ANSHUMAN87 commented on a change in pull request #8375:
URL: https://github.com/apache/tvm/pull/8375#discussion_r661310820



##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -251,7 +251,30 @@ def get_op_code_str(self, op):
             raise ImportError("The tflite package must be installed")
 
         op_code_list_idx = op.OpcodeIndex()
-        op_code_id = self.model.OperatorCodes(op_code_list_idx).BuiltinCode()
+
+        op_c = self.model.OperatorCodes(op_code_list_idx)
+        # In TFlite 2.4.x there was a change where the type of the field that 
contained
+        # the builtin code changed from int8 to int32 in the flat buffer 
representation.
+        # However to retain support for old flat buffers that were created, 
they retained
+        # the original 8 bit encoding for the operator but in a new field 
accessed by the
+        # DeprecatedBuiltinCode method.
+        # This means that the API function BuiltinCode() is used on an operator
+        # which was originally encoded as an 8 bit quantity it would look for 
the
+        # code in the new int32 field in the schema and this creates the need
+        # for the check for the magic number of 127 which is indicated by
+        # BuiltinOperator.PLACEHOLDER_FOR_GREATER_OP_CODES
+        # Remember however that this value came into existence only after 
Tensorflow
+        # lite 2.4.x and hence encase it in a try -except block.
+        # Phew !
+        try:
+            if op_c.BuiltinCode() < 
BuiltinOperator.PLACEHOLDER_FOR_GREATER_OP_CODES:

Review comment:
       Current upgrade to Tensorflow 2.4.2, also does not install schema_util 
as part of pip package.
   SO we can go ahead with current change. Later on when Tensorflow has the bug 
fixed, we can take the suggested APIs change.




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