def test_replace_constant_graph_with_constant_node(self):
graph_analyzer = GraphAnalyzer()
graph_analyzer.graph = copy.deepcopy(self.graph_def)
graph_analyzer.parse_graph()
new_constant_value = np.random.random([4, 1])
new_constant_type = tf.as_dtype(np.float32(new_constant_value).dtype)
new_constant_node = GraphRewriterHelper.create_constant_node(
self.add_node.name + "_const", new_constant_value,
new_constant_type)
assert graph_analyzer.replace_constant_graph_with_constant_node(
new_constant_node, self.add_node.name)
result_graph = graph_analyzer.dump_graph()
assert len(list(result_graph.node)) == 10
new_constant_value = np.random.random([4, 1])
new_constant_type = tf.as_dtype(np.float32(new_constant_value).dtype)
new_constant_node = GraphRewriterHelper.create_constant_node(
self.mul_node.name + "_const", new_constant_value,
new_constant_type)
assert graph_analyzer.replace_constant_graph_with_constant_node(
new_constant_node, self.mul_node.name)
result_graph = graph_analyzer.dump_graph()
assert len(list(result_graph.node)) == 8
new_constant_value = np.random.random([4, 1])
new_constant_type = tf.as_dtype(np.float32(new_constant_value).dtype)
new_constant_node = GraphRewriterHelper.create_constant_node(
self.sqrt_node.name + "_const", new_constant_value,
new_constant_type)
assert graph_analyzer.replace_constant_graph_with_constant_node(
new_constant_node, self.sqrt_node.name)
result_graph = graph_analyzer.dump_graph()
assert len(list(result_graph.node)) == 7
new_constant_value = np.random.random([4, 1])
new_constant_type = tf.as_dtype(np.float32(new_constant_value).dtype)
new_constant_node = GraphRewriterHelper.create_constant_node(
self.block_node.name + "_const", new_constant_value,
new_constant_type)
assert not graph_analyzer.replace_constant_graph_with_constant_node(
new_constant_node, self.block_node.name)
def test_no_input_output_config(self):
g = GraphAnalyzer()
g.graph = self.input_graph
g.parse_graph()
float_graph_def = g.dump_graph()
from lpot import Quantization, common
quantizer = Quantization('fake_yaml.yaml')
dataset = quantizer.dataset('dummy', shape=(20, 224, 224, 3), label=True)
quantizer.calib_dataloader = common.DataLoader(dataset, batch_size=2)
quantizer.eval_dataloader = common.DataLoader(dataset, batch_size=2)
quantizer.model = float_graph_def
output_graph = quantizer()
self.assertGreater(len(output_graph.graph_def.node), 0)
def test_replace_node(self):
graph_analyzer = GraphAnalyzer()
graph_analyzer.graph = copy.deepcopy(self.graph_def)
graph_analyzer.parse_graph()
new_add_node = node_def_pb2.NodeDef()
new_add_node.op = "Add"
new_add_node.name = "add1"
new_add_node.input.extend(
[self.input0_node.name, self.input1_node.name])
graph_analyzer.replace_node(new_add_node, self.add_node.name,
[self.mul_node.name])
result_graph = graph_analyzer.dump_graph()
assert self.add_node not in list(result_graph.node)
assert new_add_node in list(result_graph.node)
def test_invalid_input_output_config(self):
g = GraphAnalyzer()
g.graph = self.input_graph
g.parse_graph()
float_graph_def = g.dump_graph()
from lpot import Quantization, common
quantizer = Quantization('fake_yaml_2.yaml')
dataset = quantizer.dataset('dummy', shape=(20, 224, 224, 3), label=True)
quantizer.calib_dataloader = common.DataLoader(dataset, batch_size=2)
quantizer.eval_dataloader = common.DataLoader(dataset, batch_size=2)
quantizer.model = float_graph_def
model = quantizer()
# will detect the right inputs/outputs
self.assertNotEqual(model.input_node_names, ['x'])
self.assertNotEqual(model.output_node_names, ['op_to_store'])