mirror of
https://github.com/clearml/clearml-docs
synced 2025-05-02 12:04:40 +00:00
Merge script and ipynb example docs (#101)
This commit is contained in:
parent
1960a5b632
commit
5e7e6fe7c4
@ -45,8 +45,7 @@ Check out some of ClearML's automatic reporting examples for supported packages:
|
||||
* [TensorBoardX](../guides/frameworks/tensorboardx/tensorboardx.md) - logging TensorBoardX scalars, debug
|
||||
samples, and text in code using PyTorch
|
||||
* Matplotlib
|
||||
* [Matplotlib Script Example](../guides/frameworks/matplotlib/matplotlib_example.md) and [Jupyter Notebook](../guides/frameworks/matplotlib/allegro_clearml_matplotlib_example.md) -
|
||||
logging scatter diagrams plotted with Matplotlib
|
||||
* [Matplotlib](../guides/frameworks/matplotlib/matplotlib_example.md) - logging scatter diagrams plotted with Matplotlib
|
||||
* [Matplotlib with PyTorch](../guides/frameworks/pytorch/pytorch_matplotlib.md) - logging debug images shown
|
||||
by Matplotlib
|
||||
|
||||
|
@ -1,47 +0,0 @@
|
||||
---
|
||||
title: Keras with TensorBoard - Jupyter Notebook
|
||||
---
|
||||
The [ClearML_keras_TB_example.ipynb](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/jupyter_keras_TB_example.ipynb)
|
||||
example demonstrates **ClearML** automatically logging code, which is running in Jupyter Notebook and is using Keras and TensorBoard.
|
||||
|
||||
The example script does the following:
|
||||
1. Trains a simple deep neural network on the Keras built-in [MNIST](https://keras.io/api/datasets/mnist/#load_data-function)
|
||||
dataset.
|
||||
1. Builds a sequential model using a categorical crossentropy loss objective function.
|
||||
1. Specifies accuracy as the metric, and uses two callbacks: a TensorBoard callback and a model checkpoint callback.
|
||||
1. During script execution, creates an experiment named `Keras with TensorBoard example` which is associated with the `Colab notebooks` project.
|
||||
|
||||
:::note
|
||||
In the ``clearml`` GitHub repository, this example includes a clickable icon to open the notebook in Google Colab.
|
||||
:::
|
||||
|
||||
## Scalars
|
||||
|
||||
The loss and accuracy metric scalar plots appear in **RESULTS** **>** **SCALARS**, along with the resource utilization plots,
|
||||
which are titled **:monitor: machine**.
|
||||
|
||||

|
||||
|
||||
## Histograms
|
||||
|
||||
Histograms for layer density appear in **RESULTS** **>** **PLOTS**.
|
||||
|
||||

|
||||
|
||||
## Hyperparameters
|
||||
|
||||
**ClearML** automatically logs TensorFlow Definitions, which appear in **CONFIGURATIONS** **>** **HYPER PARAMETERS** **>** **TF_DEFINE**.
|
||||
|
||||

|
||||
|
||||
## Log
|
||||
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
|
||||
|
||||

|
||||
|
||||
## Configuration Objects
|
||||
|
||||
The configuration appears in **CONFIGURATIONS** **>** **CONFIGURATION OBJECTS** **>** **General**.
|
||||
|
||||

|
@ -8,7 +8,7 @@ demonstrates **ClearML**'s automatic logging of code running in a Jupyter Notebo
|
||||
The example does the following:
|
||||
1. Trains a simple deep neural network on the Keras built-in [MNIST](https://keras.io/api/datasets/mnist/#load_data-function)
|
||||
dataset.
|
||||
1. Builds a sequential model using a categorical crossentropy loss objective function.
|
||||
1. Builds a sequential model using a categorical cross entropy loss objective function.
|
||||
|
||||
1. Specifies accuracy as the metric, and uses two callbacks: a TensorBoard callback and a model checkpoint callback.
|
||||
|
||||
|
@ -2,23 +2,28 @@
|
||||
title: Keras with TensorBoard
|
||||
---
|
||||
|
||||
The [keras_tensorboard.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py)
|
||||
example demonstrates the integration of **ClearML** into code which uses Keras and TensorBoard.
|
||||
The example below demonstrates the integration of **ClearML** into code which uses Keras and TensorBoard.
|
||||
View it in [script](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py)
|
||||
or in [Jupyter Notebook](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/jupyter_keras_TB_example.ipynb)
|
||||
|
||||
The example does the following:
|
||||
:::note
|
||||
The example in [Jupyter Notebook](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/jupyter_keras_TB_example.ipynb)
|
||||
includes a clickable icon to open the notebook in Google Colab.
|
||||
:::
|
||||
|
||||
The example script does the following:
|
||||
1. Trains a simple deep neural network on the Keras built-in [MNIST](https://keras.io/api/datasets/mnist/#load_data-function)
|
||||
dataset.
|
||||
1. Builds a sequential model using a categorical crossentropy loss objective function.
|
||||
|
||||
1. Specifies accuracy as the metric, and uses two callbacks: a TensorBoard callback and a model checkpoint callback.
|
||||
|
||||
1. During script execution, it creates an experiment named `Keras with TensorBoard example` which is associated with the
|
||||
`examples` project.
|
||||
1. Builds a sequential model using a categorical cross entropy loss objective function.
|
||||
1. Specifies accuracy as the metric, and uses two callbacks: a TensorBoard callback and a model checkpoint callback.
|
||||
1. During script execution, creates an experiment named `Keras with TensorBoard example`, which is associated with the
|
||||
`examples` project (in script) or the `Colab notebooks` project (in Jupyter Notebook) .
|
||||
|
||||
|
||||
## Scalars
|
||||
|
||||
The loss and accuracy metric scalar plots appear in the **RESULTS** **>** **SCALARS**, along with the resource utilization
|
||||
plots, which are titled **:monitor: machine**.
|
||||
The loss and accuracy metric scalar plots appear in **RESULTS** **>** **SCALARS**, along with the resource utilization plots,
|
||||
which are titled **:monitor: machine**.
|
||||
|
||||

