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Fix error messages if model is required (resolves #1051)

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Rename about.__docs__ to about.__docs_models__.
This commit is contained in:
ines 2017-05-13 13:14:02 +02:00
parent 24e973b17f
commit 9003fd25e5
4 changed files with 19 additions and 20 deletions
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10
spacy/lexeme.pyx
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@ -24,6 +24,7 @@ from .attrs cimport IS_QUOTE
from .attrs cimport IS_LEFT_PUNCT
from .attrs cimport IS_RIGHT_PUNCT
from .attrs cimport IS_OOV
from . import about
memset(&EMPTY_LEXEME, 0, sizeof(LexemeC))
@ -137,11 +138,10 @@ cdef class Lexeme:
cdef int length = self.vocab.vectors_length
if length == 0:
raise ValueError(
"Word vectors set to length 0. This may be because the "
"data is not installed. If you haven't already, run"
"\npython -m spacy download %s\n"
"to install the data." % self.vocab.lang
)
"Word vectors set to length 0. This may be because you "
"don't have a model installed or loaded, or because your "
"model doesn't include word vectors. For more info, see "
"the documentation: \n%s\n" % about.__docs_models__)
vector_view = <float[:length,]>self.c.vector
return numpy.asarray(vector_view)

13
spacy/tokens/doc.pyx
View File

@ -29,6 +29,7 @@ from ..serialize.bits cimport BitArray
from ..util import normalize_slice
from ..syntax.iterators import CHUNKERS
from ..compat import is_config
from .. import about
DEF PADDING = 5
@ -403,9 +404,8 @@ cdef class Doc:
if not self.is_parsed:
raise ValueError(
"noun_chunks requires the dependency parse, which "
"requires data to be installed. If you haven't done so, run: "
"\npython -m spacy download %s\n"
"to install the data" % self.vocab.lang)
"requires data to be installed. For more info, see the "
"documentation: \n%s\n" % about.__docs_models__)
# Accumulate the result before beginning to iterate over it. This prevents
# the tokenisation from being changed out from under us during the iteration.
# The tricky thing here is that Span accepts its tokenisation changing,
@ -435,10 +435,9 @@ cdef class Doc:
if not self.is_parsed:
raise ValueError(
"sentence boundary detection requires the dependency parse, which "
"requires data to be installed. If you haven't done so, run: "
"\npython -m spacy download %s\n"
"to install the data" % self.vocab.lang)
"Sentence boundary detection requires the dependency parse, which "
"requires data to be installed. For more info, see the "
"documentation: \n%s\n" % about.__docs_models__)
cdef int i
start = 0
for i in range(1, self.length):

6
spacy/tokens/span.pyx
View File

@ -16,6 +16,7 @@ from ..util import normalize_slice
from ..attrs cimport IS_PUNCT, IS_SPACE
from ..lexeme cimport Lexeme
from ..compat import is_config
from .. import about
cdef class Span:
@ -221,9 +222,8 @@ cdef class Span:
if not self.doc.is_parsed:
raise ValueError(
"noun_chunks requires the dependency parse, which "
"requires data to be installed. If you haven't done so, run: "
"\npython -m spacy download %s\n"
"to install the data" % self.vocab.lang)
"requires data to be installed. For more info, see the "
"documentation: \n%s\n" % about.__docs_models__)
# Accumulate the result before beginning to iterate over it. This prevents
# the tokenisation from being changed out from under us during the iteration.
# The tricky thing here is that Span accepts its tokenisation changing,

10
spacy/tokens/token.pyx
View File

@ -26,6 +26,7 @@ from ..attrs cimport IS_TITLE, IS_UPPER, LIKE_URL, LIKE_NUM, LIKE_EMAIL, IS_STOP
from ..attrs cimport IS_OOV
from ..lexeme cimport Lexeme
from ..compat import is_config
from .. import about
cdef class Token:
@ -237,11 +238,10 @@ cdef class Token:
cdef int length = self.vocab.vectors_length
if length == 0:
raise ValueError(
"Word vectors set to length 0. This may be because the "
"data is not installed. If you haven't already, run"
"\npython -m spacy download %s\n"
"to install the data." % self.vocab.lang
)
"Word vectors set to length 0. This may be because you "
"don't have a model installed or loaded, or because your "
"model doesn't include word vectors. For more info, see "
"the documentation: \n%s\n" % about.__docs_models__)
vector_view = <float[:length,]>self.c.lex.vector
return numpy.asarray(vector_view)