<p dir="auto">conda activate base<br>
2.0.0-alpha0<br>
2019-05-29 19:58:31.543654: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA<br>
2019-05-29 19:58:31.557759: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1<br>
2019-05-29 19:58:31.670769: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1009] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero<br>
2019-05-29 19:58:31.672348: I tensorflow/compiler/xla/service/service.cc:162] XLA service 0x55c9b57a0a60 executing computations on platform CUDA. Devices:<br>
2019-05-29 19:58:31.672364: I tensorflow/compiler/xla/service/service.cc:169]   StreamExecutor device (0): Graphics Device, Compute Capability 7.5<br>
2019-05-29 19:58:31.693201: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2904000000 Hz<br>
2019-05-29 19:58:31.693619: I tensorflow/compiler/xla/service/service.cc:162] XLA service 0x55c9b580db30 executing computations on platform Host. Devices:<br>
2019-05-29 19:58:31.693637: I tensorflow/compiler/xla/service/service.cc:169]   StreamExecutor device (0): , <br>
2019-05-29 19:58:31.693791: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1467] Found device 0 with properties:<br>
name: Graphics Device major: 7 minor: 5 memoryClockRate(GHz): 1.71<br>
pciBusID: 0000:01:00.0<br>
totalMemory: 5.76GiB freeMemory: 5.17GiB<br>
2019-05-29 19:58:31.693804: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1546] Adding visible gpu devices: 0<br>
2019-05-29 19:58:31.693844: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0<br>
2019-05-29 19:58:31.694402: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1015] Device interconnect StreamExecutor with strength 1 edge matrix:<br>
2019-05-29 19:58:31.694413: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1021]      0<br>
2019-05-29 19:58:31.694419: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1034] 0:   N<br>
2019-05-29 19:58:31.694516: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1149] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4990 MB memory) -&gt; physical GPU (device: 0, name: Graphics Device, pci bus id: 0000:01:00.0, compute capability: 7.5)<br>
Number of training examples: 60000<br>
Number of test examples:     10000<br>
Epoch 1/5<br>
2019-05-29 19:58:32.786674: W ./tensorflow/core/framework/model.h:202] Encountered a stop event that was not preceded by a start event.<br>
2019-05-29 19:58:36.114172: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0<br>
2019-05-29 19:58:36.288348: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7<br>
2019-05-29 19:58:36.934479: E tensorflow/stream_executor/cuda/cuda_dnn.cc:338] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR<br>
2019-05-29 19:58:36.945020: E tensorflow/stream_executor/cuda/cuda_dnn.cc:338] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR<br>
2019-05-29 19:58:36.945127: W tensorflow/core/common_runtime/base_collective_executor.cc:214] BaseCollectiveExecutor::StartAbort Unknown: 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.<br>
[[{{node conv2d/Conv2D}}]]</p>
<p dir="auto"><em>Please make sure that this is a bug. As per our <a href="https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md">GitHub Policy</a>, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template</em></p>
<p dir="auto"><strong>System information</strong></p>
<ul dir="auto">
<li>Have I written custom code (as opposed to using a stock example script provided in TensorFlow):</li>
<li>OS Platform and Distribution (e.g., Linux Ubuntu 16.04):Debian</li>
<li>Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:</li>
<li>TensorFlow installed from (source or binary):binary</li>
<li>TensorFlow version (use command below):1.13.1,1.14.0，2.0.0a0，1.9.0</li>
<li>Python version:3.7,3.6</li>
<li>Bazel version (if compiling from source):</li>
<li>GCC/Compiler version (if compiling from source):</li>
<li>CUDA/cuDNN version:Cuda 10/7.5.0,7.4.2,7.4.1,7.4.0,Cuda 9 can't support 2060</li>
<li>GPU model and memory:rtx 2060 6GB</li>
</ul>
<p dir="auto">You can collect some of this information using our environment capture<br>
<a href="https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh">script</a><br>
You can also obtain the TensorFlow version with: 1. TF 1.0: <code class="notranslate">python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"</code> 2. TF 2.0: <code class="notranslate">python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"</code></p>
<p dir="auto"><strong>Describe the current behavior</strong></p>
<p dir="auto"><strong>Describe the expected behavior</strong></p>
<p dir="auto"><strong>Code to reproduce the issue</strong><br>
conda activate base<br>
2.0.0-alpha0<br>
2019-05-29 19:58:31.543654: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA<br>
2019-05-29 19:58:31.557759: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1<br>
2019-05-29 19:58:31.670769: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1009] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero<br>
2019-05-29 19:58:31.672348: I tensorflow/compiler/xla/service/service.cc:162] XLA service 0x55c9b57a0a60 executing computations on platform CUDA. Devices:<br>
2019-05-29 19:58:31.672364: I tensorflow/compiler/xla/service/service.cc:169] StreamExecutor device (0): Graphics Device, Compute Capability 7.5<br>
2019-05-29 19:58:31.693201: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2904000000 Hz<br>
2019-05-29 19:58:31.693619: I tensorflow/compiler/xla/service/service.cc:162] XLA service 0x55c9b580db30 executing computations on platform Host. Devices:<br>
2019-05-29 19:58:31.693637: I tensorflow/compiler/xla/service/service.cc:169] StreamExecutor device (0): ,<br>
2019-05-29 19:58:31.693791: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1467] Found device 0 with properties:<br>
name: Graphics Device major: 7 minor: 5 memoryClockRate(GHz): 1.71<br>
pciBusID: 0000:01:00.0<br>
totalMemory: 5.76GiB freeMemory: 5.17GiB<br>
2019-05-29 19:58:31.693804: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1546] Adding visible gpu devices: 0<br>
2019-05-29 19:58:31.693844: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0<br>
2019-05-29 19:58:31.694402: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1015] Device interconnect StreamExecutor with strength 1 edge matrix:<br>
2019-05-29 19:58:31.694413: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1021] 0<br>
2019-05-29 19:58:31.694419: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1034] 0: N<br>
2019-05-29 19:58:31.694516: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1149] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4990 MB memory) -&gt; physical GPU (device: 0, name: Graphics Device, pci bus id: 0000:01:00.0, compute capability: 7.5)<br>
Number of training examples: 60000<br>
Number of test examples: 10000<br>
Epoch 1/5<br>
2019-05-29 19:58:32.786674: W ./tensorflow/core/framework/model.h:202] Encountered a stop event that was not preceded by a start event.<br>
2019-05-29 19:58:36.114172: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0<br>
2019-05-29 19:58:36.288348: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7<br>
2019-05-29 19:58:36.934479: E tensorflow/stream_executor/cuda/cuda_dnn.cc:338] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR<br>
2019-05-29 19:58:36.945020: E tensorflow/stream_executor/cuda/cuda_dnn.cc:338] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR<br>
2019-05-29 19:58:36.945127: W tensorflow/core/common_runtime/base_collective_executor.cc:214] BaseCollectiveExecutor::StartAbort Unknown: 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.<br>
[[{{node conv2d/Conv2D}}]]</p>
<p dir="auto"><strong>Other info / logs</strong><br>
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.</p>