INSTRUCTION stringlengths 1 46.3k | RESPONSE stringlengths 75 80.2k |
|---|---|
Evaluate the XPath Location Path in the given context. | def xpathEval(self, str):
"""Evaluate the XPath Location Path in the given context. """
ret = libxml2mod.xmlXPathEval(str, self._o)
if ret is None:raise xpathError('xmlXPathEval() failed')
return xpathObjectRet(ret) |
Evaluate the XPath expression in the given context. | def xpathEvalExpression(self, str):
"""Evaluate the XPath expression in the given context. """
ret = libxml2mod.xmlXPathEvalExpression(str, self._o)
if ret is None:raise xpathError('xmlXPathEvalExpression() failed')
return xpathObjectRet(ret) |
Create a new xmlXPathParserContext | def xpathNewParserContext(self, str):
"""Create a new xmlXPathParserContext """
ret = libxml2mod.xmlXPathNewParserContext(str, self._o)
if ret is None:raise xpathError('xmlXPathNewParserContext() failed')
__tmp = xpathParserContext(_obj=ret)
return __tmp |
Search in the namespace declaration array of the context
for the given namespace name associated to the given prefix | def xpathNsLookup(self, prefix):
"""Search in the namespace declaration array of the context
for the given namespace name associated to the given prefix """
ret = libxml2mod.xmlXPathNsLookup(self._o, prefix)
return ret |
Register a new namespace. If @ns_uri is None it unregisters
the namespace | def xpathRegisterNs(self, prefix, ns_uri):
"""Register a new namespace. If @ns_uri is None it unregisters
the namespace """
ret = libxml2mod.xmlXPathRegisterNs(self._o, prefix, ns_uri)
return ret |
Search in the Variable array of the context for the given
variable value. | def xpathVariableLookup(self, name):
"""Search in the Variable array of the context for the given
variable value. """
ret = libxml2mod.xmlXPathVariableLookup(self._o, name)
if ret is None:raise xpathError('xmlXPathVariableLookup() failed')
return xpathObjectRet(ret) |
Search in the Variable array of the context for the given
variable value. | def xpathVariableLookupNS(self, name, ns_uri):
"""Search in the Variable array of the context for the given
variable value. """
ret = libxml2mod.xmlXPathVariableLookupNS(self._o, name, ns_uri)
if ret is None:raise xpathError('xmlXPathVariableLookupNS() failed')
return xpathObj... |
Evaluate the XPath Location Path in the given context. | def xpointerEval(self, str):
"""Evaluate the XPath Location Path in the given context. """
ret = libxml2mod.xmlXPtrEval(str, self._o)
if ret is None:raise treeError('xmlXPtrEval() failed')
return xpathObjectRet(ret) |
Get the xpathContext from an xpathParserContext | def context(self):
"""Get the xpathContext from an xpathParserContext """
ret = libxml2mod.xmlXPathParserGetContext(self._o)
if ret is None:raise xpathError('xmlXPathParserGetContext() failed')
__tmp = xpathContext(_obj=ret)
return __tmp |
Implement the compare operation on XPath objects: @arg1 <
@arg2 (1, 1, ... @arg1 <= @arg2 (1, 0, ... @arg1 >
@arg2 (0, 1, ... @arg1 >= @arg2 (0, 0, ... When
neither object to be compared is a node-set and the
operator is <=, <, >=, >, then the objects are compared by
... | def xpathCompareValues(self, inf, strict):
"""Implement the compare operation on XPath objects: @arg1 <
@arg2 (1, 1, ... @arg1 <= @arg2 (1, 0, ... @arg1 >
@arg2 (0, 1, ... @arg1 >= @arg2 (0, 0, ... When
neither object to be compared is a node-set and the
operat... |
Traversal function for the "ancestor" direction the
ancestor axis contains the ancestors of the context node;
the ancestors of the context node consist of the parent of
context node and the parent's parent and so on; the nodes
are ordered in reverse document order; thus the paren... | def xpathNextAncestor(self, cur):
"""Traversal function for the "ancestor" direction the
ancestor axis contains the ancestors of the context node;
the ancestors of the context node consist of the parent of
context node and the parent's parent and so on; the nodes
are orde... |
Traversal function for the "ancestor-or-self" direction he
ancestor-or-self axis contains the context node and
ancestors of the context node in reverse document order;
thus the context node is the first node on the axis, and
the context node's parent the second; parent here is
... | def xpathNextAncestorOrSelf(self, cur):
"""Traversal function for the "ancestor-or-self" direction he
ancestor-or-self axis contains the context node and
ancestors of the context node in reverse document order;
thus the context node is the first node on the axis, and
the ... |
Traversal function for the "attribute" direction TODO:
support DTD inherited default attributes | def xpathNextAttribute(self, cur):
"""Traversal function for the "attribute" direction TODO:
support DTD inherited default attributes """
if cur is None: cur__o = None
else: cur__o = cur._o
ret = libxml2mod.xmlXPathNextAttribute(self._o, cur__o)
if ret is None:raise xp... |
Traversal function for the "child" direction The child axis
contains the children of the context node in document order. | def xpathNextChild(self, cur):
"""Traversal function for the "child" direction The child axis
contains the children of the context node in document order. """
if cur is None: cur__o = None
else: cur__o = cur._o
ret = libxml2mod.xmlXPathNextChild(self._o, cur__o)
if ret ... |
Traversal function for the "descendant" direction the
