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

Class description:
urllib.request style handler for Cosign protected URLs. See http://weblogin.org SYNOPSIS: # Cosign relies on cookies. cj = http.cookiejar.MozillaCookieJar('cookies.txt') # We need an opener that handles cookies and any cosign redirects and # logins. opener = urllib.request.build_opener( urllib.request.HTTPCookieProcessor(cj), # Here's the CosignHandler. CosignHandler('https://cosign.login/page', cj, CosignPasswordMgr() # If you've got one big program you'll probably # want to keep the cookies in memory, but for # lots of little programs we get single sign on # behaviour by saving and loading to/from a # file. save_cookies=True ) ) # Construct a request for the page we actually want req = url

Method signatures and docstrings:
- def __init__(self, login_url, cj, pw_mgr, save_cookies=True): Construct new CosignHandler. Args: login_url: URL of cosign login page. Used to figure out if we have been redirected to the login page after a failed authentication, and as the URL to POST to to log in. cj: An http.cookiejar.CookieJar or equivalent. You'll need something that implements the FileCookieJar interface if you want to load/save cookies. pw_mgr: A CosignPasswordMgr object or equivalent. This object will provide (and if necessary prompt for) the username and password. save_cookies: Whether or not to save cookies to a file after each request. Required for single sign on between different scripts.
- def https_response(self, req, res): Handle https_response. If the response is from the cosign login page (starts with self.login_url) then log in to cosign and retry. Otherwise continue as normal.

Implement the Python class `CosignHandler` described below.

Class description:
urllib.request style handler for Cosign protected URLs. See http://weblogin.org SYNOPSIS: # Cosign relies on cookies. cj = http.cookiejar.MozillaCookieJar('cookies.txt') # We need an opener that handles cookies and any cosign redirects and # logins. opener = urllib.request.build_opener( urllib.request.HTTPCookieProcessor(cj), # Here's the CosignHandler. CosignHandler('https://cosign.login/page', cj, CosignPasswordMgr() # If you've got one big program you'll probably # want to keep the cookies in memory, but for # lots of little programs we get single sign on # behaviour by saving and loading to/from a # file. save_cookies=True ) ) # Construct a request for the page we actually want req = url

Method signatures and docstrings:
- def __init__(self, login_url, cj, pw_mgr, save_cookies=True): Construct new CosignHandler. Args: login_url: URL of cosign login page. Used to figure out if we have been redirected to the login page after a failed authentication, and as the URL to POST to to log in. cj: An http.cookiejar.CookieJar or equivalent. You'll need something that implements the FileCookieJar interface if you want to load/save cookies. pw_mgr: A CosignPasswordMgr object or equivalent. This object will provide (and if necessary prompt for) the username and password. save_cookies: Whether or not to save cookies to a file after each request. Required for single sign on between different scripts.
- def https_response(self, req, res): Handle https_response. If the response is from the cosign login page (starts with self.login_url) then log in to cosign and retry. Otherwise continue as normal.

<|skeleton|>
class CosignHandler:
    """urllib.request style handler for Cosign protected URLs. See http://weblogin.org SYNOPSIS: # Cosign relies on cookies. cj = http.cookiejar.MozillaCookieJar('cookies.txt') # We need an opener that handles cookies and any cosign redirects and # logins. opener = urllib.request.build_opener( urllib.request.HTTPCookieProcessor(cj), # Here's the CosignHandler. CosignHandler('https://cosign.login/page', cj, CosignPasswordMgr() # If you've got one big program you'll probably # want to keep the cookies in memory, but for # lots of little programs we get single sign on # behaviour by saving and loading to/from a # file. save_cookies=True ) ) # Construct a request for the page we actually want req = url"""

    def __init__(self, login_url, cj, pw_mgr, save_cookies=True):
        """Construct new CosignHandler. Args: login_url: URL of cosign login page. Used to figure out if we have been redirected to the login page after a failed authentication, and as the URL to POST to to log in. cj: An http.cookiejar.CookieJar or equivalent. You'll need something that implements the FileCookieJar interface if you want to load/save cookies. pw_mgr: A CosignPasswordMgr object or equivalent. This object will provide (and if necessary prompt for) the username and password. save_cookies: Whether or not to save cookies to a file after each request. Required for single sign on between different scripts."""
        <|body_0|>

    def https_response(self, req, res):
        """Handle https_response. If the response is from the cosign login page (starts with self.login_url) then log in to cosign and retry. Otherwise continue as normal."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        super().__init__()
        self.login_url = login_url
        self.cj = cj
        self.pw_mgr = pw_mgr
        self.save_cookies = save_cookies
        try:
            self.cj.load(ignore_discard=True)
        except IOError:
            pass
<|end_body_0|>

<|body_start_1|>
        if res.code == 200 and res.geturl().startswith(self.login_url + '?'):
            self.cj.extract_cookies(res, req)
            data = urllib.parse.urlencode(self.pw_mgr.get_cred())
            req2 = urllib.request.Request(self.login_url, data.encode('iso-8859-1'))
            opener = urllib.request.build_opener(urllib.request.HTTPCookieProcessor(self.cj))
            res2 = opener.open(req2)
            self.cj.extract_cookies(res2, req2)
            res = opener.open(req)
            if res.geturl().startswith(self.login_url + '?'):
                raise Exception('Login failed.')
            if self.save_cookies:
                self.cj.extract_cookies(res, req)
                self.cj.save(ignore_discard=True)
        return res
<|end_body_1|>

Solution:
class CosignHandler:
    """urllib.request style handler for Cosign protected URLs. See http://weblogin.org SYNOPSIS: # Cosign relies on cookies. cj = http.cookiejar.MozillaCookieJar('cookies.txt') # We need an opener that handles cookies and any cosign redirects and # logins. opener = urllib.request.build_opener( urllib.request.HTTPCookieProcessor(cj), # Here's the CosignHandler. CosignHandler('https://cosign.login/page', cj, CosignPasswordMgr() # If you've got one big program you'll probably # want to keep the cookies in memory, but for # lots of little programs we get single sign on # behaviour by saving and loading to/from a # file. save_cookies=True ) ) # Construct a request for the page we actually want req = url"""

    def __init__(self, login_url, cj, pw_mgr, save_cookies=True):
        """Construct new CosignHandler. Args: login_url: URL of cosign login page. Used to figure out if we have been redirected to the login page after a failed authentication, and as the URL to POST to to log in. cj: An http.cookiejar.CookieJar or equivalent. You'll need something that implements the FileCookieJar interface if you want to load/save cookies. pw_mgr: A CosignPasswordMgr object or equivalent. This object will provide (and if necessary prompt for) the username and password. save_cookies: Whether or not to save cookies to a file after each request. Required for single sign on between different scripts."""
        super().__init__()
        self.login_url = login_url
        self.cj = cj
        self.pw_mgr = pw_mgr
        self.save_cookies = save_cookies
        try:
            self.cj.load(ignore_discard=True)
        except IOError:
            pass

    def https_response(self, req, res):
        """Handle https_response. If the response is from the cosign login page (starts with self.login_url) then log in to cosign and retry. Otherwise continue as normal."""
        if res.code == 200 and res.geturl().startswith(self.login_url + '?'):
            self.cj.extract_cookies(res, req)
            data = urllib.parse.urlencode(self.pw_mgr.get_cred())
            req2 = urllib.request.Request(self.login_url, data.encode('iso-8859-1'))
            opener = urllib.request.build_opener(urllib.request.HTTPCookieProcessor(self.cj))
            res2 = opener.open(req2)
            self.cj.extract_cookies(res2, req2)
            res = opener.open(req)
            if res.geturl().startswith(self.login_url + '?'):
                raise Exception('Login failed.')
            if self.save_cookies:
                self.cj.extract_cookies(res, req)
                self.cj.save(ignore_discard=True)
        return res


unfollow

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

Class description:
Implement the Twitter class.

Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int) -> List[int]: Retrieve the 10 most recent tweet ids in the user's news feed. Each item in the news feed must be posted by users who the user followed or by the user herself. Tweets must be ordered from most recent to least recent.
- def follow(self, followerId: int, followeeId: int) -> None: Follower follows a followee. If the operation is invalid, it should be a no-op.
- def unfollow(self, followerId: int, followeeId: int) -> None: Follower unfollows a followee. If the operation is invalid, it should be a no-op.

Implement the Python class `Twitter` described below.

Class description:
Implement the Twitter class.

Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int) -> List[int]: Retrieve the 10 most recent tweet ids in the user's news feed. Each item in the news feed must be posted by users who the user followed or by the user herself. Tweets must be ordered from most recent to least recent.
- def follow(self, followerId: int, followeeId: int) -> None: Follower follows a followee. If the operation is invalid, it should be a no-op.
- def unfollow(self, followerId: int, followeeId: int) -> None: Follower unfollows a followee. If the operation is invalid, it should be a no-op.

<|skeleton|>
class Twitter:

    def __init__(self):
        """Initialize your data structure here."""
        <|body_0|>

    def postTweet(self, userId: int, tweetId: int) -> None:
        """Compose a new tweet."""
        <|body_1|>

    def getNewsFeed(self, userId: int) -> List[int]:
        """Retrieve the 10 most recent tweet ids in the user's news feed. Each item in the news feed must be posted by users who the user followed or by the user herself. Tweets must be ordered from most recent to least recent."""
        <|body_2|>

    def follow(self, followerId: int, followeeId: int) -> None:
        """Follower follows a followee. If the operation is invalid, it should be a no-op."""
        <|body_3|>

    def unfollow(self, followerId: int, followeeId: int) -> None:
        """Follower unfollows a followee. If the operation is invalid, it should be a no-op."""
        <|body_4|>

<|end_skeleton|>

<|body_start_0|>
        self.time = 0
        self.recentMax = 10
        self.tweetTime = dict()
        self.user = dict()
<|end_body_0|>

<|body_start_1|>
        if userId not in self.user:
            self.user[userId] = Twitter.Node()
        self.user[userId].tweet.append(tweetId)
        self.time += 1
        self.tweetTime[tweetId] = self.time
<|end_body_1|>

<|body_start_2|>
        if userId not in self.user:
            return list()
        else:
            ans = self.user[userId].tweet[-10:][::-1]
            for followeeId in self.user[userId].followee:
                if followeeId in self.user:
                    opt = self.user[followeeId].tweet[-10:][::-1]
                    i, j, combined = (0, 0, list())
                    while i < len(ans) and j < len(opt):
                        if self.tweetTime[ans[i]] > self.tweetTime[opt[j]]:
                            combined.append(ans[i])
                            i += 1
                        else:
                            combined.append(opt[j])
                            j += 1
                    combined.extend(ans[i:])
                    combined.extend(opt[j:])
                    ans = combined[:10]
            return ans
<|end_body_2|>

