Module `monk.tf_keras_1.training.params`

Expand source code

from tf_keras_1.training.imports import *
from system.imports import *




def set_num_epochs(num_epochs, system_dict):
    '''
    Set number of training epochs

    Args:
        num_epochs (int): Number of epochs to train the network
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["hyper-parameters"]["num_epochs"] = num_epochs;
    return system_dict;





def set_display_progress_realtime(value, system_dict):
    '''
    Set verbosity levels for iterations

    Args:
        value (bool): If True, displays progress for every iteration in the epoch
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["display_progress_realtime"] = value;
    return system_dict;




def set_display_progress(value, system_dict):
    '''
    Set all training params for epochs

    Args:
        value (bool): If True, displays summary post every epoch
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["display_progress"] = value;
    return system_dict;




def set_save_intermediate_models(value, system_dict):
    '''
    Set whether to save models post every epoch or not

    Args:
        value (bool): If True, saves model weight post every epoch
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["save_intermediate_models"] = value;
    return system_dict;




def set_save_training_logs(value, system_dict):
    '''
    Set whether to save training logs or not

    Args:
        value (bool): If True, saves all training and validation metrics. Required for comparison.
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["save_training_logs"] = value;
    return system_dict;




def set_intermediate_model_prefix(value, system_dict):
    '''
    Set a prefix to names of intermediate models being saved

    Args:
        value (str): Appends a prefix to intermediate weights
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["intermediate_model_prefix"] = value;
    return system_dict;

Functions

def set_display_progress(value, system_dict)

Set all training params for epochs

Args

value : bool: If True, displays summary post every epoch
system_dict : dict: System dictionary storing experiment state and set variables

Returns

dict: updated system dict

Expand source code

def set_display_progress(value, system_dict):
    '''
    Set all training params for epochs

    Args:
        value (bool): If True, displays summary post every epoch
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["display_progress"] = value;
    return system_dict;

def set_display_progress_realtime(value, system_dict)

Set verbosity levels for iterations

Args

value : bool: If True, displays progress for every iteration in the epoch
system_dict : dict: System dictionary storing experiment state and set variables

Returns

dict: updated system dict

Expand source code

def set_display_progress_realtime(value, system_dict):
    '''
    Set verbosity levels for iterations

    Args:
        value (bool): If True, displays progress for every iteration in the epoch
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["display_progress_realtime"] = value;
    return system_dict;

def set_intermediate_model_prefix(value, system_dict)

Set a prefix to names of intermediate models being saved

Args

value : str: Appends a prefix to intermediate weights
system_dict : dict: System dictionary storing experiment state and set variables

Returns

dict: updated system dict

Expand source code

def set_intermediate_model_prefix(value, system_dict):
    '''
    Set a prefix to names of intermediate models being saved

    Args:
        value (str): Appends a prefix to intermediate weights
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["intermediate_model_prefix"] = value;
    return system_dict;

def set_num_epochs(num_epochs, system_dict)

Set number of training epochs

Args

num_epochs : int: Number of epochs to train the network
system_dict : dict: System dictionary storing experiment state and set variables

Returns

dict: updated system dict

Expand source code

def set_num_epochs(num_epochs, system_dict):
    '''
    Set number of training epochs

    Args:
        num_epochs (int): Number of epochs to train the network
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["hyper-parameters"]["num_epochs"] = num_epochs;
    return system_dict;

def set_save_intermediate_models(value, system_dict)

Set whether to save models post every epoch or not

Args

value : bool: If True, saves model weight post every epoch
system_dict : dict: System dictionary storing experiment state and set variables

Returns

dict: updated system dict

Expand source code

def set_save_intermediate_models(value, system_dict):
    '''
    Set whether to save models post every epoch or not

    Args:
        value (bool): If True, saves model weight post every epoch
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["save_intermediate_models"] = value;
    return system_dict;

def set_save_training_logs(value, system_dict)

Set whether to save training logs or not

Args

value : bool: If True, saves all training and validation metrics. Required for comparison.
system_dict : dict: System dictionary storing experiment state and set variables

Returns

dict: updated system dict

Expand source code

def set_save_training_logs(value, system_dict):
    '''
    Set whether to save training logs or not

    Args:
        value (bool): If True, saves all training and validation metrics. Required for comparison.
        system_dict (dict): System dictionary storing experiment state and set variables

    Returns:
        dict: updated system dict
    '''
    system_dict["training"]["settings"]["save_training_logs"] = value;
    return system_dict;