diff options
Diffstat (limited to 'reference_model/src/generate/generate_dot_product.cc')
| -rw-r--r-- | reference_model/src/generate/generate_dot_product.cc | 137 |
1 files changed, 136 insertions, 1 deletions
diff --git a/reference_model/src/generate/generate_dot_product.cc b/reference_model/src/generate/generate_dot_product.cc index 67190c6..a5870c9 100644 --- a/reference_model/src/generate/generate_dot_product.cc +++ b/reference_model/src/generate/generate_dot_product.cc @@ -402,7 +402,7 @@ bool generateFullyConnected(const TosaReference::GenerateConfig& cfg, } } //---------------------------------------------------------------------------// -// Avg Pool 2D // +// Avg Pool 2D // //---------------------------------------------------------------------------// template <typename DataType> @@ -469,6 +469,139 @@ bool generateAvgPool2D(const TosaReference::GenerateConfig& cfg, return true; } +//---------------------------------------------------------------------------// +// Depthwise Conv2D // +//---------------------------------------------------------------------------// + +template <typename DataType> +bool generateDepthwiseConv2DInput(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + if (cfg.dotProductInfo.kernel.size() != 2 || cfg.dotProductInfo.kernel[0] <= 0 || cfg.dotProductInfo.kernel[1] <= 0) + { + WARNING("[Generator][DP][DWConv2D][Input] Missing or incorrect kernel size information."); + return false; + } + if (cfg.shape.size() != 4) + { + WARNING("[Generator][DP][DWConv2D][Input] Tensor shape expected 4 dimensions."); + return false; + } + + const int64_t T = TosaReference::numElementsFromShape(cfg.shape); + const uint32_t IH = cfg.shape[1]; + const uint32_t IW = cfg.shape[2]; + const uint32_t C = cfg.shape[3]; + const uint32_t KH = cfg.dotProductInfo.kernel[0]; + const uint32_t KW = cfg.dotProductInfo.kernel[1]; + + for (int64_t t = 0; t < T; ++t) + { + uint32_t ix = (t / C) % IW; + uint32_t iy = ((t / C) / IW) % IH; + uint32_t k = ((iy % KH) * KW + (ix % KW)); + + data[t] = static_cast<DataType>(generator(k)); + } + return true; +} + +template <typename DataType> +bool generateDepthwiseConv2DWeight(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + if (cfg.shape.size() != 4) + { + WARNING("[Generator][DP][DWConv2D][Weight] Tensor shape expected 4 dimensions."); + return false; + } + + const int64_t T = TosaReference::numElementsFromShape(cfg.shape); + const uint32_t KH = cfg.shape[0]; + const uint32_t KW = cfg.shape[1]; + const uint32_t C = cfg.shape[2]; + const uint32_t M = cfg.shape[3]; + + for (int64_t t = 0; t < T; ++t) + { + uint32_t kx = ((t / M) / C) % KW; + uint32_t ky = (((t / M) / C) / KW) % KH; + uint32_t k = (ky * KW + kx); + + data[t] = static_cast<DataType>(generator(k)); + } + return true; +} + +template <typename DataType> +bool generateDepthwiseConv2DBias(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + if (cfg.shape.size() != 1) + { + WARNING("[Generator][DP][DWConv2D][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 generateDepthwiseConv2D(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 generateDepthwiseConv2DInput(cfg, generator, outData, size); + case 1: + return generateDepthwiseConv2DWeight(cfg, generator, outData, size); + case 2: + return generateDepthwiseConv2DBias(cfg, generator, outData, size); + default: + WARNING("[Generator][DP][DWConv2D] 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 generateDepthwiseConv2DInput(cfg, generator, outData, size); + case 1: + return generateDepthwiseConv2DWeight(cfg, generator, outData, size); + case 2: + return generateDepthwiseConv2DBias(cfg, generator, outData, size); + default: + WARNING("[Generator][DP][DWConv2D] Invalid input tensor slot position to operator."); + return false; + } + break; + } + default: + WARNING("[Generator][DP][DWConv2D] Only supports FP32 or FP16."); + return false; + } +} } // namespace namespace TosaReference @@ -501,6 +634,8 @@ bool generateDotProduct(const GenerateConfig& cfg, void* data, size_t size) return generateFullyConnected(cfg, *generator, data, size); case tosa::Op_AVG_POOL2D: return generateAvgPool2D(cfg, *generator, data, size); + case tosa::Op_DEPTHWISE_CONV2D: + return generateDepthwiseConv2D(cfg, *generator, data, size); default: WARNING("[Generator][DP] Unsupported operator."); return false; |