Save other CI jobs' result (torch/tf pipeline, example, deepspeed etc)

.github/workflows/slack-report.yml

@@ -60,12 +60,10 @@ jobs:
 
       # Upload complete failure tables, as they might be big and only truncated versions could be sent to Slack.
       - name: Failure table artifacts
-        # Only the model testing job is concerned for this step
-        if: ${{ inputs.job == 'run_models_gpu' }}
         uses: actions/upload-artifact@v4
         with:
-          name: ci_results
-          path: ci_results
+          name: ci_results_${{ inputs.job }}
+          path: ci_results_${{ inputs.job }}
 
       - uses: actions/checkout@v4
       - uses: actions/download-artifact@v4
@@ -77,6 +75,7 @@ jobs:
           SLACK_REPORT_CHANNEL: ${{ inputs.slack_report_channel }}
           CI_EVENT: scheduled
           CI_SHA: ${{ github.sha }}
+          CI_TEST_JOB: ${{ inputs.job }}
           SETUP_STATUS: ${{ inputs.setup_status }}
         # We pass `needs.setup.outputs.quantization_matrix` as the argument. A processing in `notification_service_quantization.py` to change
         # `quantization/bnb` to `quantization_bnb` is required, as the artifact names use `_` instead of `/`.
@@ -85,3 +84,11 @@ jobs:
           pip install slack_sdk
           pip show slack_sdk
           python utils/notification_service_quantization.py "${{ inputs.quantization_matrix }}" 
+
+      # Upload complete failure tables, as they might be big and only truncated versions could be sent to Slack.
+      - name: Failure table artifacts
+        if: ${{ inputs.job == 'run_quantization_torch_gpu' }}
+        uses: actions/upload-artifact@v4
+        with:
+          name: ci_results_${{ inputs.job }}
+          path: ci_results_${{ inputs.job }}

utils/notification_service.py

@@ -416,7 +416,7 @@ def per_model_sum(model_category_dict):
             reports=sorted_model_reports,
             to_truncate=False,
         )
-        file_path = os.path.join(os.getcwd(), "ci_results/model_failures_report.txt")
+        file_path = os.path.join(os.getcwd(), f"ci_results_{job_name}/model_failures_report.txt")
         with open(file_path, "w", encoding="UTF-8") as fp:
             fp.write(model_failures_report)
 
@@ -426,18 +426,18 @@ def per_model_sum(model_category_dict):
             reports=sorted_module_reports,
             to_truncate=False,
         )
-        file_path = os.path.join(os.getcwd(), "ci_results/module_failures_report.txt")
+        file_path = os.path.join(os.getcwd(), f"ci_results_{job_name}/module_failures_report.txt")
         with open(file_path, "w", encoding="UTF-8") as fp:
             fp.write(module_failures_report)
 
         if self.prev_ci_artifacts is not None:
             # if the last run produces artifact named `ci_results`
             if (
-                "ci_results" in self.prev_ci_artifacts
-                and "model_failures_report.txt" in self.prev_ci_artifacts["ci_results"]
+                f"ci_results_{job_name}" in self.prev_ci_artifacts
+                and "model_failures_report.txt" in self.prev_ci_artifacts[f"ci_results_{job_name}"]
             ):
                 # Compute the difference of the previous/current (model failure) table
-                prev_model_failures = self.prev_ci_artifacts["ci_results"]["model_failures_report.txt"]
+                prev_model_failures = self.prev_ci_artifacts[f"ci_results_{job_name}"]["model_failures_report.txt"]
                 entries_changed = self.compute_diff_for_failure_reports(model_failures_report, prev_model_failures)
                 if len(entries_changed) > 0:
                     # Save the complete difference
@@ -447,7 +447,7 @@ def per_model_sum(model_category_dict):
                         reports=entries_changed,
                         to_truncate=False,
                     )
-                    file_path = os.path.join(os.getcwd(), "ci_results/changed_model_failures_report.txt")
+                    file_path = os.path.join(os.getcwd(), f"ci_results_{job_name}/changed_model_failures_report.txt")
                     with open(file_path, "w", encoding="UTF-8") as fp:
                         fp.write(diff_report)
 
