Prompt:
Implement the Python class `EntitiesMerger` described below.

Class description:
A stateless functor in charge of detecting and merging entities that already exist on the database before flushing the session.

Method signatures and docstrings:
- def __call__(self, session: Session, entities: Iterable[Entity], existing_entities: Optional[EntityMapping]=None) -> List[Entity]: Merge a set of entities with their existing representations and update the parent/child relationships and return a list containing ``[*updated_entities, *new_entities]``.
- def _merge(self, session: Session, entities: Iterable[Entity], new_entities: EntityMapping, existing_entities: EntityMapping) -> List[Entity]: (Recursive) inner implementation of the entity merge logic.
- def _sync_parent(cls, session: Session, entity: Entity, new_entities: EntityMapping, existing_entities: EntityMapping) -> Entity: Recursively refresh the parent of an entity all the way up in the hierarchy, to make sure that all the parent/child relations are appropriately rewired and that all the relevant objects are added to this session.
- def _append_children(entity: Entity, *children: Entity): Update the list of children of a given entity with the given list of entities. Note that, in case of ``entity_key`` conflict (the key of a new entity already exists in the entity's children), the most recent version will be used, so any column merge logic needs to happen before this method is called.
- def _merge_columns(cls, entity: Entity, existing_entity: Entity, include_children: bool=False) -> Entity: Merge two versions of an entity column by column.

Implement the Python class `EntitiesMerger` described below.

Class description:
A stateless functor in charge of detecting and merging entities that already exist on the database before flushing the session.

Method signatures and docstrings:
- def __call__(self, session: Session, entities: Iterable[Entity], existing_entities: Optional[EntityMapping]=None) -> List[Entity]: Merge a set of entities with their existing representations and update the parent/child relationships and return a list containing ``[*updated_entities, *new_entities]``.
- def _merge(self, session: Session, entities: Iterable[Entity], new_entities: EntityMapping, existing_entities: EntityMapping) -> List[Entity]: (Recursive) inner implementation of the entity merge logic.
- def _sync_parent(cls, session: Session, entity: Entity, new_entities: EntityMapping, existing_entities: EntityMapping) -> Entity: Recursively refresh the parent of an entity all the way up in the hierarchy, to make sure that all the parent/child relations are appropriately rewired and that all the relevant objects are added to this session.
- def _append_children(entity: Entity, *children: Entity): Update the list of children of a given entity with the given list of entities. Note that, in case of ``entity_key`` conflict (the key of a new entity already exists in the entity's children), the most recent version will be used, so any column merge logic needs to happen before this method is called.
- def _merge_columns(cls, entity: Entity, existing_entity: Entity, include_children: bool=False) -> Entity: Merge two versions of an entity column by column.

<|skeleton|>
class EntitiesMerger:
    """A stateless functor in charge of detecting and merging entities that already exist on the database before flushing the session."""

    def __call__(self, session: Session, entities: Iterable[Entity], existing_entities: Optional[EntityMapping]=None) -> List[Entity]:
        """Merge a set of entities with their existing representations and update the parent/child relationships and return a list containing ``[*updated_entities, *new_entities]``."""
        <|body_0|>

    def _merge(self, session: Session, entities: Iterable[Entity], new_entities: EntityMapping, existing_entities: EntityMapping) -> List[Entity]:
        """(Recursive) inner implementation of the entity merge logic."""
        <|body_1|>

    def _sync_parent(cls, session: Session, entity: Entity, new_entities: EntityMapping, existing_entities: EntityMapping) -> Entity:
        """Recursively refresh the parent of an entity all the way up in the hierarchy, to make sure that all the parent/child relations are appropriately rewired and that all the relevant objects are added to this session."""
        <|body_2|>

    def _append_children(entity: Entity, *children: Entity):
        """Update the list of children of a given entity with the given list of entities. Note that, in case of ``entity_key`` conflict (the key of a new entity already exists in the entity's children), the most recent version will be used, so any column merge logic needs to happen before this method is called."""
        <|body_3|>

    def _merge_columns(cls, entity: Entity, existing_entity: Entity, include_children: bool=False) -> Entity:
        """Merge two versions of an entity column by column."""
        <|body_4|>

<|end_skeleton|>

<|body_start_0|>
        existing_entities = existing_entities or {}
        new_entities: EntityMapping = {}
        self._merge(session, entities, new_entities=new_entities, existing_entities=existing_entities)
        return list({**existing_entities, **new_entities}.values())
<|end_body_0|>

<|body_start_1|>
        processed_entities = []
        for entity in entities:
            key = entity.entity_key
            existing_entity = existing_entities.get(key, new_entities.get(key))
            entity = self._sync_parent(session, entity, new_entities, existing_entities)
            if existing_entity:
                existing_entity = self._merge_columns(entity, existing_entity)
                self._append_children(existing_entity, *self._merge(session, entity.children, new_entities, existing_entities))
                entity = existing_entity
            else:
                new_entities[key] = entity
            processed_entities.append(entity)
        return processed_entities
<|end_body_1|>

<|body_start_2|>
        parent = get_parent(session, entity)
        if not parent:
            return entity
        existing_parent = existing_entities.get(parent.entity_key, new_entities.get(parent.entity_key))
        if not existing_parent:
            return entity
        existing_entity = next(iter((child for child in existing_parent.children if child.entity_key == entity.entity_key)), None)
        if not existing_entity:
            entity.parent = None
        else:
            entity = cls._merge_columns(entity, existing_entity, include_children=True)
        cls._append_children(existing_parent, entity)
        cls._sync_parent(session, existing_parent, new_entities, existing_entities)
        return entity
<|end_body_2|>

<|body_start_3|>
        entity.children = list({**{e.entity_key: e for e in entity.children}, **{e.entity_key: e for e in children}}.values())
        for child in children:
            child.parent = entity
            if entity.id:
                child.parent_id = entity.id
<|end_body_3|>

<|body_start_4|>
        columns = [col.key for col in entity.get_columns()]
        for col in columns:
            if col == 'meta':
                existing_entity.meta = {**(existing_entity.meta or {}), **(entity.meta or {})}
            elif col not in ('id', 'created_at'):
                try:
                    setattr(existing_entity, col, getattr(entity, col))
                except ObjectDeletedError as e:
                    logger.warning('Could not set %s on entity <%s>: %s', col, existing_entity.entity_key, e)
        if include_children:
            existing_children = {e.entity_key: e for e in existing_entity.children}
            new_children = {e.entity_key: e for e in entity.children}
            updated_children = {}
            for key, child in new_children.items():
                existing_child = existing_children.get(key)
                updated_children[key] = cls._merge_columns(child, existing_child, include_children=True) if existing_child else child
            cls._append_children(existing_entity, *updated_children.values())
        return existing_entity
<|end_body_4|>

Solution:
class EntitiesMerger:
    """A stateless functor in charge of detecting and merging entities that already exist on the database before flushing the session."""

    def __call__(self, session: Session, entities: Iterable[Entity], existing_entities: Optional[EntityMapping]=None) -> List[Entity]:
        """Merge a set of entities with their existing representations and update the parent/child relationships and return a list containing ``[*updated_entities, *new_entities]``."""
        existing_entities = existing_entities or {}
        new_entities: EntityMapping = {}
        self._merge(session, entities, new_entities=new_entities, existing_entities=existing_entities)
        return list({**existing_entities, **new_entities}.values())

    def _merge(self, session: Session, entities: Iterable[Entity], new_entities: EntityMapping, existing_entities: EntityMapping) -> List[Entity]:
        """(Recursive) inner implementation of the entity merge logic."""
        processed_entities = []
        for entity in entities:
            key = entity.entity_key
            existing_entity = existing_entities.get(key, new_entities.get(key))
            entity = self._sync_parent(session, entity, new_entities, existing_entities)
            if existing_entity:
                existing_entity = self._merge_columns(entity, existing_entity)
                self._append_children(existing_entity, *self._merge(session, entity.children, new_entities, existing_entities))
                entity = existing_entity
            else:
                new_entities[key] = entity
            processed_entities.append(entity)
        return processed_entities

    def _sync_parent(cls, session: Session, entity: Entity, new_entities: EntityMapping, existing_entities: EntityMapping) -> Entity:
        """Recursively refresh the parent of an entity all the way up in the hierarchy, to make sure that all the parent/child relations are appropriately rewired and that all the relevant objects are added to this session."""
        parent = get_parent(session, entity)
        if not parent:
            return entity
        existing_parent = existing_entities.get(parent.entity_key, new_entities.get(parent.entity_key))
        if not existing_parent:
            return entity
        existing_entity = next(iter((child for child in existing_parent.children if child.entity_key == entity.entity_key)), None)
        if not existing_entity:
            entity.parent = None
        else:
            entity = cls._merge_columns(entity, existing_entity, include_children=True)
        cls._append_children(existing_parent, entity)
        cls._sync_parent(session, existing_parent, new_entities, existing_entities)
        return entity

    def _append_children(entity: Entity, *children: Entity):
        """Update the list of children of a given entity with the given list of entities. Note that, in case of ``entity_key`` conflict (the key of a new entity already exists in the entity's children), the most recent version will be used, so any column merge logic needs to happen before this method is called."""
        entity.children = list({**{e.entity_key: e for e in entity.children}, **{e.entity_key: e for e in children}}.values())
        for child in children:
            child.parent = entity
            if entity.id:
                child.parent_id = entity.id

    def _merge_columns(cls, entity: Entity, existing_entity: Entity, include_children: bool=False) -> Entity:
        """Merge two versions of an entity column by column."""
        columns = [col.key for col in entity.get_columns()]
        for col in columns:
            if col == 'meta':
                existing_entity.meta = {**(existing_entity.meta or {}), **(entity.meta or {})}
            elif col not in ('id', 'created_at'):
                try:
                    setattr(existing_entity, col, getattr(entity, col))
                except ObjectDeletedError as e:
                    logger.warning('Could not set %s on entity <%s>: %s', col, existing_entity.entity_key, e)
        if include_children:
            existing_children = {e.entity_key: e for e in existing_entity.children}
            new_children = {e.entity_key: e for e in entity.children}
            updated_children = {}
            for key, child in new_children.items():
                existing_child = existing_children.get(key)
                updated_children[key] = cls._merge_columns(child, existing_child, include_children=True) if existing_child else child
            cls._append_children(existing_entity, *updated_children.values())
        return existing_entity


Prompt:
Implement the Python class `TestPQ3` described below.

