* update slice plugin

* add test

* fix code style

* fix trt6

* update test

* fix test

* add timeout

* update trt version

* update cmake

* can pass the fake test

* add files

* modify cmake to pass windows-ci

* for ci pass

* WITH_GLOO=ON

* for pass coverage test

* add cpuonly testcase

* add

* disable nccl when compile with cuda

* change python version in cpuonly

* add backend argument

* add required gpu

* add required:gpu

* fix scatter_add_nd and gather bug

* fix gather compile error

* add fleet api for program pass

* turn on apply pass for CI test

* fix disable fuse_all_optimizer bug

* try to test ci

* fix CI

* fill unspecified op role

* fix fuse_allreduce

* add ut to improve coverage

* remove useless change

* improve c++ coverage

* follow some comments

* test ir pass pipeline

* update doc

* reduce ut time again

The bug is that access to mean and var is incorrect, and the array will be out of bounds: the shape of mean and var is [batch_size], and the range of thread idx is 0~feature_size, so mean[idx] and var[idx] is incorrect.

When batch_size=1, the correct access is mean[0] and var[0], and a unit test with batch_size=1 is added.

* merge CMakeList.txt manual

* add platform for changethreadnum

* repair some bugs according to make error

* do nothing just flush CI

* forget change thread num

* add inplace_atol param for check_output_with_place

* Windows

* std:min and std::max should be change because of windows

* release gil before op run

* support npu grad test

* fix op_test

* Split Tracker and WorkQueue

* add WorkQueueGroup

* add unittest

* fix

* update

* update

* fix compile

* add the matmul v2 grad kernel

* relief the test case time

* update the test case for the matmul double grad

* remove the unsed code for the matmul double grad

* update the test case for the double grad matmul

* remove the unused code in dot

* add conv op check for illegal input or attributes

* [NPU] update batch norm op, test=develop

* add NHWC support for bn, test=develop

* [NPU] fix for test_norm_op_npu

* [NPU] add norm_grad

* [NPU] add CheckAxis for axis

* [NPU] delete debug codes

* norm can not use L2Normalize, norm_grad can use L2NormalizeGrad

* [NPU] delete useless codes

* [NPU] optimize norm_grad OpMaker

* Update python import path

* [NPU] log_softmax_grad, test=develop

* remove debug files, test=develop

* update lookup_table_v2 for CANN 5.0.x, test=develop

* - refactoring progressing

- Fix

- compilation fix

- another compilation fix

- refactoring

* - fix

* - compilation fix

* - compilation fix

* - missing set_format

* - compilation fix

* - reverted setting memeory format

* - Brought back format

* - Fix

* - fixes after review

* CI rerun

* CI rerun

* fix for reshape2

* added reviewers sugestions

* operators/flatten_op.cc add AsExtra

* operators/flatten_op.cc add AsExtra

* fix format

* add AsExtra in data_norm op

* pass data_layout from python to data_norm op

* fix data_layout in data_norm op
Co-authored-by: Nroot <root@bjyz-sys-gpu-kongming9.bjyz.baidu.com>

* fix commit

* Open unittest

* fix unittest on Windows

* fix constructor

* notest,test=inference;support test different suite type

* notest,test=inference;fix script bugs

* notest,test=inference;fix count time issue

* test=document_fix; fix readme grammar

* [HIP] fix op not support AMD GPU bug, the flag PADDLE_WITH_ROCM is invalid

* [HIP] fix op not support AMD GPU bug, the flag PADDLE_WITH_ROCM is invalid

* [HIP] fix op not support AMD GPU bug

* support double in deformable conv

* add double for dcn v2

* Add the extra flag for the some ops

* fix the compile problem in matmul extra

* Add fusion_lstm INT8 PTQ

* Correct mkldnn_cache_capacity and enable fc_lstm_fuse_pass only for this test

* Change mkldnn_cache_capacity

* add pool2d grad grad

* dbg

* add unittest

* update format

* add more unittests

* dbg

* transpose/slice/stride_slice/squeeze/unsqueeze op_def_enhance-1.0

* delete infer_flags and decrease-axis

* delet infer_flags and decrea_axis

* add pool2d pool3d extra()

* delete ceil_mode extra()

* delete ceil_mode extra()

* delete ceil_mode extra()

* add extra to use_mkldnn

* Support Reset for DeviceEvent

* fix code

* add more unittest

* add AsExtra tag for conv transpose op

* check the existence of use_cudnn before get this attribute

* add depthwise_conv_npu_grad op

* add depthwise_conv_npu_grad op

* add depthwise_conv_npu_grad op

* add NHWC test case

* support numpy dtype and polish code of list index.

* polish code.