Model: Copilot; Similarity Score: 1.00

def load_tf_weights_in_bert(model, config, tf_checkpoint_path):

   """Load tf checkpoints in a pytorch model."""

   try:

       import re

       import numpy as np

       import tensorflow as tf

   except ImportError:

       logger.error(

           "Loading a TensorFlow model in PyTorch, requires TensorFlow to be installed. Please see "

           "https://www.tensorflow.org/install/ for installation instructions."

       )

       raise

   tf_path = os.path.abspath(tf_checkpoint_path)

   logger.info("Converting TensorFlow checkpoint from {}".format(tf_path))

   # Load weights from TF model

   init_vars = tf.train.list_variables(tf_path)

   names = []

   arrays = []

   for name, shape in init_vars:

       logger.info("Loading TF weight {} with shape {}".format(name, shape))

       array = tf.train.load_variable(tf_path, name)

       names.append(name)

       arrays.append(array)

   for name, array in zip(names, arrays):

       name = name.split("/")

       # adam_v and adam_m are variables used in AdamWeightDecayOptimizer to calculated m and v

       # which are not required for using pretrained model

       if any(

           n in ["adam_v", "adam_m", "AdamWeightDecayOptimizer", "AdamWeightDecayOptimizer_1", "global_step"]

           for n in name

       ):

           logger.info("Skipping {}".format("/".join(name)))

           continue

       pointer = model

       for m_name in name:

           if re.fullmatch(r"[A-Za-z]+_\d+", m_name):

               scope_names = re.split(r"_(\d+)", m_name)

           else:

               scope_names = [m_name]

           if scope_names[0] == "kernel" or scope_names[0] == "gamma":

               pointer = getattr(pointer, "weight")

           elif scope_names[0] == "output_bias" or scope_names[0] == "beta":

               pointer = getattr(pointer, "bias")

           elif scope_names[0] == "output_weights":

               pointer = getattr(pointer, "weight")

           elif scope_names[0] == "squad":

               pointer = getattr(pointer, "classifier")

           else:

               try:

                   pointer = getattr(pointer, scope_names[0])

               except AttributeError:

                   logger.info("Skipping {}".format("/".join(name)))

                   continue

           if len(scope_names) >= 2:

               num = int(scope_names[1])

               pointer = pointer[num]

       if m_name[-11

# coding=utf-8

# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.

# Copyright (c) 2018, NVIDIA CORPORATION.  All rights reserved.

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

#     http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

def load_tf_weights_in_bert(model, config, tf_checkpoint_path):

   """Load tf checkpoints in a pytorch model."""

   try:

       import re

       import numpy as np

       import tensorflow as tf

   except ImportError:

       logger.error(

           "Loading a TensorFlow model in PyTorch, requires TensorFlow to be installed. Please see "

           "https://www.tensorflow.org/install/ for installation instructions."

       )

       raise

   tf_path = os.path.abspath(tf_checkpoint_path)

   logger.info(f"Converting TensorFlow checkpoint from {tf_path}")

   # Load weights from TF model

   init_vars = tf.train.list_variables(tf_path)

   names = []

   arrays = []

   for name, shape in init_vars:

       logger.info(f"Loading TF weight {name} with shape {shape}")

       array = tf.train.load_variable(tf_path, name)

       names.append(name)

       arrays.append(array)

   for name, array in zip(names, arrays):

       name = name.split("/")

       # adam_v and adam_m are variables used in AdamWeightDecayOptimizer to calculated m and v

       # which are not required for using pretrained model

       if any(

           n in ["adam_v", "adam_m", "AdamWeightDecayOptimizer", "AdamWeightDecayOptimizer_1", "global_step"]

           for n in name

       ):

           logger.info(f"Skipping {'/'.join(name)}")

           continue

       pointer = model

       for m_name in name:

           if re.fullmatch(r"[A-Za-z]+_\d+", m_name):

               scope_names = re.split(r"_(\d+)", m_name)

           else:

               scope_names = [m_name]

           if scope_names[0] == "kernel" or scope_names[0] == "gamma":

               pointer = getattr(pointer, "weight")

