test.unit.test_network.TestBuildLoss.test_image_loss() - Code Metrics - Inspection of "Multiple loss functions" - DeepRegNet/DeepReg - Measure and Improve Code Quality continuously with Scrutinizer

Passed
Pull Request — main (#662)

by Yunguan
created 2021-02-02 21:29 UTC
TestBuildLoss.test_image_loss() A

↳ Parent: test.unit.test_network
Complexity

Conditions
Size

Total Lines	32
Code Lines	24
Duplication

Lines	0
Ratio	0 %
Importance

Changes
Metric	Value
eloc	24
dl	0
loc	32
rs	9.304
c	0
b	0
f	0
cc	4
nop	4
# coding=utf-8

"""
Tests for deepreg/_model/network/ddf_dvf.py
"""
import itertools
from copy import deepcopy
from unittest.mock import MagicMock, patch

import pytest

from deepreg.model.network import RegistrationModel
from deepreg.registry import REGISTRY

moving_image_size = (1, 3, 5)
fixed_image_size = (2, 4, 6)
index_size = 2
batch_size = 3
backbone_args = {
    "local": {"extract_levels": [1, 2]},
    "global": {"extract_levels": [1, 2]},
    "unet": {"depth": 2},
}
config = {
    "backbone": {
        "num_channel_initial": 4,
    },
    "loss": {
        "image": {"name": "lncc", "weight": 0.1},
        "label": {
            "name": "dice",
            "weight": 1,
            "scales": [0, 1],
        },
        "regularization": {"weight": 0.1, "name": "bending"},
    },
}

config_multiple_losses = deepcopy(config)
config_multiple_losses["loss"]["image"] = [
    {"name": "lncc", "weight": 0.1},
    {"name": "ssd", "weight": 0.1},
    {"name": "gmi", "weight": 0.1},
]


@pytest.fixture
def model(method: str, labeled: bool, backbone: str) -> RegistrationModel:
    """
    A specific registration model object.

    :param method: name of method
    :param labeled: whether the data is labeled
    :param backbone: name of backbone
    :return: the built object
    """
    copied = deepcopy(config)
    copied["method"] = method
    copied["backbone"]["name"] = backbone
    copied["backbone"] = {**backbone_args[backbone], **copied["backbone"]}
    return REGISTRY.build_model(
        config=dict(
            name=method,  # TODO we store method twice
            moving_image_size=moving_image_size,
            fixed_image_size=fixed_image_size,
            index_size=index_size,
            labeled=labeled,
            batch_size=batch_size,
            config=copied,
        )
    )


def pytest_generate_tests(metafunc):

    """
    Test parameter generator.

    This function is called once per each test function.
    It takes the attribute `params` from the test class,
    and then use the same `params` for all tests inside the class.
    This is specific for test of registration models only.

    This is modified from the pytest documentation,
    where their version defined the params for each test function separately.

    https://docs.pytest.org/en/stable/example/parametrize.html#parametrizing-test-methods-through-per-class-configuration

    :param metafunc:
    :return:
    """
    #
    funcarglist = metafunc.cls.params
    argnames = sorted(funcarglist[0])
    metafunc.parametrize(
        argnames, [[funcargs[name] for name in argnames] for funcargs in funcarglist]
    )


class TestRegistrationModel:

    params = [dict(labeled=True), dict(labeled=False)]

    @pytest.fixture
    def empty_model(self, labeled: bool) -> RegistrationModel:
        """
        A RegistrationModel with build_model and build_loss mocked/overwritten.

