qgd_nn.py

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"""
Created on Tue Jun 30 15:44:26 2020
Copyright 2020 Peter Rakyta, Ph.D.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

You should have received a copy of the GNU General Public License
along with this program.  If not, see http://www.gnu.org/licenses/.

@author: Peter Rakyta, Ph.D.
"""




import numpy as np
from os import path
from squander.nn.qgd_nn_Wrapper import qgd_nn_Wrapper




class qgd_nn(qgd_nn_Wrapper):
    
    

    def __init__( self ):

        # call the constructor of the wrapper class
        super(qgd_nn, self).__init__()



    def get_NN_Chanels(self, qbit_num=-1, levels=-1, samples_num=-1 ):

     # call the C wrapper function
        if qbit_num > 0 and levels >= 0 and samples_num < 2:
            dim_over_2 = int(pow(2, qbit_num-1))
            samples_num = 1
            chanels, nontrivial_adaptive_layers = super(qgd_nn, self).get_NN_Chanels( qbit_num=qbit_num, levels=levels )

        elif qbit_num > 0 and levels >= 0 and samples_num > 1:
            dim_over_2 = int(pow(2, qbit_num-1))
            chanels, nontrivial_adaptive_layers = super(qgd_nn, self).get_NN_Chanels( qbit_num=qbit_num, levels=levels, samples_num=samples_num ) 
           
        else:
            print( "invalid parameters were given")


        chanels = chanels.reshape( [samples_num, qbit_num, dim_over_2, dim_over_2, 4] )

        if ( not nontrivial_adaptive_layers is None ) :
            nontrivial_adaptive_layers = nontrivial_adaptive_layers.reshape( [samples_num, -1] )

        return chanels, nontrivial_adaptive_layers