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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/utils.py | _sanitize_value | def _sanitize_value(x):
"""
Performs cleaning steps on the data so various type comparisons can
be performed correctly.
"""
if isinstance(x, _six.string_types + _six.integer_types + (float,)):
return x
elif _HAS_SKLEARN and _sp.issparse(x):
return x.todense()
elif isinstance(... | python | def _sanitize_value(x):
"""
Performs cleaning steps on the data so various type comparisons can
be performed correctly.
"""
if isinstance(x, _six.string_types + _six.integer_types + (float,)):
return x
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return x.todense()
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/utils.py | _element_equal | def _element_equal(x, y):
"""
Performs a robust equality test between elements.
"""
if isinstance(x, _np.ndarray) or isinstance(y, _np.ndarray):
try:
return (abs(_np.asarray(x) - _np.asarray(y)) < 1e-5).all()
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... | python | def _element_equal(x, y):
"""
Performs a robust equality test between elements.
"""
if isinstance(x, _np.ndarray) or isinstance(y, _np.ndarray):
try:
return (abs(_np.asarray(x) - _np.asarray(y)) < 1e-5).all()
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/utils.py | evaluate_transformer | def evaluate_transformer(model, input_data, reference_output,
verbose=False):
"""
Evaluate a transformer specification for testing.
Parameters
----------
spec: [str | MLModel]
File from where to load the Model from (OR) a loaded
version of MLModel.
inpu... | python | def evaluate_transformer(model, input_data, reference_output,
verbose=False):
"""
Evaluate a transformer specification for testing.
Parameters
----------
spec: [str | MLModel]
File from where to load the Model from (OR) a loaded
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/utils.py | _get_input_names | def _get_input_names(spec):
"""
Returns a list of the names of the inputs to this model.
:param spec: The model protobuf specification
:return: [str] A list of input feature names
"""
retval = [feature.name for feature in spec.description.input]
return retval | python | def _get_input_names(spec):
"""
Returns a list of the names of the inputs to this model.
:param spec: The model protobuf specification
:return: [str] A list of input feature names
"""
retval = [feature.name for feature in spec.description.input]
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apple/turicreate | src/unity/python/turicreate/toolkits/graph_analytics/degree_counting.py | create | def create(graph, verbose=True):
"""
Compute the in degree, out degree and total degree of each vertex.
Parameters
----------
graph : SGraph
The graph on which to compute degree counts.
verbose : bool, optional
If True, print progress updates.
Returns
-------
out :... | python | def create(graph, verbose=True):
"""
Compute the in degree, out degree and total degree of each vertex.
Parameters
----------
graph : SGraph
The graph on which to compute degree counts.
verbose : bool, optional
If True, print progress updates.
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apple/turicreate | deps/src/boost_1_68_0/tools/litre/cplusplus.py | Example.replace_emphasis | def replace_emphasis(self, s, index = 0):
"""replace the index'th emphasized text with s"""
e = self.emphasized[index]
self.body[e[0]:e[1]] = [s]
del self.emphasized[index] | python | def replace_emphasis(self, s, index = 0):
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apple/turicreate | deps/src/boost_1_68_0/tools/litre/cplusplus.py | CPlusPlusTranslator._execute | def _execute(self, code):
"""Override of litre._execute; sets up variable context before
evaluating code
"""
self.globals['example'] = self.example
eval(code, self.globals) | python | def _execute(self, code):
"""Override of litre._execute; sets up variable context before
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"""
self.globals['example'] = self.example
eval(code, self.globals) | [
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apple/turicreate | deps/src/boost_1_68_0/tools/litre/cplusplus.py | CPlusPlusTranslator.compile | def compile(
self
, howmany = 1
, pop = -1
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, extension = '.o'
, options = ['-c']
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, source_file = None
, source_suffix = '.cpp'
# C-style comments by default; handles C++ a... | python | def compile(
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, extension = '.o'
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, built_handler = lambda built_file: None
, source_file = None
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# C-style comments by default; handles C++ a... | [
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.load | def load (self, jamfile_location):
"""Loads jamfile at the given location. After loading, project global
file and jamfile needed by the loaded one will be loaded recursively.
If the jamfile at that location is loaded already, does nothing.
Returns the project module for the Jamfile."""
