Save Int16/UINT16 test outputs to native dtypes
* Int16/UInt16 reference outputs were previously saved to INT32
* Save those in their native dtypes and updated other affected code
Signed-off-by: Jerry Ge <jerry.ge@arm.com>
Change-Id: I0c3b7fba096a8cb1ddabef20ad13498b8f46d36f
diff --git a/reference_model/src/tensor.cc b/reference_model/src/tensor.cc
index 27f21f3..16020cf 100644
--- a/reference_model/src/tensor.cc
+++ b/reference_model/src/tensor.cc
@@ -353,6 +353,8 @@
half_float::half* f16databuf = nullptr;
uint8_t* ui8databuf = nullptr;
int8_t* i8databuf = nullptr;
+ int16_t* i16databuf = nullptr;
+ uint16_t* ui16databuf = nullptr;
int32_t* i32databuf = nullptr;
int64_t* i64databuf = nullptr;
bool* bdatabuf = nullptr;
@@ -444,19 +446,32 @@
free(i8databuf);
break;
case TOSA_REF_TYPE_INT16:
- case TOSA_REF_TYPE_UINT16:
- i32databuf = (int32_t*)calloc(sizeof(int32_t), elements);
- ASSERT_MEM(i32databuf);
+ i16databuf = (int16_t*)calloc(sizeof(int16_t), elements);
+ ASSERT_MEM(i16databuf);
- if (getTensorValueInt32(elements, i32databuf))
+ if (getTensorValueInt16(elements, i16databuf))
{
- free(i32databuf);
+ free(i16databuf);
return 1;
}
- nperror = NumpyUtilities::writeToNpyFile(filename, shape, i32databuf);
+ nperror = NumpyUtilities::writeToNpyFile(filename, shape, i16databuf);
- free(i32databuf);
+ free(i16databuf);
+ break;
+ case TOSA_REF_TYPE_UINT16:
+ ui16databuf = (uint16_t*)calloc(sizeof(uint16_t), elements);
+ ASSERT_MEM(ui16databuf);
+
+ if (getTensorValueUInt16(elements, ui16databuf))
+ {
+ free(ui16databuf);
+ return 1;
+ }
+
+ nperror = NumpyUtilities::writeToNpyFile(filename, shape, ui16databuf);
+
+ free(ui16databuf);
break;
case TOSA_REF_TYPE_INT48:
case TOSA_REF_TYPE_SHAPE:
@@ -761,6 +776,31 @@
return 0;
}
+int TosaReference::Tensor::readfromVector(const ArrayProxy<uint16_t> vals)
+{
+ uint32_t elements = getElementCount();
+ switch (getDtype())
+ {
+ case TOSA_REF_TYPE_INT16:
+ case TOSA_REF_TYPE_UINT16:
+ if (vals.size() != elements)
+ {
+ WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.",
+ vals.size(), elements);
+ return -1;
+ }
+
+ setTensorValueUInt16(elements, vals.data());
+ break;
+ default:
+ WARNING("The input type doesn't match the data type assigned to the tensor (%s).",
+ EnumNameTOSAREFTYPE(getDtype()));
+ return -2;
+ }
+ setIsValid();
+ return 0;
+}
+
int TosaReference::Tensor::readfromVector(const ArrayProxy<int16_t> vals)
{
uint32_t elements = getElementCount();
@@ -985,6 +1025,31 @@
return 0;
}
+int TosaReference::Tensor::writeToVector(ArrayProxy<uint16_t> vals)
+{
+ uint32_t elements = getElementCount();
+
+ switch (getDtype())
+ {
+ case TOSA_REF_TYPE_INT16:
+ case TOSA_REF_TYPE_UINT16:
+ if (vals.size() != elements)
+ {
+ WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.",
+ vals.size(), elements);
+ return -1;
+ }
+
+ getTensorValueUInt16(elements, vals.data());
+ break;
+ default:
+ WARNING("The output type doesn't match the data type assigned to the tensor (%s).",
+ EnumNameTOSAREFTYPE(getDtype()));
+ return -2;
+ }
+ return 0;
+}
+
int TosaReference::Tensor::writeToVector(ArrayProxy<int16_t> vals)
{
uint32_t elements = getElementCount();
@@ -1841,9 +1906,161 @@
}
template <class T>
+int TosaReference::TensorTemplate<T>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals)
+{
+ FATAL_ERROR("TensorTemplate<T>::setTensorValueUInt16 should not be called. "
+ "Implement template specialization version.");
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor0<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals)
+{
+ ASSERT_MSG(bufLen == getElementCount(), "Total elements must match");
+
+ (*tensor)(0) = static_cast<int32_t>(vals[0]);
