IPluginV2¶
-
class
tensorrt.
IPluginV2
¶ Plugin class for user-implemented layers.
Plugins are a mechanism for applications to implement custom layers. When combined with IPluginCreator it provides a mechanism to register plugins and look up the Plugin Registry during de-serialization.
Variables: - num_outputs –
int
The number of outputs from the layer. This is used by the implementations ofINetworkDefinition
andBuilder
. In particular, it is called prior to any call toinitialize()
. - tensorrt_version –
int
The API version with which this plugin was built. - plugin_type –
str
The plugin type. Should match the plugin name returned by the corresponding plugin creator - plugin_version –
str
The plugin version. Should match the plugin version returned by the corresponding plugin creator. - plugin_namespace –
str
The namespace that this plugin object belongs to. Ideally, all plugin objects from the same plugin library should have the same namespace. - serialization_size –
int
The size of the serialization buffer required.
-
clone
(self: tensorrt.tensorrt.IPluginV2) → tensorrt.tensorrt.IPluginV2¶ Clone the plugin object. This copies over internal plugin parameters and returns a new plugin object with these parameters.
-
configure_with_format
(self: tensorrt.tensorrt.IPluginV2, input_shapes: List[tensorrt.tensorrt.Dims], output_shapes: List[tensorrt.tensorrt.Dims], dtype: tensorrt.tensorrt.DataType, format: nvinfer1::TensorFormat, max_batch_size: int) → None¶ Configure the layer.
This function is called by the
Builder
prior toinitialize()
. It provides an opportunity for the layer to make algorithm choices on the basis of its weights, dimensions, and maximum batch size.The dimensions passed here do not include the outermost batch size (i.e. for 2D image networks, they will be 3D CHW dimensions).
Parameters: - input_shapes – The shapes of the input tensors.
- output_shapes – The shapes of the output tensors.
- dtype – The data type selected for the engine.
- format – The format selected for the engine.
- max_batch_size – The maximum batch size.
-
destroy
(self: tensorrt.tensorrt.IPluginV2) → None¶ Destroy the plugin object. This will be called when the
INetworkDefinition
,Builder
orICudaEngine
is destroyed.
-
execute_async
(self: tensorrt.tensorrt.IPluginV2, batch_size: int, inputs: List[capsule], outputs: List[capsule], workspace: capsule, stream_handle: int) → int¶ Execute the layer asynchronously.
Parameters: - batch_size – The number of inputs in the batch.
- inputs – The memory for the input tensors.
- outputs – The memory for the output tensors.
- workspace – Workspace for execution.
- stream_handle – The stream in which to execute the kernels.
Returns: 0 for success, else non-zero (which will cause engine termination).
-
get_output_shape
(self: tensorrt.tensorrt.IPluginV2, index: int, input_shapes: List[tensorrt.tensorrt.Dims]) → tensorrt.tensorrt.Dims¶ Get the dimension of an output tensor.
Parameters: - index – The index of the output tensor.
- input_shapes –
The shapes of the input tensors.
This function is called by the implementations of
INetworkDefinition
andBuilder
. In particular, it is called prior to any call toinitialize()
.
-
get_workspace_size
(self: tensorrt.tensorrt.IPluginV2, max_batch_size: int) → int¶ Find the workspace size required by the layer.
This function is called during engine startup, after
initialize()
. The workspace size returned should be sufficient for any batch size up to the maximum.Parameters: max_batch_size – int
The maximum possible batch size during inference.Returns: The workspace size.
-
initialize
(self: tensorrt.tensorrt.IPluginV2) → int¶ Initialize the layer for execution. This is called when the engine is created.
Returns: 0 for success, else non-zero (which will cause engine termination).
-
serialize
(self: tensorrt.tensorrt.IPluginV2) → memoryview¶ Serialize the plugin.
-
supports_format
(self: tensorrt.tensorrt.IPluginV2, dtype: tensorrt.tensorrt.DataType, format: nvinfer1::TensorFormat) → bool¶ Check format support.
This function is called by the implementations of
INetworkDefinition
,Builder
, andICudaEngine
. In particular, it is called when creating an engine and when deserializing an engine.Parameters: - dtype – Data type requested.
- format – TensorFormat requested.
Returns: True if the plugin supports the type-format combination.
-
terminate
(self: tensorrt.tensorrt.IPluginV2) → None¶ Release resources acquired during plugin layer initialization. This is called when the engine is destroyed.
- num_outputs –