--- /dev/null
+import caffe
+import numpy as np
+
+
+class EuclideanLossLayer(caffe.Layer):
+ """
+ Compute the Euclidean Loss in the same manner as the C++ EuclideanLossLayer
+ to demonstrate the class interface for developing layers in Python.
+ """
+
+ def setup(self, bottom, top):
+ # check input pair
+ if len(bottom) != 2:
+ raise Exception("Need two inputs to compute distance.")
+
+ def reshape(self, bottom, top):
+ # check input dimensions match
+ if bottom[0].count != bottom[1].count:
+ raise Exception("Inputs must have the same dimension.")
+ # difference is shape of inputs
+ self.diff = np.zeros_like(bottom[0].data, dtype=np.float32)
+ # loss output is scalar
+ top[0].reshape(1)
+
+ def forward(self, bottom, top):
+ self.diff[...] = bottom[0].data - bottom[1].data
+ top[0].data[...] = np.sum(self.diff**2) / bottom[0].num / 2.
+
+ def backward(self, top, propagate_down, bottom):
+ for i in range(2):
+ if not propagate_down[i]:
+ continue
+ if i == 0:
+ sign = 1
+ else:
+ sign = -1
+ bottom[i].diff[...] = sign * self.diff / bottom[i].num
--- /dev/null
+name: 'LinearRegressionExample'
+# define a simple network for linear regression on dummy data
+# that computes the loss by a PythonLayer.
+layer {
+ type: 'DummyData'
+ name: 'x'
+ top: 'x'
+ dummy_data_param {
+ shape: { dim: 10 dim: 3 dim: 2 }
+ data_filler: { type: 'gaussian' }
+ }
+}
+layer {
+ type: 'DummyData'
+ name: 'y'
+ top: 'y'
+ dummy_data_param {
+ shape: { dim: 10 dim: 3 dim: 2 }
+ data_filler: { type: 'gaussian' }
+ }
+}
+# include InnerProduct layers for parameters
+# so the net will need backward
+layer {
+ type: 'InnerProduct'
+ name: 'ipx'
+ top: 'ipx'
+ bottom: 'x'
+ inner_product_param {
+ num_output: 10
+ weight_filler { type: 'xavier' }
+ }
+}
+layer {
+ type: 'InnerProduct'
+ name: 'ipy'
+ top: 'ipy'
+ bottom: 'y'
+ inner_product_param {
+ num_output: 10
+ weight_filler { type: 'xavier' }
+ }
+}
+layer {
+ type: 'Python'
+ name: 'loss'
+ top: 'loss'
+ bottom: 'ipx'
+ bottom: 'ipy'
+ python_param {
+ # the module name -- usually the filename -- that needs to be in $PYTHONPATH
+ module: 'pyloss'
+ # the layer name -- the class name in the module
+ layer: 'EuclideanLossLayer'
+ }
+ # set loss weight so Caffe knows this is a loss layer.
+ # since PythonLayer inherits directly from Layer, this isn't automatically
+ # known to Caffe
+ loss_weight: 1
+}