diff options
Diffstat (limited to 'reference_model/src/tensor.cc')
| -rw-r--r-- | reference_model/src/tensor.cc | 392 |
1 files changed, 392 insertions, 0 deletions
diff --git a/reference_model/src/tensor.cc b/reference_model/src/tensor.cc index 5fffa8a..645b55f 100644 --- a/reference_model/src/tensor.cc +++ b/reference_model/src/tensor.cc @@ -647,6 +647,31 @@ int TosaReference::Tensor::readfromVector(const ArrayProxy<half_float::half> val return 0; } +int TosaReference::Tensor::readfromVector(const ArrayProxy<int16_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; + } + + setTensorValueInt16(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<int32_t> vals) { uint32_t elements = getElementCount(); @@ -822,6 +847,31 @@ int TosaReference::Tensor::writeToVector(ArrayProxy<half_float::half> vals) return 0; } +int TosaReference::Tensor::writeToVector(ArrayProxy<int16_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; + } + + getTensorValueInt16(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<int32_t> vals) { uint32_t elements = getElementCount(); @@ -1205,6 +1255,158 @@ int TosaReference::Tensor6<float>::setTensorValueFloat(const size_t bufLen, cons } 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. " + "Implement template specialization version."); + return 0; +} + +template <> +int TosaReference::Tensor0<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_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>::setTensorValueInt16(const size_t bufLen, const int16_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>::setTensorValueInt16(const size_t bufLen, const int16_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>::setTensorValueInt16(const size_t bufLen, const int16_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>::setTensorValueInt16(const size_t bufLen, const int16_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>::setTensorValueInt16(const size_t bufLen, const int16_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>::setTensorValueInt16(const size_t bufLen, const int16_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>::setTensorValueInt32(const size_t bufLen, const int32_t* vals) { FATAL_ERROR("TensorTemplate<T>::setTensorValueInt32 should not be called. " @@ -2041,6 +2243,196 @@ int TosaReference::Tensor6<float>::getTensorValueFloat(const size_t bufLen, floa } 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. " + "Implement template specialization version."); + return 0; +} + +template <> +int TosaReference::Tensor0<int32_t>::getTensorValueInt16(const size_t bufLen, int16_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>::getTensorValueInt16(const size_t bufLen, int16_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>::getTensorValueInt16(const size_t bufLen, int16_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>::getTensorValueInt16(const size_t bufLen, int16_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>::getTensorValueInt16(const size_t bufLen, int16_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>::getTensorValueInt16(const size_t bufLen, int16_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>::getTensorValueInt16(const size_t bufLen, int16_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>::getTensorValueInt32(const size_t bufLen, int32_t* vals) const { FATAL_ERROR("TensorTemplate<T>::getTensorValueInt32 should not be called. 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