Performance issues in the definition of programs.dataset,tensorflow_dl_models/official/mnist/dataset.py

[DLPerf]

Hello,I found some performance issues.
The first one is in the definition of dataset ,tensorflow_dl_models/official/mnist/dataset.py,
tf.data.FixedLengthRecordDataset(images_file, 28 * 28, header_bytes=16).map was called without num_parallel_calls.
I think it will increase the efficiency of your program if you add this.

The same issues also exist in tf.data.FixedLengthRecordDataset(
labels_file, 1, header_bytes=8).map ,
.map(decode_csv)),
dataset = dataset.map(decode),
dataset = dataset.map(decode)
and dataset = dataset.map(_parse_line)

Here is the documemtation of tensorflow to support this thing.

The socond one is in thedefinition of Eval,tensorflow_dl_models/research/street/python/vgsl_model.py.
sess = tf.Session('') was repeatedly called and was not closed.
I think it will increase the efficiency and avoid out of memory if you close this session after using it.

The same issues also exist in sess = tf.Session()

Here are two files to support this issue,support1 and support2

Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.