decoder

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

Class description:
an encoder-decoder with dynamic routing acquisition model

Method signatures and docstrings:
- def model(self, inputs, seq_length): apply the model
- def loss(self, targets, probs): compute the loss args: targets: the reference targets probs: the label probabilities returns: the loss
- def encoder(self, features, seq_length): encode the input features args: features: a [N x T x F] tensor seq_length: an [N] tensor containing the sequence lengths returns: - the encoded features - the encode features sequence lengths
- def decoder(self, encoded, seq_length): decode the encoded features args: encoded: a [N x T x F] tensor seq_length: encoded sequence length returns: - the label probabilities [B x L]

Implement the Python class `EncoderDecoder` described below.

Class description:
an encoder-decoder with dynamic routing acquisition model

Method signatures and docstrings:
- def model(self, inputs, seq_length): apply the model
- def loss(self, targets, probs): compute the loss args: targets: the reference targets probs: the label probabilities returns: the loss
- def encoder(self, features, seq_length): encode the input features args: features: a [N x T x F] tensor seq_length: an [N] tensor containing the sequence lengths returns: - the encoded features - the encode features sequence lengths
- def decoder(self, encoded, seq_length): decode the encoded features args: encoded: a [N x T x F] tensor seq_length: encoded sequence length returns: - the label probabilities [B x L]

<|skeleton|>
class EncoderDecoder:
    """an encoder-decoder with dynamic routing acquisition model"""

    def model(self, inputs, seq_length):
        """apply the model"""
        <|body_0|>

    def loss(self, targets, probs):
        """compute the loss args: targets: the reference targets probs: the label probabilities returns: the loss"""
        <|body_1|>

    def encoder(self, features, seq_length):
        """encode the input features args: features: a [N x T x F] tensor seq_length: an [N] tensor containing the sequence lengths returns: - the encoded features - the encode features sequence lengths"""
        <|body_2|>

    def decoder(self, encoded, seq_length):
        """decode the encoded features args: encoded: a [N x T x F] tensor seq_length: encoded sequence length returns: - the label probabilities [B x L]"""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        encoded, seq_length = self.encoder(inputs, seq_length)
        probs = self.decoder(encoded, seq_length)
        return probs
<|end_body_0|>

<|body_start_1|>
        with tf.name_scope('compute_loss'):
            iw = float(self.conf['insertion_weight'])
            up = float(self.conf['upper_prob'])
            lp = float(self.conf['lower_prob'])
            iloss = iw * tf.reduce_mean(tf.reduce_sum((1 - targets) * tf.maximum(probs - lp, 0) ** 2, 1))
            dloss = tf.reduce_mean(tf.reduce_sum(targets * tf.maximum(up - probs, 0) ** 2, 1))
            loss = dloss + iloss
        return loss
<|end_body_1|>

<|body_start_2|>
        with tf.variable_scope('encoder'):
            encoded = tf.identity(features, 'features')
            seq_length = tf.identity(seq_length, 'input_seq_length')
            for l in range(int(self.conf['numlayers_encoder'])):
                with tf.variable_scope('layer%d' % l):
                    num_units = int(self.conf['numunits_encoder'])
                    fw = tf.contrib.rnn.GRUCell(num_units)
                    bw = tf.contrib.rnn.GRUCell(num_units)
                    encoded, _ = tf.nn.bidirectional_dynamic_rnn(fw, bw, encoded, dtype=tf.float32, sequence_length=seq_length)
                    encoded = tf.concat(encoded, 2)
                    if l != int(self.conf['numlayers_encoder']) - 1:
                        with tf.name_scope('sub-sample'):
                            encoded = encoded[:, ::int(self.conf['subsample'])]
                        seq_length = tf.to_int32(tf.ceil(tf.to_float(seq_length) / float(self.conf['subsample'])))
            encoded = tf.identity(encoded, 'encoded')
            seq_length = tf.identity(seq_length, 'output_seq_length')
        return (encoded, seq_length)
<|end_body_2|>

<|body_start_3|>
        with tf.variable_scope('decoder'):
            mask = tf.sequence_mask(seq_length, tf.shape(encoded)[1])
            mask = tf.tile(mask[:, :, tf.newaxis], [1, 1, encoded.shape[-1].value])
            encoded = tf.where(mask, encoded, tf.ones_like(encoded) * encoded.dtype.min)
            outputs = tf.reduce_max(encoded, 1)
            outputs = tf.layers.dense(outputs, int(self.conf['numunits_decoder']), tf.nn.relu)
            outputs = tf.layers.dense(outputs, self.coder.numlabels, tf.nn.sigmoid)
            return outputs
<|end_body_3|>

Solution:
class EncoderDecoder:
    """an encoder-decoder with dynamic routing acquisition model"""

    def model(self, inputs, seq_length):
        """apply the model"""
        encoded, seq_length = self.encoder(inputs, seq_length)
        probs = self.decoder(encoded, seq_length)
        return probs

    def loss(self, targets, probs):
        """compute the loss args: targets: the reference targets probs: the label probabilities returns: the loss"""
        with tf.name_scope('compute_loss'):
            iw = float(self.conf['insertion_weight'])
            up = float(self.conf['upper_prob'])
            lp = float(self.conf['lower_prob'])
            iloss = iw * tf.reduce_mean(tf.reduce_sum((1 - targets) * tf.maximum(probs - lp, 0) ** 2, 1))
            dloss = tf.reduce_mean(tf.reduce_sum(targets * tf.maximum(up - probs, 0) ** 2, 1))
            loss = dloss + iloss
        return loss

    def encoder(self, features, seq_length):
        """encode the input features args: features: a [N x T x F] tensor seq_length: an [N] tensor containing the sequence lengths returns: - the encoded features - the encode features sequence lengths"""
        with tf.variable_scope('encoder'):
            encoded = tf.identity(features, 'features')
            seq_length = tf.identity(seq_length, 'input_seq_length')
            for l in range(int(self.conf['numlayers_encoder'])):
                with tf.variable_scope('layer%d' % l):
                    num_units = int(self.conf['numunits_encoder'])
                    fw = tf.contrib.rnn.GRUCell(num_units)
                    bw = tf.contrib.rnn.GRUCell(num_units)
                    encoded, _ = tf.nn.bidirectional_dynamic_rnn(fw, bw, encoded, dtype=tf.float32, sequence_length=seq_length)
                    encoded = tf.concat(encoded, 2)
                    if l != int(self.conf['numlayers_encoder']) - 1:
                        with tf.name_scope('sub-sample'):
                            encoded = encoded[:, ::int(self.conf['subsample'])]
                        seq_length = tf.to_int32(tf.ceil(tf.to_float(seq_length) / float(self.conf['subsample'])))
            encoded = tf.identity(encoded, 'encoded')
            seq_length = tf.identity(seq_length, 'output_seq_length')
        return (encoded, seq_length)

    def decoder(self, encoded, seq_length):
        """decode the encoded features args: encoded: a [N x T x F] tensor seq_length: encoded sequence length returns: - the label probabilities [B x L]"""
        with tf.variable_scope('decoder'):
            mask = tf.sequence_mask(seq_length, tf.shape(encoded)[1])
            mask = tf.tile(mask[:, :, tf.newaxis], [1, 1, encoded.shape[-1].value])
            encoded = tf.where(mask, encoded, tf.ones_like(encoded) * encoded.dtype.min)
            outputs = tf.reduce_max(encoded, 1)
            outputs = tf.layers.dense(outputs, int(self.conf['numunits_decoder']), tf.nn.relu)
            outputs = tf.layers.dense(outputs, self.coder.numlabels, tf.nn.sigmoid)
            return outputs


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

Class description:
Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis

Method signatures and docstrings:
- def __init__(self, ms, n, r, beam, params): Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q.
- def Bb_matrix(self): Matrix of the constraint on the beam
- def C_matrix(self, norm): H^norm matrices of Q

Implement the Python class `CoupledEigen` described below.

Class description:
Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis

Method signatures and docstrings:
- def __init__(self, ms, n, r, beam, params): Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q.
- def Bb_matrix(self): Matrix of the constraint on the beam
- def C_matrix(self, norm): H^norm matrices of Q

<|skeleton|>
class CoupledEigen:
    """Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis"""

    def __init__(self, ms, n, r, beam, params):
        """Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q."""
        <|body_0|>

    def Bb_matrix(self):
        """Matrix of the constraint on the beam"""
        <|body_1|>

    def C_matrix(self, norm):
        """H^norm matrices of Q"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        assert len(set(ms)) == 1
        Vp = [list(eigen_basis(m)) for m in ms]
        Vb = [q.subs(x, s) for q in eigen_basis(n)]
        Q = [mu.subs(x, s) for mu in eigen_basis(r)]
        CoupledProblem.__init__(self, Vp, Vb, Q, beam)
        self.params = params
<|end_body_0|>

<|body_start_1|>
        if isinstance(self.beam, LineBeam):
            dim = max(self.n, self.r)
            Bb = eigen_poisson.mass_matrix(dim)
            Bb = Bb[:self.n, :self.r]
            Bb *= float(self.beam.Jac)
        else:
            Bb = CoupledProblem.Bb_matrix(self)
        return Bb
<|end_body_1|>

<|body_start_2|>
        if norm is None:
            return np.eye(self.r)
        if isinstance(self.beam, LineBeam):
            diag = np.array([(pi / 2 + k * pi / 2) ** 2 for k in range(self.r)], dtype='float')
            C = np.diag(diag ** norm)
            J = self.beam.Jac
            J = J ** (1 - 2 * norm)
            C *= float(J)
        else:
            C = CoupledProblem.C_matrix(self, norm)
        return C
<|end_body_2|>

Solution:
class CoupledEigen:
    """Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis"""

    def __init__(self, ms, n, r, beam, params):
        """Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q."""
        assert len(set(ms)) == 1
        Vp = [list(eigen_basis(m)) for m in ms]
        Vb = [q.subs(x, s) for q in eigen_basis(n)]
        Q = [mu.subs(x, s) for mu in eigen_basis(r)]
        CoupledProblem.__init__(self, Vp, Vb, Q, beam)
        self.params = params

    def Bb_matrix(self):
        """Matrix of the constraint on the beam"""
        if isinstance(self.beam, LineBeam):
            dim = max(self.n, self.r)
            Bb = eigen_poisson.mass_matrix(dim)
            Bb = Bb[:self.n, :self.r]
            Bb *= float(self.beam.Jac)
        else:
            Bb = CoupledProblem.Bb_matrix(self)
        return Bb

    def C_matrix(self, norm):
        """H^norm matrices of Q"""
        if norm is None:
            return np.eye(self.r)
        if isinstance(self.beam, LineBeam):
            diag = np.array([(pi / 2 + k * pi / 2) ** 2 for k in range(self.r)], dtype='float')
            C = np.diag(diag ** norm)
            J = self.beam.Jac
            J = J ** (1 - 2 * norm)
            C *= float(J)
        else:
            C = CoupledProblem.C_matrix(self, norm)
        return C


FormatDebugInfo

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

Class description:
An error raised when VM is having an issue.

