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---
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title: Keras with TensorBoard
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---
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2022-03-13 13:07:06 +00:00
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The example below demonstrates the integration of ClearML into code which uses Keras and TensorBoard.
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View it in [script](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py)
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or in [Jupyter Notebook](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/jupyter_keras_TB_example.ipynb).
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:::note
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The example in [Jupyter Notebook](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/jupyter_keras_TB_example.ipynb)
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includes a clickable icon to open the notebook in Google Colab.
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:::
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The example script does the following:
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1. Trains a simple deep neural network on the Keras built-in [MNIST](https://keras.io/api/datasets/mnist/#load_data-function)
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dataset.
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1. Builds a sequential model using a categorical cross entropy loss objective function.
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1. Specifies accuracy as the metric, and uses two callbacks: a TensorBoard callback and a model checkpoint callback.
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1. During script execution, creates an experiment named `Keras with TensorBoard example`, which is associated with the
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`examples` project (in script) or the `Colab notebooks` project (in Jupyter Notebook) .
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## Scalars
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The loss and accuracy metric scalar plots appear in **SCALARS**, along with the resource utilization plots,
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which are titled **:monitor: machine**.
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
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## Histograms
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Histograms for layer density appear in **PLOTS**.
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
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## Hyperparameters
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ClearML automatically logs command line options generated with `argparse`, and TensorFlow Definitions.
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2022-05-26 06:54:41 +00:00
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Command line options appear in **CONFIGURATION** **>** **HYPER PARAMETERS** **>** **Args**.
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
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TensorFlow Definitions appear in **TF_DEFINE**.
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
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2021-05-18 22:31:01 +00:00
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## Console
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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
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2021-09-02 07:48:37 +00:00
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## Configuration Objects
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In the experiment code, a configuration dictionary is connected to the Task by calling the [Task.connect](../../../references/sdk/task.md#connect)
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method.
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```python
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task.connect_configuration({'test': 1337, 'nested': {'key': 'value', 'number': 1}})
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```
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It appears in **CONFIGURATION** **>** **CONFIGURATION OBJECTS** **>** **General**.
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
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