<|body_start_3|>
        if followerId != followeeId:
            if followerId not in self.user:
                self.user[followerId] = Twitter.Node()
            self.user[followerId].followee.add(followeeId)
<|end_body_3|>

<|body_start_4|>
        if followerId != followeeId:
            if followerId in self.user:
                self.user[followerId].followee.discard(followeeId)
<|end_body_4|>

Solution:
class Twitter:
    def __init__(self):
        """Initialize your data structure here."""
        self.time = 0
        self.recentMax = 10
        self.tweetTime = dict()
        self.user = dict()

    def postTweet(self, userId: int, tweetId: int) -> None:
        """Compose a new tweet."""
        if userId not in self.user:
            self.user[userId] = Twitter.Node()
        self.user[userId].tweet.append(tweetId)
        self.time += 1
        self.tweetTime[tweetId] = self.time

    def getNewsFeed(self, userId: int) -> List[int]:
        """Retrieve the 10 most recent tweet ids in the user's news feed. Each item in the news feed must be posted by users who the user followed or by the user herself. Tweets must be ordered from most recent to least recent."""
        if userId not in self.user:
            return list()
        else:
            ans = self.user[userId].tweet[-10:][::-1]
            for followeeId in self.user[userId].followee:
                if followeeId in self.user:
                    opt = self.user[followeeId].tweet[-10:][::-1]
                    i, j, combined = (0, 0, list())
                    while i < len(ans) and j < len(opt):
                        if self.tweetTime[ans[i]] > self.tweetTime[opt[j]]:
                            combined.append(ans[i])
                            i += 1
                        else:
                            combined.append(opt[j])
                            j += 1
                    combined.extend(ans[i:])
                    combined.extend(opt[j:])
                    ans = combined[:10]
            return ans

    def follow(self, followerId: int, followeeId: int) -> None:
        """Follower follows a followee. If the operation is invalid, it should be a no-op."""
        if followerId != followeeId:
            if followerId not in self.user:
                self.user[followerId] = Twitter.Node()
            self.user[followerId].followee.add(followeeId)

    def unfollow(self, followerId: int, followeeId: int) -> None:
        """Follower unfollows a followee. If the operation is invalid, it should be a no-op."""
        if followerId != followeeId:
            if followerId in self.user:
                self.user[followerId].followee.discard(followeeId)


retrieve

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

Class description:
Implement the DefinitionDetailResource class.

Method signatures and docstrings:
- def create(self, request, definition_id, **params): Initiates the creation of a Mart using the specified Mart Definition. The body of this request allows two parameters: * ``purge_on_failure``: Whether or not to purge the remnants of the Mart if creation fails at any point. Optional. Defaults to ``true``. * ``leave_incomplete``: Whether or not to leave the status of the Mart as not "complete" when the creation has actually completed. Optional. Defaults to ``false``.
- def retrieve(self, request, definition_id, **params): Retrieves details about the specified Mart Definition, as well as a list of the Marts that were created using that Definition that the user has access to.

Implement the Python class `DefinitionDetailResource` described below.

Class description:
Implement the DefinitionDetailResource class.

Method signatures and docstrings:
- def create(self, request, definition_id, **params): Initiates the creation of a Mart using the specified Mart Definition. The body of this request allows two parameters: * ``purge_on_failure``: Whether or not to purge the remnants of the Mart if creation fails at any point. Optional. Defaults to ``true``. * ``leave_incomplete``: Whether or not to leave the status of the Mart as not "complete" when the creation has actually completed. Optional. Defaults to ``false``.
- def retrieve(self, request, definition_id, **params): Retrieves details about the specified Mart Definition, as well as a list of the Marts that were created using that Definition that the user has access to.

<|skeleton|>
class DefinitionDetailResource:

    def create(self, request, definition_id, **params):
        """Initiates the creation of a Mart using the specified Mart Definition. The body of this request allows two parameters: * ``purge_on_failure``: Whether or not to purge the remnants of the Mart if creation fails at any point. Optional. Defaults to ``true``. * ``leave_incomplete``: Whether or not to leave the status of the Mart as not "complete" when the creation has actually completed. Optional. Defaults to ``false``."""
        <|body_0|>

    def retrieve(self, request, definition_id, **params):
        """Retrieves details about the specified Mart Definition, as well as a list of the Marts that were created using that Definition that the user has access to."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        user = authenticate(request)
        if not MartAccessPermissions.top().user_can_access_definition(user, definition_id):
            raise HTTPUnauthorized()
        if not get_settings().mart_allow_runtime_creation:
            raise HTTPForbidden('Runtime Mart creation is not allowed')
        creator = MartCreator(user, definition_id)
        try:
            creator.validate_parameters(request.payload.parameters)
        except Error as exc:
            raise HTTPBadRequest(str(exc))
        definition = get_definition(definition_id)
        if not MartQuota.top().can_create_mart(user, definition):
            raise HTTPForbidden('Creating a Mart of this Definition would violate your Quota')
        payload = request.payload._asdict()
        payload['owner'] = user
        payload['definition'] = definition_id
        from rex.asynctask import get_transport
        transport = get_transport()
        transport.submit_task(get_settings().mart_runtime_creation_queue, payload)
        response = self.make_response(request, payload)
        response.status = 202
        return response
<|end_body_0|>

<|body_start_1|>
        user = authenticate(request)
        mart_access = MartAccessPermissions.top()
        marts = mart_access.get_marts_for_user(user, definition_id=definition_id)
        response = {'definition': render_definition(get_definition(definition_id)), 'marts': [mart.as_dict() for mart in marts]}
        return response
<|end_body_1|>

Solution:
class DefinitionDetailResource:
    def create(self, request, definition_id, **params):
        """Initiates the creation of a Mart using the specified Mart Definition. The body of this request allows two parameters: * ``purge_on_failure``: Whether or not to purge the remnants of the Mart if creation fails at any point. Optional. Defaults to ``true``. * ``leave_incomplete``: Whether or not to leave the status of the Mart as not "complete" when the creation has actually completed. Optional. Defaults to ``false``."""
        user = authenticate(request)
        if not MartAccessPermissions.top().user_can_access_definition(user, definition_id):
            raise HTTPUnauthorized()
        if not get_settings().mart_allow_runtime_creation:
            raise HTTPForbidden('Runtime Mart creation is not allowed')
        creator = MartCreator(user, definition_id)
        try:
            creator.validate_parameters(request.payload.parameters)
        except Error as exc:
            raise HTTPBadRequest(str(exc))
        definition = get_definition(definition_id)
        if not MartQuota.top().can_create_mart(user, definition):
            raise HTTPForbidden('Creating a Mart of this Definition would violate your Quota')
        payload = request.payload._asdict()
        payload['owner'] = user
        payload['definition'] = definition_id
        from rex.asynctask import get_transport
        transport = get_transport()
        transport.submit_task(get_settings().mart_runtime_creation_queue, payload)
        response = self.make_response(request, payload)
        response.status = 202
        return response

    def retrieve(self, request, definition_id, **params):
        """Retrieves details about the specified Mart Definition, as well as a list of the Marts that were created using that Definition that the user has access to."""
        user = authenticate(request)
        mart_access = MartAccessPermissions.top()
        marts = mart_access.get_marts_for_user(user, definition_id=definition_id)
        response = {'definition': render_definition(get_definition(definition_id)), 'marts': [mart.as_dict() for mart in marts]}
        return response


forward

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

Class description:
Implement the ViltLayerBetterTransformer class.

Method signatures and docstrings:
- def __init__(self, vilt_layer, config): A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`torch.nn.Module`): The original `VilTLayer` where the weights needs to be retrieved.
- def forward(self, hidden_states, *_, **__): This is just a wrapper around the forward function proposed in: https://github.com/huggingface/transformers/pull/19553

Implement the Python class `ViltLayerBetterTransformer` described below.

Class description:
Implement the ViltLayerBetterTransformer class.

Method signatures and docstrings:
- def __init__(self, vilt_layer, config): A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`torch.nn.Module`): The original `VilTLayer` where the weights needs to be retrieved.
- def forward(self, hidden_states, *_, **__): This is just a wrapper around the forward function proposed in: https://github.com/huggingface/transformers/pull/19553

<|skeleton|>
class ViltLayerBetterTransformer:

    def __init__(self, vilt_layer, config):
        """A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`torch.nn.Module`): The original `VilTLayer` where the weights needs to be retrieved."""
        <|body_0|>

    def forward(self, hidden_states, *_, **__):
        """This is just a wrapper around the forward function proposed in: https://github.com/huggingface/transformers/pull/19553"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        super().__init__(config)
        self.in_proj_weight = nn.Parameter(torch.cat([vilt_layer.attention.attention.query.weight, vilt_layer.attention.attention.key.weight, vilt_layer.attention.attention.value.weight]))
        self.in_proj_bias = nn.Parameter(torch.cat([vilt_layer.attention.attention.query.bias, vilt_layer.attention.attention.key.bias, vilt_layer.attention.attention.value.bias]))
        self.out_proj_weight = vilt_layer.attention.output.dense.weight
        self.out_proj_bias = vilt_layer.attention.output.dense.bias
        self.linear1_weight = vilt_layer.intermediate.dense.weight
        self.linear1_bias = vilt_layer.intermediate.dense.bias
        self.linear2_weight = vilt_layer.output.dense.weight
        self.linear2_bias = vilt_layer.output.dense.bias
        self.norm1_eps = vilt_layer.layernorm_before.eps
        self.norm1_weight = vilt_layer.layernorm_before.weight
        self.norm1_bias = vilt_layer.layernorm_before.bias
        self.norm2_eps = vilt_layer.layernorm_after.eps
        self.norm2_weight = vilt_layer.layernorm_after.weight
        self.norm2_bias = vilt_layer.layernorm_after.bias
        self.num_heads = vilt_layer.attention.attention.num_attention_heads
        self.embed_dim = int(vilt_layer.attention.attention.attention_head_size * self.num_heads)
        self.is_last_layer = False
        self.norm_first = True
        self.validate_bettertransformer()
<|end_body_0|>

<|body_start_1|>
        super().forward_checker()
        attention_mask = None
        hidden_states = torch._transformer_encoder_layer_fwd(hidden_states, self.embed_dim, self.num_heads, self.in_proj_weight, self.in_proj_bias, self.out_proj_weight, self.out_proj_bias, self.use_gelu, self.norm_first, self.norm1_eps, self.norm1_weight, self.norm1_bias, self.norm2_weight, self.norm2_bias, self.linear1_weight, self.linear1_bias, self.linear2_weight, self.linear2_bias, attention_mask)
        if hidden_states.is_nested and self.is_last_layer:
            hidden_states = hidden_states.to_padded_tensor(0.0)
        return (hidden_states,)
<|end_body_1|>