Method signatures and docstrings:
- def FromDebugInfo(cls, info, error_message): Create VirtualMachineError class from debug information. Args: info: A dictionary containing debug information (such as traceroute info). error_message: the error message from the originating code. Returns: a cls exception class Raises: TypeError: if info is not an instance of dictionary.
- def FormatDebugInfo(info, error_message): A function to return a string in human readable format. Args: info: A dictionary containing debug information (such as traceroute info). error_message: the error message from the originating code. Returns: A human readable string of debug information.

Implement the Python class `VirtualMachineError` described below.

Class description:
An error raised when VM is having an issue.

Method signatures and docstrings:
- def FromDebugInfo(cls, info, error_message): Create VirtualMachineError class from debug information. Args: info: A dictionary containing debug information (such as traceroute info). error_message: the error message from the originating code. Returns: a cls exception class Raises: TypeError: if info is not an instance of dictionary.
- def FormatDebugInfo(info, error_message): A function to return a string in human readable format. Args: info: A dictionary containing debug information (such as traceroute info). error_message: the error message from the originating code. Returns: A human readable string of debug information.

<|skeleton|>
class VirtualMachineError:
    """An error raised when VM is having an issue."""

    def FromDebugInfo(cls, info, error_message):
        """Create VirtualMachineError class from debug information. Args: info: A dictionary containing debug information (such as traceroute info). error_message: the error message from the originating code. Returns: a cls exception class Raises: TypeError: if info is not an instance of dictionary."""
        <|body_0|>

    def FormatDebugInfo(info, error_message):
        """A function to return a string in human readable format. Args: info: A dictionary containing debug information (such as traceroute info). error_message: the error message from the originating code. Returns: A human readable string of debug information."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if isinstance(info, dict):
            info = VirtualMachine.VirtualMachineError.FormatDebugInfo(info, error_message)
            return cls(info)
        raise TypeError('The argument of FromDebugInfo should be an instance of dictionary.')
<|end_body_0|>

<|body_start_1|>
        sep = '\n%s\n' % ('-' * 65)

        def AddHeader(error, header, message):
            error += '{sep}{header}\n{message}\n'.format(sep=sep, header=header, message=message)
            return error

        def AddKeyIfExists(result, header, key):
            if key in info:
                result = AddHeader(result, header, info[key])
                del info[key]
            return result
        result = AddHeader('', 'error_message:', error_message) if error_message else ''
        result = AddKeyIfExists(result, 'traceroute:', 'traceroute')
        return AddHeader(result, 'Debug Info:', pprint.pformat(info))
<|end_body_1|>

Solution:
class VirtualMachineError:
    """An error raised when VM is having an issue."""

    def FromDebugInfo(cls, info, error_message):
        """Create VirtualMachineError class from debug information. Args: info: A dictionary containing debug information (such as traceroute info). error_message: the error message from the originating code. Returns: a cls exception class Raises: TypeError: if info is not an instance of dictionary."""
        if isinstance(info, dict):
            info = VirtualMachine.VirtualMachineError.FormatDebugInfo(info, error_message)
            return cls(info)
        raise TypeError('The argument of FromDebugInfo should be an instance of dictionary.')

    def FormatDebugInfo(info, error_message):
        """A function to return a string in human readable format. Args: info: A dictionary containing debug information (such as traceroute info). error_message: the error message from the originating code. Returns: A human readable string of debug information."""
        sep = '\n%s\n' % ('-' * 65)

        def AddHeader(error, header, message):
            error += '{sep}{header}\n{message}\n'.format(sep=sep, header=header, message=message)
            return error

        def AddKeyIfExists(result, header, key):
            if key in info:
                result = AddHeader(result, header, info[key])
                del info[key]
            return result
        result = AddHeader('', 'error_message:', error_message) if error_message else ''
        result = AddKeyIfExists(result, 'traceroute:', 'traceroute')
        return AddHeader(result, 'Debug Info:', pprint.pformat(info))


modify

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

Class description:
Implement the Survey class.

Method signatures and docstrings:
- def get(self, id_survey=None): Return the survey information :param id_survey: UUID
- def create(self, body): Create a new survey :param body: { name: JSON, survey_type: ENUM('test'), questions: JSON }
- def modify(self, body): Modify a survey :param body: { id_survey: UUID, name: JSON, survey_type: ENUM('test'), is_active: BOOLEAN, questions: JSON }
- def remove(self, id_survey): Remove a survey :param id_survey: UUID

Implement the Python class `Survey` described below.

Class description:
Implement the Survey class.

Method signatures and docstrings:
- def get(self, id_survey=None): Return the survey information :param id_survey: UUID
- def create(self, body): Create a new survey :param body: { name: JSON, survey_type: ENUM('test'), questions: JSON }
- def modify(self, body): Modify a survey :param body: { id_survey: UUID, name: JSON, survey_type: ENUM('test'), is_active: BOOLEAN, questions: JSON }
- def remove(self, id_survey): Remove a survey :param id_survey: UUID

<|skeleton|>
class Survey:

    def get(self, id_survey=None):
        """Return the survey information :param id_survey: UUID"""
        <|body_0|>

    def create(self, body):
        """Create a new survey :param body: { name: JSON, survey_type: ENUM('test'), questions: JSON }"""
        <|body_1|>

    def modify(self, body):
        """Modify a survey :param body: { id_survey: UUID, name: JSON, survey_type: ENUM('test'), is_active: BOOLEAN, questions: JSON }"""
        <|body_2|>

    def remove(self, id_survey):
        """Remove a survey :param id_survey: UUID"""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        if self.has_permission('RightTPI') is False:
            self.no_access()
        with Database() as db:
            if id_survey is None:
                data = db.query(Table).all()
            else:
                data = db.query(Table).get(id_survey)
        return {'data': data}
<|end_body_0|>

<|body_start_1|>
        if self.has_permission('RightTPI') is False:
            self.no_access()
        id_survey = uuid.uuid4()
        id_language_content = MultiLang.set(body['name'], True)
        with Database() as db:
            db.insert(Table(id_survey, id_language_content, body['survey_type']))
            db.commit()
        return {'id_survey': id_survey, 'message': 'survey successfully created'}
<|end_body_1|>

<|body_start_2|>
        if self.has_permission('RightTPI') is False:
            self.no_access()
        if 'id_survey' not in body:
            raise Exception('You need to pass a id_survey')
        with Database() as db:
            inspection = db.query(Inspection).filter(Inspection.id_survey == body['id_survey'], Inspection.is_completed == True).all()
            if len(inspection) > 0:
                self.remove(body['id_survey'])
                self.create(body)
            else:
                data = db.query(Table).get(body['id_survey'])
                if 'name' in body:
                    data.id_language_content_name = MultiLang.set(body['name'])
                if 'survey_type' in body:
                    data.survey_type = body['survey_type']
                if 'is_active' in body:
                    data.is_active = body['is_active']
                db.commit()
        return {'message': 'survey successfully modified'}
<|end_body_2|>

<|body_start_3|>
        if self.has_permission('RightTPI') is False:
            self.no_access()
        with Database() as db:
            data = db.query(Table).get(id_survey)
            data.is_active = False
            db.commit()
        return {'message': 'survey successfully removed'}
<|end_body_3|>

Solution:
class Survey:
    def get(self, id_survey=None):
        """Return the survey information :param id_survey: UUID"""
        if self.has_permission('RightTPI') is False:
            self.no_access()
        with Database() as db:
            if id_survey is None:
                data = db.query(Table).all()
            else:
                data = db.query(Table).get(id_survey)
        return {'data': data}

    def create(self, body):
        """Create a new survey :param body: { name: JSON, survey_type: ENUM('test'), questions: JSON }"""
        if self.has_permission('RightTPI') is False:
            self.no_access()
        id_survey = uuid.uuid4()
        id_language_content = MultiLang.set(body['name'], True)
        with Database() as db:
            db.insert(Table(id_survey, id_language_content, body['survey_type']))
            db.commit()
        return {'id_survey': id_survey, 'message': 'survey successfully created'}

    def modify(self, body):
        """Modify a survey :param body: { id_survey: UUID, name: JSON, survey_type: ENUM('test'), is_active: BOOLEAN, questions: JSON }"""
        if self.has_permission('RightTPI') is False:
            self.no_access()
        if 'id_survey' not in body:
            raise Exception('You need to pass a id_survey')
        with Database() as db:
            inspection = db.query(Inspection).filter(Inspection.id_survey == body['id_survey'], Inspection.is_completed == True).all()
            if len(inspection) > 0:
                self.remove(body['id_survey'])
                self.create(body)
            else:
                data = db.query(Table).get(body['id_survey'])
                if 'name' in body:
                    data.id_language_content_name = MultiLang.set(body['name'])
                if 'survey_type' in body:
                    data.survey_type = body['survey_type']
                if 'is_active' in body:
                    data.is_active = body['is_active']
                db.commit()
        return {'message': 'survey successfully modified'}

    def remove(self, id_survey):
        """Remove a survey :param id_survey: UUID"""
        if self.has_permission('RightTPI') is False:
            self.no_access()
        with Database() as db:
            data = db.query(Table).get(id_survey)
            data.is_active = False
            db.commit()
        return {'message': 'survey successfully removed'}


run

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

Class description:
Class to handle exclusion-style friction layer.

Method signatures and docstrings:
- def __init__(self, fric_h5, fric_dset, hsds=False, check_layers=False): Parameters ---------- fric_h5 : str Path to friction layer .h5 file (same format as exclusions file) fric_dset : str Friction layer dataset in fric_h5 hsds : bool Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS behind HSDS check_layers : bool Run a pre-flight check on each layer to ensure they contain un-excluded values
- def _generate_mask(self, *ds_slice): Generate multiplicative friction layer mask. Parameters ---------- ds_slice : int | slice | list | ndarray What to extract from ds, each arg is for a sequential axis. For example, (slice(0, 64), slice(0, 64)) will extract a 64x64 exclusions mask. Returns ------- mask : ndarray Multiplicative friction layer mask with nodata values set to 1.
- def run(cls, excl_h5, fric_dset, hsds=False): Create inclusion mask from given layers dictionary Parameters ---------- fric_h5 : str Path to friction layer .h5 file (same format as exclusions file) fric_dset : str Friction layer dataset in fric_h5 hsds : bool Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS behind HSDS Returns ------- mask : ndarray Full inclusion mask

Implement the Python class `FrictionMask` described below.

Class description:
Class to handle exclusion-style friction layer.

