[CodeStyle] use np.testing.assert_allclose instead of self.assertTrue(np.allclose(...)) (part 2) (#45213)

* autofix (get ci log)

* retrigger ci

* fix test_gather_nd_op, wrong expected in dygraph

* fix test_activation_op, unpack static graph result

* fix test_auc_op, unpack static graph result

* fix test_bce_loss, unpack static graph result

* fix test_bce_with_logits_loss, unpack static graph result

* fix test_cond, unpack static graph result

* fix test_dygraph_weight_norm, wrong numpy reference when `axis=None`

* fix test_einsum, wrong matmul inputs

* fix test_elementwise_heaviside_op, unpack static graph result

* fix test_frac_api, unpack static graph result

* skip test_group_norm_op_v2, probably the wrong numpy reference

* fix test_imperative_double_grad, wrong subscript

* skip test_imperative_tensor_clear_gradient, ???

* skip test_layer_norm_op, probably the wrong numpy reference

* fix test_math_op_patch, unpack static graph results

* fix test_masked_select_op, unpack static graph results

* fix test_mse_loss, unpack static graph results

* fix test_multi_label_soft_margin_loss, unpack static graph results

* fix test_multi_dot_op, unpack static graph results

* fix test_nll_loss, unpack static graph results

* fix test_normalization_wrapper, unpack static graph results

* fix test_pass_builder, unpack static graph results

* fix test_prelu_op, possibly an extra comma

* fix test_psroi_pool_op, unpack static graph results

* fix test_queue, unpack static graph results

* fix test_reorder_lod_tensor, compare an item with a list

* fix test_rrelu_op, unpack static graph results

* fix test_searchsorted_op, unpack static graph results

* fix test_sigmoid_focal_loss, unpack static graph results

* fix test_smooth_l1_loss, unpack static graph results

* fix test_soft_margin_loss, unpack static graph results

* fix test_softmax2d, unpack static graph results

* fix test_square_error_cost, unpack static graph results

* fix test_tril_indices_op, unpack static graph results

* fix test_unsqueeze_op, mismatch numpy reference (axis)

* skip test_layers, `static_rlt` is missing an axis

* fix test_mnist, unpack PredictorTools result (also a list)

* fix test_build_strategy, unpack PredictorTools result

* fix test_mobile_net, unpack PredictorTools result

* fix test_resnet_v2, unpack PredictorTools result

* revert some changes

revert test_layers

revert test_group_norm_op_v2

revert test_layer_norm_op

revert test_imperative_tensor_clear_gradient

* fix test_normal, use flatten instead of reshape, (PR-CI-Windows-OPENBLAS)

* empty commit, trigger CI

* fix_shape

* add clip_grad

* fix comments

* add unittest

* update logger

* [Eager] add get_tensor_from_selected_rows

* add PADDLE_ENFORCE to check SelectedRows

* use _ prefix in temp

* transfer trilinear op to phi, change name from trilinear_interp_v2 to trilinear_interp

* reserve linear_interp param

* change testcase scale if-branch

* testcase test_imperative_case

* fix trilinear testcase

* import paddle in test_trilinear_interp_v2

apply buffer_shared_inplace_pass and inplace_addto_op_pass pass to program in Standalone Executor (#45085)

* apply inplace addto in python apply_pass

* fix

* apply inplace pass for program

* skip feed and fetch var

* fix block_desc.move_from

* fix block desc

* alltoall remove inplace

* fix

* [OpAttr]Squeeze axes support Tensor

* add support_tensor

* fix unittest

* fix coverage

* transfer bilinear op to phi, change bname from bilinear_interp_v2 to bilinear_interp

* reserve linear_interp param

* fix cross device import

[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

* [Eager]Support Lazy initialization for nn.Lazyer

* 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

* 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

* 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 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>

* 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

* refactor fleet.

* refact fleet.py.

* update fleet/__init__.py.

* update fleet.py

* update code style.

* update fleet

* update fleet

* update fleet

* update fleet

* update model.py

* update fleet.

* update __init__.py

* update fleet.

* update fleet.

* update fleet

* update fleet

* update fleet

* update fleet.

* update optimizer.py

* update optimizer

* update fleet.py

* update scaler.py

* update setup.py.in