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Representation of HDF5 dataset to be used instead of a Numpy array.
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). |
__getitem__
__getitem__( key )
__len__
__len__()
refs
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/utils/HDF5Matrix