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syntaxnet: Enable building Parsey McParseface in one model to be served in TF serving #250
Commits on Jul 22, 2016
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Add ability to feed (pre-parsed) Sentence protos to SentenceBatch
SentenceBatch accepts a vector of Sentence protos to use instead of reading from the configured corpus. When using a feed, the corpus will be ignored and only the fed sentences will be used. Supports "rewind" on the feed.
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Add an input Tensor to BeamParseReader to provide serialised sentence…
… protos to parse Add an input Tensor to BeamParseReader to provide serialised sentence protos to parse. Documents may come from the input tensor (e.g. read by a DocumentSource op) or read directly from the corpus as defined in the task context. The decision of the approach should is explicit based on attributes during graph configuration.
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Add ability to read text from a vector of strings in TextReader.
If constructed with a vector of strings, TextReader will use a new "RandomAccessFile" implementation, VectorIn (cloned from the StdIn implementation) to read the strings from the vector. The format of the strings is still determined by the corpus configured in the task context.
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Add an (unused) input value to the DocumentSource op as required
The DocumentSource requires a text input tensor to be provided, even when the text is to be read from the corpus, because tensors cannot be optional. The value of the tensor is unused.
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Modify graph builder to take optional document_source at build time
If the document source is provided, it will be used and the parser will not read from the corpus. If it is provided, the document protos will be consumed from the provided op and the configured corpus will be ignored
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Script which replaces demo.sh for running Parsey McParseface model
This new script replaces demo.sh for running Parsey McParseface model. It takes a different approach from demo.sh which is that it builds the entire operation chain (tagging AND parsing) in a single model, complete with a document source and document sink. The script also exports the model in various ways, including using the TF Serving exporter, such that the model can be served using TF Serving
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