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Fix tfprof to measure the actual kernel execution time.

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Change: 151166174
This commit is contained in:
A. Unique TensorFlower 2017-03-24 12:46:58 -08:00 committed by TensorFlower Gardener
parent 45dbb0a02d
commit 404db0358a
16 changed files with 1498 additions and 536 deletions
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11
tensorflow/tools/tfprof/README.md
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@ -52,6 +52,7 @@ sys.stdout.write('total_params: %d\n' % param_stats.total_parameters)
# also requires complete shape information. It is common that shape is unknown
# statically. To complete the shape, provide run-time shape information with
# tf.RunMetadata to the API (See next example on how to provide RunMetadata).
#
tf.contrib.tfprof.model_analyzer.print_model_analysis(
tf.get_default_graph(),
tfprof_options=tf.contrib.tfprof.model_analyzer.FLOAT_OPS_OPTIONS)
@ -64,8 +65,16 @@ compute the memory and timing statistics.
```python
# Generate the meta information for the model that contains the memory usage
# and timing information.
#
# Note: When run on GPU, a kernel is first scheduled (enqueued) and then
# executed asynchronously. tfprof only tracks the execution time.
# Which is from proto CostGraphDef::Node::compute_cost.
# In addition, a substantial of time might be spent between Python and
# TensorFlow runtime, which is also not tracked by tfprof.
#
config = tf.ConfigProto(graph_options=tf.GraphOptions(build_cost_model=1))
run_metadata = tf.RunMetadata()
with tf.Session() as sess:
with tf.Session(config=config) as sess:
_ = sess.run(train_op,
options=tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE),
run_metadata=run_metadata)

12
tensorflow/tools/tfprof/internal/BUILD
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@ -102,7 +102,9 @@ tf_cc_test(
name = "tfprof_show_test",
srcs = ["tfprof_show_test.cc"],
data = [
"testdata/ckpt",
"testdata/ckpt.data-00000-of-00001",
"testdata/ckpt.index",
"testdata/ckpt.meta",
"testdata/graph.pbtxt",
"testdata/run_meta",
"testdata/tfprof_log",
@ -176,7 +178,9 @@ tf_cc_test(
name = "tfprof_stats_test",
srcs = ["tfprof_stats_test.cc"],
data = [
"testdata/ckpt",
"testdata/ckpt.data-00000-of-00001",
"testdata/ckpt.index",
"testdata/ckpt.meta",
"testdata/graph.pbtxt",
"testdata/run_meta",
"testdata/tfprof_log",
@ -212,7 +216,9 @@ tf_cc_test(
name = "tfprof_tensor_test",
srcs = ["tfprof_tensor_test.cc"],
data = [
"testdata/ckpt",
"testdata/ckpt.data-00000-of-00001",
"testdata/ckpt.index",
"testdata/ckpt.meta",
"testdata/graph.pbtxt",
],
deps = [

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24
tensorflow/tools/tfprof/internal/testdata/tfprof_log vendored
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@ -1,9 +1,17 @@
Conv2D_1€$

DW2_trainable_variables

DW_trainable_variables
Conv2DÈ-

conv2d_2/BiasAdd 

conv2d/BiasAddè
%
conv2d_1/bias_trainable_variables

conv2d_2/convolutionÀp

conv2d/convolutionð—
#
conv2d/bias_trainable_variables
'
conv2d_1/kernel_trainable_variables
%
conv2d/kernel_trainable_variables

6
tensorflow/tools/tfprof/internal/tfprof_node.cc
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@ -29,7 +29,7 @@ void TFNode::AddStepStat(const string& device, const NodeExecStats* step_stat) {
op_start_micros_ = step_stat_->all_start_micros();
if (step_stat_->op_end_rel_micros() && step_stat_->op_start_rel_micros()) {
op_exec_micros_ =
op_schedule_micros_ =
step_stat_->op_end_rel_micros() - step_stat_->op_start_rel_micros();
}
all_spent_micros_ = step_stat_->all_end_rel_micros();
@ -43,5 +43,9 @@ void TFNode::AddStepStat(const string& device, const NodeExecStats* step_stat) {
}
}
}
void TFNode::AddNodeStat(const CostGraphDef::Node* cost_node) {
kernel_compute_micros_ = cost_node->compute_cost();
}
} // namespace tfprof
} // namespace tensorflow

16
tensorflow/tools/tfprof/internal/tfprof_node.h
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@ -23,6 +23,7 @@ limitations under the License.