descendant axis contains the descendants of the context
node in document order; a descendant is a child or a child
of a child and so on. | def xpathNextDescendant(self, cur):
"""Traversal function for the "descendant" direction the
descendant axis contains the descendants of the context
node in document order; a descendant is a child or a child
of a child and so on. """
if cur is None: cur__o = None
e... |
Traversal function for the "descendant-or-self" direction
the descendant-or-self axis contains the context node and
the descendants of the context node in document order; thus
the context node is the first node on the axis, and the
first child of the context node is the second no... | def xpathNextDescendantOrSelf(self, cur):
"""Traversal function for the "descendant-or-self" direction
the descendant-or-self axis contains the context node and
the descendants of the context node in document order; thus
the context node is the first node on the axis, and the
... |
Traversal function for the "following" direction The
following axis contains all nodes in the same document as
the context node that are after the context node in
document order, excluding any descendants and excluding
attribute nodes and namespace nodes; the nodes are ordered
... | def xpathNextFollowing(self, cur):
"""Traversal function for the "following" direction The
following axis contains all nodes in the same document as
the context node that are after the context node in
document order, excluding any descendants and excluding
attribute nodes... |
Traversal function for the "following-sibling" direction
The following-sibling axis contains the following siblings
of the context node in document order. | def xpathNextFollowingSibling(self, cur):
"""Traversal function for the "following-sibling" direction
The following-sibling axis contains the following siblings
of the context node in document order. """
if cur is None: cur__o = None
else: cur__o = cur._o
ret = libxm... |
Traversal function for the "namespace" direction the
namespace axis contains the namespace nodes of the context
node; the order of nodes on this axis is
implementation-defined; the axis will be empty unless the
context node is an element We keep the XML namespace node
... | def xpathNextNamespace(self, cur):
"""Traversal function for the "namespace" direction the
namespace axis contains the namespace nodes of the context
node; the order of nodes on this axis is
implementation-defined; the axis will be empty unless the
context node is an elem... |
Traversal function for the "parent" direction The parent
axis contains the parent of the context node, if there is
one. | def xpathNextParent(self, cur):
"""Traversal function for the "parent" direction The parent
axis contains the parent of the context node, if there is
one. """
if cur is None: cur__o = None
else: cur__o = cur._o
ret = libxml2mod.xmlXPathNextParent(self._o, cur__o)
... |
Traversal function for the "preceding" direction the
preceding axis contains all nodes in the same document as
the context node that are before the context node in
document order, excluding any ancestors and excluding
attribute nodes and namespace nodes; the nodes are ordered
... | def xpathNextPreceding(self, cur):
"""Traversal function for the "preceding" direction the
preceding axis contains all nodes in the same document as
the context node that are before the context node in
document order, excluding any ancestors and excluding
attribute nodes ... |
Traversal function for the "preceding-sibling" direction
The preceding-sibling axis contains the preceding siblings
of the context node in reverse document order; the first
preceding sibling is first on the axis; the sibling
preceding that node is the second on the axis and so o... | def xpathNextPrecedingSibling(self, cur):
"""Traversal function for the "preceding-sibling" direction
The preceding-sibling axis contains the preceding siblings
of the context node in reverse document order; the first
preceding sibling is first on the axis; the sibling
p... |
Traversal function for the "self" direction The self axis
contains just the context node itself | def xpathNextSelf(self, cur):
"""Traversal function for the "self" direction The self axis
contains just the context node itself """
if cur is None: cur__o = None
else: cur__o = cur._o
ret = libxml2mod.xmlXPathNextSelf(self._o, cur__o)
if ret is None:raise xpathError('... |
Formats an error message. | def xpatherror(self, file, line, no):
"""Formats an error message. """
libxml2mod.xmlXPatherror(self._o, file, line, no) |
Returns a structured description of the model, including (where relevant)
the schema of the training data, description of the training data,
training statistics, and model hyperparameters.
Returns
-------
sections : list (of list of tuples)
A list of summary sections... | def _get_summary_struct(self):
"""
Returns a structured description of the model, including (where relevant)
the schema of the training data, description of the training data,
training statistics, and model hyperparameters.
Returns
-------
sections : list (of lis... |
Return a classification, for each example in the ``dataset``, using the
trained logistic regression model. The output SFrame contains predictions
as both class labels (0 or 1) as well as probabilities that the predicted
value is the associated label.
