morpheus.messages.memory.response_memory.ResponseMemoryProbs

class ResponseMemoryProbs(*args, **kwargs)[source]

Bases: morpheus.messages.memory.response_memory.ResponseMemory

Subclass of ResponseMemory containng an output tensor named ‘probs’.

Parameters
probscupy.ndarray

Probabilities tensor

Attributes
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
namestr

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
namestr

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
namestr

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
namestr

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

tensorcupy.ndarray

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
namestr

Tensor key name.

tensorcupy.ndarray

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
tensorstyping.Dict[str, cupy.ndarray]

Collection of tensors uniquely identified by a name.

© Copyright 2023, NVIDIA. Last updated on Apr 19, 2023.