import unittest import sys try: import py_paddle del py_paddle except ImportError: print >> sys.stderr, "It seems swig of Paddle is not installed, this " \ "unittest will not be run." sys.exit(0) import paddle.v2.parameters as parameters import paddle.v2.data_type as data_type import paddle.v2.layer as layer from paddle.v2.attr import ParamAttr from paddle.proto.ParameterConfig_pb2 import ParameterConfig import random import cStringIO import numpy def __rand_param_config__(name, psize=None): conf = ParameterConfig() conf.name = name size = 1 if psize is None: for i in xrange(2): dim = random.randint(1, 1000) conf.dims.append(dim) size *= dim else: size = psize conf.size = size assert conf.IsInitialized() return conf class TestParameters(unittest.TestCase): def test_serialization(self): params = parameters.Parameters() params.__append_config__(__rand_param_config__("param_0")) params.__append_config__(__rand_param_config__("param_1")) for name in params.names(): param = params.get(name) param[:] = numpy.random.uniform( -1.0, 1.0, size=params.get_shape(name)) params.set(name, param) tmp_file = cStringIO.StringIO() params.to_tar(tmp_file) tmp_file.seek(0) params_dup = parameters.Parameters.from_tar(tmp_file) self.assertEqual(params_dup.names(), params.names()) for name in params.names(): self.assertEqual(params.get_shape(name), params_dup.get_shape(name)) p0 = params.get(name) p1 = params_dup.get(name) self.assertTrue(numpy.isclose(p0, p1).all()) def test_initializer(self): def initializer(name): assert name == "fc.w" mat = numpy.ones((3, 2), dtype=numpy.float32) mat[1, 1] = 2 return mat x = layer.data(name="x", type=data_type.dense_vector(3)) y = layer.fc(x, size=2, bias_attr=False, param_attr=ParamAttr( name="fc.w", initializer=initializer)) params = parameters.create(y) val = params["fc.w"] assert val.shape == (3, 2) expected = numpy.array([[1, 1], [1, 2], [1, 1]], numpy.float32) assert numpy.logical_and.reduce(numpy.reshape(val == expected, 6)) def test_init_from_tar(self): def get_param(names, size): p = parameters.Parameters() for k, v in zip(names, size): p.__append_config__(__rand_param_config__(k, v)) for name in p.names(): param = p.get(name) param[:] = numpy.random.uniform( -1.0, 1.0, size=p.get_shape(name)) p.set(name, param) return p def get_parames(): name1 = ['param_0', 'param_1'] size1 = [128, 256] p1 = get_param(name1, size1) file1 = cStringIO.StringIO() p1.to_tar(file1) file1.seek(0) name2 = ['param_0', 'param_1', 'param_2'] size2 = [128, 256, 288] p2 = get_param(name2, size2) file2 = cStringIO.StringIO() p2.to_tar(file2) file2.seek(0) return p1, file1, p2, file2 p1, file1, p2, file2 = get_parames() p2.init_from_tar(file1) for name in p1.names(): self.assertEqual(p1.get_shape(name), p2.get_shape(name)) v1 = p1.get(name) v2 = p2.get(name) self.assertTrue(numpy.isclose(v1, v2).all()) p1, file1, p2, file2 = get_parames() p1.init_from_tar(file2) for name in p1.names(): self.assertEqual(p1.get_shape(name), p2.get_shape(name)) v1 = p1.get(name) v2 = p2.get(name) self.assertTrue(numpy.isclose(v1, v2).all()) if __name__ == '__main__': unittest.main()