#include "tensorflow/core/framework/allocation_description.pb.h"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/cost_graph.pb.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/step_stats.pb.h"
#include "tensorflow/core/framework/tensor_description.pb.h"
@ -39,7 +40,8 @@ class TFNode {
: node_(node),
step_stat_(nullptr),
op_start_micros_(0),
op_exec_micros_(0),
op_schedule_micros_(0),
kernel_compute_micros_(0),
all_spent_micros_(0),
requested_bytes_(0),
float_ops_(0) {
@ -76,12 +78,19 @@ class TFNode {
void AddStepStat(const string& device, const NodeExecStats* step_stat);
// Add CostGraphDef::Node.
void AddNodeStat(const CostGraphDef::Node* cost_node);
void AddFloatOps(int64 float_ops) { float_ops_ = float_ops; }
const NodeDef* node_def() { return node_; }
const std::map<string, TFNode*>& inputs() { return inputs_; }
int64 op_start_micros() { return op_start_micros_; }
int64 op_exec_micros() { return op_exec_micros_; }
// This is time spent in Op::Compute(), which is GPU kernel schedule time.
// Currently not used.
int64 op_schedule_micros() { return op_schedule_micros_; }
// This is time spent in kernel execution.
int64 kernel_compute_micros() { return kernel_compute_micros_; }
int64 all_spent_micros() { return all_spent_micros_; }
int64 requested_byptes() { return requested_bytes_; }
int64 float_ops() { return float_ops_; }
@ -101,7 +110,8 @@ class TFNode {
std::set<string> op_types_;
string device_;
int64 op_start_micros_;
int64 op_exec_micros_;
int64 op_schedule_micros_;
int64 kernel_compute_micros_;
int64 all_spent_micros_;
int64 requested_bytes_;
int64 float_ops_;

2
tensorflow/tools/tfprof/internal/tfprof_show.cc
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@ -30,7 +30,7 @@ ShowNode::ShowNode(TFNode* node) : node(node), account(true) {
if (!node->device().empty()) {
mutable_proto()->set_device(node->device());
}
mutable_proto()->set_exec_micros(node->op_exec_micros());
mutable_proto()->set_exec_micros(node->kernel_compute_micros());
mutable_proto()->set_requested_bytes(node->requested_byptes());
mutable_proto()->set_float_ops(node->float_ops());

11
tensorflow/tools/tfprof/internal/tfprof_show_test.cc
View File

@ -72,7 +72,7 @@ class TFProfShowTest : public ::testing::Test {
TEST_F(TFProfShowTest, DumpScopeMode) {
string dump_file = io::JoinPath(testing::TmpDir(), "dump");
Options opts(5, 0, 0, 0, 0, {".*"}, "name",
{"Variable"}, // accout_type_regexes
{"VariableV2"}, // accout_type_regexes
{".*"}, {""}, {".*"}, {""}, false,
{"params", "bytes", "micros", "float_ops", "num_hidden_ops"},
false, dump_file);
@ -81,9 +81,12 @@ TEST_F(TFProfShowTest, DumpScopeMode) {
string dump_str;
TF_CHECK_OK(ReadFileToString(Env::Default(), dump_file, &dump_str));
EXPECT_EQ(
"_TFProfRoot (--/450 params, --/0 flops, --/1.80KB, --/0us)\n DW "
"(3x3x3x6, 162/162 params, 0/0 flops, 648B/648B, 0us/0us)\n DW2 "
"(2x2x6x12, 288/288 params, 0/0 flops, 1.15KB/1.15KB, 0us/0us)\n",
"_TFProfRoot (--/370 params, --/0 flops, --/1.48KB, --/5us)\n "
"conv2d/bias (5, 5/5 params, 0/0 flops, 20B/20B, 1us/1us)\n "
"conv2d/kernel (3x3x3x5, 135/135 params, 0/0 flops, 540B/540B, "
"1us/1us)\n conv2d_1/bias (5, 5/5 params, 0/0 flops, 20B/20B, "
"1us/1us)\n conv2d_1/kernel (3x3x5x5, 225/225 params, 0/0 flops, "
"900B/900B, 2us/2us)\n",
dump_str);
}

14
tensorflow/tools/tfprof/internal/tfprof_stats.cc
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@ -125,6 +125,20 @@ void TFStats::ParseRunMeta() {
node->second.AddStepStat(dev_stat.device(), &node_stat);
}
}
if (!run_meta_->has_cost_graph()) {
fprintf(stderr,
"Missing CostGraphDef in RunMetadata.\nMaybe you forget to"
"set tf.ConfigProto(graph_options=tf.GraphOptions("