Class description:
Implement the TestPQ3 class.

Method signatures and docstrings:
- def test_setup(self): Test to ensure lists are set up correctly for the problem.
- def test_find_min_cuts(self): Test to ensure min cut returns correct value.

Implement the Python class `TestPQ3` described below.

Class description:
Implement the TestPQ3 class.

Method signatures and docstrings:
- def test_setup(self): Test to ensure lists are set up correctly for the problem.
- def test_find_min_cuts(self): Test to ensure min cut returns correct value.

<|skeleton|>
class TestPQ3:

    def test_setup(self):
        """Test to ensure lists are set up correctly for the problem."""
        <|body_0|>

    def test_find_min_cuts(self):
        """Test to ensure min cut returns correct value."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        result = pq.setup()
        vertices = result[0]
        node_edges = result[1]
        self.assertEqual(vertices[-1], 200, 'The vertices list has not imported correctly.')
        expected = [149, 155, 52, 87, 120, 39, 160, 137, 27, 79, 131, 100, 25, 55, 23, 126, 84, 166, 150, 62, 67, 1, 69, 35]
        self.assertEqual(node_edges[200], expected)
<|end_body_0|>

<|body_start_1|>
        vertices = [1, 2, 3, 4]
        node_edges = defaultdict(list)
        node_edges = {1: [2, 3], 2: [1, 3, 4], 3: [1, 2, 4], 4: [2, 3]}
        expected = 2
        got = pq.find_min_cuts(vertices, node_edges)
        self.assertEqual(expected, got, 'Min cut is not correct on length {} test'.format(len(vertices)))
        vertices = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
        node_edges = {1: [2, 3, 4, 5], 2: [1, 3, 4, 5], 3: [1, 2, 4, 5, 6], 4: [1, 2, 3, 5, 7], 5: [1, 2, 3, 4], 6: [7, 8, 9, 10, 3], 7: [6, 8, 9, 10, 4], 8: [6, 7, 9, 10], 9: [6, 7, 8, 10], 10: [6, 7, 8, 9]}
        expected = 2
        got = pq.find_min_cuts(vertices, node_edges)
        self.assertEqual(expected, got, 'Min cut is not correct on length {} test'.format(len(vertices)))
        vertices = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
        node_edges = {1: [2, 3, 4, 5], 2: [1, 3, 4, 5], 3: [1, 2, 4, 5, 6], 4: [1, 2, 3, 5, 7, 14], 5: [1, 2, 3, 4], 6: [7, 8, 9, 10, 3], 7: [6, 8, 9, 10, 4], 8: [6, 7, 9, 10], 9: [6, 7, 8, 10], 10: [6, 7, 8, 9], 11: [12, 13, 14, 15], 12: [11, 13, 14, 15], 13: [12, 11, 14, 15], 14: [12, 13, 11, 15, 4], 15: [12, 13, 14, 11]}
        expected = 1
        got = pq.find_min_cuts(vertices, node_edges)
        self.assertEqual(expected, got, 'Min cut is not correct on length {} test'.format(len(vertices)))
<|end_body_1|>

Solution:
class TestPQ3:
    def test_setup(self):
        """Test to ensure lists are set up correctly for the problem."""
        result = pq.setup()
        vertices = result[0]
        node_edges = result[1]
        self.assertEqual(vertices[-1], 200, 'The vertices list has not imported correctly.')
        expected = [149, 155, 52, 87, 120, 39, 160, 137, 27, 79, 131, 100, 25, 55, 23, 126, 84, 166, 150, 62, 67, 1, 69, 35]
        self.assertEqual(node_edges[200], expected)

    def test_find_min_cuts(self):
        """Test to ensure min cut returns correct value."""
        vertices = [1, 2, 3, 4]
        node_edges = defaultdict(list)
        node_edges = {1: [2, 3], 2: [1, 3, 4], 3: [1, 2, 4], 4: [2, 3]}
        expected = 2
        got = pq.find_min_cuts(vertices, node_edges)
        self.assertEqual(expected, got, 'Min cut is not correct on length {} test'.format(len(vertices)))
        vertices = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
        node_edges = {1: [2, 3, 4, 5], 2: [1, 3, 4, 5], 3: [1, 2, 4, 5, 6], 4: [1, 2, 3, 5, 7], 5: [1, 2, 3, 4], 6: [7, 8, 9, 10, 3], 7: [6, 8, 9, 10, 4], 8: [6, 7, 9, 10], 9: [6, 7, 8, 10], 10: [6, 7, 8, 9]}
        expected = 2
        got = pq.find_min_cuts(vertices, node_edges)
        self.assertEqual(expected, got, 'Min cut is not correct on length {} test'.format(len(vertices)))
        vertices = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
        node_edges = {1: [2, 3, 4, 5], 2: [1, 3, 4, 5], 3: [1, 2, 4, 5, 6], 4: [1, 2, 3, 5, 7, 14], 5: [1, 2, 3, 4], 6: [7, 8, 9, 10, 3], 7: [6, 8, 9, 10, 4], 8: [6, 7, 9, 10], 9: [6, 7, 8, 10], 10: [6, 7, 8, 9], 11: [12, 13, 14, 15], 12: [11, 13, 14, 15], 13: [12, 11, 14, 15], 14: [12, 13, 11, 15, 4], 15: [12, 13, 14, 11]}
        expected = 1
        got = pq.find_min_cuts(vertices, node_edges)
        self.assertEqual(expected, got, 'Min cut is not correct on length {} test'.format(len(vertices)))


Prompt:
Implement the Python class `Config` described below.

Class description:
Implement the Config class.

Method signatures and docstrings:
- def load_config(cls, config_path=None): Loads Walkoff configuration from JSON file Args: config_path (str): Optional path to the config. Defaults to the CONFIG_PATH class variable.
- def write_values_to_file(cls, keys=None): Writes the current walkoff configuration to a file

Implement the Python class `Config` described below.

Class description:
Implement the Config class.

Method signatures and docstrings:
- def load_config(cls, config_path=None): Loads Walkoff configuration from JSON file Args: config_path (str): Optional path to the config. Defaults to the CONFIG_PATH class variable.
- def write_values_to_file(cls, keys=None): Writes the current walkoff configuration to a file

<|skeleton|>
class Config:

    def load_config(cls, config_path=None):
        """Loads Walkoff configuration from JSON file Args: config_path (str): Optional path to the config. Defaults to the CONFIG_PATH class variable."""
        <|body_0|>

    def write_values_to_file(cls, keys=None):
        """Writes the current walkoff configuration to a file"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if config_path:
            cls.CONFIG_PATH = config_path
        if cls.CONFIG_PATH:
            try:
                if isfile(cls.CONFIG_PATH):
                    with open(cls.CONFIG_PATH) as config_file:
                        config = json.loads(config_file.read())
                        for key, value in config.items():
                            if value:
                                setattr(cls, key.upper(), value)
                else:
                    logger.warning('Config path {} is not a file.'.format(cls.CONFIG_PATH))
            except (IOError, OSError, ValueError):
                logger.warning('Could not read config file.', exc_info=True)
        cls.SQLALCHEMY_DATABASE_URI = format_db_path(cls.WALKOFF_DB_TYPE, cls.DB_PATH, 'WALKOFF_DB_USERNAME', 'WALKOFF_DB_PASSWORD')
<|end_body_0|>

<|body_start_1|>
        if keys is None:
            keys = [key for key in dir(cls) if not key.startswith('__')]
        output = {}
        for key in keys:
            if hasattr(cls, key.upper()):
                output[key.lower()] = getattr(cls, key.upper())
        with open(cls.CONFIG_PATH, 'w') as config_file:
            config_file.write(json.dumps(output, sort_keys=True, indent=4, separators=(',', ': ')))
<|end_body_1|>

Solution:
class Config:
    def load_config(cls, config_path=None):
        """Loads Walkoff configuration from JSON file Args: config_path (str): Optional path to the config. Defaults to the CONFIG_PATH class variable."""
        if config_path:
            cls.CONFIG_PATH = config_path
        if cls.CONFIG_PATH:
            try:
                if isfile(cls.CONFIG_PATH):
                    with open(cls.CONFIG_PATH) as config_file:
                        config = json.loads(config_file.read())
                        for key, value in config.items():
                            if value:
                                setattr(cls, key.upper(), value)
                else:
                    logger.warning('Config path {} is not a file.'.format(cls.CONFIG_PATH))
            except (IOError, OSError, ValueError):
                logger.warning('Could not read config file.', exc_info=True)
        cls.SQLALCHEMY_DATABASE_URI = format_db_path(cls.WALKOFF_DB_TYPE, cls.DB_PATH, 'WALKOFF_DB_USERNAME', 'WALKOFF_DB_PASSWORD')

    def write_values_to_file(cls, keys=None):
        """Writes the current walkoff configuration to a file"""
        if keys is None:
            keys = [key for key in dir(cls) if not key.startswith('__')]
        output = {}
        for key in keys:
            if hasattr(cls, key.upper()):
                output[key.lower()] = getattr(cls, key.upper())
        with open(cls.CONFIG_PATH, 'w') as config_file:
            config_file.write(json.dumps(output, sort_keys=True, indent=4, separators=(',', ': ')))


Prompt:
Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def copyRandomList_two_pass(self, head): :type head: RandomListNode :rtype: RandomListNode
- def copyRandomList_on_dict(self, head): :type head: RandomListNode :rtype: RandomListNode

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def copyRandomList_two_pass(self, head): :type head: RandomListNode :rtype: RandomListNode
- def copyRandomList_on_dict(self, head): :type head: RandomListNode :rtype: RandomListNode

<|skeleton|>
class Solution:

    def copyRandomList_two_pass(self, head):
        """:type head: RandomListNode :rtype: RandomListNode"""
        <|body_0|>

    def copyRandomList_on_dict(self, head):
        """:type head: RandomListNode :rtype: RandomListNode"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        dic = {}
        m, n = (head, head)
        while m:
            dic[m] = RandomListNode(m.label)
            m = m.next
        while n:
            dic[n].next = dic.get(n.next, None)
            dic[n].random = dic.get(n.random, None)
            n = n.next
        return dic.get(head, None)
<|end_body_0|>

<|body_start_1|>
        if not head:
            return None
        p = head
        while p:
            node = RandomListNode(p.label)
            node.next = p.next
            p.next = node
            p = p.next.next
        p = head
        while p:
            if p.random:
                p.next.random = p.random.next
            p = p.next.next
        newhead = head.next
        pold = head
        pnew = newhead
        while pnew.next:
            pold.next = pnew.next
            pold = pold.next
            pnew.next = pold.next
            pnew = pnew.next
        pold.next = None
        pnew.next = None
        return newhead
<|end_body_1|>

Solution:
class Solution:
    def copyRandomList_two_pass(self, head):
        """:type head: RandomListNode :rtype: RandomListNode"""
        dic = {}
        m, n = (head, head)
        while m:
            dic[m] = RandomListNode(m.label)
            m = m.next
        while n:
            dic[n].next = dic.get(n.next, None)
            dic[n].random = dic.get(n.random, None)
            n = n.next
        return dic.get(head, None)

    def copyRandomList_on_dict(self, head):
        """:type head: RandomListNode :rtype: RandomListNode"""
        if not head:
            return None
        p = head
        while p:
            node = RandomListNode(p.label)
            node.next = p.next
            p.next = node
            p = p.next.next
        p = head
        while p:
            if p.random:
                p.next.random = p.random.next
            p = p.next.next
        newhead = head.next
        pold = head
        pnew = newhead
        while pnew.next:
            pold.next = pnew.next
            pold = pold.next
            pnew.next = pold.next
            pnew = pnew.next
        pold.next = None
        pnew.next = None
        return newhead


handleButtons

Prompt:
Implement the Python class `MyApp` described below.

