def __init__(self,
config_file: Optional[str] = None,
override_list: List[Any] = []):
_C = CN()
_C.VALID_IMAGES = [
'CXR1576_IM-0375-2001.png', 'CXR1581_IM-0378-2001.png',
'CXR3177_IM-1497-2001.png', 'CXR2585_IM-1082-1001.png',
'CXR1125_IM-0082-1001.png', 'CXR3_IM-1384-2001.png',
'CXR1565_IM-0368-1001.png', 'CXR1105_IM-0072-1001-0001.png',
'CXR2874_IM-1280-1001.png', 'CXR1886_IM-0574-1001.png'
]
_C.MODELS = [{
'resnet18': (pretrainedmodels.resnet18(pretrained=None), 512, 224),
'resnet50':
(pretrainedmodels.resnet50(pretrained=None), 2048, 224),
'resnet101':
(pretrainedmodels.resnet101(pretrained=None), 2048, 224),
'resnet152':
(pretrainedmodels.resnet152(pretrained=None), 2048, 224),
'inception_resnet_v2':
(pretrainedmodels.inceptionresnetv2(pretrained=None), 1536, 299)
}]
# _C.MODELS_FEATURE_SIZE = {'resnet18':512, 'resnet50':2048, 'resnet101':2048, 'resnet152':2048,
# 'inception_v3':2048, 'inception_resnet_v2':1536}
# Random seed for NumPy and PyTorch, important for reproducibility.
_C.RANDOM_SEED = 42
# Opt level for mixed precision training using NVIDIA Apex. This can be
# one of {0, 1, 2}. Refer NVIDIA Apex docs for their meaning.
_C.FP16_OPT = 2
# Path to the dataset root, which structure as per README. Path is
# assumed to be relative to project root.
_C.IMAGE_PATH = '/netscratch/gsingh/MIMIC_CXR/DataSet/Indiana_Chest_XRay/Images_2'
_C.TRAIN_JSON_PATH = '/netscratch/gsingh/MIMIC_CXR/DataSet/Indiana_Chest_XRay/iu_xray_train_2.json'
_C.VAL_JSON_PATH = '/netscratch/gsingh/MIMIC_CXR/DataSet/Indiana_Chest_XRay/iu_xray_val_2.json'
_C.TEST_JSON_PATH = '/netscratch/gsingh/MIMIC_CXR/DataSet/Indiana_Chest_XRay/iu_xray_test_2.json'
_C.PRETRAINED_EMDEDDING = False
# Path to .vocab file generated by ``sentencepiece``.
_C.VOCAB_FILE_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/Indiana_Chest_XRay/Vocab/indiana.vocab"
# Path to .model file generated by ``sentencepiece``.
_C.VOCAB_MODEL_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/Indiana_Chest_XRay/Vocab/indiana.model"
_C.VOCAB_SIZE = 3000
_C.EPOCHS = 1024
_C.BATCH_SIZE = 10
_C.TEST_BATCH_SIZE = 100
_C.ITERATIONS_PER_EPOCHS = 1
_C.WEIGHT_DECAY = 1e-5
_C.NUM_LABELS = 41
_C.IMAGE_SIZE = 299
_C.MAX_SEQUENCE_LENGTH = 130
_C.DROPOUT_RATE = 0.1
_C.D_HEAD = 64
_C.TRAIN_DATASET_LENGTH = 25000
_C.INFERENCE_TIME = False
_C.COMBINED_N_LAYERS = 1
_C.BEAM_SIZE = 50
_C.PADDING_INDEX = 0
_C.EOS_INDEX = 3
_C.SOS_INDEX = 2
_C.USE_BEAM_SEARCH = True
_C.EXTRACTED_FEATURES = False
_C.IMAGE_MODEL_PATH = '/netscratch/gsingh/MIMIC_CXR/Results/Image_Feature_Extraction/MIMIC_CXR_No_ES/model.pth'
_C.EMBEDDING_DIM = 8192
_C.CONTEXT_SIZE = 1024
_C.LR_COMBINED = 1e-4
_C.MAX_LR = 1e-1
_C.SAVED_DATASET = False
_C.MODEL_NAME = 'inception_resnet_v2'
INIT_PATH = '/netscratch/gsingh/MIMIC_CXR/Results/Modified_Transformer/Indiana_15_10_2020_2/'
_C.SAVED_DATASET_PATH_TRAIN = INIT_PATH + 'DataSet/train_dataloader.pth'
_C.SAVED_DATASET_PATH_VAL = INIT_PATH + 'DataSet/val_dataloader.pth'
_C.SAVED_DATASET_PATH_TEST = INIT_PATH + 'DataSet/test_dataloader.pth'
_C.CHECKPOINT_PATH = INIT_PATH + 'CheckPoints'
_C.MODEL_PATH = INIT_PATH + 'combined_model.pth'
_C.MODEL_STATE_DIC = INIT_PATH + 'combined_model_state_dic.pth'
_C.FIGURE_PATH = INIT_PATH + 'Graphs'
_C.CSV_PATH = INIT_PATH
_C.TEST_CSV_PATH = INIT_PATH + 'test_output_image_feature_input.json'
self._C = _C
if config_file is not None:
self._C.merge_from_file(config_file)
self._C.merge_from_list(override_list)
self.add_derived_params()
