1. Fix kernel
2. Add more test case

2. Remove num_seq arguments.
3. Refine CUDA kernel of ScaleLoDTensorFunctor.
4. Change max_relative_error of gradient unitest to 0.007

* update code comments.

* update the comments.

* follow comments.

We need this operator to assign value to a tensor and the values are stored in the program so that they can be used independent of python.

* add update graph method for memory optimization transpiler to avoid rebuild graph everytime

* clean code

* reset var desc if hit cache

2. Add check grad test

feature/parallel_gpu

* "init use all default devices"

* "fix init test"

Added backward.calc_gradient to backpropagate gradient from given targets to inputs.

* test dist word2vec

* multiple trainers work

* Add Seq2BatchFunctor, which will be used in WarpCTCOp.

* Implement WrapCTCFunctor and WrapCTCKernel.

* Add unittest of warpctc_op.

* Modify the check_output inferface in python unittest framework to allow check a subset of outputs.

* Use absolute offset lod in warpctc_op and related functors.

* Refine the comments of warpctc_op.

* The new python unittest supports checking a subset of the outputs, so revoke the previous change.

* Rename the transform from LoDTensor to Tensor with shape [max_sequence_length, num_sequences, sequence_width] to PaddingSequenceFunctor.

* Update to the newest codes.

* Rename the PaddingSequenceFunctor to PaddingLoDTensorFunctor and remove the computation of dimensions out of the functos.