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Add alignment_mode argument to Span.char_span()
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@ -98,6 +98,7 @@ class Span:
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label: Union[int, str] = ...,
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kb_id: Union[int, str] = ...,
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vector: Optional[Floats1d] = ...,
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alignment_mode: str = ...,
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) -> Span: ...
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@property
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def conjuncts(self) -> Tuple[Token]: ...
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@ -362,7 +362,7 @@ cdef class Span:
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result = xp.dot(vector, other.vector) / (self.vector_norm * other.vector_norm)
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# ensure we get a scalar back (numpy does this automatically but cupy doesn't)
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return result.item()
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cpdef np.ndarray to_array(self, object py_attr_ids):
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"""Given a list of M attribute IDs, export the tokens to a numpy
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`ndarray` of shape `(N, M)`, where `N` is the length of the document.
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@ -639,7 +639,7 @@ cdef class Span:
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else:
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return self.doc[root]
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def char_span(self, int start_idx, int end_idx, label=0, kb_id=0, vector=None, id=0):
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def char_span(self, int start_idx, int end_idx, label=0, kb_id=0, vector=None, alignment_mode="strict", id=0):
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"""Create a `Span` object from the slice `span.text[start : end]`.
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start (int): The index of the first character of the span.
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@ -649,11 +649,16 @@ cdef class Span:
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kb_id (uint64 or string): An ID from a KB to capture the meaning of a named entity.
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vector (ndarray[ndim=1, dtype='float32']): A meaning representation of
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the span.
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alignment_mode (str): How character indices are aligned to token
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boundaries. Options: "strict" (character indices must be aligned
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with token boundaries), "contract" (span of all tokens completely
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within the character span), "expand" (span of all tokens at least
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partially covered by the character span). Defaults to "strict".
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RETURNS (Span): The newly constructed object.
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"""
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start_idx += self.c.start_char
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end_idx += self.c.start_char
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return self.doc.char_span(start_idx, end_idx, label=label, kb_id=kb_id, vector=vector)
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return self.doc.char_span(start_idx, end_idx, label=label, kb_id=kb_id, vector=vector, alignment_mode=alignment_mode)
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@property
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def conjuncts(self):
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