Check whether the input is a valid Tensorflow expression, i.e., Tensorflow Tensor, Variable, or Operation.

Evaluate pairwise distances between two batches of feature vectors.

Print a summary table of the network structure.

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

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

r"""Fused `upsample_2d()` followed by `tf.nn.conv2d()`. Padding is performed only once at the beginning, not between the operations. The fuse

Write text to stdout (and a file) and optionally flush.

Sum gradients across devices using NCCL ops (fast path).

Create a new run dir with increasing ID number at the start.

Slow reference implementation of `fused_bias_act()` using standard TensorFlow ops.

Reads all directory names in a given directory (non-recursive) and returns the next (increasing) run id. Assumes IDs are numbers at the start of the d

Copy all necessary files into the run dir. Assumes that the dir exists, is local, and is writable.

Apply dynamic loss scaling for the given expression.

Compute pairwise distances between two batches of feature vectors.

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

Create tf.Session based on config dict.

Create the necessary ops to include autosummaries in TensorBoard report. Note: This should be done only once per graph.

r"""Fused bias and activation function. Adds bias `b` to activation tensor `x`, evaluates activation function `act`, and scales the result by

Finds the python object with the given name.

Convert a normal path back to its template representation.

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

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

Get the value of a given variable as NumPy array. Note: This method is very inefficient -- prefer to use tflib.run(list_of_vars) whenever poss

Determine whether the given object is a top-level function, i.e., defined at module scope using 'def'.

Determine whether the given object is a valid URL string.

Calculates k-NN precision and recall for two sets of feature vectors.

Returns a list of (layer_name, output_expr, trainable_vars) tuples corresponding to individual layers of the network. Mainly intended to be us

Wrap the actual run function call for handling logging, exceptions, typing, etc.

Set the values of given tf.Variables. Equivalent to the following, but more efficient and does not bloat the tf graph: tflib.run([tf.assign(v

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

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

Undo the effect of dynamic loss scaling for the given expression.

r"""Pad, upsample, FIR filter, and downsample a batch of 2D images. Accepts a batch of 2D images of the shape `[majorDim, inH, inW, minorDim]`