* support setting linewith when printing tensor

* fix ut

* refine code

* update comments

* use small precision since windows/linux has different ramdom value

* fix typo

* adjust parameter order for consistency

* Support getitem by Bool index

* delete some debug info of bool index

* support the case that the shape of bool index is different from indexed tensor

* Support getitem by ellipsis index in dynamic mode

* change some code style

* Support getitem by none index in dynamic mode

* modify a comments style and remove useless code

* Support getitem by ellipsis index in dynamic mode

* change some code style

* in NPU environment, use CPUPlace for missing operators.

* in NPU environment, use CPUPlace for missing operators.

* fix TensorCopy bug and add unit test.

* fix code style.

* add more unit tests.

* del py2 code2

* fix test timeout

* fix stop_gradient in paddle.to_tensor

* make to_tensor copy if data is varbase

* add ut

* refine sample code

* Modified the return value of tensor.grad from numpy as tensor.

* Modify unittests.

* fixed bugs.

* Add warning info for x.grad

* fixed unittests which used x.grad

* fixed bug.

* polish printing dtype

* fix special case

* 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

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

* support deepcopy for Layer/Tensor/Paramerbase

* fix some code

* rm complexvariable

* modify test_var_base unittest

* remove duplicated codes

[inplace] Add ShareHolderWith for class Variable and SharePlaceholderWith in VarBase.detach() to share the same Tensor/SelectedRows (#29267)

* The leaf tensor concept is exposed and the gradient accumulation of leaf tensor

* The leaf tensor concept is exposed and the gradient accumulation of leaf tensor

* fix coverage

* fix api doc

* fix CI unittest

* fix CI unittest

* fix unitest

* empty tensor does’t need inner_var_

* fix some error message

* Add a class TensorInplaceVersion to count the inplace version and put it in framework::Tensor instead of Allocation or Variable.

* Add a new attribute `_inplace_version` for VarBase.

* Raise exception if an inplace operation can result in incorrect gradient computation.

* Add a new interface _bump_inplace_version() for VarBase to bump the version whenever the Tensor is modified through an inplace operation.

* For api assign, call _bump_inplace_version() when it's an inplace operation inn dynamic mode.

* Use original var_wrapper if the inplace_version is not changed.

* Replace SnapshotVarWrapperList with SnapshotVarWrapper to optimize performane.

* fix tensor detach to zero copy

* fix tensor detach to zero copy

* update version pybind to v2.4.3, test=develop

* update unittests, test=develop

* refine format

* update doc

* handle uninitialized tensor

* add ut

* rename manual_seed to seed

* rename xxx1d-->xxx1D, xxx2d-->xxx2D, xxx3d-->xxx3D

* rename manual_seed --> seed

* do not rename .cc, .cu and .h file

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* disable_static on doc example code

* donot change manual_seed on generator

* add enable_static on sample code

* convert python/paddle/fluid/layers/nn.py to bak

* fix typo

* fix code style

* fix seed to manual_seed when call functions of Generator()

* fix bug

* add tensor clone

* fix unittest test_var_base

* add sumary feature

* refine printting tensor

* add sci_mode

* add sample code

* fix indent error

* fix _format_item

* polish code

* support item indent

* add ut

* set place for ut

* fix py2 issue

* fix ut

* Support assignment to a Variable in dynamic mode. Note: not deal with backward.

* Rewrite VarBase __setitem__ for high-performance.

* try to test 3 means to do __setitem__ and test the performance of 3 means.

* Retain the means of the highest performance: C++ code and don't trace op.

* set_default_type only take effect on python floats or complex

* fix doc