Method signatures and docstrings:
- def __init__(self, fric_h5, fric_dset, hsds=False, check_layers=False): Parameters ---------- fric_h5 : str Path to friction layer .h5 file (same format as exclusions file) fric_dset : str Friction layer dataset in fric_h5 hsds : bool Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS behind HSDS check_layers : bool Run a pre-flight check on each layer to ensure they contain un-excluded values
- def _generate_mask(self, *ds_slice): Generate multiplicative friction layer mask. Parameters ---------- ds_slice : int | slice | list | ndarray What to extract from ds, each arg is for a sequential axis. For example, (slice(0, 64), slice(0, 64)) will extract a 64x64 exclusions mask. Returns ------- mask : ndarray Multiplicative friction layer mask with nodata values set to 1.
- def run(cls, excl_h5, fric_dset, hsds=False): Create inclusion mask from given layers dictionary Parameters ---------- fric_h5 : str Path to friction layer .h5 file (same format as exclusions file) fric_dset : str Friction layer dataset in fric_h5 hsds : bool Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS behind HSDS Returns ------- mask : ndarray Full inclusion mask

<|skeleton|>
class FrictionMask:
    """Class to handle exclusion-style friction layer."""

    def __init__(self, fric_h5, fric_dset, hsds=False, check_layers=False):
        """Parameters ---------- fric_h5 : str Path to friction layer .h5 file (same format as exclusions file) fric_dset : str Friction layer dataset in fric_h5 hsds : bool Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS behind HSDS check_layers : bool Run a pre-flight check on each layer to ensure they contain un-excluded values"""
        <|body_0|>

    def _generate_mask(self, *ds_slice):
        """Generate multiplicative friction layer mask. Parameters ---------- ds_slice : int | slice | list | ndarray What to extract from ds, each arg is for a sequential axis. For example, (slice(0, 64), slice(0, 64)) will extract a 64x64 exclusions mask. Returns ------- mask : ndarray Multiplicative friction layer mask with nodata values set to 1."""
        <|body_1|>

    def run(cls, excl_h5, fric_dset, hsds=False):
        """Create inclusion mask from given layers dictionary Parameters ---------- fric_h5 : str Path to friction layer .h5 file (same format as exclusions file) fric_dset : str Friction layer dataset in fric_h5 hsds : bool Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS behind HSDS Returns ------- mask : ndarray Full inclusion mask"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        self._fric_dset = fric_dset
        L = [LayerMask(fric_dset, use_as_weights=True, exclude_nodata=False)]
        super().__init__(fric_h5, layers=L, min_area=None, hsds=hsds, check_layers=check_layers)
<|end_body_0|>

<|body_start_1|>
        mask = None
        if len(ds_slice) == 1 & isinstance(ds_slice[0], tuple):
            ds_slice = ds_slice[0]
        layer_slice = (self._layers[self._fric_dset].name,) + ds_slice
        mask = self._layers[self._fric_dset][self.excl_h5[layer_slice]]
        mask[mask == self._layers[self._fric_dset].nodata_value] = 1
        return mask
<|end_body_1|>

<|body_start_2|>
        L = [LayerMask(fric_dset, use_as_weights=True, exclude_nodata=False)]
        with cls(excl_h5, *L, min_area=None, hsds=hsds) as f:
            mask = f.mask
        return mask
<|end_body_2|>

Solution:
class FrictionMask:
    """Class to handle exclusion-style friction layer."""

    def __init__(self, fric_h5, fric_dset, hsds=False, check_layers=False):
        """Parameters ---------- fric_h5 : str Path to friction layer .h5 file (same format as exclusions file) fric_dset : str Friction layer dataset in fric_h5 hsds : bool Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS behind HSDS check_layers : bool Run a pre-flight check on each layer to ensure they contain un-excluded values"""
        self._fric_dset = fric_dset
        L = [LayerMask(fric_dset, use_as_weights=True, exclude_nodata=False)]
        super().__init__(fric_h5, layers=L, min_area=None, hsds=hsds, check_layers=check_layers)

    def _generate_mask(self, *ds_slice):
        """Generate multiplicative friction layer mask. Parameters ---------- ds_slice : int | slice | list | ndarray What to extract from ds, each arg is for a sequential axis. For example, (slice(0, 64), slice(0, 64)) will extract a 64x64 exclusions mask. Returns ------- mask : ndarray Multiplicative friction layer mask with nodata values set to 1."""
        mask = None
        if len(ds_slice) == 1 & isinstance(ds_slice[0], tuple):
            ds_slice = ds_slice[0]
        layer_slice = (self._layers[self._fric_dset].name,) + ds_slice
        mask = self._layers[self._fric_dset][self.excl_h5[layer_slice]]
        mask[mask == self._layers[self._fric_dset].nodata_value] = 1
        return mask

    def run(cls, excl_h5, fric_dset, hsds=False):
        """Create inclusion mask from given layers dictionary Parameters ---------- fric_h5 : str Path to friction layer .h5 file (same format as exclusions file) fric_dset : str Friction layer dataset in fric_h5 hsds : bool Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS behind HSDS Returns ------- mask : ndarray Full inclusion mask"""
        L = [LayerMask(fric_dset, use_as_weights=True, exclude_nodata=False)]
        with cls(excl_h5, *L, min_area=None, hsds=hsds) as f:
            mask = f.mask
        return mask


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

Class description:
Represent the value of a MySensors Binary Sensor child node.

Method signatures and docstrings:
- def is_on(self): Return True if the binary sensor is on.
- def sensor_class(self): Return the class of this sensor, from SENSOR_CLASSES.

Implement the Python class `MySensorsBinarySensor` described below.

Class description:
Represent the value of a MySensors Binary Sensor child node.

Method signatures and docstrings:
- def is_on(self): Return True if the binary sensor is on.
- def sensor_class(self): Return the class of this sensor, from SENSOR_CLASSES.

<|skeleton|>
class MySensorsBinarySensor:
    """Represent the value of a MySensors Binary Sensor child node."""

    def is_on(self):
        """Return True if the binary sensor is on."""
        <|body_0|>

    def sensor_class(self):
        """Return the class of this sensor, from SENSOR_CLASSES."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        if self.value_type in self._values:
            return self._values[self.value_type] == STATE_ON
        return False
<|end_body_0|>

<|body_start_1|>
        pres = self.gateway.const.Presentation
        class_map = {pres.S_DOOR: 'opening', pres.S_MOTION: 'motion', pres.S_SMOKE: 'smoke'}
        if float(self.gateway.protocol_version) >= 1.5:
            class_map.update({pres.S_SPRINKLER: 'sprinkler', pres.S_WATER_LEAK: 'leak', pres.S_SOUND: 'sound', pres.S_VIBRATION: 'vibration', pres.S_MOISTURE: 'moisture'})
        if class_map.get(self.child_type) in SENSOR_CLASSES:
            return class_map.get(self.child_type)
<|end_body_1|>

Solution:
class MySensorsBinarySensor:
    """Represent the value of a MySensors Binary Sensor child node."""

    def is_on(self):
        """Return True if the binary sensor is on."""
        if self.value_type in self._values:
            return self._values[self.value_type] == STATE_ON
        return False

    def sensor_class(self):
        """Return the class of this sensor, from SENSOR_CLASSES."""
        pres = self.gateway.const.Presentation
        class_map = {pres.S_DOOR: 'opening', pres.S_MOTION: 'motion', pres.S_SMOKE: 'smoke'}
        if float(self.gateway.protocol_version) >= 1.5:
            class_map.update({pres.S_SPRINKLER: 'sprinkler', pres.S_WATER_LEAK: 'leak', pres.S_SOUND: 'sound', pres.S_VIBRATION: 'vibration', pres.S_MOISTURE: 'moisture'})
        if class_map.get(self.child_type) in SENSOR_CLASSES:
            return class_map.get(self.child_type)


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

Class description:
Methods for adding frequencies

Method signatures and docstrings:
- def _add_thousand_g(self, variant_obj, info_dict): Add the thousand genomes frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary
- def _add_gmaf(self, variant_obj, info_dict): Add the gmaf frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary
- def _add_exac(self, variant_obj, info_dict): Add the gmaf frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary

Implement the Python class `FrequenciesExtras` described below.

Class description:
Methods for adding frequencies

Method signatures and docstrings:
- def _add_thousand_g(self, variant_obj, info_dict): Add the thousand genomes frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary
- def _add_gmaf(self, variant_obj, info_dict): Add the gmaf frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary
- def _add_exac(self, variant_obj, info_dict): Add the gmaf frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary

<|skeleton|>
class FrequenciesExtras:
    """Methods for adding frequencies"""

    def _add_thousand_g(self, variant_obj, info_dict):
        """Add the thousand genomes frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary"""
        <|body_0|>

    def _add_gmaf(self, variant_obj, info_dict):
        """Add the gmaf frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary"""
        <|body_1|>

    def _add_exac(self, variant_obj, info_dict):
        """Add the gmaf frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        thousand_g = info_dict.get('1000GAF')
        if thousand_g:
            logger.debug('Updating thousand_g to: {0}'.format(thousand_g))
            variant_obj.thousand_g = float(thousand_g)
            variant_obj.add_frequency('1000GAF', variant_obj.get('thousand_g'))
<|end_body_0|>

<|body_start_1|>
        for transcript in variant_obj.transcripts:
            gmaf_raw = transcript.GMAF
            if gmaf_raw:
                gmaf = float(gmaf_raw.split(':')[-1])
                variant_obj.add_frequency('GMAF', gmaf)
                if not variant_obj.thousand_g:
                    variant_obj.thousand_g = gmaf
<|end_body_1|>

<|body_start_2|>
        exac = None
        exac_keys = ['ExAC', 'EXAC', 'ExACAF', 'EXACAF']
        for key in exac_keys:
            if info_dict.get(key):
                exac = float(info_dict[key])
        if not exac:
            for transcript in variant_obj.transcripts:
                exac_raw = transcript.ExAC_MAF
                if exac_raw:
                    exac = float(exac_raw.split(':')[-1])
        if exac:
            variant_obj.add_frequency('ExAC', exac)
<|end_body_2|>

Solution:
class FrequenciesExtras:
    """Methods for adding frequencies"""

    def _add_thousand_g(self, variant_obj, info_dict):
        """Add the thousand genomes frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary"""
        thousand_g = info_dict.get('1000GAF')
        if thousand_g:
            logger.debug('Updating thousand_g to: {0}'.format(thousand_g))
            variant_obj.thousand_g = float(thousand_g)
            variant_obj.add_frequency('1000GAF', variant_obj.get('thousand_g'))

    def _add_gmaf(self, variant_obj, info_dict):
        """Add the gmaf frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary"""
        for transcript in variant_obj.transcripts:
            gmaf_raw = transcript.GMAF
            if gmaf_raw:
                gmaf = float(gmaf_raw.split(':')[-1])
                variant_obj.add_frequency('GMAF', gmaf)
                if not variant_obj.thousand_g:
                    variant_obj.thousand_g = gmaf

    def _add_exac(self, variant_obj, info_dict):
        """Add the gmaf frequency Args: variant_obj (puzzle.models.Variant) info_dict (dict): A info dictionary"""
        exac = None
        exac_keys = ['ExAC', 'EXAC', 'ExACAF', 'EXACAF']
        for key in exac_keys:
            if info_dict.get(key):
                exac = float(info_dict[key])
        if not exac:
            for transcript in variant_obj.transcripts:
                exac_raw = transcript.ExAC_MAF
                if exac_raw:
                    exac = float(exac_raw.split(':')[-1])
        if exac:
            variant_obj.add_frequency('ExAC', exac)


moveZeroes

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

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def moveZeroes(self, nums: List[int]) -> None: 执行用时： 36 ms , 在所有 Python3 提交中击败了 90.63% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 44.04% 的用户 :param nums: :return:
- def moveZeroes2(self, nums: List[int]) -> None: 执行用时： 40 ms , 在所有 Python3 提交中击败了 77.26% 的用户 内存消耗： 15.3 MB , 在所有 Python3 提交中击败了 6.02% 的用户 :param nums: :return:
- def moveZeroes1(self, nums: List[int]) -> None: 执行用时： 368 ms , 在所有 Python3 提交中击败了 5.54% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 44.04% 的用户

