Helper functions for quantize and dequantize.

python/tvm/relay/frontend/tflite.py

@@ -267,6 +267,23 @@ def is_quantized(self, op):
         first_tensor = input_tensors[0]
         return first_tensor.qnn_params is not None
 
+    def quantize(self, expr, tensor_to_quantize):
+        """ Helper function to quantize a tensor with Relay """
+        tensor_type = tensor_to_quantize.tensor.Type()
+        tensor_type_str = self.get_tensor_type_str(tensor_type)
+        quantized = _qnn.op.quantize(data=expr,
+                                     output_scale=tensor_to_quantize.qnn_params['scale'],
+                                     output_zero_point=tensor_to_quantize.qnn_params['zero_point'],
+                                     out_dtype=tensor_type_str)
+        return quantized
+
+    def dequantize(self, expr, tensor):
+        """ Helper function to dequantize a tensor with Relay """
+        dequantized = _qnn.op.dequantize(data=expr,
+                                         input_scale=tensor.qnn_params['scale'],
+                                         input_zero_point=tensor.qnn_params['zero_point'])
+        return dequantized
+
     def convert_conv2d(self, op):
         """Convert TFLite conv2d"""
         return self.convert_conv(op, "conv2d")