* use wget to replace curl to download the lcov file

* add cache for lcov

Add clone method for static Variable so that this interface will be same as dygraph. It fixed some bugs in dy2stat

 add the op error message for the matmul xpu 

* delete paddle.nn.functional.assign

* fix dynamic to static error

* fix warning and no grad

* optimize softmax forward

reduce the  occupied size  of memory for the fused pattern of elementwise_add Op and activation Op(relu Op for example) (#29885)

* add view strategy on squeeze,unsqueeze,reshape,flatten

* add squeeze unittest

* add unittests

* use View strategy as name rather than Reuse Allacation

* fix view api doc

* fix format

* use core.ops when input of reshape2 is Tensor

* fix test_cross_entropy_loss error because of reshape2

* delete selected_rows

* change op_function

* little change

* solve HandleViewBetweenInputAndOutput

* - Added UT for testing elementwise_mul caching

* lint fixes

* add cast ops before and after unsupported fp16 ops.

* Keep partial net in FP32 pattern.

* Support check_finite_and_unscale and update_loss_scaling for FP16 calculation mode.

* Add fp16 support for adam op.

* add multi precision attr for adam.

* Fix the bug of test_multi_precision_fp16_train UT.

* Code format for CI.

* Fix the redefine error about MPTypeTrait on windows.

* fix bugs of the _create_accumulators func in Momentum.

* fix bug when inserting post cast op.

* Add the update_loss_scaling op in allow_set of UnusedVarCheck.

* Update for ci coverage.

* Add some doc for OptimizerWithMixedPrecision.

* Fix the code style.

* Imporve the doc of `amp_init`.

* Change for fp16 testing if users have the infer program defined in separate way.

* fix dtype of ungenerated grad var

* update ut

* refine code

* set default dtype

* fix could_use_cudnn bug

* remove debug code

* re-implement

* fix bug

* fix tensor shape bug

* fix op_num

* clean code

In creation.assgin, reuse implamention code of layers.tensor.assign to avoid maintain two code (#30227)

1. When x is Variable, call nn.shape(x) only in following cases:
 1）The shape of x is used in control flow condition.
 2）The dim to be used is negetive
2. When x is Variable, but x.shape or x.shape[idx] doesn't contain negetive value, don't convert to paddle.shape()

* change to tensor copy sync

* change to tensor copy sync

* make copy_to safe when use TensorCopy

* refine code

* add ut

* add cudapinned garbagecollector

* add testcase: cpu place -> cuda pinned place

In control flow, don't copy TensorArray from subblock to parent block when TensorArray is created in parent block.

* add tensor table

* Quantization supports 2.0 APIs

* Fix the error of save_quantized_model

* Add a necessary condition

* Remove test for white list and add header

* enhance error message of nll_loss op test=develop

Improve some error messages in parallel_executor.cc, conditional_block_op.cc, recurrent_op.cc

* simplify prepared op impl to improve performance

* fix kunlun compile error

* continue fix kunlun compile error

* only transform diff place when dtype diff

* fix failed unittests

* remove useless file

* polish impl by review comment

* test=develop, add index_select_cuda kernel