Tidy up errors and warnings

This commit is contained in:
Ines Montani 2020-10-04 11:16:31 +02:00
parent ff914f4e6f
commit bcd52e5486
15 changed files with 186 additions and 221 deletions

View File

@ -322,8 +322,7 @@ def git_checkout(
if dest.exists():
msg.fail("Destination of checkout must not exist", exits=1)
if not dest.parent.exists():
raise IOError("Parent of destination of checkout must exist")
msg.fail("Parent of destination of checkout must exist", exits=1)
if sparse and git_version >= (2, 22):
return git_sparse_checkout(repo, subpath, dest, branch)
elif sparse:

View File

@ -16,8 +16,6 @@ def add_codes(err_cls):
@add_codes
class Warnings:
W004 = ("No text fixing enabled. Run `pip install ftfy` to enable fixing "
"using ftfy.fix_text if necessary.")
W005 = ("Doc object not parsed. This means displaCy won't be able to "
"generate a dependency visualization for it. Make sure the Doc "
"was processed with a model that supports dependency parsing, and "
@ -51,8 +49,6 @@ class Warnings:
W017 = ("Alias '{alias}' already exists in the Knowledge Base.")
W018 = ("Entity '{entity}' already exists in the Knowledge Base - "
"ignoring the duplicate entry.")
W020 = ("Unnamed vectors. This won't allow multiple vectors models to be "
"loaded. (Shape: {shape})")
W021 = ("Unexpected hash collision in PhraseMatcher. Matches may be "
"incorrect. Modify PhraseMatcher._terminal_hash to fix.")
W024 = ("Entity '{entity}' - Alias '{alias}' combination already exists in "
@ -65,7 +61,7 @@ class Warnings:
"be more efficient to split your training data into multiple "
"smaller JSON files instead.")
W028 = ("Doc.from_array was called with a vector of type '{type}', "
"but is expecting one of type 'uint64' instead. This may result "
"but is expecting one of type uint64 instead. This may result "
"in problems with the vocab further on in the pipeline.")
W030 = ("Some entities could not be aligned in the text \"{text}\" with "
"entities \"{entities}\". Use "
@ -79,18 +75,17 @@ class Warnings:
"If this is surprising, make sure you have the spacy-lookups-data "
"package installed. The languages with lexeme normalization tables "
"are currently: {langs}")
W034 = ("Please install the package spacy-lookups-data in order to include "
"the default lexeme normalization table for the language '{lang}'.")
W035 = ('Discarding subpattern "{pattern}" due to an unrecognized '
"attribute or operator.")
# TODO: fix numbering after merging develop into master
W088 = ("The pipeline component {name} implements a 'begin_training' "
"method, which won't be called by spaCy. As of v3.0, 'begin_training' "
"has been renamed to 'initialize' so you likely want to rename the "
W088 = ("The pipeline component {name} implements a `begin_training` "
"method, which won't be called by spaCy. As of v3.0, `begin_training` "
"has been renamed to `initialize`, so you likely want to rename the "
"component method. See the documentation for details: "
"https://nightly.spacy.io/api/language#initialize")
W089 = ("The nlp.begin_training method has been renamed to nlp.initialize.")
W089 = ("As of spaCy v3.0, the `nlp.begin_training` method has been renamed "
"to `nlp.initialize`.")
W090 = ("Could not locate any {format} files in path '{path}'.")
W091 = ("Could not clean/remove the temp directory at {dir}: {msg}.")
W092 = ("Ignoring annotations for sentence starts, as dependency heads are set.")
@ -108,39 +103,33 @@ class Warnings:
"download a newer compatible model or retrain your custom model "
"with the current spaCy version. For more details and available "
"updates, run: python -m spacy validate")
W096 = ("The method 'disable_pipes' has become deprecated - use 'select_pipes' "
"instead.")
W097 = ("No Model config was provided to create the '{name}' component, "
"and no default configuration could be found either.")
W098 = ("No Model config was provided to create the '{name}' component, "
"so a default configuration was used.")
W099 = ("Expected 'dict' type for the 'model' argument of pipe '{pipe}', "
"but got '{type}' instead, so ignoring it.")
W096 = ("The method `nlp.disable_pipes` is now deprecated - use "
"`nlp.select_pipes` instead.")
W100 = ("Skipping unsupported morphological feature(s): '{feature}'. "
"Provide features as a dict {{\"Field1\": \"Value1,Value2\"}} or "
"string \"Field1=Value1,Value2|Field2=Value3\".")
W101 = ("Skipping `Doc` custom extension '{name}' while merging docs.")
W101 = ("Skipping Doc custom extension '{name}' while merging docs.")
W102 = ("Skipping unsupported user data '{key}: {value}' while merging docs.")
W103 = ("Unknown {lang} word segmenter '{segmenter}'. Supported "
"word segmenters: {supported}. Defaulting to {default}.")
W104 = ("Skipping modifications for '{target}' segmenter. The current "
"segmenter is '{current}'.")
W105 = ("As of spaCy v3.0, the {matcher}.pipe method is deprecated. If you "
"need to match on a stream of documents, you can use nlp.pipe and "
W105 = ("As of spaCy v3.0, the `{matcher}.pipe` method is deprecated. If you "
"need to match on a stream of documents, you can use `nlp.pipe` and "
"call the {matcher} on each Doc object.")
W107 = ("The property Doc.{prop} is deprecated. Use "
"Doc.has_annotation(\"{attr}\") instead.")
W107 = ("The property `Doc.{prop}` is deprecated. Use "
"`Doc.has_annotation(\"{attr}\")` instead.")
@add_codes
class Errors:
E001 = ("No component '{name}' found in pipeline. Available names: {opts}")
E002 = ("Can't find factory for '{name}' for language {lang} ({lang_code}). "
"This usually happens when spaCy calls nlp.{method} with custom "
"This usually happens when spaCy calls `nlp.{method}` with custom "
"component name that's not registered on the current language class. "
"If you're using a custom component, make sure you've added the "
"decorator @Language.component (for function components) or "
"@Language.factory (for class components).\n\nAvailable "
"decorator `@Language.component` (for function components) or "
"`@Language.factory` (for class components).\n\nAvailable "
"factories: {opts}")
E003 = ("Not a valid pipeline component. Expected callable, but "
"got {component} (name: '{name}'). If you're using a custom "
@ -158,14 +147,13 @@ class Errors:
E008 = ("Can't restore disabled pipeline component '{name}' because it "
"doesn't exist in the pipeline anymore. If you want to remove "
"components from the pipeline, you should do it before calling "
"`nlp.select_pipes()` or after restoring the disabled components.")
"`nlp.select_pipes` or after restoring the disabled components.")
E010 = ("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 docs:\n"
"https://nightly.spacy.io/usage/models")
