本文整理匯總了Python中tensorflow.python.framework.graph_util_impl.convert_variables_to_constants方法的典型用法代碼示例。如果您正苦於以下問題：Python graph_util_impl.convert_variables_to_constants方法的具體用法？Python graph_util_impl.convert_variables_to_constants怎麽用？Python graph_util_impl.convert_variables_to_constants使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類tensorflow.python.framework.graph_util_impl的用法示例。
在下文中一共展示了graph_util_impl.convert_variables_to_constants方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: freeze
# 需要導入模塊: from tensorflow.python.framework import graph_util_impl [as 別名]
# 或者: from tensorflow.python.framework.graph_util_impl import convert_variables_to_constants [as 別名]
def freeze():
checkpoint_prefix = os.path.join(TMP_DIR, "saved_checkpoint")
checkpoint_state_name = "checkpoint_state"
input_graph_name = "input_graph.pb"
output_graph_name = "freezed.pb"
saver_write_version = 1
# We'll create an input graph that has a single variable containing 1.0,
# and that then multiplies it by 2.
from tensorflow.python.framework import ops
with ops.Graph().as_default():
from keras import backend as K
K.set_learning_phase(0)
model = createModel()
model.load_weights(KERAS_WEIGHTS_FILE)
sess = K.get_session()
from tensorflow.python.framework.graph_util_impl import convert_variables_to_constants
# convert_variables_to_constants(sess, sess.graph.as_graph_def(), [model.output.name.split(':')[0]])
testGraph(sess, '')
from tensorflow.python.training import saver as saver_lib
saver = saver_lib.Saver(write_version=saver_write_version)
checkpoint_path = saver.save(
sess,
checkpoint_prefix,
global_step=0,
latest_filename=checkpoint_state_name)
from tensorflow.python.framework import graph_io
graph_io.write_graph(sess.graph, TMP_DIR, input_graph_name)
sess.close()
# We save out the graph to disk, and then call the const conversion
# routine.
input_graph_path = os.path.join(TMP_DIR, input_graph_name)
input_saver_def_path = ""
input_binary = False
output_node_names = model.output.name.split(':')[0]
restore_op_name = "save/restore_all"
filename_tensor_name = "save/Const:0"
output_graph_path = os.path.join(MODEL_DATA_DIR, output_graph_name)
clear_devices = False
from tensorflow.python.tools import freeze_graph
freeze_graph.freeze_graph(input_graph_path, input_saver_def_path,
input_binary, checkpoint_path, output_node_names,
restore_op_name, filename_tensor_name,
output_graph_path, clear_devices, "")
exportWordIndex(loadWordIndex())