Parameters
----------
... | def classify(self, dataset, missing_value_action='auto'):
"""
Return a classification, for each example in the ``dataset``, using the
trained logistic regression model. The output SFrame contains predictions
as both class labels (0 or 1) as well as probabilities that the predicted
... |
Appends the suffix appropriate to 'type/property-set' combination
to the specified name and returns the result. | def add_prefix_and_suffix(specified_name, type, property_set):
"""Appends the suffix appropriate to 'type/property-set' combination
to the specified name and returns the result."""
property_set = b2.util.jam_to_value_maybe(property_set)
suffix = ""
if type:
suffix = b2.build.type.generated... |
Traverses the dependency graph of 'target' and return all targets that will
be created before this one is created. If root of some dependency graph is
found during traversal, it's either included or not, dependencing of the
value of 'include_roots'. In either case, sources of root are not traver... | def traverse (target, include_roots = False, include_sources = False):
""" Traverses the dependency graph of 'target' and return all targets that will
be created before this one is created. If root of some dependency graph is
found during traversal, it's either included or not, dependencing of the
... |
Takes an 'action' instances and creates new instance of it
and all produced target. The rule-name and properties are set
to 'new-rule-name' and 'new-properties', if those are specified.
Returns the cloned action. | def clone_action (action, new_project, new_action_name, new_properties):
"""Takes an 'action' instances and creates new instance of it
and all produced target. The rule-name and properties are set
to 'new-rule-name' and 'new-properties', if those are specified.
Returns the cloned action."""
if __deb... |
Registers a new virtual target. Checks if there's already registered target, with the same
name, type, project and subvariant properties, and also with the same sources
and equal action. If such target is found it is retured and 'target' is not registered.
Otherwise, 'target' is regi... | def register (self, target):
""" Registers a new virtual target. Checks if there's already registered target, with the same
name, type, project and subvariant properties, and also with the same sources
and equal action. If such target is found it is retured and 'target' is not registered... |
Creates a virtual target with appropriate name and type from 'file'.
If a target with that name in that project was already created, returns that already
created target.
TODO: more correct way would be to compute path to the file, based on name and source location
for the... | def from_file (self, file, file_location, project):
""" Creates a virtual target with appropriate name and type from 'file'.
If a target with that name in that project was already created, returns that already
created target.
TODO: more correct way would be to compute path to... |
Appends the suffix appropriate to 'type/property_set' combination
to the specified name and returns the result. | def add_suffix (self, specified_name, file_type, prop_set):
""" Appends the suffix appropriate to 'type/property_set' combination
to the specified name and returns the result.
"""
assert isinstance(specified_name, basestring)
assert isinstance(file_type, basestring)
a... |
Adds additional instances of 'VirtualTarget' that this
one depends on. | def depends (self, d):
""" Adds additional instances of 'VirtualTarget' that this
one depends on.
"""
self.dependencies_ = unique (self.dependencies_ + d).sort () |
Generates all the actual targets and sets up build actions for
this target.
If 'scanner' is specified, creates an additional target
with the same location as actual target, which will depend on the
actual target and be associated with 'scanner'. That additional
... | def actualize (self, scanner = None):
""" Generates all the actual targets and sets up build actions for
this target.
If 'scanner' is specified, creates an additional target
with the same location as actual target, which will depend on the
actual target and be as... |
Sets the path. When generating target name, it will override any path
computation from properties. | def set_path (self, path):
""" Sets the path. When generating target name, it will override any path
computation from properties.
"""
assert isinstance(path, basestring)
self.path_ = os.path.normpath(path) |
Sets/gets the 'root' flag. Target is root is it directly correspods to some
variant of a main target. | def root (self, set = None):
""" Sets/gets the 'root' flag. Target is root is it directly correspods to some
variant of a main target.
"""
assert isinstance(set, (int, bool, type(None)))
if set:
self.root_ = True
return self.root_ |
Gets or sets the subvariant which created this target. Subvariant
is set when target is brought into existance, and is never changed
after that. In particual, if target is shared by subvariant, only
the first is stored.
s: If specified, specified the value to set,
which ... | def creating_subvariant (self, s = None):
""" Gets or sets the subvariant which created this target. Subvariant
is set when target is brought into existance, and is never changed
after that. In particual, if target is shared by subvariant, only
the first is stored.
s: If specifi... |
Helper to 'actual_name', above. Compute unique prefix used to distinguish
this target from other targets with the same name which create different
file. | def grist (self):
"""Helper to 'actual_name', above. Compute unique prefix used to distinguish
this target from other targets with the same name which create different
file.
"""
# Depending on target, there may be different approaches to generating
# unique prefix... |
Given the target name specified in constructor, returns the
name which should be really used, by looking at the <tag> properties.
The tag properties come in two flavour:
- <tag>value,
- <tag>@rule-name
In the first case, value is just added to name
In the second case,... | def __adjust_name(self, specified_name):
"""Given the target name specified in constructor, returns the
name which should be really used, by looking at the <tag> properties.