E011 = ("Unknown operator: '{op}'. Options: {opts}")
E012 = ("Cannot add pattern for zero tokens to matcher.\nKey: {key}")
E014 = ("Unknown tag ID: {tag}")
E016 = ("MultitaskObjective target should be function or one of: dep, "
"tag, ent, dep_tag_offset, ent_tag.")
E017 = ("Can only add unicode or bytes. Got type: {value_type}")
@ -181,27 +169,24 @@ class Errors:
"For example, are all labels added to the model? If you're "
"training a named entity recognizer, also make sure that none of "
"your annotated entity spans have leading or trailing whitespace "
"or punctuation. "
"You can also use the experimental `debug data` command to "
"or punctuation. You can also use the `debug data` command to "
"validate your JSON-formatted training data. For details, run:\n"
"python -m spacy debug data --help")
E025 = ("String is too long: {length} characters. Max is 2**30.")
E026 = ("Error accessing token at position {i}: out of bounds in Doc of "
"length {length}.")
E027 = ("Arguments 'words' and 'spaces' should be sequences of the same "
"length, or 'spaces' should be left default at None. spaces "
E027 = ("Arguments `words` and `spaces` should be sequences of the same "
"length, or `spaces` should be left default at None. `spaces` "
"should be a sequence of booleans, with True meaning that the "
"word owns a ' ' character following it.")
E028 = ("orths_and_spaces expects either a list of unicode string or a "
"list of (unicode, bool) tuples. Got bytes instance: {value}")
E029 = ("noun_chunks requires the dependency parse, which requires a "
E028 = ("`words` expects a list of unicode strings, but got bytes instance: {value}")
E029 = ("`noun_chunks` requires the dependency parse, which requires a "
"statistical model to be installed and loaded. For more info, see "
"the documentation:\nhttps://nightly.spacy.io/usage/models")
E030 = ("Sentence boundaries unset. You can add the 'sentencizer' "
"component to the pipeline with: "
"nlp.add_pipe('sentencizer'). "
"component to the pipeline with: `nlp.add_pipe('sentencizer')`. "
"Alternatively, add the dependency parser, or set sentence "
"boundaries by setting doc[i].is_sent_start.")
"boundaries by setting `doc[i].is_sent_start`.")
E031 = ("Invalid token: empty string ('') at position {i}.")
E033 = ("Cannot load into non-empty Doc of length {length}.")
E035 = ("Error creating span with start {start} and end {end} for Doc of "
@ -215,7 +200,7 @@ class Errors:
"issue here: http://github.com/explosion/spaCy/issues")
E040 = ("Attempt to access token at {i}, max length {max_length}.")
E041 = ("Invalid comparison operator: {op}. Likely a Cython bug?")
E042 = ("Error accessing doc[{i}].nbor({j}), for doc of length {length}.")
E042 = ("Error accessing `doc[{i}].nbor({j})`, for doc of length {length}.")
E043 = ("Refusing to write to token.sent_start if its document is parsed, "
"because this may cause inconsistent state.")
E044 = ("Invalid value for token.sent_start: {value}. Must be one of: "
@ -235,7 +220,7 @@ class Errors:
E056 = ("Invalid tokenizer exception: ORTH values combined don't match "
"original string.\nKey: {key}\nOrths: {orths}")
E057 = ("Stepped slices not supported in Span objects. Try: "
"list(tokens)[start:stop:step] instead.")
"`list(tokens)[start:stop:step]` instead.")
E058 = ("Could not retrieve vector for key {key}.")
E059 = ("One (and only one) keyword arg must be set. Got: {kwargs}")
E060 = ("Cannot add new key to vectors: the table is full. Current shape: "
@ -244,7 +229,7 @@ class Errors:
"and 63 are occupied. You can replace one by specifying the "
"`flag_id` explicitly, e.g. "
"`nlp.vocab.add_flag(your_func, flag_id=IS_ALPHA`.")
E063 = ("Invalid value for flag_id: {value}. Flag IDs must be between 1 "
E063 = ("Invalid value for `flag_id`: {value}. Flag IDs must be between 1 "
"and 63 (inclusive).")
E064 = ("Error fetching a Lexeme from the Vocab. When looking up a "
"string, the lexeme returned had an orth ID that did not match "
@ -273,7 +258,7 @@ class Errors:
E085 = ("Can't create lexeme for string '{string}'.")
E087 = ("Unknown displaCy style: {style}.")
E088 = ("Text of length {length} exceeds maximum of {max_length}. The "
"v2.x parser and NER models require roughly 1GB of temporary "
"parser and NER models require roughly 1GB of temporary "
"memory per 100,000 characters in the input. This means long "
"texts may cause memory allocation errors. If you're not using "
"the parser or NER, it's probably safe to increase the "
@ -290,8 +275,8 @@ class Errors:
E094 = ("Error reading line {line_num} in vectors file {loc}.")
E095 = ("Can't write to frozen dictionary. This is likely an internal "
"error. Are you writing to a default function argument?")
E096 = ("Invalid object passed to displaCy: Can only visualize Doc or "
"Span objects, or dicts if set to manual=True.")
E096 = ("Invalid object passed to displaCy: Can only visualize `Doc` or "
"Span objects, or dicts if set to `manual=True`.")
E097 = ("Invalid pattern: expected token pattern (list of dicts) or "
"phrase pattern (string) but got:\n{pattern}")
E098 = ("Invalid pattern: expected both RIGHT_ID and RIGHT_ATTRS.")
@ -308,11 +293,11 @@ class Errors:
E103 = ("Trying to set conflicting doc.ents: '{span1}' and '{span2}'. A "
"token can only be part of one entity, so make sure the entities "
"you're setting don't overlap.")
E106 = ("Can't find doc._.{attr} attribute specified in the underscore "
E106 = ("Can't find `doc._.{attr}` attribute specified in the underscore "
"settings: {opts}")
E107 = ("Value of doc._.{attr} is not JSON-serializable: {value}")
E107 = ("Value of `doc._.{attr}` is not JSON-serializable: {value}")
E109 = ("Component '{name}' could not be run. Did you forget to "
"call initialize()?")
"call `initialize()`?")
E110 = ("Invalid displaCy render wrapper. Expected callable, got: {obj}")
E111 = ("Pickling a token is not supported, because tokens are only views "
"of the parent Doc and can't exist on their own. A pickled token "
@ -329,8 +314,8 @@ class Errors:
E117 = ("The newly split tokens must match the text of the original token. "
"New orths: {new}. Old text: {old}.")
E118 = ("The custom extension attribute '{attr}' is not registered on the "
"Token object so it can't be set during retokenization. To "
"register an attribute, use the Token.set_extension classmethod.")
"`Token` object so it can't be set during retokenization. To "
"register an attribute, use the `Token.set_extension` classmethod.")
E119 = ("Can't set custom extension attribute '{attr}' during "
"retokenization because it's not writable. This usually means it "
"was registered with a getter function (and no setter) or as a "
@ -354,7 +339,7 @@ class Errors:
