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): No
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 20.04.2 LTS
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: No
TensorFlow installed from (source or binary): pip
TensorFlow version (use command below): 1.15.5+nv22.8
Python version: 3.8.3
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version: V11.1.105/
GPU model and memory: A30
You can collect some of this information using our environment capture
script
You can also obtain the TensorFlow version with: 1. TF 1.0: python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)" 2. TF 2.0: python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"
Describe the current behavior
I used two datasets to train my model alternatively, the model share common weights. Like this:
with tf.variable_scope('mymodel', reuse=False):
pred1 = model(dataset1)
with tf.variable_scope('mymodel', reuse=True):
pred2 = model(dataset2)
Describe the expected behavior
I used batchsize of 12 to train my model. Tensorflow works OK on T4, but Nvidia-Tensorflow gpu card OOM on A30.
Code to reproduce the issue
Provide a reproducible test case that is the bare minimum necessary to generate the problem.
Other info / logs
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.
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
You can collect some of this information using our environment capture script You can also obtain the TensorFlow version with: 1. TF 1.0:
python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"2. TF 2.0:python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"Describe the current behavior I used two datasets to train my model alternatively, the model share common weights. Like this:
Describe the expected behavior I used batchsize of 12 to train my model. Tensorflow works OK on T4, but Nvidia-Tensorflow gpu card OOM on A30.
Code to reproduce the issue Provide a reproducible test case that is the bare minimum necessary to generate the problem.
Other info / logs 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.