The tag properties come in two flavour:
- <tag>value,
- <tag>@rule-name
In the first case, val... |
Returns the directory for this target. | def path (self):
""" Returns the directory for this target.
"""
if not self.path_:
if self.action_:
p = self.action_.properties ()
(target_path, relative_to_build_dir) = p.target_path ()
if relative_to_build_dir:
# ... |
Generates actual build instructions. | def actualize (self):
""" Generates actual build instructions.
"""
if self.actualized_:
return
self.actualized_ = True
ps = self.properties ()
properties = self.adjust_properties (ps)
actual_targets = []
for i in self.targets ():
... |
Helper for 'actualize_sources'.
For each passed source, actualizes it with the appropriate scanner.
Returns the actualized virtual targets. | def actualize_source_type (self, sources, prop_set):
""" Helper for 'actualize_sources'.
For each passed source, actualizes it with the appropriate scanner.
Returns the actualized virtual targets.
"""
assert is_iterable_typed(sources, VirtualTarget)
assert isinsta... |
Creates actual jam targets for sources. Initializes two member
variables:
'self.actual_sources_' -- sources which are passed to updating action
'self.dependency_only_sources_' -- sources which are made dependencies, but
are not used otherwise.
New values will... | def actualize_sources (self, sources, prop_set):
""" Creates actual jam targets for sources. Initializes two member
variables:
'self.actual_sources_' -- sources which are passed to updating action
'self.dependency_only_sources_' -- sources which are made dependencies, but
... |
Returns all targets referenced by this subvariant,
either directly or indirectly, and either as sources,
or as dependency properties. Targets referred with
dependency property are returned a properties, not targets. | def all_referenced_targets(self, result):
"""Returns all targets referenced by this subvariant,
either directly or indirectly, and either as sources,
or as dependency properties. Targets referred with
dependency property are returned a properties, not targets."""
if __debug__:
... |
Returns the properties which specify implicit include paths to
generated headers. This traverses all targets in this subvariant,
and subvariants referred by <implcit-dependecy>properties.
For all targets which are of type 'target-type' (or for all targets,
if 'target_type... | def implicit_includes (self, feature, target_type):
""" Returns the properties which specify implicit include paths to
generated headers. This traverses all targets in this subvariant,
and subvariants referred by <implcit-dependecy>properties.
For all targets which are of typ... |
Compare if two nodes are equal. | def cmp_ast(node1, node2):
'''
Compare if two nodes are equal.
'''
if type(node1) != type(node2):
return False
if isinstance(node1, (list, tuple)):
if len(node1) != len(node2):
return False
for left, right in zip(node1, node2):
if not cmp_ast(left, ... |
Creates additional files for the individual MPL-containers. | def create_more_container_files(sourceDir, suffix, maxElements, containers, containers2):
"""Creates additional files for the individual MPL-containers."""
# Create files for each MPL-container with 20 to 'maxElements' elements
# which will be used during generation.
for container in containers:
... |
Creates additional source- and header-files for the numbered sequence MPL-containers. | def create_input_for_numbered_sequences(headerDir, sourceDir, containers, maxElements):
"""Creates additional source- and header-files for the numbered sequence MPL-containers."""
# Create additional container-list without "map".
containersWithoutMap = containers[:]
try:
containersWithoutMap.rem... |
Adjusts the limits of variadic sequence MPL-containers. | def adjust_container_limits_for_variadic_sequences(headerDir, containers, maxElements):
"""Adjusts the limits of variadic sequence MPL-containers."""
for container in containers:
headerFile = os.path.join( headerDir, "limits", container + ".hpp" )
regexMatch = r'(define\s+BOOST_MPL_LIMIT_' + c... |
Returns the (relative) path to the Boost source-directory this file is located in (if any). | def current_boost_dir():
"""Returns the (relative) path to the Boost source-directory this file is located in (if any)."""
# Path to directory containing this script.
path = os.path.dirname( os.path.realpath(__file__) )
# Making sure it is located in "${boost-dir}/libs/mpl/preprocessed".
for directo... |
Converts a string into its encoded positive integer (greater zero) or throws an exception. | def to_positive_multiple_of_10(string):
"""Converts a string into its encoded positive integer (greater zero) or throws an exception."""
try:
value = int(string)
except ValueError:
msg = '"%r" is not a positive multiple of 10 (greater zero).' % string
raise argparse.ArgumentTypeError... |
The main function. | def main():
"""The main function."""
# Find the current Boost source-directory in which this script is located.
sourceDir = current_boost_dir()
if sourceDir == None:
sourceDir = ""
# Prepare and run cmdline-parser.
cmdlineParser = argparse.ArgumentParser(description="A generato... |
Add an inner product layer to the model.
Parameters
----------
name: str
The name of this layer
W: numpy.array or bytes()
Weight matrix of shape (output_channels, input_channels)
If W is of type bytes(), i.e. quantized, other quantization related argu... | def add_inner_product(self, name, W, b, input_channels, output_channels, has_bias,
input_name, output_name, **kwargs):
"""
Add an inner product layer to the model.