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor1<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals)
+{
+ uint32_t idx = 0;
+
+ ASSERT_MSG(bufLen == getElementCount(), "Total elements must match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ (*tensor)(i0) = static_cast<int32_t>(vals[idx++]);
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor2<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals)
+{
+ uint32_t idx = 0;
+
+ ASSERT_MSG(bufLen == getElementCount(), "Total elements must match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ (*tensor)(i0, i1) = static_cast<int32_t>(vals[idx++]);
+ }
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor3<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals)
+{
+ uint32_t idx = 0;
+
+ ASSERT_MSG(bufLen == getElementCount(), "Total elements must match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ for (int i2 = 0; i2 < shape[2]; i2++)
+ {
+ (*tensor)(i0, i1, i2) = static_cast<int32_t>(vals[idx++]);
+ }
+ }
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor4<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals)
+{
+ uint32_t idx = 0;
+
+ ASSERT_MSG(bufLen == getElementCount(), "Total elements must match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ for (int i2 = 0; i2 < shape[2]; i2++)
+ {
+ for (int i3 = 0; i3 < shape[3]; i3++)
+ {
+ (*tensor)(i0, i1, i2, i3) = static_cast<int32_t>(vals[idx++]);
+ }
+ }
+ }
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor5<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals)
+{
+ uint32_t idx = 0;
+
+ ASSERT_MSG(bufLen == getElementCount(), "Total elements must match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ for (int i2 = 0; i2 < shape[2]; i2++)
+ {
+ for (int i3 = 0; i3 < shape[3]; i3++)
+ {
+ for (int i4 = 0; i4 < shape[4]; i4++)
+ {
+ (*tensor)(i0, i1, i2, i3, i4) = static_cast<int32_t>(vals[idx++]);
+ }
+ }
+ }
+ }
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor6<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals)
+{
+ uint32_t idx = 0;
+
+ ASSERT_MSG(bufLen == getElementCount(), "Total elements must match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ for (int i2 = 0; i2 < shape[2]; i2++)
+ {
+ for (int i3 = 0; i3 < shape[3]; i3++)
+ {
+ for (int i4 = 0; i4 < shape[4]; i4++)
+ {
+ for (int i5 = 0; i5 < shape[5]; i5++)
+ {
+ (*tensor)(i0, i1, i2, i3, i4, i5) = static_cast<int32_t>(vals[idx++]);
+ }
+ }
+ }
+ }
+ }
+ }
+ return 0;
+}
+
+template <class T>
int TosaReference::TensorTemplate<T>::setTensorValueInt16(const size_t bufLen, const int16_t* vals)
{
- FATAL_ERROR("TensorTemplate<T>::setTensorValueInt32 should not be called. "
+ FATAL_ERROR("TensorTemplate<T>::setTensorValueInt16 should not be called. "
"Implement template specialization version.");
return 0;
}
@@ -3211,9 +3428,199 @@
}
template <class T>
+int TosaReference::TensorTemplate<T>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const
+{
+ FATAL_ERROR("TensorTemplate<T>::getTensorValueUInt16 should not be called. "
+ "Implement template specialization version.");
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor0<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const
+{
+ int totalVals = 1;
+
+ ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match");
+
+ vals[0] = (*tensor)(0);
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor1<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const
+{
+ uint32_t idx = 0;
+ int totalVals = 1;
+
+ for (size_t i = 0; i < shape.size(); i++)
+ {
+ totalVals *= shape[i];
+ }
+
+ ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ vals[idx++] = (*tensor)(i0);
