HDF5Matrix documentation (#3931)
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@ -83,6 +83,7 @@ from keras import backend
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from keras import constraints
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from keras import activations
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from keras import regularizers
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from keras.utils import io_utils
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EXCLUDE = {
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@ -237,6 +238,12 @@ PAGES = [
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'page': 'backend.md',
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'all_module_functions': [backend],
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},
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{
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'page': 'io_utils.md',
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'classes': [
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io_utils.HDF5Matrix
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],
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},
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]
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ROOT = 'http://keras.io/'
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@ -49,6 +49,8 @@ pages:
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- Constraints: constraints.md
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- Visualization: visualization.md
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- Scikit-learn API: scikit-learn-api.md
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- Utils:
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- I/O Utils: io_utils.md
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@ -6,6 +6,30 @@ from collections import defaultdict
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class HDF5Matrix():
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'''Representation of HDF5 dataset which can be used instead of a
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Numpy array.
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# Example
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```python
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X_data = HDF5Matrix('input/file.hdf5', 'data')
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model.predict(X_data)
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```
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Providing start and end allows use of a slice of the dataset.
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Optionally, a normalizer function (or lambda) can be given. This will
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be called on every slice of data retrieved.
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# Arguments
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datapath: string, path to a HDF5 file
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dataset: string, name of the HDF5 dataset in the file specified
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in datapath
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start: int, start of desired slice of the specified dataset
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end: int, end of desired slice of the specified dataset
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normalizer: function to be called on data when retrieved
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'''
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refs = defaultdict(int)
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def __init__(self, datapath, dataset, start, end, normalizer=None):
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