We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Clean up console logging for runner
Starting the runner prints out "sys.path at container level" twice.

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py`
Content:
```
1 #  ------------------------------------------------------------------------------------------
2 #  Copyright (c) Microsoft Corporation. All rights reserved.
3 #  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.
4 #  ------------------------------------------------------------------------------------------
5 from enum import Enum
6 from pathlib import Path
7 from typing import Any
8 import sys
9 
10 from SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName
11 from SSL.utils import SSLTrainingType
12 from histopathology.datasets.tcga_crck_tiles_dataset import TcgaCrck_TilesDatasetWithReturnIndex
13 from histopathology.configs.SSL.HistoSimCLRContainer import HistoSSLContainer
14 
15 current_file = Path(__file__)
16 print(f"Running container from {current_file}")
17 print(f"Sys path container level {sys.path}")
18 
19 
20 class SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore
21     TCGA_CRCK = "CRCKTilesDataset"
22 
23 
24 class CRCK_SimCLR(HistoSSLContainer):
25     """
26     Config to train SSL model on CRCK tiles dataset.
27     Augmentation can be configured by using a configuration yml file or by specifying the set of transformations
28     in the _get_transforms method.
29     It has been tested locally and on AML on the full training dataset (93408 tiles).
30     """
31     SSLContainer._SSLDataClassMappings.update({SSLDatasetNameHiml.TCGA_CRCK.value:
32                                                TcgaCrck_TilesDatasetWithReturnIndex})
33 
34     def __init__(self, **kwargs: Any) -> None:
35         # if not running in Azure ML, you may want to override certain properties on the command line, such as:
36         # --is_debug_model = True
37         # --num_workers = 0
38         # --max_epochs = 2
39 
40         super().__init__(ssl_training_dataset_name=SSLDatasetNameHiml.TCGA_CRCK,
41                          linear_head_dataset_name=SSLDatasetNameHiml.TCGA_CRCK,
42                          azure_datasets=["TCGA-CRCk"],
43                          random_seed=1,
44                          num_workers=8,
45                          is_debug_model=False,
46                          model_checkpoint_save_interval=50,
47                          model_checkpoints_save_last_k=3,
48                          model_monitor_metric='ssl_online_evaluator/val/AreaUnderRocCurve',
49                          model_monitor_mode='max',
50                          max_epochs=50,
51                          ssl_training_batch_size=48,  # GPU memory is at 70% with batch_size=32, 2GPUs
52                          ssl_encoder=EncoderName.resnet50,
53                          ssl_training_type=SSLTrainingType.SimCLR,
54                          use_balanced_binary_loss_for_linear_head=True,
55                          ssl_augmentation_config=None,  # Change to path_augmentation to use the config
56                          linear_head_augmentation_config=None,  # Change to path_augmentation to use the config
57                          drop_last=False,
58                          **kwargs)
59
```

Path: `hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py`
Content:
```
1 #  ------------------------------------------------------------------------------------------
2 #  Copyright (c) Microsoft Corporation. All rights reserved.
3 #  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.
4 #  ------------------------------------------------------------------------------------------
5 from enum import Enum
6 from pathlib import Path
7 from typing import Any
8 import sys
9 
10 from SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName
11 from SSL.utils import SSLTrainingType
12 from health_azure.utils import is_running_in_azure_ml
13 from histopathology.datasets.panda_tiles_dataset import PandaTilesDatasetWithReturnIndex
14 from histopathology.configs.SSL.HistoSimCLRContainer import HistoSSLContainer
15 from histopathology.datasets.default_paths import PANDA_TILES_DATASET_ID
16 
17 
18 current_file = Path(__file__)
19 print(f"Running container from {current_file}")
20 print(f"Sys path container level {sys.path}")
21 
22 
23 class SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore
24     PANDA = "PandaTilesDataset"
25 
26 
27 class PANDA_SimCLR(HistoSSLContainer):
28     """
29     Config to train SSL model on Panda tiles dataset.
30     Augmentation can be configured by using a configuration yml file or by specifying the set of transformations
31     in the _get_transforms method.
