Deep Memory recall fix (#2698)

fixing deep memory recall

---------

Co-authored-by: adolkhan <adilkhan.sarsen@alumni.nu.edu.kz>

Author: adolkhan

deeplake/client/test_client.py

@@ -128,6 +128,19 @@ class Status:
         "--------------------------------------------------------------\n\n\n"
     )
 
+    completed_no_improvement = (
+        "--------------------------------------------------------------\n"
+        "|                  1338464cd80cab681bfcfw23                  |\n"
+        "--------------------------------------------------------------\n"
+        "| status                     | completed                     |\n"
+        "--------------------------------------------------------------\n"
+        "| progress                   | eta: 100.3 seconds            |\n"
+        "|                            | recall@10: 100.0% (+0.0%)     |\n"
+        "--------------------------------------------------------------\n"
+        "| results                    | recall@10: 100.0% (+0.0%)     |\n"
+        "--------------------------------------------------------------\n\n\n"
+    )
+
     failed = (
         "--------------------------------------------------------------\n"
         "|                  1338464cd80cab681bfcfff3                  |\n"
@@ -168,15 +181,15 @@ def test_deepmemory_print_status_and_list_jobs(capsys, precomputed_jobs_list):
         progress=None,
     )
     response_schema = JobResponseStatusSchema(response=pending_response)
-    response_schema.print_status(job_id, recall=None, importvement=None)
+    response_schema.print_status(job_id, recall=None, improvement=None)
     captured = capsys.readouterr()
     assert captured.out == Status.pending
 
     # for training that is in progress
     job_id = "3218464cd80cab681bfcfff3"
     training_response = create_response(job_id=job_id)
     response_schema = JobResponseStatusSchema(response=training_response)
-    response_schema.print_status(job_id, recall="85.5", importvement="2.6")
+    response_schema.print_status(job_id, recall="85.5", improvement="2.6")
     captured = capsys.readouterr()
     assert captured.out == Status.training
 
@@ -187,10 +200,36 @@ def test_deepmemory_print_status_and_list_jobs(capsys, precomputed_jobs_list):
         status="completed",
     )
     response_schema = JobResponseStatusSchema(response=completed_response)
-    response_schema.print_status(job_id, recall="85.5", importvement="2.6")
+    response_schema.print_status(job_id, recall="85.5", improvement="2.6")
     captured = capsys.readouterr()
     assert captured.out == Status.completed
 
+    job_id = "1338464cd80cab681bfcfw23"
+    completed_no_improvement_response = create_response(
+        job_id=job_id,
+        status="completed",
+        progress={
+            "eta": 100.34,
+            "last_update_at": "2021-08-31T15:00:00.000000",
+            "error": None,
+            "train_recall@10": "87.8%",
+            "best_recall@10": "100.0% (+0.0)%",
+            "epoch": 0,
+            "base_val_recall@10": 0.8292181491851807,
+            "val_recall@10": "85.5%",
+            "dataset": "query",
+            "split": 0,
+            "loss": -0.05437087118625641,
+            "delta": 2.572011947631836,
+        },
+    )
+    response_schema = JobResponseStatusSchema(
+        response=completed_no_improvement_response
+    )
+    response_schema.print_status(job_id, recall="0.0", improvement="0.0")
+    captured = capsys.readouterr()
+    assert captured.out == Status.completed_no_improvement
+
     # for jobs that failed
     job_id = "1338464cd80cab681bfcfff3"
     failed_response = create_response(
@@ -204,7 +243,7 @@ def test_deepmemory_print_status_and_list_jobs(capsys, precomputed_jobs_list):
         },
     )
     response_schema = JobResponseStatusSchema(response=failed_response)
-    response_schema.print_status(job_id, recall=None, importvement=None)
+    response_schema.print_status(job_id, recall=None, improvement=None)
     captured = capsys.readouterr()
     assert captured.out == Status.failed
 
@@ -213,18 +252,21 @@ def test_deepmemory_print_status_and_list_jobs(capsys, precomputed_jobs_list):
         training_response,
         completed_response,
         failed_response,
+        completed_no_improvement_response,
     ]
     recalls = {
         "1238464cd80cab681bfcfff3": None,
         "3218464cd80cab681bfcfff3": "85.5",
         "2138464cd80cab681bfcfff3": "85.5",
         "1338464cd80cab681bfcfff3": None,
+        "1338464cd80cab681bfcfw23": "0.0",
     }
     improvements = {
         "1238464cd80cab681bfcfff3": None,
         "3218464cd80cab681bfcfff3": "2.6",
         "2138464cd80cab681bfcfff3": "2.6",
         "1338464cd80cab681bfcfff3": None,
+        "1338464cd80cab681bfcfw23": "0.0",
     }
     response_schema = JobResponseStatusSchema(response=responses)
     output_str = response_schema.print_jobs(

deeplake/client/utils.py

@@ -145,7 +145,7 @@ def print_status(
         self,
         job_id: Union[str, List[str]],
         recall: str,
-        importvement: str,
+        improvement: str,
     ):
         if not isinstance(job_id, List):
             job_id = [job_id]
@@ -161,7 +161,7 @@ def print_status(
                     indent=" " * 30,
                     add_vertical_bars=True,
                     recall=recall,
-                    improvement=importvement,
+                    improvement=improvement,
                 )
 
             print(line)
@@ -174,7 +174,7 @@ def print_status(
                 " " * 30,
                 add_vertical_bars=True,
                 recall=recall,
-                improvement=importvement,
+                improvement=improvement,
             )
             progress_string = "| {:<27}| {:<30}"
             if progress == "None":
@@ -298,6 +298,8 @@ def get_best_recall_improvement(recall, improvement, best_recall):
     elif float(improvement) < float(bimprovement):
         return brecall, bimprovement
     else:
+        if brecall > recall:
+            return brecall, bimprovement
         return recall, improvement
 
 

deeplake/tests/dummy_data/deep_memory/precomputed_jobs_list.txt

@@ -5,4 +5,6 @@ ID                        STATUS     RESULTS                        PROGRESS
 2138464cd80cab681bfcfff3  completed  recall@10: 85.5% (+2.6%)       eta: 100.3 seconds
                                                                     recall@10: 85.5% (+2.6%)
 1338464cd80cab681bfcfff3  failed     not available yet              eta: None seconds
-                                                                    error: list indices must beintegers or slices,not str
+                                                                    error: list indices must beintegers or slices,not str
+1338464cd80cab681bfcfw23  completed  recall@10: 100.0% (+0.0%)      eta: 100.3 seconds
+                                                                    recall@10: 100.0% (+0.0%)