spaCy/spacy/tests/test_misc.py

# coding: utf-8
from __future__ import unicode_literals

import pytest
from pathlib import Path
from spacy import util
from spacy import displacy
from spacy.tokens import Span
from spacy._ml import PrecomputableAffine

from .util import get_doc


@pytest.mark.parametrize("text", ["hello/world", "hello world"])
def test_util_ensure_path_succeeds(text):
    path = util.ensure_path(text)
    assert isinstance(path, Path)


@pytest.mark.parametrize("package", ["numpy"])
def test_util_is_package(package):
    """Test that an installed package via pip is recognised by util.is_package."""
    assert util.is_package(package)


@pytest.mark.parametrize("package", ["thinc"])
def test_util_get_package_path(package):
    """Test that a Path object is returned for a package name."""
    path = util.get_package_path(package)
    assert isinstance(path, Path)


def test_displacy_parse_ents(en_vocab):
    """Test that named entities on a Doc are converted into displaCy's format."""
    doc = get_doc(en_vocab, words=["But", "Google", "is", "starting", "from", "behind"])
    doc.ents = [Span(doc, 1, 2, label=doc.vocab.strings["ORG"])]
    ents = displacy.parse_ents(doc)
    assert isinstance(ents, dict)
    assert ents["text"] == "But Google is starting from behind "
    assert ents["ents"] == [{"start": 4, "end": 10, "label": "ORG"}]


def test_displacy_parse_deps(en_vocab):
    """Test that deps and tags on a Doc are converted into displaCy's format."""
    words = ["This", "is", "a", "sentence"]
    heads = [1, 0, 1, -2]
    pos = ["DET", "VERB", "DET", "NOUN"]
    tags = ["DT", "VBZ", "DT", "NN"]
    deps = ["nsubj", "ROOT", "det", "attr"]
    doc = get_doc(en_vocab, words=words, heads=heads, pos=pos, tags=tags, deps=deps)
    deps = displacy.parse_deps(doc)
    assert isinstance(deps, dict)
    assert deps["words"] == [
        {"text": "This", "tag": "DET"},
        {"text": "is", "tag": "VERB"},
        {"text": "a", "tag": "DET"},
        {"text": "sentence", "tag": "NOUN"},
    ]
    assert deps["arcs"] == [
        {"start": 0, "end": 1, "label": "nsubj", "dir": "left"},
        {"start": 2, "end": 3, "label": "det", "dir": "left"},
        {"start": 1, "end": 3, "label": "attr", "dir": "right"},
    ]


def test_displacy_spans(en_vocab):
    """Test that displaCy can render Spans."""
    doc = get_doc(en_vocab, words=["But", "Google", "is", "starting", "from", "behind"])
    doc.ents = [Span(doc, 1, 2, label=doc.vocab.strings["ORG"])]
    html = displacy.render(doc[1:4], style="ent")
    assert html.startswith("<div")


def test_displacy_raises_for_wrong_type(en_vocab):
    with pytest.raises(ValueError):
        html = displacy.render("hello world")


def test_PrecomputableAffine(nO=4, nI=5, nF=3, nP=2):
    model = PrecomputableAffine(nO=nO, nI=nI, nF=nF, nP=nP)
    assert model.W.shape == (nF, nO, nP, nI)
    tensor = model.ops.allocate((10, nI))
    Y, get_dX = model.begin_update(tensor)
    assert Y.shape == (tensor.shape[0] + 1, nF, nO, nP)
    assert model.d_pad.shape == (1, nF, nO, nP)
    dY = model.ops.allocate((15, nO, nP))
    ids = model.ops.allocate((15, nF))
    ids[1, 2] = -1
    dY[1] = 1
    assert model.d_pad[0, 2, 0, 0] == 0.0
    model._backprop_padding(dY, ids)
    assert model.d_pad[0, 2, 0, 0] == 1.0
    model.d_pad.fill(0.0)
    ids.fill(0.0)
    dY.fill(0.0)
    ids[1, 2] = -1
    ids[1, 1] = -1
    ids[1, 0] = -1
    dY[1] = 1
    assert model.d_pad[0, 2, 0, 0] == 0.0
    model._backprop_padding(dY, ids)
    assert model.d_pad[0, 2, 0, 0] == 3.0