32     It has been tested on a toy local dataset (2 slides) and on AML on (~25 slides).
33     """
34     SSLContainer._SSLDataClassMappings.update({SSLDatasetNameHiml.PANDA.value: PandaTilesDatasetWithReturnIndex})
35 
36     def __init__(self, **kwargs: Any) -> None:
37         super().__init__(ssl_training_dataset_name=SSLDatasetNameHiml.PANDA,
38                          linear_head_dataset_name=SSLDatasetNameHiml.PANDA,
39                          azure_datasets=[PANDA_TILES_DATASET_ID],
40                          random_seed=1,
41                          num_workers=5,
42                          is_debug_model=False,
43                          model_checkpoint_save_interval=50,
44                          model_checkpoints_save_last_k=3,
45                          model_monitor_metric='ssl_online_evaluator/val/AccuracyAtThreshold05',
46                          model_monitor_mode='max',
47                          max_epochs=200,
48                          ssl_training_batch_size=128,
49                          ssl_encoder=EncoderName.resnet50,
50                          ssl_training_type=SSLTrainingType.SimCLR,
51                          use_balanced_binary_loss_for_linear_head=True,
52                          ssl_augmentation_config=None,  # Change to path_augmentation to use the config
53                          linear_head_augmentation_config=None,  # Change to path_augmentation to use the config
54                          drop_last=False,
55                          **kwargs)
56         self.pl_check_val_every_n_epoch = 10
57         PandaTilesDatasetWithReturnIndex.occupancy_threshold = 0
58         PandaTilesDatasetWithReturnIndex.random_subset_fraction = 1
59         if not is_running_in_azure_ml():
60             self.is_debug_model = True
61             self.num_workers = 0
62             self.max_epochs = 2
63
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py b/hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py
--- a/hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py
+++ b/hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py
@@ -3,19 +3,13 @@
 #  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.
 #  ------------------------------------------------------------------------------------------
 from enum import Enum
-from pathlib import Path
 from typing import Any
-import sys
 
 from SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName
 from SSL.utils import SSLTrainingType
 from histopathology.datasets.tcga_crck_tiles_dataset import TcgaCrck_TilesDatasetWithReturnIndex
 from histopathology.configs.SSL.HistoSimCLRContainer import HistoSSLContainer
 
-current_file = Path(__file__)
-print(f"Running container from {current_file}")
-print(f"Sys path container level {sys.path}")
-
 
 class SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore
     TCGA_CRCK = "CRCKTilesDataset"
diff --git a/hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py b/hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py
--- a/hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py
+++ b/hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py
@@ -3,9 +3,7 @@
 #  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.
 #  ------------------------------------------------------------------------------------------
 from enum import Enum
-from pathlib import Path
 from typing import Any
-import sys
 
 from SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName
 from SSL.utils import SSLTrainingType
@@ -15,11 +13,6 @@
 from histopathology.datasets.default_paths import PANDA_TILES_DATASET_ID
 
 
-current_file = Path(__file__)
-print(f"Running container from {current_file}")
-print(f"Sys path container level {sys.path}")
-
-
 class SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore
     PANDA = "PandaTilesDataset"

{"golden_diff": "diff --git a/hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py b/hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py\n--- a/hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py\n+++ b/hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py\n@@ -3,19 +3,13 @@\n #  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.