remove mkldnn & fix commit

Enable function coverage for U8/S8 ConvMKLDNNOpKernel

add ir memory optimize test base

add IrNode&IrVarNode&IrOpNode. test=develop

Fix util-plot for py3

* loosly check in cross_entropy_op when soft_label is True
* Add Runtime assertion in backward infer_shape check.
* Skip InferShape check when un-know the input dimensions

MKL-DNN: Add Activations and Softmax UTs to check if primitives already exist in backward

Optimize the CUDA implementation of sequence_expand op by reduce the times of copying lod data from CPU to GPU. (#15493)

* Optimize the CUDA implementation of sequence_expand op by reduce the times of copying lod data from CPU to GPU.
test=develop

* Refine the op benchmark to support setting lod in config.
test=develop

Add Conv Residual Connection UT for Projection

* This PR improve performance of prior_box op about 1.25x faster on CPU.

* Test Env:SKX 8180 with fake data on 28 threads(bs=1).
* The below table shows the ~25% improvement which generated by [eval_tp_fake_data.py](https://github.com/PaddlePaddle/Paddle/issues/15618#issuecomment-464613976).

| Type |Event | Calls |   Total     |  Min.    |   Max.      |  Ave.      |  Ratio.|
| ---------------- | ------------------ | ---- | ------- | -------- | -------- | ------------ | -------- |
| w/ optimization  | thread0::prior_box | 6000 | 921.201 | 0.110572 | 0.383402 | **0.153533** | 0.084585 |
| w/o optimization | thread0::prior_box | 6000 | 1151.85 | 0.102276 | 0.426702 | **0.191976** | 0.103337 |

test=develop

* Fix the style issue.

test=develop

Refactor MKL-DNN Sum to use reference version on fallback

* add alloc_continuous_space_op
test=develop

* Polish code
test=develop

* follow comment
test=develop

fix nightly build

fix build issue for cudaEvent_t

test=develop

test=develop

test=develop

accelerate memory optimize process

test=develop

Imperative training network to the end

Pass graph to parallel executor instead of program

test=develop

fix build issue on windows for sample prop op

* refile profiler
test=develop

* follow comment
test=develop

* Refine doc of uniform_random and fix dtype
* Update defaule value in the arguments

add per kernel config and remove const_cast.