conv specific checks:
-        for op_type in TFLiteSupportedOperators.depthwise_convolution_ops:
-            self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_depth_multiplier)
+        # Remove stride contraint from Transpose Conv because it has a specific one (see below)
+        for op_type in TFLiteSupportedOperators.transpose_convolution_ops:
+            self.specific_constraints[op_type].remove(TFLiteSupportedOperators.constraint_stride_range)
         # Transpose Conv specific checks:
         for op_type in TFLiteSupportedOperators.transpose_convolution_ops:
             self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_tconv_stride)
             self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_tconv_same)
             self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_tconv_valid)
+        # Depthwise Conv specific checks:
+        for op_type in TFLiteSupportedOperators.depthwise_convolution_ops:
+            self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_depth_multiplier)
 
         # Pooling checks:
         for op_type in TFLiteSupportedOperators.pooling_ops: