Switching to our fork of the repo (#97)

models/zhang2021/Dockerfile

@@ -5,9 +5,9 @@ ARG MODELS
 WORKDIR /app
 
 # Clone the repository
-RUN git clone https://github.com/ZhangShiyue/Lite2-3Pyramid && \
+RUN git clone https://github.com/danieldeutsch/Lite2-3Pyramid && \
     cd Lite2-3Pyramid && \
-    git checkout ede30c52fa80a6d80dc2fb32f549ba1f3159860b
+    git checkout c2a60ff4b42df879ee9be8f0fad1b5ae8160943e
 
 ## Install the python dependencies. The Github repo requires torch==1.7.1+cu110, but
 ## we use torch==1.7.1 with cuda 10.0 instead
@@ -23,9 +23,6 @@ RUN pip install --no-cache-dir \
 # Install nltk dependencies
 RUN python -c "import nltk; nltk.download('wordnet'); nltk.download('wordnet_ic'); nltk.download('sentiwordnet')"
 
-# Copy over the scoring code
-COPY src/score.py Lite2-3Pyramid/score.py
-
 # Run the warmup code
 COPY scripts/warmup.sh warmup.sh
 RUN sh warmup.sh

models/zhang2021/Readme.md

@@ -31,8 +31,8 @@ https://github.com/ZhangShiyue/Lite2-3Pyramid
 
 
 ## Docker Information
-- Image name: `danieldeutsch/zhang2021:1.0`
-- Docker Hub: 
+- Image name: `danieldeutsch/zhang2021:1.1`
+- Docker Hub: https://hub.docker.com/repository/docker/danieldeutsch/zhang2021
 - Build command:
   ```shell script
   repro setup zhang2021 [--models <model-name>+]
@@ -60,3 +60,5 @@ Not tested
 - [ ] Predictions exactly replicate results reported in the paper  
 
 ## Changelog
+### v1.1
+- Changed to our fork of the repo, which adds support for using the GPU for coref and SRL and saving the results to a file 

models/zhang2021/scripts/warmup.sh

@@ -3,7 +3,7 @@ echo "This is the reference summary" > references.txt
 echo "This is the candidate summary" > summaries.txt
 echo "1" > ids.txt
 mkdir output
-python score.py \
+python Lite2-3Pyramid.py \
   --extract_stus \
   --reference references.txt \
   --doc_id ids.txt \
@@ -13,7 +13,7 @@ python score.py \
 # Score the summary using each of the models which
 # will pre-cache them
 for model_name in ${MODELS}; do
-  python score.py \
+  python Lite2-3Pyramid.py \
     --unit output/STUs.txt \
     --summary summaries.txt \
     --model ${model_name} \

repro/models/zhang2021/__init__.py

@@ -1,6 +1,6 @@
 import os
 
-VERSION = "1.0"
+VERSION = "1.1"
 MODEL_NAME = os.path.basename(os.path.dirname(__file__))
 DOCKERHUB_REPO = f"danieldeutsch/{MODEL_NAME}"
 DEFAULT_IMAGE = f"{DOCKERHUB_REPO}:{VERSION}"

repro/models/zhang2021/model.py

@@ -55,12 +55,16 @@ def extract_stus(
             cuda = self.device != -1
             if cuda:
                 commands.append(f"export CUDA_VISIBLE_DEVICES={self.device}")
+                predict_device = 0
+            else:
+                predict_device = -1
 
             extract_command = (
-                f"python score.py"
+                f"python Lite2-3Pyramid.py"
                 f"  --extract_stus"
                 f"  --reference {container_summaries_file}"
                 f"  --doc_id {container_ids_file}"
+                f"  --device {predict_device}"
                 f"  --output_dir {container_output_dir}"
             )
             if use_coref:
@@ -187,12 +191,16 @@ def predict_batch(
             cuda = self.device != -1
             if cuda:
                 commands.append(f"export CUDA_VISIBLE_DEVICES={self.device}")
+                predict_device = 0
+            else:
+                predict_device = -1
 
             score_command = (
-                f"python score.py"
+                f"python Lite2-3Pyramid.py"
                 f"  --summary {container_candidates_file}"
                 f"  --unit {container_units_file}"
                 f"  --detail"
+                f"  --device {predict_device}"
                 f"  --output_file {container_output_file}"
             )
             if self.model is not None: