def add_step(self, step, run_meta):
"""Add statistics of a step.
Args:
step: A step uint64 used to identify the RunMetadata. Must be different
across different AddStep() calls.
run_meta: RunMetadata proto that contains statistics of a session run.
"""
# pylint: disable=protected-access
op_log = tfprof_logger._merge_default_with_oplog(
self._graph, run_meta=run_meta, add_trace=False,
add_trainable_var=False)
# pylint: enable=protected-access
print_mdl.AddStep(
step, run_meta.SerializeToString(), op_log.SerializeToString())
def add_step(self, step, run_meta):
"""Add statistics of a step.
Args:
step: int, An id used to group one or more different `run_meta` together.
When profiling with the profile_xxx APIs, user can use the `step`
id in the `options` to profile these `run_meta` together.
run_meta: RunMetadata proto that contains statistics of a session run.
"""
# pylint: disable=protected-access
op_log = tfprof_logger.merge_default_with_oplog(self._graph,
run_meta=run_meta)
# pylint: enable=protected-access
# TODO(xpan): P1: Better to find the current graph.
self._coverage = print_mdl.AddStep(step, _graph_string(self._graph),
run_meta.SerializeToString(),
op_log.SerializeToString())
def add_step(self, step, run_meta):
"""Add statistics of a step.
Args:
step: int, A step used to identify the RunMetadata. Must be different
across different AddStep() calls.
run_meta: RunMetadata proto that contains statistics of a session run.
"""
# pylint: disable=protected-access
op_log = tfprof_logger._merge_default_with_oplog(self._graph,
run_meta=run_meta)
# pylint: enable=protected-access
# TODO(xpan): P1: Better to find the current graph.
self._coverage = print_mdl.AddStep(
step,
self._graph.as_graph_def(add_shapes=True).SerializeToString(),
run_meta.SerializeToString(), op_log.SerializeToString())