huajsj commented on code in PR #11183:
URL: https://github.com/apache/tvm/pull/11183#discussion_r867319861


##########
python/tvm/relay/frontend/tflite.py:
##########
@@ -2710,6 +2743,145 @@ def convert_unpack(self, op):
 
         return squeezed
 
+    def convert_unidirectional_sequence_lstm(self, op):
+        """Long Short Term Memory for TFLite implementation."""
+        if self.is_quantized(op):
+            raise tvm.error.OpNotImplemented(
+                "TFlite quantized UNIDIRECTIONALSEQUENCELSTM operator is not 
supported yet."
+            )
+
+        input_tensors = self.get_input_tensors(op)
+        assert len(input_tensors) >= 20, "input tensors length should be >= 20"

Review Comment:
   can this LSTM function also support any small input tensor case? for example 
input tensor size = 1?



##########
python/tvm/relay/frontend/tflite.py:
##########
@@ -2710,6 +2743,145 @@ def convert_unpack(self, op):
 
         return squeezed
 
+    def convert_unidirectional_sequence_lstm(self, op):
+        """Long Short Term Memory for TFLite implementation."""
+        if self.is_quantized(op):
+            raise tvm.error.OpNotImplemented(
+                "TFlite quantized UNIDIRECTIONALSEQUENCELSTM operator is not 
supported yet."
+            )
+
+        input_tensors = self.get_input_tensors(op)
+        assert len(input_tensors) >= 20, "input tensors length should be >= 20"
+
+        # Extract input tensor from saved model
+        input_tensor = input_tensors[0]
+
+        # Extract tensors from input tensors from saved model
+        # Input weights
+        input_input_weights = input_tensors[1]
+        input_forget_weights = input_tensors[2]
+        input_cell_weights = input_tensors[3]
+        input_output_weights = input_tensors[4]
+        # Recurrent weights
+        recurrent_input_weights = input_tensors[5]
+        recurrent_forget_weights = input_tensors[6]
+        recurrent_cell_weights = input_tensors[7]
+        recurrent_output_weights = input_tensors[8]
+        # Bias weights
+        input_gate_bias = input_tensors[12]
+        forget_gate_bias = input_tensors[13]
+        cell_gate_bias = input_tensors[14]
+        output_gate_bias = input_tensors[15]
+        # State input
+        output_state_in = input_tensors[18]
+        cell_state_in = input_tensors[19]

Review Comment:
   if input_tensors size > 20, what will happened?



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