python - ValueError: setting an array element with a sequence. -


i working on classification problem using iris dataset , having trouble valueerror: setting array element sequence. converted dataset numpy.ndarray still having same error here code

import tensorflow tf  import numpy np  import pandas pd   rawdata = pd.read_csv('/home/akki/desktop/tf/iris.csv') print(np.shape(rawdata)) rawdatashuffel = rawdata.reindex(np.random.permutation(rawdata.index)).as_matrix()   data = rawdatashuffel[:,range(0,7)] print(np.shape(data)) labels = rawdatashuffel[:,8] print(np.shape(labels)) ############################################################## # 1 hot genration number_of_op_class = 3 lab = np.eye(number_of_op_class) print(lab) #print(type(lab[0]))  ########################################################################### # converting label 1 hot in range(0,100):     if labels[i] == 'setosa':         labels[i] = lab[0]     elif labels[i] == 'versicolor':         labels[i] = lab[1]     elif labels[i] == 'virginica':         labels[i] = lab[2] print(labels) print(type(labels)) #labels = np.asarray(labels)      train_data = data[range(0,79),:]  train_label = labels[range(0,79)]  test_data = data[range(80,99),:] test_labels = labels[range(80,99)]  #print(test_labels)  x = tf.placeholder(tf.float32) y_ = tf.placeholder(tf.float32)  w=tf.variable(tf.zeros([8,3])) b=tf.variable(tf.zeros([3]))  y = tf.nn.softmax(tf.matmul(x, w) + b) cross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y))  #optimiser - train_step = tf.train.adamoptimizer(0.01).minimize(cross_entropy) #calculating accuracy of our model  correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1)) accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))   #session parameters sess = tf.interactivesession() #initialising variables init = tf.initialize_all_variables() sess.run(init) #number of interations epoch=2000  step in range(epoch):    _, c=sess.run([train_step,cross_entropy], feed_dict={x: train_data, y_: train_label})     if step%500==0 :        print(c)

the error getting is

traceback (most recent call last):   file "iris.py", line 70, in <module>     _, c=sess.run([train_step,cross_entropy], feed_dict={x: train_data, y_: train_label})   file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 372, in run run_metadata_ptr)   file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 619, in _run     np_val = np.array(subfeed_val, dtype=subfeed_dtype) valueerror: setting array element sequence.


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