[python] avoid to set all weight to 1. (#1152)

* avoid to set all weight to 1.

* fix valid_class_weight

python-package/lightgbm/basic.py

@@ -1105,6 +1105,8 @@ class Dataset(object):
         weight : list, numpy array or None
             Weight to be set for each data point.
         """
+        if weight is not None and np.all(weight == 1):
+            weight = None
         self.weight = weight
         if self.handle is not None and weight is not None:
             weight = list_to_1d_numpy(weight, name='weight')

python-package/lightgbm/sklearn.py

@@ -418,6 +418,7 @@ class LGBMModel(_LGBMModelBase):
             X, y = _LGBMCheckXY(X, y, accept_sparse=True, force_all_finite=False, ensure_min_samples=2)
             _LGBMCheckConsistentLength(X, y, sample_weight)
 
+        if self.class_weight is not None:
             class_sample_weight = _LGBMComputeSampleWeight(self.class_weight, y)
             if sample_weight is None or len(sample_weight) == 0:
                 sample_weight = class_sample_weight
@@ -452,6 +453,7 @@ class LGBMModel(_LGBMModelBase):
                         else:
                             raise TypeError('eval_sample_weight, eval_class_weight, eval_init_score, and eval_group should be dict or list')
                     valid_weight = get_meta_data(eval_sample_weight, i)
+                    if get_meta_data(eval_class_weight, i) is not None:
                         valid_class_sample_weight = _LGBMComputeSampleWeight(get_meta_data(eval_class_weight, i), valid_data[1])
                         if valid_weight is None or len(valid_weight) == 0:
                             valid_weight = valid_class_sample_weight