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Functions22 in github.com/SAI990323/BIGRec

↓ 3 callersFunctionget_ndcg
(test_data, rank)
data/movie/adjust_pda.py:65
↓ 2 callersFunctionbatch
(list, batch_size=batch_size)
inference.py:133
↓ 2 callersFunctiongenerate_and_tokenize_prompt
(data_point)
train.py:148
↓ 2 callersFunctiongenerate_prompt
(data_point)
train.py:281
↓ 2 callersFunctionget_dist
(test_data)
data/game/adjust_ci.py:40
↓ 2 callersFunctionget_dist
(test_data)
data/movie/adjust_ci.py:38
↓ 2 callersFunctionget_dist
(test_data)
data/movie/adjust_pda.py:38
↓ 2 callersFunctionget_hr
(test_data, rank)
data/game/adjust_ci.py:81
↓ 2 callersFunctionget_hr
(test_data, rank)
data/movie/adjust_ci.py:81
↓ 2 callersFunctionget_ndcg
(test_data, rank)
data/game/adjust_ci.py:67
↓ 2 callersFunctionget_ndcg
(test_data, rank)
data/movie/adjust_ci.py:65
↓ 2 callersFunctiontokenize
(prompt, add_eos_token=True)
train.py:126
↓ 1 callersFunctionbatch
(list, batch_size=1)
data/game/adjust_ci.py:45
↓ 1 callersFunctionbatch
(list, batch_size=1)
data/game/evaluate.py:57
↓ 1 callersFunctionbatch
(list, batch_size=1)
data/movie/adjust_ci.py:43
↓ 1 callersFunctionbatch
(list, batch_size=1)
data/movie/adjust_pda.py:43
↓ 1 callersFunctionbatch
(list, batch_size=1)
data/movie/evaluate.py:49
↓ 1 callersFunctionevaluate
( instructions, inputs=None, temperature=0, top_p=0.9, top_k=40,
inference.py:92
↓ 1 callersFunctiongenerate_prompt
(instruction, input=None)
inference.py:149
↓ 1 callersFunctionget_hr
(test_data, rank)
data/movie/adjust_pda.py:81
Functionmain
( load_8bit: bool = False, base_model: str = "", lora_weights: str = "tloen/alpaca-lora-7b", t
inference.py:29
Functiontrain
( # model/data params base_model: str = "", # the only required argument train_data_path: List[st
train.py:29