kernel_func_lin_dense_batch.py

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 # file: kernel_func_lin_dense_batch.py
 #===============================================================================
 # Copyright 2014-2019 Intel Corporation.
 #
 # This software and the related documents are Intel copyrighted  materials,  and
 # your use of  them is  governed by the  express license  under which  they were
 # provided to you (License).  Unless the License provides otherwise, you may not
 # use, modify, copy, publish, distribute,  disclose or transmit this software or
 # the related documents without Intel's prior written permission.
 #
 # This software and the related documents  are provided as  is,  with no express
 # or implied  warranties,  other  than those  that are  expressly stated  in the
 # License.
 #===============================================================================
 
 ## <a name="DAAL-EXAMPLE-PY-KERNEL_FUNCTION_LINEAR_DENSE_BATCH"></a>
 ## \example kernel_func_lin_dense_batch.py
 
 import os
 import sys
 
 from daal.algorithms import kernel_function
 from daal.data_management import FileDataSource, DataSourceIface
 
 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
 if utils_folder not in sys.path:
     sys.path.insert(0, utils_folder)
 from utils import printNumericTable
 
 DAAL_PREFIX = os.path.join('..', 'data')
 
 # Input data set parameters
 leftDatasetFileName = os.path.join(DAAL_PREFIX, 'batch', 'kernel_function.csv')
 rightDatasetFileName = os.path.join(DAAL_PREFIX, 'batch', 'kernel_function.csv')
 
 # Kernel algorithm parameters
 k = 1.0  # Linear kernel coefficient in the k(X,Y) + b model
 b = 0.0  # Linear kernel coefficient in the k(X,Y) + b model
 
 if __name__ == "__main__":
 
     # Initialize FileDataSource<CSVFeatureManager> to retrieve the input data from a .csv file
     leftDataSource = FileDataSource(
         leftDatasetFileName, DataSourceIface.doAllocateNumericTable,
         DataSourceIface.doDictionaryFromContext
     )
 
     rightDataSource = FileDataSource(
         rightDatasetFileName, DataSourceIface.doAllocateNumericTable,
         DataSourceIface.doDictionaryFromContext
     )
 
     # Retrieve the data from the input file
     leftDataSource.loadDataBlock()
     rightDataSource.loadDataBlock()
 
     # Create algorithm objects for the kernel algorithm using the default method
     algorithm = kernel_function.linear.Batch()
 
     # Set the kernel algorithm parameter
     algorithm.parameter.k = k
     algorithm.parameter.b = b
     algorithm.parameter.computationMode = kernel_function.matrixMatrix
 
     # Set an input data table for the algorithm
     algorithm.input.set(kernel_function.X, leftDataSource.getNumericTable())
     algorithm.input.set(kernel_function.Y, rightDataSource.getNumericTable())
 
     # Compute the linear kernel function and get the computed results
     # (Result class from daal.algorithms.kernel_function)
     result = algorithm.compute()
 
     # Print the results
     printNumericTable(result.get(kernel_function.values), "Values")
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