Fix image_stats integration test (#3790)

Fix CI after changes in #3753 

### Description

Add the old job into CI for testing.

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Quick tests passed locally by running `./runtest.sh`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated.

Author: YuanTingHsieh

tests/integration_test/data/jobs/image_stats/app/config/config_fed_client.json

@@ -0,0 +1,49 @@
+{
+  "format_version": 2,
+  "executors": [
+    {
+      "tasks": [
+        "fed_stats_pre_run", "fed_stats"
+      ],
+      "executor": {
+        "id": "Executor",
+        "path": "nvflare.app_common.executors.statistics.statistics_executor.StatisticsExecutor",
+        "args": {
+          "generator_id": "local_hist_generator"
+        }
+      }
+    }
+  ],
+  "task_result_filters": [
+    {
+      "tasks": ["fed_stats"],
+      "filters":[
+        {
+          "path": "nvflare.app_common.filters.statistics_privacy_filter.StatisticsPrivacyFilter",
+          "args": {
+            "result_cleanser_ids": [
+              "min_count_cleanser"
+            ]
+          }
+        }
+      ]
+    }
+  ],
+  "task_data_filters": [],
+  "components": [
+    {
+      "id": "local_hist_generator",
+      "path": "image_statistics.ImageStatistics",
+      "args": {
+        "data_root": "/tmp/nvflare/image_stats/data"
+      }
+    },
+    {
+      "id": "min_count_cleanser",
+      "path": "nvflare.app_common.statistics.min_count_cleanser.MinCountCleanser",
+      "args": {
+        "min_count": 10
+      }
+    }
+  ]
+}

tests/integration_test/data/jobs/image_stats/app/config/config_fed_server.json

@@ -0,0 +1,32 @@
+{
+  "format_version": 2,
+  "workflows": [
+    {
+      "id": "fed_stats_controller",
+      "path": "nvflare.app_common.workflows.statistics_controller.StatisticsController",
+      "args": {
+        "min_clients": 4,
+        "statistic_configs": {
+          "count": {},
+          "histogram": {
+            "*": {
+              "bins": 255, "range": [0,256]
+            }
+          }
+        },
+        "writer_id": "stats_writer",
+        "enable_pre_run_task": true
+      }
+    }
+  ],
+  "components": [
+    {
+      "id": "stats_writer",
+      "path": "nvflare.app_common.statistics.json_stats_file_persistor.JsonStatsFileWriter",
+      "args": {
+        "output_path": "statistics/image_statistics.json",
+        "json_encoder_path": "nvflare.app_common.utils.json_utils.ObjectEncoder"
+      }
+    }
+  ]
+}

