[CodeStyle][NPU] use np.testing.assert_allclose instead of self.assertTrue(np.allclose(...)) (part 1) (#44988)

* autofix

* try resolve precision issues

* revert some changes

* clean some `err_msg`

* 0.0001 -> 1e-4

* update commented assert code

* try to fix some shape errors

* `numpy` -> `np`

* empty commit, trigger kunlun ci, test=kunlun

* empty commit, retrigger kunlun ci, test=kunlun

* empty commit, trigger kunlun ci, try fix npu memcpy_h2d, test=kunlun

* try fix npu import error, test=kunlun

* [OpAttr]Add SupportTensor for OpMaker

* fix typo

* fix code style

* add SupportTensor for concat op

* add unittest for register Tensor

* add shape checker and split attribute

* fix multi stream error.

* [Eager]Support Lazy initialization for nn.Lazyer

* use addKernel

* fix compile

* remove elementwiseAddto

* add return

* fix custom place

* fix_stop_gradient

* xpu unittest grad compute supports more types, *test=kunlun

* add instance norm xpu, *test=kunlun

* transfer bicubic_interp op to phi, change name from bicubic_interp_v2 to bicubic_interp

* test final_state_bicubic_interp api

* testcase match imperative case

* fix squared_l2_norm bug

* update buffer.h

* move check finite and unscale kernel into phi

* move infershape into phi

* move update_loss_scaling kernel into phi

* remove original kernels

* move update loss scaling infershape into phi

* add header for xpu and npu

* solve coverage failed

* fix npu test failed

* remove mutable data in cu file

* fix new executor failed

* add valid check for meta tensor output

* initial commit

* fix op maker bug

* fix mul grad bug

* add unittest

* fix add grad bug, add cpu kernel

* add paddle.geometric.message_passing

* add paddle.geometric.send_uv api, add unittest

* add fp16 judgement

* fix file typo, move compute_type to message_op

* add impl file

* fix unittest timeout time

* add review revise

* update reshard cost and cost estimator

* add unittest

* add dropout cost

* fix import error

* fix reshard code style error

* improve unittest coverage

* [Eager draft] forward_only interface migrate to autograd_api

* strings api add dygraph forward function

* rm useless comments

* draft version for check CI

* fix ci

* forward-only no need compute_require_grad and pass stop_gradient, rm useless comments

* polish yaml and using CPUPlace = phi::CPUPlace

* rm useless comments

* polish yaml and update some test case

* rm useless funcs

* polish eager_gen code

* polish code

* convert multihead to oss

* fix:bug

* fix:delete const cast

* fix:don't support bias_qk

* add vit pass

* fix:convert bug and add preln_residual_bias

* support length=-1

* add UT for convert

* add no_bias_qk support for gpu_multihead_op

* delete infer_shape depends on bias_qk

* oss just can be used in T4 and A*

* fix:change api for ROCM CI

* fix_shape

* code style

* fix assert

* fix to_tensor badreturn

* fix the api for the add

* update the document for the api add

* update add docs; test=document_fix
Co-authored-by: NLigoml <39876205+Ligoml@users.noreply.github.com>

* Add CI for assert-allclose.

* Update CI script.

* Update check_approval.

* Specify the destination path for the git diff.

* Add test samples.

* Add CI for assert-allclose with \n.

* Update test samples.

* Update ALL_ADDED_LINES_IN_TARGET_PATH.

* update GitHub username to userid, test=document_fix

* add rfc as a specification, test=document_fix

* try to integrate single and multiple rows together, test=document_fix

* remove duplicate dirs, test=document_fix

* add anchor `#background`, test=document_fix

* remove original scripts, test=document_fix

* remove test files, test=document_fix
Co-authored-by: NSigureMo <sigure.qaq@gmail.com>

* reconstruct_of_fleet_api

* update

* prune d2h memcpy for fp16 pass

* add select_p

* fix bugs

* add custom test for select_p; modify select_p primrules

* modify according to xiaoxu's comment

* add eq_p, select_p, pow_p, use autograd to test grad of high order

* add requirement of autograd, modify expected type of eq

* modify according to xiaoxu's comment

* import primops to use primops.pow