Solution:
class ViltLayerBetterTransformer:
    def __init__(self, vilt_layer, config):
        """A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`torch.nn.Module`): The original `VilTLayer` where the weights needs to be retrieved."""
        super().__init__(config)
        self.in_proj_weight = nn.Parameter(torch.cat([vilt_layer.attention.attention.query.weight, vilt_layer.attention.attention.key.weight, vilt_layer.attention.attention.value.weight]))
        self.in_proj_bias = nn.Parameter(torch.cat([vilt_layer.attention.attention.query.bias, vilt_layer.attention.attention.key.bias, vilt_layer.attention.attention.value.bias]))
        self.out_proj_weight = vilt_layer.attention.output.dense.weight
        self.out_proj_bias = vilt_layer.attention.output.dense.bias
        self.linear1_weight = vilt_layer.intermediate.dense.weight
        self.linear1_bias = vilt_layer.intermediate.dense.bias
        self.linear2_weight = vilt_layer.output.dense.weight
        self.linear2_bias = vilt_layer.output.dense.bias
        self.norm1_eps = vilt_layer.layernorm_before.eps
        self.norm1_weight = vilt_layer.layernorm_before.weight
        self.norm1_bias = vilt_layer.layernorm_before.bias
        self.norm2_eps = vilt_layer.layernorm_after.eps
        self.norm2_weight = vilt_layer.layernorm_after.weight
        self.norm2_bias = vilt_layer.layernorm_after.bias
        self.num_heads = vilt_layer.attention.attention.num_attention_heads
        self.embed_dim = int(vilt_layer.attention.attention.attention_head_size * self.num_heads)
        self.is_last_layer = False
        self.norm_first = True
        self.validate_bettertransformer()

    def forward(self, hidden_states, *_, **__):
        """This is just a wrapper around the forward function proposed in: https://github.com/huggingface/transformers/pull/19553"""
        super().forward_checker()
        attention_mask = None
        hidden_states = torch._transformer_encoder_layer_fwd(hidden_states, self.embed_dim, self.num_heads, self.in_proj_weight, self.in_proj_bias, self.out_proj_weight, self.out_proj_bias, self.use_gelu, self.norm_first, self.norm1_eps, self.norm1_weight, self.norm1_bias, self.norm2_weight, self.norm2_bias, self.linear1_weight, self.linear1_bias, self.linear2_weight, self.linear2_bias, attention_mask)
        if hidden_states.is_nested and self.is_last_layer:
            hidden_states = hidden_states.to_padded_tensor(0.0)
        return (hidden_states,)


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

Class description:
v_dealhistory视图操作

Method signatures and docstrings:
- def search_by_uid(self, uid, start, end, mtlogin, page=None): 已知id，根据时间段，查询已成交订单 :param uid:用户id :param start:起始时间 :param end:结束时间 :param page:请求页 :return:queryset
- def searchsum_by_uid(self, uid, start, end, mtlogin): 已知用户id，根据时间段，查询总和 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和

Implement the Python class `VDealhistoryDao` described below.

Class description:
v_dealhistory视图操作

Method signatures and docstrings:
- def search_by_uid(self, uid, start, end, mtlogin, page=None): 已知id，根据时间段，查询已成交订单 :param uid:用户id :param start:起始时间 :param end:结束时间 :param page:请求页 :return:queryset
- def searchsum_by_uid(self, uid, start, end, mtlogin): 已知用户id，根据时间段，查询总和 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和

<|skeleton|>
class VDealhistoryDao:
    """v_dealhistory视图操作"""

    def search_by_uid(self, uid, start, end, mtlogin, page=None):
        """已知id，根据时间段，查询已成交订单 :param uid:用户id :param start:起始时间 :param end:结束时间 :param page:请求页 :return:queryset"""
        <|body_0|>

    def searchsum_by_uid(self, uid, start, end, mtlogin):
        """已知用户id，根据时间段，查询总和 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        query = self.session.query(VDealhistory.time, VDealhistory.deal, VDealhistory.positionid, VDealhistory.login, VDealhistory.symbol, VDealhistory.action, VDealhistory.entry, VDealhistory.volume, VDealhistory.price, VDealhistory.priceposition, VDealhistory.profit, VDealhistory.storage, VDealhistory.commission, VDealhistory.profitraw).filter(VDealhistory.uid == uid)
        if start and start != '' and (start != 'undefined'):
            query = query.filter(VDealhistory.time >= start)
        if end and end != '' and (end != 'undefined'):
            query = query.filter(VDealhistory.time <= end)
        if mtlogin and mtlogin != '' and (mtlogin != 'undefined'):
            query = query.filter(VDealhistory.login == mtlogin)
        if page == -1:
            return query.all()
        if not page or page == '' or page == 'undefined':
            page = 1
        return Pagination(query=query, page=page)
<|end_body_0|>

<|body_start_1|>
        query = self.session.query(VDealhistory.time, VDealhistory.login, VDealhistory.profit, VDealhistory.storage, VDealhistory.commission, VDealhistory.profitraw).filter(VDealhistory.uid == uid)
        sum_list = []
        profit_sum = 0
        storage_sum = 0
        commission_sum = 0
        profitraw_sum = 0
        if start and start != '' and (start != 'undefined'):
            query = query.filter(VDealhistory.time >= start)
        if end and end != '' and (end != 'undefined'):
            query = query.filter(VDealhistory.time <= end)
        if mtlogin and mtlogin != '' and (mtlogin != 'undefined'):
            query = query.filter(VDealhistory.login == mtlogin)
        for obj in query:
            profit_sum = profit_sum + obj.profit
            storage_sum = storage_sum + obj.storage
            commission_sum = commission_sum + obj.commission
            profitraw_sum = profitraw_sum + obj.profitraw
        sum_list.append({'profit_sum': str(profit_sum), 'storage_sum': str(storage_sum), 'commission_sum': str(commission_sum), 'profitraw_sum': str(profitraw_sum)})
        return sum_list
<|end_body_1|>

Solution:
class VDealhistoryDao:
    """v_dealhistory视图操作"""

    def search_by_uid(self, uid, start, end, mtlogin, page=None):
        """已知id，根据时间段，查询已成交订单 :param uid:用户id :param start:起始时间 :param end:结束时间 :param page:请求页 :return:queryset"""
        query = self.session.query(VDealhistory.time, VDealhistory.deal, VDealhistory.positionid, VDealhistory.login, VDealhistory.symbol, VDealhistory.action, VDealhistory.entry, VDealhistory.volume, VDealhistory.price, VDealhistory.priceposition, VDealhistory.profit, VDealhistory.storage, VDealhistory.commission, VDealhistory.profitraw).filter(VDealhistory.uid == uid)
        if start and start != '' and (start != 'undefined'):
            query = query.filter(VDealhistory.time >= start)
        if end and end != '' and (end != 'undefined'):
            query = query.filter(VDealhistory.time <= end)
        if mtlogin and mtlogin != '' and (mtlogin != 'undefined'):
            query = query.filter(VDealhistory.login == mtlogin)
        if page == -1:
            return query.all()
        if not page or page == '' or page == 'undefined':
            page = 1
        return Pagination(query=query, page=page)

    def searchsum_by_uid(self, uid, start, end, mtlogin):
        """已知用户id，根据时间段，查询总和 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和"""
        query = self.session.query(VDealhistory.time, VDealhistory.login, VDealhistory.profit, VDealhistory.storage, VDealhistory.commission, VDealhistory.profitraw).filter(VDealhistory.uid == uid)
        sum_list = []
        profit_sum = 0
        storage_sum = 0
        commission_sum = 0
        profitraw_sum = 0
        if start and start != '' and (start != 'undefined'):
            query = query.filter(VDealhistory.time >= start)
        if end and end != '' and (end != 'undefined'):
            query = query.filter(VDealhistory.time <= end)
        if mtlogin and mtlogin != '' and (mtlogin != 'undefined'):
            query = query.filter(VDealhistory.login == mtlogin)
        for obj in query:
            profit_sum = profit_sum + obj.profit
            storage_sum = storage_sum + obj.storage
            commission_sum = commission_sum + obj.commission
            profitraw_sum = profitraw_sum + obj.profitraw
        sum_list.append({'profit_sum': str(profit_sum), 'storage_sum': str(storage_sum), 'commission_sum': str(commission_sum), 'profitraw_sum': str(profitraw_sum)})
        return sum_list


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

Class description:
Build a SimSiam model.

Method signatures and docstrings:
- def __init__(self, base_encoder, dim=2048, pred_dim=512): dim: feature dimension (default: 2048) pred_dim: hidden dimension of the predictor (default: 512)
- def forward(self, x1, x2): Input: x1: first views of images x2: second views of images Output: p1, p2, z1, z2: predictors and targets of the network See Sec. 3 of https://arxiv.org/abs/2011.10566 for detailed notations

Implement the Python class `SimSiam` described below.

Class description:
Build a SimSiam model.

