showing ValueError: Cannot feed value of shape (50, 41) for Tensor u'Placeholder:0', which has shape

[Vinayakumar R]

data set has 42 attributes and program is given below and please have a look on attached image for error

import csv

import tensorflow as tf

import random

import pandas as pd

import numpy as np

ipd = pd.read_csv("cla2/train.csv")

species = list(ipd['result'].unique())

ipd['One-hot'] = ipd['result'].map(lambda x: np.eye(len(species))[species.index(x)] )

shuffled = ipd.sample(frac=1)

trainingSet = shuffled[0:len(shuffled)-50]

testSet = shuffled[len(shuffled)-50:]

inp = tf.placeholder(tf.float32, [None, 4])

weights = tf.Variable(tf.zeros([4, 3]))

bias = tf.Variable(tf.zeros([3]))

y = tf.nn.softmax(tf.matmul(inp, weights) + bias)

y_ = tf.placeholder(tf.float32, [None, 3])

cross_entropy = -tf.reduce_sum(y_*tf.log(y))

train_step = tf.train.AdamOptimizer(0.01).minimize(cross_entropy)

correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))

accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))

init = tf.initialize_all_variables()

sess = tf.Session()

sess.run(init)

keys = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11','12','13','14','15','16','17','18','19','20','21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31','32','33','34','35','36','37','38','39','40','41']

for i in range(1000):

    train = trainingSet.sample(50)

    sess.run(train_step, feed_dict={inp: [x for x in train[keys].values],

                                    y_: [x for x in train['One-hot'].as_matrix()]})

print sess.run(accuracy, feed_dict={inp: [x for x in testSet[keys].values],

                                    y_: [x for x in testSet['One-hot'].values]})

[vaibhav jain]

Hi,

Are you able to solve your issue??

I'm trying to solve a simple ML problem with TF learn, But getting an error. Below I have added my code.

#!/usr/bin/env python
import os

os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

import tflearn

net = tflearn.input_data(shape=[None, 2]) # No of features is two
net = tflearn.fully_connected(net, 2) # No idea what the value should be
# net = tflearn.fully_connected(net, 2, activation='softmax')
net = tflearn.regression(net)

# Define model
model = tflearn.DNN(net)
data = [
    # Apple
    [105, 0],
    [110, 0],
    [100, 0],
    [140, 0],
    [130, 0],
    # Orange
    [150, 1],
    [155, 1],
    [160, 1],
    [170, 1],
    [190, 1],
]
labels = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1]

# Start training (apply gradient descent algorithm)
model.fit(data, labels, n_epoch=3, batch_size=2, show_metric=True)

pred = model.predict([[180, 0], [100, 0]])
print pred

"""
Getting error


Run id: RAATYL
Log directory: /tmp/tflearn_logs/
---------------------------------
Training samples: 10
Validation samples: 0
--

--
Traceback (most recent call last):
  File "./ml5.py", line 32, in <module>
    model.fit(data, labels, n_epoch=3, batch_size=2, show_metric=True)
  File "/home/prime/.virtualenvs/mllearn/local/lib/python2.7/site-packages/tflearn/models/dnn.py", line 216, in fit
    callbacks=callbacks)
  File "/home/prime/.virtualenvs/mllearn/local/lib/python2.7/site-packages/tflearn/helpers/trainer.py", line 338, in fit
    show_metric)
  File "/home/prime/.virtualenvs/mllearn/local/lib/python2.7/site-packages/tflearn/helpers/trainer.py", line 817, in _train
    feed_batch)
  File "/home/prime/.virtualenvs/mllearn/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 778, in run
    run_metadata_ptr)
  File "/home/prime/.virtualenvs/mllearn/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 961, in _run
    % (np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (2,) for Tensor u'TargetsData/Y:0', which has shape '(?, 2)'
"""