r/deeplearning - how is the result of deeplearning if our data is small

With a small dataset your model will be prone to being overfit. A good rule of thumb is to see if the training data is a good representation (in terms of diversity) of the end-use scenario for the model you are training. I cannot address the pix2code example you mention, but generally speaking if you are training a model to convert A (in your case image) to B (in your case its js code), sometimes you might be able to achieve B to A conversion with deterministic logic. What that means is that if you can automate the process of generating images from js code samples, then you can write your self a script that creates the data-set. This does not guarantee the quality of the data, but is a good strategy to overcome the scarcity of datasets when playing around with deep learning.