Parameters
----------
name: str
The name of this layer
W: numpy.array... |
Add a convolution layer to the network.
Please see the ConvolutionLayerParams in Core ML neural network
protobuf message for more information about input and output blob dimensions.
Parameters
----------
name: str
The name of this layer.
kernel_channels: int... | def add_convolution(self, name, kernel_channels, output_channels, height,
width, stride_height, stride_width, border_mode, groups, W, b, has_bias,
is_deconv = False, output_shape = None,
input_name = 'data', output_name = 'out',
dilation_factors = [1,1],
paddi... |
Add resize bilinear layer to the model. A layer that resizes the input to a given spatial size using bilinear interpolation.
Parameters
----------
name: str
The name of this layer.
input_name: str
The input blob name of this layer.
output_name: str
... | def add_resize_bilinear(self, name, input_name, output_name, target_height=1, target_width=1,
mode='ALIGN_ENDPOINTS_MODE'):
"""
Add resize bilinear layer to the model. A layer that resizes the input to a given spatial size using bilinear interpolation.
Parameters
... |
Add crop resize layer to the model. A layer that extracts cropped spatial patches or RoIs (regions of interest)
from the input and resizes them to a pre-specified size using bilinear interpolation.
Note that RoI Align layer can be implemented with this layer followed by a pooling layer.
Kindly r... | def add_crop_resize(self, name, input_names, output_name, target_height=1, target_width=1,
mode='STRICT_ALIGN_ENDPOINTS_MODE',
normalized_roi=False,
box_indices_mode='CORNERS_HEIGHT_FIRST',
spatial_scale=1.0)... |
Format a doc-string on the fly.
@arg format_dict: A dictionary to format the doc-strings
Example:
@add_docstring({'context': __doc_string_context})
def predict(x):
'''
{context}
>> model.predict(data)
'''
return x | def _add_docstring(format_dict):
"""
Format a doc-string on the fly.
@arg format_dict: A dictionary to format the doc-strings
Example:
@add_docstring({'context': __doc_string_context})
def predict(x):
'''
{context}
>> model.predict(data)
'... |
Serialize model summary into a dict with ordered lists of sections and section titles
Parameters
----------
model : Model object
sections : Ordered list of lists (sections) of tuples (field,value)
[
[(field1, value1), (field2, value2)],
[(field3, value3), (field4, value4)],
... | def _toolkit_serialize_summary_struct(model, sections, section_titles):
"""
Serialize model summary into a dict with ordered lists of sections and section titles
Parameters
----------
model : Model object
sections : Ordered list of lists (sections) of tuples (field,value)
[
[(fi... |
Finds the only column in `SFrame` with a type specified by `target_type`.
If there are zero or more than one such columns, an exception will be
raised. The name and type of the target column should be provided as
strings for the purpose of error feedback. | def _find_only_column_of_type(sframe, target_type, type_name, col_name):
"""
Finds the only column in `SFrame` with a type specified by `target_type`.
If there are zero or more than one such columns, an exception will be
raised. The name and type of the target column should be provided as
strings fo... |
Finds the only column in `sframe` with a type of turicreate.Image.
If there are zero or more than one image columns, an exception will
be raised. | def _find_only_image_column(sframe):
"""
Finds the only column in `sframe` with a type of turicreate.Image.
If there are zero or more than one image columns, an exception will
be raised.
"""
from turicreate import Image
return _find_only_column_of_type(sframe, target_type=Image,
... |
Finds the only column that can be interpreted as a drawing feature column.
A drawing column can be a stroke-based drawing column (with dtype list)
or a bitmap-based drawing column (with dtype turicreate.Image)
If there are zero or more than one drawing columns, an exception will be
raised. | def _find_only_drawing_column(sframe):
"""
Finds the only column that can be interpreted as a drawing feature column.
A drawing column can be a stroke-based drawing column (with dtype list)
or a bitmap-based drawing column (with dtype turicreate.Image)
If there are zero or more than one drawing... |
Convert the Json Tree to SGraph | def _SGraphFromJsonTree(json_str):
"""
Convert the Json Tree to SGraph
"""
g = json.loads(json_str)
vertices = [_Vertex(x['id'],
dict([(str(k), v) for k, v in _six.iteritems(x) if k != 'id']))
for x in g['vertices']]
edges = [... |
Return a tuple of sections and section titles.
Sections are pretty print of model coefficients
Parameters
----------
top_coefs : SFrame of top k coefficients
bottom_coefs : SFrame of bottom k coefficients
Returns
-------
(sections, section_titles) : tuple
sections : list
... | def _summarize_coefficients(top_coefs, bottom_coefs):
"""
Return a tuple of sections and section titles.