... | python | def load (self, jamfile_location):
"""Loads jamfile at the given location. After loading, project global
file and jamfile needed by the loaded one will be loaded recursively.
If the jamfile at that location is loaded already, does nothing.
Returns the project module for the Jamfile."""
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.load_parent | def load_parent(self, location):
"""Loads parent of Jamfile at 'location'.
Issues an error if nothing is found."""
assert isinstance(location, basestring)
found = b2.util.path.glob_in_parents(
location, self.JAMROOT + self.JAMFILE)
if not found:
print "er... | python | def load_parent(self, location):
"""Loads parent of Jamfile at 'location'.
Issues an error if nothing is found."""
assert isinstance(location, basestring)
found = b2.util.path.glob_in_parents(
location, self.JAMROOT + self.JAMFILE)
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.find | def find(self, name, current_location):
"""Given 'name' which can be project-id or plain directory name,
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Returns nothing of project is not found."""
assert isinstance(name, basestring)
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assert isinstance(name, basestring)
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.module_name | def module_name(self, jamfile_location):
"""Returns the name of module corresponding to 'jamfile-location'.
If no module corresponds to location yet, associates default
module name with that location."""
assert isinstance(jamfile_location, basestring)
module = self.location2modul... | python | def module_name(self, jamfile_location):
"""Returns the name of module corresponding to 'jamfile-location'.
If no module corresponds to location yet, associates default
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assert isinstance(jamfile_location, basestring)
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.find_jamfile | def find_jamfile (self, dir, parent_root=0, no_errors=0):
"""Find the Jamfile at the given location. This returns the
exact names of all the Jamfiles in the given directory. The optional
parent-root argument causes this to search not the given directory
but the ones above it up to the di... | python | def find_jamfile (self, dir, parent_root=0, no_errors=0):
"""Find the Jamfile at the given location. This returns the
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.load_jamfile | def load_jamfile(self, dir, jamfile_module):
"""Load a Jamfile at the given directory. Returns nothing.
Will attempt to load the file as indicated by the JAMFILE patterns.
Effect of calling this rule twice with the same 'dir' is underfined."""
assert isinstance(dir, basestring)
a... | python | def load_jamfile(self, dir, jamfile_module):
"""Load a Jamfile at the given directory. Returns nothing.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.load_standalone | def load_standalone(self, jamfile_module, file):
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which should be able to define targets, but although it has
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"""Loads 'file' as standalone project that has no location
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.initialize | def initialize(self, module_name, location=None, basename=None, standalone_path=''):
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module-name is the name of the project module.
location is the location (directory) of the project to initialize.
If not specified, standalone project wi... | python | def initialize(self, module_name, location=None, basename=None, standalone_path=''):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.inherit_attributes | def inherit_attributes(self, project_module, parent_module):
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assert isinstance(project_module, basestring)
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attributes = self.module2attributes[project_m... | python | def inherit_attributes(self, project_module, parent_module):
"""Make 'project-module' inherit attributes of project
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.register_id | def register_id(self, id, module):
"""Associate the given id with the given project module."""
assert isinstance(id, basestring)
assert isinstance(module, basestring)
self.id2module[id] = module | python | def register_id(self, id, module):
"""Associate the given id with the given project module."""
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.push_current | def push_current(self, project):
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from .targets import ProjectTarget
assert isinstance(project, ProjectTarget)
self.saved_current_project.append(self.curren... | python | def push_current(self, project):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.attribute | def attribute(self, project, attribute):
"""Returns the value of the specified attribute in the
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assert isinstance(project, basestring)
assert isinstance(attribute, basestring)
try:
return self.module2attributes[project].get(attribute)
... | python | def attribute(self, project, attribute):
"""Returns the value of the specified attribute in the
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assert isinstance(project, basestring)
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try:
return self.module2attributes[project].get(attribute)
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.attributeDefault | def attributeDefault(self, project, attribute, default):
"""Returns the value of the specified attribute in the
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assert isinstance(project, basestring)
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assert isinstance(default, basestring) or default is None
... | python | def attributeDefault(self, project, attribute, default):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.target | def target(self, project_module):
"""Returns the project target corresponding to the 'project-module'."""
assert isinstance(project_module, basestring)
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"""Returns the project target corresponding to the 'project-module'."""
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.add_rule | def add_rule(self, name, callable_):
"""Makes rule 'name' available to all subsequently loaded Jamfiles.
