[llm bench] Move calculation of memory consumption to memory_monitor tool

[sbalandi]

memory_monitor.py from https://github.com/openvinotoolkit/nncf/blob/develop/tools/memory_monitor.py
added two custom lines, because of issue with tkiner, founded on text2image pipeline and stable-diffusion-v2-1 with pytorch framework :

import matplotlib
# CUSTOM FIX TO AVOID ISSUE: RuntimeError: main thread is not in main loop
matplotlib.use('Agg')

Task: CVS-164392 CVS-157590

[sbalandi]

to discuss. Is it okay that:

• added delay as compilation and generation can sometimes be too fast and measure will be 0 in such cases: interval 0.01, delay 0.03
• memory consumption is not included full memory which process consume, just memory, which was consumed by code snippet:
  before, consumption from start + generate:
  [warm-up][P0] Max rss memory cost: 5113.64MBytes
  now, just generate:
  [warm-up][P0] Max rss memory cost: 3991.55MBytes
  In that case generation on next step after warm-up shows very low consumption :
  before:
  [1][P0] Max rss memory cost: 5124.81MBytes
  now:
  [1][P0] Max rss memory cost: 0.51MBytes

[sbalandi]

to discuss. Is it okay that:

• added delay as compilation and generation can sometimes be too fast and measure will be 0 in such cases: interval 0.01, delay 0.03
• memory consumption is not included full memory which process consume, just memory, which was consumed by code snippet:
  before, consumption from start + generate:
  [warm-up][P0] Max rss memory cost: 5113.64MBytes
  now, just generate:
  [warm-up][P0] Max rss memory cost: 3991.55MBytes
  In that case generation on next step after warm-up shows very low consumption :
  before:
  [1][P0] Max rss memory cost: 5124.81MBytes
  now:
  [1][P0] Max rss memory cost: 0.51MBytes

• delay is ok
• keep printing full memory and add print of increase
• move content of memory_profiling.py to memory_monitor.py