E130 = ("You are running a narrow unicode build, which is incompatible "
"with spacy >= 2.1.0. To fix this, reinstall Python and use a wide "
"unicode build instead. You can also rebuild Python and set the "
"--enable-unicode=ucs4 flag.")
"`--enable-unicode=ucs4 flag`.")
E131 = ("Cannot write the kb_id of an existing Span object because a Span "
"is a read-only view of the underlying Token objects stored in "
"the Doc. Instead, create a new Span object and specify the "
@ -367,27 +352,20 @@ class Errors:
E133 = ("The sum of prior probabilities for alias '{alias}' should not "
"exceed 1, but found {sum}.")
E134 = ("Entity '{entity}' is not defined in the Knowledge Base.")
E137 = ("Expected 'dict' type, but got '{type}' from '{line}'. Make sure "
"to provide a valid JSON object as input with either the `text` "
"or `tokens` key. For more info, see the docs:\n"
"https://nightly.spacy.io/api/cli#pretrain-jsonl")
E138 = ("Invalid JSONL format for raw text '{text}'. Make sure the input "
"includes either the `text` or `tokens` key. For more info, see "
"the docs:\nhttps://nightly.spacy.io/api/cli#pretrain-jsonl")
E139 = ("Knowledge Base for component '{name}' is empty. Use the methods "
"kb.add_entity and kb.add_alias to add entries.")
E139 = ("Knowledge base for component '{name}' is empty. Use the methods "
"`kb.add_entity` and `kb.add_alias` to add entries.")
E140 = ("The list of entities, prior probabilities and entity vectors "
"should be of equal length.")
E141 = ("Entity vectors should be of length {required} instead of the "
"provided {found}.")
E143 = ("Labels for component '{name}' not initialized. This can be fixed "
"by calling add_label, or by providing a representative batch of "
"examples to the component's initialize method.")
"examples to the component's `initialize` method.")
E145 = ("Error reading `{param}` from input file.")
E146 = ("Could not access `{path}`.")
E146 = ("Could not access {path}.")
E147 = ("Unexpected error in the {method} functionality of the "
"EntityLinker: {msg}. This is likely a bug in spaCy, so feel free "
"to open an issue.")
"to open an issue: https://github.com/explosion/spaCy/issues")
E148 = ("Expected {ents} KB identifiers but got {ids}. Make sure that "
"each entity in `doc.ents` is assigned to a KB identifier.")
E149 = ("Error deserializing model. Check that the config used to create "
@ -395,18 +373,18 @@ class Errors:
E150 = ("The language of the `nlp` object and the `vocab` should be the "
"same, but found '{nlp}' and '{vocab}' respectively.")
E152 = ("The attribute {attr} is not supported for token patterns. "
"Please use the option validate=True with Matcher, PhraseMatcher, "
"Please use the option `validate=True` with the Matcher, PhraseMatcher, "
"or EntityRuler for more details.")
E153 = ("The value type {vtype} is not supported for token patterns. "
"Please use the option validate=True with Matcher, PhraseMatcher, "
"or EntityRuler for more details.")
E154 = ("One of the attributes or values is not supported for token "
"patterns. Please use the option validate=True with Matcher, "
"patterns. Please use the option `validate=True` with the Matcher, "
"PhraseMatcher, or EntityRuler for more details.")
E155 = ("The pipeline needs to include a {pipe} in order to use "
"Matcher or PhraseMatcher with the attribute {attr}. "
"Try using nlp() instead of nlp.make_doc() or list(nlp.pipe()) "
"instead of list(nlp.tokenizer.pipe()).")
"Try using `nlp()` instead of `nlp.make_doc()` or `list(nlp.pipe())` "
"instead of `list(nlp.tokenizer.pipe())`.")
E157 = ("Can't render negative values for dependency arc start or end. "
"Make sure that you're passing in absolute token indices, not "
"relative token offsets.\nstart: {start}, end: {end}, label: "
@ -415,13 +393,11 @@ class Errors:
E159 = ("Can't find table '{name}' in lookups. Available tables: {tables}")
E160 = ("Can't find language data file: {path}")
E161 = ("Found an internal inconsistency when predicting entity links. "
"This is likely a bug in spaCy, so feel free to open an issue.")
E162 = ("Cannot evaluate textcat model on data with different labels.\n"
"Labels in model: {model_labels}\nLabels in evaluation "
"data: {eval_labels}")
"This is likely a bug in spaCy, so feel free to open an issue: "
"https://github.com/explosion/spaCy/issues")
E163 = ("cumsum was found to be unstable: its last element does not "
"correspond to sum")
E164 = ("x is neither increasing nor decreasing: {}.")
E164 = ("x is neither increasing nor decreasing: {x}.")
E165 = ("Only one class present in y_true. ROC AUC score is not defined in "
"that case.")
E166 = ("Can only merge DocBins with the same value for '{param}'.\n"
@ -436,10 +412,10 @@ class Errors:
E178 = ("Each pattern should be a list of dicts, but got: {pat}. Maybe you "
"accidentally passed a single pattern to Matcher.add instead of a "
"list of patterns? If you only want to add one pattern, make sure "
"to wrap it in a list. For example: matcher.add('{key}', [pattern])")
"to wrap it in a list. For example: `matcher.add('{key}', [pattern])`")
E179 = ("Invalid pattern. Expected a list of Doc objects but got a single "
"Doc. If you only want to add one pattern, make sure to wrap it "
"in a list. For example: matcher.add('{key}', [doc])")
"in a list. For example: `matcher.add('{key}', [doc])`")
E180 = ("Span attributes can't be declared as required or assigned by "
"components, since spans are only views of the Doc. Use Doc and "
"Token attributes (or custom extension attributes) only and remove "
@ -447,17 +423,16 @@ class Errors:
E181 = ("Received invalid attributes for unkown object {obj}: {attrs}. "
"Only Doc and Token attributes are supported.")
E182 = ("Received invalid attribute declaration: {attr}\nDid you forget "
"to define the attribute? For example: {attr}.???")
"to define the attribute? For example: `{attr}.???`")
E183 = ("Received invalid attribute declaration: {attr}\nOnly top-level "
"attributes are supported, for example: {solution}")
E184 = ("Only attributes without underscores are supported in component "
"attribute declarations (because underscore and non-underscore "
"attributes are connected anyways): {attr} -> {solution}")
E185 = ("Received invalid attribute in component attribute declaration: "
"{obj}.{attr}\nAttribute '{attr}' does not exist on {obj}.")
E186 = ("'{tok_a}' and '{tok_b}' are different texts.")
"`{obj}.{attr}`\nAttribute '{attr}' does not exist on {obj}.")
E187 = ("Only unicode strings are supported as labels.")
E189 = ("Each argument to Doc.__init__ should be of equal length.")
E189 = ("Each argument to `Doc.__init__` should be of equal length.")
E190 = ("Token head out of range in `Doc.from_array()` for token index "
