image_classifier.py: PTQ stats collection and eval in same run (#346)

* Previous implementation:
  * Stats collection required a separate run with `-qe-calibration`.
  * Specifying `--quantize-eval` without `--qe-stats-file` triggered
    dynamic quantization.
  * Running with `--quantize-eval --qe-calibration <num>` only ran
    stats collection and ignored --quantize-eval.

* New implementation:
  * Running `--quantize-eval --qe-calibration <num>` will now 
    perform stats collection according to the calibration flag,
    and then quantize the model with the collected stats (and
    run evaluation).
  * Specifying `--quantize-eval` without `--qe-stats-file` will
    trigger the same flow as in the bullet above, as if 
    `--qe-calibration 0.05` was used (i.e. 5% of the test set will
    be used for stats).
  * Added new flag: `--qe-dynamic`. From now, to do dynamic 
    quantization, need to explicitly run:
    `--quantize-eval --qe-dynamic`
  * As before, can still run `--qe-calibration` without 
    `--quantize-eval` to perform "stand-alone" stats collection
  * The following flags, which all represent different ways to
    control creation of stats or use of existing stats, are now
    mutually exclusive:
    `--qe-calibration`, `-qe-stats-file`, `--qe-dynamic`,
    `--qe-config-file`