Calling that rule wil relay to 'callable'."""
assert isinstance(name, basestring)
assert callable(callable_)
self.project_rules_.add_rule(name, callable_) | python | def add_rule(self, name, callable_):
"""Makes rule 'name' available to all subsequently loaded Jamfiles.
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assert isinstance(name, basestring)
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.__build_python_module_cache | def __build_python_module_cache(self):
"""Recursively walks through the b2/src subdirectories and
creates an index of base module name to package name. The
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for an O(1) module lookup.
For example, given the base module ... | python | def __build_python_module_cache(self):
"""Recursively walks through the b2/src subdirectories and
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRegistry.load_module | def load_module(self, name, extra_path=None):
"""Load a Python module that should be useable from Jamfiles.
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"""Load a Python module that should be useable from Jamfiles.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectAttributes.set | def set(self, attribute, specification, exact=False):
"""Set the named attribute from the specification given by the user.
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assert isinstance(attribute, basestring)
assert isinstance(exact, (int, bool))
if __debug__ and not exact:
... | python | def set(self, attribute, specification, exact=False):
"""Set the named attribute from the specification given by the user.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectAttributes.dump | def dump(self):
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print... | python | def dump(self):
"""Prints the project attributes."""
id = self.get("id")
if not id:
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRules.make_wrapper | def make_wrapper(self, callable_):
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assert callable(callable_)
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/project.py | ProjectRules.constant | def constant(self, name, value):
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apple/turicreate | deps/src/boost_1_68_0/libs/predef/tools/ci/build_log.py | BuildConsoleSummaryReport.print_action | def print_action(self, test_succeed, action):
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/printer.py | _get_weight_param_summary | def _get_weight_param_summary(wp):
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/printer.py | _summarize_network_layer_info | def _summarize_network_layer_info(layer):
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layer_type : str - type of layer
layer_name : str - name of the layer
layer_inputs : list[str] - a list of strings representing input blobs of the layer
layer_outputs : li... | python | def _summarize_network_layer_info(layer):
"""
Args:
layer - an MLModel NeuralNetwork Layer protobuf message
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layer_type : str - type of layer
layer_name : str - name of the layer
layer_inputs : list[str] - a list of strings representing input blobs of the layer
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/printer.py | summarize_neural_network_spec | def summarize_neural_network_spec(mlmodel_spec):
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mlmodel_spec : mlmodel spec
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mlmodel_spec : mlmodel spec
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/printer.py | print_network_spec | def print_network_spec(mlmodel_spec, interface_only=False):
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""" Print the network information summary.
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mlmodel_spec : the mlmodel spec
interface_only : Shows only the input and output of the network
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_SVC.py | _generate_base_svm_classifier_spec | def _generate_base_svm_classifier_spec(model):
"""
Takes an SVM classifier produces a starting spec using the parts. that are
shared between all SVMs.
"""
if not(_HAS_SKLEARN):
raise RuntimeError('scikit-learn not found. scikit-learn conversion API is disabled.')
check_fitted(model, la... | python | def _generate_base_svm_classifier_spec(model):
"""
Takes an SVM classifier produces a starting spec using the parts. that are
shared between all SVMs.
"""
if not(_HAS_SKLEARN):
raise RuntimeError('scikit-learn not found. scikit-learn conversion API is disabled.')
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_SVC.py | convert | def convert(model, feature_names, target):
"""Convert a Support Vector Classtion (SVC) model to the protobuf spec.
Parameters
----------
model: SVC
A trained SVC encoder model.
feature_names: [str], optional (default=None)
Name of the input columns.
target: str, optional (defau... | python | def convert(model, feature_names, target):
"""Convert a Support Vector Classtion (SVC) model to the protobuf spec.
Parameters
----------
model: SVC
A trained SVC encoder model.
feature_names: [str], optional (default=None)
Name of the input columns.
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_topology.py | NetGraph.make_input_layers | def make_input_layers(self):
"""
Extract the ordering of the input layers.
"""
self.input_layers = []
if hasattr(self.model, 'input_layers'):
input_keras_layers = self.model.input_layers[:]
self.input_layers = [None] * len(input_keras_layers)
f... | python | def make_input_layers(self):
"""
Extract the ordering of the input layers.
