Documentation

README.md

@@ -51,7 +51,7 @@ Choose TRAINS because...
 * Management capabilities including project management, filter-by-metric, and detailed experiment comparison.
 * Centralized server for aggregating logs, records, and general bookkeeping.
 * Automatically create a copy of models on centralized storage (TRAINS supports shared folders, S3, GS, and Azure is coming soon!).
-* Support for Jupyter notebook (see the [trains-jupyter-plugin]()) and PyCharm remote debugging (see the [trains-pycharm-plugin]()).
+* Support for Jupyter notebook (see the [trains-jupyter-plugin](https://github.com/allegroai/trains-jupyter-plugin)) and PyCharm remote debugging (see the [trains-pycharm-plugin](https://github.com/allegroai/trains-pycharm-plugin)).
 * A field-tested, feature-rich SDK for your on-the-fly customization needs.
 
 
@@ -105,8 +105,8 @@ You can test your code with it:
 
 TRAINS is composed of the following:
 
-* the [trains-server]()
-* the [Web-App]() (web user interface)
+* the [trains-server](https://github.com/allegroai/trains-server)
+* the [Web-App](https://github.com/allegroai/trains-web) (web user interface)
 * the Python SDK (auto-magically connects your code, see [Using TRAINS (Example)](#using-trains-example)).
 
 The following diagram illustrates the interaction of the TRAINS-server and a GPU machine:
@@ -151,7 +151,7 @@ The following diagram illustrates the interaction of the TRAINS-server and a GPU
 
 ## Installing and Configuring TRAINS
 
-1. Install the trains-server docker (see [Installing the TRAINS Server](../trains_server)).
+1. Install the trains-server docker (see [Installing the TRAINS Server](https://github.com/allegroai/trains-server)).
 
 1. Install the TRAINS package:
 
@@ -161,7 +161,7 @@ The following diagram illustrates the interaction of the TRAINS-server and a GPU
 
 	    trains-init
 
-After installing and configuring, your configuration is `~/trains.conf`. View a sample configuration file [here]([link to git]).
+After installing and configuring, your configuration is `~/trains.conf`. View a sample configuration file [here](https://github.com/allegroai/trains/blob/master/docs/trains.conf).
 
 ## Using TRAINS (Example)
 
@@ -173,7 +173,7 @@ Add these two lines of code to your script:
 * If no project name is provided, then the repository name is used.
 * If no task (experiment) name is provided, then the main filename is used as experiment name
 
-Executing your script prints a direct link to the currently running experiment page, for exampe:
+Executing your script prints a direct link to the currently running experiment page, for example:
 
 ```bash
 TRAINS Metrics page:
@@ -183,7 +183,7 @@ https://demoapp.trainsai.io/projects/76e5e2d45e914f52880621fe64601e85/experiment
 
 *[Add GIF screenshots here]*
 
-For more examples and use cases,  see [examples](link docs/examples/).
+For more examples and use cases, see [examples](https://github.com/allegroai/trains/tree/master/examples).
 
 ## Who Supports TRAINS?
 
@@ -208,11 +208,11 @@ Apache License, Version 2.0 (see the [LICENSE](https://www.apache.org/licenses/L
 
 ## Guidelines for Contributing
 
-See the TRAINS [Guidelines for Contributing](contributing.md).
+See the TRAINS [Guidelines for Contributing](https://github.com/allegroai/trains/blob/master/docs/contributing.md).
 
 ## FAQ
 
-See the TRAINS [FAQ](faq.md).
+See the TRAINS [FAQ](https://github.com/allegroai/trains/blob/master/docs/faq.md).
 
 <p style="font-size:0.9rem; font-weight:700; font-style:italic">May the force (and the goddess of learning rates) be with you!</p>
 

docs/faq.md

@@ -24,7 +24,7 @@ Task.current_task().set_model_design( ‘a very long text of the configuration f
 
 YES!
 
-Use an SDK [Logger](link to git) object. An instance can be always be retrieved with `Task.current_task().get_logger()`:
+Use an SDK [Logger](https://github.com/allegroai/trains/blob/master/trains/logger.py) object. An instance can be always be retrieved with `Task.current_task().get_logger()`:
 
 ```python
 logger = Task.current_task().get_logger()
@@ -33,7 +33,7 @@ logger.report_scalar("loss", "classification", iteration=42, value=1.337)
 
 TRAINS supports scalars, plots, 2d/3d scatter diagrams, histograms, surface diagrams, confusion matrices, images, and text logging.
 
-An example can be found [here](docs/manual_log.py).
+An example can be found [here](https://github.com/allegroai/trains/blob/master/examples/manual_reporting.py).
 
 **I noticed that all of my experiments appear as “Training”. Are there other options?**
 
@@ -46,7 +46,7 @@ The currently supported types are `Task.TaskTypes.training` and `Task.TaskTypes.
 task = Task.init(project_name, task_name, Task.TaskTypes.testing)
 ```
 
-If you feel we should add a few more, let us know in the [issues]() section.
+If you feel we should add a few more, let us know in the [issues](https://github.com/allegroai/trains/issues) section.
 
 **I noticed I keep getting a message “warning: uncommitted code”. What does it mean?**
 
@@ -83,7 +83,7 @@ Task.init(project_name, task_name, output_uri=’s3://bucket/folder’)
 Task.init(project_name, task_name, output_uri=’gs://bucket/folder’)
 ```
 
-These require configuring the cloud storage credentials in `~/trains.conf` (see an [example](v)).
+These require configuring the cloud storage credentials in `~/trains.conf` (see an [example](https://github.com/allegroai/trains/blob/master/docs/trains.conf)).
 
 **I am training multiple models at the same time, but I only see one of them. What happened?**
 
@@ -95,7 +95,7 @@ In the Task view, we only present the last one.
 
 YES!
 
-See  [InputModel]() and [OutputModel]().
+See  [InputModel](https://github.com/allegroai/trains/blob/master/trains/model.py#L319) and [OutputModel](https://github.com/allegroai/trains/blob/master/trains/model.py#L539).
 
 For example:
 
@@ -127,7 +127,7 @@ From this point onward, not only are the dictionary key/value pairs stored, but
 
 YES!
 
-Check our [trains-jupyter-plugin](). It is a Jupyter plugin that allows you to commit your notebook directly from Jupyter. It also saves the Python version of the code and creates an updated `requirements.txt` so you know which packages you were using.
+Check our [trains-jupyter-plugin](https://github.com/allegroai/trains-jupyter-plugin). It is a Jupyter plugin that allows you to commit your notebook directly from Jupyter. It also saves the Python version of the code and creates an updated `requirements.txt` so you know which packages you were using.
 
 **Can I use TRAINS with scikit-learn?**
 
@@ -140,7 +140,7 @@ scikit-learn is supported. Everything you do is logged, with the caveat that mod
 
 YES!
 
-This is such a common occurrence that we created a PyCharm plugin that allows for a remote debugger to grab your local repository / commit ID. See our [trains-pycharm-plugin]() repository for instructions and [latest release]().
+This is such a common occurrence that we created a PyCharm plugin that allows for a remote debugger to grab your local repository / commit ID. See our [trains-pycharm-plugin](https://github.com/allegroai/trains-pycharm-plugin) repository for instructions and [latest release](https://github.com/allegroai/trains-pycharm-plugin/releases).
 
 **How do I know a new version came out?**