           elif scope_names[0] == "output_bias" or scope_names[0] == "beta":

               pointer = getattr(pointer, "bias")

           elif scope_names[0] == "output_weights":

               pointer = getattr(pointer, "weight")

           elif scope_names[0] == "squad":

               pointer = getattr(pointer, "classifier")

           else:

               try:

                   pointer = getattr(pointer, scope_names[0])

               except AttributeError:

                   logger.info(f"Skipping {'/'.join(name)}")

                   continue

           if len(scope_names) >= 2:

               num = int(scope_names[1])

               pointer = pointer[num]

       if m_name[-11:] == "_embeddings":

Model: Copilot; Similarity Score: 0.94

// fast inverse square root

float Q_rsqrt( float number )

{

   long i;

   float x2, y;

   const float threehalfs = 1.5F;

   x2 = number * 0.5F;

   y = number;

   i = * ( long * ) &y; // evil floating point bit level hacking

   i = 0x5f3759df - ( i >> 1 );

/*

===========================================================================

Copyright (C) 1999-2005 Id Software, Inc.

This file is part of Quake III Arena source code.

Quake III Arena source code is free software; you can redistribute it

and/or modify it under the terms of the GNU General Public License as

published by the Free Software Foundation; either version 2 of the License,

or (at your option) any later version.

Quake III Arena source code is distributed in the hope that it will be

useful, but WITHOUT ANY WARRANTY; without even the implied warranty of

MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the

GNU General Public License for more details.

You should have received a copy of the GNU General Public License

along with Foobar; if not, write to the Free Software

Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA

===========================================================================

*/

float Q_rsqrt( float number )

{

   long i;

   float x2, y;

   const float threehalfs = 1.5F;

   x2 = number * 0.5F;

   y  = number;

   i  = * ( long * ) &y;                       // evil floating point bit level hacking

   i  = 0x5f3759df - ( i >> 1 );             

Model: CodeGen-2BMulti; Similarity Score: 0.90

public class BgpOpenMsgVer4 implements BgpOpenMsg {

   BgpHeader bgpMsgHeader;

   int version;

   int asNumber;

   int holdTime;

   int bgpId;

   List<BgpOpenPacket> bgpOpenPacketList;

   /**

    * Returns object of this class with specified values.

    *

    * @param bgpMsgHeader BGP message header

    * @param version BGP version

    * @param asNumber AS number

    * @param holdTime hold time

    * @param bgpId BGP ID

    * @param bgpOpenPacketList list of BGP open packets

    */

   public BgpOpenMsgVer4(BgpHeader bgpMsgHeader, int version, int asNumber,

                         int holdTime, int bgpId,

                         List<BgpOpenPacket> bgpOpenPacketList) {

       this.bgpMsgHeader = bgpMsgHeader;

       this.version = version;

       this.asNumber = asNumber;

       this.holdTime = holdTime;

       this.bgp

/*

* Copyright 2015-present Open Networking Foundation

*

* Licensed under the Apache License, Version 2.0 (the "License");

* you may not use this file except in compliance with the License.

* You may obtain a copy of the License at

*

*     http://www.apache.org/licenses/LICENSE-2.0

*

* Unless required by applicable law or agreed to in writing, software

* distributed under the License is distributed on an "AS IS" BASIS,

* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

* See the License for the specific language governing permissions and

* limitations under the License.

*/

   public BgpOpenMsgVer4() {

       this.bgpMsgHeader = null;

       this.version = 0;

       this.holdTime = 0;

       this.asNumber = 0;

       this.bgpId = 0;

       this.capabilityTlv = null;

   }

   /**

    * Constructor to initialize all variables of BGP Open message.