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor2<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const
+{
+ uint32_t idx = 0;
+ int totalVals = 1;
+
+ for (size_t i = 0; i < shape.size(); i++)
+ {
+ totalVals *= shape[i];
+ }
+
+ ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ vals[idx++] = (*tensor)(i0, i1);
+ }
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor3<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const
+{
+ uint32_t idx = 0;
+ int totalVals = 1;
+
+ for (size_t i = 0; i < shape.size(); i++)
+ {
+ totalVals *= shape[i];
+ }
+
+ ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ for (int i2 = 0; i2 < shape[2]; i2++)
+ {
+ vals[idx++] = (*tensor)(i0, i1, i2);
+ }
+ }
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor4<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const
+{
+ uint32_t idx = 0;
+ int totalVals = 1;
+
+ for (size_t i = 0; i < shape.size(); i++)
+ {
+ totalVals *= shape[i];
+ }
+
+ ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ for (int i2 = 0; i2 < shape[2]; i2++)
+ {
+ for (int i3 = 0; i3 < shape[3]; i3++)
+ {
+ vals[idx++] = (*tensor)(i0, i1, i2, i3);
+ }
+ }
+ }
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor5<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const
+{
+ uint32_t idx = 0;
+ int totalVals = 1;
+
+ for (size_t i = 0; i < shape.size(); i++)
+ {
+ totalVals *= shape[i];
+ }
+
+ ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ for (int i2 = 0; i2 < shape[2]; i2++)
+ {
+ for (int i3 = 0; i3 < shape[3]; i3++)
+ {
+ for (int i4 = 0; i4 < shape[4]; i4++)
+ {
+ vals[idx++] = (*tensor)(i0, i1, i2, i3, i4);
+ }
+ }
+ }
+ }
+ }
+
+ return 0;
+}
+
+template <>
+int TosaReference::Tensor6<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const
+{
+ uint32_t idx = 0;
+ int totalVals = 1;
+
+ for (size_t i = 0; i < shape.size(); i++)
+ {
+ totalVals *= shape[i];
+ }
+
+ ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match");
+
+ for (int i0 = 0; i0 < shape[0]; i0++)
+ {
+ for (int i1 = 0; i1 < shape[1]; i1++)
+ {
+ for (int i2 = 0; i2 < shape[2]; i2++)
+ {
+ for (int i3 = 0; i3 < shape[3]; i3++)
+ {
+ for (int i4 = 0; i4 < shape[4]; i4++)
+ {
+ for (int i5 = 0; i5 < shape[5]; i5++)
+ {
+ vals[idx++] = (*tensor)(i0, i1, i2, i3, i4, i5);
+ }
+ }
+ }
+ }
+ }
+ }
+ return 0;
+}
+
+template <class T>
int TosaReference::TensorTemplate<T>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const
{
- FATAL_ERROR("TensorTemplate<T>::getTensorValueInt32 should not be called. "
+ FATAL_ERROR("TensorTemplate<T>::getTensorValueInt16 should not be called. "
"Implement template specialization version.");
return 0;
}
diff --git a/reference_model/src/tensor.h b/reference_model/src/tensor.h
index 1659a2f..26c6aa7 100644
--- a/reference_model/src/tensor.h
+++ b/reference_model/src/tensor.h
@@ -239,22 +239,24 @@
virtual int dumpTensorParams(FILE* out) const;
virtual int dumpTensorParams(std::ostream& out) const;
- virtual int setTensorValueDouble(const size_t bufLen, const double* vals) = 0;
- virtual int setTensorValueFloat(const size_t bufLen, const float* vals) = 0;
- virtual int setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) = 0;
- virtual int setTensorValueInt8(const size_t bufLen, const int8_t* vals) = 0;
- virtual int setTensorValueInt16(const size_t bufLen, const int16_t* vals) = 0;
- virtual int setTensorValueInt32(const size_t bufLen, const int32_t* vals) = 0;
- virtual int setTensorValueInt64(const size_t bufLen, const int64_t* vals) = 0;
- virtual int setTensorValueBool(const size_t bufLen, const bool* vals) = 0;
- virtual int getTensorValueDouble(const size_t bufLen, double* fbuf) const = 0;
