* add two attributes for yolo box

* Create squeeze2.pbtxt

* Create unsqueeze2.pbtxt

* Update unsqueeze2.pbtxt

* Update squeeze2.pbtxt

* add transpose transpose opdef, test=develop

* add line, test=develop

* add pool2d and reshape2 pbtxt

* add pool2d and reshape2 pbtxt, test=develop

* delete reshape2.txt, test=develop

* add lines, test=develop

* replace 'InnerSetOverridedStopGradient' with 'SetOverridedStopGradient'.

* improve coverage.

* polish error message.

* add dynamic layer_norm plugin

* fix bug

* fix numpy.allclose

* fix format

* fix code style

* remove shepe in dynamic shape

* code format

* remove layer norm fp16

* fix format

* Fix two english api documents, transpose and strided_slice

* OP:strided_slice_op supports bool type inputs

* add op_def for gru, lstm and layer_norm

* fix no newline flag

* Add the op def for elementwise_div elementwise_pow elementwise_sub fake_quantize_dequantize_moving_average_abs_max reduce_mean sqrt test=develop

* remove .ipynb_checkpoints for opdef

* remove fake_quantize_dequantize_moving_average_abs_max for opdef

* fix c_split bug

* fix utest

* add c_embedding for tensorparallel

This reverts commit 7be6191b.

* fix inference prepare data bug

* rename functions

* typo

* typo

* typo

* UT correct

* correct condition

* correct condition

* ci coverage

* morelines

* fix ci coverage

This PR made these changes to support double grad:

1. Translate `paddle.grad` to `paddle.static.gradients` to support double grad for dy2stat.
2. Fix IfElseTransformer bug which may not change value if "Store before Load" variable is in "Store" statement is in IfElse conditional statement
3. Add `DOut` to support double grad variables in `run_program_op`
4. Add support for renaming for double grads for `jit.save/load`

* add seq_conv pbtxt

* add seq_conv pbtxt

* replace and remove complex64/128 types in custom OP and other files

* fix custom_tensor_test fail bug

* fix custom_conj_test fail bug

* fix dispatch_test_op build fail bug

* enhance error message for conv

* fix ci coverage

* improve group norm cpu precision and performance

* add unit test to group norm

* modify to complex template types for fill_constant op

* modify to complex template types for py_layer, strided_slice and reduce_sum_op.part

* run pre-commit

* use HOST or DEVICE instead of HOSTDEVICE in implementation of lgamma op

* add test for fp32

* add lgamma to op_threshold_white_list

* add cuda kernel for lgamma kernel

* modify numeric grad delta

* fix small English issue

* change LaunchElementwiseCudaKernel to LaunchSameDimsElementwiseCudaKernel