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def moveZeroes(self, nums: List[int]) -> None: 执行用时： 36 ms , 在所有 Python3 提交中击败了 90.63% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 44.04% 的用户 :param nums: :return:
- def moveZeroes2(self, nums: List[int]) -> None: 执行用时： 40 ms , 在所有 Python3 提交中击败了 77.26% 的用户 内存消耗： 15.3 MB , 在所有 Python3 提交中击败了 6.02% 的用户 :param nums: :return:
- def moveZeroes1(self, nums: List[int]) -> None: 执行用时： 368 ms , 在所有 Python3 提交中击败了 5.54% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 44.04% 的用户

<|skeleton|>
class Solution:

    def moveZeroes(self, nums: List[int]) -> None:
        """执行用时： 36 ms , 在所有 Python3 提交中击败了 90.63% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 44.04% 的用户 :param nums: :return:"""
        <|body_0|>

    def moveZeroes2(self, nums: List[int]) -> None:
        """执行用时： 40 ms , 在所有 Python3 提交中击败了 77.26% 的用户 内存消耗： 15.3 MB , 在所有 Python3 提交中击败了 6.02% 的用户 :param nums: :return:"""
        <|body_1|>

    def moveZeroes1(self, nums: List[int]) -> None:
        """执行用时： 368 ms , 在所有 Python3 提交中击败了 5.54% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 44.04% 的用户"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        start = end = 0
        len_nums = len(nums)
        while start < len_nums and nums[start] != 0:
            start += 1
            end += 1
        while start < len_nums:
            while end < len_nums and nums[end] == 0:
                end += 1
            if end == len_nums:
                break
            nums[start] = nums[end]
            start += 1
            end += 1
        while start < len(nums):
            nums[start] = 0
            start += 1
        return nums
<|end_body_0|>

<|body_start_1|>
        fast = slow = 0
        while fast < len(nums):
            while slow < len(nums) and nums[slow] != 0:
                slow += 1
                fast += 1
            if fast < len(nums) and nums[fast] != 0:
                nums[fast], nums[slow] = (nums[slow], nums[fast])
                slow += 1
            fast += 1
        print(nums)
<|end_body_1|>

<|body_start_2|>
        if len(nums) == 0:
            return
        len_nums = len(nums) - 1
        start = 0
        while start < len_nums:
            while start < len_nums and nums[start] != 0:
                start += 1
            index = start
            while index < len_nums and nums[index] == 0:
                index += 1
            if index == len_nums and nums[index] == 0:
                break
            if index > start:
                nums[start] = nums[index]
                nums[index] = 0
                start += 1
                index += 1
        print(nums)
        pass
<|end_body_2|>

Solution:
class Solution:
    def moveZeroes(self, nums: List[int]) -> None:
        """执行用时： 36 ms , 在所有 Python3 提交中击败了 90.63% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 44.04% 的用户 :param nums: :return:"""
        start = end = 0
        len_nums = len(nums)
        while start < len_nums and nums[start] != 0:
            start += 1
            end += 1
        while start < len_nums:
            while end < len_nums and nums[end] == 0:
                end += 1
            if end == len_nums:
                break
            nums[start] = nums[end]
            start += 1
            end += 1
        while start < len(nums):
            nums[start] = 0
            start += 1
        return nums

    def moveZeroes2(self, nums: List[int]) -> None:
        """执行用时： 40 ms , 在所有 Python3 提交中击败了 77.26% 的用户 内存消耗： 15.3 MB , 在所有 Python3 提交中击败了 6.02% 的用户 :param nums: :return:"""
        fast = slow = 0
        while fast < len(nums):
            while slow < len(nums) and nums[slow] != 0:
                slow += 1
                fast += 1
            if fast < len(nums) and nums[fast] != 0:
                nums[fast], nums[slow] = (nums[slow], nums[fast])
                slow += 1
            fast += 1
        print(nums)

    def moveZeroes1(self, nums: List[int]) -> None:
        """执行用时： 368 ms , 在所有 Python3 提交中击败了 5.54% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 44.04% 的用户"""
        if len(nums) == 0:
            return
        len_nums = len(nums) - 1
        start = 0
        while start < len_nums:
            while start < len_nums and nums[start] != 0:
                start += 1
            index = start
            while index < len_nums and nums[index] == 0:
                index += 1
            if index == len_nums and nums[index] == 0:
                break
            if index > start:
                nums[start] = nums[index]
                nums[index] = 0
                start += 1
                index += 1
        print(nums)
        pass


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

Class description:
Implement the rpcAgent class.

Method signatures and docstrings:
- def __init__(self): 构造方法 :return: 无
- def __run_commend(self, commend): 运行命令方法 :param commend: 要执行的命令 :return: 返回命令执行的结果
- def __on_request(self, ch, method, props, body): 回调方法，当收到消息的时候将自动调用这个方法 :param ch: :param method: :param props: :param body: :return:
- def run(self): agent入口方法 :return:

Implement the Python class `rpcAgent` described below.

Class description:
Implement the rpcAgent class.

Method signatures and docstrings:
- def __init__(self): 构造方法 :return: 无
- def __run_commend(self, commend): 运行命令方法 :param commend: 要执行的命令 :return: 返回命令执行的结果
- def __on_request(self, ch, method, props, body): 回调方法，当收到消息的时候将自动调用这个方法 :param ch: :param method: :param props: :param body: :return:
- def run(self): agent入口方法 :return:

<|skeleton|>
class rpcAgent:

    def __init__(self):
        """构造方法 :return: 无"""
        <|body_0|>

    def __run_commend(self, commend):
        """运行命令方法 :param commend: 要执行的命令 :return: 返回命令执行的结果"""
        <|body_1|>

    def __on_request(self, ch, method, props, body):
        """回调方法，当收到消息的时候将自动调用这个方法 :param ch: :param method: :param props: :param body: :return:"""
        <|body_2|>

    def run(self):
        """agent入口方法 :return:"""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        self.__connection = pika.BlockingConnection(pika.ConnectionParameters(host=conf.RBMQ_HOST))
        self.__log = mylib.mylog(conf.AGENT_LOG)
        self.__channel = self.__connection.channel()
        self.__channel.exchange_declare(exchange=conf.EXCHANGE, type='fanout')
        res = self.__channel.queue_declare(durable=True)
        self.__queue_name = res.method.queue
<|end_body_0|>

<|body_start_1|>
        import subprocess
        try:
            p = subprocess.Popen(commend, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
            error = p.stderr.read()
            if not error:
                res = p.stdout.read()
            else:
                res = error
            res = str(res, 'utf8')
        except Exception as e:
            res = e
        print(res)
        return '[%s]\n%s' % (conf.AGENT_NAME, res)
<|end_body_1|>

<|body_start_2|>
        commend = body.decode()
        self.__log.info('run commend %s' % body.decode())
        response = self.__run_commend(commend)
        ch.basic_publish(exchange='', routing_key=props.reply_to, properties=pika.BasicProperties(correlation_id=props.correlation_id), body=str(response))
        ch.basic_ack(delivery_tag=method.delivery_tag)
<|end_body_2|>

<|body_start_3|>
        self.__channel.queue_bind(exchange=conf.EXCHANGE, queue=self.__queue_name)
        self.__channel.basic_consume(self.__on_request, queue=self.__queue_name)
        print(' [x] Awaiting RPC requests')
        self.__channel.start_consuming()
<|end_body_3|>

Solution:
class rpcAgent:
    def __init__(self):
        """构造方法 :return: 无"""
        self.__connection = pika.BlockingConnection(pika.ConnectionParameters(host=conf.RBMQ_HOST))
        self.__log = mylib.mylog(conf.AGENT_LOG)
        self.__channel = self.__connection.channel()
        self.__channel.exchange_declare(exchange=conf.EXCHANGE, type='fanout')
        res = self.__channel.queue_declare(durable=True)
        self.__queue_name = res.method.queue

    def __run_commend(self, commend):
        """运行命令方法 :param commend: 要执行的命令 :return: 返回命令执行的结果"""
        import subprocess
        try:
            p = subprocess.Popen(commend, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
            error = p.stderr.read()
            if not error:
                res = p.stdout.read()
            else:
                res = error
            res = str(res, 'utf8')
        except Exception as e:
            res = e
        print(res)
        return '[%s]\n%s' % (conf.AGENT_NAME, res)

    def __on_request(self, ch, method, props, body):
        """回调方法，当收到消息的时候将自动调用这个方法 :param ch: :param method: :param props: :param body: :return:"""
        commend = body.decode()
        self.__log.info('run commend %s' % body.decode())
        response = self.__run_commend(commend)
        ch.basic_publish(exchange='', routing_key=props.reply_to, properties=pika.BasicProperties(correlation_id=props.correlation_id), body=str(response))
        ch.basic_ack(delivery_tag=method.delivery_tag)

    def run(self):
        """agent入口方法 :return:"""
        self.__channel.queue_bind(exchange=conf.EXCHANGE, queue=self.__queue_name)
        self.__channel.basic_consume(self.__on_request, queue=self.__queue_name)
        print(' [x] Awaiting RPC requests')
        self.__channel.start_consuming()


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

Class description:
Implement the Calculate class.

Method signatures and docstrings:
- def __init__(self): Description: This method contains attributes that provide responses. Args: None. Returns: affirmative, negative
- def list_input(self): Description: This method prompts the user 3 times in order to get all the sides of the triangle. Args: None. Returns: sides
- def pythag_check(self, sides): Description: This method utilizes a^2 + b^2 = c^2 to determine if any variant of sides entered is a pythagorean triple. Args: sides Returns: None.

Implement the Python class `Calculate` described below.

Class description:
Implement the Calculate class.

Method signatures and docstrings:
- def __init__(self): Description: This method contains attributes that provide responses. Args: None. Returns: affirmative, negative
- def list_input(self): Description: This method prompts the user 3 times in order to get all the sides of the triangle. Args: None. Returns: sides
- def pythag_check(self, sides): Description: This method utilizes a^2 + b^2 = c^2 to determine if any variant of sides entered is a pythagorean triple. Args: sides Returns: None.