- virtual int getTensorValueFloat(const size_t bufLen, float* fbuf) const = 0;
- virtual int getTensorValueUInt8(const size_t bufLen, uint8_t* ibuf) const = 0;
- virtual int getTensorValueInt8(const size_t bufLen, int8_t* ibuf) const = 0;
- virtual int getTensorValueInt16(const size_t bufLen, int16_t* ibuf) const = 0;
- virtual int getTensorValueInt32(const size_t bufLen, int32_t* ibuf) const = 0;
- virtual int getTensorValueInt64(const size_t bufLen, int64_t* ibuf) const = 0;
- virtual int getTensorValueBool(const size_t bufLen, bool* ibuf) const = 0;
+ virtual int setTensorValueDouble(const size_t bufLen, const double* vals) = 0;
+ virtual int setTensorValueFloat(const size_t bufLen, const float* vals) = 0;
+ virtual int setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) = 0;
+ virtual int setTensorValueInt8(const size_t bufLen, const int8_t* vals) = 0;
+ virtual int setTensorValueUInt16(const size_t bufLen, const uint16_t* vals) = 0;
+ virtual int setTensorValueInt16(const size_t bufLen, const int16_t* vals) = 0;
+ virtual int setTensorValueInt32(const size_t bufLen, const int32_t* vals) = 0;
+ virtual int setTensorValueInt64(const size_t bufLen, const int64_t* vals) = 0;
+ virtual int setTensorValueBool(const size_t bufLen, const bool* vals) = 0;
+ virtual int getTensorValueDouble(const size_t bufLen, double* fbuf) const = 0;
+ virtual int getTensorValueFloat(const size_t bufLen, float* fbuf) const = 0;
+ virtual int getTensorValueUInt8(const size_t bufLen, uint8_t* ibuf) const = 0;
+ virtual int getTensorValueInt8(const size_t bufLen, int8_t* ibuf) const = 0;
+ virtual int getTensorValueUInt16(const size_t bufLen, uint16_t* ibuf) const = 0;
+ virtual int getTensorValueInt16(const size_t bufLen, int16_t* ibuf) const = 0;
+ virtual int getTensorValueInt32(const size_t bufLen, int32_t* ibuf) const = 0;
+ virtual int getTensorValueInt64(const size_t bufLen, int64_t* ibuf) const = 0;
+ virtual int getTensorValueBool(const size_t bufLen, bool* ibuf) const = 0;
virtual int readFromNpyFile(const char* filename);
virtual int writeToNpyFile(const char* filename) const;
@@ -264,6 +266,7 @@
virtual int readfromVector(const ArrayProxy<float> vals);
virtual int readfromVector(const ArrayProxy<half_float::half> vals);
virtual int readfromVector(const ArrayProxy<int8_t> vals);
+ virtual int readfromVector(const ArrayProxy<uint16_t> vals);
virtual int readfromVector(const ArrayProxy<int16_t> vals);
virtual int readfromVector(const ArrayProxy<int32_t> vals);
virtual int readfromVector(const ArrayProxy<int64_t> vals);
@@ -273,6 +276,7 @@
virtual int writeToVector(ArrayProxy<float> vals);
virtual int writeToVector(ArrayProxy<half_float::half> vals);
virtual int writeToVector(ArrayProxy<int8_t> vals);
+ virtual int writeToVector(ArrayProxy<uint16_t> vals);
virtual int writeToVector(ArrayProxy<int16_t> vals);
virtual int writeToVector(ArrayProxy<int32_t> vals);
virtual int writeToVector(ArrayProxy<int64_t> vals);
@@ -369,6 +373,7 @@
virtual int setTensorValueFloat(const size_t bufLen, const float* vals);
virtual int setTensorValueUInt8(const size_t bufLen, const uint8_t* vals);
virtual int setTensorValueInt8(const size_t bufLen, const int8_t* vals);
+ virtual int setTensorValueUInt16(const size_t bufLen, const uint16_t* vals);
virtual int setTensorValueInt16(const size_t bufLen, const int16_t* vals);
virtual int setTensorValueInt32(const size_t bufLen, const int32_t* vals);
virtual int setTensorValueInt64(const size_t bufLen, const int64_t* vals);
@@ -378,6 +383,7 @@
virtual int getTensorValueFloat(const size_t bufLen, float* fbuf) const;
virtual int getTensorValueUInt8(const size_t bufLen, uint8_t* ibuf) const;