Class description:
MyApp implements a custom notify handler to log errors, when C++ classes and python wrapper in PyQt5 environment mismatch. mostly this relates to the situation when a C++ object is already deleted, but the python wrapper still exists. so far I know that's the only chance to log this issues. in addition it writes mouse pressed and key pressed events in debug level to log including event and object name to be analyse the input methods.

Method signatures and docstrings:
- def handleButtons(self, obj, returnValue): :param obj: :param returnValue: :return:
- def notify(self, obj, event): :param obj: :param event: :return:

Implement the Python class `MyApp` described below.

Class description:
MyApp implements a custom notify handler to log errors, when C++ classes and python wrapper in PyQt5 environment mismatch. mostly this relates to the situation when a C++ object is already deleted, but the python wrapper still exists. so far I know that's the only chance to log this issues. in addition it writes mouse pressed and key pressed events in debug level to log including event and object name to be analyse the input methods.

Method signatures and docstrings:
- def handleButtons(self, obj, returnValue): :param obj: :param returnValue: :return:
- def notify(self, obj, event): :param obj: :param event: :return:

<|skeleton|>
class MyApp:
    """MyApp implements a custom notify handler to log errors, when C++ classes and python wrapper in PyQt5 environment mismatch. mostly this relates to the situation when a C++ object is already deleted, but the python wrapper still exists. so far I know that's the only chance to log this issues. in addition it writes mouse pressed and key pressed events in debug level to log including event and object name to be analyse the input methods."""

    def handleButtons(self, obj, returnValue):
        """:param obj: :param returnValue: :return:"""
        <|body_0|>

    def notify(self, obj, event):
        """:param obj: :param event: :return:"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if obj.objectName() == 'MainWindowWindow':
            return returnValue
        if obj == self.last:
            return returnValue
        else:
            self.last = obj
        if isinstance(obj, PyQt5.QtWidgets.QTabBar):
            self.log.warning(f'Click Tab     : [{obj.tabText(obj.currentIndex())}]')
        elif isinstance(obj, PyQt5.QtWidgets.QComboBox):
            self.log.warning(f'Click DropDown: [{obj.objectName()}]')
        elif isinstance(obj, PyQt5.QtWidgets.QPushButton):
            self.log.warning(f'Click Button  : [{obj.objectName()}]')
        elif isinstance(obj, PyQt5.QtWidgets.QRadioButton):
            self.log.warning(f'Click Radio   : [{obj.objectName()}]:{obj.isChecked()}')
        elif isinstance(obj, PyQt5.QtWidgets.QGroupBox):
            self.log.warning(f'Click Group   : [{obj.objectName()}]:{obj.isChecked()}')
        elif isinstance(obj, PyQt5.QtWidgets.QCheckBox):
            self.log.warning(f'Click Checkbox: [{obj.objectName()}]:{obj.isChecked()}')
        elif isinstance(obj, PyQt5.QtWidgets.QLineEdit):
            self.log.warning(f'Click EditLine: [{obj.objectName()}]:{obj.text()}')
        else:
            self.log.warning(f'Click Object  : [{obj.objectName()}]')
        return returnValue
<|end_body_0|>

<|body_start_1|>
        try:
            returnValue = PyQt5.QtWidgets.QApplication.notify(self, obj, event)
        except Exception as e:
            self.log.critical('----------------------------------------------------')
            self.log.critical('Event: {0}'.format(event))
            self.log.critical('EventType: {0}'.format(event.type()))
            self.log.critical('Exception error in event loop: {0}'.format(e))
            self.log.critical('----------------------------------------------------')
            returnValue = False
        if not isinstance(event, PyQt5.QtGui.QMouseEvent):
            return returnValue
        if not event.button():
            return returnValue
        returnValue = self.handleButtons(obj, returnValue)
        return returnValue
<|end_body_1|>

Solution:
class MyApp:
    """MyApp implements a custom notify handler to log errors, when C++ classes and python wrapper in PyQt5 environment mismatch. mostly this relates to the situation when a C++ object is already deleted, but the python wrapper still exists. so far I know that's the only chance to log this issues. in addition it writes mouse pressed and key pressed events in debug level to log including event and object name to be analyse the input methods."""

    def handleButtons(self, obj, returnValue):
        """:param obj: :param returnValue: :return:"""
        if obj.objectName() == 'MainWindowWindow':
            return returnValue
        if obj == self.last:
            return returnValue
        else:
            self.last = obj
        if isinstance(obj, PyQt5.QtWidgets.QTabBar):
            self.log.warning(f'Click Tab     : [{obj.tabText(obj.currentIndex())}]')
        elif isinstance(obj, PyQt5.QtWidgets.QComboBox):
            self.log.warning(f'Click DropDown: [{obj.objectName()}]')
        elif isinstance(obj, PyQt5.QtWidgets.QPushButton):
            self.log.warning(f'Click Button  : [{obj.objectName()}]')
        elif isinstance(obj, PyQt5.QtWidgets.QRadioButton):
            self.log.warning(f'Click Radio   : [{obj.objectName()}]:{obj.isChecked()}')
        elif isinstance(obj, PyQt5.QtWidgets.QGroupBox):
            self.log.warning(f'Click Group   : [{obj.objectName()}]:{obj.isChecked()}')
        elif isinstance(obj, PyQt5.QtWidgets.QCheckBox):
            self.log.warning(f'Click Checkbox: [{obj.objectName()}]:{obj.isChecked()}')
        elif isinstance(obj, PyQt5.QtWidgets.QLineEdit):
            self.log.warning(f'Click EditLine: [{obj.objectName()}]:{obj.text()}')
        else:
            self.log.warning(f'Click Object  : [{obj.objectName()}]')
        return returnValue

    def notify(self, obj, event):
        """:param obj: :param event: :return:"""
        try:
            returnValue = PyQt5.QtWidgets.QApplication.notify(self, obj, event)
        except Exception as e:
            self.log.critical('----------------------------------------------------')
            self.log.critical('Event: {0}'.format(event))
            self.log.critical('EventType: {0}'.format(event.type()))
            self.log.critical('Exception error in event loop: {0}'.format(e))
            self.log.critical('----------------------------------------------------')
            returnValue = False
        if not isinstance(event, PyQt5.QtGui.QMouseEvent):
            return returnValue
        if not event.button():
            return returnValue
        returnValue = self.handleButtons(obj, returnValue)
        return returnValue


Prompt:
Implement the Python class `CustomerManager` described below.

Class description:
Customer model manager where contact_number is the unique identifier for authentication instead of usernames.

Method signatures and docstrings:
- def create_user(self, name, date_of_birth, contact_number, password, **extra_fields): Create and save an user with the given contact number and password.
- def create_superuser(self, name, date_of_birth, contact_number, password, **extra_fields): Create and save a superuser with the given email and password.

Implement the Python class `CustomerManager` described below.

Class description:
Customer model manager where contact_number is the unique identifier for authentication instead of usernames.

Method signatures and docstrings:
- def create_user(self, name, date_of_birth, contact_number, password, **extra_fields): Create and save an user with the given contact number and password.
- def create_superuser(self, name, date_of_birth, contact_number, password, **extra_fields): Create and save a superuser with the given email and password.

<|skeleton|>
class CustomerManager:
    """Customer model manager where contact_number is the unique identifier for authentication instead of usernames."""

    def create_user(self, name, date_of_birth, contact_number, password, **extra_fields):
        """Create and save an user with the given contact number and password."""
        <|body_0|>

    def create_superuser(self, name, date_of_birth, contact_number, password, **extra_fields):
        """Create and save a superuser with the given email and password."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        errors = {}
        if not name:
            errors['name'] = _('Name must be set')
        if not date_of_birth:
            errors['date_of_birth'] = _('Date of Birth must be set')
        if not contact_number:
            errors['contact_number'] = _('Contact number must be set')
        if not password:
            errors['password'] = _('Password must be set')
        if errors:
            raise ValidationError(errors)
        validate_date_of_birth(date_of_birth)
        validate_contact_number(contact_number)
        user = self.model(name=name, date_of_birth=date_of_birth, contact_number=contact_number, **extra_fields)
        user.set_password(password)
        user.save()
        return user
<|end_body_0|>

<|body_start_1|>
        extra_fields.setdefault('is_staff', True)
        extra_fields.setdefault('is_superuser', True)
        return self.create_user(name, date_of_birth, contact_number, password, **extra_fields)
<|end_body_1|>

Solution:
class CustomerManager:
    """Customer model manager where contact_number is the unique identifier for authentication instead of usernames."""

    def create_user(self, name, date_of_birth, contact_number, password, **extra_fields):
        """Create and save an user with the given contact number and password."""
        errors = {}
        if not name:
            errors['name'] = _('Name must be set')
        if not date_of_birth:
            errors['date_of_birth'] = _('Date of Birth must be set')
        if not contact_number:
            errors['contact_number'] = _('Contact number must be set')
        if not password:
            errors['password'] = _('Password must be set')
        if errors:
            raise ValidationError(errors)
        validate_date_of_birth(date_of_birth)
        validate_contact_number(contact_number)
        user = self.model(name=name, date_of_birth=date_of_birth, contact_number=contact_number, **extra_fields)
        user.set_password(password)
        user.save()
        return user

    def create_superuser(self, name, date_of_birth, contact_number, password, **extra_fields):
        """Create and save a superuser with the given email and password."""
        extra_fields.setdefault('is_staff', True)
        extra_fields.setdefault('is_superuser', True)
        return self.create_user(name, date_of_birth, contact_number, password, **extra_fields)


getChanges

Prompt:
Implement the Python class `GitLabHandler` described below.

