From d09bd33fc9175c7fdbdded8f98b5c5d3a9f8ad7d Mon Sep 17 00:00:00 2001
From: Patrik Sundberg <sundberg@google.com>
Date: Fri, 31 Aug 2018 07:28:43 -0700
Subject: Add a batch sequence example parsing op, part 2.

PiperOrigin-RevId: 211082479
---
 .../base_api/api_def_ParseSequenceExample.pbtxt    | 112 +++++++++++++++++++++
 .../python_api/api_def_ParseSequenceExample.pbtxt  |   4 +
 2 files changed, 116 insertions(+)
 create mode 100644 tensorflow/core/api_def/base_api/api_def_ParseSequenceExample.pbtxt
 create mode 100644 tensorflow/core/api_def/python_api/api_def_ParseSequenceExample.pbtxt

(limited to 'tensorflow/core/api_def')

diff --git a/tensorflow/core/api_def/base_api/api_def_ParseSequenceExample.pbtxt b/tensorflow/core/api_def/base_api/api_def_ParseSequenceExample.pbtxt
new file mode 100644
index 0000000000..b1cb9a696d
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_ParseSequenceExample.pbtxt
@@ -0,0 +1,112 @@
+op {
+  graph_op_name: "ParseSequenceExample"
+  in_arg {
+    name: "serialized"
+    description: <<END
+A vector containing binary serialized SequenceExample protos.
+END
+  }
+  in_arg {
+    name: "debug_name"
+    description: <<END
+A vector containing the names of the serialized protos.
+May contain, for example, table key (descriptive) name for the
+corresponding serialized proto.  This is purely useful for debugging
+purposes, and the presence of values here has no effect on the output.
+May also be an empty vector if no name is available.
+END
+  }
+  in_arg {
+    name: "context_dense_defaults"
+    description: <<END
+A list of Ncontext_dense Tensors (some may be empty).
+context_dense_defaults[j] provides default values
+when the SequenceExample's context map lacks context_dense_key[j].
+If an empty Tensor is provided for context_dense_defaults[j],
+then the Feature context_dense_keys[j] is required.
+The input type is inferred from context_dense_defaults[j], even when it's
+empty.  If context_dense_defaults[j] is not empty, its shape must match
+context_dense_shapes[j].
+END
+  }
+  attr {
+    name: "feature_list_dense_missing_assumed_empty"
+    description: <<END
+A vector listing the
+FeatureList keys which may be missing from the SequenceExamples.  If the
+associated FeatureList is missing, it is treated as empty.  By default,
+any FeatureList not listed in this vector must exist in the SequenceExamples.
+END
+  }
+  attr {
+    name: "context_sparse_keys"
+    description: <<END
+A list of Ncontext_sparse string Tensors (scalars).
+The keys expected in the Examples' features associated with context_sparse
+values.
+END
+  }
+  attr {
+    name: "context_dense_keys"
+    description: <<END
+A list of Ncontext_dense string Tensors (scalars).
+The keys expected in the SequenceExamples' context features associated with
+dense values.
+END
+  }
+  attr {
+    name: "feature_list_sparse_keys"
+    description: <<END
+A list of Nfeature_list_sparse string Tensors
+(scalars).  The keys expected in the FeatureLists associated with sparse
+values.
+END
+  }
+  attr {
+    name: "feature_list_dense_keys"
+    description: <<END
+A list of Nfeature_list_dense string Tensors (scalars).
+The keys expected in the SequenceExamples' feature_lists associated
+with lists of dense values.
+END
+  }
+  attr {
+    name: "context_sparse_types"
+    description: <<END
+A list of Ncontext_sparse types; the data types of data in
+each context Feature given in context_sparse_keys.
+Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
+DT_INT64 (Int64List), and DT_STRING (BytesList).
+END
+  }
+  attr {
+    name: "context_dense_shapes"
+    description: <<END
+A list of Ncontext_dense shapes; the shapes of data in
+each context Feature given in context_dense_keys.
+The number of elements in the Feature corresponding to context_dense_key[j]
+must always equal context_dense_shapes[j].NumEntries().
+The shape of context_dense_values[j] will match context_dense_shapes[j].
+END
+  }
+  attr {
+    name: "feature_list_sparse_types"
+    description: <<END
+A list of Nfeature_list_sparse types; the data types
+of data in each FeatureList given in feature_list_sparse_keys.
+Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
+DT_INT64 (Int64List), and DT_STRING (BytesList).
+END
+  }
+  attr {
+    name: "feature_list_dense_shapes"
+    description: <<END
+A list of Nfeature_list_dense shapes; the shapes of
+data in each FeatureList given in feature_list_dense_keys.
+The shape of each Feature in the FeatureList corresponding to
+feature_list_dense_key[j] must always equal
+feature_list_dense_shapes[j].NumEntries().
+END
+  }
+  summary: "Transforms a vector of brain.SequenceExample protos (as strings) into typed tensors."
+}
diff --git a/tensorflow/core/api_def/python_api/api_def_ParseSequenceExample.pbtxt b/tensorflow/core/api_def/python_api/api_def_ParseSequenceExample.pbtxt
new file mode 100644
index 0000000000..4a7e75ba0e
--- /dev/null
+++ b/tensorflow/core/api_def/python_api/api_def_ParseSequenceExample.pbtxt
@@ -0,0 +1,4 @@
+op {
+  graph_op_name: "ParseSequenceExample"
+  visibility: HIDDEN
+}
-- 
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