Sections are pretty print of model coefficients
Parameters
----------
top_coefs : SFrame of top k coefficients
bottom_coefs : SFrame of bottom k coefficients
Returns
-------
... |
Returns a tuple of the top k values from the positive and
negative values in a SArray
Parameters
----------
values : SFrame of model coefficients
k: Maximum number of largest positive and k lowest negative numbers to return
Returns
-------
(topk_positive, bottomk_positive) : tuple
... | def _toolkit_get_topk_bottomk(values, k=5):
"""
Returns a tuple of the top k values from the positive and
negative values in a SArray
Parameters
----------
values : SFrame of model coefficients
k: Maximum number of largest positive and k lowest negative numbers to return
Returns
-... |
Extract a model summary field value | def __extract_model_summary_value(model, value):
"""
Extract a model summary field value
"""
field_value = None
if isinstance(value, _precomputed_field):
field_value = value.field
else:
field_value = model._get(value)
if isinstance(field_value, float):
try:
... |
Serializes an SFrame to a list of strings, that, when printed, creates a well-formatted table. | def _make_repr_table_from_sframe(X):
"""
Serializes an SFrame to a list of strings, that, when printed, creates a well-formatted table.
"""
assert isinstance(X, _SFrame)
column_names = X.column_names()
out_data = [ [None]*len(column_names) for i in range(X.num_rows())]
column_sizes = [le... |
Display a toolkit repr according to some simple rules.
Parameters
----------
model : Turi Create model
fields: List of lists of tuples
Each tuple should be (display_name, field_name), where field_name can
be a string or a _precomputed_field object.
section_titles: List of section... | def _toolkit_repr_print(model, fields, section_titles, width = None):
"""
Display a toolkit repr according to some simple rules.
Parameters
----------
model : Turi Create model
fields: List of lists of tuples
Each tuple should be (display_name, field_name), where field_name can
... |
Map returning value, if it is unity SFrame, SArray, map it | def _map_unity_proxy_to_object(value):
"""
Map returning value, if it is unity SFrame, SArray, map it
"""
vtype = type(value)
if vtype in _proxy_map:
return _proxy_map[vtype](value)
elif vtype == list:
return [_map_unity_proxy_to_object(v) for v in value]
elif vtype == dict:
... |
Same as select columns but redirect runtime error to ToolkitError. | def _toolkits_select_columns(dataset, columns):
"""
Same as select columns but redirect runtime error to ToolkitError.
"""
try:
return dataset.select_columns(columns)
except RuntimeError:
missing_features = list(set(columns).difference(set(dataset.column_names())))
raise Tool... |
Check if a column exists in an SFrame with error message. | def _raise_error_if_column_exists(dataset, column_name = 'dataset',
dataset_variable_name = 'dataset',
column_name_error_message_name = 'column_name'):
"""
Check if a column exists in an SFrame with error message.
"""
err_msg = 'The SFrame {0} must... |
Check whether or not the requested option is one of the allowed values. | def _check_categorical_option_type(option_name, option_value, possible_values):
"""
Check whether or not the requested option is one of the allowed values.
"""
err_msg = '{0} is not a valid option for {1}. '.format(option_value, option_name)
err_msg += ' Expected one of: '.format(possible_values)
... |
Check if the input is an SArray. Provide a proper error
message otherwise. | def _raise_error_if_not_sarray(dataset, variable_name="SArray"):
"""
Check if the input is an SArray. Provide a proper error
message otherwise.
"""
err_msg = "Input %s is not an SArray."
if not isinstance(dataset, _SArray):
raise ToolkitError(err_msg % variable_name) |
Check if the input is an SFrame. Provide a proper error
message otherwise. | def _raise_error_if_not_sframe(dataset, variable_name="SFrame"):
"""
Check if the input is an SFrame. Provide a proper error
message otherwise.
"""
err_msg = "Input %s is not an SFrame. If it is a Pandas DataFrame,"
err_msg += " you may use the to_sframe() function to convert it to an SFrame."
... |
Check if the input is empty. | def _raise_error_if_sframe_empty(dataset, variable_name="SFrame"):
"""
Check if the input is empty.
"""
err_msg = "Input %s either has no rows or no columns. A non-empty SFrame "
err_msg += "is required."
if dataset.num_rows() == 0 or dataset.num_columns() == 0:
raise ToolkitError(err_m... |
Check if the input is an SFrame. Provide a proper error
message otherwise. | def _raise_error_evaluation_metric_is_valid(metric, allowed_metrics):
"""
Check if the input is an SFrame. Provide a proper error
message otherwise.
"""
err_msg = "Evaluation metric '%s' not recognized. The supported evaluation"
err_msg += " metrics are (%s)."
if metric not in allowed_metr... |
Checks if numeric parameter is within given range | def _numeric_param_check_range(variable_name, variable_value, range_bottom, range_top):
"""
Checks if numeric parameter is within given range
"""
err_msg = "%s must be between %i and %i"
if variable_value < range_bottom or variable_value > range_top:
raise ToolkitError(err_msg % (variable_n... |
Validate and canonicalize training and validation data.