Method signatures and docstrings:
- def __init__(self, base_encoder, dim=2048, pred_dim=512): dim: feature dimension (default: 2048) pred_dim: hidden dimension of the predictor (default: 512)
- def forward(self, x1, x2): Input: x1: first views of images x2: second views of images Output: p1, p2, z1, z2: predictors and targets of the network See Sec. 3 of https://arxiv.org/abs/2011.10566 for detailed notations

<|skeleton|>
class SimSiam:
    """Build a SimSiam model."""

    def __init__(self, base_encoder, dim=2048, pred_dim=512):
        """dim: feature dimension (default: 2048) pred_dim: hidden dimension of the predictor (default: 512)"""
        <|body_0|>

    def forward(self, x1, x2):
        """Input: x1: first views of images x2: second views of images Output: p1, p2, z1, z2: predictors and targets of the network See Sec. 3 of https://arxiv.org/abs/2011.10566 for detailed notations"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        super(SimSiam, self).__init__()
        self.encoder = base_encoder(num_classes=dim, zero_init_residual=True)
        prev_dim = self.encoder.fc.weight.shape[1]
        self.encoder.fc = nn.Sequential(nn.Linear(prev_dim, prev_dim, bias=False), nn.BatchNorm1d(prev_dim), nn.ReLU(inplace=True), nn.Linear(prev_dim, prev_dim, bias=False), nn.BatchNorm1d(prev_dim), nn.ReLU(inplace=True), self.encoder.fc, nn.BatchNorm1d(dim, affine=False))
        self.encoder.fc[6].bias.requires_grad = False
        self.predictor = nn.Sequential(nn.Linear(dim, pred_dim, bias=False), nn.BatchNorm1d(pred_dim), nn.ReLU(inplace=True), nn.Linear(pred_dim, dim))
<|end_body_0|>

<|body_start_1|>
        z1 = self.encoder(x1)
        z2 = self.encoder(x2)
        p1 = self.predictor(z1)
        p2 = self.predictor(z2)
        return (p1, p2, z1.detach(), z2.detach())
<|end_body_1|>

Solution:
class SimSiam:
    """Build a SimSiam model."""

    def __init__(self, base_encoder, dim=2048, pred_dim=512):
        """dim: feature dimension (default: 2048) pred_dim: hidden dimension of the predictor (default: 512)"""
        super(SimSiam, self).__init__()
        self.encoder = base_encoder(num_classes=dim, zero_init_residual=True)
        prev_dim = self.encoder.fc.weight.shape[1]
        self.encoder.fc = nn.Sequential(nn.Linear(prev_dim, prev_dim, bias=False), nn.BatchNorm1d(prev_dim), nn.ReLU(inplace=True), nn.Linear(prev_dim, prev_dim, bias=False), nn.BatchNorm1d(prev_dim), nn.ReLU(inplace=True), self.encoder.fc, nn.BatchNorm1d(dim, affine=False))
        self.encoder.fc[6].bias.requires_grad = False
        self.predictor = nn.Sequential(nn.Linear(dim, pred_dim, bias=False), nn.BatchNorm1d(pred_dim), nn.ReLU(inplace=True), nn.Linear(pred_dim, dim))

    def forward(self, x1, x2):
        """Input: x1: first views of images x2: second views of images Output: p1, p2, z1, z2: predictors and targets of the network See Sec. 3 of https://arxiv.org/abs/2011.10566 for detailed notations"""
        z1 = self.encoder(x1)
        z2 = self.encoder(x2)
        p1 = self.predictor(z1)
        p2 = self.predictor(z2)
        return (p1, p2, z1.detach(), z2.detach())


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

Class description:
Throttle Class

Method signatures and docstrings:
- def __init__(self, rate=150): Create a throttle for a specific rate/sec
- def __call__(self): Return when the throttle limit is acceptable

Implement the Python class `Throttle` described below.

Class description:
Throttle Class

Method signatures and docstrings:
- def __init__(self, rate=150): Create a throttle for a specific rate/sec
- def __call__(self): Return when the throttle limit is acceptable

<|skeleton|>
class Throttle:
    """Throttle Class"""

    def __init__(self, rate=150):
        """Create a throttle for a specific rate/sec"""
        <|body_0|>

    def __call__(self):
        """Return when the throttle limit is acceptable"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.lock = Lock()
        self.rate = rate
        self.ts = None
        self.count = 0
<|end_body_0|>

<|body_start_1|>
        with self.lock:
            now = time.time()
            if self.ts is None:
                self.ts = now
            if now - self.ts >= 1.0:
                self.count = 0
                self.ts = now
            self.count += 1
            if self.count <= self.rate:
                return
            time.sleep(self.ts + 1 - now)
<|end_body_1|>

Solution:
class Throttle:
    """Throttle Class"""

    def __init__(self, rate=150):
        """Create a throttle for a specific rate/sec"""
        self.lock = Lock()
        self.rate = rate
        self.ts = None
        self.count = 0

    def __call__(self):
        """Return when the throttle limit is acceptable"""
        with self.lock:
            now = time.time()
            if self.ts is None:
                self.ts = now
            if now - self.ts >= 1.0:
                self.count = 0
                self.ts = now
            self.count += 1
            if self.count <= self.rate:
                return
            time.sleep(self.ts + 1 - now)


shortest

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

Class description:
Implement the WordDistance class.

Method signatures and docstrings:
- def __init__(self, words): initialize your data structure here. :type words: List[str]
- def shortest(self, word1, word2): Adds a word into the data structure. :type word1: str :type word2: str :rtype: int

Implement the Python class `WordDistance` described below.

Class description:
Implement the WordDistance class.

Method signatures and docstrings:
- def __init__(self, words): initialize your data structure here. :type words: List[str]
- def shortest(self, word1, word2): Adds a word into the data structure. :type word1: str :type word2: str :rtype: int

<|skeleton|>
class WordDistance:

    def __init__(self, words):
        """initialize your data structure here. :type words: List[str]"""
        <|body_0|>

    def shortest(self, word1, word2):
        """Adds a word into the data structure. :type word1: str :type word2: str :rtype: int"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.dic = dict()
        l = len(words)
        self.max = l
        for i in xrange(l):
            word = words[i]
            if word in self.dic:
                self.dic[word].append(i)
            else:
                self.dic[word] = [i]
<|end_body_0|>

<|body_start_1|>
        l1, l2 = (self.dic[word1], self.dic[word2])
        n1, n2 = (len(l1), len(l2))
        p1, p2 = (0, 0)
        ret = self.max
        while p1 < n1 and p2 < n2:
            i1, i2 = (l1[p1], l2[p2])
            if i1 < i2:
                ret = min(i2 - i1, ret)
                p1 += 1
            else:
                ret = min(i1 - i2, ret)
                p2 += 1
        return ret
<|end_body_1|>

Solution:
class WordDistance:
    def __init__(self, words):
        """initialize your data structure here. :type words: List[str]"""
        self.dic = dict()
        l = len(words)
        self.max = l
        for i in xrange(l):
            word = words[i]
            if word in self.dic:
                self.dic[word].append(i)
            else:
                self.dic[word] = [i]

    def shortest(self, word1, word2):
        """Adds a word into the data structure. :type word1: str :type word2: str :rtype: int"""
        l1, l2 = (self.dic[word1], self.dic[word2])
        n1, n2 = (len(l1), len(l2))
        p1, p2 = (0, 0)
        ret = self.max
        while p1 < n1 and p2 < n2:
            i1, i2 = (l1[p1], l2[p2])
            if i1 < i2:
                ret = min(i2 - i1, ret)
                p1 += 1
            else:
                ret = min(i1 - i2, ret)
                p2 += 1
        return ret


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

Class description:
Represents a file system data crawler. Examples: Suppose we have the following directory structure:: /path/to/root_dir ./Patient1 ./Image.mha ./GroundTruth.mha ./some_text_file.txt ./Patient2 ./Image.mha ./GroundTruth.mha ./GroundTruthRater2.mha ./Atlas ./Atlas.mha We can use the following code to load the images `Image.mha` and `GroundTruth.mha` in the directories `Patient1` and `Patient2`: >>> class MyImgType(enum.Enum): >>> T1 = 1 >>> GroundTruth = 2 >>> >>> class MyFilePathGenerator(FilePathGenerator): >>> @staticmethod >>> def get_full_file_path(id_: str, root_dir: str, file_key, file_extension: str) -> str: >>> if file_key == MyImgType.T1: >>> file_name = 'Image' >>> elif file_key == M

Method signatures and docstrings:
- def __init__(self, root_dir: str, file_keys: list, file_path_generator: FilePathGenerator, dir_filter: DirectoryFilter=None, file_extension: str='.nii.gz'): Initializes a new instance of the FileSystemDataCrawler class. Args: root_dir (str): The path to the root directory, which contains subdirectories with the data. file_keys (list): A list of objects, which represent human readable data identifiers (one identifier for each data file to crawl). file_path_generator (FilePathGenerator): A file path generator, which converts a human readable data identifier to an data file path. dir_filter (DirectoryFilter): A directory filter, which filters a list of directories. file_extension (str): The data file extension (with or without dot).
- def _crawl_data(self, data_dir: dict): Crawls the data inside a directory.
- def _crawl_directories(self): Crawls the directories, which contain data. Returns: dict: A dictionary where the keys are the directory names and the values the full path to the directory.

Implement the Python class `FileSystemDataCrawler` described below.

Class description:
Represents a file system data crawler. Examples: Suppose we have the following directory structure:: /path/to/root_dir ./Patient1 ./Image.mha ./GroundTruth.mha ./some_text_file.txt ./Patient2 ./Image.mha ./GroundTruth.mha ./GroundTruthRater2.mha ./Atlas ./Atlas.mha We can use the following code to load the images `Image.mha` and `GroundTruth.mha` in the directories `Patient1` and `Patient2`: >>> class MyImgType(enum.Enum): >>> T1 = 1 >>> GroundTruth = 2 >>> >>> class MyFilePathGenerator(FilePathGenerator): >>> @staticmethod >>> def get_full_file_path(id_: str, root_dir: str, file_key, file_extension: str) -> str: >>> if file_key == MyImgType.T1: >>> file_name = 'Image' >>> elif file_key == M

Method signatures and docstrings:
- def __init__(self, root_dir: str, file_keys: list, file_path_generator: FilePathGenerator, dir_filter: DirectoryFilter=None, file_extension: str='.nii.gz'): Initializes a new instance of the FileSystemDataCrawler class. Args: root_dir (str): The path to the root directory, which contains subdirectories with the data. file_keys (list): A list of objects, which represent human readable data identifiers (one identifier for each data file to crawl). file_path_generator (FilePathGenerator): A file path generator, which converts a human readable data identifier to an data file path. dir_filter (DirectoryFilter): A directory filter, which filters a list of directories. file_extension (str): The data file extension (with or without dot).
- def _crawl_data(self, data_dir: dict): Crawls the data inside a directory.
- def _crawl_directories(self): Crawls the directories, which contain data. Returns: dict: A dictionary where the keys are the directory names and the values the full path to the directory.

