def test_create_from_py_layer_parameter(self):
plp = caffe_pb2.LayerParameter()
plp.type = 'Convolution'
plp.name = 'conv1'
lp = caffe.LayerParameter(plp)
plp2 = lp.to_python()
self.assertEqual(plp, plp2)
def upsample_creator(factor, num_in):
kernel = get_kernel_size(factor)
stride = factor
lp = caffe.LayerParameter(
"""name: "upsample", type: "Deconvolution"
convolution_param { kernel_size: %d stride: %d num_output: %d group: %d pad: %d
weight_filler: { type: "bilinear_upsampling" } bias_term: false }""" %
(kernel, stride, num_in, num_in, get_pad(factor)))
return caffe.create_layer(lp.to_python())
def test_from_python(self):
plp = caffe_pb2.LayerParameter()
plp.type = 'Convolution'
plp.name = 'conv1'
lp = caffe.LayerParameter("")
lp.from_python(plp)
def test_create_from_py_layer_parameter(self):
plp = caffe_pb2.LayerParameter()
plp.type = 'Convolution'
plp.name = 'conv1'
lp = caffe.LayerParameter(plp)
def test_create_from_string(self):
lp = caffe.LayerParameter("type: 'Convolution' name: 'conv1'")