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Cleanup
This removes one old print statement and some old TODOs. Some TODOs are left as future work.
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@ -126,7 +126,6 @@ def _check_pipeline_names(nlp, nlp2):
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for name in nlp2.pipe_names:
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if name in names:
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inc = _increment_suffix(name)
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# TODO Would it be better to just keep incrementing?
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if inc in names or inc in nlp2.pipe_names:
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msg.fail(fail_msg.format(name=name, new_name=inc), exits=1)
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rename[name] = inc
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@ -195,8 +194,6 @@ def use_transformer(
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)
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msg.fail(fail_msg, exits=1)
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# TODO maybe remove vectors?
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# now update the listeners
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listeners = _get_listeners(nlp)
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for listener in listeners:
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@ -289,7 +286,6 @@ def _inner_merge(nlp, nlp2, replace_listeners=False) -> Language:
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# the tok2vec should not be copied over
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continue
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if replace_listeners and _has_listener(nlp2, comp):
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# TODO does "model.tok2vec" work for everything?
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nlp2.replace_listeners(tok2vec_name, comp, ["model.tok2vec"])
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nlp.add_pipe(comp, source=nlp2, name=rename.get(comp, comp))
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if comp in rename:
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@ -306,7 +302,7 @@ def merge_pipelines(base_model: str, added_model: str, output_file: Path) -> Lan
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# to merge models:
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# - lang must be the same
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# - vectors must be the same
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# - vocabs must be the same (how to check?)
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# - vocabs must be the same
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# - tokenizer must be the same (only partially checkable)
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if nlp.lang != nlp2.lang:
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msg.fail("Can't merge - languages don't match", exits=1)
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@ -329,10 +325,9 @@ def merge_pipelines(base_model: str, added_model: str, output_file: Path) -> Lan
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# Check how many listeners there are and replace based on that
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# TODO: option to recognize frozen tok2vecs
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# TODO: take list of pipe names to copy
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# TODO: take list of pipe names to copy, ignore others
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listeners = _get_listeners(nlp2)
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replace_listeners = len(listeners) == 1
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print(replace_listeners, len(listeners))
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nlp_out = _inner_merge(nlp, nlp2, replace_listeners=replace_listeners)
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# write the final pipeline
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