Model Warmup
          model_navigator.api.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.
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inputs(Dict[str, ModelWarmupInput]) –The warmup meta data associated with every model input, including control tensors.
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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.api.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
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dtype(Optional[Union[dtype, Type[dtype]]]) –Data type
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input_data_type(ModelWarmupInputDataType) –Type of input data used for warmup
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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.api.triton.ModelWarmupInputDataType
            Bases: Enum
Model warmup input data type.
Read more in Triton Inference server model configuration
Parameters:
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ZERO–"ZERO"
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RANDOM–"RANDOM"
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FILE–"FILE"