`trw.simple_layers.compiled_net`¶

Careful here: we MUST use ordered set as order of execution is important! If not there may be inconsistencies between compiled net and executed net

Module Contents¶

Classes¶

`RuntimeAction`	Specifies the type of runtime action (e.g., execution of a node, release of node's state or evaluation of a node)
`CompiledNet`	Encapsulate a compiled network so that we can efficiently calculate the outputs
`EmptyModule`	Defines an empty module (i.e., equivalent to None but for nn.Module so that it can be stored in a
`WrapperModule`	nn.ModuleList can only store nn.Module so create a wrapper that can be stored in a nn.ModuleList

Functions¶

`find_layer_type`(nodes: list, layer_type)	Find all layer with a given type
`nodes_mark_output_dependencies`(output_nodes: list)	Marks nodes by output IDs
`remove_weak_ref`(nodes: list)	Run through all the nodes of the graph and remove weakref.
`create_weak_ref`(output_nodes: list)	Re-create the weakref references of the children for the given output_nodes recursively
`_prepare_inputs`(action, states)
`compile_nn`(output_nodes: list, other_outputs_to_keep_alive=None, remove_checks=False)	Compile a network to calculate output_nodes

trw.simple_layers.compiled_net.find_layer_type(nodes: list, layer_type)¶

Find all layer with a given type

Parameters

nodes – the starting nodes [list]
layer_type – the type of the nodes to collect

Returns

a list of nodes of the corresponding type

trw.simple_layers.compiled_net.nodes_mark_output_dependencies(output_nodes: list)¶

Marks nodes by output IDs

Parameters: output_nodes – a list of output nodes to be marked
Returns: nodes with a set of output IDs

trw.simple_layers.compiled_net.remove_weak_ref(nodes: list)¶

Run through all the nodes of the graph and remove weakref.

weakref are an issue when importing or exporting the network with pickle.: We can safely remove these weakref and reconstruct them if necessary.

Parameters: nodes – the starting nodes [list]
Returns: None

trw.simple_layers.compiled_net.create_weak_ref(output_nodes: list)¶

Re-create the weakref references of the children for the given output_nodes recursively

Parameters: output_nodes – a list of output nodes to have the children weak ref updated
Returns: None

class trw.simple_layers.compiled_net.RuntimeAction¶

Bases: enum.Enum

Specifies the type of runtime action (e.g., execution of a node, release of node’s state or evaluation of a node)

EXECUTE_NODE = 1¶

REMOVE_STATE = 2¶

EVALUATE_STATE = 3¶

trw.simple_layers.compiled_net._prepare_inputs(action, states)¶

class trw.simple_layers.compiled_net.CompiledNet(remove_checks=False)¶

Bases: torch.nn.Module

Encapsulate a compiled network so that we can efficiently calculate the outputs: of the network.

forward(self, batch)¶

Calculate the outputs of a network

Parameters: batch – (dict) a dictionary like of features
Returns: a dictionary of outputs

__getstate__(self)¶

__setstate__(self, state)¶

class trw.simple_layers.compiled_net.EmptyModule¶

Bases: torch.nn.Module

Defines an empty module (i.e., equivalent to None but for nn.Module so that it can be stored in a nn.ModuleList)

class trw.simple_layers.compiled_net.WrapperModule(module)¶

Bases: torch.nn.Module

nn.ModuleList can only store nn.Module so create a wrapper that can be stored in a nn.ModuleList

forward(self, i)¶

trw.simple_layers.compiled_net.compile_nn(output_nodes: list, other_outputs_to_keep_alive=None, remove_checks=False)¶

Compile a network to calculate output_nodes

Parameters

output_nodes – the output nodes to calculate. The order of the nodes indicates the order of the calculation and impacts the book-keeping of the shared calculation in multiple output networks
other_outputs_to_keep_alive – keeps alive unused output nodes
remove_checks – if True, some runtime checks will be disabled. This can be useful for example FCNN where the output shape will depend on the input shape

Returns

a CompiledNet

trw.simple_layers.compiled_net¶

Module Contents¶

Classes¶

Functions¶

`trw.simple_layers.compiled_net`¶