<|skeleton|>
class Calculate:

    def __init__(self):
        """Description: This method contains attributes that provide responses. Args: None. Returns: affirmative, negative"""
        <|body_0|>

    def list_input(self):
        """Description: This method prompts the user 3 times in order to get all the sides of the triangle. Args: None. Returns: sides"""
        <|body_1|>

    def pythag_check(self, sides):
        """Description: This method utilizes a^2 + b^2 = c^2 to determine if any variant of sides entered is a pythagorean triple. Args: sides Returns: None."""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        affirmative = 'This is a pythagorean triple.'
        self.affirmative = affirmative
        negative = 'This is not a pythagorean triple.'
        self.negative = negative
<|end_body_0|>

<|body_start_1|>
        count = 0
        sides = []
        while count < 3:
            answers = float(input('Please enter the sides of the triangle: '))
            sides.append(answers)
            count += 1
        return sides
<|end_body_1|>

<|body_start_2|>
        call = Calculate()
        num1 = sides[0] ** 2 + sides[1] ** 2
        num2 = sides[2] ** 2
        num3 = sides[2] ** 2 + sides[1] ** 2
        num4 = sides[0] ** 2
        num5 = sides[2] ** 2 + sides[0] ** 2
        num6 = sides[1] ** 2
        if num1 == num2:
            print(call.affirmative)
        elif num3 == num4:
            print(call.affirmative)
        elif num5 == num6:
            print(call.affirmative)
        else:
            print(call.negative)
<|end_body_2|>

Solution:
class Calculate:
    def __init__(self):
        """Description: This method contains attributes that provide responses. Args: None. Returns: affirmative, negative"""
        affirmative = 'This is a pythagorean triple.'
        self.affirmative = affirmative
        negative = 'This is not a pythagorean triple.'
        self.negative = negative

    def list_input(self):
        """Description: This method prompts the user 3 times in order to get all the sides of the triangle. Args: None. Returns: sides"""
        count = 0
        sides = []
        while count < 3:
            answers = float(input('Please enter the sides of the triangle: '))
            sides.append(answers)
            count += 1
        return sides

    def pythag_check(self, sides):
        """Description: This method utilizes a^2 + b^2 = c^2 to determine if any variant of sides entered is a pythagorean triple. Args: sides Returns: None."""
        call = Calculate()
        num1 = sides[0] ** 2 + sides[1] ** 2
        num2 = sides[2] ** 2
        num3 = sides[2] ** 2 + sides[1] ** 2
        num4 = sides[0] ** 2
        num5 = sides[2] ** 2 + sides[0] ** 2
        num6 = sides[1] ** 2
        if num1 == num2:
            print(call.affirmative)
        elif num3 == num4:
            print(call.affirmative)
        elif num5 == num6:
            print(call.affirmative)
        else:
            print(call.negative)


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

Class description:
Implement the BlendArticleReadTest class.

Method signatures and docstrings:
- def test_article_read_unsubmitted(self): Blend::Article Read—Unsubmitted .. note:: The article in question has not been submitted and thus nothing exists in the system for the requested article.
- def test_article_read_submitted_incomplete(self): Blend::Article Read—Submitted,Incomplete .. note:: The article in question has been submitted but the spread process has not populated any information beyond the first consumption. * created_at
- def test_article_read_submitted_complete(self): Blend::Article Read—Submitted,Complete .. note:: The article in question has been submitted and the spread process has finished processing the following items: * HTML Sanitization

Implement the Python class `BlendArticleReadTest` described below.

Class description:
Implement the BlendArticleReadTest class.

Method signatures and docstrings:
- def test_article_read_unsubmitted(self): Blend::Article Read—Unsubmitted .. note:: The article in question has not been submitted and thus nothing exists in the system for the requested article.
- def test_article_read_submitted_incomplete(self): Blend::Article Read—Submitted,Incomplete .. note:: The article in question has been submitted but the spread process has not populated any information beyond the first consumption. * created_at
- def test_article_read_submitted_complete(self): Blend::Article Read—Submitted,Complete .. note:: The article in question has been submitted and the spread process has finished processing the following items: * HTML Sanitization

<|skeleton|>
class BlendArticleReadTest:

    def test_article_read_unsubmitted(self):
        """Blend::Article Read—Unsubmitted .. note:: The article in question has not been submitted and thus nothing exists in the system for the requested article."""
        <|body_0|>

    def test_article_read_submitted_incomplete(self):
        """Blend::Article Read—Submitted,Incomplete .. note:: The article in question has been submitted but the spread process has not populated any information beyond the first consumption. * created_at"""
        <|body_1|>

    def test_article_read_submitted_complete(self):
        """Blend::Article Read—Submitted,Complete .. note:: The article in question has been submitted and the spread process has finished processing the following items: * HTML Sanitization"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        self.mock_collection.find_one.return_value = None
        for uuid, url in self.articles.iteritems():
            response = self.application.get(self.base_url + str(uuid))
            self.assertIn('404', response.status)
<|end_body_0|>

<|body_start_1|>
        for uuid, url in self.articles.iteritems():
            self.mock_collection.find_one.return_value = {'_id': uuid.hex, 'url': url, 'created_at': datetime.datetime(2013, 8, 4, 14, 4, 12, 639560)}
            response = self.application.get(self.base_url + str(uuid))
            self.mock_collection.find_one.assert_called_once_with({'_id': uuid.hex})
            self.mock_collection.reset_mock()
            self.assertIn('404', response.status)
<|end_body_1|>

<|body_start_2|>
        for uuid, url in self.articles.iteritems():
            self.mock_collection.find_one.return_value = {'_id': uuid.hex, 'url': url, 'created_at': datetime.datetime(2013, 8, 4, 14, 16, 20, 77773), 'etag': 'bf6285d832a356e1bf509a63edc8870f', 'parsed_at': datetime.datetime(2013, 8, 4, 14, 16, 21, 77773), 'size': 31052, 'text_container_name': '44d85795', 'text_object_name': '248d-5899-b8ca-ac2bd8233755'}
            mock_object = self._get_attached_mock(self.mock_container.get_object)
            mock_object.fetch.return_value = 'Redacted for testing purposes'
            response = self.application.get(self.base_url + str(uuid))
            self.mock_collection.find_one.assert_called_once_with({'_id': uuid.hex})
            self.mock_collection.reset_mock()
            mock_object.fetch.assert_called_once_with()
            self.assertIn('200', response.status)
            self.assertEqual('application/json', response.headers.get('Content-Type'))
            self.assertEqual('http://margarine.raxsavvy.com', response.headers.get('Access-Control-Allow-Origin'))
<|end_body_2|>

Solution:
class BlendArticleReadTest:
    def test_article_read_unsubmitted(self):
        """Blend::Article Read—Unsubmitted .. note:: The article in question has not been submitted and thus nothing exists in the system for the requested article."""
        self.mock_collection.find_one.return_value = None
        for uuid, url in self.articles.iteritems():
            response = self.application.get(self.base_url + str(uuid))
            self.assertIn('404', response.status)

    def test_article_read_submitted_incomplete(self):
        """Blend::Article Read—Submitted,Incomplete .. note:: The article in question has been submitted but the spread process has not populated any information beyond the first consumption. * created_at"""
        for uuid, url in self.articles.iteritems():
            self.mock_collection.find_one.return_value = {'_id': uuid.hex, 'url': url, 'created_at': datetime.datetime(2013, 8, 4, 14, 4, 12, 639560)}
            response = self.application.get(self.base_url + str(uuid))
            self.mock_collection.find_one.assert_called_once_with({'_id': uuid.hex})
            self.mock_collection.reset_mock()
            self.assertIn('404', response.status)

    def test_article_read_submitted_complete(self):
        """Blend::Article Read—Submitted,Complete .. note:: The article in question has been submitted and the spread process has finished processing the following items: * HTML Sanitization"""
        for uuid, url in self.articles.iteritems():
            self.mock_collection.find_one.return_value = {'_id': uuid.hex, 'url': url, 'created_at': datetime.datetime(2013, 8, 4, 14, 16, 20, 77773), 'etag': 'bf6285d832a356e1bf509a63edc8870f', 'parsed_at': datetime.datetime(2013, 8, 4, 14, 16, 21, 77773), 'size': 31052, 'text_container_name': '44d85795', 'text_object_name': '248d-5899-b8ca-ac2bd8233755'}
            mock_object = self._get_attached_mock(self.mock_container.get_object)
            mock_object.fetch.return_value = 'Redacted for testing purposes'
            response = self.application.get(self.base_url + str(uuid))
            self.mock_collection.find_one.assert_called_once_with({'_id': uuid.hex})
            self.mock_collection.reset_mock()
            mock_object.fetch.assert_called_once_with()
            self.assertIn('200', response.status)
            self.assertEqual('application/json', response.headers.get('Content-Type'))
            self.assertEqual('http://margarine.raxsavvy.com', response.headers.get('Access-Control-Allow-Origin'))


call

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

Class description:
TRU-NET Encoder-Decoder Encoder

Method signatures and docstrings:
- def __init__(self, t_params, encoder_params, h_w, attn_ablation=0): Args: t_params (dict): params related to training/testing encoder_params (dict): params related to encoder h_w ([type]): height and width of convolution output for this layer attn_ablation (int, optional): ablation mode for encoder layers. Defaults to 0 for cross attention 1 = Averaging 2 = Concatenation 3 = Last hidden state 4 = Self Attention
- def call(self, _input, training=True): [summary] Args: _input ([type]): (batch_size, seq_len, h, w, c) training (bool, optional): [description]. Defaults to True. Returns: [type]: (batch_size, seq_len1, h1, w1, c1)

Implement the Python class `TRUNET_Encoder` described below.

