experiments/STT-tensorflow
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Expose clear_attr in the python graph API. Use it to clear hanging nodes with no input/output from being TPU compiled.

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PiperOrigin-RevId: 236171147
This commit is contained in:
A. Unique TensorFlower 2019-02-28 12:13:54 -08:00 committed by TensorFlower Gardener
parent e59d6b67ad
commit 4059344a81
7 changed files with 339 additions and 223 deletions
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9
tensorflow/c/python_api.cc
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@ -41,6 +41,15 @@ void SetAttr(TF_Graph* graph, TF_Operation* op, const char* attr_name,
RecordMutation(graph, *op, "setting attribute");
}
void ClearAttr(TF_Graph* graph, TF_Operation* op, const char* attr_name,
TF_Status* status) {
AttrValue attr_val;
mutex_lock l(graph->mu);
op->node.ClearAttr(attr_name);
RecordMutation(graph, *op, "clearing attribute");
}
void SetRequestedDevice(TF_Graph* graph, TF_Operation* op, const char* device) {
mutex_lock l(graph->mu);
op->node.set_requested_device(device);

5
tensorflow/c/python_api.h
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@ -32,6 +32,11 @@ void AddControlInput(TF_Graph* graph, TF_Operation* op, TF_Operation* input);
void SetAttr(TF_Graph* graph, TF_Operation* op, const char* attr_name,
TF_Buffer* attr_value_proto, TF_Status* status);
// Clears the attr in the node_def Protocol Buffer and sets a status upon
// completion.
void ClearAttr(TF_Graph* graph, TF_Operation* op, const char* attr_name,
TF_Status* status);
void SetRequestedDevice(TF_Graph* graph, TF_Operation* op, const char* device);
// Updates 'dst' to consume 'new_src'.

444
tensorflow/opensource_only.files
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tensorflow/third_party/eigen3/unsupported/Eigen/CXX11/src/FixedPoint/MatMatProductNEON.h
tensorflow/third_party/eigen3/unsupported/Eigen/CXX11/src/FixedPoint/FixedPointTypes.h
tensorflow/third_party/eigen3/unsupported/Eigen/CXX11/src/FixedPoint/MatVecProduct.h
tensorflow/third_party/eigen3/unsupported/Eigen/CXX11/FixedPoint
tensorflow/third_party/eigen3/unsupported/Eigen/CXX11/ThreadPool
tensorflow/third_party/eigen3/Eigen/QR
tensorflow/third_party/eigen3/Eigen/SVD
tensorflow/third_party/eigen3/Eigen/LU
tensorflow/third_party/eigen3/Eigen/Cholesky
tensorflow/third_party/eigen3/Eigen/Eigenvalues
tensorflow/third_party/eigen3/Eigen/Core
tensorflow/third_party/BUILD
tensorflow/third_party/termcolor.BUILD
tensorflow/third_party/gif.BUILD
tensorflow/third_party/tflite_mobilenet.BUILD
tensorflow/third_party/mkl/LICENSE
tensorflow/third_party/mkl/build_defs.bzl
tensorflow/third_party/mkl/mkl.BUILD
tensorflow/third_party/mkl/MKL_LICENSE
tensorflow/third_party/mkl/BUILD
tensorflow/third_party/nccl/build_defs.bzl.tpl
tensorflow/third_party/nccl/LICENSE
tensorflow/third_party/nccl/nccl_configure.bzl
tensorflow/third_party/nccl/archive.BUILD
tensorflow/third_party/nccl/BUILD
tensorflow/third_party/nccl/system.BUILD.tpl
tensorflow/third_party/snappy.BUILD
tensorflow/third_party/python_runtime/BUILD
tensorflow/third_party/googleapis.BUILD
tensorflow/third_party/boringssl/BUILD
tensorflow/third_party/protobuf/BUILD
tensorflow/third_party/backports_weakref.BUILD
tensorflow/third_party/tflite_smartreply.BUILD
tensorflow/third_party/swig.BUILD
tensorflow/compat_template.__init__.py
tensorflow/tools/lib_package/libtensorflow_test.sh
tensorflow/tools/lib_package/libtensorflow_java_test.sh
tensorflow/tools/lib_package/libtensorflow_test.c
tensorflow/tools/lib_package/concat_licenses.sh
tensorflow/tools/lib_package/LibTensorFlowTest.java
tensorflow/tools/lib_package/BUILD
tensorflow/tools/lib_package/README.md
tensorflow/tools/pip_package/check_load_py_test.py
tensorflow/tools/pip_package/simple_console.py
tensorflow/tools/pip_package/pip_smoke_test.py
tensorflow/tools/pip_package/BUILD
tensorflow/tools/pip_package/simple_console_for_windows.py
tensorflow/tools/pip_package/build_pip_package.sh
tensorflow/tools/pip_package/README
tensorflow/tools/pip_package/setup.py
tensorflow/tools/pip_package/MANIFEST.in
tensorflow/tools/ci_build/remote/BUILD
tensorflow/tools/def_file_filter/def_file_filter.py.tpl
tensorflow/tools/def_file_filter/BUILD.tpl
tensorflow/tools/def_file_filter/BUILD
tensorflow/tools/def_file_filter/def_file_filter_configure.bzl
tensorflow/api_template.__init__.py
tensorflow/contrib/tpu/profiler/pip_package/BUILD
tensorflow/contrib/tpu/profiler/pip_package/cloud_tpu_profiler/__init__.py
tensorflow/contrib/tpu/profiler/pip_package/cloud_tpu_profiler/main.py
tensorflow/contrib/tpu/profiler/pip_package/build_pip_package.sh
tensorflow/contrib/tpu/profiler/pip_package/README
tensorflow/contrib/tpu/profiler/pip_package/setup.py
tensorflow/contrib/mpi/BUILD
tensorflow/__init__.py
tensorflow/stream_executor/build_defs.bzl
tensorflow/api_template_v1.__init__.py
tensorflow/compat_template_v1.__init__.py
tensorflow/compat_template.__init__.py
tensorflow/api_template.__init__.py
tensorflow/__init__.py

