def test_conv(depth, image_width, image_height, image_batch_count, filter_size,
filter_count, stride, padding, input_values, filter_values):
"""Tests a Conv replacement."""
input_constant_name = "input_constant"
filter_constant_name = "filter_constant"
conv_name = "conv"
float_graph_def = graph_pb2.GraphDef()
input_constant = quantize_graph.create_constant_node(
input_constant_name,
value=input_values,
dtype=dtypes.float32,
shape=[image_batch_count, image_height, image_width, depth])
float_graph_def.node.extend([input_constant])
filter_constant = quantize_graph.create_constant_node(
filter_constant_name,
value=filter_values,
dtype=dtypes.float32,
shape=[filter_size, filter_size, depth, filter_count])
float_graph_def.node.extend([filter_constant])
conv_node = quantize_graph.create_node(
"Conv2D", conv_name, [input_constant_name, filter_constant_name])
quantize_graph.set_attr_dtype(conv_node, "T", dtypes.float32)
quantize_graph.set_attr_int_list(conv_node, "strides", [1, stride, stride, 1])
quantize_graph.set_attr_string(conv_node, "padding", padding)
float_graph_def.node.extend([conv_node])
test_graph(float_graph_def, {}, [conv_name])
def test_max_pool(self):
input_constant_name = "input_constant"
max_pool_name = "max_pool"
float_graph_def = graph_pb2.GraphDef()
input_constant = quantize_graph.create_constant_node(
input_constant_name,
value=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
dtype=dtypes.float32,
shape=[1, 2, 6, 1])
float_graph_def.node.extend([input_constant])
max_pool_node = quantize_graph.create_node("MaxPool", max_pool_name,
[input_constant_name])
quantize_graph.set_attr_int_list(max_pool_node, "ksize", [1, 2, 2, 1])
quantize_graph.set_attr_int_list(max_pool_node, "strides", [1, 1, 1, 1])
quantize_graph.set_attr_string(max_pool_node, "padding", b"SAME")
float_graph_def.node.extend([max_pool_node])
test_graph(float_graph_def, {}, [max_pool_name])
def test_avg_pool(self):
input_constant_name = "input_constant"
avg_pool_name = "avg_pool"
float_graph_def = tf.GraphDef()
input_constant = quantize_graph.create_constant_node(input_constant_name,
value=[1, 2, 3, 4, 5,
6, 7, 8, 9, 10,
11, 12],
dtype=tf.float32,
shape=[1, 2, 6, 1])
float_graph_def.node.extend([input_constant])
avg_pool_node = quantize_graph.create_node("AvgPool", avg_pool_name,
[input_constant_name])
quantize_graph.set_attr_dtype(avg_pool_node, "T", tf.float32)
quantize_graph.set_attr_int_list(avg_pool_node, "ksize", [1, 2, 2, 1])
quantize_graph.set_attr_int_list(avg_pool_node, "strides", [1, 1, 1, 1])
quantize_graph.set_attr_string(avg_pool_node, "padding", b"SAME")
float_graph_def.node.extend([avg_pool_node])
test_graph(float_graph_def, {}, [avg_pool_name])
def test_avg_pool(self):
input_constant_name = "input_constant"
avg_pool_name = "avg_pool"
float_graph_def = tf.GraphDef()
input_constant = quantize_graph.create_constant_node(
input_constant_name,
value=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
dtype=tf.float32,
shape=[1, 2, 6, 1])
float_graph_def.node.extend([input_constant])
avg_pool_node = quantize_graph.create_node("AvgPool", avg_pool_name,
[input_constant_name])
quantize_graph.set_attr_dtype(avg_pool_node, "T", tf.float32)
quantize_graph.set_attr_int_list(avg_pool_node, "ksize", [1, 2, 2, 1])
quantize_graph.set_attr_int_list(avg_pool_node, "strides",
[1, 1, 1, 1])
quantize_graph.set_attr_string(avg_pool_node, "padding", b"SAME")
float_graph_def.node.extend([avg_pool_node])
test_graph(float_graph_def, {}, [avg_pool_name])