virtual int getTensorValueInt8(const size_t bufLen, int8_t* ibuf) const;
+ virtual int getTensorValueUInt16(const size_t bufLen, uint16_t* ibuf) const;
virtual int getTensorValueInt16(const size_t bufLen, int16_t* ibuf) const;
virtual int getTensorValueInt32(const size_t bufLen, int32_t* ibuf) const;
virtual int getTensorValueInt64(const size_t bufLen, int64_t* ibuf) const;
@@ -572,6 +578,21 @@
int Tensor6<int32_t>::setTensorValueInt8(const size_t bufLen, const int8_t* vals);
template <>
+int Tensor0<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals);
+template <>
+int Tensor1<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals);
+template <>
+int Tensor2<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals);
+template <>
+int Tensor3<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals);
+template <>
+int Tensor4<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals);
+template <>
+int Tensor5<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals);
+template <>
+int Tensor6<int32_t>::setTensorValueUInt16(const size_t bufLen, const uint16_t* vals);
+
+template <>
int Tensor0<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_t* vals);
template <>
int Tensor1<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_t* vals);
@@ -632,6 +653,21 @@
int Tensor6<int32_t>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const;
template <>
+int Tensor0<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const;
+template <>
+int Tensor1<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const;
+template <>
+int Tensor2<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const;
+template <>
+int Tensor3<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const;
+template <>
+int Tensor4<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const;
+template <>
+int Tensor5<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const;
+template <>
+int Tensor6<int32_t>::getTensorValueUInt16(const size_t bufLen, uint16_t* vals) const;
+
+template <>
int Tensor0<int32_t>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const;
template <>
int Tensor1<int32_t>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const;
diff --git a/verif/frameworks/tosa_verif_framework_compiler_runner.py b/verif/frameworks/tosa_verif_framework_compiler_runner.py
index ce9b253..56daa51 100755
--- a/verif/frameworks/tosa_verif_framework_compiler_runner.py
+++ b/verif/frameworks/tosa_verif_framework_compiler_runner.py
@@ -695,7 +695,11 @@
tf_result = tf_result.astype(np.int8)
elif tf_result.dtype == np.uint8:
tf_result = tf_result.astype(np.uint8)
- elif tf_result.dtype == np.int16 or tf_result.dtype == np.int64:
+ elif tf_result.dtype == np.int16:
+ tf_result = tf_result.astype(np.int16)
+ elif tf_result.dtype == np.uint16:
+ tf_result = tf_result.astype(np.uint16)
+ elif tf_result.dtype == np.int64:
tf_result = tf_result.astype(np.int32)
# For now, search for the first output from ref_model
diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py
index bc931dc..8440853 100644
--- a/verif/generator/tosa_test_gen.py
+++ b/verif/generator/tosa_test_gen.py
@@ -195,6 +195,10 @@
return np.int8(self.rng.integers(low=low, high=high, size=shape))
elif dtype == DType.UINT8:
return np.uint8(self.rng.integers(low=low, high=high, size=shape))
+ elif dtype == DType.INT16:
+ return np.int16(self.rng.integers(low=low, high=high, size=shape))
+ elif dtype == DType.UINT16:
+ return np.uint16(self.rng.integers(low=low, high=high, size=shape))
elif dtype in (DType.INT48, DType.SHAPE):
return np.int64(self.rng.integers(low=low, high=high, size=shape))
elif dtype in (