Tensorflow function(一)

tf.import_graph_def:

import_graph_def(
    graph_def,
    input_map=None,
    return_elements=None,
    name=None,
    op_dict=None,
    producer_op_list=None
):
Imports the graph from graph_def into the current default Graph


This function provides a way to import a serialized TensorFlow GraphDef protocol buffer, and extract individual objects in the GraphDef as tf.Tensor and tf.Operation objects. Once extracted, these objects are placed into the current default Graph. See tf.Graph.as_graph_def for a way to create a GraphDef proto


Args:
graph_def: A GraphDef proto containing operations to be imported into the default graph.
name: (Optional.) A prefix that will be prepended to the names in graph_def. Note that this does not apply to       imported function names. Defaults to "import".
Returns:
A list of Operation and/or Tensor objects from the imported graph, corresponding to the names in return_elements




tf.Graph:


as_default():
Returns a context manager that makes this Graph the default graph.


This method should be used if you want to create multiple graphs in the same process. For convenience, a global default graph is provided, and all ops will be added to this graph if you do not create a new graph explicitly. Use this method with the with keyword to specify that ops created within the scope of a block should be added to this graph.


The default graph is a property of the current thread. If you create a new thread, and wish to use the default graph in that thread, you must explicitly add a with g.as_default(): in that thread's function.


Returns:
A context manager for using this graph as the default graph.




tf.gfile.GFile:

File I/O wrappers without thread locking.
Properties:
mode:
Returns the mode in which the file was opened.
name:
Returns the file name.
__init__(
    name,
    mode='r'
)


read(n=-1):
Returns the contents of a file as a string.
Starts reading from current position in file.
Args:
n: Read 'n' bytes if n != -1. If n = -1, reads to end of file.
Returns:
'n' bytes of the file (or whole file) in bytes mode or 'n' bytes of the string if in string (regular) mode






Prepares an object detection tensorflow graph for inference using model configuration and an optional trained checkpoint. Outputs inference graph, associated checkpoint files, a frozen inference graph and a SavedModel >>(https://tensorflow.github.io/serving/serving_basic.html).<<