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Types & classes25 in github.com/OpenGVLab/EfficientQAT

⨍ Functions 110◇ Types & classes 25
↓ 38 callersClassConversation
A class that manages prompt templates and keeps all conversation history.
deita_dataset/conversation.py:30
↓ 6 callersClassBlockTrainDataset
datautils_block.py:231
↓ 2 callersClassCatcher
quantize/block_ap.py:79
↓ 1 callersClassCustomizedTritonAutoTuner
quantize/triton_utils/custom_autotune.py:15
↓ 1 callersClassDataCollatorForCausalLM
datautils_e2e.py:21
↓ 1 callersClassQuantLinear
quantize/int_linear_real.py:26
↓ 1 callersClassSupervisedDataset
Dataset for supervised fine-tuning.
deita_dataset/train.py:260
↓ 1 callersClassUniformAffineQuantizer
quantize/quantizer.py:23
ClassDataArguments
main_e2e_qp.py:82
ClassDataArguments
deita_dataset/train.py:44
ClassErrorCode
https://platform.openai.com/docs/guides/error-codes/api-errors
deita_dataset/constants.py:34
ClassGenerationArguments
main_e2e_qp.py:197
ClassLazySupervisedDataset
Dataset for supervised fine-tuning.
deita_dataset/train.py:295
ClassModelArguments
main_e2e_qp.py:63
ClassModelArguments
deita_dataset/train.py:38
ClassMultiBlock
quantize/utils.py:8
ClassNativeScalerWithGradNormCount
utils.py:25
ClassPPLvalCallback
main_e2e_qp.py:431
ClassQuantLinear
Quantized Module that can perform quantized convolution or normal convolution. To activate quantization, please use set_quant_state function.
quantize/int_linear_fake.py:10
ClassSeparatorStyle
Separator styles.
deita_dataset/conversation.py:10
ClassTrainingArguments
main_e2e_qp.py:136
ClassTrainingArguments
deita_dataset/train.py:53
ClassTritonModuleMixin
quantize/int_linear_real.py:20
ClassTritonModuleMixin
quantize/triton_utils/mixin.py:1
ClassTruncateFunction
quantize/utils.py:81