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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/virtual_target.py | Subvariant.implicit_includes | 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... | python | 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.
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apple/turicreate | src/unity/python/turicreate/meta/asttools/__init__.py | cmp_ast | 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
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if not cmp_ast(left, ... | python | def cmp_ast(node1, node2):
'''
Compare if two nodes are equal.
'''
if type(node1) != type(node2):
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apple/turicreate | deps/src/boost_1_68_0/libs/mpl/preprocessed/boost_mpl_preprocess.py | create_more_container_files | 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:
... | python | def create_more_container_files(sourceDir, suffix, maxElements, containers, containers2):
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# Create files for each MPL-container with 20 to 'maxElements' elements
# which will be used during generation.
for container in containers:
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apple/turicreate | deps/src/boost_1_68_0/libs/mpl/preprocessed/boost_mpl_preprocess.py | create_input_for_numbered_sequences | 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... | python | 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".
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apple/turicreate | deps/src/boost_1_68_0/libs/mpl/preprocessed/boost_mpl_preprocess.py | adjust_container_limits_for_variadic_sequences | 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... | python | 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" )
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apple/turicreate | deps/src/boost_1_68_0/libs/mpl/preprocessed/boost_mpl_preprocess.py | current_boost_dir | 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 "${boost-dir}/libs/mpl/preprocessed".
for directo... | python | def current_boost_dir():
"""Returns the (relative) path to the Boost source-directory this file is located in (if any)."""
# Path to directory containing this script.
path = os.path.dirname( os.path.realpath(__file__) )
# Making sure it is located in "${boost-dir}/libs/mpl/preprocessed".
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apple/turicreate | deps/src/boost_1_68_0/libs/mpl/preprocessed/boost_mpl_preprocess.py | to_positive_multiple_of_10 | def to_positive_multiple_of_10(string):
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raise argparse.ArgumentTypeError... | python | def to_positive_multiple_of_10(string):
"""Converts a string into its encoded positive integer (greater zero) or throws an exception."""
try:
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except ValueError:
msg = '"%r" is not a positive multiple of 10 (greater zero).' % string
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apple/turicreate | deps/src/boost_1_68_0/libs/mpl/preprocessed/boost_mpl_preprocess.py | main | 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... | python | 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... | [
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/builder.py | NeuralNetworkBuilder.add_inner_product | 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... | python | 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
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/builder.py | NeuralNetworkBuilder.add_convolution | def add_convolution(self, name, kernel_channels, output_channels, height,
width, stride_height, stride_width, border_mode, groups, W, b, has_bias,
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/builder.py | NeuralNetworkBuilder.add_resize_bilinear | def add_resize_bilinear(self, name, input_name, output_name, target_height=1, target_width=1,
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Add resize bilinear layer to the model. A layer that resizes the input to a given spatial size using bilinear interpolation.
Parameters
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Add resize bilinear layer to the model. A layer that resizes the input to a given spatial size using bilinear interpolation.
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/builder.py | NeuralNetworkBuilder.add_crop_resize | def add_crop_resize(self, name, input_names, output_name, target_height=1, target_width=1,
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _toolkit_serialize_summary_struct | 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)
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Serialize model summary into a dict with ordered lists of sections and section titles
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model : Model object
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _add_docstring | 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)
'... | python | def _add_docstring(format_dict):
"""
Format a doc-string on the fly.
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def predict(x):
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _find_only_column_of_type | 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... | python | 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
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _find_only_image_column | 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,
... | python | 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,
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _find_only_drawing_column | 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... | python | 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)
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _SGraphFromJsonTree | 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 = [... | python | 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 = [... | [
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _summarize_coefficients | 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
-------
... | python | 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
-------
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _toolkit_get_topk_bottomk | 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
-... | python | 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
-... | [
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | __extract_model_summary_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:
... | python | 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:
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _make_repr_table_from_sframe | 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... | python | 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... | [
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _toolkit_repr_print | 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
... | python | 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
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _map_unity_proxy_to_object | 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:
... | python | 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:
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _toolkits_select_columns | 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... | python | 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... | [
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _raise_error_if_column_exists | 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... | python | 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... | [
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _check_categorical_option_type | 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)
... | python | 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)
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _raise_error_if_not_sarray | 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) | python | 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."
