tf.keras.utils.HDF5Matrix

Class `HDF5Matrix`

Defined in tensorflow/python/keras/utils/io_utils.py.

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

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.

`init`

__init__(
    datapath,
    dataset,
    start=0,
    end=None,
    normalizer=None
)

Initialize self. See help(type(self)) for accurate signature.

Properties

`dtype`

Gets the datatype of the dataset.

Returns:

A numpy dtype string.

`ndim`

Gets the number of dimensions (rank) of the dataset.

Returns:

An integer denoting the number of dimensions (rank) of the dataset.

`shape`

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

Returns:

A numpy-style shape tuple.

`size`

Gets the total dataset size (number of elements).

Returns:

An integer denoting the number of elements in the dataset.

Methods