* fix compile error in CUDA10 test=develop

* remove double in pad2d test=develop

* fix stat shape back in global auc scenario
* add UT to cover global auc

* add register op_data_type test=develop

* fix register bug in isfinite op test=develop

* rm int int64_t in pad2d gradKernel  test=develop

* optimize adam speed by removing _finish_update test=develop

* fix SparseAdamFunctor param list test=develop

* Remove scale_op in expect_list of adam_op test=develop

* fix test optimizer loss assert error test=develop

* fix test optimizer loss assert error test=develop

* modify PADDLE_ENFORCE usage test=develop

* fix op_type in lamb_op.cc test=develop

* fix errors ostream format bug test=develop

* add betaPowOut in ngraph op test=develop

* fix ngraph::op api for gcc8 test=develop

* clean code test=develop

* modify struct into class test=develop

* remove code of beta1Tensor in lamb_op test=develop

Update iou_similarity op to support non-normalized bbox

test=develop

* test=develop, speed dense calc & communication

test=develop

1. Make while_op accept GPU conditional data
2. Add more complex test cases for while_loop API

* Fix softmax cuda bug

* Refine multihead log and softmax logic

* yolo_box OP add Attr(clip_bbox). test=develop

* fix elementwise_pow bug on integer, test=develop

* use llrint to support elementwise_pow_grad, test=develop

* add some tests, test=develop

* revert grad functor, test=develop

* rename paddle throw error macro, test=develop

* fix new error use case, test=develop

* Add reshape int8 op

test=develop

* Change test to CPUPlace

test=develop

* Correct tests

test=develop

* add fake init for the trainer, fix large memory hold in the trainer
* do not merge recv vars from a remote endpoint, test=develop
* add recv and save op, merge slice var in one op, save memory
* remove hsigmoid with pull sparse, test=develop

test=develop

* add seed op

* MKLDNN v1.0 rebase to Paddle 1.6
test=develop

* Add hacky paddle::string::to_string() implementation

* vectorize<int64-t>() -> vectorize() cleanup
test=develop

* PADDLE_ENFORCE and void_cast fixes
test=develop

* Rebase changes
test=develop

* Cosmetics
test=develop

* Delete MKL from mkldnn.cmake
test=develop

* CMake debug commands
test=develop

* Delete MKLDNN_VERBOSE and rebase fixes
test=develop

* Rebase fixes
test=develop

* Temporarily disable int8 resnet101 vgg16 and vgg19 tests
test=develop

* Add libmkldnn.so.1 to python setup
test=develop

* Add libmkldnn.so.1 to inference_lib cmake after rebase
test=develop

* Post rebase fixes + FC int8 changes
test=develop

* Fix LRN NHWC
test=develop

* Fix NHWC conv3d
test=develop

* Windows build fix + next conv3d fix
test=develop

* Fix conv2d on AVX2 machines
test=develop

* accelerate mean op test=develop

* polish infer shape registry, test=develop

* modify some operators registry, test=develop

Add tests to use dy/dx to make sure the gradient values calculated by the control flow backward is correct. Also fixed bugs detected by those tests.

Fix bugs:

1. Unlike sum_op, optimizer ops don't allow uninitialized input tensor. But in conditional_block_grad_op, since the conditional_block may not run, the output gradient tensor may be uninitialized, which will cause the optimizer op error. To fix it, we should let optimizer ops support uninitialized input like sum_op or assign the uninitialized gradient to 0 when the conditional_block_grad_op doesn't run. I found there are about 10+ optimizer ops. **To be simpler, I just assign output gradient of the conditional_block_grad_op to 0 in this PR**. But it can be further explored whether we can make optimizer ops like sum_op to support uninitialized input tensor because theoretically we can speed up without the assigning in conditional_block_grad_op.

2. Infer parameter shapes during append_backward. I didn't know that all our parameters are in global block. When op_desc is inferring shapes at the sub-block, it may not know the shape of gradients of parameters whose shape information is at global block. I fixed it by inferring shapes of gradients from forward var.

This PR also did some code clean up:
1. Print the var name when sgd_op catches shape error so that it is easier to debug
2. Fix a typo: dicta -> dict

test=develop

* - BAtch norm mkl-dnn NHWC

test=develop

- compilation fix

test=develop

- UT fix

- cosmetics

test=develop

- Fix to Batch Norm MKL-DNN NHWC UT

test=develop

Conflicts:
	paddle/fluid/operators/batch_norm_op.h

* - Lint fixes

test=develop

* dygraph Embedding layer use lookuptable v2
test=develop

* fix test_nce
test=develop

* fix fill_constant_batch_size_like_op precious problem  test=develop

test=develop

* set dim[0] to -1 if dim[0] < 0 and remove assertion to runtime, test=develop

* modify ENFORCE message, test=develop

* add validation for x.shape[0] > 0, test=develop

* add ut, test=develop