def before_run(self, run_context):
if not self._wrapper_initialized:
local_cli_wrapper.LocalCLIDebugWrapperSession.__init__(
self, run_context.session)
self._wrapper_initialized = True
# Increment run call counter.
self._run_call_count += 1
# Adapt run_context to an instance of OnRunStartRequest for invoking
# superclass on_run_start().
on_run_start_request = framework.OnRunStartRequest(
run_context.original_args.fetches,
run_context.original_args.feed_dict, None, None,
self._run_call_count)
on_run_start_response = self.on_run_start(on_run_start_request)
self._performed_action = on_run_start_response.action
run_args = session_run_hook.SessionRunArgs(
None, feed_dict=None, options=config_pb2.RunOptions())
if self._performed_action == framework.OnRunStartAction.DEBUG_RUN:
self._decorate_options_for_debug(run_args.options,
run_context.session.graph)
elif self._performed_action == framework.OnRunStartAction.INVOKE_STEPPER:
raise NotImplementedError(
"OnRunStartAction INVOKE_STEPPER has not been implemented.")
return run_args
def before_run(self, run_context):
if not self._wrapper_initialized:
local_cli_wrapper.LocalCLIDebugWrapperSession.__init__(
self,
run_context.session,
ui_type=self._ui_type,
dump_root=self._dump_root,
thread_name_filter=self._thread_name_filter)
# Actually register tensor filters registered prior to the construction
# of the underlying LocalCLIDebugWrapperSession object.
for filter_name in self._pending_tensor_filters:
local_cli_wrapper.LocalCLIDebugWrapperSession.add_tensor_filter(
self, filter_name,
self._pending_tensor_filters[filter_name])
self._wrapper_initialized = True
# Increment run call counter.
self._run_call_count += 1
# Adapt run_context to an instance of OnRunStartRequest for invoking
# superclass on_run_start().
on_run_start_request = framework.OnRunStartRequest(
run_context.original_args.fetches,
run_context.original_args.feed_dict, None, None,
self._run_call_count)
on_run_start_response = self.on_run_start(on_run_start_request)
self._performed_action = on_run_start_response.action
run_args = session_run_hook.SessionRunArgs(
None, feed_dict=None, options=config_pb2.RunOptions())
if self._performed_action == framework.OnRunStartAction.DEBUG_RUN:
self._decorate_options_for_debug(
run_args.options, run_context.session.graph,
framework.WatchOptions(
node_name_regex_whitelist=(
on_run_start_response.node_name_regex_whitelist),
op_type_regex_whitelist=(
on_run_start_response.op_type_regex_whitelist),
tensor_dtype_regex_whitelist=(
on_run_start_response.tensor_dtype_regex_whitelist),
tolerate_debug_op_creation_failures=(
on_run_start_response.
tolerate_debug_op_creation_failures)))
elif self._performed_action == framework.OnRunStartAction.INVOKE_STEPPER:
# The _finalized property must be set to False so that the NodeStepper
# can insert ops for retrieving TensorHandles.
# pylint: disable=protected-access
run_context.session.graph._finalized = False
# pylint: enable=protected-access
with stepper.NodeStepper(
run_context.session, run_context.original_args.fetches,
run_context.original_args.feed_dict) as node_stepper:
self.invoke_node_stepper(node_stepper,
restore_variable_values_on_exit=True)
return run_args
def before_run(self, run_context):
if not self._session_wrapper:
self._session_wrapper = local_cli_wrapper.LocalCLIDebugWrapperSession(
run_context.session,
ui_type=self._ui_type,
dump_root=self._dump_root,
thread_name_filter=self._thread_name_filter,
config_file_path=self._config_file_path)
# Actually register tensor filters registered prior to the construction
# of the underlying LocalCLIDebugWrapperSession object.
for filter_name in self._pending_tensor_filters:
self._session_wrapper.add_tensor_filter(
filter_name, self._pending_tensor_filters[filter_name])
# Increment run call counter.
self._session_wrapper.increment_run_call_count()
# Adapt run_context to an instance of OnRunStartRequest for invoking
# superclass on_run_start().
on_run_start_request = framework.OnRunStartRequest(
run_context.original_args.fetches,
run_context.original_args.feed_dict, None, None,
self._session_wrapper.run_call_count)
on_run_start_response = self._session_wrapper.on_run_start(
on_run_start_request)
self._performed_action = on_run_start_response.action
run_args = session_run_hook.SessionRunArgs(
None, feed_dict=None, options=config_pb2.RunOptions())
if self._performed_action == framework.OnRunStartAction.DEBUG_RUN:
# pylint: disable=protected-access
self._session_wrapper._decorate_run_options_for_debug(
run_args.options,
on_run_start_response.debug_urls,
debug_ops=on_run_start_response.debug_ops,
node_name_regex_allowlist=(
on_run_start_response.node_name_regex_allowlist),
op_type_regex_allowlist=(
on_run_start_response.op_type_regex_allowlist),
tensor_dtype_regex_allowlist=(
on_run_start_response.tensor_dtype_regex_allowlist),
tolerate_debug_op_creation_failures=(
on_run_start_response.tolerate_debug_op_creation_failures))
# pylint: enable=protected-access
elif self._performed_action == framework.OnRunStartAction.PROFILE_RUN:
# pylint: disable=protected-access
self._session_wrapper._decorate_run_options_for_profile(
run_args.options)
# pylint: enable=protected-access
return run_args
def before_run(self, run_context):
if not self._wrapper_initialized:
local_cli_wrapper.LocalCLIDebugWrapperSession.__init__(
self, run_context.session, ui_type=self._ui_type)
self._wrapper_initialized = True
# Increment run call counter.
self._run_call_count += 1
# Adapt run_context to an instance of OnRunStartRequest for invoking
# superclass on_run_start().
on_run_start_request = framework.OnRunStartRequest(
run_context.original_args.fetches,
run_context.original_args.feed_dict, None, None,
self._run_call_count)
on_run_start_response = self.on_run_start(on_run_start_request)
self._performed_action = on_run_start_response.action
run_args = session_run_hook.SessionRunArgs(
None, feed_dict=None, options=config_pb2.RunOptions())
if self._performed_action == framework.OnRunStartAction.DEBUG_RUN:
self._decorate_options_for_debug(run_args.options,
run_context.session.graph)
elif self._performed_action == framework.OnRunStartAction.INVOKE_STEPPER:
# The _finalized property must be set to False so that the NodeStepper
# can insert ops for retrieving TensorHandles.
# pylint: disable=protected-access
run_context.session.graph._finalized = False
# pylint: enable=protected-access
self.invoke_node_stepper(stepper.NodeStepper(
run_context.session, run_context.original_args.fetches,
run_context.original_args.feed_dict),
restore_variable_values_on_exit=True)
return run_args
