def testConstructWrapperWithExistingEmptyDumpRoot(self):
os.mkdir(self._tmp_dir)
self.assertTrue(os.path.isdir(self._tmp_dir))
local_cli_wrapper.LocalCLIDebugWrapperSession(session.Session(),
dump_root=self._tmp_dir,
log_usage=False)
def testConstructWrapperWithExistingFileDumpRoot(self):
file_path = os.path.join(self._tmp_dir, "foo")
open(file_path, "a").close() # Create the file
self.assertTrue(os.path.isfile(file_path))
with self.assertRaisesRegex(ValueError, "dump_root path points to a file"):
local_cli_wrapper.LocalCLIDebugWrapperSession(
session.Session(), dump_root=file_path, log_usage=False)
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)
# 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_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))
# 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
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
return run_args
def testConstructWrapperWithExistingNonEmptyDumpRoot(self):
dir_path = os.path.join(self._tmp_dir, "foo")
os.mkdir(dir_path)
self.assertTrue(os.path.isdir(dir_path))
with self.assertRaisesRegex(
ValueError, "dump_root path points to a non-empty directory"):
local_cli_wrapper.LocalCLIDebugWrapperSession(
session.Session(), dump_root=self._tmp_dir, log_usage=False)
def run_saved_model_with_feed_dict(saved_model_dir,
tag_set,
signature_def_key,
input_tensor_key_feed_dict,
outdir,
overwrite_flag,
tf_debug=False):
"""Runs SavedModel and fetch all outputs.
Runs the input dictionary through the MetaGraphDef within a SavedModel
specified by the given tag_set and SignatureDef. Also save the outputs to file
if outdir is not None.
Args:
saved_model_dir: Directory containing the SavedModel to execute.
tag_set: Group of tag(s) of the MetaGraphDef with the SignatureDef map, in
string format, separated by ','. For tag-set contains multiple tags, all
tags must be passed in.
signature_def_key: A SignatureDef key string.
input_tensor_key_feed_dict: A dictionary maps input keys to numpy ndarrays.
outdir: A directory to save the outputs to. If the directory doesn't exist,
it will be created.
overwrite_flag: A boolean flag to allow overwrite output file if file with
the same name exists.
tf_debug: A boolean flag to use TensorFlow Debugger (TFDBG) to observe the
intermediate Tensor values and runtime GraphDefs while running the
SavedModel.
Raises:
ValueError: When any of the input tensor keys is not valid.
RuntimeError: An error when output file already exists and overwrite is not
enabled.
"""
# Get a list of output tensor names.
meta_graph_def = saved_model_utils.get_meta_graph_def(
saved_model_dir, tag_set)
# Re-create feed_dict based on input tensor name instead of key as session.run
# uses tensor name.
inputs_tensor_info = _get_inputs_tensor_info_from_meta_graph_def(
meta_graph_def, signature_def_key)
# Check if input tensor keys are valid.
for input_key_name in input_tensor_key_feed_dict.keys():
if input_key_name not in inputs_tensor_info.keys():
raise ValueError(
'"%s" is not a valid input key. Please choose from %s, or use '
'--show option.' %
(input_key_name,
'"' + '", "'.join(inputs_tensor_info.keys()) + '"'))
inputs_feed_dict = {
inputs_tensor_info[key].name: tensor
for key, tensor in input_tensor_key_feed_dict.items()
}
# Get outputs
outputs_tensor_info = _get_outputs_tensor_info_from_meta_graph_def(
meta_graph_def, signature_def_key)
# Sort to preserve order because we need to go from value to key later.
output_tensor_keys_sorted = sorted(outputs_tensor_info.keys())
output_tensor_names_sorted = [
outputs_tensor_info[tensor_key].name
for tensor_key in output_tensor_keys_sorted
]
with session.Session(graph=ops_lib.Graph()) as sess:
loader.load(sess, tag_set.split(','), saved_model_dir)
if tf_debug:
sess = local_cli_wrapper.LocalCLIDebugWrapperSession(sess)
outputs = sess.run(output_tensor_names_sorted,
feed_dict=inputs_feed_dict)
for i, output in enumerate(outputs):
output_tensor_key = output_tensor_keys_sorted[i]
print('Result for output key %s:\n%s' %
(output_tensor_key, output))
# Only save if outdir is specified.
if outdir:
# Create directory if outdir does not exist
if not os.path.isdir(outdir):
os.makedirs(outdir)
output_full_path = os.path.join(outdir,
output_tensor_key + '.npy')
# If overwrite not enabled and file already exist, error out
if not overwrite_flag and os.path.exists(output_full_path):
raise RuntimeError(
'Output file %s already exists. Add \"--overwrite\" to overwrite'
' the existing output files.' % output_full_path)
np.save(output_full_path, output)
print('Output %s is saved to %s' %
(output_tensor_key, output_full_path))
def testConstructWrapper(self):
local_cli_wrapper.LocalCLIDebugWrapperSession(session.Session(),
log_usage=False)
def __init__(self):
sess = session.Session(graph=ops_lib.Graph())
loader.load(sess, tag_set.split(','), saved_model_dir)
if tf_debug:
sess = local_cli_wrapper.LocalCLIDebugWrapperSession(sess)
self._sess = sess