"""
self.input_layers = []
if hasattr(self.model, 'input_layers'):
input_keras_layers = self.model.input_layers[:]
self.input_layers = [None] * len(input_keras_layers)
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_topology.py | NetGraph.make_output_layers | def make_output_layers(self):
"""
Extract the ordering of output layers.
"""
# TODO
# use successors == 0 as the criteria for output layer
# will fail when some intermediate layers also generate output.
# However, because the possibility of having inserted layers,... | python | def make_output_layers(self):
"""
Extract the ordering of output layers.
"""
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_topology.py | NetGraph.generate_blob_names | def generate_blob_names(self):
"""
Generate blob names for each one of the edge. At this time, Keras does not
support "fork" operation (a layer with more than 1 blob output). So we just
use names of the src layer to identify a blob. We also assume all neural
networks are singly... | python | def generate_blob_names(self):
"""
Generate blob names for each one of the edge. At this time, Keras does not
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_topology.py | NetGraph._remove_layer | def _remove_layer(self, layer):
"""
remove the layer and its input/output edges
"""
successors = self.get_successors(layer)
predecessors = self.get_predecessors(layer)
# remove all edges
for succ in successors:
self._remove_edge(layer, succ)
fo... | python | def _remove_layer(self, layer):
"""
remove the layer and its input/output edges
"""
successors = self.get_successors(layer)
predecessors = self.get_predecessors(layer)
# remove all edges
for succ in successors:
self._remove_edge(layer, succ)
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_topology.py | NetGraph._insert_layer_after | def _insert_layer_after(self, layer_idx, new_layer, new_keras_layer):
"""
Insert the new_layer after layer, whose position is layer_idx. The new layer's
parameter is stored in a Keras layer called new_keras_layer
"""
# reminder: new_keras_layer is not part of the original Keras n... | python | def _insert_layer_after(self, layer_idx, new_layer, new_keras_layer):
"""
Insert the new_layer after layer, whose position is layer_idx. The new layer's
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_topology.py | NetGraph._insert_layer_between | def _insert_layer_between(self, src, snk, new_layer, new_keras_layer):
"""
Insert the new_layer before layer, whose position is layer_idx. The new layer's
parameter is stored in a Keras layer called new_keras_layer
"""
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insert_pos = self.layer_list.inde... | python | def _insert_layer_between(self, src, snk, new_layer, new_keras_layer):
"""
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_topology.py | NetGraph.defuse_activation | def defuse_activation(self):
"""
Defuse the fused activation layers in the network.
"""
idx, nb_layers = 0, len(self.layer_list)
while idx < nb_layers:
layer = self.layer_list[idx]
k_layer = self.keras_layer_map[layer]
# unwrap time-distributed... | python | def defuse_activation(self):
"""
Defuse the fused activation layers in the network.
"""
idx, nb_layers = 0, len(self.layer_list)
while idx < nb_layers:
layer = self.layer_list[idx]
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_topology.py | NetGraph._get_1d_interface_edges | def _get_1d_interface_edges(self):
"""
Get edges that represents transition from not 1D to 1D, and 1D to not 1D
A 'in_edge e(u,v)' means u operates on non-1D blobs, but v operates on 1D blobs.
An 'out_edge e(u,v)' means u operates on 1D blobs, but v operates on non-1D blobs.
"""
... | python | def _get_1d_interface_edges(self):
"""
Get edges that represents transition from not 1D to 1D, and 1D to not 1D
A 'in_edge e(u,v)' means u operates on non-1D blobs, but v operates on 1D blobs.
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_topology.py | NetGraph.insert_1d_permute_layers | def insert_1d_permute_layers(self):
"""
Insert permutation layers before a 1D start point or after 1D end point
"""
idx, nb_layers = 0, len(self.layer_list)
in_edges, out_edges = self._get_1d_interface_edges()
# Hacky Warning: (1) use a 4-D permute, which is not likely t... | python | def insert_1d_permute_layers(self):
"""
Insert permutation layers before a 1D start point or after 1D end point
"""
idx, nb_layers = 0, len(self.layer_list)
in_edges, out_edges = self._get_1d_interface_edges()
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apple/turicreate | src/unity/python/turicreate/meta/asttools/mutators/replace_mutator.py | replace_nodes | def replace_nodes(root, old, new):
'''
Replace the old node with the new one.
