mindarmour.utils

Util methods of MindArmour.

class mindarmour.utils.GradWrap(network)[source]

Construct a network to compute the gradient of network outputs in input space and weighted by weight, expressed as a jacobian matrix.

Parameters: network (Cell) – The target network to wrap.

Examples

>>> data = Tensor(np.ones([1, 1, 32, 32]).astype(np.float32)*0.01)
>>> label = Tensor(np.ones([1, 10]).astype(np.float32))
>>> num_classes = 10
>>> sens = np.zeros((data.shape[0], num_classes)).astype(np.float32)
>>> sens[:, 1] = 1.0
>>> net = NET()
>>> wrap_net = GradWrap(net)
>>> wrap_net(data, Tensor(sens))

construct(*data)[source]

Compute jacobian matrix.

Parameters: data (Tensor) – Data consists of inputs and weight. - inputs: Inputs of network. - weight: Weight of each gradient, ‘weight’ has the same shape with labels.
Returns: Tensor, Jacobian matrix.

class mindarmour.utils.GradWrapWithLoss(network)[source]

Construct a network to compute the gradient of loss function in input space and weighted by weight.

Parameters: network (Cell) – The target network to wrap.

Examples

>>> data = Tensor(np.ones([1, 1, 32, 32]).astype(np.float32)*0.01)
>>> labels = Tensor(np.ones([1, 10]).astype(np.float32))
>>> net = NET()
>>> loss_fn = nn.SoftmaxCrossEntropyWithLogits()
>>> loss_net = WithLossCell(net, loss_fn)
>>> grad_all = GradWrapWithLoss(loss_net)
>>> out_grad = grad_all(data, labels)

construct(inputs, labels)[source]

Compute gradient of inputs with labels and weight.

Parameters

inputs (Tensor) – Inputs of network.
labels (Tensor) – Labels of inputs.

Returns

Tensor, gradient matrix.

class mindarmour.utils.LogUtil[source]

Logging module.

Raises: SyntaxError – If create this class.

add_handler(handler)[source]

Add other handler supported by logging module.

Parameters: handler (logging.Handler) – Other handler supported by logging module.
Raises: ValueError – If handler is not an instance of logging.Handler.

debug(tag, msg, *args)[source]

Log ‘[tag] msg % args’ with severity ‘DEBUG’.

Parameters

tag (str) – Logger tag.
msg (str) – Logger message.
args (Any) – Auxiliary value.

error(tag, msg, *args)[source]

Log ‘[tag] msg % args’ with severity ‘ERROR’.

Parameters

tag (str) – Logger tag.
msg (str) – Logger message.
args (Any) – Auxiliary value.

static get_instance()[source]

Get instance of class LogUtil.

Returns: Object, instance of class LogUtil.

info(tag, msg, *args)[source]

Log ‘[tag] msg % args’ with severity ‘INFO’.

Parameters

tag (str) – Logger tag.
msg (str) – Logger message.
args (Any) – Auxiliary value.

set_level(level)[source]

Set the logging level of this logger, level must be an integer or a string. Supported levels are ‘NOTSET’(integer: 0), ‘ERROR’(integer: 1-40), ‘WARNING’(‘WARN’, integer: 1-30), ‘INFO’(integer: 1-20) and ‘DEBUG’(integer: 1-10). For example, if logger.set_level(‘WARNING’) or logger.set_level(21), then logger.warn() and logger.error() in scripts would be printed while running, while logger.info() or logger.debug() would not be printed.

Parameters: level (Union[int, str]) – Level of logger.

warn(tag, msg, *args)[source]

Log ‘[tag] msg % args’ with severity ‘WARNING’.

Parameters

tag (str) – Logger tag.
msg (str) – Logger message.
args (Any) – Auxiliary value.