Finishing Colincsl's SpatialDropout1D (keras-team#4416)

* Added SpatialDropout1D

This is a straightforward modification of SpatialDropout2D but for 1D data.

* Added SpatialDropout1D to docs

* SpatialDropout1D test

* Fixed indent issue

* Combined TF and TH dimension conditions

Use the same 1D dimensions for TensorFlow and Theano in SpatialDropout1D.

* trailing whitespace

* Removed dim_ordering variable

* Removing dim_ordering values

removing dim_ordering values as requested

docs/autogen.py

@@ -139,6 +139,7 @@
             core.Dense,
             core.Activation,
             core.Dropout,
+            core.SpatialDropout1D,
             core.SpatialDropout2D,
             core.SpatialDropout3D,
             core.Flatten,

keras/layers/core.py

@@ -96,6 +96,37 @@ def get_config(self):
         return dict(list(base_config.items()) + list(config.items()))
 
 
+class SpatialDropout1D(Dropout):
+    '''This version performs the same function as Dropout, however it drops
+    entire 1D feature maps instead of individual elements. If adjacent frames
+    within feature maps are strongly correlated (as is normally the case in
+    early convolution layers) then regular dropout will not regularize the
+    activations and will otherwise just result in an effective learning rate
+    decrease. In this case, SpatialDropout1D will help promote independence
+    between feature maps and should be used instead.
+
+    # Arguments
+        p: float between 0 and 1. Fraction of the input units to drop.
+
+    # Input shape
+        3D tensor with shape:
+        `(samples, timesteps, channels)`
+
+    # Output shape
+        Same as input
+
+    # References
+        - [Efficient Object Localization Using Convolutional Networks](https://arxiv.org/pdf/1411.4280.pdf)
+    '''
+    def __init__(self, p, **kwargs):
+        super(SpatialDropout1D, self).__init__(p, **kwargs)
+
+    def _get_noise_shape(self, x):
+        input_shape = K.shape(x)
+        noise_shape = (input_shape[0], 1, input_shape[2])
+        return noise_shape
+
+
 class SpatialDropout2D(Dropout):
     '''This version performs the same function as Dropout, however it drops
     entire 2D feature maps instead of individual elements. If adjacent pixels

tests/keras/layers/test_core.py

@@ -153,6 +153,10 @@ def test_dropout():
                kwargs={'p': 0.5},
                input_shape=(3, 2))
 
+    layer_test(core.SpatialDropout1D,
+               kwargs={'p': 0.5},
+               input_shape=(2, 3, 4))
+
     layer_test(core.SpatialDropout2D,
                kwargs={'p': 0.5},
                input_shape=(2, 3, 4, 5))