Old must be an indirect child of root
:param root: ast node that contains an indirect reference to old
:param old: node to replace
:param new: node to replace `old` with
'''
rep = Replacer(old, new)
... | python | def replace_nodes(root, old, new):
'''
Replace the old node with the new one.
Old must be an indirect child of root
:param root: ast node that contains an indirect reference to old
:param old: node to replace
:param new: node to replace `old` with
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rep = Replacer(old, new)
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/configure.py | log_component_configuration | def log_component_configuration(component, message):
"""Report something about component configuration that the user should better know."""
assert isinstance(component, basestring)
assert isinstance(message, basestring)
__component_logs.setdefault(component, []).append(message) | python | def log_component_configuration(component, message):
"""Report something about component configuration that the user should better know."""
assert isinstance(component, basestring)
assert isinstance(message, basestring)
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apple/turicreate | src/unity/python/turicreate/toolkits/_feature_engineering/__init__.py | create | def create(dataset, transformers):
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Create a Transformer object to transform data for feature engineering.
Parameters
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dataset : SFrame
The dataset to use for training the model.
transformers: Transformer | list[Transformer]
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"""
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apple/turicreate | src/unity/python/turicreate/toolkits/sound_classifier/_audio_feature_extractor.py | VGGishFeatureExtractor._preprocess_data | def _preprocess_data(audio_data, verbose=True):
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Preprocess each example, breaking it up into frames.
Returns two numpy arrays: preprocessed frame and their indexes
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Preprocess each example, breaking it up into frames.
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apple/turicreate | src/unity/python/turicreate/toolkits/sound_classifier/_audio_feature_extractor.py | VGGishFeatureExtractor._extract_features | def _extract_features(self, preprocessed_data, verbose=True):
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apple/turicreate | src/unity/python/turicreate/toolkits/sound_classifier/_audio_feature_extractor.py | VGGishFeatureExtractor.get_deep_features | def get_deep_features(self, audio_data, verbose):
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apple/turicreate | src/unity/python/turicreate/toolkits/sound_classifier/_audio_feature_extractor.py | VGGishFeatureExtractor.get_spec | def get_spec(self):
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Return the Core ML spec
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/__init__.py | safe_isinstance | def safe_isinstance(value, types=None, class_names=None):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/__init__.py | value_to_jam | def value_to_jam(value, methods=False):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/__init__.py | abbreviate_dashed | def abbreviate_dashed(s):
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r = []
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return '-'.join(r) | python | def abbreviate_dashed(s):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/__init__.py | abbreviate | def abbreviate(s):
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"""
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apple/turicreate | src/unity/python/turicreate/toolkits/_decision_tree.py | Node.to_dict | def to_dict(self):
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apple/turicreate | src/unity/python/turicreate/toolkits/_decision_tree.py | DecisionTree.to_json | def to_json(self, root_id = 0, output = {}):
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apple/turicreate | src/unity/python/turicreate/toolkits/_decision_tree.py | DecisionTree.get_prediction_score | def get_prediction_score(self, node_id):
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apple/turicreate | src/unity/python/turicreate/toolkits/_decision_tree.py | DecisionTree.get_prediction_path | def get_prediction_path(self, node_id, missing_id = []):
"""
Return the prediction path from this node to the parent node.
Parameters
----------
node_id : id of the node to get the prediction path.
missing_id : Additional info that contains nodes with missing features... | python | def get_prediction_path(self, node_id, missing_id = []):
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apple/turicreate | src/unity/python/turicreate/toolkits/graph_analytics/label_propagation.py | create | def create(graph, label_field,
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max_iterations=None,
_single_precision=False,
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"""
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weight_field='',
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apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | _is_not_pickle_safe_gl_model_class | def _is_not_pickle_safe_gl_model_class(obj_class):
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Check if a Turi create model is pickle safe.
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Check if a Turi create model is pickle safe.
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apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | _is_not_pickle_safe_gl_class | def _is_not_pickle_safe_gl_class(obj_class):
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Check if class is a Turi create model.
