Error

INFO:tensorflow:Calling model_fn.

ValueErrorTraceback (most recent call last)
<ipython-input-6-1882d5ed9c2a> in <module>()
      9     input_fn=train_input_fn,
     10     steps=20000,
---> 11     hooks=[logging_hook])    

/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.pyc in train(self, input_fn, hooks, steps, max_steps, saving_listeners)
    361 
    362     saving_listeners = _check_listeners_type(saving_listeners)
--> 363     loss = self._train_model(input_fn, hooks, saving_listeners)
    364     logging.info('Loss for final step: %s.', loss)
    365     return self

/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.pyc in _train_model(self, input_fn, hooks, saving_listeners)
    841       return self._train_model_distributed(input_fn, hooks, saving_listeners)
    842     else:
--> 843       return self._train_model_default(input_fn, hooks, saving_listeners)
    844 
    845   def _train_model_default(self, input_fn, hooks, saving_listeners):

/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.pyc in _train_model_default(self, input_fn, hooks, saving_listeners)
    854       worker_hooks.extend(input_hooks)
    855       estimator_spec = self._call_model_fn(
--> 856           features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)
    857       return self._train_with_estimator_spec(estimator_spec, worker_hooks,
    858                                              hooks, global_step_tensor,

/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.pyc in _call_model_fn(self, features, labels, mode, config)
    829 
    830     logging.info('Calling model_fn.')
--> 831     model_fn_results = self._model_fn(features=features, **kwargs)
    832     logging.info('Done calling model_fn.')
    833 

<ipython-input-4-78df2dfbf323> in cnn_model_fn(features, labels, mode)
     24     """Model function for CNN."""
     25     # Input Layer
---> 26     input_layer = tf.reshape(features["x"], [-1, 100, 100, 1])
     27 
     28     # Convolutional Layer #1

/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_array_ops.pyc in reshape(tensor, shape, name)
   6111   if _ctx is None or not _ctx._eager_context.is_eager:
   6112     _, _, _op = _op_def_lib._apply_op_helper(
-> 6113         "Reshape", tensor=tensor, shape=shape, name=name)
   6114     _result = _op.outputs[:]
   6115     _inputs_flat = _op.inputs

/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.pyc in _apply_op_helper(self, op_type_name, name, **keywords)
    785         op = g.create_op(op_type_name, inputs, output_types, name=scope,
    786                          input_types=input_types, attrs=attr_protos,
--> 787                          op_def=op_def)
    788       return output_structure, op_def.is_stateful, op
    789 

/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.pyc in create_op(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_shapes, compute_device)
   3390           input_types=input_types,
   3391           original_op=self._default_original_op,
-> 3392           op_def=op_def)
   3393 
   3394       # Note: shapes are lazily computed with the C API enabled.

/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.pyc in __init__(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def)
   1732           op_def, inputs, node_def.attr)
   1733       self._c_op = _create_c_op(self._graph, node_def, grouped_inputs,
-> 1734                                 control_input_ops)
   1735     else:
   1736       self._c_op = None

/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.pyc in _create_c_op(graph, node_def, inputs, control_inputs)
   1568   except errors.InvalidArgumentError as e:
   1569     # Convert to ValueError for backwards compatibility.
-> 1570     raise ValueError(str(e))
   1571 
   1572   return c_op

ValueError: Dimension size must be evenly divisible by 10000 but is 100 for 'Reshape' (op: 'Reshape') with input shapes: [100], [4] and with input tensors computed as partial shapes: input[1] = [?,100,100,1].