morpheus.messages.memory.inference_memory.InferenceMemory

(Latest Version)
class InferenceMemory(*, count=None, tensors=None)[source]

Bases: morpheus.messages.memory.tensor_memory.TensorMemory

This is a base container class for data that will be used for inference stages. This class is designed to hold generic tensor data in cupy arrays.

Attributes
tensor_names

Methods

get_input(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_input(name, tensor)

Update the input 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_input(name)[source]

Get the tensor stored in the container identified by name. Alias for InferenceMemory.get_tensor.

Parameters
namestr

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

Returns
cupy.ndarray

Inputs corresponding to name.

Raises
KeyError

If input name does not exist in the 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_input(name, tensor)[source]

Update the input tensor identified by name. Alias for InferenceMemory.set_tensor

Parameters
namestr

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

tensorcupy.ndarray

Tensor as a CuPy array.

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 11, 2023.