示例#1
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    def testCreatingLinks(self):
        l = HTMLevel(0, {"size": [1], "nodeCloning": True}, previous_level_size=[1])
        prev_size = [8, 8]
        correct_links = {0: range(np.prod(prev_size))}

        links = l._get_links([1, 1], prev_size)

        self.assertEqual(links, correct_links)
示例#2
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    def testCreatingLinks(self):
        l = HTMLevel(0, {
            'size': [1],
            'nodeCloning': True
        },
                     previous_level_size=[1])
        prev_size = [8, 8]
        correct_links = {0: range(np.prod(prev_size))}

        links = l._get_links([1, 1], prev_size)

        self.assertEqual(links, correct_links)
示例#3
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    def runTest(self):
        params = {"transitionMemory": 4, "requestedGroupsCount": 3}
        l = HTMLevel(0, {"size": [1], "nodeCloning": True}, previous_level_size=[1])

        for p in patterns:
            l.do_spatial_learning([p])

        for p in patterns:
            l.do_temporal_learning([p])

        desired_TAM = np.array([[2.0, 4.0, 3.0, 5.0], [3.0, 0.0, 4.0, 2.0], [4.0, 0.0, 0.0, 3.0], [0.0, 0.0, 0.0, 0.0]])
        self.assertEqual(np.array_equal(l.nodes[0].tp.TAM, desired_TAM), True)

        l.finalize_learning()
        self.assertEqual(len(l.nodes[0].tp.temporal_groups), params["requestedGroupsCount"])

        # testing creating nodes using params
        params = {
            "nodeCloning": True,
            "size": [8, 8],
            "overlap": [0, 0],
            # Spatial pooler
            "maxCoincidenceCount": 128,
            "spatialPoolerAlgorithm": "gaussian",
            "sigma": 1,
            "maxDistance": 0.1,
            # Temporal pooler
            "requestedGroupsCount": 20,
            "temporalPoolerAlgorithm": "maxProp",
            "transitionMemory": 4,
        }
        l = HTMLevel(1, params, previous_level_size=[1])
        self.assertEqual(len(l.nodes), 1)
示例#4
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    def runTest(self):
        params = {'transitionMemory': 4, 'requestedGroupsCount': 3}
        l = HTMLevel(0, {
            'size': [1],
            'nodeCloning': True
        },
                     previous_level_size=[1])

        for p in patterns:
            l.do_spatial_learning([p])

        for p in patterns:
            l.do_temporal_learning([p])

        desired_TAM = np.array([[2., 4., 3., 5.], [3., 0., 4., 2.],
                                [4., 0., 0., 3.], [0., 0., 0., 0.]])
        self.assertEqual(np.array_equal(l.nodes[0].tp.TAM, desired_TAM), True)

        l.finalize_learning()
        self.assertEqual(len(l.nodes[0].tp.temporal_groups),
                         params['requestedGroupsCount'])

        # testing creating nodes using params
        params = {
            'nodeCloning': True,
            'size': [8, 8],
            'overlap': [0, 0],

            # Spatial pooler
            'maxCoincidenceCount': 128,
            'spatialPoolerAlgorithm': 'gaussian',
            'sigma': 1,
            'maxDistance': 0.1,

            # Temporal pooler
            'requestedGroupsCount': 20,
            'temporalPoolerAlgorithm': 'maxProp',
            'transitionMemory': 4,
        }
        l = HTMLevel(1, params, previous_level_size=[1])
        self.assertEqual(len(l.nodes), 1)
示例#5
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    def create_network(self, params):
        """Create network based on the provided parameters.

        Args:
            params: list of dicts sorted starting from the bottom level
        """
        if params is None:
            raise ValueError("Parameter 'params' should not be empty.")

        if self.verbose: print("Creating network...")

        for level_no in range(len(params)):

            if level_no == 0:
                # assuming rectangular arrangement of nodes
                if self.is_image_sensor:
                    self.patch_size = [
                        int(self.sensor.width / params[0]['size'][0]),
                        int(self.sensor.height / params[0]['size'][1])
                    ]
                    if self.verbose:
                        print("Patch size is set to %s." % self.patch_size)
                prev_level_size = params[0]['size']
            else:
                prev_level_size = params[level_no - 1]['size']

            level = HTMLevel(level_no,
                             params=params[level_no],
                             debug=self.debug,
                             previous_level_size=prev_level_size)
            self.add_level(level)

        for level_no in range(len(self.levels) - 1):
            self.levels[level_no].above_links = self.levels[level_no + 1].links

        if self.verbose: print("=" * 40)