<|skeleton|>
class FileSystemDataCrawler:
    """Represents a file system data crawler. Examples: Suppose we have the following directory structure:: /path/to/root_dir ./Patient1 ./Image.mha ./GroundTruth.mha ./some_text_file.txt ./Patient2 ./Image.mha ./GroundTruth.mha ./GroundTruthRater2.mha ./Atlas ./Atlas.mha We can use the following code to load the images `Image.mha` and `GroundTruth.mha` in the directories `Patient1` and `Patient2`: >>> class MyImgType(enum.Enum): >>> T1 = 1 >>> GroundTruth = 2 >>> >>> class MyFilePathGenerator(FilePathGenerator): >>> @staticmethod >>> def get_full_file_path(id_: str, root_dir: str, file_key, file_extension: str) -> str: >>> if file_key == MyImgType.T1: >>> file_name = 'Image' >>> elif file_key == M"""

    def __init__(self, root_dir: str, file_keys: list, file_path_generator: FilePathGenerator, dir_filter: DirectoryFilter=None, file_extension: str='.nii.gz'):
        """Initializes a new instance of the FileSystemDataCrawler class. Args: root_dir (str): The path to the root directory, which contains subdirectories with the data. file_keys (list): A list of objects, which represent human readable data identifiers (one identifier for each data file to crawl). file_path_generator (FilePathGenerator): A file path generator, which converts a human readable data identifier to an data file path. dir_filter (DirectoryFilter): A directory filter, which filters a list of directories. file_extension (str): The data file extension (with or without dot)."""
        <|body_0|>

    def _crawl_data(self, data_dir: dict):
        """Crawls the data inside a directory."""
        <|body_1|>

    def _crawl_directories(self):
        """Crawls the directories, which contain data. Returns: dict: A dictionary where the keys are the directory names and the values the full path to the directory."""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        super().__init__()
        self.root_dir = root_dir
        self.dir_filter = dir_filter
        self.file_keys = file_keys
        self.file_path_generator = file_path_generator
        self.file_extension = file_extension if file_extension.startswith('.') else '.' + file_extension
        self.data = {}
        data_dir = self._crawl_directories()
        self._crawl_data(data_dir)
<|end_body_0|>

<|body_start_1|>
        for id_, path in data_dir.items():
            data_dict = {id_: path}
            for item in self.file_keys:
                file_path = self.file_path_generator.get_full_file_path(id_, path, item, self.file_extension)
                data_dict[item] = file_path
            self.data[id_] = data_dict
<|end_body_1|>

<|body_start_2|>
        if not os.path.isdir(self.root_dir):
            raise ValueError('root_dir {} does not exist'.format(self.root_dir))
        data_dirs = next(os.walk(self.root_dir))[1]
        if self.dir_filter:
            data_dirs = self.dir_filter.filter_directories(data_dirs)
        return {data_dir: os.path.join(self.root_dir, data_dir) for data_dir in data_dirs if any((file.endswith(self.file_extension) for file in os.listdir(os.path.join(self.root_dir, data_dir))))}
<|end_body_2|>

Solution:
class FileSystemDataCrawler:
    """Represents a file system data crawler. Examples: Suppose we have the following directory structure:: /path/to/root_dir ./Patient1 ./Image.mha ./GroundTruth.mha ./some_text_file.txt ./Patient2 ./Image.mha ./GroundTruth.mha ./GroundTruthRater2.mha ./Atlas ./Atlas.mha We can use the following code to load the images `Image.mha` and `GroundTruth.mha` in the directories `Patient1` and `Patient2`: >>> class MyImgType(enum.Enum): >>> T1 = 1 >>> GroundTruth = 2 >>> >>> class MyFilePathGenerator(FilePathGenerator): >>> @staticmethod >>> def get_full_file_path(id_: str, root_dir: str, file_key, file_extension: str) -> str: >>> if file_key == MyImgType.T1: >>> file_name = 'Image' >>> elif file_key == M"""

    def __init__(self, root_dir: str, file_keys: list, file_path_generator: FilePathGenerator, dir_filter: DirectoryFilter=None, file_extension: str='.nii.gz'):
        """Initializes a new instance of the FileSystemDataCrawler class. Args: root_dir (str): The path to the root directory, which contains subdirectories with the data. file_keys (list): A list of objects, which represent human readable data identifiers (one identifier for each data file to crawl). file_path_generator (FilePathGenerator): A file path generator, which converts a human readable data identifier to an data file path. dir_filter (DirectoryFilter): A directory filter, which filters a list of directories. file_extension (str): The data file extension (with or without dot)."""
        super().__init__()
        self.root_dir = root_dir
        self.dir_filter = dir_filter
        self.file_keys = file_keys
        self.file_path_generator = file_path_generator
        self.file_extension = file_extension if file_extension.startswith('.') else '.' + file_extension
        self.data = {}
        data_dir = self._crawl_directories()
        self._crawl_data(data_dir)

    def _crawl_data(self, data_dir: dict):
        """Crawls the data inside a directory."""
        for id_, path in data_dir.items():
            data_dict = {id_: path}
            for item in self.file_keys:
                file_path = self.file_path_generator.get_full_file_path(id_, path, item, self.file_extension)
                data_dict[item] = file_path
            self.data[id_] = data_dict

    def _crawl_directories(self):
        """Crawls the directories, which contain data. Returns: dict: A dictionary where the keys are the directory names and the values the full path to the directory."""
        if not os.path.isdir(self.root_dir):
            raise ValueError('root_dir {} does not exist'.format(self.root_dir))
        data_dirs = next(os.walk(self.root_dir))[1]
        if self.dir_filter:
            data_dirs = self.dir_filter.filter_directories(data_dirs)
        return {data_dir: os.path.join(self.root_dir, data_dir) for data_dir in data_dirs if any((file.endswith(self.file_extension) for file in os.listdir(os.path.join(self.root_dir, data_dir))))}


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

Class description:
Information about the test instance for a single uplink/downlink traffic channel

Method signatures and docstrings:
- def __init__(self, is_uplink, is_udp, duration, ip, port): Create a traffic test instance with the given values Args: is_uplink (bool): whether the test is uplink (else downlink) is_udp (bool): whether the test is UDP (else TCP) duration (int): the duration of the test, in seconds ip (ipaddress.ip_address): the IP of the test device (UE) port (int): the port number of the test device (UE)
- def __repr__(self): String representation of this test instance

Implement the Python class `TrafficTestInstance` described below.

Class description:
Information about the test instance for a single uplink/downlink traffic channel

Method signatures and docstrings:
- def __init__(self, is_uplink, is_udp, duration, ip, port): Create a traffic test instance with the given values Args: is_uplink (bool): whether the test is uplink (else downlink) is_udp (bool): whether the test is UDP (else TCP) duration (int): the duration of the test, in seconds ip (ipaddress.ip_address): the IP of the test device (UE) port (int): the port number of the test device (UE)
- def __repr__(self): String representation of this test instance

<|skeleton|>
class TrafficTestInstance:
    """Information about the test instance for a single uplink/downlink traffic channel"""

    def __init__(self, is_uplink, is_udp, duration, ip, port):
        """Create a traffic test instance with the given values Args: is_uplink (bool): whether the test is uplink (else downlink) is_udp (bool): whether the test is UDP (else TCP) duration (int): the duration of the test, in seconds ip (ipaddress.ip_address): the IP of the test device (UE) port (int): the port number of the test device (UE)"""
        <|body_0|>

    def __repr__(self):
        """String representation of this test instance"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.duration = duration
        self.ip = ip
        self.is_udp = is_udp
        self.is_uplink = is_uplink
        self.port = port
<|end_body_0|>

<|body_start_1|>
        link_type = 'UPLINK' if self.is_uplink else 'DOWNLINK'
        protocol = 'UDP' if self.is_udp else 'TCP'
        return f'{type(self).__name__}: {link_type} {protocol} test, {self.duration} seconds for test device at {self.ip.exploded}:{self.port}'
<|end_body_1|>

Solution:
class TrafficTestInstance:
    """Information about the test instance for a single uplink/downlink traffic channel"""

    def __init__(self, is_uplink, is_udp, duration, ip, port):
        """Create a traffic test instance with the given values Args: is_uplink (bool): whether the test is uplink (else downlink) is_udp (bool): whether the test is UDP (else TCP) duration (int): the duration of the test, in seconds ip (ipaddress.ip_address): the IP of the test device (UE) port (int): the port number of the test device (UE)"""
        self.duration = duration
        self.ip = ip
        self.is_udp = is_udp
        self.is_uplink = is_uplink
        self.port = port

    def __repr__(self):
        """String representation of this test instance"""
        link_type = 'UPLINK' if self.is_uplink else 'DOWNLINK'
        protocol = 'UDP' if self.is_udp else 'TCP'
        return f'{type(self).__name__}: {link_type} {protocol} test, {self.duration} seconds for test device at {self.ip.exploded}:{self.port}'


Run

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

Class description:
Delete Compute Engine security policy rules. *{command}* is used to delete security policy rules. ## EXAMPLES To delete the rule at priority 1000, run: $ {command} 1000 \\ --security-policy=my-policy

Method signatures and docstrings:
- def Args(cls, parser, support_regional_security_policy, support_net_lb): Generates the flagset for a Delete command.
- def Run(cls, release_track, args, support_regional_security_policy, support_net_lb): Validates arguments and deletes security policy rule(s).

Implement the Python class `DeleteHelper` described below.

Class description:
Delete Compute Engine security policy rules. *{command}* is used to delete security policy rules. ## EXAMPLES To delete the rule at priority 1000, run: $ {command} 1000 \\ --security-policy=my-policy

Method signatures and docstrings:
- def Args(cls, parser, support_regional_security_policy, support_net_lb): Generates the flagset for a Delete command.
- def Run(cls, release_track, args, support_regional_security_policy, support_net_lb): Validates arguments and deletes security policy rule(s).

<|skeleton|>
class DeleteHelper:
    """Delete Compute Engine security policy rules. *{command}* is used to delete security policy rules. ## EXAMPLES To delete the rule at priority 1000, run: $ {command} 1000 \\ --security-policy=my-policy"""

    def Args(cls, parser, support_regional_security_policy, support_net_lb):
        """Generates the flagset for a Delete command."""
        <|body_0|>

    def Run(cls, release_track, args, support_regional_security_policy, support_net_lb):
        """Validates arguments and deletes security policy rule(s)."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if support_regional_security_policy or support_net_lb:
            cls.NAME_ARG = flags.PriorityArgument('delete', is_plural=True)
            cls.NAME_ARG.AddArgument(parser, operation_type='delete', cust_metavar='PRIORITY')
            flags.AddRegionFlag(parser, 'delete')
            cls.SECURITY_POLICY_ARG = security_policies_flags.SecurityPolicyMultiScopeArgumentForRules()
        else:
            flags.AddPriority(parser, 'delete', is_plural=True)
            cls.SECURITY_POLICY_ARG = security_policies_flags.SecurityPolicyArgumentForRules()
        cls.SECURITY_POLICY_ARG.AddArgument(parser)
        parser.display_info.AddCacheUpdater(security_policies_flags.SecurityPoliciesCompleter)
<|end_body_0|>