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---... | python | def _is_not_pickle_safe_gl_class(obj_class):
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apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | _get_gl_class_type | def _get_gl_class_type(obj_class):
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Internal util to get the type of the GLC class. The pickle file stores
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apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | _get_gl_object_from_persistent_id | def _get_gl_object_from_persistent_id(type_tag, gl_archive_abs_path):
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apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | GLPickler.persistent_id | def persistent_id(self, obj):
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Provide a persistent ID for "saving" GLC objects by reference. Return
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apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | GLPickler.close | def close(self):
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Close the pickle file, and the zip archive file. The single zip archive
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apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | GLUnpickler.persistent_load | def persistent_load(self, pid):
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----------
pid : The persistent ID used in pickle file to save the GLC object.
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"""
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apple/turicreate | src/unity/python/turicreate/_gl_pickle.py | GLUnpickler.close | def close(self):
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_converter.py | convert | def convert(sk_obj, input_features = None,
output_feature_names = None):
"""
Convert scikit-learn pipeline, classifier, or regressor to Core ML format.
Parameters
----------
sk_obj: model | [model] of scikit-learn format.
Scikit learn model(s) to convert to a Core ML format.
... | python | def convert(sk_obj, input_features = None,
output_feature_names = None):
"""
Convert scikit-learn pipeline, classifier, or regressor to Core ML format.
Parameters
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sk_obj: model | [model] of scikit-learn format.
Scikit learn model(s) to convert to a Core ML format.
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/reflection.py | ParseMessage | def ParseMessage(descriptor, byte_str):
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Args:
descriptor: Protobuf Descriptor object
byte_str: Serialized protocol buffer byte string
Returns:
Newly created protobuf Message object.
"""
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"""Generate a new Message instance from this Descriptor and a byte string.
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descriptor: Protobuf Descriptor object
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class Parent(message.Message):
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apple/turicreate | src/unity/python/turicreate/toolkits/image_analysis/image_analysis.py | load_images | def load_images(url, format='auto', with_path=True, recursive=True, ignore_failure=True, random_order=False):
"""
Loads images from a directory. JPEG and PNG images are supported.
Parameters
----------
url : str
The string of the path where all the images are stored.
format : {'PNG' | ... | python | def load_images(url, format='auto', with_path=True, recursive=True, ignore_failure=True, random_order=False):
"""
Loads images from a directory. JPEG and PNG images are supported.
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apple/turicreate | src/unity/python/turicreate/toolkits/image_analysis/image_analysis.py | _decode | def _decode(image_data):
"""
Internal helper function for decoding a single Image or an SArray of Images
"""
from ...data_structures.sarray import SArray as _SArray
from ... import extensions as _extensions
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"""
Internal helper function for decoding a single Image or an SArray of Images
"""
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apple/turicreate | src/unity/python/turicreate/toolkits/image_analysis/image_analysis.py | resize | def resize(image, width, height, channels=None, decode=False,
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"""
Resizes the image or SArray of Images to a specific width, height, and
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Parameters
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image : turicreate.Image | SArray
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"""
Resizes the image or SArray of Images to a specific width, height, and
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _convert_1bit_array_to_byte_array | def _convert_1bit_array_to_byte_array(arr):
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Convert bit array to byte array.
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# Padding if necessary
while len(arr) < 8 or len(... | python | def _convert_1bit_array_to_byte_array(arr):
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Convert bit array to byte array.
:param arr: list
Bits as a list where each element is an integer of 0 or 1
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numpy.array
1D numpy array of type uint8
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _decompose_bytes_to_bit_arr | def _decompose_bytes_to_bit_arr(arr):
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Unpack bytes to bits
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bit_arr: list
Decomposed bit stream as a list of 0/1s of length (len(arr) * 8)
"""
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... | python | def _decompose_bytes_to_bit_arr(arr):
"""
Unpack bytes to bits
:param arr: list
Byte Stream, as a list of uint8 values
Returns
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bit_arr: list
Decomposed bit stream as a list of 0/1s of length (len(arr) * 8)
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _get_linear_lookup_table_and_weight | def _get_linear_lookup_table_and_weight(nbits, wp):
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Number of bits to represent a quantized weight value
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Weight blob to be quantized
Returns
-------
lookup_table: numpy.array
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"""
Generate a linear lookup table.
