Issue 1:
Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes, simple dummy code

import tensorflow as tf

def main():
config = tf.ConfigProto()

sess = tf.Session(config=config)

x = tf.random.uniform([16, 64, 64, 3])
net = x
net = tf.layers.conv2d(net, filters=16, kernel_size=3, padding='same', strides=2)
net = tf.layers.flatten(net)
net = tf.layers.dense(net, 1)

sess.run(tf.global_variables_initializer())

out = sess.run(net)
print(out)

if __name__ == '__main__':
main()

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 18.04

TensorFlow installed from (source or binary): Both source and compiled tested

TensorFlow version (use command below): v1.13.1-0-g6612da8951

Python version: Tested on both 3.5 and 3.6

Bazel version (if compiling from source): 0.19.2

GCC/Compiler version (if compiling from source): gcc-6 (Ubuntu 6.5.0-2ubuntu1~18.04) 6.5.0 20181026

CUDA/cuDNN version: Tested with 10.0/7.5 and 10.1/7.5

GPU model and memory: GTX 1660 TI 6GB

You can collect some of this information using our environment capture script

You can also obtain the TensorFlow version with

python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"

Describe the current behavior

Using any convolution layers fails. Same error with all both versions of CUDA. ~/.nv directory cleared between runs. Same error in docker images as well. CUDNN verified to be working correctly with simple CUDNN programs (e.g. this)

Describe the expected behavior

Code should print an array of 16 numbers

Code to reproduce the issue

Provide a reproducible test case that is the bare minimum necessary to generate the problem.

Other info / logs

2019-03-26 11:14:43.230340: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-03-26 11:14:43.330837: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-03-26 11:14:43.331452: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x3d4a090 executing computations on platform CUDA. Devices:
2019-03-26 11:14:43.331472: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): GeForce GTX 1660 Ti, Compute Capability 7.5
2019-03-26 11:14:43.356898: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3400255000 Hz
2019-03-26 11:14:43.357161: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x3db1d00 executing computations on platform Host. Devices:
2019-03-26 11:14:43.357190: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): <undefined>, <undefined>
2019-03-26 11:14:43.357646: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: GeForce GTX 1660 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.8
pciBusID: 0000:01:00.0
totalMemory: 5.77GiB freeMemory: 5.19GiB
2019-03-26 11:14:43.357674: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-03-26 11:14:43.358609: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-03-26 11:14:43.358630: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0
2019-03-26 11:14:43.358640: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N
2019-03-26 11:14:43.359045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5016 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1660 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
WARNING:tensorflow:From simpletf_test/tf_convnet.py:11: conv2d (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.
Instructions for updating:
Use keras.layers.conv2d instead.
WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
WARNING:tensorflow:From simpletf_test/tf_convnet.py:12: flatten (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.
Instructions for updating:
Use keras.layers.flatten instead.
WARNING:tensorflow:From simpletf_test/tf_convnet.py:13: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.
Instructions for updating:
Use keras.layers.dense instead.
2019-03-26 11:14:43.819308: I tensorflow/stream_executor/dso_loader.cc:152] successfully opened CUDA library libcublas.so.10.0 locally
2019-03-26 11:14:44.479283: E tensorflow/stream_executor/cuda/cuda_dnn.cc:334] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-03-26 11:14:44.498430: E tensorflow/stream_executor/cuda/cuda_dnn.cc:334] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1334, in _do_call
return fn(*args)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node conv2d/Conv2D}}]]
[[{{node dense/BiasAdd}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "simpletf_test/tf_convnet.py", line 22, in <module>
main()
File "simpletf_test/tf_convnet.py", line 18, in main
out = sess.run(net)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 929, in run
run_metadata_ptr)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1328, in _do_run
run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node conv2d/Conv2D (defined at simpletf_test/tf_convnet.py:11) ]]
[[node dense/BiasAdd (defined at simpletf_test/tf_convnet.py:13) ]]

