orbit.utils.SummaryManager
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A utility class for managing summary writing.
Inherits From: SummaryManagerInterface
orbit.utils.SummaryManager(
summary_dir, summary_fn, global_step=None
)
Args | |
|---|---|
summary_dir
|
The directory in which to write summaries. If None, all
summary writing operations provided by this class are no-ops.
|
summary_fn
|
A callable defined accepting name, value, and step
parameters, making calls to tf.summary functions to write summaries.
|
global_step
|
A tf.Variable containing the global step value.
|
Methods
flush
flush()
Flushes the underlying summary writers.
summary_writer
summary_writer(
relative_path=''
)
Returns the underlying summary writer for a specific subdirectory.
| Args | |
|---|---|
relative_path
|
The current path in which to write summaries, relative to the summary directory. By default it is empty, which corresponds to the root directory. |
write_summaries
write_summaries(
summary_dict
)
Writes summaries for the given dictionary of values.
This recursively creates subdirectories for any nested dictionaries
provided in summary_dict, yielding a hierarchy of directories which will
then be reflected in the TensorBoard UI as different colored curves.
For example, users may evaluate on multiple datasets and return
summary_dict as a nested dictionary:
{
"dataset1": {
"loss": loss1,
"accuracy": accuracy1
},
"dataset2": {
"loss": loss2,
"accuracy": accuracy2
},
}
This will create two subdirectories, "dataset1" and "dataset2", inside the summary root directory. Each directory will contain event files including both "loss" and "accuracy" summaries.
| Args | |
|---|---|
summary_dict
|
A dictionary of values. If any value in summary_dict is
itself a dictionary, then the function will create a subdirectory with
name given by the corresponding key. This is performed recursively. Leaf
values are then summarized using the summary writer instance specific to
the parent relative path.
|