Refitter

class tensorrt.Refitter(self: tensorrt.tensorrt.Refitter, engine: tensorrt.tensorrt.ICudaEngine, logger: tensorrt.tensorrt.ILogger) → None

Updates weights in an ICudaEngine .

Variables

  • error_recorder – IErrorRecorder Application-implemented error reporting interface for TensorRT objects.

  • logger – ILogger The logger provided when creating the refitter.

Parameters

  • engine – The engine to refit.

  • logger – The logger to use.

__del__(self: tensorrt.tensorrt.Refitter) → None
__exit__(exc_type, exc_value, traceback)

Context managers are deprecated and have no effect. Objects are automatically freed when the reference count reaches 0.

__init__(self: tensorrt.tensorrt.Refitter, engine: tensorrt.tensorrt.ICudaEngine, logger: tensorrt.tensorrt.ILogger) → None
Parameters

  • engine – The engine to refit.

  • logger – The logger to use.

get_all(self: tensorrt.tensorrt.Refitter) → Tuple[List[str], List[tensorrt.tensorrt.WeightsRole]]

Get description of all weights that could be refitted.

Returns

The names of layers with refittable weights, and the roles of those weights.

get_all_weights(self: tensorrt.tensorrt.Refitter) → List[str]

Get names of all weights that could be refitted.

Returns

The names of refittable weights.

get_dynamic_range(self: tensorrt.tensorrt.Refitter, tensor_name: str) → tuple

Gets the dynamic range of a tensor. If the dynamic range was never set, returns the range computed during calibration.

Parameters

tensor_name – The name of the tensor whose dynamic range to retrieve.

Returns

Tuple[float, float] A tuple containing the [minimum, maximum] of the dynamic range.

get_missing(self: tensorrt.tensorrt.Refitter) → Tuple[List[str], List[tensorrt.tensorrt.WeightsRole]]

Get description of missing weights.

For example, if some Weights have been set, but the engine was optimized in a way that combines weights, any unsupplied Weights in the combination are considered missing.

Returns

The names of layers with missing weights, and the roles of those weights.

get_missing_weights(self: tensorrt.tensorrt.Refitter) → List[str]

Get names of missing weights.

For example, if some Weights have been set, but the engine was optimized in a way that combines weights, any unsupplied Weights in the combination are considered missing.

Returns

The names of missing weights, empty string for unnamed weights.

get_tensors_with_dynamic_range(self: tensorrt.tensorrt.Refitter) → List[str]

Get names of all tensors that have refittable dynamic ranges.

Returns

The names of tensors with refittable dynamic ranges.

refit_cuda_engine(self: tensorrt.tensorrt.Refitter) → bool

Updates associated engine. Return True if successful.

Failure occurs if get_missing() != 0 before the call.

set_dynamic_range(self: tensorrt.tensorrt.Refitter, tensor_name: str, range: List[float]) → bool

Update dynamic range for a tensor.

Parameters

  • tensor_name – The name of the tensor whose dynamic range to update.

  • range – The new range.

Returns

True if successful, False otherwise.

Returns false if there is no Int8 engine tensor derived from a network tensor of that name. If successful, then get_missing() may report that some weights need to be supplied.

set_named_weights(self: tensorrt.tensorrt.Refitter, name: str, weights: tensorrt.tensorrt.Weights) → bool

Specify new weights of given name. Possible reasons for rejection are:

  • The name of weights is empty or does not correspond to any refittable weights.

  • The number of weights is inconsistent with the original specification.

Modifying the weights before method refit_cuda_engine() completes will result in undefined behavior.

Parameters

  • name – The name of the weights to be refitted.

  • weights – The new weights to associate with the name.

Returns

True on success, or False if new weights are rejected.

set_weights(self: tensorrt.tensorrt.Refitter, layer_name: str, role: tensorrt.tensorrt.WeightsRole, weights: tensorrt.tensorrt.Weights) → bool

Specify new weights for a layer of given name. Possible reasons for rejection are:

  • There is no such layer by that name.

  • The layer does not have weights with the specified role.

  • The number of weights is inconsistent with the layer’s original specification.

Modifying the weights before refit_cuda_engine() completes will result in undefined behavior.

Parameters

  • layer_name – The name of the layer.

  • role – The role of the weights. See WeightsRole for more information.

  • weights – The weights to refit with.

Returns

True on success, or False if new weights are rejected.