Class description:
Implement the GitLabHandler class.

Method signatures and docstrings:
- def _process_change(self, payload, user, repo, repo_url, project, event, codebase=None): Consumes the JSON as a python object and actually starts the build. :arguments: payload Python Object that represents the JSON sent by GitLab Service Hook.
- def _process_merge_request_change(self, payload, project, event, codebase=None): Consumes the merge_request JSON as a python object and turn it into a buildbot change. :arguments: payload Python Object that represents the JSON sent by GitLab Service Hook.
- def getChanges(self, request): Reponds only to POST events and starts the build process :arguments: request the http request object

Implement the Python class `GitLabHandler` described below.

Class description:
Implement the GitLabHandler class.

Method signatures and docstrings:
- def _process_change(self, payload, user, repo, repo_url, project, event, codebase=None): Consumes the JSON as a python object and actually starts the build. :arguments: payload Python Object that represents the JSON sent by GitLab Service Hook.
- def _process_merge_request_change(self, payload, project, event, codebase=None): Consumes the merge_request JSON as a python object and turn it into a buildbot change. :arguments: payload Python Object that represents the JSON sent by GitLab Service Hook.
- def getChanges(self, request): Reponds only to POST events and starts the build process :arguments: request the http request object

<|skeleton|>
class GitLabHandler:

    def _process_change(self, payload, user, repo, repo_url, project, event, codebase=None):
        """Consumes the JSON as a python object and actually starts the build. :arguments: payload Python Object that represents the JSON sent by GitLab Service Hook."""
        <|body_0|>

    def _process_merge_request_change(self, payload, project, event, codebase=None):
        """Consumes the merge_request JSON as a python object and turn it into a buildbot change. :arguments: payload Python Object that represents the JSON sent by GitLab Service Hook."""
        <|body_1|>

    def getChanges(self, request):
        """Reponds only to POST events and starts the build process :arguments: request the http request object"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        changes = []
        refname = payload['ref']
        match = re.match('^refs/(heads|tags)/(.+)$', refname)
        if not match:
            log.msg("Ignoring refname `%s': Not a branch" % refname)
            return changes
        branch = match.group(2)
        if payload.get('deleted'):
            log.msg("Branch `%s' deleted, ignoring" % branch)
            return changes
        for commit in payload['commits']:
            if not commit.get('distinct', True):
                log.msg('Commit `%s` is a non-distinct commit, ignoring...' % (commit['id'],))
                continue
            files = []
            for kind in ('added', 'modified', 'removed'):
                files.extend(commit.get(kind, []))
            when_timestamp = dateparse(commit['timestamp'])
            log.msg('New revision: %s' % commit['id'][:8])
            change = {'author': '%s <%s>' % (commit['author']['name'], commit['author']['email']), 'files': files, 'comments': commit['message'], 'revision': commit['id'], 'when_timestamp': when_timestamp, 'branch': branch, 'revlink': commit['url'], 'repository': repo_url, 'project': project, 'category': event, 'properties': {'event': event}}
            if codebase is not None:
                change['codebase'] = codebase
            changes.append(change)
        return changes
<|end_body_0|>

<|body_start_1|>
        attrs = payload['object_attributes']
        commit = attrs['last_commit']
        when_timestamp = dateparse(commit['timestamp'])
        repo_url = attrs['source']['git_http_url']
        changes = [{'author': '%s <%s>' % (commit['author']['name'], commit['author']['email']), 'files': [], 'comments': 'MR#{}: {}\n\n{}'.format(attrs['iid'], attrs['title'], attrs['description']), 'revision': commit['id'], 'when_timestamp': when_timestamp, 'branch': attrs['source_branch'], 'repository': repo_url, 'project': project, 'category': event, 'revlink': attrs['url'], 'properties': {'target_branch': attrs['target_branch'], 'target_repository': attrs['target']['git_http_url'], 'event': event}}]
        if codebase is not None:
            changes[0]['codebase'] = codebase
        return changes
<|end_body_1|>

<|body_start_2|>
        expected_secret = isinstance(self.options, dict) and self.options.get('secret')
        if expected_secret:
            received_secret = request.getHeader(_HEADER_GITLAB_TOKEN)
            if received_secret != expected_secret:
                raise ValueError('Invalid secret')
        try:
            payload = json.load(request.content)
        except Exception as e:
            raise ValueError('Error loading JSON: ' + str(e))
        event_type = request.getHeader(_HEADER_EVENT)
        event_type = bytes2NativeString(event_type)
        event_type = payload.get('object_kind', event_type)
        project = request.args.get('project', [''])[0]
        codebase = request.args.get('codebase', [None])[0]
        if event_type in ('push', 'tag_push', 'Push Hook'):
            user = payload['user_name']
            repo = payload['repository']['name']
            repo_url = payload['repository']['url']
            changes = self._process_change(payload, user, repo, repo_url, project, event_type, codebase=codebase)
        elif event_type == 'merge_request':
            changes = self._process_merge_request_change(payload, project, event_type, codebase=codebase)
        else:
            changes = []
        if changes:
            log.msg('Received {} changes from {} gitlab event'.format(len(changes), event_type))
        return (changes, 'git')
<|end_body_2|>

Solution:
class GitLabHandler:
    def _process_change(self, payload, user, repo, repo_url, project, event, codebase=None):
        """Consumes the JSON as a python object and actually starts the build. :arguments: payload Python Object that represents the JSON sent by GitLab Service Hook."""
        changes = []
        refname = payload['ref']
        match = re.match('^refs/(heads|tags)/(.+)$', refname)
        if not match:
            log.msg("Ignoring refname `%s': Not a branch" % refname)
            return changes
        branch = match.group(2)
        if payload.get('deleted'):
            log.msg("Branch `%s' deleted, ignoring" % branch)
            return changes
        for commit in payload['commits']:
            if not commit.get('distinct', True):
                log.msg('Commit `%s` is a non-distinct commit, ignoring...' % (commit['id'],))
                continue
            files = []
            for kind in ('added', 'modified', 'removed'):
                files.extend(commit.get(kind, []))
            when_timestamp = dateparse(commit['timestamp'])
            log.msg('New revision: %s' % commit['id'][:8])
            change = {'author': '%s <%s>' % (commit['author']['name'], commit['author']['email']), 'files': files, 'comments': commit['message'], 'revision': commit['id'], 'when_timestamp': when_timestamp, 'branch': branch, 'revlink': commit['url'], 'repository': repo_url, 'project': project, 'category': event, 'properties': {'event': event}}
            if codebase is not None:
                change['codebase'] = codebase
            changes.append(change)
        return changes

    def _process_merge_request_change(self, payload, project, event, codebase=None):
        """Consumes the merge_request JSON as a python object and turn it into a buildbot change. :arguments: payload Python Object that represents the JSON sent by GitLab Service Hook."""
        attrs = payload['object_attributes']
        commit = attrs['last_commit']
        when_timestamp = dateparse(commit['timestamp'])
        repo_url = attrs['source']['git_http_url']
        changes = [{'author': '%s <%s>' % (commit['author']['name'], commit['author']['email']), 'files': [], 'comments': 'MR#{}: {}\n\n{}'.format(attrs['iid'], attrs['title'], attrs['description']), 'revision': commit['id'], 'when_timestamp': when_timestamp, 'branch': attrs['source_branch'], 'repository': repo_url, 'project': project, 'category': event, 'revlink': attrs['url'], 'properties': {'target_branch': attrs['target_branch'], 'target_repository': attrs['target']['git_http_url'], 'event': event}}]
        if codebase is not None:
            changes[0]['codebase'] = codebase
        return changes

    def getChanges(self, request):
        """Reponds only to POST events and starts the build process :arguments: request the http request object"""
        expected_secret = isinstance(self.options, dict) and self.options.get('secret')
        if expected_secret:
            received_secret = request.getHeader(_HEADER_GITLAB_TOKEN)
            if received_secret != expected_secret:
                raise ValueError('Invalid secret')
        try:
            payload = json.load(request.content)
        except Exception as e:
            raise ValueError('Error loading JSON: ' + str(e))
        event_type = request.getHeader(_HEADER_EVENT)
        event_type = bytes2NativeString(event_type)
        event_type = payload.get('object_kind', event_type)
        project = request.args.get('project', [''])[0]
        codebase = request.args.get('codebase', [None])[0]
        if event_type in ('push', 'tag_push', 'Push Hook'):
            user = payload['user_name']
            repo = payload['repository']['name']
            repo_url = payload['repository']['url']
            changes = self._process_change(payload, user, repo, repo_url, project, event_type, codebase=codebase)
        elif event_type == 'merge_request':
            changes = self._process_merge_request_change(payload, project, event_type, codebase=codebase)
        else:
            changes = []
        if changes:
            log.msg('Received {} changes from {} gitlab event'.format(len(changes), event_type))
        return (changes, 'git')


call

Prompt:
Implement the Python class `MoeModel` described below.

Class description:
A softmax over a mixture of logistic models (with L2 regularization).

Method signatures and docstrings:
- def __init__(self, vocab_size: int=3862, num_mixtures: int=2, use_input_context_gate: bool=False, use_output_context_gate: bool=False, normalizer_params: Optional[dict[str, Any]]=None, vocab_as_last_dim: bool=False, l2_regularizer: Optional[tf.keras.regularizers.Regularizer]=None, **kwargs): Creates a Mixture of (Logistic) Experts model. The model consists of a per-class softmax distribution over a configurable number of logistic classifiers. One of the classifiers in the mixture is not trained, and always predicts 0. Args: vocab_size: The number of classes in the dataset. num_mixtures: The number of mixtures (excluding a dummy 'expert' that always predicts the non-existence of an entity). use_input_context_gate: if True apply context gate layer to the input. use_output_context_gate: if True apply context gate layer to the output. normalizer_params: parameters of the batch normalization. vocab_as_last_dim: if True reshape `activations` and make `vocab_size` as the last dimension
- def call(self, inputs: tf.Tensor) -> dict[str, tf.Tensor]: MoE forward call. Args: inputs: 'batch_size' x 'num_features' matrix of input features. Returns: A dictionary with a tensor containing the probability predictions of the model in the 'predictions' key. The dimensions of the tensor are batch_size x num_classes.

