readme files, delete duplicate files

README.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](docker/README.md).
+See [docker](docs/Docker%20reference/Docker.md).
 
 
 This library is currently under development, please report any bugs or feature reuest in issues section.

docs/Docker reference/Docker.md

@@ -1 +1,117 @@
---8<-- "../docker/README.md"
+# OpenML-Tensorflow container
+
+The docker container has the latest version of OpenML-Tensorflow downloaded and pre-installed. It can be used to run TensorFlow Deep Learning analysis on OpenML datasets. 
+This document contains information about:
+
+[Usage](#usage): how to use the image\
+[Using Locally Stored Datasets](#using-locally-stored-datasets-optional): mounting datasets from the local cache\
+[Environment Variables](#environment-variable): setting the cache directory path\
+
+## Usage
+
+These are the steps to use the image:
+
+1. Pull the docker image 
+```
+docker pull taniyadas/openml-tensorflow:latest
+```
+2. If you want to run a local script, it needs to be mounted first. Mount it into the 'app' folder:
+```text
+docker run -it -v PATH/TO/CODE_FOLDER:/app taniyadas/openml-tensorflow /bin/bash
+```
+You can also mount multiple directories into the container (such as your code file directory and dataset directory ) using:
+```text
+docker run -t -i -v PATH/TO/CODE_FOLDER:/app -v PATH/TO/DATASET_FOLDER:/app/dataset taniyadas/openml-tensorflow /bin/bash
+```
+3. Please make sure to give the correct path to the dataset. For example, 
+```text
+openml_tensorflow.config.dir = 'dataset/Images'
+```
+4. Run your code scripts using, for example:
+```text
+ python docs/Examples/tf_image_classification.py
+```
+
+## Using Locally Stored Datasets 
+
+If you don't want to download the dataset each time you run your script, you can mount your dataset saved in your local cache directory to the container. 
+
+### Example Usage
+
+1. Mount the dataset to the 'app/dataset' folder
+
+```
+docker run -t -i -v PATH/TO/CODE_FOLDER:/app -v PATH/TO/DATASET_FOLDER:/app/dataset taniyadas/openml-tensorflow /bin/bash
+```
+
+2. Set correct path to the dataset.  
+```text
+openml_tensorflow.config.dir = '/app/dataset/Images'
+``` 
+
+## Environment Variable 
+
+You can configure the cache directory to control where 'OpenML' datasets are downloaded and cached.
+
+```
+cache_dir = "/app/.openml"
+openml.config.set_root_cache_directory(cache_dir)
+```# OpenML-Tensorflow container
+
+The docker container has the latest version of OpenML-Tensorflow downloaded and pre-installed. It can be used to run TensorFlow Deep Learning analysis on OpenML datasets. 
+This document contains information about:
+
+[Usage](#usage): how to use the image\
+[Using Locally Stored Datasets](#using-locally-stored-datasets-optional): mounting datasets from the local cache\
+[Environment Variables](#environment-variable): setting the cache directory path\
+
+## Usage
+
+These are the steps to use the image:
+
+1. Pull the docker image 
+```
+docker pull taniyadas/openml-tensorflow:latest
+```
+2. If you want to run a local script, it needs to be mounted first. Mount it into the 'app' folder:
+```text
+docker run -it -v PATH/TO/CODE_FOLDER:/app taniyadas/openml-tensorflow /bin/bash
+```
+You can also mount multiple directories into the container (such as your code file directory and dataset directory ) using:
+```text
+docker run -t -i -v PATH/TO/CODE_FOLDER:/app -v PATH/TO/DATASET_FOLDER:/app/dataset taniyadas/openml-tensorflow /bin/bash
+```
+3. Please make sure to give the correct path to the dataset. For example, 
+```text
+openml_tensorflow.config.dir = 'dataset/Images'
+```
+4. Run your code scripts using, for example:
+```text
+ python docs/Examples/tf_image_classification.py
+```
+
+## Using Locally Stored Datasets 
+
+If you don't want to download the dataset each time you run your script, you can mount your dataset saved in your local cache directory to the container. 
+
+### Example Usage
+
+1. Mount the dataset to the 'app/dataset' folder
+
+```
+docker run -t -i -v PATH/TO/CODE_FOLDER:/app -v PATH/TO/DATASET_FOLDER:/app/dataset taniyadas/openml-tensorflow /bin/bash
+```
+
+2. Set correct path to the dataset.  
+```text
+openml_tensorflow.config.dir = '/app/dataset/Images'
+``` 
+
+## Environment Variable 
+
+You can configure the cache directory to control where 'OpenML' datasets are downloaded and cached.
+
+```
+cache_dir = "/app/.openml"
+openml.config.set_root_cache_directory(cache_dir)
+```