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Number of bits to represent a quantized weight value
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Weight blob to be quantized
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _get_kmeans_lookup_table_and_weight | def _get_kmeans_lookup_table_and_weight(nbits, w, init='k-means++', tol=1e-2, n_init=1, rand_seed=0):
"""
Generate K-Means lookup table given a weight parameter field
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:param w:
Weight as numpy array
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-------
lut: numpy.a... | python | def _get_kmeans_lookup_table_and_weight(nbits, w, init='k-means++', tol=1e-2, n_init=1, rand_seed=0):
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Generate K-Means lookup table given a weight parameter field
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _quantize_channelwise_linear | def _quantize_channelwise_linear(weight, nbits, axis=0):
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Linearly quantize weight blob.
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Weight to be quantized.
:param nbits: int
Number of bits per weight element
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Linearly quantize weight blob.
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Weight to be quantized.
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Number of bits per weight element
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _quantize_wp | def _quantize_wp(wp, nbits, qm, axis=0, **kwargs):
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Quantize the weight blob
:param wp: numpy.array
Weight parameters
:param nbits: int
Number of bits
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Quantization mode
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"""
Quantize the weight blob
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | _quantize_wp_field | def _quantize_wp_field(wp, nbits, qm, shape, axis=0, **kwargs):
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Quantize WeightParam field in Neural Network Protobuf
:param wp: MLModel.NeuralNetwork.WeightParam
WeightParam field
:param nbits: int
Number of bits to be quantized
:param qm: str
Quantization mode
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"""
Quantize WeightParam field in Neural Network Protobuf
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | compare_models | def compare_models(full_precision_model, quantized_model,
sample_data):
"""
Utility function to compare the performance of a full precision vs quantized model
:param full_precision_model: MLModel
The full precision model with float32 weights
:param quantized_model... | python | def compare_models(full_precision_model, quantized_model,
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"""
Utility function to compare the performance of a full precision vs quantized model
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/quantization_utils.py | quantize_weights | def quantize_weights(full_precision_model,
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Utility function to convert a full precision (float) MLModel to a
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apple/turicreate | src/unity/python/turicreate/toolkits/recommender/item_similarity_recommender.py | create | def create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
nearest_items=None,
similarity_type='jaccard',
threshold=0.001,
only_top_k=64,
verbose=True,
target_memory_usage = 8*102... | python | def create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
nearest_items=None,
similarity_type='jaccard',
threshold=0.001,
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | _get_elementwise_name_from_keras_layer | def _get_elementwise_name_from_keras_layer(keras_layer):
"""
Get the keras layer name from the activation name.
"""
if isinstance(keras_layer, _keras.layers.Add):
return 'ADD'
elif isinstance(keras_layer, _keras.layers.Multiply):
return 'MULTIPLY'
elif isinstance(keras_layer, _ke... | python | def _get_elementwise_name_from_keras_layer(keras_layer):
"""
Get the keras layer name from the activation name.
"""
if isinstance(keras_layer, _keras.layers.Add):
return 'ADD'
elif isinstance(keras_layer, _keras.layers.Multiply):
return 'MULTIPLY'
elif isinstance(keras_layer, _ke... | [
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_dense | def convert_dense(builder, layer, input_names, output_names, keras_layer):
"""
Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and o... | python | def convert_dense(builder, layer, input_names, output_names, keras_layer):
"""
Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_embedding | def convert_embedding(builder, layer, input_names, output_names, keras_layer):
"""Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get input and ou... | python | def convert_embedding(builder, layer, input_names, output_names, keras_layer):
"""Convert a dense layer from keras to coreml.
Parameters
keras_layer: layer
----------
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
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A keras layer object.
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_activation | def convert_activation(builder, layer, input_names, output_names, keras_layer):
"""
Convert an activation layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get ... | python | def convert_activation(builder, layer, input_names, output_names, keras_layer):
"""
Convert an activation layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
# Get ... | [
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Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_advanced_relu | def convert_advanced_relu(builder, layer, input_names, output_names, keras_layer):
"""
Convert an ReLU layer with maximum value from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
... | python | def convert_advanced_relu(builder, layer, input_names, output_names, keras_layer):
"""
Convert an ReLU layer with maximum value from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
... | [
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Parameters
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keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/keras/_layers2.py | convert_convolution | def convert_convolution(builder, layer, input_names, output_names, keras_layer):
"""
Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
_check... | python | def convert_convolution(builder, layer, input_names, output_names, keras_layer):
"""
Convert convolution layer from keras to coreml.
Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object.
"""
_check... | [
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Parameters
----------
keras_layer: layer
A keras layer object.
builder: NeuralNetworkBuilder
A neural network builder object. | [
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