Reduced memory in benchmark

packages/client/libclient-py/quickmpc/qmpc.py

@@ -6,7 +6,7 @@
 from .qmpc_server import QMPCServer
 from .share import Share
 from .utils.parse_csv import parse, parse_csv
-from .utils.restore import restore
+from .restore import restore
 
 logger = logging.getLogger(__name__)
 # qmpc.JobStatus でアクセスできるようにエイリアスを設定する

packages/client/libclient-py/quickmpc/utils/restore.py → packages/client/libclient-py/quickmpc/restore.py

@@ -6,6 +6,11 @@
 import numpy as np
 from natsort import natsorted
 
+import google.protobuf.json_format
+from .proto.common_types.common_types_pb2 import Schema
+from .share import Share
+from .utils.if_present import if_present
+
 
 def get_meta(job_uuid: str, path: str):
     file_name = glob.glob(f"{path}/dim?-{job_uuid}-*")[0]
@@ -28,30 +33,44 @@ def get_result(job_uuid: str, path: str, party: int):
 
 
 def restore(job_uuid: str, path: str, party_size: int) -> Any:
-    schema = []
+    column_number = get_meta(job_uuid, path)
+
+    schema = [None]*column_number
     result: Any = []
 
-    column_number = get_meta(job_uuid, path)
+    is_schema = True if len(
+        glob.glob(f"{path}/schema-{job_uuid}-*")) != 0 else False
     is_dim2 = True if len(
         glob.glob(f"{path}/dim2-{job_uuid}-*")) != 0 else False
     if column_number == 0:
-        return [[]] if is_dim2 else []
+        if is_schema:
+            return {"schema": [], "table": [[]]}
+        elif is_dim2:
+            return [[]]
+        else:
+            return []
 
     for party in range(party_size):
         if party == 0:
-            for val in get_result(job_uuid, f"{path}/schema", party):
-                schema.append(val)
+            for i, val in enumerate(get_result(job_uuid, f"{path}/schema", party)):
+                col_sch = google.protobuf.json_format.Parse(
+                    val, Schema())
+                schema[i] = col_sch
 
         itr = 0
         for val in get_result(job_uuid, f"{path}/dim?", party):
+            f = Share.get_pre_convert_func(schema[itr % column_number])
             if itr >= len(result):
-                result.append(Decimal(val))
+                result.append(f(val))
             else:
-                result[itr] += Decimal(val)
+                result[itr] += f(val)
             itr += 1
+    result = np.array(result)\
+        .reshape(-1, column_number).tolist() if is_dim2 else result
+    if is_dim2 and len(result) == 0:
+        schema = []
+        result = [[]]
 
-    result_float = np.vectorize(float)(result)
-    result = np.array(result_float)\
-        .reshape(-1, column_number).tolist() if is_dim2 else result_float
-    result = {"schema": schema, "table": result} if len(schema) else result
+    results = if_present(result, Share.convert_type, schema)
+    result = {"schema": schema, "table": results} if is_schema else results
     return result

scripts/libclient/src/utils.py

@@ -1,6 +1,7 @@
 
 import time
-
+import glob
+import os
 from quickmpc import QMPC, JobStatus
 
 qmpc: QMPC = QMPC([
@@ -9,9 +10,11 @@
     "http://localhost:50003",
 ])
 
-def __try_get_computation_result(job_uuid, is_limit):
+def __try_get_computation_result(job_uuid, is_limit, path = './result'):
     try:
-        get_res = qmpc.get_computation_result(job_uuid)
+        if not os.path.isdir(path):
+            os.mkdir(path)
+        get_res = qmpc.get_computation_result(job_uuid, path)
     except:
         if is_limit:
             raise
@@ -23,7 +26,12 @@ def __try_get_computation_result(job_uuid, is_limit):
         all_completed = all([status == JobStatus.COMPLETED
                                 for status in get_res["statuses"]])
 
+    if glob.glob(f"{path}/schema*{job_uuid}-*") == 0:
+        return None
     if all_completed:
+        res = qmpc.restore(job_uuid, path)
+        print(job_uuid)
+        get_res["results"] = res
         # NOTE
         # 計算結果取得時には含まれていないが，job_uuidがmodelの取得に使われるので
         # このような処理をしている