[GitHub] [tvm] ashutosh-arm commented on a diff in pull request #12042: [TFLite] Enable int64 biases for int16 quantized operators

[GitBox <gi...@apache.org>]

ashutosh-arm commented on code in PR #12042:
URL: https://github.com/apache/tvm/pull/12042#discussion_r1018896087


##########
src/relay/qnn/op/dense.cc:
##########
@@ -47,12 +47,14 @@ bool QnnDenseRel(const Array<Type>& types, int num_inputs, const Attrs& attrs,
   if (data == nullptr || weight == nullptr) return false;
   const auto* param = attrs.as<DenseAttrs>();
   ICHECK(param != nullptr) << "DenseAttrs cannot be nullptr.";
-  ICHECK(data->dtype == DataType::Int(8) || data->dtype == DataType::UInt(8))
-      << "Expected quantized dense type(int8, uint8) for input but was " << data->dtype;
+  ICHECK(data->dtype == DataType::Int(8) || data->dtype == DataType::UInt(8) ||
+         data->dtype == DataType::Int(16) || data->dtype == DataType::UInt(16))
+      << "Expected quantized dense type(int8, uint8, int16, uint16) for input but was "
+      << data->dtype;
   ICHECK(weight->dtype == DataType::Int(8) || weight->dtype == DataType::UInt(8))
       << "Expected quantized dense type(int8, uint8) for weight but was " << weight->dtype;
-  ICHECK(param->out_dtype == DataType::Int(32))
-      << "Expected quantized dense type(int32) for output but was " << param->out_dtype;
+  ICHECK(param->out_dtype == DataType::Int(32) || param->out_dtype == DataType::Int(64))
+      << "Expected quantized dense type(int32, int64) for output but was " << param->out_dtype;

Review Comment:
   Do we need additional dtype checks for bias as well based on output dtype? If yes, then probably we should check the QNN Conv2D type checker too.



##########
tests/python/contrib/test_ethosn/test_convert_equivalents.py:
##########
@@ -227,7 +227,7 @@ def expected():
 @requires_ethosn
 @pytest.mark.parametrize(
     "dtype,shape,constant_shape",
-    [("int16", (1, 16, 12, 4), None)],
+    [("float32", (1, 16, 12, 4), None)],

Review Comment:
   Just curious: why the dtype change?



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