Add Dropout and BatchwiseDropout

PyTorch/sparseconvnet/dropout.py

+# Copyright 2016-present, Facebook, Inc.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from torch.autograd import Function, Variable
+from torch.nn import Module
+from .utils import *
+from .sparseConvNetTensor import SparseConvNetTensor
+
+class Dropout(Module):
+    def __init__(self, p = 0.5):
+        Module.__init__(self)
+        self.p = p
+    def forward(self, input):
+        output = SparseConvNetTensor()
+        i = input.features
+        if self.training:
+            m = i.new().resize_(1).expand_as(i).fill_(1-self.p)
+            output.features = i * torch.bernoulli(m)
+        else:
+            output.features = i * (1 - self.p)
+        output.metadata = input.metadata
+        output.spatial_size = input.spatial_size
+        return output
+    def input_spatial_size(self, out_size):
+        return out_size
+
+class BatchwiseDropout(Module):
+    def __init__(self, p = 0.5):
+        Module.__init__(self)
+        self.p = p
+    def forward(self, input):
+        output = SparseConvNetTensor()
+        i = input.features
+        if self.training:
+            m = i.new().resize_(1).expand(1,i.shape[1]).fill_(1-self.p)
+            output.features = i * torch.bernoulli(m)
+        else:
+            output.features = i * (1 - self.p)
+        output.metadata = input.metadata
+        output.spatial_size = input.spatial_size
+        return output
+    def input_spatial_size(self, out_size):
+        return out_size