prompt: 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()
  
  ```
  
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
  --- 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"
  
verification_info: {"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"}]}