Utils

Utility modules for OpenDDI framework.

logger

class openddi.utils.logger.Logger(filename)[source]

Bases: object

Custom logger class for handling both file and console logging.

Parameters:

filename (str) – Path to the log file

__init__(filename)[source]
debug(message)[source]

Log debug level message.

Parameters:

message (str) – Message to log

info(message)[source]

Log info level message.

Parameters:

message (str) – Message to log

warning(message)[source]

Log warning level message.

Parameters:

message (str) – Message to log

error(message)[source]

Log error level message.

Parameters:

message (str) – Message to log

critical(message)[source]

Log critical level message.

Parameters:

message (str) – Message to log

openddi.utils.logger.create_logger(args)[source]

Create and configure a logger instance with timestamp and model name.

Parameters:

args – Configuration arguments containing model information

Returns:

Configured logger instance

Return type:

Logger

Logger

class openddi.utils.logger.Logger(filename)[source]

Bases: object

Custom logger class for handling both file and console logging.

Parameters:

filename (str) – Path to the log file

__init__(filename)[source]
debug(message)[source]

Log debug level message.

Parameters:

message (str) – Message to log

info(message)[source]

Log info level message.

Parameters:

message (str) – Message to log

warning(message)[source]

Log warning level message.

Parameters:

message (str) – Message to log

error(message)[source]

Log error level message.

Parameters:

message (str) – Message to log

critical(message)[source]

Log critical level message.

Parameters:

message (str) – Message to log

create_logger

openddi.utils.logger.create_logger(args)[source]

Create and configure a logger instance with timestamp and model name.

Parameters:

args – Configuration arguments containing model information

Returns:

Configured logger instance

Return type:

Logger

utils

openddi.utils.utils.set_random_seed(seed, deterministic=False)[source]
openddi.utils.utils.normalize(mx)[source]
openddi.utils.utils.normalize_adj(adj)[source]
openddi.utils.utils.skip_adj(adj)[source]
openddi.utils.utils.sparse_mx_to_torch_sparse_tensor(sparse_mx)[source]
openddi.utils.utils.compute_multiclass_metrics(y_true, y_pred)[source]
openddi.utils.utils.plot_metric(history, metric_name, save_path)[source]
openddi.utils.utils.ensure_dir(path)[source]

set_random_seed

openddi.utils.utils.set_random_seed(seed, deterministic=False)[source]

normalize

openddi.utils.utils.normalize(mx)[source]

normalize_adj

openddi.utils.utils.normalize_adj(adj)[source]

skip_adj

openddi.utils.utils.skip_adj(adj)[source]

sparse_mx_to_torch_sparse_tensor

openddi.utils.utils.sparse_mx_to_torch_sparse_tensor(sparse_mx)[source]

compute_multiclass_metrics

openddi.utils.utils.compute_multiclass_metrics(y_true, y_pred)[source]

plot_metric

openddi.utils.utils.plot_metric(history, metric_name, save_path)[source]

ensure_dir

openddi.utils.utils.ensure_dir(path)[source]

config