6
tensorflow/python/framework/ops.py
View File

@ -2551,6 +2551,12 @@ class Operation(object):
shapes_list = attr_value_pb2.AttrValue.ListValue(shape=shapes)
self._set_attr(attr_name, attr_value_pb2.AttrValue(list=shapes_list))
def _clear_attr(self, attr_name):
"""Private method used to clear an attribute in the node_def."""
# pylint: disable=protected-access
c_api.ClearAttr(self._graph._c_graph, self._c_op, attr_name)
# pylint: enable=protected-access
def get_attr(self, name):
"""Returns the value of the attr of this op with the given `name`.

32
tensorflow/python/tpu/tpu.py
View File

@ -62,6 +62,10 @@ _UNSUPPORTED_OPS = set([
"TensorSummaryV2",
])
# Ops which can be safely pruned from XLA compile if they have no consumers.
# These ops should also have no inputs.
_UNCONNECTED_OPS_TO_PRUNE = set(["Placeholder", "VarHandleOp"])
_MAX_WARNING_LINES = 5
_TPU_REPLICATE_ATTR = "_tpu_replicate"
@ -1574,3 +1578,31 @@ def rewrite_for_inference(computation,
device_assignment=device_assignment,
name=name)
# pylint: enable=undefined-variable
def prune_unconnected_ops_from_xla(prune_graph):
"""Prunes unconnected ops as listed in _UNCONNECTED_OPS_TO_PRUNE.
Args:
prune_graph: A tensorflow graph from which we wish to prune unconnected ops
as listed in _UNCONNECTED_OPS_TO_PRUNE. In general, these ops should have
no inputs and no consumers. These can often be left behind due to graph
construction rewiring (for instance TF-Hub). While they never execute,
they will cause XLA compile to fail so we strip them from XLA compile by
removing the tpu_replicate attribute.
"""
# Scan over the top level graph and all function graphs.
for graph in [prune_graph] + list(prune_graph._functions.values()): # pylint: disable=protected-access
for op in graph.get_operations():
if op.type not in _UNCONNECTED_OPS_TO_PRUNE:
continue
outputs_consumed = False
for output in op.outputs:
if output.consumers():
outputs_consumed = True
break
if not outputs_consumed:
logging.info(
"Pruning OP %s of type %s from XLA Compile due to "
"it being disconnected.", op.name, op.type)
op._clear_attr(_TPU_REPLICATE_ATTR) # pylint: disable=protected-access

