* add multinomial cpu kernel

* fix C++ notype error

* fix windows ci array len error

* let array len be const

* change array to vector

* add cuda kernrl with num_distribution is 1, and not support replacement=False

* add multinomial python api

* support num_distribution different multinomial distributions

* add categorical class

* fix test_distribution enable_static error

* add unittest for different setting of Categorical

* optimize format

* little change

* little change

* add raise error if shape not match, optimize format

* fix windows CI dtype error in concat

* little changes

* little changes2

* change values type to int64

* change values type to int64

* change values type to int64

* Add test_resnet_v2.py test=develop

* refine grid_sample and temporal_shift

* fleet support non_distributed training in dygraph mode; test=develop

* add xpu test

* notest;add kunlun_test

* notest;add kunlun_test

* notest;test=kunlun

* notest;test=kunlun

* notest;test=kunlun

* notest;test=kunlun

* test=kunlun

* update 2.0 API for dice_loss and log_loss test=document_fix

* fix test_se_resnet unittest

* fix test_se_resnet unittest

* add comments for decresing test_se_resnet precision

* fix the scatternd/scatterndadd

* fix the doc of scatter

* replace rank with ndim

As the title

* migrate code example and doc

* add multinomial cpu kernel

* fix C++ notype error

* fix windows ci array len error

* let array len be const

* change array to vector

* add cuda kernrl with num_distribution is 1, and not support replacement=False

* add multinomial python api

* support num_distribution different multinomial distributions

* add multinomial python api unittest

* change output dtype to int64

* fix coverage prob

* optimize format

* fix dtype of output error, should be int64_t

* increase tolerance

* increase the difference between low and high

* change tolerance of Normal log_prob method

* change probs tolerance to 1e-4

* change tolerance of Normal kl method

* test=develop, optimize geo communicator 

* remove data parallel scale loss & apply collective_grads

* move apply in minimize

* fix failed unittests

* polish Program api doc & example

* polish CompiledProgram api doc & example

* polish ParallelEnv api doc & examples

* polish details, test=document_fix

* polish program doc details, test=document_fix

* polish details, test=document_fix

* fix note format error, test=document_fix

* add lost example, test=document_fix

* fix lost example, test=document_fix

Refine Dy2stat APIs to 2.0rc

After discussion, we accepted 3 key points from reviewers:

1. In 2.0rc we changed dygraph_to_static folder to dy2static
2. Keep the three files: convert_call_func.py, convert_operators.py, variable_trans_func.py
3. Remove convert_operators path when users import convert_xxx. 

After this PR, users can import convert_xxx APIs by:

`import paddle.jit.dy2static.convert_xxx`

The file structure will be:

```
jit
    dy2static
          convert_operators.py
          convert_func_call.py
          variable_trans_func.py
```

Detail changed API in files:

In python/paddle/jit/dygraph_to_static/convert_call_func.py:
from ...fluid.dygraph.dygraph_to_static.convert_call_func import convert_call  #DEFINE_ALIAS

In python/paddle/jit/dygraph_to_static/convert_operators.py:
from ...fluid.dygraph.dygraph_to_static.convert_operators import cast_bool_if_necessary  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_assert  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_ifelse  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_len  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_logical_and  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_logical_not  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_logical_or  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_print  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_var_dtype  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_var_shape  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.convert_operators import convert_while_loop  #DEFINE_ALIAS

In python/paddle/jit/dygraph_to_static/variable_trans_func.py:
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import create_fill_constant_node  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import create_static_variable_gast_node  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import data_layer_not_check  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import to_static_variable  #DEFINE_ALIAS
from ...fluid.dygraph.dygraph_to_static.variable_trans_func import to_static_variable_gast_node  #DEFINE_ALIAS

* add paddle.enable_static() to some testcase

* add seed to random in test_activation_op

* update a randomseed

* update a randomseed

This PR fixed two bugs when converting LSTM in dy2stat:

is_unsupported has a condition can trigger Python syntax error
LSTM API's implementation in _rnn_static_graph doesn't include parameter initialization, which can cause dy2stat error.

* add gloo initializer, test=develop

We decreased the batch size on CPU so that it can run correctly on Win/Mac machine, this may cause the delta to be larger. So I set larger delta value.

* fix is_empty api and code example; test=develop

* add transformer generate square subsequent mask api

* add dtype for input, update doc, use -np.inf

* add dtype for input, update doc, use -np.inf

* Add support for mkldnn ops types selection with FLAGS in dygraph

* use regex to match DNNL verbose

* python3 encoding fix

* set default value to strategy in distributed_optimizer test=develop