* add inplace_map for trace_op in pybind

* fix inplace problem of setitem

* refactor the param format  of trace_op
Co-authored-by: Npangyoki <pangyoki@126.com>

* update seqconv_eltadd_relu_fuse_pass ut

* update ut

* update ut

* update ut

* update squared_mat_sub_fuse_pass ut

* update ut

* update ut

* rename cuda to gpu

* revert CMake change

* resolve conflit

* rename other cuda to gpu

* poish details

* relu forward opt

* add gelu functor

* optimize code

* add seqpool_cvm_concat_fuse_pass ut

* rename ut name

* fix when out_dtype is same with x.dtype and still transform type error

* fix spell error

* mean first version

* fix scalar mean

* add fp16 dtype for api

* fix timeout bug

* update

* update repeated_fc_relu_fuse_pass ut

* update ut

* update

* fix bugs

* modify code style

* fix bugs of _get_global_group

* add timeout

* add timeout

* PassAutoScan base_line use same config

* try run base_line

* fix dropout Mask of output attr error

* fix dropout Mask of output attr error

* updates the check_file_diff_approvals for allocation refactor, test=develop

* fix a bug, test=develop

* remove eigen and blas dir

* fix declare error

* add mkldnn conv_transpose_bias fuse pass ut

* update conv_transpose_bias_mkldnn_fuse_pass ut

* update conv_transpose_bias_mkldnn_fuse_pass ut

* update conv_transpose_bias_mkldnn_fuse_pass ut

* restrict conv2d data_format in conv_transpose_bias_mkldnn_fuse_pass

* update ut timeout setting

* update ut

* add pten conj kernel

* modify conj_kernel file path

* add defined cuda macro to cuda/conj_kernel.h

* support FP16 for more ops

* add amp list tests

* refine reduce_mean_grad

* fix OP benchmark ci

* fix fp16 reduce_mean

* updat ut, but still have some problems

* remove mean/reduce_mean fp16 kernel

softmax_with_cross_entropy optimization with soft label. This PR includes optimization of
    "SoftmaxWithCrossEntropySoftLabel" : compute log_softmax and then compute loss.
    "CrossEntropySoftLabel" : compute loss with softmax as input.
These optimization includes following technics:
    read data to buffer with vectorization
    compute max and sum in warp
    fixed loop size with macro
Performance (computation time):
    softmax_with_cross_entropy_0 (forward) : -40.1%
    softmax_with_cross_entropy_0 (backward): -41%

* add matmul_scale matmul_v2_scale fuse pass

* add scaletensor judge

* modify var name

* add timeout notest;test=coverag

* fix error commit

* fix use_mkldnn attr

* fix use_mkldnn attr

* test if windows still need numpy <=1.19

* modify acoording to zhouwei's comment

* add multi_tensor for momentum and clear_grads for optimizer

* fix bug for dygraph

* add unittest

* refine comment

* add param_group

* refine regularizaiton logic

* del clear_grads

* add clear_grads

* add dispensable check of None

* refine clear_grad

* fix build bug

* refine code by comment

* refine code

* add multi tensor check

* refine param_group update

* add multi tensor for static mode

* refine comments

* delete useless comma for momentum

* refine comment for momentum

* refine code by commment

* fix bugs when run reshape

* fix ci bug