Parameters
----------
dataset : SFrame
Dataset for training the model.
target : string
Name of the column containing the target variable.
features : list[string], optional
List of feature names used.
validation_s... | def _validate_data(dataset, target, features=None, validation_set='auto'):
"""
Validate and canonicalize training and validation data.
Parameters
----------
dataset : SFrame
Dataset for training the model.
target : string
Name of the column containing the target variable.
... |
Validate a row label column. If the row label is not specified, a column is
created with row numbers, named with the string in the `default_label`
parameter.
Parameters
----------
dataset : SFrame
Input dataset.
label : str, optional
Name of the column containing row labels.
... | def _validate_row_label(dataset, label=None, default_label='__id'):
"""
Validate a row label column. If the row label is not specified, a column is
created with row numbers, named with the string in the `default_label`
parameter.
Parameters
----------
dataset : SFrame
Input dataset.... |
Returns Mac version as a tuple of integers, making it easy to do proper
version comparisons. On non-Macs, it returns an empty tuple. | def _mac_ver():
"""
Returns Mac version as a tuple of integers, making it easy to do proper
version comparisons. On non-Macs, it returns an empty tuple.
"""
import platform
import sys
if sys.platform == 'darwin':
ver_str = platform.mac_ver()[0]
return tuple([int(v) for v in v... |
Print a message making it clear to the user what compute resource is used in
neural network training. | def _print_neural_compute_device(cuda_gpus, use_mps, cuda_mem_req=None, has_mps_impl=True):
"""
Print a message making it clear to the user what compute resource is used in
neural network training.
"""
num_cuda_gpus = len(cuda_gpus)
if num_cuda_gpus >= 1:
gpu_names = ', '.join(gpu['name'... |
Get a proto class from the MessageFactory by name.
Args:
factory: a MessageFactory instance.
full_name: str, the fully qualified name of the proto type.
Returns:
A class, for the type identified by full_name.
Raises:
KeyError, if the proto is not found in the factory's descriptor pool. | def _GetMessageFromFactory(factory, full_name):
"""Get a proto class from the MessageFactory by name.
Args:
factory: a MessageFactory instance.
full_name: str, the fully qualified name of the proto type.
Returns:
A class, for the type identified by full_name.
Raises:
KeyError, if the proto is n... |
Create a Protobuf class whose fields are basic types.
Note: this doesn't validate field names!
Args:
fields: dict of {name: field_type} mappings for each field in the proto. If
this is an OrderedDict the order will be maintained, otherwise the
fields will be sorted by name.
full_name: opti... | def MakeSimpleProtoClass(fields, full_name=None, pool=None):
"""Create a Protobuf class whose fields are basic types.
Note: this doesn't validate field names!
Args:
fields: dict of {name: field_type} mappings for each field in the proto. If
this is an OrderedDict the order will be maintained, otherw... |
Populate FileDescriptorProto for MessageFactory's DescriptorPool. | def _MakeFileDescriptorProto(proto_file_name, full_name, field_items):
"""Populate FileDescriptorProto for MessageFactory's DescriptorPool."""
package, name = full_name.rsplit('.', 1)
file_proto = descriptor_pb2.FileDescriptorProto()
file_proto.name = os.path.join(package.replace('.', '/'), proto_file_name)
f... |
Convert a decision tree model to protobuf format.
Parameters
----------
decision_tree : DecisionTreeClassifier
A trained scikit-learn tree model.
input_name: str
Name of the input columns.
output_name: str
Name of the output columns.
Returns
-------
model_spec... | def convert(model, input_name, output_features):
"""Convert a decision tree model to protobuf format.
Parameters
----------
decision_tree : DecisionTreeClassifier
A trained scikit-learn tree model.
input_name: str
Name of the input columns.
output_name: str
Name of the... |
Returns user-defined metadata, making sure information all models should
have is also available, as a dictionary | def _get_model_metadata(model_class, metadata, version=None):
"""
Returns user-defined metadata, making sure information all models should
have is also available, as a dictionary
"""
from turicreate import __version__
info = {
'turicreate_version': __version__,
'type': model_cla... |
Sets user-defined metadata, making sure information all models should have
is also available | def _set_model_metadata(mlmodel, model_class, metadata, version=None):
"""
Sets user-defined metadata, making sure information all models should have
is also available
"""
info = _get_model_metadata(model_class, metadata, version)
mlmodel.user_defined_metadata.update(info) |
Converts name to camel-case and returns it. | def _ToCamelCase(name):
"""Converts name to camel-case and returns it."""
capitalize_next = False
result = []
for c in name:
if c == '_':
if result:
capitalize_next = True
elif capitalize_next:
result.append(c.upper())
capitalize_next = False
else:
result += c
# L... |
Converts name to Json name and returns it. | def _ToJsonName(name):
"""Converts name to Json name and returns it."""
capitalize_next = False
result = []
for c in name:
if c == '_':
capitalize_next = True
elif capitalize_next:
result.append(c.upper())
capitalize_next = False
else:
result += c
return ''.join(result) |
Sets the descriptor's options
This function is used in generated proto2 files to update descriptor
options. It must not be used outside proto2. | def _SetOptions(self, options, options_class_name):
"""Sets the descriptor's options
This function is used in generated proto2 files to update descriptor
options. It must not be used outside proto2.