\n #  ------------------------------------------------------------------------------------------\n from enum import Enum\n-from pathlib import Path\n from typing import Any\n-import sys\n \n from SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName\n from SSL.utils import SSLTrainingType\n from histopathology.datasets.tcga_crck_tiles_dataset import TcgaCrck_TilesDatasetWithReturnIndex\n from histopathology.configs.SSL.HistoSimCLRContainer import HistoSSLContainer\n \n-current_file = Path(__file__)\n-print(f\"Running container from {current_file}\")\n-print(f\"Sys path container level {sys.path}\")\n-\n \n class SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore\n     TCGA_CRCK = \"CRCKTilesDataset\"\ndiff --git a/hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py b/hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py\n--- a/hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py\n+++ b/hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py\n@@ -3,9 +3,7 @@\n #  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.\n #  ------------------------------------------------------------------------------------------\n from enum import Enum\n-from pathlib import Path\n from typing import Any\n-import sys\n \n from SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName\n from SSL.utils import SSLTrainingType\n@@ -15,11 +13,6 @@\n from histopathology.datasets.default_paths import PANDA_TILES_DATASET_ID\n \n \n-current_file = Path(__file__)\n-print(f\"Running container from {current_file}\")\n-print(f\"Sys path container level {sys.path}\")\n-\n-\n class SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore\n     PANDA = \"PandaTilesDataset\"\n", "issue": "Clean up console logging for runner\nStarting the runner prints out \"sys.path at container level\" twice.\n", "before_files": [{"content": "#  ------------------------------------------------------------------------------------------\n#  Copyright (c) Microsoft Corporation. All rights reserved.\n#  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.\n#  ------------------------------------------------------------------------------------------\nfrom enum import Enum\nfrom pathlib import Path\nfrom typing import Any\nimport sys\n\nfrom SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName\nfrom SSL.utils import SSLTrainingType\nfrom histopathology.datasets.tcga_crck_tiles_dataset import TcgaCrck_TilesDatasetWithReturnIndex\nfrom histopathology.configs.SSL.HistoSimCLRContainer import HistoSSLContainer\n\ncurrent_file = Path(__file__)\nprint(f\"Running container from {current_file}\")\nprint(f\"Sys path container level {sys.path}\")\n\n\nclass SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore\n    TCGA_CRCK = \"CRCKTilesDataset\"\n\n\nclass CRCK_SimCLR(HistoSSLContainer):\n    \"\"\"\n    Config to train SSL model on CRCK tiles dataset.\n    Augmentation can be configured by using a configuration yml file or by specifying the set of transformations\n    in the _get_transforms method.\n    It has been tested locally and on AML on the full training dataset (93408 tiles).\n    \"\"\"\n    SSLContainer._SSLDataClassMappings.update({SSLDatasetNameHiml.TCGA_CRCK.value:\n                                               TcgaCrck_TilesDatasetWithReturnIndex})\n\n    def __init__(self, **kwargs: Any) -> None:\n        # if not running in Azure ML, you may want to override certain properties on the command line, such as:\n        # --is_debug_model = True\n        # --num_workers = 0\n        # --max_epochs = 2\n\n        super().__init__(ssl_training_dataset_name=SSLDatasetNameHiml.TCGA_CRCK,\n                         linear_head_dataset_name=SSLDatasetNameHiml.TCGA_CRCK,\n                         azure_datasets=[\"TCGA-CRCk\"],\n                         random_seed=1,\n                         num_workers=8,\n                         is_debug_model=False,\n                         model_checkpoint_save_interval=50,\n                         model_checkpoints_save_last_k=3,\n                         model_monitor_metric='ssl_online_evaluator/val/AreaUnderRocCurve',\n                         model_monitor_mode='max',\n                         max_epochs=50,\n                         ssl_training_batch_size=48,  # GPU memory is at 70% with batch_size=32, 2GPUs\n                         ssl_encoder=EncoderName.resnet50,\n                         ssl_training_type=SSLTrainingType.SimCLR,\n                         use_balanced_binary_loss_for_linear_head=True,\n                         ssl_augmentation_config=None,  # Change to path_augmentation to use the config\n                         linear_head_augmentation_config=None,  # Change to path_augmentation to use the config\n                         drop_last=False,\n                         **kwargs)\n", "path": "hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py"}, {"content": "#  ------------------------------------------------------------------------------------------\n#  Copyright (c) Microsoft Corporation. All rights reserved.