Pickle import.

Forcefully enter the specified variable scope, ignoring any surrounding scopes.

Perform stochastic weight averaging on the compatible values of all trainable variables from the given network, including sub-networks

Construct training op to update the registered variables based on their gradients.

Ask the user the question until the user inputs a valid answer.

Create a new autosummary. Args: name: Name to use in TensorBoard value: TensorFlow expression or python value to track

Finds the python object with the given name and calls it as a function.

Convert a minibatch of images from uint8 to float32 with configurable dynamic range. Can be used as an input transformation for Network.run().

Convert a minibatch of images from float32 to uint8 with configurable dynamic range. Can be used as an output transformation for Network.run().

Convert a normal path to template and the convert it back to a normal path with given path type.

Copy the compatible values of all trainable variables from the given network, including sub-networks

Takes in a list of tuples of (src, dst) paths and copies files. Will create all necessary directories.

Copy the values of all variables from the given network, excluding sub-networks.

Copy the values of all trainable variables from the given network, including sub-networks.

Create tf.Variable with large initial value without bloating the tf graph.

Exponent in base 2.

Shortcut function for flattening a tensor.

Convert the seconds to human readable string with days, hours, minutes and seconds.

Given a type name string (or an object having a __name__ attribute), return matching Numpy and ctypes types that have the same size in bytes.

How much time passed between the previous two calls to update.

Get the directory path of the module containing the given object name.

How much time has passed since the last call to update.

How much time has passed since the creation of the context.

Return the fully-qualified name of a top-level function.

Get the local name of a given variable, without any surrounding name scopes.

Function decorator for declaring custom import handlers.

Initialize TensorFlow session using good default settings.

Initialize all tf.Variables that have not already been initialized. Equivalent to the following, but more efficient and does not bloat the tf gra

Linear interpolation.

Linear interpolation with clip.

List all files recursively in a given directory while ignoring given file and directory names. Returns list of tuples containing both absolute and

Logarithm in base 2.

Download the given URL and return a binary-mode file object to access the data.

Print a summary table of the network structure.

Register the gradients of the given loss function with respect to the given variables. Intended to be called once per GPU.

Re-initialize all trainable variables of this network, including sub-networks.

Re-initialize all variables of this network, including sub-networks.

Call FileWriter.add_summary() with all summaries in the default graph, automatically finalizing and merging them on the first call.

Set the global username override value.

Set the value of a given variable based on the given NumPy array. Note: This method is very inefficient -- prefer to use tflib.set_vars() when

Construct a TensorFlow op that updates the variables of this network to be slightly closer to those of the given network.

Construct summary ops to include histograms of all trainable parameters in TensorBoard.

Convert a Tensorflow shape to a list of ints.

Tell whether a stopping condition has been triggered one way or another.

Create a run dir, gather files related to the run, copy files to the run dir, and launch the run in appropriate place.

Calculate the product of the tuple elements.