Corrected 3 small typos in training.py error messages.
@@ -195,7 +195,7 @@ def _standardize_sample_or_class_weights(x_weight, output_names, weight_type):
else:
raise TypeError('The model has multiple outputs, so `' +
weight_type + '` '
- 'should be either a list of a dict. '
+ 'should be either a list or a dict. '
'Provided `' + weight_type +
'` type not understood: ' +
str(x_weight))
@@ -701,7 +701,7 @@ class Model(Container):
elif isinstance(loss_weights, list):
if len(loss_weights) != len(self.outputs):
raise ValueError('When passing a list as loss_weights, '
- 'it should have one entry per model outputs. '
+ 'it should have one entry per model output. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed loss_weights=' +
str(loss_weights))
@@ -719,7 +719,7 @@ class Model(Container):
if len(target_tensors) != len(self.outputs):
raise ValueError(
'When passing a list as `target_tensors`, '
- 'it should have one entry per model outputs. '
+ 'it should have one entry per model output. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed target_tensors=' +
str(target_tensors))
@@ -794,7 +794,7 @@ class Model(Container):
elif isinstance(sample_weight_mode, list):
if len(sample_weight_mode) != len(self.outputs):
raise ValueError('When passing a list as sample_weight_mode, '
- 'it should have one entry per model outputs. '
+ 'it should have one entry per model output. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed '
'sample_weight_mode=' +
