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54 lines
2.3 KiB
Markdown
54 lines
2.3 KiB
Markdown
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---
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title: TensorFlow MNIST
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---
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The [tensorflow_mnist.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/tensorflow/tensorflow_mnist.py)
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example demonstrates the integration of **ClearML** into code that uses TensorFlow and Keras to train a neural network on
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the Keras built-in [MNIST](https://www.tensorflow.org/api_docs/python/tf/keras/datasets/mnist) handwritten digits dataset.
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The script builds a TensorFlow Keras model, and trains and tests it with the following:
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* Loss objective function - [tf.keras.metrics.SparseCategoricalCrossentropy](https://www.tensorflow.org/api_docs/python/tf/keras/losses/SparseCategoricalCrossentropy)
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* Accuracy metric - [tf.keras.metrics.SparseCategoricalAccuracy](https://www.tensorflow.org/api_docs/python/tf/keras/metrics/SparseCategoricalAccuracy)
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* Model checkpointing - [tf.clearml.Checkpoint](https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint?hl=ca) and [tf.train.CheckpointManager](https://www.tensorflow.org/api_docs/python/tf/train/CheckpointManager?hl=ca)
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When the script runs, it creates an experiment named `Tensorflow v2 mnist with summaries`, which is associated with the
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`examples` project.
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## Scalars
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The loss and accuracy metric scalar plots appear in the experiment's page in the **ClearML web UI** under **RESULTS**
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**>** **SCALARS**. Resource utilization plots, which are titled **:monitor: machine**, also appear in the *SCALARS** tab.
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![image](../../../img/examples_tensorflow_mnist_06.png)
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## Hyperparameters
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**ClearML** automatically logs TensorFlow Definitions. They appear in **CONFIGURATIONS** **>** **HYPER PARAMETERS**
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**>** **TF_DEFINE**.
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![image](../../../img/examples_tensorflow_mnist_01.png)
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## Log
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All console output appears in **RESULTS** **>** **LOG**.
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![image](../../../img/examples_tensorflow_mnist_05.png)
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## Artifacts
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Model artifacts associated with the experiment appear in the info panel of the **EXPERIMENTS** tab and in the info panel
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of the **MODELS** tab.
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The experiment info panel shows model tracking, including the model name and design (in this case, no design was stored).
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![image](../../../img/examples_tensorflow_mnist_03.png)
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The model info panel contains the model details, including:
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* Model design
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* Label enumeration
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* Model URL
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* Framework
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* Snapshot locations.
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![image](../../../img/examples_tensorflow_mnist_10.png)
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