Add the missing doc strings in elemwise ops

apache · Jan 28, 2020 · 68add63 · 68add63
1 parent 12efe01
commit 68add63
Showing 1 changed file with 10 additions and 0 deletions.
diff --git a/python/tvm/relay/frontend/tflite.py b/python/tvm/relay/frontend/tflite.py
@@ -714,13 +714,15 @@ def convert_div(self, op):
         return self._convert_elemwise(_op.divide, op)
 
     def convert_pow(self, op):
+        """Convert TFLite POW"""
         # Check if the input tensor is quantized, call QNN op
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
                 'TFlite quantized POW operator is not supported yet.')
         return self._convert_elemwise(_op.power, op)
 
     def convert_squared_difference(self, op):
+        """Convert TFLite SQUARED DIFFERENCE"""
         # Check if the input tensor is quantized, call QNN op
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
@@ -732,51 +734,59 @@ def convert_squared_difference(self, op):
         return out
 
     def convert_maximum(self, op):
+        """Convert TFLite MAXIMUM"""
         # Check if the input tensor is quantized, call QNN op
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
                 'TFlite quantized MAXIMUM operator is not supported yet.')
         return self._convert_elemwise(_op.maximum, op)
 
     def convert_minimum(self, op):
+        """Convert TFLite MINIMUM"""
         # Check if the input tensor is quantized, call QNN op
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
                 'TFlite quantized MINIMUM operator is not supported yet.')
         return self._convert_elemwise(_op.minimum, op)
 
     def convert_greater(self, op):
+        """Convert TFLite GREATER"""
         # Check if the input tensor is quantized, call QNN op
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
                 'TFlite quantized GREATER operator is not supported yet.')
         return self._convert_elemwise(_op.greater, op)
 
     def convert_greater_equal(self, op):
+        """Convert TFLite GREATER_EQUAL"""
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
                 'TFlite quantized GREATER_EQUAL operator is not supported yet.')
         return self._convert_elemwise(_op.greater_equal, op)
 
     def convert_less(self, op):
+        """Convert TFLite LESS"""
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
                 'TFlite quantized LESS operator is not supported yet.')
         return self._convert_elemwise(_op.less, op)
 
     def convert_less_equal(self, op):
+        """Convert TFLite LESS_EQUAL"""
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
                 'TFlite quantized LESS_EQUAL operator is not supported yet.')
         return self._convert_elemwise(_op.less_equal, op)
 
     def convert_equal(self, op):
+        """Convert TFLite EQUAL"""
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
                 'TFlite quantized EQUAL operator is not supported yet.')
         return self._convert_elemwise(_op.equal, op)
 
     def convert_not_equal(self, op):
+        """Convert TFLite NOT_EQUAL"""
         if self.is_quantized(op):
             raise tvm.error.OpNotImplemented(
                 'TFlite quantized NOT_EQUAL operator is not supported yet.')