<|body_start_1|>
        holder = base_classes.ComputeApiHolder(release_track)
        refs = []
        if support_regional_security_policy or support_net_lb:
            if args.security_policy:
                security_policy_ref = cls.SECURITY_POLICY_ARG.ResolveAsResource(args, holder.resources, default_scope=compute_scope.ScopeEnum.GLOBAL)
                if getattr(security_policy_ref, 'region', None) is not None:
                    for name in args.names:
                        refs.append(holder.resources.Parse(name, collection='compute.regionSecurityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail, 'region': security_policy_ref.region, 'securityPolicy': args.security_policy}))
                else:
                    for name in args.names:
                        refs.append(holder.resources.Parse(name, collection='compute.securityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail, 'securityPolicy': args.security_policy}))
            else:
                for name in args.names:
                    try:
                        refs.append(holder.resources.Parse(name, collection='compute.regionSecurityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail, 'region': getattr(args, 'region', None)}))
                    except (resources.RequiredFieldOmittedException, resources.WrongResourceCollectionException):
                        refs.append(holder.resources.Parse(name, collection='compute.securityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail}))
        else:
            for name in args.names:
                refs.append(holder.resources.Parse(name, collection='compute.securityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail, 'securityPolicy': args.security_policy}))
        utils.PromptForDeletion(refs)
        requests = []
        for ref in refs:
            security_policy_rule = client.SecurityPolicyRule(ref, compute_client=holder.client)
            requests.extend(security_policy_rule.Delete(only_generate_request=True))
        return holder.client.MakeRequests(requests)
<|end_body_1|>

Solution:
class DeleteHelper:
    """Delete Compute Engine security policy rules. *{command}* is used to delete security policy rules. ## EXAMPLES To delete the rule at priority 1000, run: $ {command} 1000 \\ --security-policy=my-policy"""

    def Args(cls, parser, support_regional_security_policy, support_net_lb):
        """Generates the flagset for a Delete command."""
        if support_regional_security_policy or support_net_lb:
            cls.NAME_ARG = flags.PriorityArgument('delete', is_plural=True)
            cls.NAME_ARG.AddArgument(parser, operation_type='delete', cust_metavar='PRIORITY')
            flags.AddRegionFlag(parser, 'delete')
            cls.SECURITY_POLICY_ARG = security_policies_flags.SecurityPolicyMultiScopeArgumentForRules()
        else:
            flags.AddPriority(parser, 'delete', is_plural=True)
            cls.SECURITY_POLICY_ARG = security_policies_flags.SecurityPolicyArgumentForRules()
        cls.SECURITY_POLICY_ARG.AddArgument(parser)
        parser.display_info.AddCacheUpdater(security_policies_flags.SecurityPoliciesCompleter)

    def Run(cls, release_track, args, support_regional_security_policy, support_net_lb):
        """Validates arguments and deletes security policy rule(s)."""
        holder = base_classes.ComputeApiHolder(release_track)
        refs = []
        if support_regional_security_policy or support_net_lb:
            if args.security_policy:
                security_policy_ref = cls.SECURITY_POLICY_ARG.ResolveAsResource(args, holder.resources, default_scope=compute_scope.ScopeEnum.GLOBAL)
                if getattr(security_policy_ref, 'region', None) is not None:
                    for name in args.names:
                        refs.append(holder.resources.Parse(name, collection='compute.regionSecurityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail, 'region': security_policy_ref.region, 'securityPolicy': args.security_policy}))
                else:
                    for name in args.names:
                        refs.append(holder.resources.Parse(name, collection='compute.securityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail, 'securityPolicy': args.security_policy}))
            else:
                for name in args.names:
                    try:
                        refs.append(holder.resources.Parse(name, collection='compute.regionSecurityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail, 'region': getattr(args, 'region', None)}))
                    except (resources.RequiredFieldOmittedException, resources.WrongResourceCollectionException):
                        refs.append(holder.resources.Parse(name, collection='compute.securityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail}))
        else:
            for name in args.names:
                refs.append(holder.resources.Parse(name, collection='compute.securityPolicyRules', params={'project': properties.VALUES.core.project.GetOrFail, 'securityPolicy': args.security_policy}))
        utils.PromptForDeletion(refs)
        requests = []
        for ref in refs:
            security_policy_rule = client.SecurityPolicyRule(ref, compute_client=holder.client)
            requests.extend(security_policy_rule.Delete(only_generate_request=True))
        return holder.client.MakeRequests(requests)


provenance

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

Class description:
Implement the Get_Boston_Landmark class.

Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Create the provenance document describing everything happening in this script. Each run of the script will generate a new document describing that invocation event.

Implement the Python class `Get_Boston_Landmark` described below.

Class description:
Implement the Get_Boston_Landmark class.

Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Create the provenance document describing everything happening in this script. Each run of the script will generate a new document describing that invocation event.

<|skeleton|>
class Get_Boston_Landmark:

    def execute(trial=False):
        """Retrieve some data sets (not using the API here for the sake of simplicity)."""
        <|body_0|>

    def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
        """Create the provenance document describing everything happening in this script. Each run of the script will generate a new document describing that invocation event."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        startTime = datetime.datetime.now()
        client = dml.pymongo.MongoClient()
        repo = client.repo
        repo.authenticate('hxjia_jiahaozh', 'hxjia_jiahaozh')
        url = 'http://bostonopendata-boston.opendata.arcgis.com/datasets/7a7aca614ad740e99b060e0ee787a228_3.csv'
        bl = pd.read_csv(url)
        new_bl = pd.DataFrame({'Name': bl['Name_of_Pr'], 'Address': bl['Address'], 'Neighborhood': bl['Neighborho']})
        r = json.loads(new_bl.to_json(orient='records'))
        repo.dropCollection('Boston_Landmarks')
        repo.createCollection('Boston_Landmarks')
        repo['hxjia_jiahaozh.Boston_Landmarks'].insert_many(r)
        repo['hxjia_jiahaozh.Boston_Landmarks'].metadata({'complete': True})
        print(repo['hxjia_jiahaozh.Boston_Landmarks'].metadata())
        repo.logout()
        endTime = datetime.datetime.now()
        return {'start': startTime, 'end': endTime}
<|end_body_0|>

<|body_start_1|>
        client = dml.pymongo.MongoClient()
        repo = client.repo
        repo.authenticate('hxjia_jiahaozh', 'hxjia_jiahaozh')
        doc.add_namespace('alg', 'http://datamechanics.io/algorithm/hxjia_jiahaozh/bostonlandmark')
        doc.add_namespace('dat', 'http://datamechanics.io/data/hxjia_jiahaozh/landmark')
        doc.add_namespace('ont', 'http://datamechanics.io/ontology#')
        doc.add_namespace('log', 'http://datamechanics.io/log/')
        doc.add_namespace('bdp', 'http://bostonopendata-boston.opendata.arcgis.com/datasets/')
        this_script = doc.agent('alg:hxjia_jiahaozh#get_boston_landmark', {prov.model.PROV_TYPE: prov.model.PROV['SoftwareAgent'], 'ont:Extension': 'py'})
        resource = doc.entity('bdp:7a7aca614ad740e99b060e0ee787a228_3', {'prov:label': 'Boston_Landmarks, Service Requests', prov.model.PROV_TYPE: 'ont:DataResource', 'ont:Extension': 'csv'})
        get_landmarks = doc.activity('log:uuid' + str(uuid.uuid4()), startTime, endTime)
        doc.wasAssociatedWith(get_landmarks, this_script)
        doc.usage(get_landmarks, resource, startTime, None, {prov.model.PROV_TYPE: 'ont:Retrieval', 'ont:Query': '?type=Boston+Landmarks&$select=Name,Address,Neighborhood'})
        landmarks = doc.entity('dat:hxjia_jiahaozh#landmarks', {prov.model.PROV_LABEL: 'Boston Landmarks', prov.model.PROV_TYPE: 'ont:DataSet'})
        doc.wasAttributedTo(landmarks, this_script)
        doc.wasGeneratedBy(landmarks, get_landmarks, endTime)
        doc.wasDerivedFrom(landmarks, resource, get_landmarks, get_landmarks, get_landmarks)
        repo.logout()
        return doc
<|end_body_1|>

Solution:
class Get_Boston_Landmark:
    def execute(trial=False):
        """Retrieve some data sets (not using the API here for the sake of simplicity)."""
        startTime = datetime.datetime.now()
        client = dml.pymongo.MongoClient()
        repo = client.repo
        repo.authenticate('hxjia_jiahaozh', 'hxjia_jiahaozh')
        url = 'http://bostonopendata-boston.opendata.arcgis.com/datasets/7a7aca614ad740e99b060e0ee787a228_3.csv'
        bl = pd.read_csv(url)
        new_bl = pd.DataFrame({'Name': bl['Name_of_Pr'], 'Address': bl['Address'], 'Neighborhood': bl['Neighborho']})
        r = json.loads(new_bl.to_json(orient='records'))
        repo.dropCollection('Boston_Landmarks')
        repo.createCollection('Boston_Landmarks')
        repo['hxjia_jiahaozh.Boston_Landmarks'].insert_many(r)
        repo['hxjia_jiahaozh.Boston_Landmarks'].metadata({'complete': True})
        print(repo['hxjia_jiahaozh.Boston_Landmarks'].metadata())
        repo.logout()
        endTime = datetime.datetime.now()
        return {'start': startTime, 'end': endTime}

    def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
        """Create the provenance document describing everything happening in this script. Each run of the script will generate a new document describing that invocation event."""
        client = dml.pymongo.MongoClient()
        repo = client.repo
        repo.authenticate('hxjia_jiahaozh', 'hxjia_jiahaozh')
        doc.add_namespace('alg', 'http://datamechanics.io/algorithm/hxjia_jiahaozh/bostonlandmark')
        doc.add_namespace('dat', 'http://datamechanics.io/data/hxjia_jiahaozh/landmark')
        doc.add_namespace('ont', 'http://datamechanics.io/ontology#')
        doc.add_namespace('log', 'http://datamechanics.io/log/')
        doc.add_namespace('bdp', 'http://bostonopendata-boston.opendata.arcgis.com/datasets/')
        this_script = doc.agent('alg:hxjia_jiahaozh#get_boston_landmark', {prov.model.PROV_TYPE: prov.model.PROV['SoftwareAgent'], 'ont:Extension': 'py'})
        resource = doc.entity('bdp:7a7aca614ad740e99b060e0ee787a228_3', {'prov:label': 'Boston_Landmarks, Service Requests', prov.model.PROV_TYPE: 'ont:DataResource', 'ont:Extension': 'csv'})
        get_landmarks = doc.activity('log:uuid' + str(uuid.uuid4()), startTime, endTime)
        doc.wasAssociatedWith(get_landmarks, this_script)
        doc.usage(get_landmarks, resource, startTime, None, {prov.model.PROV_TYPE: 'ont:Retrieval', 'ont:Query': '?type=Boston+Landmarks&$select=Name,Address,Neighborhood'})
        landmarks = doc.entity('dat:hxjia_jiahaozh#landmarks', {prov.model.PROV_LABEL: 'Boston Landmarks', prov.model.PROV_TYPE: 'ont:DataSet'})
        doc.wasAttributedTo(landmarks, this_script)
        doc.wasGeneratedBy(landmarks, get_landmarks, endTime)
        doc.wasDerivedFrom(landmarks, resource, get_landmarks, get_landmarks, get_landmarks)
        repo.logout()
        return doc


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

Class description:
Implement the NativeSolution class.

