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pollfly
2022-01-30 12:54:40 +02:00
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docs/guides/frameworks/tensorflow/tensorboard_pr_curve.md
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@@ -3,16 +3,16 @@ title: TensorBoard PR Curve
---
The [tensorboard_pr_curve.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/tensorflow/tensorboard_pr_curve.py)
example demonstrates the integration of **ClearML** into code that uses TensorFlow and TensorBoard.
example demonstrates the integration of ClearML into code that uses TensorFlow and TensorBoard.
The example script does the following:
* Creates an experiment named `tensorboard pr_curve` in the `examples` project.
* Creates three classes, R, G, and B, and generates colors within the RGB space from normal distributions. The true
label of each random color is associated with the normal distribution that generated it.
* Computes the probability that each color belongs to the class, using three other normal distributions.
* Generate PR curves using those probabilities.
* Creates a summary per class using [tensorboard.plugins.pr_curve.summary](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/pr_curve/summary.py),
* Automatically logs the TensorBoard output, TensorFlow Definitions, and output to the console, using **ClearML**.
* When the script runs, Creates an experiment named `tensorboard pr_curve`, which is associated with the `examples` project.
* ClearML automatically captures TensorBoard output, TensorFlow Definitions, and output to the console
## Plots
@@ -27,7 +27,7 @@ In the **ClearML Web UI**, the PR Curve summaries appear in the experiment's pag
## Hyperparameters
**ClearML** automatically logs TensorFlow Definitions. They appear in **CONFIGURATIONS** **>** **HYPER PARAMETERS** **>** **TF_DEFINE**.
ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATIONS** **>** **HYPER PARAMETERS** **>** **TF_DEFINE**.
![image](../../../img/examples_tensorboard_pr_curve_04.png)

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docs/guides/frameworks/tensorflow/tensorboard_toy.md
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@@ -3,22 +3,15 @@ title: TensorBoard Toy
---
The [tensorboard_toy.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/tensorflow/tensorboard_toy.py)
example demonstrates **ClearML**'s automatic logging of TensorBoard scalars, histograms, images, and text, as well as
example demonstrates ClearML's automatic logging of TensorBoard scalars, histograms, images, and text, as well as
all other console output and TensorFlow Definitions.
The script uses `tf.summary.create_file_writer` with the following:
* `tf.summary.histogram`
* `tf.summary.scalar`
* `tf.summary.text`
* `tf.summary.image`
When the script runs, it creates an experiment named `tensorboard toy example`, which is associated with the `examples`
When the script runs, it creates an experiment named `tensorboard toy example` in the `examples`
project.
## Scalars
The `tf.summary.scalar` output appears in the experiment's page in the **ClearML web UI** under **RESULTS** **>**
The `tf.summary.scalar` output appears in the ClearML web UI, in the experiment's **RESULTS** **>**
**SCALARS**. Resource utilization plots, which are titled **:monitor: machine**, also appear in the **SCALARS** tab.
![image](../../../img/examples_tensorboard_toy_03.png)
@@ -31,13 +24,13 @@ The `tf.summary.histogram` output appears in **RESULTS** **>** **PLOTS**.
## Debug Samples
**ClearML** automatically tracks images and text output to TensorFlow. They appear in **RESULTS** **>** **DEBUG SAMPLES**.
ClearML automatically tracks images and text output to TensorFlow. They appear in **RESULTS** **>** **DEBUG SAMPLES**.
![image](../../../img/examples_tensorboard_toy_05.png)
## Hyperparameters
**ClearML** automatically logs TensorFlow Definitions. They appear in **CONFIGURATIONS** **>** **HYPER PARAMETERS** **>**
ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATIONS** **>** **HYPER PARAMETERS** **>**
**TF_DEFINE**.
![image](../../../img/examples_tensorboard_toy_01.png)

9
docs/guides/frameworks/tensorflow/tensorflow_mnist.md
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@@ -6,14 +6,7 @@ The [tensorflow_mnist.py](https://github.com/allegroai/clearml/blob/master/examp
example demonstrates the integration of ClearML into code that uses TensorFlow and Keras to train a neural network on
the Keras built-in [MNIST](https://www.tensorflow.org/api_docs/python/tf/keras/datasets/mnist) handwritten digits dataset.
The script builds a TensorFlow Keras model, and trains and tests it with the following:
* Loss objective function - [tf.keras.metrics.SparseCategoricalCrossentropy](https://www.tensorflow.org/api_docs/python/tf/keras/losses/SparseCategoricalCrossentropy)
* Accuracy metric - [tf.keras.metrics.SparseCategoricalAccuracy](https://www.tensorflow.org/api_docs/python/tf/keras/metrics/SparseCategoricalAccuracy)
* 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)
When the script runs, it creates an experiment named `Tensorflow v2 mnist with summaries`, which is associated with the
`examples` project.
When the script runs, it creates an experiment named `Tensorflow v2 mnist with summaries` in the `examples` project.
## Scalars