How to use new_scope method in localstack

Best Python code snippet using localstack_python

models.py

Source:models.py

1import tensorflow as tf2slim = tf.contrib.slim3from tensorflow.contrib.slim.nets import inception4import inception_resnet_v25import inception_v46import densenet7import numpy as np8class densenet_model:9    def __init__(self, model_path, model='denset169', new_scope=None):10        self.image_size = 29911        self.num_labels = 100012        self.num_channels = 313        self.new_scope = new_scope14        15        assert model in ['densenet169']16        if model == 'densenet169':17            self.arg_scope = densenet.densenet_arg_scope18            self.inception_model = densenet.densenet16919            self.scope='densenet169'20        x_input = tf.placeholder(tf.float32, shape=(None,self.image_size,self.image_size,self.num_channels))21        if self.new_scope is None:22           self.new_scope = self.scope 23        self.model_path = model_path24        self.mean = np.array([123.68, 116.78, 103.94]).reshape(1,1,1,3)25        self.scale_factor = 0.01726        self.first = True27    def initialize(self, sess):28        self.saver.restore(sess, self.model_path)29    def predict(self, img):30        # from inception preprocess to densenet preprocess:31        img = ((img+1) *127.5 - self.mean) * self.scale_factor32        reuse = not self.first33        with slim.arg_scope(self.arg_scope()):34          _, end_points = self.inception_model(35              img, num_classes=self.num_labels, is_training=False, reuse=reuse, scope=self.new_scope)36        if self.first:37          if self.scope != self.new_scope:38            var_dict = {var.op.name.replace(self.new_scope, self.scope, 1): var 39                for var in slim.get_model_variables(scope=self.new_scope)}40          else:41            var_dict = slim.get_model_variables(scope=self.scope)42          self.saver = tf.train.Saver(var_dict)43        self.first = False44        return end_points['Logits']45class inception_model:46    def __init__(self, model_path, model='inception_v3', new_scope=None):47        self.image_size = 29948        self.num_labels = 100149        self.num_channels = 350        self.new_scope = new_scope51        52        assert model in ['inception_v3', 'inception_v4', 'inception_resnet_v2', 'densenet']53        if model == 'inception_v3':54            self.arg_scope = inception.inception_v3_arg_scope55            self.inception_model = inception.inception_v356            self.scope='InceptionV3'57        elif model == 'inception_v4':58            self.arg_scope = inception_v4.inception_v4_arg_scope59            self.inception_model = inception_v4.inception_v460            self.scope='InceptionV4'61        elif model == 'inception_resnet_v2':62            self.arg_scope = inception_resnet_v2.inception_resnet_v2_arg_scope63            self.inception_model = inception_resnet_v2.inception_resnet_v264            self.scope='InceptionResnetV2'65        elif model == 'densenet':66            self.arg_scope = densenet.densenet_arg_scope67            self.inception_model = densenet.densenet16968            self.scope='densenet169'69        x_input = tf.placeholder(tf.float32, shape=(None,self.image_size,self.image_size,self.num_channels))70        if self.new_scope is None:71           self.new_scope = self.scope 72        self.first = True73        self.model_path = model_path74    def initialize(self, sess):75        self.saver.restore(sess, self.model_path)76    def predict(self, img):77        reuse = not self.first78        with slim.arg_scope(self.arg_scope()):79          _, end_points = self.inception_model(80              img, num_classes=self.num_labels, is_training=False, reuse=reuse, scope=self.new_scope)81        if self.first:82          if self.scope != self.new_scope:83            var_dict = {var.op.name.replace(self.new_scope, self.scope, 1): var 84                for var in slim.get_model_variables(scope=self.new_scope)}85          else:86            var_dict = slim.get_model_variables(scope=self.scope)87          self.saver = tf.train.Saver(var_dict)88        self.first = False...

scope.py

Source:scope.py

1from typing import List, Any, Dict, Optional, Union, Set2from crytic_compile.utils.naming import Filename3from slither.core.declarations import Contract, Import, Pragma4from slither.core.declarations.custom_error_top_level import CustomErrorTopLevel5from slither.core.declarations.enum_top_level import EnumTopLevel6from slither.core.declarations.function_top_level import FunctionTopLevel7from slither.core.declarations.structure_top_level import StructureTopLevel8from slither.slithir.variables import Constant9def _dict_contain(d1: Dict, d2: Dict) -> bool:10    """11    Return true if d1 is included in d212    """13    d2_keys = d2.keys()14    return all(item in d2_keys for item in d1.keys())15# pylint: disable=too-many-instance-attributes16class FileScope:17    def __init__(self, filename: Filename):18        self.filename = filename19        self.accessible_scopes: List[FileScope] = []20        self.contracts: Dict[str, Contract] = {}21        # Custom error are a list instead of a dict22        # Because we parse the function signature later on23        # So we simplify the logic and have the scope fields all populated24        self.custom_errors: Set[CustomErrorTopLevel] = set()25        self.enums: Dict[str, EnumTopLevel] = {}26        # Functions is a list instead of a dict27        # Because we parse the function signature later on28        # So we simplify the logic and have the scope fields all populated29        self.functions: Set[FunctionTopLevel] = set()30        self.imports: Set[Import] = set()31        self.pragmas: Set[Pragma] = set()32        self.structures: Dict[str, StructureTopLevel] = {}33    def add_accesible_scopes(self) -> bool:34        """35        Add information from accessible scopes. Return true if new information was obtained36        :return:37        :rtype:38        """39        learn_something = False40        for new_scope in self.accessible_scopes:41            if not _dict_contain(new_scope.contracts, self.contracts):42                self.contracts.update(new_scope.contracts)43                learn_something = True44            if not new_scope.custom_errors.issubset(self.custom_errors):45                self.custom_errors |= new_scope.custom_errors46                learn_something = True47            if not _dict_contain(new_scope.enums, self.enums):48                self.enums.update(new_scope.enums)49                learn_something = True50            if not new_scope.functions.issubset(self.functions):51                self.functions |= new_scope.functions52                learn_something = True53            if not new_scope.imports.issubset(self.imports):54                self.imports |= new_scope.imports55                learn_something = True56            if not new_scope.pragmas.issubset(self.pragmas):57                self.pragmas |= new_scope.pragmas58                learn_something = True59            if not _dict_contain(new_scope.structures, self.structures):60                self.structures.update(new_scope.structures)61                learn_something = True62        return learn_something63    def get_contract_from_name(self, name: Union[str, Constant]) -> Optional[Contract]:64        if isinstance(name, Constant):65            return self.contracts.get(name.name, None)66        return self.contracts.get(name, None)67    # region Built in definitions68    ###################################################################################69    ###################################################################################70    def __eq__(self, other: Any) -> bool:71        if isinstance(other, str):72            return other == self.filename73        return NotImplemented74    def __neq__(self, other: Any) -> bool:75        if isinstance(other, str):76            return other != self.filename77        return NotImplemented78    def __str__(self) -> str:79        return str(self.filename.relative)80    def __hash__(self) -> int:81        return hash(self.filename.relative)...

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