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _raise_error_if_not_sframe | def _raise_error_if_not_sframe(dataset, variable_name="SFrame"):
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _raise_error_if_sframe_empty | def _raise_error_if_sframe_empty(dataset, variable_name="SFrame"):
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"""
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _raise_error_evaluation_metric_is_valid | def _raise_error_evaluation_metric_is_valid(metric, allowed_metrics):
"""
Check if the input is an SFrame. Provide a proper error
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"""
err_msg = "Evaluation metric '%s' not recognized. The supported evaluation"
err_msg += " metrics are (%s)."
if metric not in allowed_metr... | python | def _raise_error_evaluation_metric_is_valid(metric, allowed_metrics):
"""
Check if the input is an SFrame. Provide a proper error
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _numeric_param_check_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... | python | def _numeric_param_check_range(variable_name, variable_value, range_bottom, range_top):
"""
Checks if numeric parameter is within given range
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err_msg = "%s must be between %i and %i"
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _validate_data | 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.
... | python | def _validate_data(dataset, target, features=None, validation_set='auto'):
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Validate and canonicalize training and validation data.
Parameters
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dataset : SFrame
Dataset for training the model.
target : string
Name of the column containing the target variable.
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _validate_row_label | def _validate_row_label(dataset, label=None, default_label='__id'):
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Validate a row label column. If the row label is not specified, a column is
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dataset : SFrame
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Validate a row label column. If the row label is not specified, a column is
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _mac_ver | def _mac_ver():
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Returns Mac version as a tuple of integers, making it easy to do proper
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"""
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import sys
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"""
Returns Mac version as a tuple of integers, making it easy to do proper
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apple/turicreate | src/unity/python/turicreate/toolkits/_internal_utils.py | _print_neural_compute_device | 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'... | python | 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'... | [
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/proto_builder.py | _GetMessageFromFactory | 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... | python | 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.
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A class, for the type identified by full_name.
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/proto_builder.py | MakeSimpleProtoClass | 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... | python | def MakeSimpleProtoClass(fields, full_name=None, pool=None):
"""Create a Protobuf class whose fields are basic types.
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fields: dict of {name: field_type} mappings for each field in the proto. If
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/proto_builder.py | _MakeFileDescriptorProto | 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... | python | 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)
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apple/turicreate | src/external/coremltools_wrap/coremltools/coremltools/converters/sklearn/_decision_tree_classifier.py | convert | 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... | python | 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.
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apple/turicreate | src/unity/python/turicreate/toolkits/_coreml_utils.py | _get_model_metadata | 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... | python | 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__,
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apple/turicreate | src/unity/python/turicreate/toolkits/_coreml_utils.py | _set_model_metadata | 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) | python | 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)
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/descriptor.py | _ToCamelCase | def _ToCamelCase(name):
"""Converts name to camel-case and returns it."""
capitalize_next = False
result = []
for c in name:
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capitalize_next = False
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# L... | python | 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
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capitalize_next = False
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/descriptor.py | _ToJsonName | def _ToJsonName(name):
"""Converts name to Json name and returns it."""
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return ''.join(result) | python | def _ToJsonName(name):
"""Converts name to Json name and returns it."""
capitalize_next = False
result = []
for c in name:
if c == '_':
capitalize_next = True
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/descriptor.py | DescriptorBase._SetOptions | 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... | python | 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
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/descriptor.py | DescriptorBase.GetOptions | def GetOptions(self):
"""Retrieves descriptor options.
This method returns the options set or creates the default options for the
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"""
if self._options:
return self._options
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try:
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"""Retrieves descriptor options.
This method returns the options set or creates the default options for the
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"""
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return self._options
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/descriptor.py | _NestedDescriptorBase.CopyToProto | 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_... | python | 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.
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apple/turicreate | src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/descriptor.py | Descriptor.EnumValueName | 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.
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enum: string name of the Enum.
value: int, value of the enum.
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Raises:
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"""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.
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string name of the enum value.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | resolve_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... | python | 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.