"build_cost_model=1)) to Session()\n");
}
for (const auto& node_pb : run_meta_->cost_graph().node()) {
auto node = nodes_map_.find(node_pb.name());
if (node == nodes_map_.end()) {
continue;
}
node->second.AddNodeStat(&node_pb);
}
}
} // namespace tfprof
} // namespace tensorflow

84
tensorflow/tools/tfprof/internal/tfprof_stats_test.cc
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@ -81,16 +81,24 @@ TEST_F(TFProfStatsTest, CustomOpType) {
TFProfNode expected;
CHECK(protobuf::TextFormat::ParseFromString(
"name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: "
"0\ntotal_exec_micros: 0\ntotal_requested_bytes: 1800\ntotal_parameters: "
"450\nchildren {\n name: \"DW\"\n exec_micros: 0\n requested_bytes: "
"648\n parameters: 162\n total_exec_micros: 0\n "
"total_requested_bytes: 648\n total_parameters: 162\n device: "
"0\ntotal_exec_micros: 5\ntotal_requested_bytes: 1480\ntotal_parameters: "
"370\nchildren {\n name: \"conv2d/bias\"\n exec_micros: 1\n "
"requested_bytes: 20\n parameters: 5\n total_exec_micros: 1\n "
"total_requested_bytes: 20\n total_parameters: 5\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 0\n "
"total_float_ops: 0\n}\nchildren {\n name: \"DW2\"\n exec_micros: 0\n "
"requested_bytes: 1152\n parameters: 288\n total_exec_micros: 0\n "
"total_requested_bytes: 1152\n total_parameters: 288\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 0\n "
"total_float_ops: 0\n}\nfloat_ops: 0\ntotal_float_ops: 0\n",
"total_float_ops: 0\n}\nchildren {\n name: \"conv2d/kernel\"\n "
"exec_micros: 1\n requested_bytes: 540\n parameters: 135\n "
"total_exec_micros: 1\n total_requested_bytes: 540\n total_parameters: "
"135\n device: \"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: "
"0\n total_float_ops: 0\n}\nchildren {\n name: \"conv2d_1/bias\"\n "
"exec_micros: 1\n requested_bytes: 20\n parameters: 5\n "
"total_exec_micros: 1\n total_requested_bytes: 20\n total_parameters: "
"5\n device: \"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: "
"0\n total_float_ops: 0\n}\nchildren {\n name: \"conv2d_1/kernel\"\n "
"exec_micros: 2\n requested_bytes: 900\n parameters: 225\n "
"total_exec_micros: 2\n total_requested_bytes: 900\n total_parameters: "
"225\n device: \"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: "
"0\n total_float_ops: 0\n}\nfloat_ops: 0\ntotal_float_ops: 0\n",
&expected));
EXPECT_EQ(expected.DebugString(), root.DebugString());
}
@ -105,16 +113,24 @@ TEST_F(TFProfStatsTest, CheckPointOpType) {
TFProfNode expected;
CHECK(protobuf::TextFormat::ParseFromString(
"name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: "
"0\ntotal_exec_micros: 0\ntotal_requested_bytes: 1800\ntotal_parameters: "
"450\nchildren {\n name: \"DW\"\n exec_micros: 0\n requested_bytes: "
"648\n parameters: 162\n total_exec_micros: 0\n "
"total_requested_bytes: 648\n total_parameters: 162\n device: "
"0\ntotal_exec_micros: 5\ntotal_requested_bytes: 1480\ntotal_parameters: "
"370\nchildren {\n name: \"conv2d/bias\"\n exec_micros: 1\n "
"requested_bytes: 20\n parameters: 5\n total_exec_micros: 1\n "
"total_requested_bytes: 20\n total_parameters: 5\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 0\n "
"total_float_ops: 0\n}\nchildren {\n name: \"DW2\"\n exec_micros: 0\n "
"requested_bytes: 1152\n parameters: 288\n total_exec_micros: 0\n "
"total_requested_bytes: 1152\n total_parameters: 288\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 0\n "
"total_float_ops: 0\n}\nfloat_ops: 0\ntotal_float_ops: 0\n",
"total_float_ops: 0\n}\nchildren {\n name: \"conv2d/kernel\"\n "
"exec_micros: 1\n requested_bytes: 540\n parameters: 135\n "
"total_exec_micros: 1\n total_requested_bytes: 540\n total_parameters: "
