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// Operators that deal with SummaryProtos (encoded as DT_STRING tensors) as
// inputs or outputs in various ways.
// See docs in ../ops/summary_ops.cc.
#include <unordered_set>
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/resource_mgr.h"
#include "tensorflow/core/framework/summary.pb.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/histogram/histogram.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/protobuf.h"
namespace tensorflow {
template <typename T>
class SummaryScalarOp : public OpKernel {
public:
explicit SummaryScalarOp(OpKernelConstruction* context) : OpKernel(context) {}
void Compute(OpKernelContext* c) override {
const Tensor& tags = c->input(0);
const Tensor& values = c->input(1);
OP_REQUIRES(c, tags.IsSameSize(values) ||
(TensorShapeUtils::IsLegacyScalar(tags.shape()) &&
TensorShapeUtils::IsLegacyScalar(values.shape())),
errors::InvalidArgument("tags and values not the same shape: ",
tags.shape().ShortDebugString(), " != ",
values.shape().ShortDebugString()));
auto Ttags = tags.flat<string>();
auto Tvalues = values.flat<T>();
Summary s;
for (int i = 0; i < Ttags.size(); i++) {
Summary::Value* v = s.add_value();
v->set_tag(Ttags(i));
v->set_simple_value(Tvalues(i));
}
Tensor* summary_tensor = nullptr;
OP_REQUIRES_OK(c, c->allocate_output(0, TensorShape({}), &summary_tensor));
CHECK(s.SerializeToString(&summary_tensor->scalar<string>()()));
}
};
REGISTER_KERNEL_BUILDER(Name("ScalarSummary")
.Device(DEVICE_CPU)
.TypeConstraint<float>("T"),
SummaryScalarOp<float>);
REGISTER_KERNEL_BUILDER(Name("ScalarSummary")
.Device(DEVICE_CPU)
.TypeConstraint<double>("T"),
SummaryScalarOp<double>);
class SummaryHistoOp : public OpKernel {
public:
// SummaryHistoOp could be extended to take a list of custom bucket
// boundaries as an option.
explicit SummaryHistoOp(OpKernelConstruction* context) : OpKernel(context) {}
void Compute(OpKernelContext* c) override {
const Tensor& tags = c->input(0);
const Tensor& values = c->input(1);
const auto flat = values.flat<float>();
OP_REQUIRES(c, TensorShapeUtils::IsLegacyScalar(tags.shape()),
errors::InvalidArgument("tags must be scalar"));
// Build histogram of values in "values" tensor
histogram::Histogram histo;
for (int64 i = 0; i < flat.size(); i++) {
float v = flat(i);
if (!std::isfinite(v)) {
c->SetStatus(
errors::OutOfRange("Nan in summary histogram for: ", name()));
break;
}
histo.Add(v);
}
Summary s;
Summary::Value* v = s.add_value();
v->set_tag(tags.scalar<string>()());
histo.EncodeToProto(v->mutable_histo(), false /* Drop zero buckets */);
Tensor* summary_tensor = nullptr;
OP_REQUIRES_OK(c, c->allocate_output(0, TensorShape({}), &summary_tensor));
CHECK(s.SerializeToString(&summary_tensor->scalar<string>()()));
}
};
REGISTER_KERNEL_BUILDER(Name("HistogramSummary").Device(DEVICE_CPU),
SummaryHistoOp);
struct HistogramResource : public ResourceBase {
histogram::ThreadSafeHistogram histogram;
string DebugString() override { return "A historam summary. Stats ..."; }
};
class SummaryMergeOp : public OpKernel {
public:
explicit SummaryMergeOp(OpKernelConstruction* context) : OpKernel(context) {}
void Compute(OpKernelContext* c) override {
Summary s;
std::unordered_set<string> tags;
for (int input_num = 0; input_num < c->num_inputs(); input_num++) {
const Tensor& in = c->input(input_num);
auto in_vec = in.flat<string>();
for (int i = 0; i < in_vec.dimension(0); i++) {
const string& s_in = in_vec(i);
Summary summary_in;
if (!ParseProtoUnlimited(&summary_in, s_in)) {
c->SetStatus(errors::InvalidArgument(
"Could not parse one of the summary inputs"));
return;
}
for (int v = 0; v < summary_in.value_size(); v++) {
if (!tags.insert(summary_in.value(v).tag()).second) {
c->SetStatus(errors::InvalidArgument(
strings::StrCat("Duplicate tag ", summary_in.value(v).tag(),
" found in summary inputs")));
return;
}
*s.add_value() = summary_in.value(v);
}
}
}
Tensor* summary_tensor = nullptr;
OP_REQUIRES_OK(c, c->allocate_output(0, TensorShape({}), &summary_tensor));
CHECK(s.SerializeToString(&summary_tensor->scalar<string>()()));
}
};
REGISTER_KERNEL_BUILDER(Name("MergeSummary").Device(DEVICE_CPU),
SummaryMergeOp);
} // namespace tensorflow
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