Method signatures and docstrings:
- def next_step(current, towers): The following algorithm will try to identify the next best step :param current: :param towers: :return:
- def is_hopable(towers): Check if a given seq can be hap till user in position 0 will be able to jump outside the seq :param towers: list of integers describes set of towers :return: Boolean

Implement the Python class `NativeSolution` described below.

Class description:
Implement the NativeSolution class.

Method signatures and docstrings:
- def next_step(current, towers): The following algorithm will try to identify the next best step :param current: :param towers: :return:
- def is_hopable(towers): Check if a given seq can be hap till user in position 0 will be able to jump outside the seq :param towers: list of integers describes set of towers :return: Boolean

<|skeleton|>
class NativeSolution:

    def next_step(current, towers):
        """The following algorithm will try to identify the next best step :param current: :param towers: :return:"""
        <|body_0|>

    def is_hopable(towers):
        """Check if a given seq can be hap till user in position 0 will be able to jump outside the seq :param towers: list of integers describes set of towers :return: Boolean"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if current + towers[current] >= len(towers):
            return current + towers[current]
        sub = towers[current + 1:current + towers[current] + 1]
        options = []
        for i, v in enumerate(sub):
            if v == 0:
                options.append(v)
            else:
                options.append(v + i)
        if options:
            sub_next = options.index(max(options))
            current += sub_next + 1
        return current
<|end_body_0|>

<|body_start_1|>
        if len(towers) == 0 or towers[0] == 0:
            return False
        print('Testing {}'.format(towers))
        current = 0
        count = 0
        while True:
            if current >= len(towers):
                print('hopping with {} numbers of jumps'.format(count))
                return True
            if towers[current] == 0:
                return False
            count += 1
            current = NativeSolution.next_step(current, towers)
<|end_body_1|>

Solution:
class NativeSolution:
    def next_step(current, towers):
        """The following algorithm will try to identify the next best step :param current: :param towers: :return:"""
        if current + towers[current] >= len(towers):
            return current + towers[current]
        sub = towers[current + 1:current + towers[current] + 1]
        options = []
        for i, v in enumerate(sub):
            if v == 0:
                options.append(v)
            else:
                options.append(v + i)
        if options:
            sub_next = options.index(max(options))
            current += sub_next + 1
        return current

    def is_hopable(towers):
        """Check if a given seq can be hap till user in position 0 will be able to jump outside the seq :param towers: list of integers describes set of towers :return: Boolean"""
        if len(towers) == 0 or towers[0] == 0:
            return False
        print('Testing {}'.format(towers))
        current = 0
        count = 0
        while True:
            if current >= len(towers):
                print('hopping with {} numbers of jumps'.format(count))
                return True
            if towers[current] == 0:
                return False
            count += 1
            current = NativeSolution.next_step(current, towers)


migrate

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

Class description:
Implement the BackupMigrationExecutor class.

Method signatures and docstrings:
- def migrate(self, targets, plan=None, fake=False, fake_initial=False): Migrates the database up to the given targets. Django first needs to create all project states before a migration is (un)applied and in a second step run all the database operations.
- def _migrate_all_forwards(self, plan, full_plan, fake, fake_initial): Take a list of 2-tuples of the form (migration instance, False) and apply them in the order they occur in the full_plan.

Implement the Python class `BackupMigrationExecutor` described below.

Class description:
Implement the BackupMigrationExecutor class.

Method signatures and docstrings:
- def migrate(self, targets, plan=None, fake=False, fake_initial=False): Migrates the database up to the given targets. Django first needs to create all project states before a migration is (un)applied and in a second step run all the database operations.
- def _migrate_all_forwards(self, plan, full_plan, fake, fake_initial): Take a list of 2-tuples of the form (migration instance, False) and apply them in the order they occur in the full_plan.

<|skeleton|>
class BackupMigrationExecutor:

    def migrate(self, targets, plan=None, fake=False, fake_initial=False):
        """Migrates the database up to the given targets. Django first needs to create all project states before a migration is (un)applied and in a second step run all the database operations."""
        <|body_0|>

    def _migrate_all_forwards(self, plan, full_plan, fake, fake_initial):
        """Take a list of 2-tuples of the form (migration instance, False) and apply them in the order they occur in the full_plan."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if plan is None:
            plan = self.migration_plan(targets)
        full_plan = self.migration_plan(self.loader.graph.leaf_nodes(), clean_start=True)
        state = self._migrate_all_forwards(plan, full_plan, fake=fake, fake_initial=fake_initial)
        self.check_replacements()
        return state
<|end_body_0|>

<|body_start_1|>
        migrations_to_run = {m[0] for m in plan}
        state = ProjectState(real_apps=list(self.loader.unmigrated_apps))
        for migration, _ in full_plan:
            if not migrations_to_run:
                break
            if migration in migrations_to_run:
                if 'apps' not in state.__dict__:
                    if self.progress_callback:
                        self.progress_callback('render_start')
                    state.apps
                    if self.progress_callback:
                        self.progress_callback('render_success')
                state = self.apply_migration(state, migration, fake=fake, fake_initial=fake_initial)
                migrations_to_run.remove(migration)
        return state
<|end_body_1|>

Solution:
class BackupMigrationExecutor:
    def migrate(self, targets, plan=None, fake=False, fake_initial=False):
        """Migrates the database up to the given targets. Django first needs to create all project states before a migration is (un)applied and in a second step run all the database operations."""
        if plan is None:
            plan = self.migration_plan(targets)
        full_plan = self.migration_plan(self.loader.graph.leaf_nodes(), clean_start=True)
        state = self._migrate_all_forwards(plan, full_plan, fake=fake, fake_initial=fake_initial)
        self.check_replacements()
        return state

    def _migrate_all_forwards(self, plan, full_plan, fake, fake_initial):
        """Take a list of 2-tuples of the form (migration instance, False) and apply them in the order they occur in the full_plan."""
        migrations_to_run = {m[0] for m in plan}
        state = ProjectState(real_apps=list(self.loader.unmigrated_apps))
        for migration, _ in full_plan:
            if not migrations_to_run:
                break
            if migration in migrations_to_run:
                if 'apps' not in state.__dict__:
                    if self.progress_callback:
                        self.progress_callback('render_start')
                    state.apps
                    if self.progress_callback:
                        self.progress_callback('render_success')
                state = self.apply_migration(state, migration, fake=fake, fake_initial=fake_initial)
                migrations_to_run.remove(migration)
        return state


divide

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

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def divide(self, dividend, divisor): :type dividend: int :type divisor: int :rtype: int
- def divide__shift(self, dividend, divisor): :type dividend: int :type divisor: int :rtype: int

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def divide(self, dividend, divisor): :type dividend: int :type divisor: int :rtype: int
- def divide__shift(self, dividend, divisor): :type dividend: int :type divisor: int :rtype: int

<|skeleton|>
class Solution:

    def divide(self, dividend, divisor):
        """:type dividend: int :type divisor: int :rtype: int"""
        <|body_0|>

    def divide__shift(self, dividend, divisor):
        """:type dividend: int :type divisor: int :rtype: int"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if not divisor or (dividend == -2 ** 31 and divisor == -1) or (dividend == 2 ** 31 and divisor == 1):
            return 2 ** 31 - 1
        result = 0
        sign = dividend * divisor < 0
        dividendabs = abs(dividend)
        divisorabs = abs(divisor)
        while divisorabs <= dividendabs:
            temp, doubles = (divisorabs, 1)
            while temp << 1 <= dividendabs:
                temp <<= 1
                doubles <<= 1
            dividendabs -= temp
            result += doubles
        return -1 * result if sign else result
<|end_body_0|>

<|body_start_1|>
        if not divisor or (dividend == -2 ** 31 and divisor == -1) or (dividend == 2 ** 31 and divisor == 1):
            return 2 ** 31 - 1
        dividendabs = abs(dividend)
        divisorabs = abs(divisor)
        maxShiftDigit = 0
        while divisorabs << maxShiftDigit <= dividendabs:
            maxShiftDigit += 1
        sign, result = (dividend * divisor < 0, 0)
        for i in range(maxShiftDigit - 1, -1, -1):
            shiftValue = divisorabs << i
            if shiftValue <= dividendabs:
                result += 1 << i
                dividendabs -= shiftValue
        return -1 * result if sign else result
<|end_body_1|>

Solution:
class Solution:
    def divide(self, dividend, divisor):
        """:type dividend: int :type divisor: int :rtype: int"""
        if not divisor or (dividend == -2 ** 31 and divisor == -1) or (dividend == 2 ** 31 and divisor == 1):
            return 2 ** 31 - 1
        result = 0
        sign = dividend * divisor < 0
        dividendabs = abs(dividend)
        divisorabs = abs(divisor)
        while divisorabs <= dividendabs:
            temp, doubles = (divisorabs, 1)
            while temp << 1 <= dividendabs:
                temp <<= 1
                doubles <<= 1
            dividendabs -= temp
            result += doubles
        return -1 * result if sign else result

    def divide__shift(self, dividend, divisor):
        """:type dividend: int :type divisor: int :rtype: int"""
        if not divisor or (dividend == -2 ** 31 and divisor == -1) or (dividend == 2 ** 31 and divisor == 1):
            return 2 ** 31 - 1
        dividendabs = abs(dividend)
        divisorabs = abs(divisor)
        maxShiftDigit = 0
        while divisorabs << maxShiftDigit <= dividendabs:
            maxShiftDigit += 1
        sign, result = (dividend * divisor < 0, 0)
        for i in range(maxShiftDigit - 1, -1, -1):
            shiftValue = divisorabs << i
            if shiftValue <= dividendabs:
                result += 1 << i
                dividendabs -= shiftValue
        return -1 * result if sign else result


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

Class description:
Implementation of the 'PodInfo_PodSpec_VolumeInfo_AzureFile' model. TODO: type description here. Attributes: read_only (string): TODO: Type description here. secret_name (string): TODO: Type description here. share_name (string): TODO: Type description here.

