correction in docs

README.md

@@ -50,7 +50,7 @@ print('URL for run: %s/run/%d' % (openml.config.server, run.run_id))
 Note: The input layer of the network should be compatible with OpenML data output shape. Please check [examples](/docs/Examples/) for more information.
 
 
-Additionally, if you want to publish the run with onnx file, then you must call ```openml_pytorch.add_onnx_to_run()``` immediately before ```run.publish()```. 
+Additionally, if you want to publish the run with onnx file, then you must call ```openml_tensorflow.add_onnx_to_run()``` immediately before ```run.publish()```. 
 
 ```python
 run = openml_tensorflow.add_onnx_to_run(run)

docs/API reference/Config.md

@@ -1,2 +1,20 @@
 # Config
-::: config
+
+Config file to define all hyperparameters.
+
+```python
+from tensorflow.keras.preprocessing.image import ImageDataGenerator
+
+epoch = 10
+batch_size = 32
+datagen = ImageDataGenerator()
+step_per_epoch = 100
+target_size = (128, 128)
+x_col = None
+y_col = None  # TODO: Remove? This is not used if a task is defined.
+
+perform_validation = False
+validation_split = 0.1  # The percentage of data set aside for the validation set
+validation_steps = 1
+datagen_valid = ImageDataGenerator()
+kwargs = {}

docs/index.md

@@ -59,7 +59,7 @@ run = openml_tensorflow.add_onnx_to_run(run)
 #### Using docker image
 
 The docker container has the latest version of [OpenML-Tensorflow](https://github.com/openml/openml-tensorflow) downloaded and pre-installed. It can be used to run TensorFlow Deep Learning analysis on OpenML datasets. 
-See [docker](/docs/Docker%20reference/Docker.md).
+See [docker](./Docker%20reference/Docker.md).
 
 
 This library is currently under development, please report any bugs or feature request in issues section.