Function kern_default

dnn/src/fallback/conv_bias/algos.cpp:60–120

}

void kern_default(const ConvBiasImpl::NCBKernParam& p) {
    dt_byte* workspace_ptr = static_cast<dt_byte*>(p.workspace_ptr);

    auto filter_meta_ptr =
            reinterpret_cast<const ConvBiasForward::CanonizedFilterMeta*>(
                    &p.filter_meta);
    auto filter_meta = *filter_meta_ptr;
    auto layouts = get_layouts(p);

    TensorND src{
            reinterpret_cast<dt_byte*>(const_cast<void*>(p.src_ptr.get_ptr())),
            layouts[0]};
    TensorND filter{const_cast<void*>(p.filter_ptr.get_ptr()), layouts[1]};
    auto bias_ptr = reinterpret_cast<dt_byte*>(const_cast<void*>(p.bias_ptr.get_ptr()));
    TensorND bias{bias_ptr, layouts[2]};
    TensorND dst{
            reinterpret_cast<dt_byte*>(const_cast<void*>(p.dst_ptr.get_ptr())),
            layouts[3]};

    auto sfb = dst;
    if (bias.layout.dtype.enumv() != dst.layout.dtype.enumv()) {
        // intermediate result
        sfb = TensorND{workspace_ptr, TensorLayout{dst.layout, bias.layout.dtype}};
    }
#define DISPATCH_RAW(in_dt, bias_dt, out_dt, cmode, func)                       \
    else if (                                                                   \
            src.layout.dtype.enumv() == DTypeTrait<dtype::in_dt>::enumv &&      \
            filter.layout.dtype.enumv() == DTypeTrait<dtype::in_dt>::enumv &&   \
            (!bias.layout.dtype.valid() ||                                      \
             bias.layout.dtype.enumv() == DTypeTrait<dtype::bias_dt>::enumv) && \
            sfb.layout.dtype.enumv() == DTypeTrait<dtype::out_dt>::enumv &&     \
            p.compute_mode == param::ConvBias::ComputeMode::cmode) {            \
        func(src, filter, bias, sfb, workspace_ptr, filter_meta);               \
    }
#define DISPATCH(in_dt, out_dt)                                                       \
    DISPATCH_RAW(                                                                     \
            in_dt, out_dt, out_dt, DEFAULT,                                           \
            (megdnn::naive::convolution::forward_bias<                                \
                    DTypeTrait<dtype::in_dt>::ctype, DTypeTrait<dtype::in_dt>::ctype, \
                    DTypeTrait<dtype::out_dt>::ctype,                                 \
                    DTypeTrait<dtype::out_dt>::ctype>))
    if (0) {
    }
    DISPATCH(Float32, Float32)
    DISPATCH(Int8, Int16)
    DISPATCH(Int8, Int32)
    DISPATCH(QuantizedS8, QuantizedS32)
    DISPATCH(Quantized8Asymm, QuantizedS32)
#if !MEGDNN_DISABLE_FLOAT16
    DISPATCH(Float16, Float16)
    DISPATCH_RAW(
            Float16, Float16, Float16, FLOAT32,
            (megdnn::naive::convolution::forward_bias<
                    dt_float16, dt_float16, dt_float16, dt_float32>))
#endif
    else {
        megdnn_throw(ssprintf(
                "unsupported naive ConvBias(%s, %s, %s) -> %s", src.layout.dtype.name(),