Implement the Python class `MoeModel` described below.

Class description:
A softmax over a mixture of logistic models (with L2 regularization).

Method signatures and docstrings:
- def __init__(self, vocab_size: int=3862, num_mixtures: int=2, use_input_context_gate: bool=False, use_output_context_gate: bool=False, normalizer_params: Optional[dict[str, Any]]=None, vocab_as_last_dim: bool=False, l2_regularizer: Optional[tf.keras.regularizers.Regularizer]=None, **kwargs): Creates a Mixture of (Logistic) Experts model. The model consists of a per-class softmax distribution over a configurable number of logistic classifiers. One of the classifiers in the mixture is not trained, and always predicts 0. Args: vocab_size: The number of classes in the dataset. num_mixtures: The number of mixtures (excluding a dummy 'expert' that always predicts the non-existence of an entity). use_input_context_gate: if True apply context gate layer to the input. use_output_context_gate: if True apply context gate layer to the output. normalizer_params: parameters of the batch normalization. vocab_as_last_dim: if True reshape `activations` and make `vocab_size` as the last dimension
- def call(self, inputs: tf.Tensor) -> dict[str, tf.Tensor]: MoE forward call. Args: inputs: 'batch_size' x 'num_features' matrix of input features. Returns: A dictionary with a tensor containing the probability predictions of the model in the 'predictions' key. The dimensions of the tensor are batch_size x num_classes.

<|skeleton|>
class MoeModel:
    """A softmax over a mixture of logistic models (with L2 regularization)."""

    def __init__(self, vocab_size: int=3862, num_mixtures: int=2, use_input_context_gate: bool=False, use_output_context_gate: bool=False, normalizer_params: Optional[dict[str, Any]]=None, vocab_as_last_dim: bool=False, l2_regularizer: Optional[tf.keras.regularizers.Regularizer]=None, **kwargs):
        """Creates a Mixture of (Logistic) Experts model. The model consists of a per-class softmax distribution over a configurable number of logistic classifiers. One of the classifiers in the mixture is not trained, and always predicts 0. Args: vocab_size: The number of classes in the dataset. num_mixtures: The number of mixtures (excluding a dummy 'expert' that always predicts the non-existence of an entity). use_input_context_gate: if True apply context gate layer to the input. use_output_context_gate: if True apply context gate layer to the output. normalizer_params: parameters of the batch normalization. vocab_as_last_dim: if True reshape `activations` and make `vocab_size` as the last dimension"""
        <|body_0|>

    def call(self, inputs: tf.Tensor) -> dict[str, tf.Tensor]:
        """MoE forward call. Args: inputs: 'batch_size' x 'num_features' matrix of input features. Returns: A dictionary with a tensor containing the probability predictions of the model in the 'predictions' key. The dimensions of the tensor are batch_size x num_classes."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        super().__init__(**kwargs)
        self._vocab_size = vocab_size
        self._num_mixtures = num_mixtures
        self._use_input_context_gate = use_input_context_gate
        self._use_output_context_gate = use_output_context_gate
        self._vocab_as_last_dim = vocab_as_last_dim
        self._normalizer_params = normalizer_params
        self._l2_regularizer = l2_regularizer
        if use_input_context_gate:
            self._input_context_gate = nn_layers.ContextGate(normalizer_fn=layers.BatchNormalization, normalizer_params=normalizer_params, name='input_context_gate')
        if use_output_context_gate:
            self._output_context_gate = nn_layers.ContextGate(normalizer_fn=layers.BatchNormalization, normalizer_params=normalizer_params, name='output_context_gate')
        self._gate_dense = layers.Dense(vocab_size * (num_mixtures + 1), activation=None, bias_initializer=None, kernel_regularizer=l2_regularizer, name='gate')
        self._expert_dense = layers.Dense(vocab_size * num_mixtures, activation=None, kernel_regularizer=l2_regularizer, name='expert')
<|end_body_0|>

<|body_start_1|>
        if self._use_input_context_gate:
            inputs = self._input_context_gate(inputs)
        gate_activations = self._gate_dense(inputs)
        expert_activations = self._expert_dense(inputs)
        if self._vocab_as_last_dim:
            gate_activations = tf.reshape(gate_activations, [-1, self._num_mixtures + 1, self._vocab_size])
            expert_activations = tf.reshape(expert_activations, [-1, self._num_mixtures, self._vocab_size])
        else:
            gate_activations = tf.reshape(gate_activations, [-1, self._num_mixtures + 1])
            expert_activations = tf.reshape(expert_activations, [-1, self._num_mixtures])
        gating_distribution = tf.nn.softmax(gate_activations, axis=1)
        expert_distribution = tf.nn.sigmoid(expert_activations)
        final_probabilities = tf.reduce_sum(gating_distribution[:, :self._num_mixtures] * expert_distribution, axis=1)
        if not self._vocab_as_last_dim:
            final_probabilities = tf.reshape(final_probabilities, [-1, self._vocab_size])
        return {'predictions': final_probabilities}
<|end_body_1|>

Solution:
class MoeModel:
    """A softmax over a mixture of logistic models (with L2 regularization)."""

    def __init__(self, vocab_size: int=3862, num_mixtures: int=2, use_input_context_gate: bool=False, use_output_context_gate: bool=False, normalizer_params: Optional[dict[str, Any]]=None, vocab_as_last_dim: bool=False, l2_regularizer: Optional[tf.keras.regularizers.Regularizer]=None, **kwargs):
        """Creates a Mixture of (Logistic) Experts model. The model consists of a per-class softmax distribution over a configurable number of logistic classifiers. One of the classifiers in the mixture is not trained, and always predicts 0. Args: vocab_size: The number of classes in the dataset. num_mixtures: The number of mixtures (excluding a dummy 'expert' that always predicts the non-existence of an entity). use_input_context_gate: if True apply context gate layer to the input. use_output_context_gate: if True apply context gate layer to the output. normalizer_params: parameters of the batch normalization. vocab_as_last_dim: if True reshape `activations` and make `vocab_size` as the last dimension"""
        super().__init__(**kwargs)
        self._vocab_size = vocab_size
        self._num_mixtures = num_mixtures
        self._use_input_context_gate = use_input_context_gate
        self._use_output_context_gate = use_output_context_gate
        self._vocab_as_last_dim = vocab_as_last_dim
        self._normalizer_params = normalizer_params
        self._l2_regularizer = l2_regularizer
        if use_input_context_gate:
            self._input_context_gate = nn_layers.ContextGate(normalizer_fn=layers.BatchNormalization, normalizer_params=normalizer_params, name='input_context_gate')
        if use_output_context_gate:
            self._output_context_gate = nn_layers.ContextGate(normalizer_fn=layers.BatchNormalization, normalizer_params=normalizer_params, name='output_context_gate')
        self._gate_dense = layers.Dense(vocab_size * (num_mixtures + 1), activation=None, bias_initializer=None, kernel_regularizer=l2_regularizer, name='gate')
        self._expert_dense = layers.Dense(vocab_size * num_mixtures, activation=None, kernel_regularizer=l2_regularizer, name='expert')

    def call(self, inputs: tf.Tensor) -> dict[str, tf.Tensor]:
        """MoE forward call. Args: inputs: 'batch_size' x 'num_features' matrix of input features. Returns: A dictionary with a tensor containing the probability predictions of the model in the 'predictions' key. The dimensions of the tensor are batch_size x num_classes."""
        if self._use_input_context_gate:
            inputs = self._input_context_gate(inputs)
        gate_activations = self._gate_dense(inputs)
        expert_activations = self._expert_dense(inputs)
        if self._vocab_as_last_dim:
            gate_activations = tf.reshape(gate_activations, [-1, self._num_mixtures + 1, self._vocab_size])
            expert_activations = tf.reshape(expert_activations, [-1, self._num_mixtures, self._vocab_size])
        else:
            gate_activations = tf.reshape(gate_activations, [-1, self._num_mixtures + 1])
            expert_activations = tf.reshape(expert_activations, [-1, self._num_mixtures])
        gating_distribution = tf.nn.softmax(gate_activations, axis=1)
        expert_distribution = tf.nn.sigmoid(expert_activations)
        final_probabilities = tf.reduce_sum(gating_distribution[:, :self._num_mixtures] * expert_distribution, axis=1)
        if not self._vocab_as_last_dim:
            final_probabilities = tf.reshape(final_probabilities, [-1, self._vocab_size])
        return {'predictions': final_probabilities}


PromoteDocument

Prompt:
Implement the Python class `Database` described below.

Class description:
Database Abstraction Layer

Method signatures and docstrings:
- def GetDocument(document_id: str) -> Document: Fetch a specific document
- def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]: Fetch a specific document set
- def PutDocument(document: Document) -> Document: Update a specific document
- def PromoteDocument(currentStage: Stage, nextStage: Stage): Promote documents in SUCCESS state from current stage to next stage WAITING state

Implement the Python class `Database` described below.

