Model Warmup
model_navigator.triton.ModelWarmup
dataclass
Model warmup configuration.
Read more in Triton Inference server model configuration
Parameters:
-
batch_size
(int
, default:1
) –The batch size of the inference request. This must be >= 1. For models that don't support batching, batch_size must be 1.
-
inputs
(Dict[str, ModelWarmupInput]
) –The warmup meta data associated with every model input, including control tensors.
-
iterations
(int
, default:0
) –The number of iterations that this warmup sample will be executed. For example, if this field is set to 2, 2 model executions using this sample will be scheduled for warmup. Default value is 0 which indicates that this sample will be used only once.
__post_init__
Validate the configuration for early error handling.
Source code in model_navigator/triton/specialized_configs/common.py
model_navigator.triton.ModelWarmupInput
dataclass
Model warmup input configuration.
Read more in Triton Inference server model configuration
Parameters:
-
shape
(Tuple[int, ...]
) –Shape of the model input/output
-
dtype
(Optional[Union[dtype, Type[dtype]]]
) –Data type
-
input_data_type
(ModelWarmupInputDataType
) –Type of input data used for warmup
-
input_data_file
(Optional[Path]
, default:None
) –Path to file with input data. Provide the path where the file is located. Required only when input_data_type is
ModelWarmupInputDataType.DATA_FILE
__post_init__
Validate the configuration for early error handling.
Source code in model_navigator/triton/specialized_configs/common.py
model_navigator.triton.ModelWarmupInputDataType
Bases: Enum
Model warmup input data type.
Read more in Triton Inference server model configuration
Parameters:
-
ZERO
–"ZERO"
-
RANDOM
–"RANDOM"
-
FILE
–"FILE"