[CK_BUILDER] Integrate CKB validation with CK verification (#3649)

* ck-builder: tensor copy function

This function copies one tensor to another, so that the memory
layout can be changed between them.

* ck-builder: fix ck::bhalf literals

These types don't work properly.

* ck-builder: abstract compare_elements in gpu_verification.hpp and make builder use it

This reduces the amount of duplicated code a bit.

* ck-builder: add flat tensor iterator

This "iterator" type pretends to be a pointer, useful for passing
tensors to functions expecting pointer-like types.

* ck-builder: integrate validation with ck gpu verification

By templating the gpu_verify function over iterators, we can use
the new FlatTensorIterator to adapt the function to multi-
dimensional tensors without changing either implementation
too much.

* ck-builder: add check_by_accumulations

This changes the gpu_verification.hpp code to also accept "iterator"
types for the relevant gpu_verify and gpu_reduce_max functions.

* ck: fix test_gpu_verification GenerateRandomData for bhalf

is_integer_it<bhalf_t> yields true, but it is not actually
an integer.

* ck: make gpu_verification kernels be proper persistent kernels

Previously these were using a hardcoded value for the grid size. This
commit changes that so that the grid size is automatically derived
from the kernel's occupancy and the number of multiprocessors on
the GPU.

* ck: clean up gpu_verification.hpp using block_reduce

This implements a small generic block reduce function, and rewrites
the rest of gpu_verification.hpp using that function to clean it up
a bit.

* ck-builder: doc typos

* ck-builder: update testing readme with validation interface.

* ck-builder: rebase fixes + review comments

* ck-builder: fix device integer generation with float types

Passing bfloat here causes a nans due to type_convert performing
a bitcast.

* ck: another bhalf_t bug

CK expects that int-generation with ck::bhalf_t yields bhalf integers,
not unsigned integers. This makes the logic of FillUniformRandInteger
compatible with GeneratorTensor_2<InDataType>, however idiotic that
may be.