|
||||
|
||||
@ -44,16 +49,17 @@ TensorFlow Definitions appear in **TF_DEFINE**.
|
||||
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
|
||||
|
||||

|
||||

|
||||
|
||||
## Configuration Objects
|
||||
|
||||
In the experiment code, a configuration dictionary is connected to the Task by calling the [Task.connect](../../../references/sdk/task.md#connect)
|
||||
method.
|
||||
|
||||
```python
|
||||
task.connect_configuration({'test': 1337, 'nested': {'key': 'value', 'number': 1}})
|
||||
```
|
||||
|
||||
It appears in **CONFIGURATIONS** **>** **CONFIGURATION OBJECTS**.
|
||||
It appears in **CONFIGURATIONS** **>** **CONFIGURATION OBJECTS** **>** **General**.
|
||||
|
||||

|
||||

|
@ -1,32 +0,0 @@
|
||||
---
|
||||
title: Matplotlib - Jupyter Notebook
|
||||
---
|
||||
|
||||
The [jupyter_matplotlib_example.ipynb](https://github.com/allegroai/clearml/blob/master/examples/frameworks/matplotlib/jupyter_matplotlib_example.ipynb)
|
||||
example demonstrates the integration of **ClearML** into code running in Jupyter Notebook, which uses `matplotlib` to plot
|
||||
scatter diagrams, and show images. **ClearML** automatically logs the diagrams and images. When the script runs, ClearML
|
||||
creates an experiment named `Matplotlib example` which is associated with the `Colab notebooks` project.
|
||||
|
||||
:::note
|
||||
In the ``clearml`` GitHub repository, this example includes a clickable icon to open the notebook in Google Colab.
|
||||
:::
|
||||
|
||||
## Plots
|
||||
|
||||
The scatter plots appear in the **ClearML Web UI**, in **RESULTS** **>** **PLOTS**.
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
## Debug Samples
|
||||
|
||||
The images appear in **RESULTS** **>** **DEBUG SAMPLES**. Each debug sample image is associated with a metric.
|
||||
|
||||

|
||||
|
||||
View the debug sample in the image viewer.
|
||||
|
||||

|
@ -2,10 +2,21 @@
|
||||
title: Matplotlib
|
||||
---
|
||||
|
||||
The [matplotlib_example.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/matplotlib/matplotlib_example.py)
|
||||
example demonstrates integrating **ClearML** into code that uses `matplotlib` to plot scatter diagrams, and show images.
|
||||
**ClearML** automatically logs the diagrams and images. When the script runs, it creates an experiment named `Matplotlib example`,
|
||||
which is associated with the `examples` project.
|
||||
The example below demonstrates integrating **ClearML** into code that uses `matplotlib` to plot scatter diagrams, and
|
||||
show images. **ClearML** automatically logs the diagrams and images.
|
||||
|
||||
View the example in [script](https://github.com/allegroai/clearml/blob/master/examples/frameworks/matplotlib/matplotlib_example.py)
|
||||
or in [Jupyter Notebook](https://github.com/allegroai/clearml/blob/master/examples/frameworks/matplotlib/jupyter_matplotlib_example.ipynb).
|
||||
|
||||
:::note
|
||||
The example in [Jupyter Notebook](https://github.com/allegroai/clearml/blob/master/examples/frameworks/matplotlib/jupyter_matplotlib_example.ipynb),
|
||||
includes a clickable icon to open the notebook in Google Colab.
|
||||
:::
|
||||
|
||||
When the example runs, it creates an experiment named `Matplotlib example`,
|
||||
which is associated with the `examples` project (in script) or the `Colab notebooks` project (in Jupyter Notebook).
|
||||
|
||||
|
||||
|
||||
## Plots
|
||||
|
||||
|
@ -67,10 +67,10 @@ module.exports = {
|
||||
{'Autokeras': ['guides/frameworks/autokeras/integration_autokeras', 'guides/frameworks/autokeras/autokeras_imdb_example']},
|
||||
{'FastAI': ['guides/frameworks/fastai/fastai_with_tensorboard']},
|
||||
{
|
||||
'Keras': ['guides/frameworks/keras/allegro_clearml_keras_tb_example', 'guides/frameworks/keras/jupyter', 'guides/frameworks/keras/keras_tensorboard']
|
||||
'Keras': ['guides/frameworks/keras/jupyter', 'guides/frameworks/keras/keras_tensorboard']
|
||||
},
|
||||
{'LightGBM': ['guides/frameworks/lightgbm/lightgbm_example']},
|
||||
{'Matplotlib': ['guides/frameworks/matplotlib/allegro_clearml_matplotlib_example', 'guides/frameworks/matplotlib/matplotlib_example']},
|
||||
{'Matplotlib': ['guides/frameworks/matplotlib/matplotlib_example']},
|
||||
{'Pytorch':
|
||||
['guides/frameworks/pytorch/pytorch_distributed_example', 'guides/frameworks/pytorch/pytorch_matplotlib',
|
||||
'guides/frameworks/pytorch/pytorch_mnist', 'guides/frameworks/pytorch/pytorch_tensorboard', 'guides/frameworks/pytorch/pytorch_tensorboardx',
|
||||
|
Loading…
Reference in New Issue
Block a user