@@ -643,8 +643,11 @@ def get_new_model_failure_blocks(self, with_header=True):
         sorted_dict = sorted(self.model_results.items(), key=lambda t: t[0])
 
         prev_model_results = {}
-        if "ci_results" in self.prev_ci_artifacts and "model_results.json" in self.prev_ci_artifacts["ci_results"]:
-            prev_model_results = json.loads(self.prev_ci_artifacts["ci_results"]["model_results.json"])
+        if (
+            f"ci_results_{job_name}" in self.prev_ci_artifacts
+            and "model_results.json" in self.prev_ci_artifacts[f"ci_results_{job_name}"]
+        ):
+            prev_model_results = json.loads(self.prev_ci_artifacts[f"ci_results_{job_name}"]["model_results.json"])
 
         all_failure_lines = {}
         for job, job_result in sorted_dict:
@@ -1139,20 +1142,32 @@ def prepare_reports(title, header, reports, to_truncate=True):
             with open(os.path.join(directory, "selected_warnings.json")) as fp:
                 selected_warnings = json.load(fp)
 
-    if not os.path.isdir(os.path.join(os.getcwd(), "ci_results")):
-        os.makedirs(os.path.join(os.getcwd(), "ci_results"))
+    if not os.path.isdir(os.path.join(os.getcwd(), f"ci_results_{job_name}")):
+        os.makedirs(os.path.join(os.getcwd(), f"ci_results_{job_name}"))
 
     # Only the model testing job is concerned: this condition is to avoid other jobs to upload the empty list as
     # results.
     if job_name == "run_models_gpu":
-        with open("ci_results/model_results.json", "w", encoding="UTF-8") as fp:
+        with open(f"ci_results_{job_name}/model_results.json", "w", encoding="UTF-8") as fp:
             json.dump(model_results, fp, indent=4, ensure_ascii=False)
 
+    # Must have the same keys as in `additional_results`.
+    # The values are used as the file names where to save the corresponding CI job results.
+    test_to_result_name = {
+        "PyTorch pipelines": "torch_pipeline",
+        "TensorFlow pipelines": "tf_pipeline",
+        "Examples directory": "example",
+        "Torch CUDA extension tests": "deepspeed",
+    }
+    for job, job_result in additional_results.items():
+        with open(f"ci_results_{job_name}/{test_to_result_name[job]}_results.json", "w", encoding="UTF-8") as fp:
+            json.dump(job_result, fp, indent=4, ensure_ascii=False)
+
     prev_ci_artifacts = None
     target_workflow = "huggingface/transformers/.github/workflows/self-scheduled.yml@refs/heads/main"
     if os.environ.get("CI_WORKFLOW_REF") == target_workflow:
         # Get the last previously completed CI's failure tables
-        artifact_names = ["ci_results"]
+        artifact_names = [f"ci_results_{job_name}"]
         output_dir = os.path.join(os.getcwd(), "previous_reports")
         os.makedirs(output_dir, exist_ok=True)
         prev_ci_artifacts = get_last_daily_ci_reports(

utils/notification_service_quantization.py

@@ -242,6 +242,13 @@ def post_reply(self):
                             {"line": line, "trace": stacktraces.pop(0)}
                         )
 
+    job_name = os.getenv("CI_TEST_JOB")
+    if not os.path.isdir(os.path.join(os.getcwd(), f"ci_results_{job_name}")):
+        os.makedirs(os.path.join(os.getcwd(), f"ci_results_{job_name}"))
+
+    with open(f"ci_results_{job_name}/quantization_results.json", "w", encoding="UTF-8") as fp:
+        json.dump(quantization_results, fp, indent=4, ensure_ascii=False)
+
     message = QuantizationMessage(
         title,
         results=quantization_results,