完整報錯如下:

--------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-4-85ad0fe8ebcc> in <module>()4 # model = tf.keras.models.load_model('cats_and_dogs_small_2.h5')5 ----> 6 model = load_model('cats_and_dogs_small_2.h5')7 model.summary() # As a reminder.15 frames /usr/local/lib/python3.6/dist-packages/keras/engine/saving.py in load_wrapper(*args, **kwargs)456 os.remove(tmp_filepath)457 return res --> 458 return load_function(*args, **kwargs)459 460 return load_wrapper/usr/local/lib/python3.6/dist-packages/keras/engine/saving.py in load_model(filepath, custom_objects, compile)548 if H5Dict.is_supported_type(filepath):549 with H5Dict(filepath, mode='r') as h5dict: --> 550 model = _deserialize_model(h5dict, custom_objects, compile)551 elif hasattr(filepath, 'write') and callable(filepath.write):552 def load_function(h5file):/usr/local/lib/python3.6/dist-packages/keras/engine/saving.py in _deserialize_model(h5dict, custom_objects, compile)241 raise ValueError('No model found in config.')242 model_config = json.loads(model_config.decode('utf-8')) --> 243 model = model_from_config(model_config, custom_objects=custom_objects)244 model_weights_group = h5dict['model_weights']245 /usr/local/lib/python3.6/dist-packages/keras/engine/saving.py in model_from_config(config, custom_objects)591 '`Sequential.from_config(config)`?')592 from ..layers import deserialize --> 593 return deserialize(config, custom_objects=custom_objects)594 595 /usr/local/lib/python3.6/dist-packages/keras/layers/__init__.py in deserialize(config, custom_objects)166 module_objects=globs,167 custom_objects=custom_objects, --> 168 printable_module_name='layer')/usr/local/lib/python3.6/dist-packages/keras/utils/generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)145 config['config'],146 custom_objects=dict(list(_GLOBAL_CUSTOM_OBJECTS.items()) + --> 147 list(custom_objects.items())))148 with CustomObjectScope(custom_objects):149 return cls.from_config(config['config'])/usr/local/lib/python3.6/dist-packages/keras/engine/sequential.py in from_config(cls, config, custom_objects)299 for conf in layer_configs:300 layer = layer_module.deserialize(conf, --> 301 custom_objects=custom_objects)302 model.add(layer)303 if not model.inputs and build_input_shape:/usr/local/lib/python3.6/dist-packages/keras/layers/__init__.py in deserialize(config, custom_objects)166 module_objects=globs,167 custom_objects=custom_objects, --> 168 printable_module_name='layer')/usr/local/lib/python3.6/dist-packages/keras/utils/generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)147 list(custom_objects.items())))148 with CustomObjectScope(custom_objects): --> 149 return cls.from_config(config['config'])150 else:151 # Then `cls` may be a function returning a class./usr/local/lib/python3.6/dist-packages/keras/engine/base_layer.py in from_config(cls, config)1101 A layer instance.1102 """ -> 1103 return cls(**config)1104 1105 def count_params(self):/usr/local/lib/python3.6/dist-packages/keras/legacy/interfaces.py in wrapper(*args, **kwargs)89 warnings.warn('Update your `' + object_name + '` call to the ' +90 'Keras 2 API: ' + signature, stacklevel=2) ---> 91 return func(*args, **kwargs)92 wrapper._original_function = func93 return wrapper/usr/local/lib/python3.6/dist-packages/keras/layers/convolutional.py in __init__(self, filters, kernel_size, strides, padding, data_format, dilation_rate, activation, use_bias, kernel_initializer, bias_initializer, kernel_regularizer, bias_regularizer, activity_regularizer, kernel_constraint, bias_constraint, **kwargs)482 kernel_constraint=kernel_constraint,483 bias_constraint=bias_constraint, --> 484 **kwargs)485 486 def get_config(self):/usr/local/lib/python3.6/dist-packages/keras/layers/convolutional.py in __init__(self, rank, filters, kernel_size, strides, padding, data_format, dilation_rate, activation, use_bias, kernel_initializer, bias_initializer, kernel_regularizer, bias_regularizer, activity_regularizer, kernel_constraint, bias_constraint, **kwargs)115 self.activation = activations.get(activation)116 self.use_bias = use_bias --> 117 self.kernel_initializer = initializers.get(kernel_initializer)118 self.bias_initializer = initializers.get(bias_initializer)119 self.kernel_regularizer = regularizers.get(kernel_regularizer)/usr/local/lib/python3.6/dist-packages/keras/initializers.py in get(identifier)499 def get(identifier):500 if isinstance(identifier, dict): --> 501 return deserialize(identifier)502 elif isinstance(identifier, six.string_types):503 config = {'class_name': str(identifier), 'config': {}}/usr/local/lib/python3.6/dist-packages/keras/initializers.py in deserialize(config, custom_objects)494 module_objects=globals(),495 custom_objects=custom_objects, --> 496 printable_module_name='initializer')497 498 /usr/local/lib/python3.6/dist-packages/keras/utils/generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)138 if cls is None:139 raise ValueError('Unknown ' + printable_module_name + --> 140 ': ' + class_name)141 if hasattr(cls, 'from_config'):142 custom_objects = custom_objects or {}ValueError: Unknown initializer: GlorotUniform

解決方案如下:

from keras.models import load_model import tensorflow as tf model = load_model('cats_and_dogs_small_2.h5') model.summary() # As a reminder.

改成:

from keras.models import load_model import tensorflow as tf model = tf.keras.models.load_model('cats_and_dogs_small_2.h5') model.summary() # As a reminder.

?

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