\n#  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.\n#  ------------------------------------------------------------------------------------------\nfrom enum import Enum\nfrom pathlib import Path\nfrom typing import Any\nimport sys\n\nfrom SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName\nfrom SSL.utils import SSLTrainingType\nfrom health_azure.utils import is_running_in_azure_ml\nfrom histopathology.datasets.panda_tiles_dataset import PandaTilesDatasetWithReturnIndex\nfrom histopathology.configs.SSL.HistoSimCLRContainer import HistoSSLContainer\nfrom histopathology.datasets.default_paths import PANDA_TILES_DATASET_ID\n\n\ncurrent_file = Path(__file__)\nprint(f\"Running container from {current_file}\")\nprint(f\"Sys path container level {sys.path}\")\n\n\nclass SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore\n    PANDA = \"PandaTilesDataset\"\n\n\nclass PANDA_SimCLR(HistoSSLContainer):\n    \"\"\"\n    Config to train SSL model on Panda tiles dataset.\n    Augmentation can be configured by using a configuration yml file or by specifying the set of transformations\n    in the _get_transforms method.\n    It has been tested on a toy local dataset (2 slides) and on AML on (~25 slides).\n    \"\"\"\n    SSLContainer._SSLDataClassMappings.update({SSLDatasetNameHiml.PANDA.value: PandaTilesDatasetWithReturnIndex})\n\n    def __init__(self, **kwargs: Any) -> None:\n        super().__init__(ssl_training_dataset_name=SSLDatasetNameHiml.PANDA,\n                         linear_head_dataset_name=SSLDatasetNameHiml.PANDA,\n                         azure_datasets=[PANDA_TILES_DATASET_ID],\n                         random_seed=1,\n                         num_workers=5,\n                         is_debug_model=False,\n                         model_checkpoint_save_interval=50,\n                         model_checkpoints_save_last_k=3,\n                         model_monitor_metric='ssl_online_evaluator/val/AccuracyAtThreshold05',\n                         model_monitor_mode='max',\n                         max_epochs=200,\n                         ssl_training_batch_size=128,\n                         ssl_encoder=EncoderName.resnet50,\n                         ssl_training_type=SSLTrainingType.SimCLR,\n                         use_balanced_binary_loss_for_linear_head=True,\n                         ssl_augmentation_config=None,  # Change to path_augmentation to use the config\n                         linear_head_augmentation_config=None,  # Change to path_augmentation to use the config\n                         drop_last=False,\n                         **kwargs)\n        self.pl_check_val_every_n_epoch = 10\n        PandaTilesDatasetWithReturnIndex.occupancy_threshold = 0\n        PandaTilesDatasetWithReturnIndex.random_subset_fraction = 1\n        if not is_running_in_azure_ml():\n            self.is_debug_model = True\n            self.num_workers = 0\n            self.max_epochs = 2\n", "path": "hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py"}], "after_files": [{"content": "#  ------------------------------------------------------------------------------------------\n#  Copyright (c) Microsoft Corporation. All rights reserved.\n#  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.\n#  ------------------------------------------------------------------------------------------\nfrom enum import Enum\nfrom typing import Any\n\nfrom SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName\nfrom SSL.utils import SSLTrainingType\nfrom histopathology.datasets.tcga_crck_tiles_dataset import TcgaCrck_TilesDatasetWithReturnIndex\nfrom histopathology.configs.SSL.HistoSimCLRContainer import HistoSSLContainer\n\n\nclass SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore\n    TCGA_CRCK = \"CRCKTilesDataset\"\n\n\nclass CRCK_SimCLR(HistoSSLContainer):\n    \"\"\"\n    Config to train SSL model on CRCK tiles dataset.\n    Augmentation can be configured by using a configuration yml file or by specifying the set of transformations\n    in the _get_transforms method.\n    It has been tested locally and on AML on the full training dataset (93408 tiles).\n    \"\"\"\n    SSLContainer._SSLDataClassMappings.update({SSLDatasetNameHiml.TCGA_CRCK.value:\n                                               TcgaCrck_TilesDatasetWithReturnIndex})\n\n    def __init__(self, **kwargs: Any) -> None:\n        # if not running in Azure ML, you may want to override certain properties on the command line, such as:\n        # --is_debug_model = True\n        # --num_workers = 0\n        # --max_epochs = 2\n\n        super().