Python* API Reference for Intel® Data Analytics Acceleration Library 2019 Update 5

kernel_func_lin_dense_batch.py

1 # file: kernel_func_lin_dense_batch.py
2 #===============================================================================
3 # Copyright 2014-2019 Intel Corporation.
4 #
5 # This software and the related documents are Intel copyrighted materials, and
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 
17 
18 
19 import os
20 import sys
21 
22 from daal.algorithms import kernel_function
23 from daal.data_management import FileDataSource, DataSourceIface
24 
25 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
26 if utils_folder not in sys.path:
27  sys.path.insert(0, utils_folder)
28 from utils import printNumericTable
29 
30 DAAL_PREFIX = os.path.join('..', 'data')
31 
32 # Input data set parameters
33 leftDatasetFileName = os.path.join(DAAL_PREFIX, 'batch', 'kernel_function.csv')
34 rightDatasetFileName = os.path.join(DAAL_PREFIX, 'batch', 'kernel_function.csv')
35 
36 # Kernel algorithm parameters
37 k = 1.0 # Linear kernel coefficient in the k(X,Y) + b model
38 b = 0.0 # Linear kernel coefficient in the k(X,Y) + b model
39 
40 if __name__ == "__main__":
41 
42  # Initialize FileDataSource<CSVFeatureManager> to retrieve the input data from a .csv file
43  leftDataSource = FileDataSource(
44  leftDatasetFileName, DataSourceIface.doAllocateNumericTable,
45  DataSourceIface.doDictionaryFromContext
46  )
47 
48  rightDataSource = FileDataSource(
49  rightDatasetFileName, DataSourceIface.doAllocateNumericTable,
50  DataSourceIface.doDictionaryFromContext
51  )
52 
53  # Retrieve the data from the input file
54  leftDataSource.loadDataBlock()
55  rightDataSource.loadDataBlock()
56 
57  # Create algorithm objects for the kernel algorithm using the default method
58  algorithm = kernel_function.linear.Batch()
59 
60  # Set the kernel algorithm parameter
61  algorithm.parameter.k = k
62  algorithm.parameter.b = b
63  algorithm.parameter.computationMode = kernel_function.matrixMatrix
64 
65  # Set an input data table for the algorithm
66  algorithm.input.set(kernel_function.X, leftDataSource.getNumericTable())
67  algorithm.input.set(kernel_function.Y, rightDataSource.getNumericTable())
68 
69  # Compute the linear kernel function and get the computed results
70  # (Result class from daal.algorithms.kernel_function)
71  result = algorithm.compute()
72 
73  # Print the results
74  printNumericTable(result.get(kernel_function.values), "Values")

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