tf.contrib.learn.evaluate(
graph,
output_dir,
checkpoint_path,
eval_dict,
update_op=None,
global_step_tensor=None,
supervisor_master='',
log_every_steps=10,
feed_fn=None,
max_steps=None
)
Defined in tensorflow/contrib/learn/python/learn/graph_actions.py
.
Evaluate a model loaded from a checkpoint. (deprecated)
Given graph
, a directory to write summaries to (output_dir
), a checkpoint
to restore variables from, and a dict
of Tensor
s to evaluate, run an eval
loop for max_steps
steps, or until an exception (generally, an
end-of-input signal from a reader operation) is raised from running
eval_dict
.
In each step of evaluation, all tensors in the eval_dict
are evaluated, and
every log_every_steps
steps, they are logged. At the very end of evaluation,
a summary is evaluated (finding the summary ops using Supervisor
's logic)
and written to output_dir
.
Args:
graph
: AGraph
to train. It is expected that this graph is not in use elsewhere.output_dir
: A string containing the directory to write a summary to.checkpoint_path
: A string containing the path to a checkpoint to restore. Can beNone
if the graph doesn't require loading any variables.eval_dict
: Adict
mapping string names to tensors to evaluate. It is evaluated in every logging step. The result of the final evaluation is returned. Ifupdate_op
is None, then it's evaluated in every step. Ifmax_steps
isNone
, this should depend on a reader that will raise an end-of-input exception when the inputs are exhausted.update_op
: ATensor
which is run in every step.global_step_tensor
: AVariable
containing the global step. IfNone
, one is extracted from the graph using the same logic as inSupervisor
. Used to place eval summaries on training curves.supervisor_master
: The master string to use when preparing the session.log_every_steps
: Integer. Output logs everylog_every_steps
evaluation steps. The logs contain theeval_dict
and timing information.feed_fn
: A function that is called every iteration to produce afeed_dict
passed tosession.run
calls. Optional.max_steps
: Integer. Evaluateeval_dict
this many times.
Returns:
A tuple (eval_results, global_step)
:
* eval_results
: A dict
mapping string
to numeric values (int
, float
)
that are the result of running eval_dict in the last step. None
if no
eval steps were run.
* global_step
: The global step this evaluation corresponds to.
Raises:
ValueError
: ifoutput_dir
is empty.