Hello! Our static bug checker has found a performance issue in mobile_deployment/tensorflow/slim/models/research/object_detection/model_lib_v2.py: eager_eval_loop is repeatedly called in a for loop, but there is a tf.function decorated function compute_eval_dict defined and called in eager_eval_loop.
In that case, when eager_eval_loop is called in a loop, the function compute_eval_dict will create a new graph every time, and that can trigger tf.function retracing warning.
Here is the tensorflow document to support it.
Briefly, for better efficiency, it's better to use:
@tf.function
def inner():
pass
def outer():
inner() than:
def outer():
@tf.function
def inner():
pass
inner()Looking forward to your reply.
Hello! Our static bug checker has found a performance issue in mobile_deployment/tensorflow/slim/models/research/object_detection/model_lib_v2.py:
eager_eval_loopis repeatedly called in a for loop, but there is a tf.function decorated functioncompute_eval_dictdefined and called ineager_eval_loop.In that case, when
eager_eval_loopis called in a loop, the functioncompute_eval_dictwill create a new graph every time, and that can trigger tf.function retracing warning.Here is the tensorflow document to support it.
Briefly, for better efficiency, it's better to use:
than:
Looking forward to your reply.