def test_conv_ext_false_bias_term(self, weights_biases_mock,
layout_attrs_mock):
weights_biases_mock.return_value = {}
layout_attrs_mock.return_value = {}
params = {
'pad': 10,
'kernel_size': 11,
'stride': 12,
'dilation': 13,
'group': 14,
'num_output': 15,
'bias_term': False
}
node = PB({'pb': FakeConvProtoLayer(FakeMultiParam(params))})
res = DeconvFrontExtractor.extract(node)
res = node
exp_res = {
'op': 'Deconv2D',
'pad': np.array([[0, 0], [0, 0], [10, 10], [10, 10]]),
'pad_spatial_shape': np.array([[10, 10], [10, 10]]),
'stride': np.array([1, 1, 12, 12]),
'kernel_spatial': np.array([11, 11]),
'dilation': np.array([1, 1, 13, 13]),
'group': 14,
'bias_addable': True,
'bias_term': False,
}
self.assertTrue(weights_biases_mock.called)
self.assertTrue(layout_attrs_mock.called)
for key in exp_res.keys():
if key in ('pad', 'pad_spatial_shape', 'stride', 'kernel_spatial',
'dilation', 'bias_term'):
np.testing.assert_equal(res[key], exp_res[key])
else:
self.assertEqual(res[key], exp_res[key])
def test_conv_ext_empty_numbers(self, weights_biases_mock,
layout_attrs_mock):
weights_biases_mock.return_value = {}
layout_attrs_mock.return_value = {}
params = {
'pad': None,
'kernel_size': None,
'stride': None,
'dilation': None,
'group': 14,
'num_output': 15,
'bias_term': True,
'pad_w': 3,
'pad_h': 4,
'kernel_w': 5,
'kernel_h': 6,
'stride_h': 3,
'stride_w': 2,
}
node = PB({'pb': FakeConvProtoLayer(FakeMultiParam(params))})
res = DeconvFrontExtractor.extract(node)
res = node
exp_res = {
'op': 'Deconv2D',
'pad': np.array([[0, 0], [0, 0], [4, 4], [3, 3]]),
'pad_spatial_shape': np.array([[4, 4], [3, 3]]),
'stride': np.array([1, 1, 3, 2]),
'kernel_spatial': np.array([6, 5]),
'dilation': np.array([1, 1, 1, 1]),
'group': 14,
'bias_addable': True,
}
self.assertTrue(weights_biases_mock.called)
self.assertTrue(layout_attrs_mock.called)
for key in exp_res.keys():
if key in ('pad', 'pad_spatial_shape', 'stride', 'kernel_spatial',
'dilation'):
np.testing.assert_equal(res[key], exp_res[key])
else:
self.assertEqual(res[key], exp_res[key])
