ggml/examples: add backend support for numerical optimization (#949)

ggml/examples: add backend support for numerical optimization (#949)

* CUDA eval works

* stochastic gradient descent op

* Adam except decay

* CUDA CROSS_ENTROPY_LOSS_BACK

* CUDA mnist-fc training works

* backend CLI arg

* refactor gguf load

* remove sched from opt_step_adam

* implement l1 regularization (weight decay)

* extra call to add optimizer

* initialize gradients with ggml_graph_reset

* gradient accumulation

* increment iter per eval instead of epoch

* adjust backend interfaces

* fix ggml_graph_reset without backend

* fix ggml graph export/import

* fixup

* rename

* revert ggml_opt changes

* more general CUDA repeat_back

* update documentation, fix CNN

* validation split

* add clarifying comment

* optimize PyTorch training

* adjust buffer size, thread count

* fix 0.0f validation split

* Update examples/mnist/mnist-common.cpp

Co-authored-by: Georgi Gerganov <redacted>
* fix gradient accumulation

* tensor flag for accumulators -> tensor hash set

* Update include/ggml.h

Co-authored-by: slaren <redacted>
* Update tests/test-backend-ops.cpp

Co-authored-by: slaren <redacted>
* Update tests/test-backend-ops.cpp

Co-authored-by: slaren <redacted>
* fix test prints

* Update src/ggml-backend.c

Co-authored-by: Georgi Gerganov <redacted>
* better CUDA support for noncontiguous out_prod

* add comment

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Co-authored-by: Georgi Gerganov <redacted>
Co-authored-by: slaren <redacted>