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fix pylint issue #169

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Merged
chensuyue merged 1 commit into from
Nov 25, 2022
Merged

fix pylint issue #169

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18 changes: 12 additions & 6 deletions neural_compressor/experimental/common/criterion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1252,14 +1252,17 @@ def __call__(self, **kwargs):
class SelfKnowledgeDistillationLoss(KnowledgeDistillationFramework):
"""SelfKnowledge Distillation Loss."""

def __init__(self, layer_mappings=[], loss_types=None, loss_weights=None, temperature=1.0,add_origin_loss=False, student_model=None, teacher_model=None):
def __init__(self, layer_mappings=[], loss_types=None, loss_weights=None, temperature=1.0,add_origin_loss=False,
student_model=None, teacher_model=None):
"""Initialize SelfKnowledge Distillation Loss class.

Args:
layer_mappings (list): layers of distillation.Format like
[[[student1_layer_name1, teacher_layer_name1],[student2_layer_name1, teacher_layer_name1]],[[student1_layer_name2, teacher_layer_name2],[student2_layer_name2, teacher_layer_name2]]]
[[[student1_layer_name1, teacher_layer_name1],[student2_layer_name1, teacher_layer_name1]],
[[student1_layer_name2, teacher_layer_name2],[student2_layer_name2, teacher_layer_name2]]]
loss_types (list, optional): loss types. Defaults to ['CE'] * len(layer_mappings).
loss_weights (list, optional): loss weights. Defaults to [1.0 / len(layer_mappings)] * len(layer_mappings).temperature (float, optional): use to calculate the soft label CE.
loss_weights (list, optional): loss weights. Defaults to [1.0 / len(layer_mappings)] *
len(layer_mappings).temperature (float, optional): use to calculate the soft label CE.
temperature (optional): temperature. Defaults to 1.0.
add_origin_loss (bool, optional): whether to add origin loss for hard label loss.
student_model (optional): student model. Defaults to None.
Expand Down Expand Up @@ -1342,14 +1345,17 @@ class PyTorchSelfKnowledgeDistillationLoss(
SelfKnowledgeDistillationLoss
):
"""PyTorch SelfKnowledge Distillation Loss."""
def __init__(self, layer_mappings=[], loss_types=None, loss_weights=None, temperature=1.0,add_origin_loss=False, student_model=None, teacher_model=None):
def __init__(self, layer_mappings=[], loss_types=None, loss_weights=None, temperature=1.0,add_origin_loss=False,
student_model=None, teacher_model=None):
"""Initialize PyTorch SelfKnowledge Distillation Loss class.

Args:
layer_mappings (list): layers of distillation.Format like
[[[student1_layer_name1, teacher_layer_name1],[student2_layer_name1, teacher_layer_name1]],[[student1_layer_name2, teacher_layer_name2],[student2_layer_name2, teacher_layer_name2]]]
[[[student1_layer_name1, teacher_layer_name1],[student2_layer_name1, teacher_layer_name1]],
[[student1_layer_name2, teacher_layer_name2],[student2_layer_name2, teacher_layer_name2]]]
loss_types (list, optional): loss types. Defaults to ['CE'] * len(layer_mappings).
loss_weights (list, optional): loss weights. Defaults to [1.0 / len(layer_mappings)] * len(layer_mappings).temperature (float, optional): use to calculate the soft label CE.
loss_weights (list, optional): loss weights. Defaults to [1.0 / len(layer_mappings)] *
len(layer_mappings).temperature (float, optional): use to calculate the soft label CE.
temperature (optional): temperature. Defaults to 1.0.
add_origin_loss (bool, optional): whether to add origin loss for hard label loss.
student_model (optional): student model. Defaults to None.
Expand Down