Class description:
Database Abstraction Layer

Method signatures and docstrings:
- def GetDocument(document_id: str) -> Document: Fetch a specific document
- def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]: Fetch a specific document set
- def PutDocument(document: Document) -> Document: Update a specific document
- def PromoteDocument(currentStage: Stage, nextStage: Stage): Promote documents in SUCCESS state from current stage to next stage WAITING state

<|skeleton|>
class Database:
    """Database Abstraction Layer"""

    def GetDocument(document_id: str) -> Document:
        """Fetch a specific document"""
        <|body_0|>

    def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]:
        """Fetch a specific document set"""
        <|body_1|>

    def PutDocument(document: Document) -> Document:
        """Update a specific document"""
        <|body_2|>

    def PromoteDocument(currentStage: Stage, nextStage: Stage):
        """Promote documents in SUCCESS state from current stage to next stage WAITING state"""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        try:
            response = Database.Table.get_item(Key={'DocumentID': document_id})
        except Exception as e:
            response = None
            Logger.info(f'Database GetDocument : document_id = {document_id} : exception = {e}')
        if response and response.get('Item') and (response['ResponseMetadata']['HTTPStatusCode'] == 200):
            return Document.from_dict(response['Item'])
        else:
            return None
<|end_body_0|>

<|body_start_1|>
        for stage in stages:
            for state in states:
                response = Database.Table.query(IndexName=INDEX_PROGRESS, KeyConditionExpression=Key('StageState').eq(f'{stage}{HASH}{state}'.title()))
                for item in response['Items']:
                    yield Document.from_dict(item)
        return []
<|end_body_1|>

<|body_start_2|>
        response = Database.Table.put_item(Item=document.to_dict())
        Logger.info(f'Database.PutDocument : DocumentID = {document.DocumentID}')
        return PASS if response['ResponseMetadata']['HTTPStatusCode'] == 200 else FAIL
<|end_body_2|>

<|body_start_3|>
        for documentToUpdate in Database.GetDocuments([currentStage], [State.SUCCESS]):
            Logger.info(f'Moving {documentToUpdate} stage to {nextStage}')
            documentToUpdate.Stage = nextStage
            documentToUpdate.State = State.WAITING
            Database.PutDocument(documentToUpdate)
<|end_body_3|>

Solution:
class Database:
    """Database Abstraction Layer"""

    def GetDocument(document_id: str) -> Document:
        """Fetch a specific document"""
        try:
            response = Database.Table.get_item(Key={'DocumentID': document_id})
        except Exception as e:
            response = None
            Logger.info(f'Database GetDocument : document_id = {document_id} : exception = {e}')
        if response and response.get('Item') and (response['ResponseMetadata']['HTTPStatusCode'] == 200):
            return Document.from_dict(response['Item'])
        else:
            return None

    def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]:
        """Fetch a specific document set"""
        for stage in stages:
            for state in states:
                response = Database.Table.query(IndexName=INDEX_PROGRESS, KeyConditionExpression=Key('StageState').eq(f'{stage}{HASH}{state}'.title()))
                for item in response['Items']:
                    yield Document.from_dict(item)
        return []

    def PutDocument(document: Document) -> Document:
        """Update a specific document"""
        response = Database.Table.put_item(Item=document.to_dict())
        Logger.info(f'Database.PutDocument : DocumentID = {document.DocumentID}')
        return PASS if response['ResponseMetadata']['HTTPStatusCode'] == 200 else FAIL

    def PromoteDocument(currentStage: Stage, nextStage: Stage):
        """Promote documents in SUCCESS state from current stage to next stage WAITING state"""
        for documentToUpdate in Database.GetDocuments([currentStage], [State.SUCCESS]):
            Logger.info(f'Moving {documentToUpdate} stage to {nextStage}')
            documentToUpdate.Stage = nextStage
            documentToUpdate.State = State.WAITING
            Database.PutDocument(documentToUpdate)


normalize

Prompt:
Implement the Python class `ToTensor` described below.

Class description:
Convert ndarray to Tensor.

Method signatures and docstrings:
- def __call__(self, sample): @param sample (tuple|ndarray): numpy image|images @return tensor image
- def normalize(self, image): @param image (numpy): image axis are H x W x C @return tensor of normalized image in range [0,1] with axis C X H X W

Implement the Python class `ToTensor` described below.

Class description:
Convert ndarray to Tensor.

Method signatures and docstrings:
- def __call__(self, sample): @param sample (tuple|ndarray): numpy image|images @return tensor image
- def normalize(self, image): @param image (numpy): image axis are H x W x C @return tensor of normalized image in range [0,1] with axis C X H X W

<|skeleton|>
class ToTensor:
    """Convert ndarray to Tensor."""

    def __call__(self, sample):
        """@param sample (tuple|ndarray): numpy image|images @return tensor image"""
        <|body_0|>

    def normalize(self, image):
        """@param image (numpy): image axis are H x W x C @return tensor of normalized image in range [0,1] with axis C X H X W"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if type(sample) == tuple:
            image, noise_image = sample
            return (self.normalize(image), self.normalize(noise_image))
        else:
            return self.normalize(sample)
<|end_body_0|>

<|body_start_1|>
        image = image.transpose((2, 0, 1))
        image = image.astype(np.float32) / 255.0
        return image
<|end_body_1|>

Solution:
class ToTensor:
    """Convert ndarray to Tensor."""

    def __call__(self, sample):
        """@param sample (tuple|ndarray): numpy image|images @return tensor image"""
        if type(sample) == tuple:
            image, noise_image = sample
            return (self.normalize(image), self.normalize(noise_image))
        else:
            return self.normalize(sample)

    def normalize(self, image):
        """@param image (numpy): image axis are H x W x C @return tensor of normalized image in range [0,1] with axis C X H X W"""
        image = image.transpose((2, 0, 1))
        image = image.astype(np.float32) / 255.0
        return image


process

Prompt:
Implement the Python class `pre_plot` described below.

Class description:
Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important.

Method signatures and docstrings:
- def __init__(self, params_pre): Instantiates the pre_plot class as a callable. Args: params_pre (dictionary): Preprocessing section of Delta configuration Returns: None
- def process(self, data_chunk, executor=None): Plots the data chunk. Args: data_chunk (2d image): Data chunk to be wavelet transformed. executor (PEP-3148-style executor): Executor on which to execute. Returns: data_chunk (2d_image): Wavelet-filtered images

Implement the Python class `pre_plot` described below.

Class description:
Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important.

Method signatures and docstrings:
- def __init__(self, params_pre): Instantiates the pre_plot class as a callable. Args: params_pre (dictionary): Preprocessing section of Delta configuration Returns: None
- def process(self, data_chunk, executor=None): Plots the data chunk. Args: data_chunk (2d image): Data chunk to be wavelet transformed. executor (PEP-3148-style executor): Executor on which to execute. Returns: data_chunk (2d_image): Wavelet-filtered images

<|skeleton|>
class pre_plot:
    """Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important."""

    def __init__(self, params_pre):
        """Instantiates the pre_plot class as a callable. Args: params_pre (dictionary): Preprocessing section of Delta configuration Returns: None"""
        <|body_0|>

    def process(self, data_chunk, executor=None):
        """Plots the data chunk. Args: data_chunk (2d image): Data chunk to be wavelet transformed. executor (PEP-3148-style executor): Executor on which to execute. Returns: data_chunk (2d_image): Wavelet-filtered images"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.time_range = params_pre['time_range']
        self.plot_dir = params_pre['plot_dir']
        self.logger = logging.getLogger('simple')
<|end_body_0|>

<|body_start_1|>
        plotter = plot_ecei_timeslice(data_chunk)
        tidx_plot = [data_chunk.tb.time_to_idx(t) for t in self.time_range]
        if tidx_plot[0] is not None:
            self.logger.info(f'Plotting data into {self.plot_dir}. Plotting indices {tidx_plot[0]},                {tidx_plot[-1]}')
            for tidx in range(tidx_plot[0], tidx_plot[1]):
                fig = plotter.create_plot(data_chunk, tidx)
                fig.savefig(join(self.plot_dir, f'chunk_{data_chunk.tb.chunk_idx}_{tidx:04d}.png'))
        return data_chunk
<|end_body_1|>

Solution:
class pre_plot:
    """Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important."""

    def __init__(self, params_pre):
        """Instantiates the pre_plot class as a callable. Args: params_pre (dictionary): Preprocessing section of Delta configuration Returns: None"""
        self.time_range = params_pre['time_range']
        self.plot_dir = params_pre['plot_dir']
        self.logger = logging.getLogger('simple')

    def process(self, data_chunk, executor=None):
        """Plots the data chunk. Args: data_chunk (2d image): Data chunk to be wavelet transformed. executor (PEP-3148-style executor): Executor on which to execute. Returns: data_chunk (2d_image): Wavelet-filtered images"""
        plotter = plot_ecei_timeslice(data_chunk)
        tidx_plot = [data_chunk.tb.time_to_idx(t) for t in self.time_range]
        if tidx_plot[0] is not None:
            self.logger.info(f'Plotting data into {self.plot_dir}. Plotting indices {tidx_plot[0]},                {tidx_plot[-1]}')
            for tidx in range(tidx_plot[0], tidx_plot[1]):
                fig = plotter.create_plot(data_chunk, tidx)
                fig.savefig(join(self.plot_dir, f'chunk_{data_chunk.tb.chunk_idx}_{tidx:04d}.png'))
        return data_chunk


Prompt:
Implement the Python class `_Node` described below.

Class description:
A node as it is used in the tree structure. Each node contains the object it represents and a list of children. Children can be other nodes or arbitrary other objects. Any object in a tree which is not of the type _Node is considered a leaf.

Method signatures and docstrings:
- def __init__(self, o, str_func=None): You have to define the object this node represents. Also you can define an output function which will be used to represent this node. If no function is defined, the default str representation is used. keyword arguments str_func -- output function
- def __str__(self): Override str(self.o) if str_func is defined.

Implement the Python class `_Node` described below.

Class description:
A node as it is used in the tree structure. Each node contains the object it represents and a list of children. Children can be other nodes or arbitrary other objects. Any object in a tree which is not of the type _Node is considered a leaf.

Method signatures and docstrings:
- def __init__(self, o, str_func=None): You have to define the object this node represents. Also you can define an output function which will be used to represent this node. If no function is defined, the default str representation is used. keyword arguments str_func -- output function
- def __str__(self): Override str(self.o) if str_func is defined.

<|skeleton|>
class _Node:
    """A node as it is used in the tree structure. Each node contains the object it represents and a list of children. Children can be other nodes or arbitrary other objects. Any object in a tree which is not of the type _Node is considered a leaf."""

    def __init__(self, o, str_func=None):
        """You have to define the object this node represents. Also you can define an output function which will be used to represent this node. If no function is defined, the default str representation is used. keyword arguments str_func -- output function"""
        <|body_0|>

    def __str__(self):
        """Override str(self.o) if str_func is defined."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.o = o
        self.children = []
        self.str_func = str_func
<|end_body_0|>

<|body_start_1|>
        if self.str_func is not None:
            return self.str_func(self.o)
        else:
            return str(self.o)
<|end_body_1|>

Solution:
class _Node:
    """A node as it is used in the tree structure. Each node contains the object it represents and a list of children. Children can be other nodes or arbitrary other objects. Any object in a tree which is not of the type _Node is considered a leaf."""

    def __init__(self, o, str_func=None):
        """You have to define the object this node represents. Also you can define an output function which will be used to represent this node. If no function is defined, the default str representation is used. keyword arguments str_func -- output function"""
        self.o = o
        self.children = []
        self.str_func = str_func

    def __str__(self):
        """Override str(self.o) if str_func is defined."""
        if self.str_func is not None:
            return self.str_func(self.o)
        else:
            return str(self.o)


testValid

Prompt:
Implement the Python class `TestIsValidName` described below.

