Gets the Resource Utilization Statistics For Your Google Colab

get_google_colab_resource_utilization

def get_colab_usage(pip_install=False, import_libs=True, return_fn=True):
    """ Retrieve Google Colab Resource Utilization Stats
    
    Args:
        pip_install (bool, optional): Whether to preform pip installs
        import_libs (bool, optional): Whether to import libraries
        return_fn (bool, optional): Whether or not to return get_usage fn
    
    Returns:
        The get_usage fn ...
            (potentially... only if return_fn flag is set to True)
            ... which can be used to determine resource utilization stats
            at any time in the future of this session without need for
            any pip installs or library imports or fn definitions
    """
    
    if pip_install:
        # memory footprint support libraries/code
        !ln -sf /opt/bin/nvidia-smi /usr/bin/nvidia-smi
        !pip install gputil
        !pip install psutil
        !pip install humanize

    if import_libs:
        import psutil
        import humanize
        import os
        import GPUtil as GPU

    def print_resource_usage():
        """Function that actually retrieves resource utilization statistics"""   
        
        # Get the activate GPU
        # TODO >>> GPU not guaranteed to be the only one <<< TODO
        gpu = GPU.getGPUs()[0]

        # Get current process
        process = psutil.Process(os.getpid())

        # Get general ram usage
        gen_ram = humanize.naturalsize(psutil.virtual_memory().available)

        # Get processor size
        proc_size = humanize.naturalsize(process.memory_info().rss)

        # Get gpu stats
        gpu_free_mem  = gpu.memoryFree
        gpu_used_mem  = gpu.memoryUsed
        gpu_util_mem  = gpu.memoryUtil*100
        gpu_total_mem = gpu.memoryTotal

        # Print interpretable resource utilization statistics
        print("\n------------------------------------------------------")
        print("             RESOURCE USAGE STATISTICS                ")
        print("------------------------------------------------------\n")
        print("Gen RAM Free: {:8} | " \
              "Proc size   : {}"\
              "".format(gen_ram, proc_size)) 
        
        print("GPU RAM Free: {:4.0f} MB | " \
              "Used        : {:5.0f} MB | " \
              "Util        : {:5.0f}% | " \
              "Total       : {:5.0f}MB\n" \
              "".format(gpu_free_mem, gpu_used_mem, 
                        gpu_util_mem, gpu_total_mem))

    # Internally call the fn
    print_resource_usage()

    if return_fn:
        return(print_resource_usage)

# This will print the resource utilization and give us access
# to the fn `get_usage` which can now be called like a regular
# function with no arguments required.
get_usage = get_colab_usage(pip_install=True, return_fn=True)

Sample of Expected Output

------------------------------------------------------
             RESOURCE USAGE STATISTICS                
------------------------------------------------------

Gen RAM Free: 26.4 GB  | Proc size   : 162.4 MB
GPU RAM Free: 11441 MB | Used        :     0 MB | Util        :     0% | Total       : 11441MB