Added TENSOR_QUANT8_SYMM type.
Test: none
Change-Id: I02fc8698b3f80e1ae2a318e5cde593c6d7222bac
Merged-In: I02fc8698b3f80e1ae2a318e5cde593c6d7222bac
(cherry picked from commit bae91697b5397693a10f225de3d39102152e4f18)
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index 9e7d8f0..2e48ba0 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -47,7 +47,7 @@
* used to convert the 16 bit number to a real value in the following way:
* realValue = integerValue * scale.
*
- * scale is a 32 bit floating point with value greater then zero.
+ * scale is a 32 bit floating point with value greater than zero.
*/
TENSOR_QUANT16_SYMM = 7,
/** A tensor of IEEE 754 16 bit floating point values. */
@@ -97,6 +97,16 @@
* real_value = (integer_value - zeroPoint) * scale.
*/
TENSOR_QUANT16_ASYMM = 12,
+ /**
+ * A tensor of 8 bit signed integers that represent real numbers.
+ *
+ * Attached to this tensor is a number representing real value scale that is
+ * used to convert the 8 bit number to a real value in the following way:
+ * realValue = integerValue * scale.
+ *
+ * scale is a 32 bit floating point with value greater than zero.
+ */
+ TENSOR_QUANT8_SYMM = 13,
/* ADDING A NEW FUNDAMENTAL TYPE REQUIRES UPDATING THE VALUE OF
* OperandTypeRange::FUNDAMENTAL_MAX.
*/
@@ -111,7 +121,7 @@
enum OperandTypeRange : uint32_t {
BASE_MIN = 0,
FUNDAMENTAL_MIN = 0,
- FUNDAMENTAL_MAX = 12,
+ FUNDAMENTAL_MAX = 13,
OEM_MIN = 10000,
OEM_MAX = 10001,
BASE_MAX = 0xFFFF,
diff --git a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
index 1bbb203..590116e 100644
--- a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
@@ -161,6 +161,7 @@
case OperandType::TENSOR_FLOAT32:
case OperandType::TENSOR_INT32:
case OperandType::TENSOR_QUANT8_ASYMM:
+ case OperandType::TENSOR_QUANT8_SYMM:
case OperandType::TENSOR_QUANT16_ASYMM:
case OperandType::TENSOR_QUANT16_SYMM:
case OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:
@@ -199,6 +200,7 @@
return 1.0f;
case OperandType::TENSOR_INT32:
return -1.0f;
+ case OperandType::TENSOR_QUANT8_SYMM:
case OperandType::TENSOR_QUANT8_ASYMM:
case OperandType::TENSOR_QUANT16_ASYMM:
case OperandType::TENSOR_QUANT16_SYMM:
@@ -235,6 +237,8 @@
return {1};
case OperandType::TENSOR_QUANT8_ASYMM:
return {-1, 256};
+ case OperandType::TENSOR_QUANT8_SYMM:
+ return {-129, -1, 1, 128};
case OperandType::TENSOR_QUANT16_ASYMM:
return {-1, 65536};
case OperandType::TENSOR_QUANT16_SYMM:
@@ -292,6 +296,7 @@
newOperand.zeroPoint = 0;
break;
case OperandType::TENSOR_QUANT8_ASYMM:
+ case OperandType::TENSOR_QUANT8_SYMM:
case OperandType::TENSOR_QUANT16_ASYMM:
case OperandType::TENSOR_QUANT16_SYMM:
newOperand.dimensions =