x and y must be either both None or both non-None

Package:

tensorflow

158813

Exception Class:

ValueError

Raise code

""" 
      shape is broadcast-compatible with `x`, `y`, and `condition`.

  Raises:
    ValueError: When exactly one of `x` or `y` is non-`None`; or when
      `condition`, `x`, and `y` have incompatible shapes.
  """
  if (x is None) != (y is None):
    raise ValueError('x and y must be either both None or both non-None')

  with ops.name_scope('RaggedWhere', name, [condition, x, y]):
    condition = ragged_tensor.convert_to_tensor_or_ragged_tensor(
        condition, name='condition')
    if x is None:
      return _coordinate_where(condition)
    else:

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Links to the raise (2)

https://github.com/tensorflow/tensorflow/blob/7acd515ec218b414d5b16e6710268ac03d9f5421/tensorflow/python/ops/ragged/ragged_where_op.py#L78 https://github.com/tensorflow/tensorflow/blob/7acd515ec218b414d5b16e6710268ac03d9f5421/tensorflow/python/ops/ragged/ragged_where_op.py#L160

Ways to fix

x shouldn't be None while y is not None or vice versa. Both of them should be None together or not None.

How to reproduce the error:

pipenv install tensorflow

import tensorflow as tf
x = tf.ragged.constant([['A', 'B'], ['C', 'D', 'E']])
y = tf.ragged.constant([['a', 'b'], ['c', 'd', 'e']])
condition = tf.ragged.constant([[True, False], [True, False, True]])
result = tf.where(condition,x,None)
print(result)

The error:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py in wrapper(*args, **kwargs)
    205     try:
--> 206       return target(*args, **kwargs)
    207     except (TypeError, ValueError):

/usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/array_ops.py in where_v2(condition, x, y, name)
   4691   else:
-> 4692     raise ValueError("x and y must both be non-None or both be None.")
   4693 

ValueError: x and y must both be non-None or both be None.
During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-39-a29909fd81bb> in <module>()
      2 y = tf.ragged.constant([['a', 'b'], ['c', 'd', 'e']])
      3 condition = tf.ragged.constant([[True, False], [True, False, True]])
----> 4 result = tf.where(condition,x,None)
      5 print(result)

/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py in wrapper(*args, **kwargs)
    208       # Note: convert_to_eager_tensor currently raises a ValueError, not a
    209       # TypeError, when given unexpected types.  So we need to catch both.
--> 210       result = dispatch(wrapper, args, kwargs)
    211       if result is not OpDispatcher.NOT_SUPPORTED:
    212         return result

/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py in dispatch(op, args, kwargs)
    120   """
    121   for dispatcher in getattr(op, DISPATCH_ATTR):
--> 122     result = dispatcher.handle(args, kwargs)
    123     if result is not OpDispatcher.NOT_SUPPORTED:
    124       return result

/usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/ragged/ragged_dispatch.py in handle(self, args, kwargs)
    257   def handle(self, args, kwargs):
    258     if self.is_supported(args, kwargs):
--> 259       return self._ragged_op(*args, **kwargs)
    260     else:
    261       return self.NOT_SUPPORTED

/usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/ragged/ragged_where_op.py in where_v2(condition, x, y, name)
     76   """
     77   if (x is None) != (y is None):
---> 78     raise ValueError('x and y must be either both None or both non-None')
     79 
     80   with ops.name_scope('RaggedWhere', name, [condition, x, y]):

ValueError: x and y must be either both None or both non-None

Fixed code:

x and y should be both not None or None at the same time. one None and the not None cause the error.

import tensorflow as tf
x = tf.ragged.constant([['A', 'B'], ['C', 'D', 'E']])
y = tf.ragged.constant([['a', 'b'], ['c', 'd', 'e']])
condition = tf.ragged.constant([[True, False], [True, False, True]])
result = tf.where(condition,x,y)
print(result)

Correct output:

<tf.RaggedTensor [[b'A', b'b'], [b'C', b'd', b'E']]>

Jul 02, 2021

kellemnegasi 29.0k

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