"""
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | generate_from_reference | 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... | python | def generate_from_reference(target_reference, project, property_set_):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | TargetRegistry.main_target_alternative | 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 | python | 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)
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | TargetRegistry.main_target_sources | 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
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | TargetRegistry.main_target_requirements | def main_target_requirements(self, specification, project):
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- refining project requirements with the one specified for the target
'specificat... | python | def main_target_requirements(self, specification, project):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | TargetRegistry.main_target_usage_requirements | def main_target_usage_requirements (self, specification, project):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | TargetRegistry.main_target_default_build | 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... | python | def main_target_default_build (self, specification, project):
""" Return the default build value to use when declaring a main target,
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | BasicTarget.sources | def sources (self):
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The extra properties specified for sources are not represented.
The only used of this rule at the moment is the '--dump-tests'
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"""
if self.source... | python | def sources (self):
""" Returns the list of AbstractTargets which are used as sources.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | BasicTarget.common_properties | def common_properties (self, build_request, requirements):
""" Given build request and requirements, return properties
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properties.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | BasicTarget.match | def match (self, property_set_, debug):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | BasicTarget.generate_dependency_properties | def generate_dependency_properties(self, properties, ps):
""" Takes a target reference, which might be either target id
or a dependency property, and generates that target using
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Returns a tuple (result, usage_requirements).
"""
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | BasicTarget.generate | def generate (self, ps):
""" Determines final build properties, generates sources,
and calls 'construct'. This method should not be
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"""
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""" Determines final build properties, generates sources,
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | BasicTarget.compute_usage_requirements | def compute_usage_requirements (self, subvariant):
""" Given the set of generated targets, and refined build
properties, determines and sets appripriate usage requirements
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"""
assert isinstance(subvariant, virtual_target.Subvariant)
rproperties =... | python | def compute_usage_requirements (self, subvariant):
""" Given the set of generated targets, and refined build
properties, determines and sets appripriate usage requirements
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"""
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/build/targets.py | BasicTarget.create_subvariant | def create_subvariant (self, root_targets, all_targets,
build_request, sources,
rproperties, usage_requirements):
"""Creates a new subvariant-dg instances for 'targets'
- 'root-targets' the virtual targets will be returned to dependents
- '... | python | def create_subvariant (self, root_targets, all_targets,
build_request, sources,
rproperties, usage_requirements):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/tools/builtin.py | variant | def variant (name, parents_or_properties, explicit_properties = []):
""" Declares a new variant.
First determines explicit properties for this variant, by
refining parents' explicit properties with the passed explicit
properties. The result is remembered and will be used if
this vari... | python | def variant (name, parents_or_properties, explicit_properties = []):
""" Declares a new variant.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/tools/builtin.py | register_globals | def register_globals ():
""" Registers all features and variants declared by this module.
"""
# This feature is used to determine which OS we're on.
# In future, this may become <target-os> and <host-os>
# TODO: check this. Compatibility with bjam names? Subfeature for version?
os = sys.platfor... | python | def register_globals ():
""" Registers all features and variants declared by this module.
"""
# This feature is used to determine which OS we're on.
# In future, this may become <target-os> and <host-os>
# TODO: check this. Compatibility with bjam names? Subfeature for version?
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/tools/builtin.py | lib | def lib(names, sources=[], requirements=[], default_build=[], usage_requirements=[]):
"""The implementation of the 'lib' rule. Beyond standard syntax that rule allows
simplified: 'lib a b c ;'."""
assert is_iterable_typed(names, basestring)
assert is_iterable_typed(sources, basestring)
assert is_ite... | python | def lib(names, sources=[], requirements=[], default_build=[], usage_requirements=[]):
"""The implementation of the 'lib' rule. Beyond standard syntax that rule allows
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assert is_iterable_typed(names, basestring)
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/tools/builtin.py | CompileAction.adjust_properties | def adjust_properties (self, prop_set):
""" For all virtual targets for the same dependency graph as self,
i.e. which belong to the same main target, add their directories
to include path.
"""
assert isinstance(prop_set, property_set.PropertySet)
s = self.targets ... | python | def adjust_properties (self, prop_set):
""" For all virtual targets for the same dependency graph as self,
i.e. which belong to the same main target, add their directories
to include path.
