<h3 dir="auto">Environment info</h3>
<p dir="auto">Operating System: Ubuntu 16.04</p>
<p dir="auto">Installed version of CUDA and cuDNN:<br>
(please attach the output of <code class="notranslate">ls -l /path/to/cuda/lib/libcud*</code>):<br>
-rw-r--r-- 1 root root    558720 Sep 15 07:02 /usr/local/cuda/lib64/libcudadevrt.a<br>
lrwxrwxrwx 1 root root        16 Sep 15 07:05 /usr/local/cuda/lib64/libcudart.so -&gt; libcudart.so.8.0<br>
lrwxrwxrwx 1 root root        19 Sep 15 07:05 /usr/local/cuda/lib64/libcudart.so.8.0 -&gt; libcudart.so.8.0.44<br>
-rw-r--r-- 1 root root    415432 Sep 15 07:02 /usr/local/cuda/lib64/libcudart.so.8.0.44<br>
-rw-r--r-- 1 root root    775162 Sep 15 07:02 /usr/local/cuda/lib64/libcudart_static.a<br>
lrwxrwxrwx 1 xj   users       13 Jul 27 13:55 /usr/local/cuda/lib64/libcudnn.so -&gt; libcudnn.so.5<br>
lrwxrwxrwx 1 xj   users       17 Jul 27 13:55 /usr/local/cuda/lib64/libcudnn.so.5 -&gt; libcudnn.so.5.1.5<br>
-rwxr-xr-x 1 xj   xj    78065952 Apr 23 03:17 /usr/local/cuda/lib64/libcudnn.so.5.0.5<br>
-rwxrwxr-x 1 xj   users 79337624 Jul 27 13:53 /usr/local/cuda/lib64/libcudnn.so.5.1.5<br>
-rw-rw-r-- 1 xj   users 69756172 Jul 27 13:53 /usr/local/cuda/lib64/libcudnn_static.a</p>
<p dir="auto">If installed from source, provide</p>
<ol dir="auto">
<li>The commit hash (<code class="notranslate">git rev-parse HEAD</code>)<br>
<a class="commit-link" data-hovercard-type="commit" data-hovercard-url="https://github.com/tensorflow/tensorflow/commit/bad7c50b9dc9789ad7dd0a62daca40b7269841ed/hovercard" href="https://github.com/tensorflow/tensorflow/commit/bad7c50b9dc9789ad7dd0a62daca40b7269841ed"><tt>bad7c50</tt></a></li>
<li>The output of <code class="notranslate">bazel version</code><br>
.<br>
Build label: 0.3.1<br>
Build target: bazel-out/local-fastbuild/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar<br>
Build time: Fri Jul 29 09:09:52 2016 (1469783392)<br>
Build timestamp: 1469783392<br>
Build timestamp as int: 1469783392</li>
</ol>
<h3 dir="auto">If possible, provide a minimal reproducible example (We usually don't have time to read hundreds of lines of your code)</h3>
<p dir="auto">from <strong>future</strong> import absolute_import<br>
from <strong>future</strong> import division<br>
from <strong>future</strong> import print_function</p>
<p dir="auto">import tensorflow as tf<br>
import tensorflow.contrib as contrib<br>
import numpy as np</p>
<h1 dir="auto">Data sets</h1>
<p dir="auto">IRIS_TRAINING = "iris_training.csv"<br>
IRIS_TEST = "iris_test.csv"</p>
<h1 dir="auto">Load datasets.</h1>
<p dir="auto">training_set = contrib.learn.datasets.base.load_csv_with_header(filename=IRIS_TRAINING,<br>
target_dtype=np.int,<br>
features_dtype=np.float32)<br>
test_set = contrib.learn.datasets.base.load_csv_with_header(filename=IRIS_TEST,<br>
target_dtype=np.int,<br>
features_dtype=np.float32)</p>
<h1 dir="auto">Specify that all features have real-value data</h1>
<p dir="auto">feature_columns = [contrib.layers.real_valued_column("", dimension=4)]</p>
<h1 dir="auto">Build 3 layer DNN with 10, 20, 10 units respectively.</h1>
<p dir="auto">classifier = contrib.learn.DNNClassifier(feature_columns=feature_columns,<br>
hidden_units=[10, 20, 10],<br>
n_classes=2,<br>
model_dir="/tmp/iris_model")</p>
<h1 dir="auto">Fit model.</h1>
<p dir="auto">classifier.fit(x=training_set.data,<br>
y=training_set.target.astype(np.int),<br>
steps=200)</p>
<p dir="auto">After upgrade from 0.10.0 to 0.11.0rc0 my code no longer runs:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="(802, 277)
(802, 1)
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
Traceback (most recent call last):
  File &quot;brain.py&quot;, line 47, in &lt;module&gt;
    classifier.fit(x=trainX, y=trainY, steps=2000)
