diff options
Diffstat (limited to 'reference_model/src/generate/generate_dot_product.cc')
| -rw-r--r-- | reference_model/src/generate/generate_dot_product.cc | 143 |
1 files changed, 143 insertions, 0 deletions
diff --git a/reference_model/src/generate/generate_dot_product.cc b/reference_model/src/generate/generate_dot_product.cc index 046007e..7337969 100644 --- a/reference_model/src/generate/generate_dot_product.cc +++ b/reference_model/src/generate/generate_dot_product.cc @@ -736,6 +736,147 @@ bool generateTransposeConv2D(const TosaReference::GenerateConfig& cfg, return false; } } + +//---------------------------------------------------------------------------// +// Conv3D // +//---------------------------------------------------------------------------// + +template <typename DataType> +bool generateConv3DInput(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + if (cfg.dotProductInfo.kernel.size() != 3 || cfg.dotProductInfo.kernel[0] <= 0 || + cfg.dotProductInfo.kernel[1] <= 0 || cfg.dotProductInfo.kernel[2] <= 0) + { + WARNING("[Generator][DP][Conv3D][Input] Missing or incorrect kernel size information."); + return false; + } + if (cfg.shape.size() != 5) + { + WARNING("[Generator][DP][Conv3D][Input] Tensor shape expected 5 dimensions."); + return false; + } + + const int64_t T = TosaReference::numElementsFromShape(cfg.shape); + const uint32_t ID = cfg.shape[1]; + const uint32_t IH = cfg.shape[2]; + const uint32_t IW = cfg.shape[3]; + const uint32_t IC = cfg.shape[4]; + const uint32_t KD = cfg.dotProductInfo.kernel[0]; + const uint32_t KH = cfg.dotProductInfo.kernel[1]; + const uint32_t KW = cfg.dotProductInfo.kernel[2]; + + for (int64_t t = 0; t < T; ++t) + { + uint32_t ic = t % IC; + uint32_t ix = (t / IC) % IW; + uint32_t iy = ((t / IC) / IW) % IH; + uint32_t id = (((t / IC) / IW) / IH) % ID; + uint32_t k = (((id % KD) * KH + (iy % KH)) * KW + (ix % KW)) * IC + ic; + + data[t] = static_cast<DataType>(generator(k)); + } + return true; +} + +template <typename DataType> +bool generateConv3DWeight(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + if (cfg.shape.size() != 5) + { + WARNING("[Generator][DP][Conv3D][Weight] Tensor shape expected 5 dimensions."); + return false; + } + + const int64_t T = TosaReference::numElementsFromShape(cfg.shape); + const uint32_t KD = cfg.shape[0]; + const uint32_t KH = cfg.shape[1]; + const uint32_t KW = cfg.shape[2]; + const uint32_t IC = cfg.shape[3]; + + for (int64_t t = 0; t < T; ++t) + { + uint32_t ic = t % IC; + uint32_t kx = (t / IC) % KW; + uint32_t ky = ((t / IC) / KW) % KH; + uint32_t kd = (((t / IC) / KW) / KH) % KD; + uint32_t k = ((kd * KH + ky) * KW + kx) * IC + ic; + + data[t] = static_cast<DataType>(generator(k)); + } + return true; +} + +template <typename DataType> +bool generateConv3DBias(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + if (cfg.shape.size() != 1) + { + WARNING("[Generator][DP][Conv3D][Bias] Tensor shape expected 1 dimension."); + return false; + } + + const uint32_t T = cfg.shape[0]; + + for (uint32_t t = 0; t < T; ++t) + { + data[t] = static_cast<DataType>(generator(2)); + } + return true; +} + +bool generateConv3D(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + void* data, + size_t size) +{ + switch (cfg.dataType) + { + case DType::DType_FP32: { + float* outData = reinterpret_cast<float*>(data); + switch (cfg.inputPos) + { + case 0: + return generateConv3DInput(cfg, generator, outData, size); + case 1: + return generateConv3DWeight(cfg, generator, outData, size); + case 2: + return generateConv3DBias(cfg, generator, outData, size); + default: + WARNING("[Generator][DP][Conv3D] Invalid input tensor slot position to operator."); + return false; + } + break; + } + case DType::DType_FP16: { + half_float::half* outData = reinterpret_cast<half_float::half*>(data); + switch (cfg.inputPos) + { + case 0: + return generateConv3DInput(cfg, generator, outData, size); + case 1: + return generateConv3DWeight(cfg, generator, outData, size); + case 2: + return generateConv3DBias(cfg, generator, outData, size); + default: + WARNING("[Generator][DP][Conv3D] Invalid input tensor slot position to operator."); + return false; + } + break; + } + default: + WARNING("[Generator][DP][Conv3D] Only supports FP32 or FP16."); + return false; + } +} //---------------------------------------------------------------------------// // FFT2D // //---------------------------------------------------------------------------// @@ -858,6 +999,8 @@ bool generateDotProduct(const GenerateConfig& cfg, void* data, size_t size) return generateDepthwiseConv2D(cfg, *generator, data, size); case tosa::Op_TRANSPOSE_CONV2D: return generateTransposeConv2D(cfg, *generator, data, size); + case tosa::Op_CONV3D: + return generateConv3D(cfg, *generator, data, size); case tosa::Op_FFT2D: return generateFFT2D(cfg, *generator, data, size); default: |