Caused by op 'conv2d/Conv2D', defined at:
File "simpletf_test/tf_convnet.py", line 22, in <module>
main()
File "simpletf_test/tf_convnet.py", line 11, in main
net = tf.layers.conv2d(net, filters=16, kernel_size=3)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/util/deprecation.py", line 324, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/layers/convolutional.py", line 424, in conv2d
return layer.apply(inputs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/keras/engine/base_layer.py", line 1227, in apply
return self.__call__(inputs, *args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/layers/base.py", line 530, in __call__
outputs = super(Layer, self).__call__(inputs, *args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/keras/engine/base_layer.py", line 554, in __call__
outputs = self.call(inputs, *args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/keras/layers/convolutional.py", line 194, in call
outputs = self._convolution_op(inputs, self.kernel)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/nn_ops.py", line 966, in __call__
return self.conv_op(inp, filter)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/nn_ops.py", line 591, in __call__
return self.call(inp, filter)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/nn_ops.py", line 208, in __call__
name=self.name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 1026, in conv2d
data_format=data_format, dilations=dilations, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3300, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1801, in __init__
self._traceback = tf_stack.extract_stack()

UnknownError (see above for traceback): Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node conv2d/Conv2D (defined at simpletf_test/tf_convnet.py:11) ]]
[[node dense/BiasAdd (defined at simpletf_test/tf_convnet.py:13) ]]

Issue 2:
I'm having issues installing tensorflow on my mac device. I seem to be getting a protobuf version mismatch with rc0 wheel.

Installing collected packages: protobuf, tensorflow

Found existing installation: protobuf 3.0.0a2

Uninstalling protobuf-3.0.0a2:

Successfully uninstalled protobuf-3.0.0a2

Found existing installation: tensorflow 0.11.0rc0

Uninstalling tensorflow-0.11.0rc0:

Successfully uninstalled tensorflow-0.11.0rc0

Successfully installed protobuf-3.0.0 tensorflow-0.11.0rc1

And then trying to import

python -c "import tensorflow"
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/usr/local/lib/python2.7/site-packages/tensorflow/__init__.py", line 23, in <module>
from tensorflow.python import *
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/__init__.py", line 53, in <module>
from tensorflow.core.framework.graph_pb2 import *
File "/usr/local/lib/python2.7/site-packages/tensorflow/core/framework/graph_pb2.py", line 16, in <module>
from tensorflow.core.framework import node_def_pb2 as tensorflow_dot_core_dot_framework_dot_node__def__pb2
File "/usr/local/lib/python2.7/site-packages/tensorflow/core/framework/node_def_pb2.py", line 16, in <module>
from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2
File "/usr/local/lib/python2.7/site-packages/tensorflow/core/framework/attr_value_pb2.py", line 16, in <module>
from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2
File "/usr/local/lib/python2.7/site-packages/tensorflow/core/framework/tensor_pb2.py", line 16, in <module>
from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
File "/usr/local/lib/python2.7/site-packages/tensorflow/core/framework/tensor_shape_pb2.py", line 22, in <module>
serialized_pb=_b('\n,tensorflow/core/framework/tensor_shape.proto\x12\ntensorflow\"z\n\x10TensorShapeProto\x12-\n\x03\x64im\x18\x02 \x03(\x0b\x32 .tensorflow.TensorShapeProto.Dim\x12\x14\n\x0cunknown_rank\x18\x03 \x01(\x08\x1a!\n\x03\x44im\x12\x0c\n\x04size\x18\x01 \x01(\x03\x12\x0c\n\x04name\x18\x02 \x01(\tB2\n\x18org.tensorflow.frameworkB\x11TensorShapeProtosP\x01\xf8\x01\x01\x62\x06proto3')
TypeError: __init__() got an unexpected keyword argument 'syntax'

This thread #11 seems to mention this to be a protobuf version mismatch error but I'm not sure.

Any workarounds or if anyone has a clue on what's wrong?