本文整理匯總了Python中keras.layers.SpatialDropout3D方法的典型用法代碼示例。如果您正苦於以下問題：Python layers.SpatialDropout3D方法的具體用法？Python layers.SpatialDropout3D怎麽用？Python layers.SpatialDropout3D使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類keras.layers的用法示例。
在下文中一共展示了layers.SpatialDropout3D方法的3個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: keras_dropout
# 需要導入模塊: from keras import layers [as 別名]
# 或者: from keras.layers import SpatialDropout3D [as 別名]
def keras_dropout(layer, rate):
"""
Keras dropout layer.
"""
from keras import layers
input_dim = len(layer.input.shape)
if input_dim == 2:
return layers.SpatialDropout1D(rate)
elif input_dim == 3:
return layers.SpatialDropout2D(rate)
elif input_dim == 4:
return layers.SpatialDropout3D(rate)
else:
return layers.Dropout(rate) 示例2: test_dropout
# 需要導入模塊: from keras import layers [as 別名]
# 或者: from keras.layers import SpatialDropout3D [as 別名]
def test_dropout():
layer_test(layers.Dropout,
kwargs={'rate': 0.5},
input_shape=(3, 2))
layer_test(layers.Dropout,
kwargs={'rate': 0.5, 'noise_shape': [3, 1]},
input_shape=(3, 2))
layer_test(layers.Dropout,
kwargs={'rate': 0.5, 'noise_shape': [None, 1]},
input_shape=(3, 2))
layer_test(layers.SpatialDropout1D,
kwargs={'rate': 0.5},
input_shape=(2, 3, 4))
for data_format in ['channels_last', 'channels_first']:
for shape in [(4, 5), (4, 5, 6)]:
if data_format == 'channels_last':
input_shape = (2,) + shape + (3,)
else:
input_shape = (2, 3) + shape
layer_test(layers.SpatialDropout2D if len(shape) == 2 else layers.SpatialDropout3D,
kwargs={'rate': 0.5,
'data_format': data_format},
input_shape=input_shape)
# Test invalid use cases
with pytest.raises(ValueError):
layer_test(layers.SpatialDropout2D if len(shape) == 2 else layers.SpatialDropout3D,
kwargs={'rate': 0.5,
'data_format': 'channels_middle'},
input_shape=input_shape) 示例3: create_context_module
# 需要導入模塊: from keras import layers [as 別名]
# 或者: from keras.layers import SpatialDropout3D [as 別名]
def create_context_module(input_layer, n_level_filters, dropout_rate=0.3, data_format="channels_first"):
convolution1 = create_convolution_block(input_layer=input_layer, n_filters=n_level_filters)
dropout = SpatialDropout3D(rate=dropout_rate, data_format=data_format)(convolution1)
convolution2 = create_convolution_block(input_layer=dropout, n_filters=n_level_filters)
return convolution2