        :param labeled: whether the data is labeled
        :return: the mocked object
        """
        with patch.multiple(
            RegistrationModel,
            build_model=MagicMock(return_value=None),
            build_loss=MagicMock(return_value=None),
        ):
            return RegistrationModel(
                moving_image_size=moving_image_size,
                fixed_image_size=fixed_image_size,
                index_size=index_size,
                labeled=labeled,
                batch_size=batch_size,
                config=dict(),
            )

    def test_get_config(self, empty_model, labeled):

        got = empty_model.get_config()
        assert got == dict(
            moving_image_size=moving_image_size,
            fixed_image_size=fixed_image_size,
            index_size=index_size,
            labeled=labeled,
            batch_size=batch_size,
            config=dict(),
            num_devices=1,
            name="RegistrationModel",
        )

    def test_build_inputs(self, empty_model, labeled):

        inputs = empty_model.build_inputs()
        expected_inputs_len = 5 if labeled else 3
        assert len(inputs) == expected_inputs_len

        moving_image = inputs["moving_image"]
        fixed_image = inputs["fixed_image"]
        indices = inputs["indices"]
        assert moving_image.shape == (batch_size, *moving_image_size)
        assert fixed_image.shape == (batch_size, *fixed_image_size)
        assert indices.shape == (batch_size, index_size)

        if labeled:
            moving_label = inputs["moving_label"]
            fixed_label = inputs["fixed_label"]
            assert moving_label.shape == (batch_size, *moving_image_size)
            assert fixed_label.shape == (batch_size, *fixed_image_size)

    def test_concat_images(self, empty_model, labeled):

        inputs = empty_model.build_inputs()
        moving_image = inputs["moving_image"]
        fixed_image = inputs["fixed_image"]
        if labeled:
            moving_label = inputs["moving_label"]
            images = empty_model.concat_images(moving_image, fixed_image, moving_label)
            assert images.shape == (batch_size, *fixed_image_size, 3)
        else:
            images = empty_model.concat_images(moving_image, fixed_image)
            assert images.shape == (batch_size, *fixed_image_size, 2)


class TestBuildLoss:

    params = [
        dict(config=config, option=0, expected=2),
        dict(config=config, option=1, expected=2),
        dict(config=config, option=2, expected=3),
        dict(config=config_multiple_losses, option=3, expected=5),
    ]

    def test_image_loss(self, config: dict, option: int, expected: int):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        method = "ddf"
        backbone = "local"
        labeled = True
        copied = deepcopy(config)
        copied["method"] = method
        copied["backbone"]["name"] = backbone
        copied["backbone"] = {**backbone_args[backbone], **copied["backbone"]}

        if option == 0:
            # remove image loss config, so loss is not used
            copied["loss"].pop("image")
        elif option == 1:
            # set image loss weight to zero, so loss is not used
            copied["loss"]["image"]["weight"] = 0.0
        elif option == 2:
            # remove image loss weight, so loss is used with default weight 1
            copied["loss"]["image"].pop("weight")

        ddf_model = REGISTRY.build_model(
            config=dict(
                name=method,  # TODO we store method twice
                moving_image_size=moving_image_size,
                fixed_image_size=fixed_image_size,
                index_size=index_size,
                labeled=labeled,
                batch_size=batch_size,
                config=copied,
            )
        )

        assert len(ddf_model._model.losses) == expected
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent


class TestDDFModel:

    params = [
        dict(method=method, labeled=labeled, backbone=backbone)
        for method, labeled, backbone in itertools.product(
            ["ddf"], [True, False], ["local", "global", "unet"]
        )
    ]

    def test_build_model(self, model, labeled, backbone):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        expected_outputs_len = 3 if labeled else 2
        if backbone == "global":
            expected_outputs_len += 1
            theta = model._outputs["theta"]
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
            assert theta.shape == (batch_size, 4, 3)
        assert len(model._outputs) == expected_outputs_len
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent

        ddf = model._outputs["ddf"]
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        pred_fixed_image = model._outputs["pred_fixed_image"]
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        assert ddf.shape == (batch_size, *fixed_image_size, 3)
        assert pred_fixed_image.shape == (batch_size, *fixed_image_size)

        if labeled:
            pred_fixed_label = model._outputs["pred_fixed_label"]
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
            assert pred_fixed_label.shape == (batch_size, *fixed_image_size)

    def test_build_loss(self, model, labeled, backbone):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        expected = 3 if labeled else 2
        assert len(model._model.losses) == expected
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent

