# weights['out'] = tf.get_variable('out',shape=[dimension,2], initializer=tf.contrib.layers.xavier_initializer()) # biases['out'] = tf.Variable(tf.random_normal([2])) return weights, biases weights, biases = loadWeightsAndBiases() sess = tf.Session() init = tf.global_variables_initializer() sess.run(init) bS = 450 vBS = 1 print("before data loads") dataObject = dh.COCOData(batchsize=int(bS / 2), vbatchsize=vBS) dataObject.dataLoadByName(objectIDNames[0]) dataObject.loadPureDataByIdName(objectIDNames[0]) pureD, pureL = dataObject.pureData[0], np.asarray( [[0, 1] for i in range(len(dataObject.pureData[0]))]) anythingElseD, anythingElseL = dataObject.dataLoadAnythingElse() print("after data loads") dataPointP = getDataPoint(pureD[0:int(bS / 2)], weights, biases, int(bS / 2), answers=pureL[0:int(bS / 2)]) dataPointAE = getDataPoint(anythingElseD[0:int(bS / 2)],