tf.keras.utils.HDF5Matrix

TensorFlow 1 version View source on GitHub

Representation of HDF5 dataset to be used instead of a Numpy array.

tf.keras.utils.HDF5Matrix(
    datapath, dataset, start=0, end=None, normalizer=None
)

Example:

    x_data = HDF5Matrix('input/file.hdf5', 'data')
    model.predict(x_data)

Providing start and end allows use of a slice of the dataset.

Optionally, a normalizer function (or lambda) can be given. This will be called on every slice of data retrieved.

Arguments:

  • datapath: string, path to a HDF5 file
  • dataset: string, name of the HDF5 dataset in the file specified in datapath
  • start: int, start of desired slice of the specified dataset
  • end: int, end of desired slice of the specified dataset
  • normalizer: function to be called on data when retrieved

Returns:

An array-like HDF5 dataset.

Attributes:

  • dtype: Gets the datatype of the dataset.

  • ndim: Gets the number of dimensions (rank) of the dataset.

  • shape: Gets a numpy-style shape tuple giving the dataset dimensions.

  • size: Gets the total dataset size (number of elements).

Methods

__getitem__

View source

__getitem__(
    key
)

__len__

View source

__len__()

Class Variables

  • refs