"'{index}' with value '{value}' (equivalent to relative head "
"index: '{rel_head_index}'). The head indices should be relative "
@ -471,17 +446,32 @@ class Errors:
"({curr_dim}).")
E194 = ("Unable to aligned mismatched text '{text}' and words '{words}'.")
E195 = ("Matcher can be called on {good} only, got {got}.")
E196 = ("Refusing to write to token.is_sent_end. Sentence boundaries can "
"only be fixed with token.is_sent_start.")
E196 = ("Refusing to write to `token.is_sent_end`. Sentence boundaries can "
"only be fixed with `token.is_sent_start`.")
E197 = ("Row out of bounds, unable to add row {row} for key {key}.")
E198 = ("Unable to return {n} most similar vectors for the current vectors "
"table, which contains {n_rows} vectors.")
E199 = ("Unable to merge 0-length span at doc[{start}:{end}].")
E200 = ("Specifying a base model with a pretrained component '{component}' "
"can not be combined with adding a pretrained Tok2Vec layer.")
E201 = ("Span index out of range.")
E199 = ("Unable to merge 0-length span at `doc[{start}:{end}]`.")
E200 = ("Can't yet set {attr} from Span. Vote for this feature on the "
"issue tracker: http://github.com/explosion/spaCy/issues")
# TODO: fix numbering after merging develop into master
E092 = ("The sentence-per-line IOB/IOB2 file is not formatted correctly. "
"Try checking whitespace and delimiters. See "
"https://nightly.spacy.io/api/cli#convert")
E093 = ("The token-per-line NER file is not formatted correctly. Try checking "
"whitespace and delimiters. See https://nightly.spacy.io/api/cli#convert")
E904 = ("Cannot initialize StaticVectors layer: nO dimension unset. This "
"dimension refers to the output width, after the linear projection "
"has been applied.")
E905 = ("Cannot initialize StaticVectors layer: nM dimension unset. This "
"dimension refers to the width of the vectors table.")
E906 = ("Unexpected `loss` value in pretraining objective: {loss_type}")
E907 = ("Unexpected `objective_type` value in pretraining objective: {objective_type}")
E908 = ("Can't set `spaces` without `words` in `Doc.__init__`.")
E909 = ("Expected {name} in parser internals. This is likely a bug in spaCy.")
E910 = ("Encountered NaN value when computing loss for component '{name}'.")
E911 = ("Invalid feature: {feat}. Must be a token attribute.")
E912 = ("Failed to initialize lemmatizer. Missing lemmatizer table(s) found "
"for mode '{mode}'. Required tables: {tables}. Found: {found}.")
E913 = ("Corpus path can't be None. Maybe you forgot to define it in your "
@ -494,44 +484,44 @@ class Errors:
"final score, set its weight to null in the [training.score_weights] "
"section of your training config.")
E916 = ("Can't log score for '{name}' in table: not a valid score ({score_type})")
E917 = ("Received invalid value {value} for 'state_type' in "
E917 = ("Received invalid value {value} for `state_type` in "
"TransitionBasedParser: only 'parser' or 'ner' are valid options.")
E918 = ("Received invalid value for vocab: {vocab} ({vocab_type}). Valid "
"values are an instance of spacy.vocab.Vocab or True to create one"
"values are an instance of `spacy.vocab.Vocab` or True to create one"
" (default).")
E919 = ("A textcat 'positive_label' '{pos_label}' was provided for training "
E919 = ("A textcat `positive_label` '{pos_label}' was provided for training "
"data that does not appear to be a binary classification problem "
"with two labels. Labels found: {labels}")
E920 = ("The textcat's 'positive_label' setting '{pos_label}' "
E920 = ("The textcat's `positive_label` setting '{pos_label}' "
"does not match any label in the training data or provided during "
"initialization. Available labels: {labels}")
E921 = ("The method 'set_output' can only be called on components that have "
"a Model with a 'resize_output' attribute. Otherwise, the output "
E921 = ("The method `set_output` can only be called on components that have "
"a Model with a `resize_output` attribute. Otherwise, the output "
"layer can not be dynamically changed.")
E922 = ("Component '{name}' has been initialized with an output dimension of "
"{nO} - cannot add any more labels.")
E923 = ("It looks like there is no proper sample data to initialize the "
"Model of component '{name}'. "
"This is likely a bug in spaCy, so feel free to open an issue.")
"Model of component '{name}'. This is likely a bug in spaCy, so "
"feel free to open an issue: https://github.com/explosion/spaCy/issues")
E924 = ("The '{name}' component does not seem to be initialized properly. "
"This is likely a bug in spaCy, so feel free to open an issue.")
"This is likely a bug in spaCy, so feel free to open an issue: "
"https://github.com/explosion/spaCy/issues")
E925 = ("Invalid color values for displaCy visualizer: expected dictionary "
"mapping label names to colors but got: {obj}")
E926 = ("It looks like you're trying to modify nlp.{attr} directly. This "
E926 = ("It looks like you're trying to modify `nlp.{attr}` directly. This "
"doesn't work because it's an immutable computed property. If you "
"need to modify the pipeline, use the built-in methods like "
"nlp.add_pipe, nlp.remove_pipe, nlp.disable_pipe or nlp.enable_pipe "
"instead.")
"`nlp.add_pipe`, `nlp.remove_pipe`, `nlp.disable_pipe` or "
"`nlp.enable_pipe` instead.")
E927 = ("Can't write to frozen list Maybe you're trying to modify a computed "
"property or default function argument?")
E928 = ("A 'KnowledgeBase' can only be serialized to/from from a directory, "
E928 = ("A KnowledgeBase can only be serialized to/from from a directory, "
"but the provided argument {loc} points to a file.")
E929 = ("A 'KnowledgeBase' could not be read from {loc} - the path does "
"not seem to exist.")
E930 = ("Received invalid get_examples callback in {name}.initialize. "
E929 = ("Couldn't read KnowledgeBase from {loc}. The path does not seem to exist.")
E930 = ("Received invalid get_examples callback in `{name}.initialize`. "
"Expected function that returns an iterable of Example objects but "
"got: {obj}")
E931 = ("Encountered Pipe subclass without Pipe.{method} method in component "
E931 = ("Encountered Pipe subclass without `Pipe.{method}` method in component "
"'{name}'. If the component is trainable and you want to use this "
"method, make sure it's overwritten on the subclass. If your "
"component isn't trainable, add a method that does nothing or "
@ -544,21 +534,21 @@ class Errors:
"models, see the models directory: https://spacy.io/models. If you "
"want to create a blank model, use spacy.blank: "
"nlp = spacy.blank(\"{name}\")")
E942 = ("Executing after_{name} callback failed. Expected the function to "
E942 = ("Executing `after_{name}` callback failed. Expected the function to "