"135\n device: \"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: "
"0\n total_float_ops: 0\n}\nchildren {\n name: \"conv2d_1/bias\"\n "
"exec_micros: 1\n requested_bytes: 20\n parameters: 5\n "
"total_exec_micros: 1\n total_requested_bytes: 20\n total_parameters: "
"5\n device: \"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: "
"0\n total_float_ops: 0\n}\nchildren {\n name: \"conv2d_1/kernel\"\n "
"exec_micros: 2\n requested_bytes: 900\n parameters: 225\n "
"total_exec_micros: 2\n total_requested_bytes: 900\n total_parameters: "
"225\n device: \"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: "
"0\n total_float_ops: 0\n}\nfloat_ops: 0\ntotal_float_ops: 0\n",
&expected));
EXPECT_EQ(expected.DebugString(), root.DebugString());
}
@ -144,16 +160,24 @@ TEST_F(TFProfStatsTest, TestFloatOps) {
TFProfNode expected;
CHECK(protobuf::TextFormat::ParseFromString(
"name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: "
"0\ntotal_exec_micros: 11\ntotal_requested_bytes: "
"5280\ntotal_parameters: 450\nchildren {\n name: \"Conv2D\"\n "
"exec_micros: 0\n requested_bytes: 432\n total_exec_micros: 0\n "
"total_requested_bytes: 432\n total_parameters: 0\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 5832\n "
"total_float_ops: 5832\n}\nchildren {\n name: \"Conv2D_1\"\n "
"exec_micros: 10\n requested_bytes: 384\n total_exec_micros: 10\n "
"total_requested_bytes: 384\n total_parameters: 0\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 4608\n "
"total_float_ops: 4608\n}\nfloat_ops: 0\ntotal_float_ops: 10440\n",
"0\ntotal_exec_micros: 96\ntotal_requested_bytes: "
"8656\ntotal_parameters: 370\nchildren {\n name: \"conv2d/BiasAdd\"\n "
"exec_micros: 12\n requested_bytes: 1440\n total_exec_micros: 12\n "
"total_requested_bytes: 1440\n total_parameters: 0\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 360\n "
"total_float_ops: 360\n}\nchildren {\n name: \"conv2d/convolution\"\n "
"exec_micros: 60\n requested_bytes: 1440\n total_exec_micros: 60\n "
"total_requested_bytes: 1440\n total_parameters: 0\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 19440\n "
"total_float_ops: 19440\n}\nchildren {\n name: \"conv2d_2/BiasAdd\"\n "
"exec_micros: 2\n requested_bytes: 640\n total_exec_micros: 2\n "
"total_requested_bytes: 640\n total_parameters: 0\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 160\n "
"total_float_ops: 160\n}\nchildren {\n name: \"conv2d_2/convolution\"\n "
" exec_micros: 13\n requested_bytes: 640\n total_exec_micros: 13\n "
"total_requested_bytes: 640\n total_parameters: 0\n device: "
"\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 14400\n "
"total_float_ops: 14400\n}\nfloat_ops: 0\ntotal_float_ops: 34360\n",
&expected));
EXPECT_EQ(expected.DebugString(), root.DebugString());
}
@ -183,8 +207,8 @@ TEST_F(TFProfStatsTest, TestShowTensorValue) {
TFProfNode expected;
CHECK(protobuf::TextFormat::ParseFromString(
"name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: "
"0\ntotal_exec_micros: 11\ntotal_requested_bytes: "
"5280\ntotal_parameters: 450\nfloat_ops: 0\ntotal_float_ops: 10440\n",
"0\ntotal_exec_micros: 96\ntotal_requested_bytes: "
"8656\ntotal_parameters: 370\nfloat_ops: 0\ntotal_float_ops: 34360\n",
&expected));
EXPECT_EQ(expected.DebugString(), root.DebugString());
}

403
tensorflow/tools/tfprof/internal/tfprof_tensor_test.cc
View File

@ -55,7 +55,7 @@ class TFProfTensorTest : public ::testing::Test {
};
TEST_F(TFProfTensorTest, Basics) {
Options opts(3, 0, 0, 0, 0, {".*"}, "name", {"Variable"}, {".*"}, {""},
Options opts(3, 0, 0, 0, 0, {".*"}, "name", {"VariableV2"}, {".*"}, {""},
{".*"}, {""}, false, {"tensor_value"}, // show the tensor value.