tests/integration_test/data/jobs/image_stats/app/custom/image_statistics.py

@@ -0,0 +1,132 @@
+# Copyright (c) 2023, NVIDIA CORPORATION.  All rights reserved.
+#
+# 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.
+
+import glob
+import os
+from typing import Dict, List, Optional
+
+import numpy as np
+from monai.data import ITKReader, load_decathlon_datalist
+from monai.transforms import LoadImage
+
+from nvflare.apis.fl_context import FLContext
+from nvflare.app_common.abstract.statistics_spec import Bin, DataType, Feature, Histogram, HistogramType, Statistics
+from nvflare.security.logging import secure_log_traceback
+
+
+class ImageStatistics(Statistics):
+    def __init__(self, data_root: str = "/tmp/nvflare/image_stats/data", data_list_key: str = "data"):
+        """local image statistics generator .
+        Args:
+            data_root: directory with local image data.
+            data_list_key: data list key to use.
+        Returns:
+            a Shareable with the computed local statistics`
+        """
+        super().__init__()
+        self.data_list_key = data_list_key
+        self.data_root = data_root
+        self.data_list = None
+        self.client_name = None
+
+        self.loader = None
+        self.failure_images = 0
+        self.fl_ctx = None
+
+    def initialize(self, fl_ctx: FLContext):
+        self.fl_ctx = fl_ctx
+        self.client_name = fl_ctx.get_identity_name()
+        self.loader = LoadImage(image_only=True)
+        self.loader.register(ITKReader())
+        self._load_data_list(self.client_name, fl_ctx)
+
+        if self.data_list is None:
+            raise ValueError("data is not loaded. make sure the data is loaded")
+
+    def _load_data_list(self, client_name, fl_ctx: FLContext) -> bool:
+        dataset_json = glob.glob(os.path.join(self.data_root, client_name + "*.json"))
+        if len(dataset_json) != 1:
+            self.log_error(
+                fl_ctx, f"No unique matching dataset list found in {self.data_root} for client {client_name}"
+            )
+            return False
+        dataset_json = dataset_json[0]
+        self.log_info(fl_ctx, f"Reading data from {dataset_json}")
+
+        data_list = load_decathlon_datalist(
+            data_list_file_path=dataset_json, data_list_key=self.data_list_key, base_dir=self.data_root
+        )
+        self.data_list = {"train": data_list}
+
+        self.log_info(fl_ctx, f"Client {client_name} has {len(self.data_list)} images")
+        return True
+
+    def pre_run(
+        self,
+        statistics: List[str],
+        num_of_bins: Optional[Dict[str, Optional[int]]],
+        bin_ranges: Optional[Dict[str, Optional[List[float]]]],
+    ):
+        return {}
+
+    def features(self) -> Dict[str, List[Feature]]:
+        return {"train": [Feature("intensity", DataType.FLOAT)]}
+
+    def count(self, dataset_name: str, feature_name: str) -> int:
+        image_paths = self.data_list[dataset_name]
+        return len(image_paths)
+
+    def failure_count(self, dataset_name: str, feature_name: str) -> int:
+
+        return self.failure_images
+
+    def histogram(
+        self, dataset_name: str, feature_name: str, num_of_bins: int, global_min_value: float, global_max_value: float
+    ) -> Histogram:
+        histogram_bins: List[Bin] = []
+        histogram = np.zeros((num_of_bins,), dtype=np.int64)
+        bin_edges = []
+        for i, entry in enumerate(self.data_list[dataset_name]):
+            file = entry.get("image")
+            try:
+                img = self.loader(file)
+                curr_histogram, bin_edges = np.histogram(
+                    img, bins=num_of_bins, range=(global_min_value, global_max_value)
+                )
+                histogram += curr_histogram
+                bin_edges = bin_edges.tolist()
+
+                if i % 100 == 0:
+                    self.logger.info(
+                        f"{self.client_name}, adding {i + 1} of {len(self.data_list[dataset_name])}: {file}"
+                    )
+            except Exception as e:
+                self.failure_images += 1
+                self.logger.critical(
+                    f"Failed to load file {file} with exception: {e.__str__()}. " f"Skipping this image..."
+                )
+
+        if num_of_bins + 1 != len(bin_edges):
+            secure_log_traceback()
+            raise ValueError(
+                f"bin_edges size: {len(bin_edges)} is not matching with number of bins + 1: {num_of_bins + 1}"
+            )
+
+        for j in range(num_of_bins):
+            low_value = bin_edges[j]
+            high_value = bin_edges[j + 1]
+            bin_sample_count = histogram[j]
+            histogram_bins.append(Bin(low_value=low_value, high_value=high_value, sample_count=bin_sample_count))
+
+        return Histogram(HistogramType.STANDARD, histogram_bins)

tests/integration_test/data/jobs/image_stats/meta.json

@@ -0,0 +1,10 @@
+{
+  "name": "image_stats",
+  "resource_spec": {},
+  "min_clients" : 4,
+  "deploy_map": {
+    "app": [
+      "@ALL"
+    ]
+  }
+}

tests/integration_test/data/test_configs/standalone_job/image_stats.yml

@@ -1,7 +1,7 @@
 additional_python_paths:
 - ../../examples/advanced/federated-statistics/image_stats
 cleanup: true
-jobs_root_dir: ../../examples/advanced/federated-statistics/image_stats/jobs
+jobs_root_dir: ./data/jobs
 project_yaml: data/projects/4_clients.yml
 tests:
 - event_sequence:
@@ -26,6 +26,6 @@ tests:
   - cp ../../examples/advanced/federated-statistics/image_stats/requirements.txt ../../examples/advanced/federated-statistics/image_stats/temp_requirements.txt
   - sed -i '/nvflare\|jupyter\|notebook/d' ../../examples/advanced/federated-statistics/image_stats/temp_requirements.txt
   - pip install -r ../../examples/advanced/federated-statistics/image_stats/temp_requirements.txt
-  - bash ../../examples/advanced/federated-statistics/image_stats/prepare_data.sh
+  - python ../../examples/advanced/federated-statistics/image_stats/prepare_data.py --input_dir /tmp/nvflare/image_stats/data --output_dir /tmp/nvflare/image_stats/data
   - rm -f ../../examples/advanced/federated-statistics/image_stats/temp_requirements.txt
   test_name: Test example image_stats.