Class description:
TRU-NET Encoder-Decoder Encoder

Method signatures and docstrings:
- def __init__(self, t_params, encoder_params, h_w, attn_ablation=0): Args: t_params (dict): params related to training/testing encoder_params (dict): params related to encoder h_w ([type]): height and width of convolution output for this layer attn_ablation (int, optional): ablation mode for encoder layers. Defaults to 0 for cross attention 1 = Averaging 2 = Concatenation 3 = Last hidden state 4 = Self Attention
- def call(self, _input, training=True): [summary] Args: _input ([type]): (batch_size, seq_len, h, w, c) training (bool, optional): [description]. Defaults to True. Returns: [type]: (batch_size, seq_len1, h1, w1, c1)

<|skeleton|>
class TRUNET_Encoder:
    """TRU-NET Encoder-Decoder Encoder"""

    def __init__(self, t_params, encoder_params, h_w, attn_ablation=0):
        """Args: t_params (dict): params related to training/testing encoder_params (dict): params related to encoder h_w ([type]): height and width of convolution output for this layer attn_ablation (int, optional): ablation mode for encoder layers. Defaults to 0 for cross attention 1 = Averaging 2 = Concatenation 3 = Last hidden state 4 = Self Attention"""
        <|body_0|>

    def call(self, _input, training=True):
        """[summary] Args: _input ([type]): (batch_size, seq_len, h, w, c) training (bool, optional): [description]. Defaults to True. Returns: [type]: (batch_size, seq_len1, h1, w1, c1)"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        super(TRUNET_Encoder, self).__init__()
        self.encoder_params = encoder_params
        self.t_params = t_params
        self.layer_count = encoder_params['enc_layer_count']
        self.CGRU_Input_Layer = TRUNET_CGRU_Input_Layer(t_params, encoder_params['CGRUs_params'][0])
        self.CGRU_Attn_layers = []
        for idx in range(encoder_params['attn_layers_count']):
            _layer = TRUNET_CGRU_Attention_Layer(t_params, encoder_params['CGRUs_params'][idx + 1], encoder_params['ATTN_params'][idx], encoder_params['ATTN_DOWNSCALING_params_enc'], encoder_params['seq_len_factor_reduction'][idx], self.encoder_params['attn_layers_num_of_splits'][idx], h_w, attn_ablation)
            self.CGRU_Attn_layers.append(_layer)
<|end_body_0|>

<|body_start_1|>
        hidden_state = self.CGRU_Input_Layer(_input, training)
        hidden_state = self.CGRU_Attn_layers[0](hidden_state, training=training)
        hidden_states = hidden_state
        for idx in range(1, self.encoder_params['attn_layers_count']):
            hidden_state = self.CGRU_Attn_layers[idx](hidden_state, training=training)
            hidden_states = tf.concat([hidden_states, hidden_state], axis=1)
        return hidden_states
<|end_body_1|>

Solution:
class TRUNET_Encoder:
    """TRU-NET Encoder-Decoder Encoder"""

    def __init__(self, t_params, encoder_params, h_w, attn_ablation=0):
        """Args: t_params (dict): params related to training/testing encoder_params (dict): params related to encoder h_w ([type]): height and width of convolution output for this layer attn_ablation (int, optional): ablation mode for encoder layers. Defaults to 0 for cross attention 1 = Averaging 2 = Concatenation 3 = Last hidden state 4 = Self Attention"""
        super(TRUNET_Encoder, self).__init__()
        self.encoder_params = encoder_params
        self.t_params = t_params
        self.layer_count = encoder_params['enc_layer_count']
        self.CGRU_Input_Layer = TRUNET_CGRU_Input_Layer(t_params, encoder_params['CGRUs_params'][0])
        self.CGRU_Attn_layers = []
        for idx in range(encoder_params['attn_layers_count']):
            _layer = TRUNET_CGRU_Attention_Layer(t_params, encoder_params['CGRUs_params'][idx + 1], encoder_params['ATTN_params'][idx], encoder_params['ATTN_DOWNSCALING_params_enc'], encoder_params['seq_len_factor_reduction'][idx], self.encoder_params['attn_layers_num_of_splits'][idx], h_w, attn_ablation)
            self.CGRU_Attn_layers.append(_layer)

    def call(self, _input, training=True):
        """[summary] Args: _input ([type]): (batch_size, seq_len, h, w, c) training (bool, optional): [description]. Defaults to True. Returns: [type]: (batch_size, seq_len1, h1, w1, c1)"""
        hidden_state = self.CGRU_Input_Layer(_input, training)
        hidden_state = self.CGRU_Attn_layers[0](hidden_state, training=training)
        hidden_states = hidden_state
        for idx in range(1, self.encoder_params['attn_layers_count']):
            hidden_state = self.CGRU_Attn_layers[idx](hidden_state, training=training)
            hidden_states = tf.concat([hidden_states, hidden_state], axis=1)
        return hidden_states


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

Class description:
Dataclass to keep track of statistics.

Method signatures and docstrings:
- def stats_initializer(cls, shape, *, dtype=jnp.float32): Constructor to init a empty Stats instance. Args: shape: shape of the statistics (mean, mean_sq and mean_abs) dtype: the dtype of the stats (default: float32). Returns: A new instance of Stats, with statistics intialized to 0.
- def create_updated_stats(cls, stats, samples, *, axis=None, paxis_name=None, alpha=None, mask=None, exclude_zeros=False): Create a new Stats instance that represents the updated statistics. Since flax.struct.dataclass objects are frozen, this method creates a new instance of Stats with updated stats and returns it. Args: stats: A Stats dataclass object to be updated. samples: An array to update the current statistics with. axis: axis to average input samples over, e.g. to calculate stats per channel. paxis_name: the axis name used to combine batch statistics from multiple devices. See `jax.pmap` for a description of axis names. alpha: Smoothing parameter to use for moving average. If None, will use 1/n, where n is the stat count. mask: Optional boolean tensor of the same shape as 'samples' specifying which valu

Implement the Python class `Stats` described below.

Class description:
Dataclass to keep track of statistics.

Method signatures and docstrings:
- def stats_initializer(cls, shape, *, dtype=jnp.float32): Constructor to init a empty Stats instance. Args: shape: shape of the statistics (mean, mean_sq and mean_abs) dtype: the dtype of the stats (default: float32). Returns: A new instance of Stats, with statistics intialized to 0.
- def create_updated_stats(cls, stats, samples, *, axis=None, paxis_name=None, alpha=None, mask=None, exclude_zeros=False): Create a new Stats instance that represents the updated statistics. Since flax.struct.dataclass objects are frozen, this method creates a new instance of Stats with updated stats and returns it. Args: stats: A Stats dataclass object to be updated. samples: An array to update the current statistics with. axis: axis to average input samples over, e.g. to calculate stats per channel. paxis_name: the axis name used to combine batch statistics from multiple devices. See `jax.pmap` for a description of axis names. alpha: Smoothing parameter to use for moving average. If None, will use 1/n, where n is the stat count. mask: Optional boolean tensor of the same shape as 'samples' specifying which valu

<|skeleton|>
class Stats:
    """Dataclass to keep track of statistics."""

    def stats_initializer(cls, shape, *, dtype=jnp.float32):
        """Constructor to init a empty Stats instance. Args: shape: shape of the statistics (mean, mean_sq and mean_abs) dtype: the dtype of the stats (default: float32). Returns: A new instance of Stats, with statistics intialized to 0."""
        <|body_0|>

    def create_updated_stats(cls, stats, samples, *, axis=None, paxis_name=None, alpha=None, mask=None, exclude_zeros=False):
        """Create a new Stats instance that represents the updated statistics. Since flax.struct.dataclass objects are frozen, this method creates a new instance of Stats with updated stats and returns it. Args: stats: A Stats dataclass object to be updated. samples: An array to update the current statistics with. axis: axis to average input samples over, e.g. to calculate stats per channel. paxis_name: the axis name used to combine batch statistics from multiple devices. See `jax.pmap` for a description of axis names. alpha: Smoothing parameter to use for moving average. If None, will use 1/n, where n is the stat count. mask: Optional boolean tensor of the same shape as 'samples' specifying which valu"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        key = jax.random.PRNGKey(1)
        shape = tuple(shape)
        return cls(n=0, mean=flax.nn.initializers.zeros(key, shape, dtype), mean_abs=flax.nn.initializers.zeros(key, shape, dtype), mean_sq=flax.nn.initializers.zeros(key, shape, dtype), mean_batch_maximum=flax.nn.initializers.zeros(key, shape, dtype), mean_batch_minimum=flax.nn.initializers.zeros(key, shape, dtype))
<|end_body_0|>

<|body_start_1|>
        if mask is None:
            mask = jnp.full(samples.shape, True)
        shape_utils.assert_shapes_compatible(samples.shape, mask.shape)
        mask = jnp.broadcast_to(mask, samples.shape)
        if exclude_zeros:
            mask = mask & (samples != 0)

        def _moving_avg(old_avg, new_val, masked_reduction_fn):
            masked_new_val_reduced = masked_reduction_fn(new_val, mask=mask, axis=axis, paxis_name=paxis_name, keepdims=True)
            valid_mask = jnp.isfinite(masked_new_val_reduced)
            delta = jnp.where(valid_mask, masked_new_val_reduced - old_avg, 0)
            new_avg = old_avg + alpha * delta
            return new_avg
        new_n = stats.n + 1
        if alpha is None:
            alpha = 1.0 / new_n
        new_mean = _moving_avg(stats.mean, samples, masked_reduction_fn=masked_mean)
        new_mean_abs = _moving_avg(stats.mean_abs, jnp.abs(samples), masked_reduction_fn=masked_mean)
        new_mean_sq = _moving_avg(stats.mean_sq, jnp.square(samples), masked_reduction_fn=masked_mean)
        new_mean_batch_minimum = _moving_avg(stats.mean_batch_minimum, samples, masked_reduction_fn=masked_mean_of_min)
        new_mean_batch_maximum = _moving_avg(stats.mean_batch_maximum, samples, masked_reduction_fn=masked_mean_of_max)
        return cls(n=new_n, mean=new_mean, mean_abs=new_mean_abs, mean_sq=new_mean_sq, mean_batch_minimum=new_mean_batch_minimum, mean_batch_maximum=new_mean_batch_maximum)
<|end_body_1|>

Solution:
class Stats:
    """Dataclass to keep track of statistics."""

    def stats_initializer(cls, shape, *, dtype=jnp.float32):
        """Constructor to init a empty Stats instance. Args: shape: shape of the statistics (mean, mean_sq and mean_abs) dtype: the dtype of the stats (default: float32). Returns: A new instance of Stats, with statistics intialized to 0."""
        key = jax.random.PRNGKey(1)
        shape = tuple(shape)
        return cls(n=0, mean=flax.nn.initializers.zeros(key, shape, dtype), mean_abs=flax.nn.initializers.zeros(key, shape, dtype), mean_sq=flax.nn.initializers.zeros(key, shape, dtype), mean_batch_maximum=flax.nn.initializers.zeros(key, shape, dtype), mean_batch_minimum=flax.nn.initializers.zeros(key, shape, dtype))

    def create_updated_stats(cls, stats, samples, *, axis=None, paxis_name=None, alpha=None, mask=None, exclude_zeros=False):
        """Create a new Stats instance that represents the updated statistics. Since flax.struct.dataclass objects are frozen, this method creates a new instance of Stats with updated stats and returns it. Args: stats: A Stats dataclass object to be updated. samples: An array to update the current statistics with. axis: axis to average input samples over, e.g. to calculate stats per channel. paxis_name: the axis name used to combine batch statistics from multiple devices. See `jax.pmap` for a description of axis names. alpha: Smoothing parameter to use for moving average. If None, will use 1/n, where n is the stat count. mask: Optional boolean tensor of the same shape as 'samples' specifying which valu"""
        if mask is None:
            mask = jnp.full(samples.shape, True)
        shape_utils.assert_shapes_compatible(samples.shape, mask.shape)
        mask = jnp.broadcast_to(mask, samples.shape)
        if exclude_zeros:
            mask = mask & (samples != 0)

        def _moving_avg(old_avg, new_val, masked_reduction_fn):
            masked_new_val_reduced = masked_reduction_fn(new_val, mask=mask, axis=axis, paxis_name=paxis_name, keepdims=True)
            valid_mask = jnp.isfinite(masked_new_val_reduced)
            delta = jnp.where(valid_mask, masked_new_val_reduced - old_avg, 0)
            new_avg = old_avg + alpha * delta
            return new_avg
        new_n = stats.n + 1
        if alpha is None:
            alpha = 1.0 / new_n
        new_mean = _moving_avg(stats.mean, samples, masked_reduction_fn=masked_mean)
        new_mean_abs = _moving_avg(stats.mean_abs, jnp.abs(samples), masked_reduction_fn=masked_mean)
        new_mean_sq = _moving_avg(stats.mean_sq, jnp.square(samples), masked_reduction_fn=masked_mean)
        new_mean_batch_minimum = _moving_avg(stats.mean_batch_minimum, samples, masked_reduction_fn=masked_mean_of_min)
        new_mean_batch_maximum = _moving_avg(stats.mean_batch_maximum, samples, masked_reduction_fn=masked_mean_of_max)
        return cls(n=new_n, mean=new_mean, mean_abs=new_mean_abs, mean_sq=new_mean_sq, mean_batch_minimum=new_mean_batch_minimum, mean_batch_maximum=new_mean_batch_maximum)


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

Class description:
Implement the unitTests class.