false);
const TFProfNode& root = tf_stats_->PrintGraph("scope", opts);
@ -64,239 +64,176 @@ TEST_F(TFProfTensorTest, Basics) {
CHECK(protobuf::TextFormat::ParseFromString(
"name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: "
"0\ntotal_exec_micros: 0\ntotal_requested_bytes: 0\ntotal_parameters: "
"450\nchildren {\n name: \"DW\"\n exec_micros: 0\n requested_bytes: "
"0\n parameters: 162\n total_exec_micros: 0\n total_requested_bytes: "
"0\n total_parameters: 162\n float_ops: 0\n total_float_ops: 0\n "
"tensor_value {\n dtype: DT_FLOAT\n value_double: -0.00117808\n "
"value_double: -0.000709941\n value_double: -0.00174816\n "
"value_double: -0.000495372\n value_double: 0.000243039\n "
"value_double: -0.000126313\n value_double: -0.000663929\n "
"value_double: -0.000495198\n value_double: -0.000893934\n "
"value_double: -0.00179659\n value_double: 0.000408874\n "
"value_double: -0.00120166\n value_double: -0.00109484\n "
"value_double: -0.000200362\n value_double: 0.000726721\n "
"value_double: -0.000277568\n value_double: 0.00180584\n "
"value_double: 0.000997271\n value_double: -0.00185987\n "
"value_double: -0.00113401\n value_double: -0.000528852\n "
"value_double: -0.000197412\n value_double: 1.32871e-05\n "
"value_double: -0.000285896\n value_double: -0.000428898\n "
"value_double: -0.000424633\n value_double: 2.15488e-05\n "
"value_double: 0.00149753\n value_double: -0.000884576\n "
"value_double: -0.0013795\n value_double: -0.000650125\n "
"value_double: 0.00191612\n value_double: 4.71838e-05\n "
"value_double: 0.000400201\n value_double: 0.00239555\n "
"value_double: -0.00177706\n value_double: -0.000781899\n "
"value_double: -0.00145247\n value_double: 0.0020025\n "
"value_double: 0.000597419\n value_double: 0.00135456\n "
"value_double: 0.0015876\n value_double: -0.000993568\n "
"value_double: 0.0006509\n value_double: -0.000894533\n "
"value_double: -0.00129322\n value_double: 0.0003859\n "
"value_double: 0.000415186\n value_double: -0.000439212\n "
"value_double: 0.000442138\n value_double: 0.00212353\n "
"value_double: 0.000702953\n value_double: 0.000713424\n "
"value_double: -0.000304877\n value_double: -9.17046e-05\n "
"value_double: -0.000801103\n value_double: 0.000304854\n "
"value_double: -0.00070527\n value_double: -0.00106408\n "
"value_double: -0.000909906\n value_double: -4.49183e-05\n "
"value_double: 0.000104172\n value_double: -0.000438067\n "
"value_double: -0.000317689\n value_double: -0.000769914\n "
"value_double: -0.00157729\n value_double: 0.000220733\n "
"value_double: 0.00107268\n value_double: -0.000186449\n "
"value_double: -0.000807328\n value_double: 0.000456308\n "
"value_double: -0.000593729\n value_double: -0.000954873\n "
"value_double: -0.000268676\n value_double: 9.06328e-05\n "
"value_double: -0.000323473\n value_double: -0.000628768\n "
"value_double: 0.000664985\n value_double: 0.0020999\n "
"value_double: -0.000932228\n value_double: -0.00203203\n "
"value_double: 0.000565405\n value_double: 0.000167899\n "
"value_double: 0.00054897\n value_double: 0.000612407\n "
"value_double: -0.000619301\n value_double: 0.00169361\n "
"value_double: -0.000188057\n value_double: 0.000267652\n "
"value_double: -0.00127341\n value_double: -0.000218836\n "
"value_double: -0.000431722\n value_double: 5.41867e-05\n "
"value_double: 0.000296628\n value_double: 0.000819415\n "
"value_double: -0.000758993\n value_double: -0.000114477\n "
"value_double: 6.29219e-05\n value_double: 0.000726988\n "
"value_double: -0.00135974\n value_double: 2.28447e-05\n "
"value_double: 0.00120547\n value_double: -0.00136907\n "
"value_double: -0.00140188\n value_double: 0.000201145\n "
"value_double: -0.000774109\n value_double: 0.000798465\n "
"value_double: -0.00131861\n value_double: 3.08996e-05\n "
"value_double: -0.000637026\n value_double: 0.00228975\n "
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" value_double: -0.175214\n value_double: -0.211524\n "
