morpheus.messages.memory.response_memory.ResponseMemoryAE

(Latest Version)
class ResponseMemoryAE(*args, **kwargs)[source]

Bases: morpheus.messages.memory.response_memory.ResponseMemory

Subclass of ResponseMemory specific to the AutoEncoder pipeline.

Parameters
probs

Probabilities tensor

user_id

User id the inference was performed against.

explain_df

Explainability Dataframe, for each feature a column will exist with a name in the form of: {feature}_z_loss containing the loss z-score along with max_abs_z and mean_abs_z columns

Attributes
explain_df

probs

tensor_names

Methods

get_output(name) Get the Tensor stored in the container identified by name.
get_tensor(name) Get the Tensor stored in the container identified by name.
get_tensors() Get the tensors contained by this instance.
has_tensor(name) Returns True if a tensor with the requested name exists in the tensors object
set_output(name, tensor) Update the output tensor identified by name.
set_tensor(name, tensor) Update the tensor identified by name.
set_tensors(tensors) Overwrite the tensors stored by this instance.
get_output(name)[source]

Get the Tensor stored in the container identified by name. Alias for ResponseMemory.get_tensor.

Parameters
name

Key used to do lookup in tensors dict of message container.

Returns
cupy.ndarray

Tensors corresponding to name.

Raises
KeyError

If output name does not exist in message container.

get_tensor(name)[source]

Get the Tensor stored in the container identified by name.

Parameters
name

Tensor key name.

Returns
cupy.ndarray

Tensor.

Raises
KeyError

If tensor name does not exist in the container.

get_tensors()[source]

Get the tensors contained by this instance. It is important to note that when C++ execution is enabled the returned tensors will be a Python copy of the tensors stored in the C++ object. As such any changes made to the tensors will need to be updated with a call to set_tensors.

Returns
typing.Dict[str, cp.ndarray]

has_tensor(name)[source]

Returns True if a tensor with the requested name exists in the tensors object

Parameters
name

Name to lookup

Returns
bool

True if the tensor was found

set_output(name, tensor)[source]

Update the output tensor identified by name. Alias for ResponseMemory.set_tensor

Parameters
name

Key used to do lookup in tensors dict of the container.

tensor

Tensor as a CuPy array.

Raises
ValueError

If the number of rows in tensor does not match count

set_tensor(name, tensor)[source]

Update the tensor identified by name.

Parameters
name

Tensor key name.

tensor

Tensor as a CuPy array.

Raises
ValueError

If the number of rows in tensor does not match count

set_tensors(tensors)[source]

Overwrite the tensors stored by this instance. If the length of the tensors has changed, then the count property should also be updated.

Parameters
tensors

Collection of tensors uniquely identified by a name.

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