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Diffstat (limited to 'tensorflow/core/api_def/base_api/api_def_ParseSequenceExample.pbtxt')
-rw-r--r-- | tensorflow/core/api_def/base_api/api_def_ParseSequenceExample.pbtxt | 112 |
1 files changed, 112 insertions, 0 deletions
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." +} |