* support mobilenet for kunlun (#29458)

* add xpu ops for training transformer in kunlun (#29539)

* 1.fix matmul bug 2. add one hot

* add xpu error msg
Co-authored-by: Nprocr <procrboo@gmail.com>
Co-authored-by: Ntaixiurong <taixiurong@126.com>

register the op version for some ops

* add multitask

* add multitask, test=develop

* fix code style, test=develop

* add partail push dense, test=develop

* fix has_kay in py3, test=develop

* fix, test=develop

* fix, test=develop

* fix, test=develop

test=develop

* use iwyu clean include, test=develop, test=win

* compilation error, test=develop

* fix compilation error2, test=develop

* fix compilation error3, test=develop

* fix compilation error4, test=develop

* fix compilation error5, test=develop

* fix compilation error6, test=develop

* fix compilation error7, test=develop

* fix compilation error8, test=develop

* fix compilation error8, test=develop

* fix compilation error10, test=develop

* fix compilation error11, test=develop

 fix the CudaPinMemory bug for the equal op and add the test case for the equal op

add broadcast feature for elementwise logical op

Update the code for the compare ops for the broadcast function

Update the code for the compare_ops, update the api and doc 

* fix doc of logical_* op.

* fix doc of op pow.

* fix comment syntax error9D

* fix operator reciprocal demo.

* fix logical_* ops' doc. test=develop,test=document_fix

* bug fix. test=develop,test=document_fix

* bug fix. test=develop,test=document_fix

* bug fix. test=develop,test=document_fix

* bug fix. test=develop,test=document_fix

* polish reader error message, test=develop

* fix detail error, test=develop

* reset activation dcudnn change, test=develop

test=develop

* add new macro BOOST_GET_SAFELY & unittests, test=develop

* add different macro type, test=develop

* fix get macro type in executor, test=develop

* four macro part change backup

* using one macro for all case, test=develop

* revert attribute change, test=develop

* change to three func to solve gcc4.8 bug, test=develop

* polish some details, test=develop

* save InferVarType changes, test=develop

* remove code comments, test=develop

* tweak code, test=develop

* fix compilation warning, update merge_ids_op split_ids_op to new interface, test=develop

* modify fused_bn_activation_op, test=develop

* fix error of fused_bn_activation_op, test=develop

* fix PADDLE_ENFORCE and unittest coverage issue, test=develop

* tweak PADDLE_ENFORCE messages, test=develop

* improve unittest coverage, test=develop

* add StaticGraphInferVarType class, test=develop

* rebase develop branch, test=develop

* fix unittest error, test=develop

* remove comments, test=develop

* improve unittest coverage, test=develop

* imporve error message and imporve unittest coverage, test=develop

* upgrade InferVarType API, test=develop

* tweak pyfunc error message, test=develop

* fix compilation conflict - save_combine_op, test=develop

* Support LoDTEnsorArray in fetch op

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

test=develop

As the title

As the title.

* optimize compare and logical ops error info
* add out and cond dtype test

* solve the conflict of ops with the same name. test=develop

API/OP (ConditionalBlock) error message enhancement (#23480)

* OP (recurrent) error message enhancement

This reverts commit abe3e690.
test=develop

* delete invalid check inferface Ref & VectorRef, test=develop

* fix vector ref delete error, test=develop

* try the new check inferface, test=develop

* change all related code with new check macro, test=develop

* remove static assert, test=develop

* polish detail, test=develop

* skip coverage problem, test=develop

* add new check macro, test=develop

* solve the conflict of ops with the same name. test=develop

* update linspace, equal operators to API 2.0, test=develop

* equal support higher performance CUDA kernel, test=develop

* update comment of equal&linspace operator, test=develop

* update comment of equal&linspace operator, test=develop

* refine the error message of tensor_array_read_write Op

* refine grad maker, test=develop

* refactor tracer stage 1, test=develop

* merge develop to solve conflict third times, test=develop

* Add support for dynamic_decode(while) training. test=develop

* Fix assign_op and tensor_array_read_write_op after solving conflict. test=develop

* Fix test_rnn_decode_api.py. test=develop

* Refine docs for apis in rnn.py. test=develop

* Adjust outputs of dynamic_decode. test=develop

* Remove the force_cpu update in assign_op. test=develop

* Remove the force_cpu update in assign_op. test=develop

* Make RNNCell.get_initial_states support batch_dim_idx argument. test=develop

* Rename _create_array_outof_while as _create_array_out_of_while in rnn.py.
test=develop

1. Make while_op accept GPU conditional data
2. Add more complex test cases for while_loop API

* polish infer shape registry, test=develop

* modify some operators registry, test=develop

Add tests to use dy/dx to make sure the gradient values calculated by the control flow backward is correct. Also fixed bugs detected by those tests.

Fix bugs:

1. Unlike sum_op, optimizer ops don't allow uninitialized input tensor. But in conditional_block_grad_op, since the conditional_block may not run, the output gradient tensor may be uninitialized, which will cause the optimizer op error. To fix it, we should let optimizer ops support uninitialized input like sum_op or assign the uninitialized gradient to 0 when the conditional_block_grad_op doesn't run. I found there are about 10+ optimizer ops. **To be simpler, I just assign output gradient of the conditional_block_grad_op to 0 in this PR**. But it can be further explored whether we can make optimizer ops like sum_op to support uninitialized input tensor because theoretically we can speed up without the assigning in conditional_block_grad_op.

2. Infer parameter shapes during append_backward. I didn't know that all our parameters are in global block. When op_desc is inferring shapes at the sub-block, it may not know the shape of gradients of parameters whose shape information is at global block. I fixed it by inferring shapes of gradients from forward var.

This PR also did some code clean up:
1. Print the var name when sgd_op catches shape error so that it is easier to debug
2. Fix a typo: dicta -> dict