__init__(ssl_training_dataset_name=SSLDatasetNameHiml.TCGA_CRCK,\n                         linear_head_dataset_name=SSLDatasetNameHiml.TCGA_CRCK,\n                         azure_datasets=[\"TCGA-CRCk\"],\n                         random_seed=1,\n                         num_workers=8,\n                         is_debug_model=False,\n                         model_checkpoint_save_interval=50,\n                         model_checkpoints_save_last_k=3,\n                         model_monitor_metric='ssl_online_evaluator/val/AreaUnderRocCurve',\n                         model_monitor_mode='max',\n                         max_epochs=50,\n                         ssl_training_batch_size=48,  # GPU memory is at 70% with batch_size=32, 2GPUs\n                         ssl_encoder=EncoderName.resnet50,\n                         ssl_training_type=SSLTrainingType.SimCLR,\n                         use_balanced_binary_loss_for_linear_head=True,\n                         ssl_augmentation_config=None,  # Change to path_augmentation to use the config\n                         linear_head_augmentation_config=None,  # Change to path_augmentation to use the config\n                         drop_last=False,\n                         **kwargs)\n", "path": "hi-ml-histopathology/src/histopathology/configs/SSL/CRCK_SimCLRContainer.py"}, {"content": "#  ------------------------------------------------------------------------------------------\n#  Copyright (c) Microsoft Corporation. All rights reserved.\n#  Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.\n#  ------------------------------------------------------------------------------------------\nfrom enum import Enum\nfrom typing import Any\n\nfrom SSL.lightning_containers.ssl_container import EncoderName, SSLContainer, SSLDatasetName\nfrom SSL.utils import SSLTrainingType\nfrom health_azure.utils import is_running_in_azure_ml\nfrom histopathology.datasets.panda_tiles_dataset import PandaTilesDatasetWithReturnIndex\nfrom histopathology.configs.SSL.HistoSimCLRContainer import HistoSSLContainer\nfrom histopathology.datasets.default_paths import PANDA_TILES_DATASET_ID\n\n\nclass SSLDatasetNameHiml(SSLDatasetName, Enum):  # type: ignore\n    PANDA = \"PandaTilesDataset\"\n\n\nclass PANDA_SimCLR(HistoSSLContainer):\n    \"\"\"\n    Config to train SSL model on Panda tiles dataset.\n    Augmentation can be configured by using a configuration yml file or by specifying the set of transformations\n    in the _get_transforms method.\n    It has been tested on a toy local dataset (2 slides) and on AML on (~25 slides).\n    \"\"\"\n    SSLContainer._SSLDataClassMappings.update({SSLDatasetNameHiml.PANDA.value: PandaTilesDatasetWithReturnIndex})\n\n    def __init__(self, **kwargs: Any) -> None:\n        super().__init__(ssl_training_dataset_name=SSLDatasetNameHiml.PANDA,\n                         linear_head_dataset_name=SSLDatasetNameHiml.PANDA,\n                         azure_datasets=[PANDA_TILES_DATASET_ID],\n                         random_seed=1,\n                         num_workers=5,\n                         is_debug_model=False,\n                         model_checkpoint_save_interval=50,\n                         model_checkpoints_save_last_k=3,\n                         model_monitor_metric='ssl_online_evaluator/val/AccuracyAtThreshold05',\n                         model_monitor_mode='max',\n                         max_epochs=200,\n                         ssl_training_batch_size=128,\n                         ssl_encoder=EncoderName.resnet50,\n                         ssl_training_type=SSLTrainingType.SimCLR,\n                         use_balanced_binary_loss_for_linear_head=True,\n                         ssl_augmentation_config=None,  # Change to path_augmentation to use the config\n                         linear_head_augmentation_config=None,  # Change to path_augmentation to use the config\n                         drop_last=False,\n                         **kwargs)\n        self.pl_check_val_every_n_epoch = 10\n        PandaTilesDatasetWithReturnIndex.occupancy_threshold = 0\n        PandaTilesDatasetWithReturnIndex.random_subset_fraction = 1\n        if not is_running_in_azure_ml():\n            self.is_debug_model = True\n            self.num_workers = 0\n            self.max_epochs = 2\n", "path": "hi-ml-histopathology/src/histopathology/configs/SSL/PANDA_SimCLRContainer.py"}]}