Method signatures and docstrings:
- def __init__(self, read_only=None, secret_name=None, share_name=None): Constructor for the PodInfo_PodSpec_VolumeInfo_AzureFile class
- def from_dictionary(cls, dictionary): Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as obtained from the deserialization of the server's response. The keys MUST match property names in the API description. Returns: object: An instance of this structure class.

Implement the Python class `PodInfo_PodSpec_VolumeInfo_AzureFile` described below.

Class description:
Implementation of the 'PodInfo_PodSpec_VolumeInfo_AzureFile' model. TODO: type description here. Attributes: read_only (string): TODO: Type description here. secret_name (string): TODO: Type description here. share_name (string): TODO: Type description here.

Method signatures and docstrings:
- def __init__(self, read_only=None, secret_name=None, share_name=None): Constructor for the PodInfo_PodSpec_VolumeInfo_AzureFile class
- def from_dictionary(cls, dictionary): Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as obtained from the deserialization of the server's response. The keys MUST match property names in the API description. Returns: object: An instance of this structure class.

<|skeleton|>
class PodInfo_PodSpec_VolumeInfo_AzureFile:
    """Implementation of the 'PodInfo_PodSpec_VolumeInfo_AzureFile' model. TODO: type description here. Attributes: read_only (string): TODO: Type description here. secret_name (string): TODO: Type description here. share_name (string): TODO: Type description here."""

    def __init__(self, read_only=None, secret_name=None, share_name=None):
        """Constructor for the PodInfo_PodSpec_VolumeInfo_AzureFile class"""
        <|body_0|>

    def from_dictionary(cls, dictionary):
        """Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as obtained from the deserialization of the server's response. The keys MUST match property names in the API description. Returns: object: An instance of this structure class."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        self.read_only = read_only
        self.secret_name = secret_name
        self.share_name = share_name
<|end_body_0|>

<|body_start_1|>
        if dictionary is None:
            return None
        read_only = dictionary.get('readOnly')
        secret_name = dictionary.get('secretName')
        share_name = dictionary.get('shareName')
        return cls(read_only, secret_name, share_name)
<|end_body_1|>

Solution:
class PodInfo_PodSpec_VolumeInfo_AzureFile:
    """Implementation of the 'PodInfo_PodSpec_VolumeInfo_AzureFile' model. TODO: type description here. Attributes: read_only (string): TODO: Type description here. secret_name (string): TODO: Type description here. share_name (string): TODO: Type description here."""

    def __init__(self, read_only=None, secret_name=None, share_name=None):
        """Constructor for the PodInfo_PodSpec_VolumeInfo_AzureFile class"""
        self.read_only = read_only
        self.secret_name = secret_name
        self.share_name = share_name

    def from_dictionary(cls, dictionary):
        """Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as obtained from the deserialization of the server's response. The keys MUST match property names in the API description. Returns: object: An instance of this structure class."""
        if dictionary is None:
            return None
        read_only = dictionary.get('readOnly')
        secret_name = dictionary.get('secretName')
        share_name = dictionary.get('shareName')
        return cls(read_only, secret_name, share_name)


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

Class description:
Internal class used to explore arrays.

Method signatures and docstrings:
- def explore_expr(expr, value, is_child): Function to explore array values. See Explorer.explore_expr for more information.
- def explore_type(name, datatype, is_child): Function to explore array types. See Explorer.explore_type for more information.

Implement the Python class `ArrayExplorer` described below.

Class description:
Internal class used to explore arrays.

Method signatures and docstrings:
- def explore_expr(expr, value, is_child): Function to explore array values. See Explorer.explore_expr for more information.
- def explore_type(name, datatype, is_child): Function to explore array types. See Explorer.explore_type for more information.

<|skeleton|>
class ArrayExplorer:
    """Internal class used to explore arrays."""

    def explore_expr(expr, value, is_child):
        """Function to explore array values. See Explorer.explore_expr for more information."""
        <|body_0|>

    def explore_type(name, datatype, is_child):
        """Function to explore array types. See Explorer.explore_type for more information."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        target_type = value.type.target()
        print("'%s' is an array of '%s'." % (expr, str(target_type)))
        index = 0
        try:
            index = int(raw_input("Enter the index of the element you want to explore in '%s': " % expr))
        except ValueError:
            if is_child:
                Explorer.return_to_parent_value()
            return False
        element = None
        try:
            element = value[index]
            str(element)
        except gdb.MemoryError:
            print('Cannot read value at index %d.' % index)
            raw_input('Press enter to continue... ')
            return True
        Explorer.explore_expr('%s[%d]' % (Explorer.guard_expr(expr), index), element, True)
        return True
<|end_body_0|>

<|body_start_1|>
        target_type = datatype.target()
        print("%s is an array of '%s'." % (name, str(target_type)))
        Explorer.explore_type('the array element of %s' % name, target_type, is_child)
        return False
<|end_body_1|>

Solution:
class ArrayExplorer:
    """Internal class used to explore arrays."""

    def explore_expr(expr, value, is_child):
        """Function to explore array values. See Explorer.explore_expr for more information."""
        target_type = value.type.target()
        print("'%s' is an array of '%s'." % (expr, str(target_type)))
        index = 0
        try:
            index = int(raw_input("Enter the index of the element you want to explore in '%s': " % expr))
        except ValueError:
            if is_child:
                Explorer.return_to_parent_value()
            return False
        element = None
        try:
            element = value[index]
            str(element)
        except gdb.MemoryError:
            print('Cannot read value at index %d.' % index)
            raw_input('Press enter to continue... ')
            return True
        Explorer.explore_expr('%s[%d]' % (Explorer.guard_expr(expr), index), element, True)
        return True

    def explore_type(name, datatype, is_child):
        """Function to explore array types. See Explorer.explore_type for more information."""
        target_type = datatype.target()
        print("%s is an array of '%s'." % (name, str(target_type)))
        Explorer.explore_type('the array element of %s' % name, target_type, is_child)
        return False


setData

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

Class description:
This is the base widget for Plots, derived from `QWidget`. This widget does not implement any plotting. It merely is a wrapping widget that contains the actual plot widget in it. This actual plot widget can be set dynamically. Use :class:`PlotWidget` as base for implementing widgets that can be added to this container.

Method signatures and docstrings:
- def __init__(self, parent: Optional[QtWidgets.QWidget]=None): Constructor for :class:`PlotWidgetContainer`.
- def setPlotWidget(self, widget: 'PlotWidget') -> None: Set the plot widget. Makes sure that the added widget receives new data. :param widget: plot widget
- def setData(self, data: DataDictBase) -> None: set Data. If a plot widget is defined, call the widget's :meth:`PlotWidget.setData` method. :param data: input data to be plotted.

Implement the Python class `PlotWidgetContainer` described below.

Class description:
This is the base widget for Plots, derived from `QWidget`. This widget does not implement any plotting. It merely is a wrapping widget that contains the actual plot widget in it. This actual plot widget can be set dynamically. Use :class:`PlotWidget` as base for implementing widgets that can be added to this container.

Method signatures and docstrings:
- def __init__(self, parent: Optional[QtWidgets.QWidget]=None): Constructor for :class:`PlotWidgetContainer`.
- def setPlotWidget(self, widget: 'PlotWidget') -> None: Set the plot widget. Makes sure that the added widget receives new data. :param widget: plot widget
- def setData(self, data: DataDictBase) -> None: set Data. If a plot widget is defined, call the widget's :meth:`PlotWidget.setData` method. :param data: input data to be plotted.

<|skeleton|>
class PlotWidgetContainer:
    """This is the base widget for Plots, derived from `QWidget`. This widget does not implement any plotting. It merely is a wrapping widget that contains the actual plot widget in it. This actual plot widget can be set dynamically. Use :class:`PlotWidget` as base for implementing widgets that can be added to this container."""

    def __init__(self, parent: Optional[QtWidgets.QWidget]=None):
        """Constructor for :class:`PlotWidgetContainer`."""
        <|body_0|>

    def setPlotWidget(self, widget: 'PlotWidget') -> None:
        """Set the plot widget. Makes sure that the added widget receives new data. :param widget: plot widget"""
        <|body_1|>

    def setData(self, data: DataDictBase) -> None:
        """set Data. If a plot widget is defined, call the widget's :meth:`PlotWidget.setData` method. :param data: input data to be plotted."""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        super().__init__(parent=parent)
        self.plotWidget: Optional['PlotWidget'] = None
        self.data: Optional[DataDictBase] = None
        layout: QtWidgets.QVBoxLayout = QtWidgets.QVBoxLayout(self)
        layout.setContentsMargins(0, 0, 0, 0)
        self.setLayout(layout)
<|end_body_0|>

<|body_start_1|>
        if widget is self.plotWidget:
            return
        if self.plotWidget is not None:
            self.layout().removeWidget(self.plotWidget)
            self.plotWidget.deleteLater()
        self.plotWidget = widget
        if self.plotWidget is not None:
            self.layout().addWidget(widget)
            self.plotWidget.setData(self.data)
<|end_body_1|>

<|body_start_2|>
        self.data = data
        if self.plotWidget is not None:
            self.plotWidget.setData(self.data)
<|end_body_2|>

Solution:
class PlotWidgetContainer:
    """This is the base widget for Plots, derived from `QWidget`. This widget does not implement any plotting. It merely is a wrapping widget that contains the actual plot widget in it. This actual plot widget can be set dynamically. Use :class:`PlotWidget` as base for implementing widgets that can be added to this container."""

    def __init__(self, parent: Optional[QtWidgets.QWidget]=None):
        """Constructor for :class:`PlotWidgetContainer`."""
        super().__init__(parent=parent)
        self.plotWidget: Optional['PlotWidget'] = None
        self.data: Optional[DataDictBase] = None
        layout: QtWidgets.QVBoxLayout = QtWidgets.QVBoxLayout(self)
        layout.setContentsMargins(0, 0, 0, 0)
        self.setLayout(layout)

    def setPlotWidget(self, widget: 'PlotWidget') -> None:
        """Set the plot widget. Makes sure that the added widget receives new data. :param widget: plot widget"""
        if widget is self.plotWidget:
            return
        if self.plotWidget is not None:
            self.layout().removeWidget(self.plotWidget)
            self.plotWidget.deleteLater()
        self.plotWidget = widget
        if self.plotWidget is not None:
            self.layout().addWidget(widget)
            self.plotWidget.setData(self.data)

    def setData(self, data: DataDictBase) -> None:
        """set Data. If a plot widget is defined, call the widget's :meth:`PlotWidget.setData` method. :param data: input data to be plotted."""
        self.data = data
        if self.plotWidget is not None:
            self.plotWidget.setData(self.data)