diff --git a/paddleslim/dist/single_distiller.py b/paddleslim/dist/single_distiller.py index defb19a8a6ecda8f2a747033323ccb8eeda07281..70b843c90fec6bdf906045dbac3097f8dfba3ff1 100644 --- a/paddleslim/dist/single_distiller.py +++ b/paddleslim/dist/single_distiller.py @@ -107,7 +107,8 @@ def fsp_loss(teacher_var1_name, teacher_var2_name, student_var1_name, student_var2_name(str): The name of student_var2. Except for the second dimension, all other dimensions should be consistent with student_var1. - program(Program): The input distiller program. + program(Program): The input distiller program. + default: fluid.default_main_program() Return(Variable): fsp distiller loss. """ teacher_var1 = program.global_block().var(teacher_var1_name) @@ -128,7 +129,8 @@ def l2_loss(teacher_var_name, student_var_name, Args: teacher_var_name(str): The name of teacher_var. student_var_name(str): The name of student_var. - program(Program): The input distiller program. + program(Program): The input distiller program. + default: fluid.default_main_program() Return(Variable): l2 distiller loss. """ student_var = program.global_block().var(student_var_name) @@ -148,7 +150,8 @@ def soft_label_loss(teacher_var_name, Args: teacher_var_name(str): The name of teacher_var. student_var_name(str): The name of student_var. - program(Program): The input distiller program. + program(Program): The input distiller program. + default: fluid.default_main_program() teacher_temperature(float): Temperature used to divide teacher_feature_map before softmax. default: 1.0 student_temperature(float): Temperature used to divide @@ -170,7 +173,8 @@ def loss(loss_func, program=fluid.default_main_program(), **kwargs): """ Combine variables from student model and teacher model by self defined loss. Args: - program(Program): The input distiller program. + program(Program): The input distiller program. + default: fluid.default_main_program() loss_func(function): The user self defined loss function. Return(Variable): self defined distiller loss. """