tf.raw_ops.ParseSingleSequenceExample

Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors.

serialized A Tensor of type string. A scalar containing a binary serialized SequenceExample proto.
feature_list_dense_missing_assumed_empty A Tensor of type string. A vector listing the FeatureList keys which may be missing from the SequenceExample. If the associated FeatureList is missing, it is treated as empty. By default, any FeatureList not listed in this vector must exist in the SequenceExample.
context_sparse_keys A list of Tensor objects with type string. A list of Ncontext_sparse string Tensors (scalars). The keys expected in the Examples' features associated with context_sparse values.
context_dense_keys A list of Tensor objects with type string. A list of Ncontext_dense string Tensors (scalars). The keys expected in the SequenceExamples' context features associated with dense values.
feature_list_sparse_keys A list of Tensor objects with type string. A list of Nfeature_list_sparse string Tensors (scalars). The keys expected in the FeatureLists associated with sparse values.
feature_list_dense_keys A list of Tensor objects with type string. A list of Nfeature_list_dense string Tensors (scalars). The keys expected in the SequenceExamples' feature_lists associated with lists of dense values.
context_dense_defaults A list of Tensor objects with types from: float32, int64, string. 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].
debug_name A Tensor of type string. A scalar containing the name of the serialized proto. May