tf.keras.utils.HDF5Matrix

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

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.utils.HDF5Matrix, `tf.compat.v2.keras.utils.HDF5Matrix`

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

    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__(
    key
)

__len__()