"""
self._options = options
self._options_class_name = options_class_name
# Does this descr... |
Retrieves descriptor options.
This method returns the options set or creates the default options for the
descriptor. | def GetOptions(self):
"""Retrieves descriptor options.
This method returns the options set or creates the default options for the
descriptor.
"""
if self._options:
return self._options
from google.protobuf import descriptor_pb2
try:
options_class = getattr(descriptor_pb2, self._... |
Copies this to the matching proto in descriptor_pb2.
Args:
proto: An empty proto instance from descriptor_pb2.
Raises:
Error: If self couldnt be serialized, due to to few constructor arguments. | def CopyToProto(self, proto):
"""Copies this to the matching proto in descriptor_pb2.
Args:
proto: An empty proto instance from descriptor_pb2.
Raises:
Error: If self couldnt be serialized, due to to few constructor arguments.
"""
if (self.file is not None and
self._serialized_... |
Returns the string name of an enum value.
This is just a small helper method to simplify a common operation.
Args:
enum: string name of the Enum.
value: int, value of the enum.
Returns:
string name of the enum value.
Raises:
KeyError if either the Enum doesn't exist or the va... | def EnumValueName(self, enum, value):
"""Returns the string name of an enum value.
This is just a small helper method to simplify a common operation.
Args:
enum: string name of the Enum.
value: int, value of the enum.
Returns:
string name of the enum value.
Raises:
KeyErr... |
Given a target_reference, made in context of 'project',
returns the AbstractTarget instance that is referred to, as well
as properties explicitly specified for this reference. | def resolve_reference(target_reference, project):
""" Given a target_reference, made in context of 'project',
returns the AbstractTarget instance that is referred to, as well
as properties explicitly specified for this reference.
"""
# Separate target name from properties override
assert isinsta... |
Attempts to generate the target given by target reference, which
can refer both to a main target or to a file.
Returns a list consisting of
- usage requirements
- generated virtual targets, if any
target_reference: Target reference
project: Project where the reference is made
prop... | def generate_from_reference(target_reference, project, property_set_):
""" Attempts to generate the target given by target reference, which
can refer both to a main target or to a file.
Returns a list consisting of
- usage requirements
- generated virtual targets, if any
target_reference: Targe... |
Registers the specified target as a main target alternatives.
Returns 'target'. | def main_target_alternative (self, target):
""" Registers the specified target as a main target alternatives.
Returns 'target'.
"""
assert isinstance(target, AbstractTarget)
target.project ().add_alternative (target)
return target |
Return the list of sources to use, if main target rule is invoked
with 'sources'. If there are any objects in 'sources', they are treated
as main target instances, and the name of such targets are adjusted to
be '<name_of_this_target>__<name_of_source_target>'. Such renaming
is disabled ... | def main_target_sources (self, sources, main_target_name, no_renaming=0):
"""Return the list of sources to use, if main target rule is invoked
with 'sources'. If there are any objects in 'sources', they are treated
as main target instances, and the name of such targets are adjusted to
be... |
Returns the requirement to use when declaring a main target,
which are obtained by
- translating all specified property paths, and
- refining project requirements with the one specified for the target
'specification' are the properties xplicitly specified for a
main target... | def main_target_requirements(self, specification, project):
"""Returns the requirement to use when declaring a main target,
which are obtained by
- translating all specified property paths, and
- refining project requirements with the one specified for the target
'specificat... |
Returns the use requirement to use when declaraing a main target,
which are obtained by
- translating all specified property paths, and
- adding project's usage requirements
specification: Use-properties explicitly specified for a main target
project: ... | def main_target_usage_requirements (self, specification, project):
""" Returns the use requirement to use when declaraing a main target,
which are obtained by
- translating all specified property paths, and
- adding project's usage requirements
specification: Use... |
Return the default build value to use when declaring a main target,
which is obtained by using specified value if not empty and parent's
default build attribute otherwise.
specification: Default build explicitly specified for a main target
project: Project where t... | def main_target_default_build (self, specification, project):
""" Return the default build value to use when declaring a main target,
which is obtained by using specified value if not empty and parent's
default build attribute otherwise.
specification: Default build explicit... |
Helper rules to detect cycles in main target references. | def start_building (self, main_target_instance):
""" Helper rules to detect cycles in main target references.
"""
assert isinstance(main_target_instance, MainTarget)
if id(main_target_instance) in self.targets_being_built_:
names = []
for t in self.targets_being_b... |
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