** ValueError: setting an array element with a sequence** :

From the code you showed us, the only thing we can tell is that you are trying to create an array from a list that isn’t shaped like a multi-dimensional array. For example

```
numpy.array([[1,2], [2, 3, 4]]) # wrong!
```

or

```
numpy.array([[1,2], [2, [3, 4]]]) # wrong!
```

will yield this error message, because the shape of the input list isn’t a (generalised) “box” that can be turned into a multidimensional array. So probably `UnFilteredDuringExSummaryOfMeansArray`

contains sequences of different lengths.

Another possible cause for this error message is trying to use a string as an element in an array of type `float`

:

```
numpy.array([1.2, "abc"], dtype=float) # wrong!
```

That is what you are trying according to your edit. If you really want to have a NumPy array containing both strings and floats, you could use the dtype `object`

, which enables the array to hold arbitrary Python objects:

```
numpy.array([1.2, "abc"], dtype=object)
```

Without knowing what your code is supposed to accomplish, I can’t tell if this is what you want.

**The Python ValueError:**

```
ValueError: setting an array element with a sequence.
```

Means exactly what it says, you’re trying to cram a sequence of numbers into a single number slot. It can be thrown under various circumstances.

**1. When you pass a python tuple or list to be interpreted as a numpy array element:**

```
import numpy
numpy.array([1,2,3]) #good
numpy.array([1, (2,3)]) #Fail, can't convert a tuple into a numpy
#array element
numpy.mean([5,(6+7)]) #good
numpy.mean([5,tuple(range(2))]) #Fail, can't convert a tuple into a numpy
#array element
def foo():
return 3
numpy.array([2, foo()]) #good
def foo():
return [3,4]
numpy.array([2, foo()]) #Fail, can't convert a list into a numpy
#array element
```

**2. By trying to cram a numpy array length > 1 into a numpy array element:**

```
x = np.array([1,2,3])
x[0] = np.array([4]) #good
x = np.array([1,2,3])
x[0] = np.array([4,5]) #Fail, can't convert the numpy array to fit
#into a numpy array element
```

A numpy array is being created, and numpy doesn’t know how to cram multivalued tuples or arrays into single element slots. It expects whatever you give it to evaluate to a single number, if it doesn’t, Numpy responds that it doesn’t know how to set an array element with a sequence.

In my case , I got this Error in Tensorflow , Reason was i was trying to feed a array with different length or sequences :

example :

```
import tensorflow as tf
input_x = tf.placeholder(tf.int32,[None,None])
word_embedding = tf.get_variable('embeddin',shape=[len(vocab_),110],dtype=tf.float32,initializer=tf.random_uniform_initializer(-0.01,0.01))
embedding_look=tf.nn.embedding_lookup(word_embedding,input_x)
with tf.Session() as tt:
tt.run(tf.global_variables_initializer())
a,b=tt.run([word_embedding,embedding_look],feed_dict={input_x:example_array})
print(b)
```

And if my array is :

```
example_array = [[1,2,3],[1,2]]
```

Then i will get error :

```
ValueError: setting an array element with a sequence.
```

but if i do padding then :

```
example_array = [[1,2,3],[1,2,0]]
```

Now it’s working.