"return an initialized nlp object but got: {value}. Maybe "
"you forgot to return the modified object in your function?")
E943 = ("Executing before_creation callback failed. Expected the function to "
E943 = ("Executing `before_creation` callback failed. Expected the function to "
"return an uninitialized Language subclass but got: {value}. Maybe "
"you forgot to return the modified object in your function or "
"returned the initialized nlp object instead?")
E944 = ("Can't copy pipeline component '{name}' from source model '{model}': "
E944 = ("Can't copy pipeline component '{name}' from source '{model}': "
"not found in pipeline. Available components: {opts}")
E945 = ("Can't copy pipeline component '{name}' from source. Expected loaded "
"nlp object, but got: {source}")
E947 = ("Matcher.add received invalid 'greedy' argument: expected "
E947 = ("`Matcher.add` received invalid `greedy` argument: expected "
"a string value from {expected} but got: '{arg}'")
E948 = ("Matcher.add received invalid 'patterns' argument: expected "
"a List, but got: {arg_type}")
E948 = ("`Matcher.add` received invalid 'patterns' argument: expected "
"a list, but got: {arg_type}")
E949 = ("Can only create an alignment when the texts are the same.")
E952 = ("The section '{name}' is not a valid section in the provided config.")
E953 = ("Mismatched IDs received by the Tok2Vec listener: {id1} vs. {id2}")
@ -570,9 +560,9 @@ class Errors:
"for your language.")
E956 = ("Can't find component '{name}' in [components] block in the config. "
"Available components: {opts}")
E957 = ("Writing directly to Language.factories isn't needed anymore in "
"spaCy v3. Instead, you can use the @Language.factory decorator "
"to register your custom component factory or @Language.component "
E957 = ("Writing directly to `Language.factories` isn't needed anymore in "
"spaCy v3. Instead, you can use the `@Language.factory` decorator "
"to register your custom component factory or `@Language.component` "
"to register a simple stateless function component that just takes "
"a Doc and returns it.")
E958 = ("Language code defined in config ({bad_lang_code}) does not match "
@ -590,99 +580,93 @@ class Errors:
"component.\n\n{config}")
E962 = ("Received incorrect {style} for pipe '{name}'. Expected dict, "
"got: {cfg_type}.")
E963 = ("Can't read component info from @Language.{decorator} decorator. "
E963 = ("Can't read component info from `@Language.{decorator}` decorator. "
"Maybe you forgot to call it? Make sure you're using "
"@Language.{decorator}() instead of @Language.{decorator}.")
"`@Language.{decorator}()` instead of `@Language.{decorator}`.")
E964 = ("The pipeline component factory for '{name}' needs to have the "
"following named arguments, which are passed in by spaCy:\n- nlp: "
"receives the current nlp object and lets you access the vocab\n- "
"name: the name of the component instance, can be used to identify "
"the component, output losses etc.")
E965 = ("It looks like you're using the @Language.component decorator to "
E965 = ("It looks like you're using the `@Language.component` decorator to "
"register '{name}' on a class instead of a function component. If "
"you need to register a class or function that *returns* a component "
"function, use the @Language.factory decorator instead.")
E966 = ("nlp.add_pipe now takes the string name of the registered component "
"function, use the `@Language.factory` decorator instead.")
E966 = ("`nlp.add_pipe` now takes the string name of the registered component "
"factory, not a callable component. Expected string, but got "
"{component} (name: '{name}').\n\n- If you created your component "
"with nlp.create_pipe('name'): remove nlp.create_pipe and call "
"nlp.add_pipe('name') instead.\n\n- If you passed in a component "
"like TextCategorizer(): call nlp.add_pipe with the string name "
"instead, e.g. nlp.add_pipe('textcat').\n\n- If you're using a custom "
"component: Add the decorator @Language.component (for function "
"components) or @Language.factory (for class components / factories) "
"with `nlp.create_pipe('name')`: remove nlp.create_pipe and call "
"`nlp.add_pipe('name')` instead.\n\n- If you passed in a component "
"like `TextCategorizer()`: call `nlp.add_pipe` with the string name "
"instead, e.g. `nlp.add_pipe('textcat')`.\n\n- If you're using a custom "
"component: Add the decorator `@Language.component` (for function "
"components) or `@Language.factory` (for class components / factories) "
"to your custom component and assign it a name, e.g. "
"@Language.component('your_name'). You can then run "
"nlp.add_pipe('your_name') to add it to the pipeline.")
"`@Language.component('your_name')`. You can then run "
"`nlp.add_pipe('your_name')` to add it to the pipeline.")
E967 = ("No {meta} meta information found for '{name}'. This is likely a bug in spaCy.")
E968 = ("nlp.replace_pipe now takes the string name of the registered component "
E968 = ("`nlp.replace_pipe` now takes the string name of the registered component "
"factory, not a callable component. Expected string, but got "
"{component}.\n\n- If you created your component with"
"with nlp.create_pipe('name'): remove nlp.create_pipe and call "
"nlp.replace_pipe('{name}', 'name') instead.\n\n- If you passed in a "
"component like TextCategorizer(): call nlp.replace_pipe with the "
"string name instead, e.g. nlp.replace_pipe('{name}', 'textcat').\n\n"
"with `nlp.create_pipe('name')`: remove `nlp.create_pipe` and call "
"`nlp.replace_pipe('{name}', 'name')` instead.\n\n- If you passed in a "
"component like `TextCategorizer()`: call `nlp.replace_pipe` with the "
"string name instead, e.g. `nlp.replace_pipe('{name}', 'textcat')`.\n\n"
"- If you're using a custom component: Add the decorator "
"@Language.component (for function components) or @Language.factory "
"`@Language.component` (for function components) or `@Language.factory` "
"(for class components / factories) to your custom component and "
"assign it a name, e.g. @Language.component('your_name'). You can "
"then run nlp.replace_pipe('{name}', 'your_name').")
"assign it a name, e.g. `@Language.component('your_name')`. You can "
"then run `nlp.replace_pipe('{name}', 'your_name')`.")
E969 = ("Expected string values for field '{field}', but received {types} instead. ")
E970 = ("Can not execute command '{str_command}'. Do you have '{tool}' installed?")
E971 = ("Found incompatible lengths in Doc.from_array: {array_length} for the "
E971 = ("Found incompatible lengths in `Doc.from_array`: {array_length} for the "
"array and {doc_length} for the Doc itself.")
E972 = ("Example.__init__ got None for '{arg}'. Requires Doc.")
