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--- pipeline:window:cryolo:training [2019/09/17 15:31]
twagner
+++ pipeline:window:cryolo:training [2019/09/18 08:36]
twagner
@@ Line 3: / Line 3: @@
 nvidia-smi
 </code>
-For this tutorial, we assume that you have either a single GPU or want to use GPU 0. In the GUI you have to fill in the mandatory fields:
+For this tutorial, we assume that you have either a single GPU or want to use GPU 0.
-{{ :pipeline:window:cryolo:cryolo_training.png?700 |}}
-The default number of warmup epochs((One epoch is a complete pass through the training data.)) is fine as long as you don't want to refine an existing model. During the warmup training epochs it will not try to estimate the size of your particle, which helps crYOLO to converge.
 <note tip>
-Before you start the training, you might want to change the GPU. By default, crYOLO will use GPU 0. The following command will show the status of all GPUs:
-<code>
-nvidia-smi
-</code>
 In the //"Optional arguments"// tab you can change the GPU that should be used by crYOLO. If you have multiple GPUs (e.g. GPU 0 and GPU 1) you can also use both by setting the GPU argument to '0 1'.
 </note>
+In the GUI you have to fill in the mandatory fields:
+{{ :pipeline:window:cryolo:cryolo_training.png?700 |}}
+The default number of warmup epochs((One epoch is a complete pass through the training data.)) is fine as long as you don't want to refine an existing model. During the warmup training epochs it will not try to estimate the size of your particle, which helps crYOLO to converge.
 <note tip>

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