Python* API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

kernel_func_lin_dense_batch.py

1 # file: kernel_func_lin_dense_batch.py
2 #===============================================================================
3 # Copyright 2014-2020 Intel Corporation
4 #
5 # Licensed under the Apache License, Version 2.0 (the "License");
6 # you may not use this file except in compliance with the License.
7 # You may obtain a copy of the License at
8 #
9 # http://www.apache.org/licenses/LICENSE-2.0
10 #
11 # Unless required by applicable law or agreed to in writing, software
12 # distributed under the License is distributed on an "AS IS" BASIS,
13 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 # See the License for the specific language governing permissions and
15 # limitations under the License.
16 #===============================================================================
17 
18 
19 
20 
21 import os
22 import sys
23 
24 from daal.algorithms import kernel_function
25 from daal.data_management import FileDataSource, DataSourceIface
26 
27 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
28 if utils_folder not in sys.path:
29  sys.path.insert(0, utils_folder)
30 from utils import printNumericTable
31 
32 DAAL_PREFIX = os.path.join('..', 'data')
33 
34 # Input data set parameters
35 leftDatasetFileName = os.path.join(DAAL_PREFIX, 'batch', 'kernel_function.csv')
36 rightDatasetFileName = os.path.join(DAAL_PREFIX, 'batch', 'kernel_function.csv')
37 
38 # Kernel algorithm parameters
39 k = 1.0 # Linear kernel coefficient in the k(X,Y) + b model
40 b = 0.0 # Linear kernel coefficient in the k(X,Y) + b model
41 
42 if __name__ == "__main__":
43 
44  # Initialize FileDataSource<CSVFeatureManager> to retrieve the input data from a .csv file
45  leftDataSource = FileDataSource(
46  leftDatasetFileName, DataSourceIface.doAllocateNumericTable,
47  DataSourceIface.doDictionaryFromContext
48  )
49 
50  rightDataSource = FileDataSource(
51  rightDatasetFileName, DataSourceIface.doAllocateNumericTable,
52  DataSourceIface.doDictionaryFromContext
53  )
54 
55  # Retrieve the data from the input file
56  leftDataSource.loadDataBlock()
57  rightDataSource.loadDataBlock()
58 
59  # Create algorithm objects for the kernel algorithm using the default method
60  algorithm = kernel_function.linear.Batch()
61 
62  # Set the kernel algorithm parameter
63  algorithm.parameter.k = k
64  algorithm.parameter.b = b
65  algorithm.parameter.computationMode = kernel_function.matrixMatrix
66 
67  # Set an input data table for the algorithm
68  algorithm.input.set(kernel_function.X, leftDataSource.getNumericTable())
69  algorithm.input.set(kernel_function.Y, rightDataSource.getNumericTable())
70 
71  # Compute the linear kernel function and get the computed results
72  # (Result class from daal.algorithms.kernel_function)
73  result = algorithm.compute()
74 
75  # Print the results
76  printNumericTable(result.get(kernel_function.values), "Values")

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