As the title

* disable ut test_tsm on windows

* fix error

* add ut execuate time

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

* 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()

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

1. Type of index: int, slice(step must be 1).

2. Type of value: 
 (1) int32, int64, float32, bool; 
 (2) numpy.array(int32, int64, float32, bool);<Note: float64 is not supported>
 (3) paddle.Tensor(int32, int64, float32, float64, bool);

[Dy2Stat] Fix bug for loop: a variable is used and created in loop, but used before created (#29769)

Support to transformfor ele in var stms in which var is a slice of Tensor.

Before this commit, test_slice use old api `dygraph_to_static_func` to use Dynamic-t-Static and use Executor explicitly，which is not recommended to users.
After fixed, use recommended API `paddle.jit.to_static` to replace `dygraph_to_static_func`, which won't trigger the random exception on coverage CI.

Unit test reported memory not enough on CPU machines. Reduce batch size again.

[Dy2Stat] 1. Fix bug of for-range stmts. 2. Support that step value is negative in for-range stmts (#29519)

1. Fix error in _build_cond_stmt of for-range stmts. 

2. Support that step value is negative in for-range stmts

3. Fix code because of the diff between Py2 and Py3

Fix 3 Windows Unittests

test_fuse_all_reduce_pass: Paddle cannot run multiple-GPU on Windows so set single visible GPU flag
test_feed_data_check_shape_type: Paddle cannot run multiple-GPU on Windows so set single visible GPU flag
test_tsm: Winodws GPU size is not enough so decrease batch size and data size.

* Fix a bug when running on an operating system without "bash."

* add execution condition

* for ci-coverage

* get cpu information to check the precision problem

* Update compilation environment for musl version

* update dependencies

* remove test code

check cpu info

remove test code

review

* update alpine and third_party denpendencies

* add newline for ci Code format

Reduce exception type so that if covert_to_static failed, it reports right error message.

[Dy2Stat] Fix bug: Do not use gast.Subscript to replace gast.Name in when transforming for_enumerate_loop (#29310)

[Dy2stat] Add a decorator paddle.jit.not_to_static to support that not to convert a function in Dynamic-to-Static. (#29253)

Usage scenarios：A function could have run successfully in static mode,  you can use it to decorate a function in the following cases:
  1. An unknown error occurs in the dynamic-to-static conversion process of the function;
  2. In the internal implementation of the function, it has two branches: dynamic branch and static branch;
  3. Users don't want to convert the function in the process of dynamic to static.

This PR fixes several problems in dy2stat for Deoldify model in PaddleGan.

In model, software engineer wrote if x.shape == y.shape, the Tenser shape is a tuple in dygraph so the == returns True/False, but in static graph the == becomes element-wise comparison, which is a different behavior. In this PR we reduce the element-wise comparison result.

If software engineer write computations which uses parameters in hooks, the static graph can loss the parameter variable because we put param_guard at forward of a Layer. In this PR we made param_guard cover pre-hook and post-hook.

In PaddleGan, software engineer calculated some parameter values in __init__ by running some dygraph code. Those code also run during dy2stat. So some variables may be assign as a VarBase (Tensor) first and then Variable, which raised an error. We fixed the bug in this PR by handling the case.

TODO: We just added testcase for the 1. shape comparison. Should add test case for 2. and 3. But since we are chasing 2.0RC, I will do it in the near future PR

test_mnist failed on CUDA11. We found that it is due to PaddleInference IR Optimization after debugging. We disable it in this PR and we will re-enable it after PaddleInference fixes it.

[Dy2Stat] Fix bug: the return statement should be transformed to an equivalent Paddle/Python if statement, which depends on if conditions of the return stmt. (#29165)

GridGenerator model failed because the output shape of `linspace` is (-1). The reason is that C++ InferShape fixes the shape to (-1): 

https://github.com/PaddlePaddle/Paddle/blob/5da3d514ebaa6fffd48c4a2e6bb5b16268dae92e/paddle/fluid/operators/linspace_op.cc#L49

We cannot set the shape in C++ infer shape because this Tensor may not be initialized during compile time, but when input `num` of `linspace` is an integer, we know the shape at compiler time. This PR simply set the shape in Python and add GridGenerator as unittest.
 

[Dynamic-to-Static] Support **kwargs as input of the function which is decorated by `jit.save.to_static` (#29098)

* split train_mode and has_grad

* fix format

* fix ci problems

* fix sample code

* Support pop for dict in dy2stat

* Move convert_pop to convert_operators.py and polish convert_pop

Add support for using tuple as tensor.shape (For example: a, b, c, d = x.shape)

* upgrade comment string to raw string

* fix string in

* fix string with ' '

* revert update on comments

* upgrade only necessary

* fix sample code checker

* fix comments with '''

[Dynamic-to-Static] Fix bug of convert_logical_and/convert_logical_or: the operands are executed sequentially(#28993)

  
  1) The operands are executed sequentially according to the running logic of Python.
  
  2) If the left hand operand is True(for convert_logical_or)/False(for convert_logical_and), the right hand operand should be executed.

The PR description is long. See details in the PR link.

* add lstm, simple rnn op kernel

* fix the test_lstm for the rnn op

* change func name

* fix forward postprocess bug

* add gru forward, backward code

* remove unittest.skipIf; use a big rnn op instead of combination op

* fix input doesn't have gradient bug

* add eigen lstm forward, backward
Co-authored-by: Nwawltor <fangzeyang0904@hotmail.com>

[Dynamic-to-Static] Fix bug in loop_transformer: loop vars should contain the var from ancestor-for-node (#28735)

* modfied the timeout value for 5 ut

* modified timeout value for test_resnet