E972 = ("`Example.__init__` got None for '{arg}'. Requires Doc.")
E973 = ("Unexpected type for NER data")
E974 = ("Unknown {obj} attribute: {key}")
E976 = ("The method 'Example.from_dict' expects a {type} as {n} argument, "
E976 = ("The method `Example.from_dict` expects a {type} as {n} argument, "
"but received None.")
E977 = ("Can not compare a MorphAnalysis with a string object. "
"This is likely a bug in spaCy, so feel free to open an issue.")
"This is likely a bug in spaCy, so feel free to open an issue: "
"https://github.com/explosion/spaCy/issues")
E978 = ("The {name} method takes a list of Example objects, but got: {types}")
E979 = ("Cannot convert {type} to an Example object.")
E980 = ("Each link annotation should refer to a dictionary with at most one "
"identifier mapping to 1.0, and all others to 0.0.")
E981 = ("The offsets of the annotations for 'links' could not be aligned "
E981 = ("The offsets of the annotations for `links` could not be aligned "
"to token boundaries.")
E982 = ("The 'ent_iob' attribute of a Token should be an integer indexing "
E982 = ("The `Token.ent_iob` attribute should be an integer indexing "
"into {values}, but found {value}.")
E983 = ("Invalid key for '{dict}': {key}. Available keys: "
"{keys}")
E984 = ("Invalid component config for '{name}': component block needs either "
"a key 'factory' specifying the registered function used to "
"initialize the component, or a key 'source' key specifying a "
"spaCy model to copy the component from. For example, factory = "
"\"ner\" will use the 'ner' factory and all other settings in the "
"block will be passed to it as arguments. Alternatively, source = "
"\"en_core_web_sm\" will copy the component from that model.\n\n{config}")
E985 = ("Can't load model from config file: no 'nlp' section found.\n\n{config}")
"a key `factory` specifying the registered function used to "
"initialize the component, or a key `source` key specifying a "
"spaCy model to copy the component from. For example, `factory = "
"\"ner\"` will use the 'ner' factory and all other settings in the "
"block will be passed to it as arguments. Alternatively, `source = "
"\"en_core_web_sm\"` will copy the component from that model.\n\n{config}")
E985 = ("Can't load model from config file: no [nlp] section found.\n\n{config}")
E986 = ("Could not create any training batches: check your input. "
"Are the train and dev paths defined? "
"Is 'discard_oversize' set appropriately? ")
E987 = ("The text of an example training instance is either a Doc or "
"a string, but found {type} instead.")
E988 = ("Could not parse any training examples. Ensure the data is "
"formatted correctly.")
E989 = ("'nlp.update()' was called with two positional arguments. This "
"Are the train and dev paths defined? Is `discard_oversize` set appropriately? ")
E989 = ("`nlp.update()` was called with two positional arguments. This "
"may be due to a backwards-incompatible change to the format "
"of the training data in spaCy 3.0 onwards. The 'update' "
"function should now be called with a batch of 'Example' "
"objects, instead of (text, annotation) tuples. ")
E991 = ("The function 'select_pipes' should be called with either a "
"'disable' argument to list the names of the pipe components "
"function should now be called with a batch of Example "
"objects, instead of `(text, annotation)` tuples. ")
E991 = ("The function `nlp.select_pipes` should be called with either a "
"`disable` argument to list the names of the pipe components "
"that should be disabled, or with an 'enable' argument that "
"specifies which pipes should not be disabled.")
E992 = ("The function `select_pipes` was called with `enable`={enable} "
"and `disable`={disable} but that information is conflicting "
"for the `nlp` pipeline with components {names}.")
E993 = ("The config for 'nlp' needs to include a key 'lang' specifying "
E993 = ("The config for the nlp object needs to include a key `lang` specifying "
"the code of the language to initialize it with (for example "
"'en' for English) - this can't be 'None'.\n\n{config}")
E996 = ("Could not parse {file}: {msg}")
"'en' for English) - this can't be None.\n\n{config}")
E997 = ("Tokenizer special cases are not allowed to modify the text. "
"This would map '{chunk}' to '{orth}' given token attributes "
"'{token_attrs}'.")
E999 = ("Unable to merge the `Doc` objects because they do not all share "
E999 = ("Unable to merge the Doc objects because they do not all share "
"the same `Vocab`.")
E1000 = ("The Chinese word segmenter is pkuseg but no pkuseg model was "
"loaded. Provide the name of a pretrained model or the path to "
@ -694,35 +678,24 @@ class Errors:
E1003 = ("Unsupported lemmatizer mode '{mode}'.")
E1004 = ("Missing lemmatizer table(s) found for lemmatizer mode '{mode}'. "
"Required tables: {tables}. Found: {found}. Maybe you forgot to "
"call nlp.initialize() to load in the data?")
"call `nlp.initialize()` to load in the data?")
E1005 = ("Unable to set attribute '{attr}' in tokenizer exception for "
"'{chunk}'. Tokenizer exceptions are only allowed to specify "
"`ORTH` and `NORM`.")
E1006 = ("Unable to initialize {name} model with 0 labels.")
"ORTH and NORM.")
E1007 = ("Unsupported DependencyMatcher operator '{op}'.")
E1008 = ("Invalid pattern: each pattern should be a list of dicts. Check "
"that you are providing a list of patterns as `List[List[dict]]`.")
E1009 = ("String for hash '{val}' not found in StringStore. Set the value "
"through token.morph_ instead or add the string to the "
"StringStore with `nlp.vocab.strings.add(string)`.")
E1010 = ("Unable to set entity information for token {i} which is included "
"in more than one span in entities, blocked, missing or outside.")
E1011 = ("Unsupported default '{default}' in doc.set_ents. Available "
E1011 = ("Unsupported default '{default}' in `doc.set_ents`. Available "
"options: {modes}")
E1012 = ("Entity spans and blocked/missing/outside spans should be "
"provided to doc.set_ents as lists of `Span` objects.")
"provided to `doc.set_ents` as lists of Span objects.")
E1013 = ("Invalid morph: the MorphAnalysis must have the same vocab as the "
"token itself. To set the morph from this MorphAnalysis, set from "
"the string value with: `token.set_morph(str(other_morph))`.")
@add_codes
class TempErrors:
T003 = ("Resizing pretrained Tagger models is not currently supported.")
T007 = ("Can't yet set {attr} from Span. Vote for this feature on the "
"issue tracker: http://github.com/explosion/spaCy/issues")
# Deprecated model shortcuts, only used in errors and warnings
OLD_MODEL_SHORTCUTS = {
"en": "en_core_web_sm", "de": "de_core_news_sm", "es": "es_core_news_sm",

