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

* 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

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

* 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

* Simplify the options of spawn based on fleetrun

* polish details

* polish doc details

Change-Id: Ia5279b0cbb6a5b3970aff66e9510e0d85efa70ce

* test=develop, add model_average and lookahead

* fix syncbn convet

* add unittest

* add dispenable input 'shape' for core.ops.reshape2

* add dispenable inputs for core.ops.reshape2/expand/slice

* add ut

* Polish and Optimize the print/repr message of all layer

* fix some code format

1. when slice_item is a slice: 
 1) the start of __getitem__ should be std::max(start, 0) if slice
 2) the start of __getitem__ should be std::min(end, dim) 
2. when slice_item is an integer, it should be in [-dim_len, dim_len) 
3. Fix error message to use accurate data

* add attribute for batch_norm

* fix beam search bug

* add dygraph unittest

* update dynamic_decode argument doc

* add warning info for state which has no lengths attribute

* Support storage of large parameters

* Reduce the complexity of the unittest

* Reduce the complexity of the unittest,commented out unittest for

* add unittest for static.save/load

* Increase the timeout threshold of 'test_static_save_load'

* Increase the timeout threshold of 'test_static_save_load'

* Increase the timeout threshold of 'test_static_save_load' and 'test_paddle_save_load'

* Increase the timeout threshold of 'test_static_save_load' and 'test_paddle_save_load'

* dot op support complex types

* matmul support complex types

* add test case

* matmul broadcast gradient support complex

* move conjFunctor to complex_functor.h

* update, test=develop

* add distributed.split, test=develop

* Add mkldnn nearest_interp and bilinear_interp op
* don't run mkldnn interpolate in default
* add interpolate_mkldnn_pass

* fix ut

Change-Id: I151e152919a1863db07792bffb42d0ca68995756

* rm check_import_scipy, rm chunk_eval and mean_iou in paddle.metric.__init__.py

* Revert "rm check_import_scipy, rm chunk_eval and mean_iou in paddle.metric.__init__.py"

This reverts commit 179ba8c2b22bc31fe8d8a126e31820792cbd0f4e.

* delete paddle.metric.chunk_eval and paddle.metric.mean_iou

* delete paddle.nn.clip and paddle.nn.clip_by_norm

* delete paddle.nn.functional.activation.hard_sigmoid and paddle.nn.functional.activation.hard_swish

* delete paddle.nn.Pool2D, paddle.nn.BilinearTensorProduct, paddle.nn.RowConv, paddle.nn.functional.row_conv

* fix extension import error

* fix unittest for row_conv and Pool2D

[Windows CI test] Enable unittest test_optimizer_in_control_flow and remove unnecessay code (#29851)