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import numpy as np
import unittest
import caffe
class TestBlobProtoToArray(unittest.TestCase):
def test_old_format(self):
data = np.zeros((10,10))
blob = caffe.proto.caffe_pb2.BlobProto()
blob.data.extend(list(data.flatten()))
shape = (1,1,10,10)
blob.num, blob.channels, blob.height, blob.width = shape
arr = caffe.io.blobproto_to_array(blob)
self.assertEqual(arr.shape, shape)
def test_new_format(self):
data = np.zeros((10,10))
blob = caffe.proto.caffe_pb2.BlobProto()
blob.data.extend(list(data.flatten()))
blob.shape.dim.extend(list(data.shape))
arr = caffe.io.blobproto_to_array(blob)
self.assertEqual(arr.shape, data.shape)
def test_no_shape(self):
data = np.zeros((10,10))
blob = caffe.proto.caffe_pb2.BlobProto()
blob.data.extend(list(data.flatten()))
with self.assertRaises(ValueError):
caffe.io.blobproto_to_array(blob)
def test_scalar(self):
data = np.ones((1)) * 123
blob = caffe.proto.caffe_pb2.BlobProto()
blob.data.extend(list(data.flatten()))
arr = caffe.io.blobproto_to_array(blob)
self.assertEqual(arr, 123)
class TestArrayToDatum(unittest.TestCase):
def test_label_none_size(self):
# Set label
d1 = caffe.io.array_to_datum(
np.ones((10,10,3)), label=1)
# Don't set label
d2 = caffe.io.array_to_datum(
np.ones((10,10,3)))
# Not setting the label should result in a smaller object
self.assertGreater(
len(d1.SerializeToString()),
len(d2.SerializeToString()))
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