Add harness summary job (#9457)

* format yml

* add make_table_results

* add summary job

* add a job to print single result

* upload full directory

.github/workflows/llm-harness-evaluation.yml

@@ -171,7 +171,13 @@ jobs:
           export HF_DATASETS=$HARNESS_HF_HOME/datasets
           export HF_DATASETS_CACHE=$HARNESS_HF_HOME/datasets
           source /opt/intel/oneapi/setvars.sh
-          python run_llb.py --model bigdl-llm --pretrained ${MODEL_PATH} --precision ${{ matrix.precision }} --device ${{ matrix.device }} --tasks ${{ matrix.task }} --batch_size 1 --no_cache --output_path results
+          python run_llb.py \
+          --model bigdl-llm \
+          --pretrained ${MODEL_PATH} \
+          --precision ${{ matrix.precision }} \
+          --device ${{ matrix.device }} \
+          --tasks ${{ matrix.task }} \
+          --batch_size 1 --no_cache --output_path results
 
 
       - name: Compare with golden accuracy
@@ -179,8 +185,45 @@ jobs:
         if: ${{github.event_name == 'schedule'}}
         working-directory: ${{ github.workspace }}/python/llm
         run: |
-          python test/benchmark/harness_nightly/accuracy_regression.py dev/benchmark/harness/results/${{ matrix.model_name }}/${{ matrix.device }}/${{ matrix.precision }}/${{ matrix.task }}/result.json test/benchmark/harness_nightly/golden_results.json
+          python test/benchmark/harness_nightly/accuracy_regression.py \
+          dev/benchmark/harness/results/${{ matrix.model_name }}/${{ matrix.device }}/${{ matrix.precision }}/${{ matrix.task }}/result.json \
+          test/benchmark/harness_nightly/golden_results.json
         
+      - uses: actions/upload-artifact@v3
+        with:
+          name: harness_results
+          path:
+            ${{ github.workspace }}/python/llm/dev/benchmark/harness/results/**
 
+      - name: echo single result
+        shell: bash
         
+        working-directory: ${{ github.workspace }}/python/llm/dev/benchmark/harness/results/
+        run: |
+          cat ${{ matrix.model_name }}/${{ matrix.device }}/${{ matrix.precision }}/${{ matrix.task }}/result.json
 
+  llm-harness-summary:
+    if: ${{ always() }}
+    needs: llm-harness-evalution
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - name: Set up Python 3.9
+        uses: actions/setup-python@v4
+        with:
+          python-version: 3.9
+      - name: Install dependencies
+        shell: bash
+        run: |
+          pip install --upgrade pip
+          pip install jsonlines  pytablewriter regex
+      - name: Download all results
+        uses: actions/download-artifact@v3
+        with:
+          name: harness_results
+          path: results          
+      - name: Summarize the results
+        shell: bash
+        run: |
+          ls results
+          python ${{ github.workspace }}/python/llm/dev/benchmark/harness/make_table_results.py results

python/llm/dev/benchmark/harness/make_table_results.py

@@ -0,0 +1,85 @@
+#
+# Copyright 2016 The BigDL Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+"""
+Usage:
+   python make_table_results.py <input_dir>
+"""
+
+import logging
+from pytablewriter import MarkdownTableWriter, LatexTableWriter
+import os
+import json
+import sys
+from harness_to_leaderboard import task_to_metric
+
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+
+def make_table(result_dict):
+    """Generate table of results."""
+    md_writer = MarkdownTableWriter()
+    latex_writer = LatexTableWriter()
+    md_writer.headers = ["Model", "Precision", "Task", "Metric", "Value"]
+    latex_writer.headers = ["Model", "Precision", "Task", "Metric", "Value"]
+
+    values = []
+    for model, model_results in result_dict.items():
+        for precision, prec_results in model_results.items():
+            for task, task_results in prec_results.items():
+
+                results = task_results["results"]
+                m = task_to_metric[task]
+                if len(results) > 1:
+                    result = results[task]
+                else:
+                    result = list(results.values())[0]
+
+                values.append([model, precision, task, m, "%.2f" % (result[m] * 100)])
+
+                model = ""    
+                precision = ""
+        
+    md_writer.value_matrix = values
+    latex_writer.value_matrix = values
+
+    # todo: make latex table look good
+    # print(latex_writer.dumps())
+
+    return md_writer.dumps()
+
+
+if __name__ == "__main__":
+
+    # loop dirs and subdirs in results dir
+    # for each dir, load json files
+    merged_results = dict()
+    for dirpath, dirnames, filenames in os.walk(sys.argv[1]):
+        # skip dirs without files
+        if not filenames:
+            continue
+        for filename in sorted([f for f in filenames if f.endswith(".json")]):
+            path = os.path.join(dirpath, filename)
+            model, device, precision, task = dirpath.split('/')[-4:]
+            with open(path, "r") as f:
+                result_dict = json.load(f)
+            if model not in merged_results:
+                merged_results[model] = dict()
+            if precision not in merged_results[model]:
+                merged_results[model][precision] = dict()
+            merged_results[model][precision][task] = result_dict
+    print(make_table(merged_results))