Beispiel #1
0
def check_notebook_name_exists(check_notebook_name_exists_json):
    check_notebook_name_exists_dict = json_decoder.decode(
        check_notebook_name_exists_json)

    # if new installation, create global notebooks table

    if not (notebook_global_table_exist()):
        create_notebook_global_table()

    # opens the global notebooks table, and checks whether notebook exists

    fileObject = open("NOTEBOOKS_DATA", "rb")
    table = pickle.load(fileObject)

    if any(obj['notebook_name'] ==
           check_notebook_name_exists_dict['notebook_name'] for obj in table):
        return json_encoder.encode({
            "message": "Success",
            "comment": "Notebook name exists"
        })

    return json_encoder.encode({
        "message": "Success",
        "comment": "Notebook name available"
    })
Beispiel #2
0
def add_notebook():
    print("changed")
    try:
        # notebook is of type weakdict to create references of it
        notebook = weakdict(request.json)

        # creating a reference of notebook's data
        weakdict_notebook = weakref.proxy(notebook)

        fileObject = open("NOTEBOOK_" + notebook['notebook_name'], "wb")
        pickle.dump(notebook, fileObject)
        fileObject.close()

        # if new installation, create a global notebooks table

        if not (notebook_global_table_exist()):
            create_notebook_global_table()

        # open global notebooks table and add notebook configuration

        fileObject = open("NOTEBOOKS_DATA", "rb")
        table = pickle.load(fileObject)
        fileObject.close()

        table.append({
            "notebook_name": notebook['notebook_name'],
            "GPU_count": int(notebook['GPU_count']),
            "CPU_count": int(notebook['CPU_count']),
            "is_online": False
        })

        fileObject = open("NOTEBOOKS_DATA", "wb")
        pickle.dump(table, fileObject)
        fileObject.close()

        # open global user table and add this notebook to user's list of created notebooks

        table = pickle.load(open("USERTABLE", "rb"))
        for obj in table:
            if obj['username'] == notebook['username']:
                obj['created_notebooks'].append(notebook['notebook_name'])

        pickle.dump(table, open("USERTABLE", "wb"))

        return json_encoder.encode({
            "message": "Success",
            "comment": "Notebook created"
        })
    except:
        return json_encoder.encode({
            "message": "Failure",
            "comment": "Other error"
        })
def get_devices():
    # Currently works only on Linux
    # Fails on windows.
    # Check for unix
    if (os.name == 'posix'):
        n_cpu = psutil.cpu_count()

    # if new installation, create a global notebooks table
    if not (notebook_global_table_exist()):
        create_notebook_global_table()

    table = pickle.load(open("NOTEBOOKS_DATA", "rb"))
    a_cpu = n_cpu - sum(obj["CPU_count"] for obj in table)

    return json_encoder.encode({"message": "Success", "CPU_available": a_cpu})
Beispiel #4
0
def get_devices():
    # Currently works only on Linux
    # Fails on windows.

    # Check for unix
    if (os.name == 'posix'):

        # get GPU count if avaiable
        try:
            n_gpu = len(GPUtil.getGPUs())
        except:
            n_gpu = 0

        # get CPU count
        n_cpu = psutil.cpu_count()

    # For windows, use tensorflow to get details
    else:
        local_devices = device_lib.list_local_devices()
        n_gpu = len([x.name for x in local_devices if x.device_type == 'GPU'])
        n_cpu = psutil.cpu_count()

    # if new installation, create a global notebooks table

    if not (notebook_global_table_exist()):
        create_notebook_global_table()

    table = pickle.load(open("NOTEBOOKS_DATA", "rb"))

    # Send number of CPUs and GPUs currently available

    a_gpu = n_gpu - sum(obj["GPU_count"] for obj in table if obj['is_online'])
    a_cpu = n_cpu - sum(obj["CPU_count"] for obj in table if obj['is_online'])

    return json_encoder.encode({
        "message": "Success",
        "GPU_count": n_gpu,
        "CPU_count": n_cpu,
        "GPU_available": a_gpu,
        "CPU_available": a_cpu
    })