Method signatures and docstrings:
- def test_single_test(self): Forces class testing
- def time_limit_test(self, nmax): Timelimit testing

Implement the Python class `unitTests` described below.

Class description:
Implement the unitTests class.

Method signatures and docstrings:
- def test_single_test(self): Forces class testing
- def time_limit_test(self, nmax): Timelimit testing

<|skeleton|>
class unitTests:

    def test_single_test(self):
        """Forces class testing"""
        <|body_0|>

    def time_limit_test(self, nmax):
        """Timelimit testing"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        test = '20 40 60 80 100\n0 1 2 3 4\n1 0'
        d = Forces(test)
        self.assertEqual(d.numw, [0, 1, 2, 3, 4])
        self.assertEqual(Forces(test).calculate(), '4900')
        test = '119 119 119 119 119\n0 0 0 0 0\n10 0'
        self.assertEqual(Forces(test).calculate(), '4930')
        test = ''
        test = ''
<|end_body_0|>

<|body_start_1|>
        import random
        import timeit
        test = str(nmax) + ' ' + str(nmax) + '\n'
        numnums = [str(i) + ' ' + str(i + 1) for i in range(nmax)]
        test += '\n'.join(numnums) + '\n'
        nums = [random.randint(1, 10000) for i in range(nmax)]
        test += ' '.join(map(str, nums)) + '\n'
        start = timeit.default_timer()
        d = Forces(test)
        calc = timeit.default_timer()
        d.calculate()
        stop = timeit.default_timer()
        print('\nTimelimit Test: ' + '{0:.3f}s (init {1:.3f}s calc {2:.3f}s)'.format(stop - start, calc - start, stop - calc))
<|end_body_1|>

Solution:
class unitTests:
    def test_single_test(self):
        """Forces class testing"""
        test = '20 40 60 80 100\n0 1 2 3 4\n1 0'
        d = Forces(test)
        self.assertEqual(d.numw, [0, 1, 2, 3, 4])
        self.assertEqual(Forces(test).calculate(), '4900')
        test = '119 119 119 119 119\n0 0 0 0 0\n10 0'
        self.assertEqual(Forces(test).calculate(), '4930')
        test = ''
        test = ''

    def time_limit_test(self, nmax):
        """Timelimit testing"""
        import random
        import timeit
        test = str(nmax) + ' ' + str(nmax) + '\n'
        numnums = [str(i) + ' ' + str(i + 1) for i in range(nmax)]
        test += '\n'.join(numnums) + '\n'
        nums = [random.randint(1, 10000) for i in range(nmax)]
        test += ' '.join(map(str, nums)) + '\n'
        start = timeit.default_timer()
        d = Forces(test)
        calc = timeit.default_timer()
        d.calculate()
        stop = timeit.default_timer()
        print('\nTimelimit Test: ' + '{0:.3f}s (init {1:.3f}s calc {2:.3f}s)'.format(stop - start, calc - start, stop - calc))


lock

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

Class description:
Implement the LockingTree class.

Method signatures and docstrings:
- def __init__(self, parent): :type parent: List[int]
- def lock(self, num, user): :type num: int :type user: int :rtype: bool
- def unlock(self, num, user): :type num: int :type user: int :rtype: bool
- def upgrade(self, num, user): :type num: int :type user: int :rtype: bool

Implement the Python class `LockingTree` described below.

Class description:
Implement the LockingTree class.

Method signatures and docstrings:
- def __init__(self, parent): :type parent: List[int]
- def lock(self, num, user): :type num: int :type user: int :rtype: bool
- def unlock(self, num, user): :type num: int :type user: int :rtype: bool
- def upgrade(self, num, user): :type num: int :type user: int :rtype: bool

<|skeleton|>
class LockingTree:

    def __init__(self, parent):
        """:type parent: List[int]"""
        <|body_0|>

    def lock(self, num, user):
        """:type num: int :type user: int :rtype: bool"""
        <|body_1|>

    def unlock(self, num, user):
        """:type num: int :type user: int :rtype: bool"""
        <|body_2|>

    def upgrade(self, num, user):
        """:type num: int :type user: int :rtype: bool"""
        <|body_3|>

<|end_skeleton|>

<|body_start_0|>
        self.__parent = parent
        self.__children = [[] for _ in xrange(len(parent))]
        for i, x in enumerate(parent):
            if x != -1:
                self.__children[x].append(i)
        self.__locked = {}
<|end_body_0|>

<|body_start_1|>
        if num in self.__locked:
            return False
        self.__locked[num] = user
        return True
<|end_body_1|>

<|body_start_2|>
        if self.__locked.get(num) != user:
            return False
        del self.__locked[num]
        return True
<|end_body_2|>

<|body_start_3|>
        node = num
        while node != -1:
            if node in self.__locked:
                return False
            node = self.__parent[node]
        result = False
        stk = [num]
        while stk:
            node = stk.pop()
            if node in self.__locked:
                del self.__locked[node]
                result = True
            for child in self.__children[node]:
                stk.append(child)
        if result:
            self.__locked[num] = user
        return result
<|end_body_3|>

Solution:
class LockingTree:
    def __init__(self, parent):
        """:type parent: List[int]"""
        self.__parent = parent
        self.__children = [[] for _ in xrange(len(parent))]
        for i, x in enumerate(parent):
            if x != -1:
                self.__children[x].append(i)
        self.__locked = {}

    def lock(self, num, user):
        """:type num: int :type user: int :rtype: bool"""
        if num in self.__locked:
            return False
        self.__locked[num] = user
        return True

    def unlock(self, num, user):
        """:type num: int :type user: int :rtype: bool"""
        if self.__locked.get(num) != user:
            return False
        del self.__locked[num]
        return True

    def upgrade(self, num, user):
        """:type num: int :type user: int :rtype: bool"""
        node = num
        while node != -1:
            if node in self.__locked:
                return False
            node = self.__parent[node]
        result = False
        stk = [num]
        while stk:
            node = stk.pop()
            if node in self.__locked:
                del self.__locked[node]
                result = True
            for child in self.__children[node]:
                stk.append(child)
        if result:
            self.__locked[num] = user
        return result


delete

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

Class description:
This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/permissions/(?P<permission_id>[0-9]+)/$

Method signatures and docstrings:
- def get_object(self, request, *args, **kwargs): Trying to get permission(permission and repository id) in database and return them :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: UserPermissions object or DoesNotExist exception :raise UserPermissions.DoesNotExist
- def get(self, request: Request, *args, **kwargs: dict) -> Response: This method handle GET request return JSON with detailed information for specific permission :param request: http request :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: HTTP response with serialized in JSON permission data
- def delete(self, request: Request, *args, **kwargs: dict) -> Response: This method handle DELETE http request on permission detail endpoint :param request: http request :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: on success HTTP 204 status code, else return 404

Implement the Python class `PermissionDetail` described below.

Class description:
This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/permissions/(?P<permission_id>[0-9]+)/$

Method signatures and docstrings:
- def get_object(self, request, *args, **kwargs): Trying to get permission(permission and repository id) in database and return them :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: UserPermissions object or DoesNotExist exception :raise UserPermissions.DoesNotExist
- def get(self, request: Request, *args, **kwargs: dict) -> Response: This method handle GET request return JSON with detailed information for specific permission :param request: http request :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: HTTP response with serialized in JSON permission data
- def delete(self, request: Request, *args, **kwargs: dict) -> Response: This method handle DELETE http request on permission detail endpoint :param request: http request :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: on success HTTP 204 status code, else return 404

<|skeleton|>
class PermissionDetail:
    """This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/permissions/(?P<permission_id>[0-9]+)/$"""

    def get_object(self, request, *args, **kwargs):
        """Trying to get permission(permission and repository id) in database and return them :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: UserPermissions object or DoesNotExist exception :raise UserPermissions.DoesNotExist"""
        <|body_0|>

    def get(self, request: Request, *args, **kwargs: dict) -> Response:
        """This method handle GET request return JSON with detailed information for specific permission :param request: http request :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: HTTP response with serialized in JSON permission data"""
        <|body_1|>

    def delete(self, request: Request, *args, **kwargs: dict) -> Response:
        """This method handle DELETE http request on permission detail endpoint :param request: http request :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: on success HTTP 204 status code, else return 404"""
        <|body_2|>

<|end_skeleton|>

<|body_start_0|>
        try:
            permission = UserPermissions.objects.get(id=kwargs['permission_id'], repository_id=kwargs['repository_id'])
        except UserPermissions.DoesNotExist:
            raise Http404
        super(PermissionDetail, self).check_permissions(request)
        return permission
<|end_body_0|>

<|body_start_1|>
        permission = self.get_object(request, **kwargs)
        serializer_context = {'request': Request(request), 'repository_id': kwargs['repository_id']}
        serializer = PermissionSerializer(permission, context=serializer_context)
        return Response(serializer.data)
<|end_body_1|>

<|body_start_2|>
        permission = self.get_object(request, **kwargs)
        super(PermissionDetail, self).check_object_permissions(request, permission)
        permission.delete()
        return Response(status=status.HTTP_204_NO_CONTENT)
<|end_body_2|>

