diff options
Diffstat (limited to 'reference_model/src/tensor.cc')
| -rw-r--r-- | reference_model/src/tensor.cc | 776 |
1 files changed, 776 insertions, 0 deletions
diff --git a/reference_model/src/tensor.cc b/reference_model/src/tensor.cc index e84507b..f9ec937 100644 --- a/reference_model/src/tensor.cc +++ b/reference_model/src/tensor.cc @@ -323,6 +323,8 @@ int TosaReference::Tensor::writeToNpyFile(const char* filename) const float* f32databuf = nullptr; double* f64databuf = nullptr; half_float::half* f16databuf = nullptr; + uint8_t* ui8databuf = nullptr; + int8_t* i8databuf = nullptr; int32_t* i32databuf = nullptr; int64_t* i64databuf = nullptr; bool* bdatabuf = nullptr; @@ -369,9 +371,48 @@ int TosaReference::Tensor::writeToNpyFile(const char* filename) const free(f16databuf); break; case TOSA_REF_TYPE_INT32: + i32databuf = (int32_t*)calloc(sizeof(int32_t), elements); + ASSERT_MEM(i32databuf); + + if (getTensorValueInt32(elements, i32databuf)) + { + free(i32databuf); + return 1; + } + + nperror = NumpyUtilities::writeToNpyFile(filename, shape, i32databuf); + + free(i32databuf); + break; case TOSA_REF_TYPE_UINT8: + ui8databuf = (uint8_t*)calloc(sizeof(uint8_t), elements); + ASSERT_MEM(ui8databuf); + + if (getTensorValueUInt8(elements, ui8databuf)) + { + free(ui8databuf); + return 1; + } + + nperror = NumpyUtilities::writeToNpyFile(filename, shape, ui8databuf); + + free(ui8databuf); + break; case TOSA_REF_TYPE_INT4: case TOSA_REF_TYPE_INT8: + i8databuf = (int8_t*)calloc(sizeof(int8_t), elements); + ASSERT_MEM(i8databuf); + + if (getTensorValueInt8(elements, i8databuf)) + { + free(i8databuf); + return 1; + } + + nperror = NumpyUtilities::writeToNpyFile(filename, shape, i8databuf); + + free(i8databuf); + break; case TOSA_REF_TYPE_INT16: case TOSA_REF_TYPE_UINT16: i32databuf = (int32_t*)calloc(sizeof(int32_t), elements); @@ -663,6 +704,31 @@ int TosaReference::Tensor::readfromVector(const ArrayProxy<half_float::half> val return 0; } +int TosaReference::Tensor::readfromVector(const ArrayProxy<int8_t> vals) +{ + uint32_t elements = getElementCount(); + switch (getDtype()) + { + case TOSA_REF_TYPE_INT8: + case TOSA_REF_TYPE_UINT8: + 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; + } + + setTensorValueInt8(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(); @@ -863,6 +929,30 @@ int TosaReference::Tensor::writeToVector(ArrayProxy<half_float::half> vals) return 0; } +int TosaReference::Tensor::writeToVector(ArrayProxy<int8_t> vals) +{ + uint32_t elements = getElementCount(); + switch (getDtype()) + { + case TOSA_REF_TYPE_INT8: + case TOSA_REF_TYPE_UINT8: + 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; + } + + getTensorValueInt8(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(); @@ -1415,6 +1505,310 @@ int TosaReference::Tensor6<double>::setTensorValueFloat(const size_t bufLen, con } template <class T> +int TosaReference::TensorTemplate<T>::setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) +{ + FATAL_ERROR("TensorTemplate<T>::setTensorValueUInt8 should not be called. " + "Implement template specialization version."); + return 0; +} + +template <> +int TosaReference::Tensor0<int32_t>::setTensorValueUInt8(const size_t bufLen, const uint8_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>::setTensorValueUInt8(const size_t bufLen, const uint8_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>::setTensorValueUInt8(const size_t bufLen, const uint8_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>::setTensorValueUInt8(const size_t bufLen, const uint8_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>::setTensorValueUInt8(const size_t bufLen, const uint8_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>::setTensorValueUInt8(const size_t bufLen, const uint8_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>::setTensorValueUInt8(const size_t bufLen, const uint8_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>::setTensorValueInt8(const size_t bufLen, const int8_t* vals) +{ + FATAL_ERROR("TensorTemplate<T>::setTensorValueInt8 should not be called. " + "Implement template specialization version."); + return 0; +} + +template <> +int TosaReference::Tensor0<int32_t>::setTensorValueInt8(const size_t bufLen, const int8_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>::setTensorValueInt8(const size_t bufLen, const int8_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>::setTensorValueInt8(const size_t bufLen, const int8_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>::setTensorValueInt8(const size_t bufLen, const int8_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>::setTensorValueInt8(const size_t bufLen, const int8_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>::setTensorValueInt8(const size_t bufLen, const int8_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>::setTensorValueInt8(const size_t bufLen, const int8_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. " @@ -2403,6 +2797,388 @@ int TosaReference::Tensor6<float>::getTensorValueFloat(const size_t bufLen, floa } template <class T> +int TosaReference::TensorTemplate<T>::getTensorValueUInt8(const size_t bufLen, uint8_t* vals) const +{ + std::cout << "T is: " << typeid(T).name() << std::endl; + FATAL_ERROR("TensorTemplate<T>::getTensorValueUInt8 should not be called. " + "Implement template specialization version."); + return 0; +} + +template <> +int TosaReference::Tensor0<int32_t>::getTensorValueUInt8(const size_t bufLen, uint8_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>::getTensorValueUInt8(const size_t bufLen, uint8_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>::getTensorValueUInt8(const size_t bufLen, uint8_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>::getTensorValueUInt8(const size_t bufLen, uint8_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>::getTensorValueUInt8(const size_t bufLen, uint8_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>::getTensorValueUInt8(const size_t bufLen, uint8_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>::getTensorValueUInt8(const size_t bufLen, uint8_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>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const +{ + std::cout << "T is: " << typeid(T).name() << std::endl; + FATAL_ERROR("TensorTemplate<T>::getTensorValueInt8 should not be called. " + "Implement template specialization version."); + return 0; +} + +template <> +int TosaReference::Tensor0<int32_t>::getTensorValueInt8(const size_t bufLen, int8_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>::getTensorValueInt8(const size_t bufLen, int8_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>::getTensorValueInt8(const size_t bufLen, int8_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>::getTensorValueInt8(const size_t bufLen, int8_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>::getTensorValueInt8(const size_t bufLen, int8_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>::getTensorValueInt8(const size_t bufLen, int8_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>::getTensorValueInt8(const size_t bufLen, int8_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. " |