# Make an instantiated object of this class immutable.
self._C.freeze()
def __init__(self,
config_file: Optional[str] = None,
override_list: List[Any] = []):
_C = CN()
_C.VALID_IMAGES = [
'8a4e1705-f30d7e1d-dd1ef999-a8521d7e-e64ad0c9.jpg.npy',
'6660e8d2-6381a94a-843d96da-11713488-59a660eb.jpg.npy',
'8a4e1705-f30d7e1d-dd1ef999-a8521d7e-e64ad0c9.jpg.npy',
'865486e4-6d43765f-e1cebccc-d80670c5-b9aeea25.jpg.npy',
'35ab1e49-b049f284-ba901484-a52ba49e-053d2c10.jpg.npy',
'f3d88efb-8d1f70db-a2131320-90053712-cfd9a1bd.jpg.npy',
'c5937742-fb73ee63-48b37017-9cc947e5-fa8342d4.jpg.npy',
'b3ce45dc-111ceca0-bab01f71-9b22033a-ae9705dd.jpg.npy',
'6660e8d2-6381a94a-843d96da-11713488-59a660eb.jpg.npy',
'4fc9abbd-f405ecdb-ca896442-413d67c8-928fe3c4.jpg.npy'
]
# Random seed for NumPy and PyTorch, important for reproducibility.
_C.RANDOM_SEED = 42
# Opt level for mixed precision training using NVIDIA Apex. This can be
# one of {0, 1, 2}. Refer NVIDIA Apex docs for their meaning.
_C.FP16_OPT = 2
# Path to the dataset root, which structure as per README. Path is
# assumed to be relative to project root.
_C.TRAIN_IMAGE_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/JPG_DataSet_Split/Without_Preprocessing_Reports/Train_Features_Extracted"
_C.TRAIN_JSON_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/MIMIC_CXR_Reports/Report_CSV_Files/no_missing_train.json"
_C.VALID_IMAGE_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/JPG_DataSet_Split/Without_Preprocessing_Reports/Valid_Features_Extracted"
_C.VALID_JSON_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/MIMIC_CXR_Reports/Report_CSV_Files/no_missing_valid.json"
_C.TEST_IMAGE_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/JPG_DataSet_Split/Without_Preprocessing_Reports/Test_Images"
_C.TEST_JSON_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/MIMIC_CXR_Reports/Report_CSV_Files/no_missing_test.json"
_C.PRETRAINED_EMDEDDING = False
# Path to .vocab file generated by ``sentencepiece``.
_C.VOCAB_FILE_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/JPG_DataSet_Split/Vocab/Vocab.vocab"
# Path to .model file generated by ``sentencepiece``.
_C.VOCAB_MODEL_PATH = "/netscratch/gsingh/MIMIC_CXR/DataSet/JPG_DataSet_Split/Vocab/Vocab.model"
_C.VOCAB_SIZE = 10000
_C.EPOCHS = 1024
_C.BATCH_SIZE = 650
_C.TEST_BATCH_SIZE = 100
_C.ITERATIONS_PER_EPOCHS = 1
_C.WEIGHT_DECAY = 1e-5
_C.NUM_LABELS = 41
_C.IMAGE_SIZE = 299
_C.MAX_SEQUENCE_LENGTH = 150
_C.DROPOUT_RATE = 0.1
_C.D_HEAD = 64
_C.N_HEAD = 12
_C.TRAIN_DATASET_LENGTH = 25000
_C.INFERENCE_TIME = False
_C.COMBINED_N_LAYERS = 1
_C.BEAM_SIZE = 3
_C.PADDING_INDEX = 0
_C.EOS_INDEX = 0
_C.SOS_INDEX = 0
_C.EXTRACTED_FEATURES = True
_C.IMAGE_MODEL_PATH = '/netscratch/gsingh/MIMIC_CXR/Results/Image_Feature_Extraction/MIMIC_CXR_No_ES/model.pth'
_C.EMBEDDING_DIM = 768
_C.CONTEXT_SIZE = 768
_C.LR_COMBINED = 1e-3
_C.MAX_LR = 1e-1
_C.SAVED_DATASET = False
INIT_PATH = '/netscratch/gsingh/MIMIC_CXR/Results/Modified_Transformer/Complete_mimic_dataset/'
_C.SAVED_DATASET_PATH_TRAIN = INIT_PATH + 'DataSet/train_dataloader.pth'
_C.SAVED_DATASET_PATH_VAL = INIT_PATH + 'DataSet/val_dataloader.pth'
_C.SAVED_DATASET_PATH_TEST = INIT_PATH + 'DataSet/test_dataloader.pth'
_C.CHECKPOINT_PATH = INIT_PATH + 'CheckPoints'
_C.MODEL_PATH = INIT_PATH + 'combined_model.pth'
_C.MODEL_STATE_DIC = INIT_PATH + 'combined_model_state_dic.pth'
_C.FIGURE_PATH = INIT_PATH + 'Graphs'
_C.CSV_PATH = INIT_PATH
_C.TEST_CSV_PATH = INIT_PATH + 'test_output_image_feature_input.csv'
self._C = _C
if config_file is not None:
self._C.merge_from_file(config_file)
self._C.merge_from_list(override_list)
self.add_derived_params()
# Make an instantiated object of this class immutable.
self._C.freeze()