"value_double: 0.167042\n value_double: -0.216357\n value_double: "
"-0.0218886\n value_double: -0.244211\n value_double: 0.175301\n "
" value_double: 0.0654932\n value_double: -0.0419763\n "
"value_double: -0.103275\n value_double: -0.0848433\n "
"value_double: -0.0845421\n value_double: -0.00269318\n "
"value_double: -0.145978\n value_double: -0.217061\n value_double: "
"-0.0937043\n value_double: 0.235796\n value_double: -0.0893372\n "
" value_double: 0.000827968\n value_double: 0.0172743\n "
"value_double: -0.234205\n value_double: -0.0867703\n "
"value_double: 0.131704\n value_double: 0.134143\n value_double: "
"-0.162257\n value_double: -0.129706\n value_double: 0.0763288\n "
" value_double: 0.156988\n value_double: 0.220033\n value_double: "
"-0.179884\n value_double: 0.066697\n value_double: 0.212322\n "
"value_double: -0.0961226\n value_double: -0.11223\n value_double: "
"0.249944\n value_double: 0.115673\n value_double: -0.100203\n "
"value_double: 0.125645\n value_double: -0.256104\n value_double: "
"0.0996534\n value_double: 0.167306\n value_double: -0.00700775\n "
" value_double: 0.242145\n value_double: 0.088406\n value_double: "
"0.0975334\n value_double: -0.0309525\n value_double: -0.0422794\n "
" value_double: 0.20739\n value_double: 0.113992\n value_double: "
"0.253818\n value_double: -0.0857835\n value_double: 0.223902\n "
"value_double: 0.10291\n value_double: 0.103091\n value_double: "
"-0.177502\n value_double: -0.0258242\n value_double: -0.130567\n "
" value_double: -0.15999\n value_double: -0.101484\n "
"value_double: 0.0188813\n value_double: 0.160626\n value_double: "
"0.0467491\n value_double: 0.193634\n value_double: -0.0910993\n "
" value_double: 0.0440249\n value_double: -0.255389\n "
"value_double: -0.240244\n value_double: -0.213171\n value_double: "
"0.175978\n value_double: -0.0251202\n value_double: 0.0943941\n "
" value_double: -0.196194\n value_double: 0.163395\n value_double: "
"-0.010777\n value_double: -0.0626751\n value_double: -0.246234\n "
" value_double: 0.0662063\n value_double: 0.120589\n "
"value_double: 0.237322\n value_double: 0.0849243\n value_double: "
"-0.066591\n value_double: 0.0512236\n value_double: -0.144309\n "
" value_double: -0.235415\n value_double: -0.0565311\n "
"value_double: 0.0882529\n value_double: -0.215923\n value_double: "
"-0.0873292\n value_double: -0.0691103\n value_double: "
"-0.00238678\n value_double: 0.147789\n value_double: -0.124451\n "
" value_double: 0.205044\n value_double: -0.0596834\n "
"value_double: 0.0268479\n value_double: 0.0857448\n value_double: "
"-0.0923855\n value_double: -0.0960547\n value_double: 0.169869\n "
" value_double: 0.16988\n value_double: -0.032271\n value_double: "
"-0.120731\n value_double: -0.199086\n value_double: 0.181199\n "
"value_double: 0.00897732\n value_double: -0.257469\n "
"value_double: -0.135556\n value_double: -0.149663\n value_double: "
"-0.00990398\n value_double: 0.221165\n value_double: 0.0327134\n "
" value_double: -0.0392821\n value_double: -0.0614503\n "
"value_double: 0.246602\n value_double: -0.171692\n value_double: "
"-0.150835\n value_double: -0.13854\n value_double: -0.244668\n "
"value_double: 0.0790781\n value_double: 0.212678\n value_double: "
"0.0782059\n value_double: -0.177888\n value_double: -0.165914\n "
" value_double: -0.164251\n value_double: 0.165007\n value_double: "
"0.239615\n value_double: -0.217642\n value_double: -0.219843\n "
"value_double: 0.0828398\n value_double: 0.00272235\n "
"value_double: -0.0323662\n value_double: -0.255953\n "
"value_double: 0.237298\n value_double: -0.0896481\n value_double: "
"-0.0605349\n value_double: 0.231679\n value_double: -0.123842\n "
" value_double: 0.0858642\n value_double: 0.23111\n value_double: "
"0.0491742\n }\n}\nfloat_ops: 0\ntotal_float_ops: 0\n",
&expected));
EXPECT_EQ(expected.DebugString(), root.DebugString());
}