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'parser' instead of 'deps' for state_type

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svlandeg 2020-09-23 16:53:49 +02:00
parent 6c85fab316
commit dd2292793f
5 changed files with 8 additions and 8 deletions
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4
spacy/cli/templates/quickstart_training.jinja
View File

@ -59,7 +59,7 @@ factory = "parser"
[components.parser.model]
@architectures = "spacy.TransitionBasedParser.v1"
state_type = "deps"
state_type = "parser"
extra_state_tokens = false
hidden_width = 128
maxout_pieces = 3
@ -185,7 +185,7 @@ factory = "parser"
[components.parser.model]
@architectures = "spacy.TransitionBasedParser.v1"
state_type = "deps"
state_type = "parser"
extra_state_tokens = false
hidden_width = 128
maxout_pieces = 3

4
spacy/ml/models/parser.py
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@ -42,7 +42,7 @@ def build_tb_parser_model(
tok2vec (Model[List[Doc], List[Floats2d]]):
Subnetwork to map tokens into vector representations.
state_type (str):
String value denoting the type of parser model: "deps" or "ner"
String value denoting the type of parser model: "parser" or "ner"
extra_state_tokens (bool): Whether or not to use additional tokens in the context
to construct the state vector. Defaults to `False`, which means 3 and 8
for the NER and parser respectively. When set to `True`, this would become 6
@ -61,7 +61,7 @@ def build_tb_parser_model(
Usually inferred from data at the beginning of training, or loaded from
disk.
"""
if state_type == "deps":
if state_type == "parser":
nr_feature_tokens = 13 if extra_state_tokens else 8
elif state_type == "ner":
nr_feature_tokens = 6 if extra_state_tokens else 3

2
spacy/pipeline/dep_parser.pyx
View File

@ -15,7 +15,7 @@ from ..training import validate_examples
default_model_config = """
[model]
@architectures = "spacy.TransitionBasedParser.v1"
state_type = "deps"
state_type = "parser"
extra_state_tokens = false
hidden_width = 64
maxout_pieces = 2

4
spacy/tests/serialize/test_serialize_config.py
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@ -67,7 +67,7 @@ width = ${components.tok2vec.model.width}
parser_config_string = """
[model]
@architectures = "spacy.TransitionBasedParser.v1"
state_type = "deps"
state_type = "parser"
extra_state_tokens = false
hidden_width = 66
maxout_pieces = 2
@ -97,7 +97,7 @@ def my_parser():
)
parser = build_tb_parser_model(
tok2vec=tok2vec,
state_type="deps",
state_type="parser",
extra_state_tokens=True,
hidden_width=65,
maxout_pieces=5,

2
website/docs/api/architectures.md
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@ -450,7 +450,7 @@ consists of either two or three subnetworks:
| Name | Description |
| -------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `tok2vec` | Subnetwork to map tokens into vector representations. ~~Model[List[Doc], List[Floats2d]]~~ |
| `state_type` | Which task to extract features for. Possible values are "ner" and "dependencies". ~~str~~ |
| `state_type` | Which task to extract features for. Possible values are "ner" and "parser". ~~str~~ |
| `extra_state_tokens` | Whether to use an expanded feature set when extracting the state tokens. Slightly slower, but sometimes improves accuracy slightly. Defaults to `False`. ~~bool~~ |
| `hidden_width` | The width of the hidden layer. ~~int~~ |
| `maxout_pieces` | How many pieces to use in the state prediction layer. Recommended values are `1`, `2` or `3`. If `1`, the maxout non-linearity is replaced with a [`Relu`](https://thinc.ai/docs/api-layers#relu) non-linearity if `use_upper` is `True`, and no non-linearity if `False`. ~~int~~ |