Updated some Descriptions

Author: lapplislazuli

Dockerfile

@@ -1,6 +1,6 @@
 FROM nvcr.io/nvidia/pytorch:20.01-py3
 
-LABEL maintainer="L.H.Applis@tu-delft.nl"
+LABEL maintainer="L.H.Applis@tudelft.nl"
 LABEL name="ciselab/codebert-code2text"
 LABEL url="https://github.com/ciselab/CodeBert-CodeToText-Reproduction"
 LABEL vcs="https://github.com/ciselab/CodeBert-CodeToText-Reproduction"

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2020 CISELab
+Copyright (c) 2022 CISELab
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -24,8 +24,6 @@ You can build the docker file beforehand using
 docker build . -t ciselab/codebert-code2text:1.3 -t ciselab/codebert-code2text:latest
 ```
 
-Or you can comment-in the build parts in the docker-compose.yml
-
 Run the experiment using 
 
 ```
@@ -71,7 +69,7 @@ The CPU Containers starts ~20 threads for training and your server should have >
 
 In comparison, training on a RTX 1070 took 7h per epoch. 
 Training on a 3080ti took 6h per epoch. 
-Training on an A40 took ~4h per epoch. In general, GPU tries to allocate around 12gb of memory. 
+Training on an A40 took ~4h per epoch. In general, the GPU tries to allocate around 12gb of memory. 
 
 In general, despite being a good first step, GPU Containers turned out to be quite fragile. 
 We have seen multiple problems with Framework-Versions, Hardware and OS combinations. 

changes.md

@@ -13,7 +13,7 @@ this file holds the changes applied to the existing project from CodeXGlue
 ---------
 
 
-- Moved to Cuda Container, removed conda environment.yml in favour of pip requirements.txt
+- Moved to Cuda Container, removed conda environment.yml in Docker in favour of pip requirements.txt
 - Added a lot of known problems
 - Updated Code to match CodeXGlue Repository (has been changed since initial checkout)
 - Updated Composes to only use one GPU default

docker-compose-minimal.yml

@@ -1,7 +1,7 @@
 version: '3.8'
 
 services:
-  experiment:
+  codebert_minimal_example:
     image: ciselab/codebert-code2text
     build:
       context: .

docker-compose-pretrained-minimal.yml

@@ -1,7 +1,7 @@
 version: '3.8'
 
 services:
-  experiment:
+  codebert_prediction_minimal_example:
     image: ciselab/codebert-code2text
     volumes:
       - ./dataset/java/:/dataset:ro

docker-compose-python.yml

@@ -1,11 +1,11 @@
 version: '3.8'
 
 services:
-  python-codebert-training:
+  codebert_python_training:
     image: ciselab/codebert-code2text:1.3
     volumes:
-      - ./dataset/java/:/dataset:ro
-      - ./compose_output:/experiment/output
+      - ./dataset/python/:/dataset:ro
+      - ./python_compose_output:/experiment/output
     environment:
       epochs: 10
       lang: python

docker-compose.yml

@@ -1,11 +1,11 @@
 version: '3.8'
 
 services:
-  experiment:
+  codebert_java_training:
     image: ciselab/codebert-code2text
     volumes:
       - ./dataset/java/:/dataset:ro
-      - ./compose_output:/experiment/output
+      - ./java_compose_output:/experiment/output
     environment:
       epochs: 10
       train_file: /dataset/train.jsonl