Class description:
Implement the TestIsValidName class.

Method signatures and docstrings:
- def testNonAlnumCharacters(self): user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax.
- def testWhitespace(self): user: isValidName: reject leading, trailing or multiple whitespace
- def testValid(self): user: isValidName: accept names in any language, with spaces

Implement the Python class `TestIsValidName` described below.

Class description:
Implement the TestIsValidName class.

Method signatures and docstrings:
- def testNonAlnumCharacters(self): user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax.
- def testWhitespace(self): user: isValidName: reject leading, trailing or multiple whitespace
- def testValid(self): user: isValidName: accept names in any language, with spaces

<|skeleton|>
class TestIsValidName:

    def testNonAlnumCharacters(self):
        """user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax."""
        <|body_0|>

    def testWhitespace(self):
        """user: isValidName: reject leading, trailing or multiple whitespace"""
        <|body_1|>

    def testValid(self):
        """user: isValidName: accept names in any language, with spaces"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        invalid = u'! # $ % ^ & * ( ) = + , : ; " | ~ / \\ \x00 \u202a'.split()
        base = u'User%sName'
        for c in invalid:
            name = base % c
            assert not user.isValidName(self.request, name)
<|end_body_0|>

<|body_start_1|>
        cases = (u' User Name', u'User Name ', u'User   Name')
        for test in cases:
            assert not user.isValidName(self.request, test)
<|end_body_1|>

<|body_start_2|>
        cases = (u'Jürgen Hermann', u'ניר סופר', u'CamelCase', u'가각간갇갈 갉갊감 갬갯걀갼')
        for test in cases:
            assert user.isValidName(self.request, test)
<|end_body_2|>

Solution:
class TestIsValidName:
    def testNonAlnumCharacters(self):
        """user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax."""
        invalid = u'! # $ % ^ & * ( ) = + , : ; " | ~ / \\ \x00 \u202a'.split()
        base = u'User%sName'
        for c in invalid:
            name = base % c
            assert not user.isValidName(self.request, name)

    def testWhitespace(self):
        """user: isValidName: reject leading, trailing or multiple whitespace"""
        cases = (u' User Name', u'User Name ', u'User   Name')
        for test in cases:
            assert not user.isValidName(self.request, test)

    def testValid(self):
        """user: isValidName: accept names in any language, with spaces"""
        cases = (u'Jürgen Hermann', u'ניר סופר', u'CamelCase', u'가각간갇갈 갉갊감 갬갯걀갼')
        for test in cases:
            assert user.isValidName(self.request, test)


draw

Prompt:
Implement the Python class `ObstacleMap` described below.

Class description:
Maintains an obstacle map. The map contains binary values: 0 (free) or 1 (occupied). The map is stored as a matrix with shape (height,width). The map can be used to simulate rangefinder readings.

Method signatures and docstrings:
- def __init__(self, path, max_dist=80): Creates an obstacle map. Arguments: path: path to a grayscale image representing the map max_dist: maximum rangefinder reading (cm)
- def draw(self, surface): Draws the obstacle map onto the surface.
- def get_first_hit(self, T_sonar_map): Calculates distance that sonar would report given current pose. Arguments: T_sonar_map: sonar-to-map transformation matrix Returns: First-hit distance or zero if no hit.

Implement the Python class `ObstacleMap` described below.

Class description:
Maintains an obstacle map. The map contains binary values: 0 (free) or 1 (occupied). The map is stored as a matrix with shape (height,width). The map can be used to simulate rangefinder readings.

Method signatures and docstrings:
- def __init__(self, path, max_dist=80): Creates an obstacle map. Arguments: path: path to a grayscale image representing the map max_dist: maximum rangefinder reading (cm)
- def draw(self, surface): Draws the obstacle map onto the surface.
- def get_first_hit(self, T_sonar_map): Calculates distance that sonar would report given current pose. Arguments: T_sonar_map: sonar-to-map transformation matrix Returns: First-hit distance or zero if no hit.

<|skeleton|>
class ObstacleMap:
    """Maintains an obstacle map. The map contains binary values: 0 (free) or 1 (occupied). The map is stored as a matrix with shape (height,width). The map can be used to simulate rangefinder readings."""

    def __init__(self, path, max_dist=80):
        """Creates an obstacle map. Arguments: path: path to a grayscale image representing the map max_dist: maximum rangefinder reading (cm)"""
        <|body_0|>

    def draw(self, surface):
        """Draws the obstacle map onto the surface."""
        <|body_1|>

    def get_first_hit(self, T_sonar_map):
        """Calculates distance that sonar would report given current pose. Arguments: T_sonar_map: sonar-to-map transformation matrix Returns: First-hit distance or zero if no hit."""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        self.max_dist = max_dist
        self.grid = imread(path, 0).astype('float32') / 255.0
        self.height = self.grid.shape[0]
        self.width = self.grid.shape[1]
<|end_body_0|>

<|body_start_1|>
        omap_array = ((1.0 - self.grid.transpose()) * 255.0).astype('int')
        omap_array = np.tile(np.expand_dims(omap_array, axis=-1), [1, 1, 3])
        pygame.surfarray.blit_array(surface, omap_array)
<|end_body_1|>

<|body_start_2|>
        for i in range(self.max_dist):
            pt_sonar = vec(i, 0)
            pt_map = mul(T_sonar_map, pt_sonar)
            r = int(pt_map[1])
            c = int(pt_map[0])
            if r < 0 or r >= self.grid.shape[0]:
                continue
            if c < 0 or c >= self.grid.shape[1]:
                continue
            if self.grid[r, c] > 0:
                return i + np.random.normal(0, 2, 1)[0]
        return 0.0
<|end_body_2|>

Solution:
class ObstacleMap:
    """Maintains an obstacle map. The map contains binary values: 0 (free) or 1 (occupied). The map is stored as a matrix with shape (height,width). The map can be used to simulate rangefinder readings."""

    def __init__(self, path, max_dist=80):
        """Creates an obstacle map. Arguments: path: path to a grayscale image representing the map max_dist: maximum rangefinder reading (cm)"""
        self.max_dist = max_dist
        self.grid = imread(path, 0).astype('float32') / 255.0
        self.height = self.grid.shape[0]
        self.width = self.grid.shape[1]

    def draw(self, surface):
        """Draws the obstacle map onto the surface."""
        omap_array = ((1.0 - self.grid.transpose()) * 255.0).astype('int')
        omap_array = np.tile(np.expand_dims(omap_array, axis=-1), [1, 1, 3])
        pygame.surfarray.blit_array(surface, omap_array)

    def get_first_hit(self, T_sonar_map):
        """Calculates distance that sonar would report given current pose. Arguments: T_sonar_map: sonar-to-map transformation matrix Returns: First-hit distance or zero if no hit."""
        for i in range(self.max_dist):
            pt_sonar = vec(i, 0)
            pt_map = mul(T_sonar_map, pt_sonar)
            r = int(pt_map[1])
            c = int(pt_map[0])
            if r < 0 or r >= self.grid.shape[0]:
                continue
            if c < 0 or c >= self.grid.shape[1]:
                continue
            if self.grid[r, c] > 0:
                return i + np.random.normal(0, 2, 1)[0]
        return 0.0


isSymmetric

Prompt:
Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def isSymmetric(self, root): 采用递归 :type root: TreeNode :rtype: bool
- def isSymmetric(self, root): 采用迭代,改用队列实现 首先从队列中拿出两个节点(left和right)比较 将left的left节点和right的right节点放入队列 将left的right节点和right的left节点放入队列 :param root: :return:

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def isSymmetric(self, root): 采用递归 :type root: TreeNode :rtype: bool
- def isSymmetric(self, root): 采用迭代,改用队列实现 首先从队列中拿出两个节点(left和right)比较 将left的left节点和right的right节点放入队列 将left的right节点和right的left节点放入队列 :param root: :return:

<|skeleton|>
class Solution:

    def isSymmetric(self, root):
        """采用递归 :type root: TreeNode :rtype: bool"""
        <|body_0|>

    def isSymmetric(self, root):
        """采用迭代,改用队列实现 首先从队列中拿出两个节点(left和right)比较 将left的left节点和right的right节点放入队列 将left的right节点和right的left节点放入队列 :param root: :return:"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        def dfs(left, right):
            if left is None and right is None:
                return True
            if left is None or right is None:
                return False
            if left.val != right.val:
                return False
            return dfs(left.left, right.right) and dfs(left.right, right.left)
        return dfs(root.left, root.right)
<|end_body_0|>

<|body_start_1|>
        if not root or not (root.left or root.right):
            return True
        queue = [root.left, root.right]
        while queue:
            left = queue.pop(0)
            right = queue.pop(0)
            if not left and (not right):
                continue
            if not left or not right:
                return False
            if left.val != right.val:
                return False
            queue.append(left.left)
            queue.append(right.right)
            queue.append(left.right)
            queue.append(right.left)
        return True
<|end_body_1|>

Solution:
class Solution:
    def isSymmetric(self, root):
        """采用递归 :type root: TreeNode :rtype: bool"""
        def dfs(left, right):
            if left is None and right is None:
                return True
            if left is None or right is None:
                return False
            if left.val != right.val:
                return False
            return dfs(left.left, right.right) and dfs(left.right, right.left)
        return dfs(root.left, root.right)

    def isSymmetric(self, root):
        """采用迭代,改用队列实现 首先从队列中拿出两个节点(left和right)比较 将left的left节点和right的right节点放入队列 将left的right节点和right的left节点放入队列 :param root: :return:"""
        if not root or not (root.left or root.right):
            return True
        queue = [root.left, root.right]
        while queue:
            left = queue.pop(0)
            right = queue.pop(0)
            if not left and (not right):
                continue
            if not left or not right:
                return False
            if left.val != right.val:
                return False
            queue.append(left.left)
            queue.append(right.right)
            queue.append(left.right)
            queue.append(right.left)
        return True


Prompt:
Implement the Python class `Common` described below.

Class description:
cancel_btn and skip btn

Method signatures and docstrings:
- def check_cancelBtn(self): if there is a update button cancel it then :return:
- def check_skipBtn(self): to skip advertising :return:

Implement the Python class `Common` described below.

