Extend image verification tool to generate report about image

- Validity of Backend.AI-specific labels and guides on how to fix them, e.g.,\* base-distro: check the actual glibc version in the image
- service-ports: check consistency with service-defs (whether it's based on service-defs or intrinsic services)

- CUDA runtime version(s) installed at the image filesystem
- Location(s) of Python/R/etc. runtimes found in the image filesystem\* There may be multiple runtimes. (e.g., system Python, conda, pyenv, etc.)
- The (summarized) list of installed packages for each runtime

- The (summarized) list of installed system packages
- Run a small test workload using the image (e.g., fashion-MNIST for CUDA-enabled images)\* We start simple, but it's important to set up an automated workflow so that we could add more sophisticated test workloads as we find new compatibility issues in our customer sites and as new CUDA versions & AI frameworks come out.

JIRA Issue: BA-142