"""
assert isinstance(prop_set, property_set.PropertySet)
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apple/turicreate | src/unity/python/turicreate/toolkits/recommender/popularity_recommender.py | create | def create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
random_seed=0,
verbose=True):
"""
Create a model that makes recommendations using item popularity. When no
target column is provided, the popularity is ... | python | def create(observation_data,
user_id='user_id', item_id='item_id', target=None,
user_data=None, item_data=None,
random_seed=0,
verbose=True):
"""
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apple/turicreate | src/external/xgboost/python-package/xgboost/sklearn.py | XGBModel.get_params | def get_params(self, deep=False):
"""Get parameter.s"""
params = super(XGBModel, self).get_params(deep=deep)
if params['missing'] is np.nan:
params['missing'] = None # sklearn doesn't handle nan. see #4725
if not params.get('eval_metric', True):
del params['eval_... | python | def get_params(self, deep=False):
"""Get parameter.s"""
params = super(XGBModel, self).get_params(deep=deep)
if params['missing'] is np.nan:
params['missing'] = None # sklearn doesn't handle nan. see #4725
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apple/turicreate | src/external/xgboost/python-package/xgboost/sklearn.py | XGBModel.get_xgb_params | def get_xgb_params(self):
"""Get xgboost type parameters."""
xgb_params = self.get_params()
xgb_params['silent'] = 1 if self.silent else 0
if self.nthread <= 0:
xgb_params.pop('nthread', None)
return xgb_params | python | def get_xgb_params(self):
"""Get xgboost type parameters."""
xgb_params = self.get_params()
xgb_params['silent'] = 1 if self.silent else 0
if self.nthread <= 0:
xgb_params.pop('nthread', None)
return xgb_params | [
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apple/turicreate | src/external/xgboost/python-package/xgboost/sklearn.py | XGBModel.fit | def fit(self, X, y, eval_set=None, eval_metric=None,
early_stopping_rounds=None, verbose=True):
# pylint: disable=missing-docstring,invalid-name,attribute-defined-outside-init
"""
Fit the gradient boosting model
Parameters
----------
X : array_like
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early_stopping_rounds=None, verbose=True):
# pylint: disable=missing-docstring,invalid-name,attribute-defined-outside-init
"""
Fit the gradient boosting model
Parameters
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X : array_like
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apple/turicreate | src/external/xgboost/python-package/xgboost/sklearn.py | XGBClassifier.fit | def fit(self, X, y, sample_weight=None, eval_set=None, eval_metric=None,
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/utility.py | add_grist | def add_grist (features):
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""" Transform a string by bracketing it with "<>". If already bracketed, does nothing.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/utility.py | replace_grist | def replace_grist (features, new_grist):
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Returns the string with the new grist.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/utility.py | get_value | def get_value (property):
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"""
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""" Gets the value of a property, that is, the part following the grist, if any.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/utility.py | get_grist | def get_grist (value):
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/utility.py | ungrist | def ungrist (value):
""" Returns the value without grist.
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"""
assert is_iterable_typed(value, basestring) or isinstance(value, basestring)
def ungrist_one (value):
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""" Returns the value without grist.
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/utility.py | replace_suffix | def replace_suffix (name, new_suffix):
""" Replaces the suffix of name by new_suffix.
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"""
assert isinstance(name, basestring)
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split = os.path.splitext (name)
return split [0] + new_suffix | python | def replace_suffix (name, new_suffix):
""" Replaces the suffix of name by new_suffix.
If no suffix exists, the new one is added.
"""
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/utility.py | split_action_id | def split_action_id (id):
""" Splits an id in the toolset and specific rule parts. E.g.
'gcc.compile.c++' returns ('gcc', 'compile.c++')
"""
assert isinstance(id, basestring)
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toolset = split [0]
name = ''
if len (split) > 1:
name = split [1]
retu... | python | def split_action_id (id):
""" Splits an id in the toolset and specific rule parts. E.g.
'gcc.compile.c++' returns ('gcc', 'compile.c++')
"""
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apple/turicreate | deps/src/boost_1_68_0/tools/build/src/util/utility.py | on_windows | def on_windows ():
""" Returns true if running on windows, whether in cygwin or not.
"""
if bjam.variable("NT"):
return True
elif bjam.variable("UNIX"):
uname = bjam.variable("JAMUNAME")
if uname and uname[0].startswith("CYGWIN"):
return True
return False | python | def on_windows ():
""" Returns true if running on windows, whether in cygwin or not.
