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12b2634 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | import os
# Configuration for the data
DATA_TRAIN_INDEX_PATH = ""
DATA_EVAL_INDEX_PATH = ""
# Configuration for the model
PATCH_STREAM = True # Stream training / inference
PATCH_SIZE = 16 # Patch Size
PATCH_LENGTH = 1024 # Patch Length
CHAR_NUM_LAYERS = 6 # Number of layers in the decoder
PATCH_NUM_LAYERS = 20 # Number of layers in the encoder
HIDDEN_SIZE = 1280 # Hidden Size
# Configuration for the training
BATCH_SIZE = 1
LEARNING_RATE = 1e-5
NUM_EPOCHS = 64 # Number of epochs to train for (if early stopping doesn't intervene)
ACCUMULATION_STEPS = 1 # Accumulation steps to simulate large batch size
PATCH_SAMPLING_BATCH_SIZE = 0 # Batch size for patch during training, 0 for full conaudio
LOAD_FROM_CHECKPOINT = False # Whether to load weights from a checkpoint
WANDB_LOGGING = False # Whether to log to wandb
WANDB_KEY = '<your_wandb_key>'
PRETRAINED_PATH = "" # Path of pretrained weights
EXP_TAG = '' # Experiment tag for name differentiation
NAME = EXP_TAG + \
"_p_size_" + str(PATCH_SIZE) + \
"_p_length_" + str(PATCH_LENGTH) + \
"_p_layers_" + str(PATCH_NUM_LAYERS) + \
"_c_layers_" + str(CHAR_NUM_LAYERS) + \
"_h_size_" + str(HIDDEN_SIZE) + \
"_lr_" + str(LEARNING_RATE) + \
"_batch_" + str(BATCH_SIZE)
WEIGHTS_PATH = "weights_notagen_" + NAME + ".pth" # Path to save weights
LOGS_PATH = "logs_notagen_" + NAME + ".txt" # Path to save logs
WANDB_NAME = NAME
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