Merge pull request #15 from matlab-deep-learning/compatibility

Add compatibility code for gpt2

Author: bwdGitHub

Diff for: +gpt2/+internal/getSupportFilePath.m

@@ -7,6 +7,10 @@
 arguments
     fileName (1,1) string
 end
+if ismember(version('-release'),["2020a","2020b"])
+    filePath = legacySupportFilePath(fileName);
+    return
+end
 sd = matlab.internal.examples.utils.getSupportFileDir();
 localFileDir = {"data","networks"};%#ok
 localFile = fullfile(sd,"nnet",localFileDir{:},fileName);
@@ -15,4 +19,37 @@
 end
 fileURL = strjoin([localFileDir,fileName],"/");
 filePath = matlab.internal.examples.downloadSupportFile("nnet",fileURL);
+end
+
+function filePath = legacySupportFilePath(fileName)
+% For releases before matlab.internal.examples.downloadSupportFile,
+% use manual download code. We save to the repo's root directory instead of
+% the userpath.
+% Create directories for the model.
+modelType = 'gpt2-355M';
+modelDirectory = fullfile(fileparts(mfilename('fullpath')),'..','..',modelType);
+filePath = fullfile(modelDirectory,fileName);
+iCreateDirectoryIfItDoesNotExist(modelDirectory);
+
+iDownloadFileIfItDoesNotExist( ...
+    filePath, ...
+    "https://ssd.mathworks.com/supportfiles/nnet/data/networks/"+fileName );
+end
+
+function iCreateDirectoryIfItDoesNotExist(directory)
+if ~exist(directory, 'dir')
+    fprintf('Creating directory ''%s''...\n', directory);
+    mkdir(directory);
+else
+    fprintf('Skipped creating directory ''%s'' as it already exists\n', directory);
+end
+end
+
+function iDownloadFileIfItDoesNotExist(destination, source)
+if ~exist(destination, 'file')
+    fprintf('Downloading file ''%s'' ...\n', destination);
+    websave(destination, source);
+else
+    fprintf('Skipped downloading file ''%s'' as it already exists\n', destination);
+end
 end

Diff for: README.md

@@ -15,8 +15,6 @@ This repository implements deep learning transformer models in MATLAB.
 ## Getting Started
 Download or [clone](https://www.mathworks.com/help/matlab/matlab_prog/use-source-control-with-projects.html#mw_4cc18625-9e78-4586-9cc4-66e191ae1c2c) this repository to your machine and open it in MATLAB. 
 
-For R2020a or R2020b download the repo at the corresponding tagged release, or if you are using `git` then `git checkout <release>` where `<release>` is `R2020a` or `R2020b`.
-
 ## Functions
 ### bert
 `mdl = bert` loads a pretrained BERT transformer model and if necessary, downloads the model weights. The output `mdl` is structure with fields `Tokenizer` and `Parameters` that contain the BERT tokenizer and the model parameters, respectively.