    def test_postprocess(self, model, labeled, backbone):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        indices, processed = model.postprocess(
            inputs=model._inputs, outputs=model._outputs
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        )
        assert indices.shape == (batch_size, index_size)
        expected = 7 if labeled else 4
        if backbone == "global":
            expected += 1
        assert len(processed) == expected


class TestDVFModel:

    params = [
        dict(method=method, labeled=labeled, backbone=backbone)
        for method, labeled, backbone in itertools.product(
            ["dvf"], [True, False], ["local", "unet"]
        )
    ]

    def test_build_model(self, model, labeled, backbone):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        expected_outputs_len = 4 if labeled else 3
        assert len(model._outputs) == expected_outputs_len
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent

        dvf = model._outputs["dvf"]
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        ddf = model._outputs["ddf"]
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        pred_fixed_image = model._outputs["pred_fixed_image"]
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        assert dvf.shape == (batch_size, *fixed_image_size, 3)
        assert ddf.shape == (batch_size, *fixed_image_size, 3)
        assert pred_fixed_image.shape == (batch_size, *fixed_image_size)

        if labeled:
            pred_fixed_label = model._outputs["pred_fixed_label"]
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
            assert pred_fixed_label.shape == (batch_size, *fixed_image_size)

    def test_build_loss(self, model, labeled, backbone):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        expected = 3 if labeled else 2
        assert len(model._model.losses) == expected
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent

    def test_postprocess(self, model, labeled, backbone):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        indices, processed = model.postprocess(
            inputs=model._inputs, outputs=model._outputs
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        )
        assert indices.shape == (batch_size, index_size)
        expected = 8 if labeled else 5
        assert len(processed) == expected


class TestConditionalModel:

    params = [
        dict(method=method, labeled=labeled, backbone=backbone)
        for method, labeled, backbone in itertools.product(
            ["conditional"], [True], ["local", "unet"]
        )
    ]

    def test_build_model(self, model, labeled, backbone):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        assert len(model._outputs) == 1
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        pred_fixed_label = model._outputs["pred_fixed_label"]
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        assert pred_fixed_label.shape == (batch_size, *fixed_image_size)

    def test_build_loss(self, model, labeled, backbone):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        assert len(model._model.losses) == 1
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent

    def test_postprocess(self, model, labeled, backbone):
param = 5

class Foo:
    def __init__(self, param):   # "param" would be flagged here
        self.param = param
        indices, processed = model.postprocess(
            inputs=model._inputs, outputs=model._outputs
class MyParent:
    def __init__(self):
        self._x = 1;
        self.y = 2;

class MyChild(MyParent):
    def some_method(self):
        return self._x    # Ok, since accessed from a child class

class AnotherClass:
    def some_method(self, instance_of_my_child):
        return instance_of_my_child._x   # Would be flagged as AnotherClass is not
                                         # a child class of MyParent
        )
        assert indices.shape == (batch_size, index_size)
        assert len(processed) == 5

1			# coding=utf-8
2
3			"""
4			Tests for deepreg/_model/network/ddf_dvf.py
5			"""
6			import itertools
7			from copy import deepcopy
8			from unittest.mock import MagicMock, patch
9
10			import pytest
11
12			from deepreg.model.network import RegistrationModel
13			from deepreg.registry import REGISTRY
14
15			moving_image_size = (1, 3, 5)
16			fixed_image_size = (2, 4, 6)
17			index_size = 2
18			batch_size = 3
19			backbone_args = {
20			"local": {"extract_levels": [1, 2]},
21			"global": {"extract_levels": [1, 2]},
22			"unet": {"depth": 2},
23			}
24			config = {
25			"backbone": {
26			"num_channel_initial": 4,
27			},
28			"loss": {
29			"image": {"name": "lncc", "weight": 0.1},
30			"label": {
31			"name": "dice",
32			"weight": 1,
33			"scales": [0, 1],
34			},
35			"regularization": {"weight": 0.1, "name": "bending"},
36			},
37			}
38
39			config_multiple_losses = deepcopy(config)
40			config_multiple_losses["loss"]["image"] = [
DeepRegNet / DeepReg

Pull Request — main (#662)

TestBuildLoss.test_image_loss() A

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