Merge pull request #600 from PAIR-code/dev

v0.4.1 Release

Author: jameswex

Dockerfile

@@ -2,34 +2,31 @@
 # https://hub.docker.com/_/python
 FROM python:3.7-slim
 
-# Default demo app command to run.
-ENV APP_COMMAND "lit_nlp.examples.lm_demo:get_wsgi_app()"
-
-# Copy local code to the container image.
-ENV APP_HOME /app
-WORKDIR $APP_HOME
-COPY . ./
-
 # Update Ubuntu packages and install basic utils
 RUN apt-get update
 RUN apt-get install -y wget curl gnupg2 gcc g++
 
 # Install yarn
 RUN curl -sS https://dl.yarnpkg.com/debian/pubkey.gpg | apt-key add -
-RUN echo "deb https://dl.yarnpkg.com/debian/ stable main" | tee /etc/apt/sources.list.d/yarn.list
+RUN echo "deb https://dl.yarnpkg.com/debian/ stable main" | \
+    tee /etc/apt/sources.list.d/yarn.list
 RUN apt update && apt -y install yarn
 
 # Install Anaconda
 RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
-  && bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/anaconda3 \
-  && rm Miniconda3-latest-Linux-x86_64.sh
+    && bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/anaconda3 \
+    && rm Miniconda3-latest-Linux-x86_64.sh
 
 # Set path to conda
 ENV PATH /opt/anaconda3/bin:$PATH
 
+# Copy local code to the container image.
+ENV APP_HOME /app
+WORKDIR $APP_HOME
+COPY . ./
+
 # Set up conda environment with production dependencies
 # This step is slow as it installs many packages.
-COPY environment.yml .
 RUN conda env create -f environment.yml
 
 # Workaround for 'conda activate' depending on shell features
@@ -50,5 +47,15 @@ WORKDIR lit_nlp/client
 RUN yarn && yarn build && rm -rf node_modules/*
 WORKDIR $APP_HOME
 
+# Default demo app command to run.
+ARG DEFAULT_DEMO="glue_demo"
+ENV DEMO_NAME $DEFAULT_DEMO
+
+ARG DEFAULT_PORT="5432"
+ENV DEMO_PORT $DEFAULT_PORT
+
 # Run LIT server
-CMD exec gunicorn -c lit_nlp/examples/gunicorn_config.py $APP_COMMAND
+ENTRYPOINT exec gunicorn \
+           -c lit_nlp/examples/gunicorn_config.py \
+           --bind="0.0.0.0:$DEMO_PORT" \
+           "lit_nlp.examples.$DEMO_NAME:get_wsgi_app()"

RELEASE.md

@@ -1,20 +1,37 @@
 # Language Interpretability Tool releases
 
+## Release 0.4.1
+
+This is a bug fix release aimed at improving visual clarity and common
+workflows.
+
+The UI has been slightly revamped, bugs have been fixed, and new capabilities
+have been added. Notable changes include:
+
+- Adds "open in new tab" feature to LIT Notebook widget
+- Adds support for `SparseMultilabelPreds` to LIME
+- Improves color consistency across the UI
+- Switching NumPy instead of SciKit Learn for PCA
+- Ensuring all built-in demos are compatible with the Docker
+- Updating the Dockerfile to support run-time `DEMO_NAME` and `DEMO_PORT` args
+- Fixed a rendering bug in the Confusion Matrix related column and row spans
+  when "hide empty labels" is turned on
+
 ## Release 0.4
 
 This release adds a lot of new features. The website and documentation have
 been updated accordingly.
 
 The UI has been slightly revamped, bugs have been fixed, and new capabilities
-have been added. Noteable changes include:
+have been added. Notable changes include:
 - Support for Google Cloud Vertex AI notebooks.
 - Preliminary support for tabular and image data, in addition to NLP models.
 - Addition of TCAV global interpretability method.
 - New counterfactual generators for ablating or flipping text tokens for
   minimal changes to flip predictions.
 - New counterfactual generator for tabular data for minimal changes to flip
   predictions.
-- Partial depdence plots for tabular input features.
+- Partial dependence plots for tabular input features.
 - Ability to set binary classification thresholds separately for different
   facets of the dataset
 - Controls to find optimal thresholds across facets given different fairness
@@ -26,12 +43,12 @@ This release adds the ability to use LIT directly in colab and jupyter
 notebooks. The website and documentation have been updated accordingly.
 
 The UI has been slightly revamped, bugs have been fixed, and new capabilities
-have been added. Noteable changes include:
+have been added. Notable changes include:
 - Notebook mode added.
 - New annotated text visualization module added.
 - Allow saving/loading of generated datapoints, and dynamic adding of new
   datasets by path in the UI.
-- Added syncronized scrolling between duplicated modules when comparing
+- Added synchronized scrolling between duplicated modules when comparing
   datapoints or models.
 - Added a focus service for visually linking focus (i.e. hover) states between
   components.