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Source code for nets.data.example

import numpy as np


[docs]class Field(object): r""" A ``Field`` defines the data to process from a raw dataset. It will convert the data into a tensor. The data can be a string, integers, float etc. The data is meant to be preprocessed and the attribute ``transform`` handles the way the user want to process the raw data. """ def __init__(self, transform=None, dtype=None): self.transform = transform self.dtype = dtype
[docs] def process(self, value): """Applies the transformation and changes the data's type if necessary. Args: value (Tensor): Returns: """ if self.transform is not None: value = self.transform(value) if self.dtype is not None: value = value.astype(self.dtype) return value
[docs]class Example(object): r""" Store a single training / testing example, and store it as an attribute. Highly inspired from PyTorch [example](https://github.com/pytorch/text/blob/master/torchtext/data/example.py) """
[docs] @classmethod def fromlist(cls, values, fields): """ Add an example from a list of data with respect to the fields. Args: values: raw data fields (tuple(string, Field)): fields to preprocess the data on Returns: None """ example = cls() for (value, field) in zip(values, fields): assert len(field) == 2, f"expected a field template similar to \ ('name_field', Field()) but got {format(field)}" assert isinstance(field[1], Field), f"expected a field template similar to \ ('name_field', Field()) but got {format(field)}" name = field[0] value = field[1].process(value) setattr(example, name, value) return example

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