Python* API Reference for Intel® Data Analytics Acceleration Library 2019

serialization.py

1 # file: serialization.py
2 #===============================================================================
3 # Copyright 2014-2018 Intel Corporation.
4 #
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6 # your use of them is governed by the express license under which they were
7 # provided to you (License). Unless the License provides otherwise, you may not
8 # use, modify, copy, publish, distribute, disclose or transmit this software or
9 # the related documents without Intel's prior written permission.
10 #
11 # This software and the related documents are provided as is, with no express
12 # or implied warranties, other than those that are expressly stated in the
13 # License.
14 #===============================================================================
15 
16 ## <a name="DAAL-EXAMPLE-PY-SERIALIZATION"></a>
17 ## \example serialization.py
18 
19 import os
20 import sys
21 
22 import numpy as np
23 
24 from daal.data_management import HomogenNumericTable, FileDataSource, DataSource, InputDataArchive, OutputDataArchive
25 
26 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
27 if utils_folder not in sys.path:
28  sys.path.insert(0, utils_folder)
29 from utils import printNumericTable
30 
31 # Input data set parameters
32 datasetFileName = os.path.join('..', 'data', 'batch', 'serialization.csv')
33 
34 
35 def serializeNumericTable(dataTable):
36 
37  # Create a data archive to serialize the numeric table
38  dataArch = InputDataArchive()
39 
40  # Serialize the numeric table into the data archive
41  dataTable.serialize(dataArch)
42 
43  # Get the length of the serialized data in bytes
44  length = dataArch.getSizeOfArchive()
45 
46  # Store the serialized data in an array
47  buffer = np.zeros(length, dtype=np.ubyte)
48  dataArch.copyArchiveToArray(buffer)
49 
50  return buffer
51 
52 
53 def deserializeNumericTable(buffer):
54 
55  # Create a data archive to deserialize the numeric table
56  dataArch = OutputDataArchive(buffer)
57 
58  # Create a numeric table object
59  dataTable = HomogenNumericTable()
60 
61  # Deserialize the numeric table from the data archive
62  dataTable.deserialize(dataArch)
63 
64  return dataTable
65 
66 
67 if __name__ == "__main__":
68 
69  # Initialize FileDataSource_CSVFeatureManager to retrieve the input data from a .csv file
70  dataSource = FileDataSource(
71  datasetFileName, DataSource.doAllocateNumericTable, DataSource.doDictionaryFromContext
72  )
73 
74  # Retrieve the data from the input file
75  dataSource.loadDataBlock()
76 
77  # Retrieve a numeric table
78  dataTable = dataSource.getNumericTable()
79 
80  # Print the original data
81  printNumericTable(dataTable, "Data before serialization:")
82 
83  # Serialize the numeric table into the memory buffer
84  buffer = serializeNumericTable(dataTable)
85 
86  # Deserialize the numeric table from the memory buffer
87  restoredDataTable = deserializeNumericTable(buffer)
88 
89  # Print the restored data
90  printNumericTable(restoredDataTable, "Data after deserialization:")

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