Add CudaSlice<f32> accessor methods to GpuTrainResult and GradientResult
(loss_cuda_slice, grad_norm_cuda_slice) in ml-dqn, eliminating redundant
tensor_to_cuda_slice_f32 calls at every training guard check site.
- GpuTrainResult: add from_fused_scalars() constructor and CudaSlice extractors
- GradientResult: add CudaSlice extractors that delegate to GpuTrainResult
- fused_training.rs: use from_fused_scalars() instead of Tensor::new() wrapping
- train_step.rs: use result.loss_cuda_slice() instead of tensor_to_cuda_slice_f32
- training_loop.rs: same CudaSlice accessor pattern for both fused and accum paths
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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