* Add MKL-DNN Benchmarking to CRNN-CTC

* Make crnn-ctc scripts more portable

* Add documentation for cycle to crnn-ctc-reader

* Update crnn-ctc readme for CPU execution

* Merge CRNN-CTC train & inference scripts

* Fix mnist model & ce, kaffe graph yapf issues

* Remove LD_LIBRARY_PATH from crnn-ctc scripts

* CRNN-CTC scripts: set parallel to true

Abort script if batch_size is lower than num of cores

* CRNN-CTC scripts: limit mode options in infer

* CRNN-CTC scripts: set mkldnn parallel to False

* Refine code for English dataset.
1. Remove a pooling layer.
2. Change classes_num to 94.
3. Modify some arguments in ctc_train.py
4. Add learning rate decay policy.

* Fix readme.

* Fix README.

* Remove consine decay.

* Remove eval.sh

1. Add document.
2. Add arguments for saving model and init model.
3. Refine inference.py and eval.py.
4. Make ctc_reader.py support for custom data.

1. Add download of data into ctc_read.py
2. Use 'clone' instead of 'get_inference_program'
3. Add time to train log

2. Add ceil mode for pooling

2. Add inference script
3. Add load model script
4. Add some functions into ctc_reader

1. Move all network defining to 'crnn_ctc_model.py'
2. Add initilizer for some layers
3. Rename 'fluid/ocr' to 'fluid/ocr_recognition'
4. Remove copyright
5. Rename some functions