View File

@ -6,6 +6,7 @@ from thinc.api import expand_window, residual, Maxout, Mish, PyTorchLSTM
from ...tokens import Doc
from ...util import registry
from ...errors import Errors
from ...ml import _character_embed
from ..staticvectors import StaticVectors
from ..featureextractor import FeatureExtractor
@ -201,7 +202,7 @@ def CharacterEmbed(
"""
feature = intify_attr(feature)
if feature is None:
raise ValueError("Invalid feature: Must be a token attribute.")
raise ValueError(Errors.E911(feat=feature))
if also_use_static_vectors:
model = chain(
concatenate(

View File

@ -1,11 +1,11 @@
from typing import List, Tuple, Callable, Optional, cast
from thinc.initializers import glorot_uniform_init
from thinc.util import partial
from thinc.types import Ragged, Floats2d, Floats1d
from thinc.api import Model, Ops, registry
from ..tokens import Doc
from ..errors import Errors
@registry.layers("spacy.StaticVectors.v1")
@ -76,16 +76,9 @@ def init(
nO = Y.data.shape[1]
if nM is None:
raise ValueError(
"Cannot initialize StaticVectors layer: nM dimension unset. "
"This dimension refers to the width of the vectors table."
)
raise ValueError(Errors.E905)
if nO is None:
raise ValueError(
"Cannot initialize StaticVectors layer: nO dimension unset. "
"This dimension refers to the output width, after the linear "
"projection has been applied."
)
raise ValueError(Errors.E904)
model.set_dim("nM", nM)
model.set_dim("nO", nO)
model.set_param("W", init_W(model.ops, (nO, nM)))

View File

@ -9,10 +9,11 @@ from ...strings cimport hash_string
from ...structs cimport TokenC
from ...tokens.doc cimport Doc, set_children_from_heads
from ...training.example cimport Example
from ...errors import Errors
from .stateclass cimport StateClass
from ._state cimport StateC
from ...errors import Errors
# Calculate cost as gold/not gold. We don't use scalar value anyway.
cdef int BINARY_COSTS = 1
cdef weight_t MIN_SCORE = -90000
@ -704,7 +705,7 @@ cdef class ArcEager(TransitionSystem):
def get_cost(self, StateClass stcls, gold, int i):
if not isinstance(gold, ArcEagerGold):
raise TypeError("Expected ArcEagerGold")
raise TypeError(Errors.E909.format(name="ArcEagerGold"))
cdef ArcEagerGold gold_ = gold
gold_state = gold_.c
n_gold = 0
@ -717,7 +718,7 @@ cdef class ArcEager(TransitionSystem):
cdef int set_costs(self, int* is_valid, weight_t* costs,
StateClass stcls, gold) except -1:
if not isinstance(gold, ArcEagerGold):
raise TypeError("Expected ArcEagerGold")
raise TypeError(Errors.E909.format(name="ArcEagerGold"))
cdef ArcEagerGold gold_ = gold
gold_.update(stcls)
gold_state = gold_.c

