anijain2305 commented on a change in pull request #5848:
URL: https://github.com/apache/incubator-tvm/pull/5848#discussion_r445135010
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File path: python/tvm/relay/frontend/tflite.py
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@@ -2566,17 +2613,27 @@ def convert_quantize(self, op):
input_tensors = self.get_input_tensors(op)
assert len(input_tensors) == 1, "input tensors length should be 1"
input_tensor = input_tensors[0]
+ input_tensor_type_str =
self.get_tensor_type_str(input_tensor.tensor.Type())
in_expr = self.get_expr(input_tensor.tensor_idx)
output_tensors = self.get_output_tensors(op)
assert len(output_tensors) == 1, "output tensors length should be 1"
output_tensor = output_tensors[0]
+ output_tensor_type_str =
self.get_tensor_type_str(output_tensor.tensor.Type())
# The output must be quantized
assert output_tensor.qnn_params
- # Quantize the input
- out = self.quantize(in_expr, output_tensor)
+ # TFLite Quantize op can also act as Requantize op
+ if input_tensor_type_str == "float32":
+ out = self.quantize(in_expr, output_tensor)
+ else:
+ out = _qnn.op.requantize(in_expr,
+
input_scale=input_tensor.qnn_params['scale'],
+
input_zero_point=input_tensor.qnn_params['zero_point'],
+
output_scale=output_tensor.qnn_params['scale'],
+
output_zero_point=output_tensor.qnn_params['zero_point'],
+ out_dtype=output_tensor_type_str)
return out
Review comment:
You are right. I will add a test case in this PR. This will enable us to
keep those 5 end to end tests as well.
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