Issue 1:
Environment info

Operating System: Ubuntu 16.04

Installed version of CUDA and cuDNN:

(please attach the output of ls -l /path/to/cuda/lib/libcud*):

-rw-r--r-- 1 root root 558720 Sep 15 07:02 /usr/local/cuda/lib64/libcudadevrt.a

lrwxrwxrwx 1 root root 16 Sep 15 07:05 /usr/local/cuda/lib64/libcudart.so -> libcudart.so.8.0

lrwxrwxrwx 1 root root 19 Sep 15 07:05 /usr/local/cuda/lib64/libcudart.so.8.0 -> libcudart.so.8.0.44

-rw-r--r-- 1 root root 415432 Sep 15 07:02 /usr/local/cuda/lib64/libcudart.so.8.0.44

-rw-r--r-- 1 root root 775162 Sep 15 07:02 /usr/local/cuda/lib64/libcudart_static.a

lrwxrwxrwx 1 xj users 13 Jul 27 13:55 /usr/local/cuda/lib64/libcudnn.so -> libcudnn.so.5

lrwxrwxrwx 1 xj users 17 Jul 27 13:55 /usr/local/cuda/lib64/libcudnn.so.5 -> libcudnn.so.5.1.5

-rwxr-xr-x 1 xj xj 78065952 Apr 23 03:17 /usr/local/cuda/lib64/libcudnn.so.5.0.5

-rwxrwxr-x 1 xj users 79337624 Jul 27 13:53 /usr/local/cuda/lib64/libcudnn.so.5.1.5

-rw-rw-r-- 1 xj users 69756172 Jul 27 13:53 /usr/local/cuda/lib64/libcudnn_static.a

If installed from source, provide

The commit hash (git rev-parse HEAD)

bad7c50

The output of bazel version

.

Build label: 0.3.1

Build target: bazel-out/local-fastbuild/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar

Build time: Fri Jul 29 09:09:52 2016 (1469783392)

Build timestamp: 1469783392

Build timestamp as int: 1469783392

If possible, provide a minimal reproducible example (We usually don't have time to read hundreds of lines of your code)

from future import absolute_import

from future import division

from future import print_function

import tensorflow as tf

import tensorflow.contrib as contrib

import numpy as np

Data sets

IRIS_TRAINING = "iris_training.csv"

IRIS_TEST = "iris_test.csv"

Load datasets.

training_set = contrib.learn.datasets.base.load_csv_with_header(filename=IRIS_TRAINING,

target_dtype=np.int,

features_dtype=np.float32)

test_set = contrib.learn.datasets.base.load_csv_with_header(filename=IRIS_TEST,

target_dtype=np.int,

features_dtype=np.float32)

Specify that all features have real-value data

feature_columns = [contrib.layers.real_valued_column("", dimension=4)]

Build 3 layer DNN with 10, 20, 10 units respectively.

classifier = contrib.learn.DNNClassifier(feature_columns=feature_columns,

hidden_units=[10, 20, 10],

n_classes=2,

model_dir="/tmp/iris_model")

Fit model.

classifier.fit(x=training_set.data,

y=training_set.target.astype(np.int),

steps=200)

Issue 2:
After upgrade from 0.10.0 to 0.11.0rc0 my code no longer runs:

(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 <module>
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

My code:

...
print shape(trainX) # (802, 277)
print shape(trainY) # (802, 1)
classifier.fit(x=trainX, y=trainY, steps=2000)
...

This worked fine on 0.10.0. Notice the shapes in the beginning of output (looks like a valid combination to me).

What related GitHub issues or StackOverflow threads have you found by searching the web for your problem?

none

Environment info

Operating System: Fedora 23, TF 0.11.0rc0