Python keras.layers.SpatialDropout3D() Examples

The following are 10 code examples of keras.layers.SpatialDropout3D(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module keras.layers , or try the search function .
Example #1
Source Project: nni   Author: microsoft   File: layers.py    License: MIT License 6 votes vote down vote up
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) 
Example #2
Source Project: DeepLearning_Wavelet-LSTM   Author: hello-sea   File: core_test.py    License: MIT License 5 votes vote down vote up
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) 
Example #3
Source Project: DeepLearning_Wavelet-LSTM   Author: hello-sea   File: core_test.py    License: MIT License 5 votes vote down vote up
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) 
Example #4
Source Project: DeepLearning_Wavelet-LSTM   Author: hello-sea   File: core_test.py    License: MIT License 5 votes vote down vote up
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) 
Example #5
Source Project: DeepLearning_Wavelet-LSTM   Author: hello-sea   File: core_test.py    License: MIT License 5 votes vote down vote up
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) 
Example #6
Source Project: DeepLearning_Wavelet-LSTM   Author: hello-sea   File: core_test.py    License: MIT License 5 votes vote down vote up
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) 
Example #7
Source Project: DeepLearning_Wavelet-LSTM   Author: hello-sea   File: core_test.py    License: MIT License 5 votes vote down vote up
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) 
Example #8
Source Project: DeepLearning_Wavelet-LSTM   Author: hello-sea   File: core_test.py    License: MIT License 5 votes vote down vote up
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) 
Example #9
Source Project: 3DUnetCNN   Author: ellisdg   File: isensee2017.py    License: MIT License 5 votes vote down vote up
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 
Example #10
Source Project: Keras-Brats-Improved-Unet3d   Author: MLearing   File: isensee2017.py    License: MIT License 5 votes vote down vote up
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