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# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# =============================================================================
"""Exposes the Python wrapper conversion to trt_graph."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
# pylint: disable=unused-import,line-too-long
import six as _six
from tensorflow.contrib.tensorrt.wrap_conversion import trt_convert
from tensorflow.core.framework import graph_pb2
from tensorflow.python.framework import errors
from tensorflow.python.framework import errors_impl as _impl
from tensorflow.python.framework import ops
# TODO(skama): get outputs from session when implemented as c++
# optimization pass
def create_inference_graph(input_graph_def,
outputs,
max_batch_size=1,
max_workspace_size_bytes=2 << 20):
"""Python wrapper for the TRT transormation.
Args:
input_graph_def: GraphDef object containing a model to be transformed.
outputs: List of tensors or node names for the model outputs.
max_batch_size: max size for the input batch
max_workspace_size_bytes: parameter to control memory allocation (in Bytes)
Returns:
New GraphDef with TRTEngineOps placed in graph replacing subgraphs.
Raises:
RuntimeError: if the returned status message is malformed.
"""
def py2bytes(inp):
return inp
def py3bytes(inp):
return inp.encode("utf-8", errors="surrogateescape")
def py2string(inp):
return inp
def py3string(inp):
return inp.decode("utf-8")
if _six.PY2:
to_bytes = py2bytes
to_string = py2string
else:
to_bytes = py3bytes
to_string = py3string
out_names = []
for i in outputs:
if isinstance(i, ops.Tensor):
out_names.append(to_bytes(i.name))
else:
out_names.append(to_bytes(i))
input_graph_def_str = input_graph_def.SerializeToString()
# TODO(sami): Fix this when we can return status from C++ library
# There is a problem with the TF internal library setup that doesn't
# allow us to return a status object from C++. Thus we return a
# pair or strings where first one is encoded status and the second
# one is the transformed graphs protobuf string.
out = trt_convert(input_graph_def_str, out_names, max_batch_size,
max_workspace_size_bytes)
status = to_string(out[0])
output_graph_def_string = out[1]
del input_graph_def_str # Save some memory
if len(status) < 2:
raise _impl.UnknownError(None, None, status)
if status[:2] != "OK":
msg = status.split(";")
if len(msg) == 1:
raise RuntimeError("Status message is malformed {}".format(status))
# pylint: disable=protected-access
raise _impl._make_specific_exception(None, None, ";".join(msg[1:]),
int(msg[0]))
# pylint: enable=protected-access
output_graph_def = graph_pb2.GraphDef()
output_graph_def.ParseFromString(output_graph_def_string)
del output_graph_def_string # Save some memory
return output_graph_def
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