  File &quot;/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn.py&quot;, line 435, in fit
    max_steps=max_steps)
  File &quot;/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py&quot;, line 333, in fit
    max_steps=max_steps)
  File &quot;/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py&quot;, line 662, in _train_model
    train_op, loss_op = self._get_train_ops(features, targets)
  File &quot;/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py&quot;, line 963, in _get_train_ops
    _, loss, train_op = self._call_model_fn(features, targets, ModeKeys.TRAIN)
  File &quot;/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py&quot;, line 944, in _call_model_fn
    return self._model_fn(features, targets, mode=mode, params=self.params)
  File &quot;/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn.py&quot;, line 258, in _dnn_classifier_model_fn
    weight=_get_weight_tensor(features, weight_column_name))
  File &quot;/usr/lib/python2.7/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py&quot;, line 329, in sigmoid_cross_entropy
    logits.get_shape().assert_is_compatible_with(multi_class_labels.get_shape())
  File &quot;/usr/lib/python2.7/site-packages/tensorflow/python/framework/tensor_shape.py&quot;, line 750, in assert_is_compatible_with
    raise ValueError(&quot;Shapes %s and %s are incompatible&quot; % (self, other))
ValueError: Shapes (?, 1) and (?,) are incompatible"><pre class="notranslate"><code class="notranslate">(802, 277)
(802, 1)
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
Traceback (most recent call last):
  File "brain.py", line 47, in &lt;module&gt;
    classifier.fit(x=trainX, y=trainY, steps=2000)
  File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn.py", line 435, in fit
    max_steps=max_steps)
  File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 333, in fit
    max_steps=max_steps)
  File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 662, in _train_model
    train_op, loss_op = self._get_train_ops(features, targets)
  File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 963, in _get_train_ops
    _, loss, train_op = self._call_model_fn(features, targets, ModeKeys.TRAIN)
  File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 944, in _call_model_fn
    return self._model_fn(features, targets, mode=mode, params=self.params)
  File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn.py", line 258, in _dnn_classifier_model_fn
    weight=_get_weight_tensor(features, weight_column_name))
  File "/usr/lib/python2.7/site-packages/tensorflow/contrib/losses/python/losses/loss_ops.py", line 329, in sigmoid_cross_entropy
    logits.get_shape().assert_is_compatible_with(multi_class_labels.get_shape())
  File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/tensor_shape.py", line 750, in assert_is_compatible_with
    raise ValueError("Shapes %s and %s are incompatible" % (self, other))
ValueError: Shapes (?, 1) and (?,) are incompatible
</code></pre></div>
<p dir="auto">My code:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="...
print shape(trainX) # (802, 277)
print shape(trainY) # (802, 1)
classifier.fit(x=trainX, y=trainY, steps=2000)
..."><pre class="notranslate"><code class="notranslate">...
print shape(trainX) # (802, 277)
print shape(trainY) # (802, 1)
classifier.fit(x=trainX, y=trainY, steps=2000)
...
</code></pre></div>
<p dir="auto">This worked fine on 0.10.0. Notice the shapes in the beginning of output (looks like a valid combination to me).</p>
<h3 dir="auto">What related GitHub issues or StackOverflow threads have you found by searching the web for your problem?</h3>
<p dir="auto">none</p>
<h3 dir="auto">Environment info</h3>
<p dir="auto">Operating System: Fedora 23, TF 0.11.0rc0</p>