1
tensorflow/python/tpu/tpu_estimator.py
View File

@ -2477,6 +2477,7 @@ class TPUEstimator(estimator_lib.Estimator):
if self._experimental_exported_model_uses_all_cores:
tensors_on_cpu = tpu.rewrite(
tpu_computation, device_assignment=device_assignment)
tpu.prune_unconnected_ops_from_xla(ops.get_default_graph())
else:
tensors_on_cpu = tpu.rewrite_for_inference(
tpu_computation, device_assignment=device_assignment)

63
tensorflow/python/tpu/tpu_test.py
View File

@ -19,12 +19,17 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import importer
from tensorflow.python.framework import ops
from tensorflow.python.layers import convolutional
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import control_flow_util
from tensorflow.python.ops import init_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import variable_scope
from tensorflow.python.platform import test
from tensorflow.python.tpu import tpu
from tensorflow.python.tpu import tpu_feed
@ -76,5 +81,63 @@ class TPULayerRewriteTest(test.TestCase):
tpu.rewrite(loop)
class TPUGraphPruneTest(test.TestCase):
def test_prune_unconnected_ops(self):
with ops.Graph().as_default():
a = array_ops.placeholder(dtype=dtypes.float32, name="a")
b = array_ops.placeholder(dtype=dtypes.float32, name="b")
constant_op.constant(1.0, name="constant")
x = variable_scope.get_variable(
name="x",
dtype=dtypes.float32,
shape=[],
use_resource=True,
initializer=init_ops.constant_initializer(2.0))
y = variable_scope.get_variable(
name="y",
dtype=dtypes.float32,
shape=[],
use_resource=True,
initializer=init_ops.constant_initializer(3.0))
math_ops.add(a, b)
math_ops.add(x, y)
graph_def = ops.get_default_graph().as_graph_def()
for node in graph_def.node:
# Attach a TPU_REPLICATE_ATTR to each node.
node.attr[tpu._TPU_REPLICATE_ATTR].s = b"0"
# Rewire placeholder "a" and variable "y" leaving them unconnected.
for (input_index, node_input) in enumerate(node.input):
if node_input == "b":
node.input[input_index] = "constant"
if node_input == "y":
node.input[input_index] = "x"
with ops.Graph().as_default() as graph:
# Reimport the graph and prune unconnected ops.
importer.import_graph_def(graph_def)
tpu.prune_unconnected_ops_from_xla(ops.get_default_graph())
# Verify that ops "a" and "x" still have TPU_REPLICATE_ATTR.
a = graph.get_operation_by_name("import/a").get_attr(
tpu._TPU_REPLICATE_ATTR)
self.assertEqual(b"0", a)
x = graph.get_operation_by_name("import/x").get_attr(
tpu._TPU_REPLICATE_ATTR)
self.assertEqual(b"0", x)
# Verify that ops "b" and "y" have TPU_REPLICATE_ATTR removed.
with self.assertRaisesRegexp(
ValueError,
"Operation \'import/b\' has no attr named \'_tpu_replicate\'"):
graph.get_operation_by_name("import/b").get_attr(
tpu._TPU_REPLICATE_ATTR)
with self.assertRaisesRegexp(
ValueError,
"Operation \'import/y\' has no attr named \'_tpu_replicate\'"):
graph.get_operation_by_name("import/y").get_attr(
tpu._TPU_REPLICATE_ATTR)
if __name__ == "__main__":
test.main()