* CUDA: fix build error from ambiguous __half conversions in conv2d
Building conv2d with half precision failed because `__half` defines
multiple implicit conversion operators (to float, int, short, etc.),
causing ambiguous overload resolution when multiplying with float.
Introduce a templated `to_float` helper that explicitly converts
`__half` via `__half2float`, while passing through float unchanged.
Use this helper in conv2d accumulation to ensure unambiguous and
correct promotion to float.
Fixes some build errors with half-precision kernels on CUDA.
ggml-ci
* CUDA: Replace custom to_float helper with unified ggml_cuda_cast and add half‑>float conversion
* CUDA: Add missing convert.cuh header
* CUDA: remove unnecessary extension in ggml_cuda_cast
* CUDA: Address review comment, remove second type template argument
#include "conv2d.cuh"
+#include "convert.cuh"
struct conv_params {
const int64_t IW, IH;
const int64_t in_x = calculate_input_coord(out_x, kx, P.ST_X, P.DL_X, P.PD_X);
const float input_val = input[Layout::input_index(n, c_in, in_y, in_x, P)];
- const float kernel_val = kernel[Layout::kernel_index(c_out, c_in, ky, kx, P)];
- acc += (input_val * kernel_val);
+ const T kernel_val = kernel[Layout::kernel_index(c_out, c_in, ky, kx, P)];
+ acc += (input_val * ggml_cuda_cast<float>(kernel_val));
}
}
}