* add instance norm op

* Initial, functional commit

* Clean commit related files
test=develop

* add TRT shape check, test=develop

* model_input_shape == runtime_input_shape, refine message, test=develop

* support 2-level lod of input in sequence_pool test=develop

* fix lod level bug in .cu test=develop

1. group_norm support data_layout=NHWC
2. modified doc of group_norm

- LRN mkl-dnn kernel refactor

test=develop

- compilation fix

- Another compilation fix

- Compilation fix

- another compilation fix

- compilation fix

- Crash fix

- optional LRN mkldnn workspace

- Added mid allocation

- Workaround for tests

- Removed gradient from is_test ut

- Removed mid for inference

- Reverted LRN mid removal for is_test

- PADDLE_ENFORCE adjusted

- Rebase to templatization commit

- Compilation fix

- compilation fix

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- lint

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- Fix to crash

- Rebase to recent codebase

 - lin

- lint

- compilation fix

modified interpolate_op to support tensor attribute

1. the parameter out_shape of image_resize、resize_nearest/bilinear/trilinear can be a list or a 1-D tensor variable. If a list, each element can be an integer or a tensor variable with shape: [1].

2. the parameter scale of above Ops can be a 1-D tensor variable.
modified document of image_resize, resize_nearest, resize_bilinear, resize_trilinear and add some code example.

add crop_tensor op. The main difference with crop is :

1. If the argument shape is a list, each element is an integer or a tensor variable with shape: [1]. This way is suitable for the case that the shape may be changed each iteration.

2. If the argument shape is a variable. Its rank must be 1. In crop op, the rank of shape must be the same as x

offsets can be a list, in which each element is an integer or a tensor variavle with shape: [1].

* fix conflicts
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* change mask_bias_reorder
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* add ComputeMask function to make code clear
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* change according to reviews
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* change according to reviews
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* Add template functions for Acquire primitive/primitive_desc
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* Move acquire primitive descriptor to protected section
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* Remove constraint that last dimension is forced to be 1 in cross_entropy
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* modify labels last dims test=develop

* add precise roi pooling op test=develop

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* detail the description test=develop

* test=develop

* elaborate the doc for return type test=develop

* test=develop

* 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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* strided_slice op basic function test=develop

* test=develop rewrite and fix

* fix bug test=develop

* fix for the PADDLE_ENFORCE usage

* add some unit testw

* fix for the aip  test and copright and fix test=develop

* fix API.spec test=develop

* fix API.spec test=develop

* add axis parameter test=develop

* fix for the build error test=develop

* fix python api  test=develop

* fix the build test=develop

* fix build test=develop

* fix API spec test=develop

* test=develop add some comment and single op test

* fix API spece test=develop

* fix test=develop

* fix test=develop

* fix api test=develop

* fix api test=develop

* fix API.spec test=develop

* fix typo test=develop

* fix API.spec test=develop

* fix API typo test=develop

* fix doc and API.spec test=develop

* rpc retry for asycsend/get/prefetch

* test=develop, change retry vlog level to 3

* test=develop, set default grpc_retry_times is 3

* update elementwise double grad to save gpu memory, test=develop

* update elementwise_mul/div_grad_grad to save memory, test=develop

* remove eval function in eigen statement to save memory, test=develop

* add unittest for elementwise_div_grad_grad without dout, test=develop

* add unittest for elementwise_add_grad_grad without ddx, test=develop

* add float16 cuda kernel for elementwise double grad op, test=develop

test=develop

* add deformable conv v1 op, test=develop

improve pow op according to reviews:
1. Delete unnecessary judgement statements in PowGradOpDescMaker;
2. Improve test of test_api;

overload GetKernelTypeForVar

add stop_gradient=True when attr(factor) is tensor Variable, change examples in API pow.
test=develop,test=document_preview

add support parameter inference when argument shape is a list containing integer and tensor variable;
test=develop

fix reshape op according to reviews:
1. improve or message;
2. improve test of test_api.
test=develop,test=document_preview

fix reshape op: Add error message in nn.py, test=develop

add stop_gradient=True when attr(shape) is tensor Variable.
change examples in API reshape.
test=develop,test=document_preview

add support parameter inference when arguments starts or ends is a list containing integer and tensor variable;
test=develop,test=document_preview

improve slice op according to review(from hongyu). test=develop

fix slice op according to review: infer_flags, test=develop

fix slice op: improve overload operator __getitem__ to support attrs(starts and ends) are Variable.
test=develop,test=document_preview

fix test_slice_op: add TestSliceOp_decs_dim_6 to resolve conflict with test_slice_ngraph_op. test=develop

add stop_gradient=True when attr(starts) or attr(ends) is tensor Variable.
test=develop,test=document_preview

1. add tensor support for argument expand_times in expand op;
2. add support parameter inference when argument expand_times is a list containing integer and tensor variable;

improve expand op according to reviews:
1. add doc of ExpandTimes in expand_op.cc;
2. improve the test of test_api.

add stop_gradient=True when attr(expand_times) is tensor Variable, change code examples.
test=develop,test=document_preview

* cpu conv_grad_grad

* Implement the operator with sprase matrix multiply

* Update the URL of mklml library.

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* Disable MKLML implematation when using no-linux.

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* optimize bp with mkl sparse matrix
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* tmp add fused_emb_seq layer

* Add the support of padding_idx attribute.

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* add padding_idx support
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* implement grad refer lego
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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.
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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.
test=develop

* 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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* add kernel for squeeze_op, test=develop

* delete comment, test=develop

* add kernel for unstack_op, test=develop

* add kernel for unstack_op, test=develop

* add kernel for unstack_op, test=develop

* adjust the code format, test=develop

* modify some comment, test=develop

test=develop

* add one_hot_v2_op to remove last_dims==1 test=develop

* add api unittest code for CI_Coverage test=develop

* improve CI_Coverage rate by adding test_with_depth test=develop

test=develop

- fix to BWD

test=develop

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

test=develop

- Cosmetic fixes

test=develop

* 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.
test=develop

* Set default value for newly added arguments in test_fc_op.
test=develop