Inputs CPU Raw Data

Inputs Info : cluster

inputs_data : array, contains the raw byte representation of the input tensor data, stored as a 1D flattened buffer.
inputs_shapes : array, specifies the shape of the input tensor. Since the data is stored as a flattened 1D buffer, this shape is necessary to reconstruct the original dimensions.
inputs string length : array, used when the tensor type is string. If the tensor has shape [5,3], this field contains 15 values, each representing the length of a corresponding string element. This ensures that the actual size of inputs_data is known despite variable string lengths.
inputs_ranks : array, indicates the rank of the tensor, i.e. the number of dimensions (Scalar = 0, 1D = 1, 2D = 2, etc.).
inputs_types : array, defines the ONNX tensor type as an enumerated value (e.g. FLOAT, INT64, STRING).

Losses Info : cluster

outputs_raw_data : array, contains the raw byte representation of the input tensor data, stored as a 1D flattened buffer.
output_shapes_array : array, specifies the shape of the input tensor. Since the data is stored as a flattened 1D buffer, this shape is necessary to reconstruct the original dimensions.
output_strings_length_array : array, used when the tensor type is string. If the tensor has shape [5,3], this field contains 15 values, each representing the length of a corresponding string element. This ensures that the actual size of inputs_data is known despite variable string lengths.
output_ranks_array : array, indicates the rank of the tensor, i.e. the number of dimensions (Scalar = 0, 1D = 1, 2D = 2, etc.).
output_types_array : array, defines the ONNX tensor type as an enumerated value (e.g. FLOAT, INT64, STRING).
losses_names : array, specifies which loss the data correspond to.