Solution:
class PermissionDetail:
    """This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/permissions/(?P<permission_id>[0-9]+)/$"""

    def get_object(self, request, *args, **kwargs):
        """Trying to get permission(permission and repository id) in database and return them :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: UserPermissions object or DoesNotExist exception :raise UserPermissions.DoesNotExist"""
        try:
            permission = UserPermissions.objects.get(id=kwargs['permission_id'], repository_id=kwargs['repository_id'])
        except UserPermissions.DoesNotExist:
            raise Http404
        super(PermissionDetail, self).check_permissions(request)
        return permission

    def get(self, request: Request, *args, **kwargs: dict) -> Response:
        """This method handle GET request return JSON with detailed information for specific permission :param request: http request :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: HTTP response with serialized in JSON permission data"""
        permission = self.get_object(request, **kwargs)
        serializer_context = {'request': Request(request), 'repository_id': kwargs['repository_id']}
        serializer = PermissionSerializer(permission, context=serializer_context)
        return Response(serializer.data)

    def delete(self, request: Request, *args, **kwargs: dict) -> Response:
        """This method handle DELETE http request on permission detail endpoint :param request: http request :param args: other parameters :param kwargs: dict parsed url variables {"permission_id": "id", "repository_id":"id"} :return: on success HTTP 204 status code, else return 404"""
        permission = self.get_object(request, **kwargs)
        super(PermissionDetail, self).check_object_permissions(request, permission)
        permission.delete()
        return Response(status=status.HTTP_204_NO_CONTENT)


transfer

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

Class description:
AgentSession class is a child class of the abstract class "Session" It allows the user to perform privileged bank transactions - deposit, withdraw, transfer, create account and delete account It also verfies input looking for constraints and value error (invalid amount)

Method signatures and docstrings:
- def deposit(self, account, amount): Checks amount and makes deposit to account
- def withdraw(self, account, amount): Checks amount and withdraws from account
- def transfer(self, account1, account2, amount): Checks amount and makes transfer
- def is_account_new(self, account): Check if the account is a new account created in this session
- def create_account(self, account, name): Creates account
- def delete_account(self, account, name): Delete account, remove account from active accounts in accounts and add it to the _deleted_accounts list

Implement the Python class `AgentSession` described below.

Class description:
AgentSession class is a child class of the abstract class "Session" It allows the user to perform privileged bank transactions - deposit, withdraw, transfer, create account and delete account It also verfies input looking for constraints and value error (invalid amount)

Method signatures and docstrings:
- def deposit(self, account, amount): Checks amount and makes deposit to account
- def withdraw(self, account, amount): Checks amount and withdraws from account
- def transfer(self, account1, account2, amount): Checks amount and makes transfer
- def is_account_new(self, account): Check if the account is a new account created in this session
- def create_account(self, account, name): Creates account
- def delete_account(self, account, name): Delete account, remove account from active accounts in accounts and add it to the _deleted_accounts list

<|skeleton|>
class AgentSession:
    """AgentSession class is a child class of the abstract class "Session" It allows the user to perform privileged bank transactions - deposit, withdraw, transfer, create account and delete account It also verfies input looking for constraints and value error (invalid amount)"""

    def deposit(self, account, amount):
        """Checks amount and makes deposit to account"""
        <|body_0|>

    def withdraw(self, account, amount):
        """Checks amount and withdraws from account"""
        <|body_1|>

    def transfer(self, account1, account2, amount):
        """Checks amount and makes transfer"""
        <|body_2|>

    def is_account_new(self, account):
        """Check if the account is a new account created in this session"""
        <|body_3|>

    def create_account(self, account, name):
        """Creates account"""
        <|body_4|>

    def delete_account(self, account, name):
        """Delete account, remove account from active accounts in accounts and add it to the _deleted_accounts list"""
        <|body_5|>

<|end_skeleton|>

<|body_start_0|>
        if 0 <= amount <= 99999999:
            self.summary.record_deposit(account, amount)
        else:
            raise ValueError('Invalid transaction value for agent mode')
<|end_body_0|>

<|body_start_1|>
        if 0 <= amount <= 99999999:
            self.summary.record_withdraw(account, amount)
        else:
            raise ValueError('Invalid transaction value for agent mode')
<|end_body_1|>

<|body_start_2|>
        if 0 <= amount <= 99999999:
            self.summary.record_transfer(account1, account2, amount)
        else:
            raise ValueError('Invalid transaction value for agent mode')
<|end_body_2|>

<|body_start_3|>
        if account in self._new_accounts:
            return True
        else:
            return False
<|end_body_3|>

<|body_start_4|>
        if not (self.accounts.is_account_active(account) or self.is_account_new(account)):
            self._new_accounts.append(int(account))
            self.summary.record_create_account(account, name)
        else:
            raise ValueError('Account {} already exists'.format(account))
<|end_body_4|>

<|body_start_5|>
        if self.accounts.is_account_active(account):
            self.accounts.delete_account(account)
            self._deleted_accounts.append(account)
            self.summary.record_delete_account(account, name)
        else:
            raise ValueError('Account {} is not active, it cannot be deleted'.format(account))
<|end_body_5|>

Solution:
class AgentSession:
    """AgentSession class is a child class of the abstract class "Session" It allows the user to perform privileged bank transactions - deposit, withdraw, transfer, create account and delete account It also verfies input looking for constraints and value error (invalid amount)"""

    def deposit(self, account, amount):
        """Checks amount and makes deposit to account"""
        if 0 <= amount <= 99999999:
            self.summary.record_deposit(account, amount)
        else:
            raise ValueError('Invalid transaction value for agent mode')

    def withdraw(self, account, amount):
        """Checks amount and withdraws from account"""
        if 0 <= amount <= 99999999:
            self.summary.record_withdraw(account, amount)
        else:
            raise ValueError('Invalid transaction value for agent mode')

    def transfer(self, account1, account2, amount):
        """Checks amount and makes transfer"""
        if 0 <= amount <= 99999999:
            self.summary.record_transfer(account1, account2, amount)
        else:
            raise ValueError('Invalid transaction value for agent mode')

    def is_account_new(self, account):
        """Check if the account is a new account created in this session"""
        if account in self._new_accounts:
            return True
        else:
            return False

    def create_account(self, account, name):
        """Creates account"""
        if not (self.accounts.is_account_active(account) or self.is_account_new(account)):
            self._new_accounts.append(int(account))
            self.summary.record_create_account(account, name)
        else:
            raise ValueError('Account {} already exists'.format(account))

    def delete_account(self, account, name):
        """Delete account, remove account from active accounts in accounts and add it to the _deleted_accounts list"""
        if self.accounts.is_account_active(account):
            self.accounts.delete_account(account)
            self._deleted_accounts.append(account)
            self.summary.record_delete_account(account, name)
        else:
            raise ValueError('Account {} is not active, it cannot be deleted'.format(account))


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

Class description:
Implement the BookingListResource class.

Method signatures and docstrings:
- def get(self): Get all bookings.
- def post(self): Create a new booking

Implement the Python class `BookingListResource` described below.

Class description:
Implement the BookingListResource class.

Method signatures and docstrings:
- def get(self): Get all bookings.
- def post(self): Create a new booking

<|skeleton|>
class BookingListResource:

    def get(self):
        """Get all bookings."""
        <|body_0|>

    def post(self):
        """Create a new booking"""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        params = bookings_parser.parse_args()
        query = Booking.query
        for _, filter_op in params.items():
            query = filter_op.apply(query, Booking)
        return query.all()
<|end_body_0|>

<|body_start_1|>
        data = api.payload
        data['initial_date'] = dt.fromisoformat(data['initial_date']).date()
        data['final_date'] = dt.fromisoformat(data['final_date']).date()
        initial_date = data['initial_date']
        final_date = data['final_date']
        publication_id = data['publication_id']
        overlapped_bookings = Booking.query.filter((Booking.initial_date.between(initial_date, final_date) | Booking.final_date.between(initial_date, final_date)) & (Booking.publication_id == publication_id) & Booking.booking_status.in_([BookingStatus.ACCEPTED.value, BookingStatus.PENDING.value]) & Booking.blockchain_status.in_([BlockChainStatus.CONFIRMED.value, BlockChainStatus.PENDING.value, BlockChainStatus.UNSET.value])).all()
        if len(overlapped_bookings) >= 1:
            return ({'message': 'The intent booking has overlapping dates'}, 412)
        new_booking = Booking(**data)
        db.session.add(new_booking)
        db.session.commit()
        return (api.marshal(new_booking, booking_model), 201)
<|end_body_1|>

Solution:
class BookingListResource:
    def get(self):
        """Get all bookings."""
        params = bookings_parser.parse_args()
        query = Booking.query
        for _, filter_op in params.items():
            query = filter_op.apply(query, Booking)
        return query.all()

    def post(self):
        """Create a new booking"""
        data = api.payload
        data['initial_date'] = dt.fromisoformat(data['initial_date']).date()
        data['final_date'] = dt.fromisoformat(data['final_date']).date()
        initial_date = data['initial_date']
        final_date = data['final_date']
        publication_id = data['publication_id']
        overlapped_bookings = Booking.query.filter((Booking.initial_date.between(initial_date, final_date) | Booking.final_date.between(initial_date, final_date)) & (Booking.publication_id == publication_id) & Booking.booking_status.in_([BookingStatus.ACCEPTED.value, BookingStatus.PENDING.value]) & Booking.blockchain_status.in_([BlockChainStatus.CONFIRMED.value, BlockChainStatus.PENDING.value, BlockChainStatus.UNSET.value])).all()
        if len(overlapped_bookings) >= 1:
            return ({'message': 'The intent booking has overlapping dates'}, 412)
        new_booking = Booking(**data)
        db.session.add(new_booking)
        db.session.commit()
        return (api.marshal(new_booking, booking_model), 201)


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

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def moveZeroes1(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.

Implement the Python class `Solution` described below.

Class description:
Implement the Solution class.

Method signatures and docstrings:
- def moveZeroes1(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.

<|skeleton|>
class Solution:

    def moveZeroes1(self, nums):
        """:type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
        <|body_0|>

    def moveZeroes(self, nums):
        """:type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
        <|body_1|>

<|end_skeleton|>

<|body_start_0|>
        length = len(nums)
        zero = [0] * length
        cur = 0
        for index, num in enumerate(nums):
            if num == 0:
                cur += 1
            else:
                zero[index] = cur
        for index, num in enumerate(nums):
            if num != 0:
                num[index - zero[index]] = num
        for i in range(cur):
            nums[length - i] = 0
<|end_body_0|>

<|body_start_1|>
        length = len(nums)
        cur = 0
        for index, num in enumerate(nums):
            if num == 0:
                cur += 1
            else:
                nums[index - cur] = num
        for i in range(cur):
            nums[length - i - 1] = 0
<|end_body_1|>

Solution:
class Solution:
    def moveZeroes1(self, nums):
        """:type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
        length = len(nums)
        zero = [0] * length
        cur = 0
        for index, num in enumerate(nums):
            if num == 0:
                cur += 1
            else:
                zero[index] = cur
        for index, num in enumerate(nums):
            if num != 0:
                num[index - zero[index]] = num
        for i in range(cur):
            nums[length - i] = 0

    def moveZeroes(self, nums):
        """:type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
        length = len(nums)
        cur = 0
        for index, num in enumerate(nums):
            if num == 0:
                cur += 1
            else:
                nums[index - cur] = num
        for i in range(cur):
            nums[length - i - 1] = 0