"""
if bjam.variable("NT"):
return True
elif bjam.variable("UNIX"):
uname = bjam.variable("JAMUNAME")
if uname and uname[0].startswith("CYGWIN"):
return True
return False | [
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apple/turicreate | src/unity/python/turicreate/toolkits/clustering/kmeans.py | _validate_dataset | def _validate_dataset(dataset):
"""
Validate the main Kmeans dataset.
Parameters
----------
dataset: SFrame
Input dataset.
"""
if not (isinstance(dataset, _SFrame)):
raise TypeError("Input 'dataset' must be an SFrame.")
if dataset.num_rows() == 0 or dataset.num_columns(... | python | def _validate_dataset(dataset):
"""
Validate the main Kmeans dataset.
Parameters
----------
dataset: SFrame
Input dataset.
"""
if not (isinstance(dataset, _SFrame)):
raise TypeError("Input 'dataset' must be an SFrame.")
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apple/turicreate | src/unity/python/turicreate/toolkits/clustering/kmeans.py | _validate_initial_centers | def _validate_initial_centers(initial_centers):
"""
Validate the initial centers.
Parameters
----------
initial_centers : SFrame
Initial cluster center locations, in SFrame form.
"""
if not (isinstance(initial_centers, _SFrame)):
raise TypeError("Input 'initial_centers' must... | python | def _validate_initial_centers(initial_centers):
"""
Validate the initial centers.
Parameters
----------
initial_centers : SFrame
Initial cluster center locations, in SFrame form.
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apple/turicreate | src/unity/python/turicreate/toolkits/clustering/kmeans.py | _validate_num_clusters | def _validate_num_clusters(num_clusters, initial_centers, num_rows):
"""
Validate the combination of the `num_clusters` and `initial_centers`
parameters in the Kmeans model create function. If the combination is
valid, determine and return the correct number of clusters.
Parameters
----------
... | python | def _validate_num_clusters(num_clusters, initial_centers, num_rows):
"""
Validate the combination of the `num_clusters` and `initial_centers`
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apple/turicreate | src/unity/python/turicreate/toolkits/clustering/kmeans.py | _validate_features | def _validate_features(features, column_type_map, valid_types, label):
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Identify the subset of desired `features` that are valid for the Kmeans
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Parameters
----------
features : list[str]
Desired feature names.
column... | python | def _validate_features(features, column_type_map, valid_types, label):
"""
Identify the subset of desired `features` that are valid for the Kmeans
model. A warning is emitted for each feature that is excluded.
Parameters
----------
features : list[str]
Desired feature names.
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Desired feature names.
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apple/turicreate | src/unity/python/turicreate/toolkits/clustering/kmeans.py | create | def create(dataset, num_clusters=None, features=None, label=None,
initial_centers=None, max_iterations=10, batch_size=None,
verbose=True):
"""
Create a k-means clustering model. The KmeansModel object contains the
computed cluster centers and the cluster assignment for each instance in... | python | def create(dataset, num_clusters=None, features=None, label=None,
initial_centers=None, max_iterations=10, batch_size=None,
verbose=True):
"""
Create a k-means clustering model. The KmeansModel object contains the
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apple/turicreate | src/unity/python/turicreate/toolkits/clustering/kmeans.py | KmeansModel.predict | def predict(self, dataset, output_type='cluster_id', verbose=True):
"""
Return predicted cluster label for instances in the new 'dataset'.
K-means predictions are made by assigning each new instance to the
closest cluster center.
Parameters
----------
dataset : S... | python | def predict(self, dataset, output_type='cluster_id', verbose=True):
"""
Return predicted cluster label for instances in the new 'dataset'.
K-means predictions are made by assigning each new instance to the
closest cluster center.
Parameters
----------
dataset : S... | [
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Dataset of new observations. Must include the features used for
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apple/turicreate | src/unity/python/turicreate/toolkits/clustering/kmeans.py | KmeansModel._get | def _get(self, field):
"""
Return the value of a given field.
+-----------------------+----------------------------------------------+
| Field | Description |
+=======================+==============================================... | python | def _get(self, field):
"""
Return the value of a given field.
+-----------------------+----------------------------------------------+
| Field | Description |
+=======================+==============================================... | [
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| Field | Description |
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