Comments (3)
This release does not support distributed computation.
from tensorflow.
Hi kmatzen: As mentioned in our FAQ, this release does not have an RPC and distributed implementation available yet: http://tensorflow.org/resources/faq.md#running_a_tensorflow_computation, but we are working on it and hope to make it available when it's ready.
As a short-term proxy, you can see the Cifar tutorial for an example of how training and distributing among multiple GPUs works -- http://tensorflow.org/tutorials/deep_cnn/index.md
from tensorflow.
(De-duping with #23)
from tensorflow.
Related Issues (20)
- tf.math.reciprocal lacks support of int input on CPU, inconsistent with the documentation
- using tf.linalg.det in custom loss function yields matrix inversion error HOT 1
- Could not interpret optimizer identifier: <keras.src.optimizers.adam.Adam object HOT 4
- Unrecognized keyword arguments passed to Embedding HOT 4
- tf.raw_ops.ApproximateEqual/Erfinv fail support a few data types, inconsistent with the documentation
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- TensorflowLite for Windows on Arm
- Allocating all memory, CUDA OOM
- Segmentation fault (core dumped) HOT 1
- Fail to build from source: API rate limit exceeded for 216.228.127.129 HOT 1
- how to solve this error ? : AttributeError: module 'keras._tf_keras.keras.layers' has no attribute 'experimental' HOT 4
- XNNPACK is not supported in Linux armv7-a when compile source code
- tflite-support not compatible with python 3.11 aarch64 Raspberry Pi 4 HOT 3
- Improper use of PluggableDevice data pointer
- bazel build tensorflow/lite issues brought by "tensorflow\lite\kernels\stablehlo_reduce_window.cc" HOT 1
- Model Loading Error with Bi-directional LSTM layer HOT 2
- CategoryEncoding layer lacks consideration of 0-dimension inputs HOT 3
- ValueError occurred when building cascaded model with loaded sub-model HOT 6
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from tensorflow.