View File

@ -1,16 +1,18 @@
from collections import Counter
from libc.stdint cimport int32_t
from cymem.cymem cimport Pool
from collections import Counter
from ...typedefs cimport weight_t, attr_t
from ...lexeme cimport Lexeme
from ...attrs cimport IS_SPACE
from ...training.example cimport Example
from ...errors import Errors
from .stateclass cimport StateClass
from ._state cimport StateC
from .transition_system cimport Transition, do_func_t
from ...errors import Errors
cdef enum:
MISSING
@ -248,7 +250,7 @@ cdef class BiluoPushDown(TransitionSystem):
def get_cost(self, StateClass stcls, gold, int i):
if not isinstance(gold, BiluoGold):
raise TypeError("Expected BiluoGold")
raise TypeError(Errors.E909.format(name="BiluoGold"))
cdef BiluoGold gold_ = gold
gold_state = gold_.c
n_gold = 0
@ -261,7 +263,7 @@ cdef class BiluoPushDown(TransitionSystem):
cdef int set_costs(self, int* is_valid, weight_t* costs,
StateClass stcls, gold) except -1:
if not isinstance(gold, BiluoGold):
raise TypeError("Expected BiluoGold")
raise TypeError(Errors.E909.format(name="BiluoGold"))
cdef BiluoGold gold_ = gold
gold_.update(stcls)
gold_state = gold_.c

View File

@ -238,7 +238,7 @@ class Morphologizer(Tagger):
truths.append(eg_truths)
d_scores, loss = loss_func(scores, truths)
if self.model.ops.xp.isnan(loss):
raise ValueError("nan value when computing loss")
raise ValueError(Errors.E910.format(name=self.name))
return float(loss), d_scores
def score(self, examples, **kwargs):

View File

@ -125,7 +125,7 @@ class SentenceRecognizer(Tagger):
truths.append(eg_truth)
d_scores, loss = loss_func(scores, truths)
if self.model.ops.xp.isnan(loss):
raise ValueError("nan value when computing loss")
raise ValueError(Errors.E910.format(name=self.name))
return float(loss), d_scores
def initialize(self, get_examples, *, nlp=None):

View File

@ -15,7 +15,7 @@ from .pipe import Pipe, deserialize_config
from ..language import Language
from ..attrs import POS, ID
from ..parts_of_speech import X
from ..errors import Errors, TempErrors, Warnings
from ..errors import Errors, Warnings
from ..scorer import Scorer
from ..training import validate_examples
from .. import util
@ -258,7 +258,7 @@ class Tagger(Pipe):
truths = [eg.get_aligned("TAG", as_string=True) for eg in examples]
d_scores, loss = loss_func(scores, truths)
if self.model.ops.xp.isnan(loss):
raise ValueError("nan value when computing loss")
raise ValueError(Errors.E910.format(name=self.name))
return float(loss), d_scores
def initialize(self, get_examples, *, nlp=None, labels=None):

View File

@ -905,7 +905,7 @@ def _auc(x, y):
if np.all(dx <= 0):
direction = -1
else:
raise ValueError(Errors.E164.format(x))
raise ValueError(Errors.E164.format(x=x))
area = direction * np.trapz(y, x)
if isinstance(area, np.memmap):

View File

@ -245,7 +245,7 @@ cdef class Doc:
self.noun_chunks_iterator = self.vocab.get_noun_chunks
cdef bint has_space
if words is None and spaces is not None:
raise ValueError("words must be set if spaces is set")
raise ValueError(Errors.E908)
elif spaces is None and words is not None:
self.has_unknown_spaces = True
else:

View File

@ -17,7 +17,7 @@ from ..lexeme cimport Lexeme
from ..symbols cimport dep
from ..util import normalize_slice
from ..errors import Errors, TempErrors, Warnings
from ..errors import Errors, Warnings
from .underscore import Underscore, get_ext_args
@ -652,7 +652,7 @@ cdef class Span:
return self.root.ent_id
def __set__(self, hash_t key):
raise NotImplementedError(TempErrors.T007.format(attr="ent_id"))
raise NotImplementedError(Errors.E200.format(attr="ent_id"))
property ent_id_:
"""RETURNS (str): The (string) entity ID."""
@ -660,7 +660,7 @@ cdef class Span:
return self.root.ent_id_
def __set__(self, hash_t key):
raise NotImplementedError(TempErrors.T007.format(attr="ent_id_"))
raise NotImplementedError(Errors.E200.format(attr="ent_id_"))
@property
def orth_(self):

View File

@ -3,7 +3,7 @@ from wasabi import Printer
from .. import tags_to_entities
from ...training import iob_to_biluo
from ...tokens import Doc, Span
from ...util import load_model
from ...errors import Errors
from ...util import load_model, get_lang_class
@ -103,11 +103,7 @@ def conll_ner_to_docs(
lines = [line.strip() for line in conll_sent.split("\n") if line.strip()]
cols = list(zip(*[line.split() for line in lines]))
if len(cols) < 2:
raise ValueError(
"The token-per-line NER file is not formatted correctly. "
"Try checking whitespace and delimiters. See "
"https://nightly.spacy.io/api/cli#convert"
)
raise ValueError(Errors.E093)
length = len(cols[0])
words.extend(cols[0])
sent_starts.extend([True] + [False] * (length - 1))

View File

@ -4,6 +4,7 @@ from .conll_ner_to_docs import n_sents_info
from ...vocab import Vocab
from ...training import iob_to_biluo, tags_to_entities
from ...tokens import Doc, Span
from ...errors import Errors
from ...util import minibatch
@ -45,9 +46,7 @@ def read_iob(raw_sents, vocab, n_sents):
sent_words, sent_iob = zip(*sent_tokens)
sent_tags = ["-"] * len(sent_words)
else:
raise ValueError(
"The sentence-per-line IOB/IOB2 file is not formatted correctly. Try checking whitespace and delimiters. See https://nightly.spacy.io/api/cli#convert"
)
raise ValueError(Errors.E092)
words.extend(sent_words)
tags.extend(sent_tags)
iob.extend(sent_iob)

View File

@ -16,6 +16,7 @@ from ..attrs import ID
from ..ml.models.multi_task import build_cloze_multi_task_model
from ..ml.models.multi_task import build_cloze_characters_multi_task_model
from ..schemas import ConfigSchemaTraining, ConfigSchemaPretrain
from ..errors import Errors
from ..util import registry, load_model_from_config, dot_to_object
@ -151,9 +152,9 @@ def create_objective(config: Config):
distance = L2Distance(normalize=True, ignore_zeros=True)
return partial(get_vectors_loss, distance=distance)
else:
raise ValueError("Unexpected loss type", config["loss"])
raise ValueError(Errors.E906.format(loss_type=config["loss"]))
else:
raise ValueError("Unexpected objective_type", objective_type)
raise ValueError(Errors.E907.format(objective_type=objective_type))
def get_vectors_loss(ops, docs, prediction, distance):