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+#include "tensorflow/core/framework/op.h"
+
+namespace tensorflow {
+
+// Operators that deal with SummaryProtos (encoded as DT_STRING tensors) as
+// inputs or outputs in various ways.
+
+REGISTER_OP("ScalarSummary")
+    .Input("tags: string")
+    .Input("values: T")
+    .Output("summary: string")
+    .Attr("T: {float, double}")
+    .Doc(R"doc(
+Outputs a `Summary` protocol buffer with scalar values.
+
+The input `tags` and `values` must have the same shape.  The generated summary
+has a summary value for each tag-value pair in `tags` and `values`.
+
+tags: 1-D. Tags for the summary.
+values: 1-D, same size as `tags.  Values for the summary.
+summary: Scalar.  Serialized `Summary` protocol buffer.
+)doc");
+
+REGISTER_OP("HistogramSummary")
+    .Input("tag: string")
+    .Input("values: float")
+    .Output("summary: string")
+    .Doc(R"doc(
+Outputs a `Summary` protocol buffer with a histogram.
+
+The generated
+[`Summary`](https://tensorflow.googlesource.com/tensorflow/+/master/tensorflow/core/framework/summary.proto)
+has one summary value containing a histogram for `values`.
+
+This op reports an `OutOfRange` error if any value is not finite.
+
+tag: Scalar.  Tag to use for the `Summary.Value`.
+values: Any shape. Values to use to build the histogram.
+summary: Scalar. Serialized `Summary` protocol buffer.
+)doc");
+
+REGISTER_OP("ImageSummary")
+    .Input("tag: string")
+    .Input("tensor: float")
+    .Output("summary: string")
+    .Attr("max_images: int >= 1 = 3")
+    .Attr(
+        "bad_color: tensor = { dtype: DT_UINT8 "
+        "tensor_shape: { dim { size: 4 } } "
+        "int_val: 255 int_val: 0 int_val: 0 int_val: 255 }")
+    .Doc(R"doc(
+Outputs a `Summary` protocol buffer with images.
+
+The summary has up to `max_images` summary values containing images. The
+images are built from `tensor` which must be 4-D with shape `[batch_size,
+height, width, channels]` and where `channels` can be:
+
+*  1: `tensor` is interpreted as Grayscale.
+*  3: `tensor` is interpreted as RGB.
+*  4: `tensor` is interpreted as RGBA.
+
+The images have the same number of channels as the input tensor. Their values
+are normalized, one image at a time, to fit in the range `[0, 255]`.  The
+op uses two different normalization algorithms:
+
+*  If the input values are all positive, they are rescaled so the largest one
+   is 255.
+
+*  If any input value is negative, the values are shifted so input value 0.0
+   is at 127.  They are then rescaled so that either the smallest value is 0,
+   or the largest one is 255.
+
+The `tag` argument is a scalar `Tensor` of type `string`.  It is used to
+build the `tag` of the summary values:
+
+*  If `max_images` is 1, the summary value tag is '*tag*/image'.
+*  If `max_images` is greater than 1, the summary value tags are
+   generated sequentially as '*tag*/image/0', '*tag*/image/1', etc.
+
+The `bad_color` argument is the color to use in the generated images for
+non-finite input values.  It is a `unit8` 1-D tensor of length `channels`.
+Each element must be in the range `[0, 255]` (It represents the value of a
+pixel in the output image).  Non-finite values in the input tensor are
+replaced by this tensor in the output image.  The default value is the color
+red.
+
+tag: Scalar. Used to build the `tag` attribute of the summary values.
+tensor: 4-D of shape `[batch_size, height, width, channels]` where
+  `channels` is 1, 3, or 4.
+max_images: Max number of batch elements to generate images for.
+bad_color: Color to use for pixels with non-finite values.
+summary: Scalar. Serialized `Summary` protocol buffer.
+)doc");
+
+REGISTER_OP("MergeSummary")
+    .Input("inputs: N * string")
+    .Output("summary: string")
+    .Attr("N : int >= 1")
+    .Doc(R"doc(
+Merges summaries.
+
+This op creates a
+[`Summary`](https://tensorflow.googlesource.com/tensorflow/+/master/tensorflow/core/framework/summary.proto)
+protocol buffer that contains the union of all the values in the input
+summaries.
+
+When the Op is run, it reports an `InvalidArgument` error if multiple values
+in the summaries to merge use the same tag.
+
+inputs: Can be of any shape.  Each must contain serialized `Summary` protocol
+  buffers.
+summary: Scalar. Serialized `Summary` protocol buffer.
+)doc");
+
+}  // namespace tensorflow