Class description:
cancel_btn and skip btn

Method signatures and docstrings:
- def check_cancelBtn(self): if there is a update button cancel it then :return:
- def check_skipBtn(self): to skip advertising :return:

<|skeleton|>
class Common:
    """cancel_btn and skip btn"""

    def check_cancelBtn(self):
        """if there is a update button cancel it then :return:"""
        <|body_0|>

    def check_skipBtn(self):
        """to skip advertising :return:"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        try:
            cancel_btn = self.find_element(*self.cancel_loc)
        except NoSuchElementException:
            logging.info('=====cancel button does not exist in page =====')
        else:
            cancel_btn.click()
            logging.info('=====Click Cancel btn====')
<|end_body_0|>

<|body_start_1|>
        try:
            skip_btn = self.find_element(*self.skip_loc)
        except NoSuchElementException:
            logging.info('=====skip button does not exist in page =====')
        else:
            skip_btn.click()
            logging.info('=====Click skip btn====')
<|end_body_1|>

Solution:
class Common:
    """cancel_btn and skip btn"""

    def check_cancelBtn(self):
        """if there is a update button cancel it then :return:"""
        try:
            cancel_btn = self.find_element(*self.cancel_loc)
        except NoSuchElementException:
            logging.info('=====cancel button does not exist in page =====')
        else:
            cancel_btn.click()
            logging.info('=====Click Cancel btn====')

    def check_skipBtn(self):
        """to skip advertising :return:"""
        try:
            skip_btn = self.find_element(*self.skip_loc)
        except NoSuchElementException:
            logging.info('=====skip button does not exist in page =====')
        else:
            skip_btn.click()
            logging.info('=====Click skip btn====')


format

Prompt:
Implement the Python class `HtmlColorFormatter` described below.

Class description:
Class to format Python logs in coloured HTML.

Method signatures and docstrings:
- def __init__(self, append_br: bool=False, replace_nl_with_br: bool=True) -> None: Args: append_br: append ``
`` to each line? replace_nl_with_br: replace ``\\n`` with ``
`` in messages? See https://hg.python.org/cpython/file/3.5/Lib/logging/__init__.py
- def format(self, record: logging.LogRecord) -> str: Internal function to format the :class:`LogRecord` as HTML. See https://docs.python.org/3.4/library/logging.html#logging.LogRecord

Implement the Python class `HtmlColorFormatter` described below.

Class description:
Class to format Python logs in coloured HTML.

Method signatures and docstrings:
- def __init__(self, append_br: bool=False, replace_nl_with_br: bool=True) -> None: Args: append_br: append ``
`` to each line? replace_nl_with_br: replace ``\\n`` with ``
`` in messages? See https://hg.python.org/cpython/file/3.5/Lib/logging/__init__.py
- def format(self, record: logging.LogRecord) -> str: Internal function to format the :class:`LogRecord` as HTML. See https://docs.python.org/3.4/library/logging.html#logging.LogRecord

<|skeleton|>
class HtmlColorFormatter:
    """Class to format Python logs in coloured HTML."""

    def __init__(self, append_br: bool=False, replace_nl_with_br: bool=True) -> None:
        """Args: append_br: append ``
`` to each line? replace_nl_with_br: replace ``\\n`` with ``
`` in messages? See https://hg.python.org/cpython/file/3.5/Lib/logging/__init__.py"""
        <|body_0|>

    def format(self, record: logging.LogRecord) -> str:
        """Internal function to format the :class:`LogRecord` as HTML. See https://docs.python.org/3.4/library/logging.html#logging.LogRecord"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        super().__init__(fmt='%(message)s', datefmt='%Y-%m-%d %H:%M:%S', style='%')
        self.append_br = append_br
        self.replace_nl_with_br = replace_nl_with_br
<|end_body_0|>

<|body_start_1|>
        super().format(record)
        record.asctime = self.formatTime(record, self.datefmt)
        bg_col = self.log_background_colors[record.levelno]
        msg = escape(record.getMessage())
        if self.replace_nl_with_br:
            msg = msg.replace('\n', '
')
        html = '{time}.{ms:03d} {name}:{lvname}: {msg}{br}'.format(time=record.asctime, ms=int(record.msecs), name=record.name, lvname=record.levelname, color=self.log_colors[record.levelno], msg=msg, bg=f';background-color:{bg_col}' if bg_col else '', br='
' if self.append_br else '')
        return html
<|end_body_1|>

Solution:
class HtmlColorFormatter:
    """Class to format Python logs in coloured HTML."""

    def __init__(self, append_br: bool=False, replace_nl_with_br: bool=True) -> None:
        """Args: append_br: append ``
`` to each line? replace_nl_with_br: replace ``\\n`` with ``
`` in messages? See https://hg.python.org/cpython/file/3.5/Lib/logging/__init__.py"""
        super().__init__(fmt='%(message)s', datefmt='%Y-%m-%d %H:%M:%S', style='%')
        self.append_br = append_br
        self.replace_nl_with_br = replace_nl_with_br

    def format(self, record: logging.LogRecord) -> str:
        """Internal function to format the :class:`LogRecord` as HTML. See https://docs.python.org/3.4/library/logging.html#logging.LogRecord"""
        super().format(record)
        record.asctime = self.formatTime(record, self.datefmt)
        bg_col = self.log_background_colors[record.levelno]
        msg = escape(record.getMessage())
        if self.replace_nl_with_br:
            msg = msg.replace('\n', '
')
        html = '{time}.{ms:03d} {name}:{lvname}: {msg}{br}'.format(time=record.asctime, ms=int(record.msecs), name=record.name, lvname=record.levelname, color=self.log_colors[record.levelno], msg=msg, bg=f';background-color:{bg_col}' if bg_col else '', br='
' if self.append_br else '')
        return html


货币字符串转换类，负责转换货币种类 美元转换为欧元 欧元转换为美元

Prompt:
Implement the Python class `CurrencyStringConverter` described below.

Class description:
货币字符串转换类，负责转换货币种类 美元转换为欧元 欧元转换为美元

Method signatures and docstrings:
- def is_number(self, s): 判断字符串是否为数字 :param s: 字符串 :return:
- def dollar_to_euro(self, prices, interest): 美元转换为欧元 实例：74.23*0.8=€59.38 保留小数点后两位 :param prices:价钱列表 由字符串组成，判断元素是否为数字 :param interest:利率 :return:列表 有字符串组成
- def euro_to_dollar(self, prices, interest): 欧元欧元转换为美元 实例：€59,38/0.8=74.23 先取出59,38转换为59.38 保留小数点后两位 :param prices:价钱列表 由字符串组成，判断元素是否为数字 :param interest:利率 :return:列表 有字符串组成

Implement the Python class `CurrencyStringConverter` described below.

Class description:
货币字符串转换类，负责转换货币种类 美元转换为欧元 欧元转换为美元

Method signatures and docstrings:
- def is_number(self, s): 判断字符串是否为数字 :param s: 字符串 :return:
- def dollar_to_euro(self, prices, interest): 美元转换为欧元 实例：74.23*0.8=€59.38 保留小数点后两位 :param prices:价钱列表 由字符串组成，判断元素是否为数字 :param interest:利率 :return:列表 有字符串组成
- def euro_to_dollar(self, prices, interest): 欧元欧元转换为美元 实例：€59,38/0.8=74.23 先取出59,38转换为59.38 保留小数点后两位 :param prices:价钱列表 由字符串组成，判断元素是否为数字 :param interest:利率 :return:列表 有字符串组成

<|skeleton|>
class CurrencyStringConverter:
    """货币字符串转换类，负责转换货币种类 美元转换为欧元 欧元转换为美元"""

    def is_number(self, s):
        """判断字符串是否为数字 :param s: 字符串 :return:"""
        <|body_0|>

    def dollar_to_euro(self, prices, interest):
        """美元转换为欧元 实例：74.23*0.8=€59.38 保留小数点后两位 :param prices:价钱列表 由字符串组成，判断元素是否为数字 :param interest:利率 :return:列表 有字符串组成"""
        <|body_1|>

    def euro_to_dollar(self, prices, interest):
        """欧元欧元转换为美元 实例：€59,38/0.8=74.23 先取出59,38转换为59.38 保留小数点后两位 :param prices:价钱列表 由字符串组成，判断元素是否为数字 :param interest:利率 :return:列表 有字符串组成"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        try:
            float(s)
            return True
        except ValueError:
            pass
        return False
<|end_body_0|>

<|body_start_1|>
        euros = []
        for i in range(0, len(prices)):
            price = prices[i]
            if self.is_number(price):
                euro = '€{:.2f}'.format(float(price) * interest)
                euros.append("'" + euro.replace('.', ',') + "'")
            else:
                euros.append(price)
                continue
        return euros
<|end_body_1|>

<|body_start_2|>
        dollars = []
        for i in range(0, len(prices)):
            price = prices[i][2:len(prices[i]) - 1]
            price = price.replace(',', '.')
            if self.is_number(price):
                dollar = '{:.2f}'.format(float(price) / interest)
                dollars.append(dollar)
            else:
                dollars.append(price)
                continue
        return dollars
<|end_body_2|>

Solution:
class CurrencyStringConverter:
    """货币字符串转换类，负责转换货币种类 美元转换为欧元 欧元转换为美元"""

    def is_number(self, s):
        """判断字符串是否为数字 :param s: 字符串 :return:"""
        try:
            float(s)
            return True
        except ValueError:
            pass
        return False

    def dollar_to_euro(self, prices, interest):
        """美元转换为欧元 实例：74.23*0.8=€59.38 保留小数点后两位 :param prices:价钱列表 由字符串组成，判断元素是否为数字 :param interest:利率 :return:列表 有字符串组成"""
        euros = []
        for i in range(0, len(prices)):
            price = prices[i]
            if self.is_number(price):
                euro = '€{:.2f}'.format(float(price) * interest)
                euros.append("'" + euro.replace('.', ',') + "'")
            else:
                euros.append(price)
                continue
        return euros

    def euro_to_dollar(self, prices, interest):
        """欧元欧元转换为美元 实例：€59,38/0.8=74.23 先取出59,38转换为59.38 保留小数点后两位 :param prices:价钱列表 由字符串组成，判断元素是否为数字 :param interest:利率 :return:列表 有字符串组成"""
        dollars = []
        for i in range(0, len(prices)):
            price = prices[i][2:len(prices[i]) - 1]
            price = price.replace(',', '.')
            if self.is_number(price):
                dollar = '{:.2f}'.format(float(price) / interest)
                dollars.append(dollar)
            else:
                dollars.append(price)
                continue
        return dollars