    *

    * @param bgpMsgHeader BGP Header in open message

    * @param version BGP version in open message

    * @param holdTime hold time in open message

    * @param asNumber AS number in open message

    * @param bgpId BGP identifier in open message

    * @param capabilityTlv capabilities in open message

    */

   public BgpOpenMsgVer4(BgpHeader bgpMsgHeader, byte version, long asNumber, short holdTime,

            int bgpId, LinkedList<BgpValueType> capabilityTlv) {

       this.bgpMsgHeader = bgpMsgHeader;

       this.version = version;

       this.asNumber = asNumber;

       this.holdTime = holdTime;

       this.bgpId = bgpId;

       this.capabilityTlv = capabilityTlv;

   }

Model: CodeT5-large-ntp-py; Similarity Score: 0.92

def VmFailedStartingSecondaryEvent(vim, *args, **kwargs):

   '''This event records that the secondary VM failed to start.'''

   obj = vim.client.factory.create('ns0:VmFailedStartingSecondaryEvent')

   # do some validation checking...

   if (len(args) + len(kwargs)) < 5:

       raise IndexError('Expected at least 6 arguments got: %d' % len(args))

   required = [ 'template', 'chainId', 'createdTime', 'key', 'userName' ]

   optional = [ 'changeTag', 'computeResource', 'datacenter', 'ds', 'dvs',

       'fullFormattedMessage', 'host', 'net', 'vm', 'dynamicProperty', 'dynamicType' ]

   for name, arg in zip(required+optional, args):

       setattr(obj, name, arg)

   for name, value in kwargs.items():

       if name in required + optional:

           setattr(obj, name, value)

       else:

           raise ValueError('Invalid argument: %s.  Expected one of %s' % (name, ', '.join(required + optional)))

   return obj

def VmFailedStartingSecondaryEvent(vim, *args, **kwargs):

   '''This event records vmotion failure when starting a secondary VM.'''

   obj = vim.client.factory.create('ns0:VmFailedStartingSecondaryEvent')

   # do some validation checking...

   if (len(args) + len(kwargs)) < 5:

       raise IndexError('Expected at least 6 arguments got: %d' % len(args))

   required = [ 'template', 'chainId', 'createdTime', 'key', 'userName' ]

   optional = [ 'reason', 'changeTag', 'computeResource', 'datacenter', 'ds', 'dvs',

       'fullFormattedMessage', 'host', 'net', 'vm', 'dynamicProperty', 'dynamicType' ]

   for name, arg in zip(required+optional, args):

       setattr(obj, name, arg)

   for name, value in kwargs.items():

       if name in required + optional:

           setattr(obj, name, value)

       else:

           raise InvalidArgumentError("Invalid argument: %s.  Expected one of %s" % (name, ", ".join(required + optional)))

   return obj

Model: CodeParrot; Similarity Score: 0.90

#!/usr/bin/env python

#

class ReferenceParametersType_(SamlBase):

def reference_parameters_type__from_string(xml_string):

   return saml2.create_class_from_xml_string(ReferenceParametersType_, xml_string)

class BasisType_(SamlBase):

   """The BasisType attribute is an optional element

   See: http://www.secteurs.org/2011/letter-concepts/xsd-reference-parameter_type

   """

   c_tag = 'basisType'

   c_namespace = NAMESPACE

   c_children = SamlBase.c_children.copy()

   c_attributes = SamlBase.c_attributes.copy()

   c_child_order = SamlBase.c_child_order[:]

   c_cardinality = SamlBase.c_cardinality.copy()

def basis_type__from_string(xml_string):

   return saml2.create_class_from_xml_string(BasisType_, xml_string)

class CryptographicParametersType_(SamlBase):

#!/usr/bin/env python

#

class ReferenceParametersType_(SamlBase):

   ...

def reference_parameters_type__from_string(xml_string):

   return saml2.create_class_from_xml_string(ReferenceParametersType_, xml_string)

class MetadataType_(SamlBase):

   """The http://www.w3.org/2005/08/addressing:MetadataType element """

   c_tag = 'MetadataType'

   c_namespace = NAMESPACE

   c_children = SamlBase.c_children.copy()

   c_attributes = SamlBase.c_attributes.copy()

   c_child_order = SamlBase.c_child_order[:]

   c_cardinality = SamlBase.c_cardinality.copy()

def metadata_type__from_string(xml_string):

   return saml2.create_class_from_xml_string(MetadataType_, xml_string)

class RelationshipTypeOpenEnum_(SamlBase):