Enhance batch_norm_op: support 2d and 5d data and unbiased variance estimation

[zhouxiao-coder]

Solve #5811

As part of the job of another PR #5686 , I separate the code that related to batch_norm_op enhancement as a standalone PR for better code review.

This PR does several modifications to the original batch_norm_op implementation.

• Extract normalization logic to a common header file, check issue Implement normalization methods(BatchNorm/LayerNorm/BatchRenorm) as functions in a common header file #5685 for disscussion.

• Fix assertion logic. Some outputs should appear only in training mode.

• Support unbiased variance estimation, i.e. the bessel's correction.

• Support 2D tensor (tensor_format="NC") and 5D tensor (tensor_format="NCDHW" or "NDHWC") in CPU

• Support 2D tensor (tensor_format="NC") and 5D tensor (tensor_format="NCDHW" or "NDHWC") in GPU.

• Operator unit test. See issue Support "In place" computation in operator unit test #5842 .

2D tensor is not supported by cudnn batch norm implementation, so changes need to be made to the GPU code.

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