* Set states of recurrent op as dependent vars in prune of save inference model

This PR will fix the save/load inference model problem of RNN models.

The reason of the bug is that save_inferenc_model will prune OPs that doesn't contribute to Output. But in recurrent_op, States are not Output, OPs refers States will be pruned. 

This fix adds States of recurrent_op as dependent var so that OPs referring States won't be pruned. 

* Fix conv2d+dequantize squash for residual fusion

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* Change condition

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Add boost as dependency of prune

fix #19862

* Add fc_elementwise_layernorm_fuse pass and unittest.

* Add fused_fc_elementwise_layernorm op and its GPU kernel.
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* Apply fc_elementwise_layernorm_fuse_pass to GPU inference.

* Add the setting of attrs in the definition of binary_op.
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* Add comment.

* Implement the unittest.
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* Change the unittest name of layer_norm.
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* fix memory reuse bug on feeding variables, test=develop

* add comments to reference count members, test=develop

* rm return in vfork

* rm return in vfork
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* support preload thread
* sleep before fleet wrapper exit for pslib core dump
* optimize hdfs log
* fix master+patch bug

* refactor dygraph,test=develop

* fix failed unittest,test=develop

* polish code,test=develop

* check windows ci error,test=develop
try to fix windows ci error by np.allclose,test=develop

* polish vlog and profiler, test=develop

* try to fix preceding ops order,test=develop

* test transformer in windows ci, test=develop

* use python c-api to speed up tracer.trace,test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, add ut for debug string and gradient_accumulator

* test=develop, add tests for layer/gradient_accumulator/prepared_op

* test=develop, fix complie error for test_prepared_op

* test=develop, add more ut for dygraph

* test=develop, create API.spec for dygraph api change

* add transform_data to dygraph

* test=develop, refoctor name to make it easier to understand

* test=develop, refoctor name to make it easier to understand

* add test and change input to const ref for safety

* test=develop, fix multi-gpu failed problem , add Tracer tests, change PADDLEENFORCE to PADDLEENFORCE_EQ

* add ut for data transform

* refine ut for data_transform

* test=develop, fix ut failed on parallel se-resnext

* test=develop, change one more PADDLE_ENFORCE

* add test_tracer on multiple devices

* test=develop, change place to mutable for data transform

* test=develop, add transform data on same place test and remove useless log

* test=develop, Add to do for data layout and and ut for conv2d with no bias

* fix warning info
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* fix bug of all_reduce_deps_pass
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* Refine the codes related to fc op.

* Add GPU implementation for fc functor.

* Apply fc_fuse_pass in GPU inference.
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* Change the cmake for fc op.

* Change PADDLE_ENFORCE to PADDLE_ENFORCE_EQ.

* Add an attribute to set the activation type in fc_op.

* Enhance the unittest of fc_op.
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* Remove the declaration of FCOpGrad back to the header file.
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* Set default value for newly added arguments in test_fc_op.
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* Enhance fc_fuse_pass to enable fusing relu.

* Allow print the shapes of var_desc in graph.
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* Enhance fc_fuse_pass_tester.

* Remove the use of PADDLE_ENFORCE.
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* Correct the number of ops after fusing.
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* Fix a typo.
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* Set activation_type to null when there is no relu in fc.
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* Refine fc_fuse_pass's codes.

* Enable the set of shape for tensor.

* Refine repeated_fc_relu_pass and add unittest.
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* Open fuse all reduce op
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* Add Fuse optimization op log

* Add log in fuse_optimizer op pass and fuse all_reduce op pass

* replace with boost::optional<bool>
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* Polish code
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* fix code coverage
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TemporaryAllocator is a singleton used for allocating memory for Cudnn. Since it is a singleton, we can delete it for better performance in memory.

We replace TemporaryAllocator by CUDADeviceContextAllocator and CUDADeviceContextAllocation, which uses stream callback to delete the memory allocated for the stream to avoid singleton.

Also added data_feed_proto to operator to fix CI in CPU compilation

* make leaky relu inplacable, test=develop

* force add unittests to pass coverage, test=develop

* fix vlog level and fuse option type
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* Refine the codes related to fc op.

* Add GPU implementation for fc functor.

* Apply fc_fuse_pass in GPU inference.
test=develop

* Change the cmake for fc op.

* Change PADDLE_ENFORCE to PADDLE_ENFORCE_EQ.

* Add an attribute to set the activation type in fc_op.

* Enhance the unittest of fc_op.
test=develop

* Remove the declaration of FCOpGrad back to the header file.
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* Set default value for newly added arguments in test_fc_op.
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* Enable fused_all_reduce_op_handle support GPU and CPU Gradients

remove unused accuracy-diff warpctc-cudnn implementation

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* merge_empty_lod_tensor, test=develop

* fix multiclass_nms, test=develop

* refine API.spec, test=develop

* add unittest case for fetch, test=develop

* add lod tensor test, test=develop

* return index for multiclass_nms, test=develop

* add api for multiclass_nms2

* update API.spc, test=develop

* refine api doc, test=develop

* fix test_detection.py, test=develop

* polish code, test=develop

* add more unittest case, test=develop

fix cmakelist deps: remove unnecessary deps and add proper op deps

* remove -Wmaybe-uninitialized warning

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* remove uninitialized op_handle_ in scale_loss_grad_op_handle.cc

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* test=develop codegen for fused elementwise operation

* fix test=develop

* Fix bug: add feed_vars to the prune function

* remove assert.h

* change PADDLE_ASSERT_MSG to PADDLE_ENFORCE

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* fix tensorrt paddle_enforce

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* enable ngraph throught build_strategy test=develop

* add unittest test=develop

* put use_ngraph unconditional test=develop

* remove paddle_enforce test=develop

* remove paddle_enforce test=develop

* fix copyright test=develop

* limit for ngraph only test=develop

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* Add a interface to enable cudnn for inference.

* Add cudnn_placement_pass.
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* Set the default value of cudnn_enabled_op_types to null.
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* Write the common basic class, placement_pass_base, to refine the codes.
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* Call EnableCUDNN in unittest.
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* Refine cudnn_placement_pass tester.

* Enable the testing of cudnn_placement_pass in inference's unittest.
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* Add the check of op kernels.
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* using MKLDNNMemoryFormat = mkldnn::memory::format changes
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* PADDLE_ENFORCE update
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Change backward_guard to optimize_guard to maximize the allreduce overlap