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hpi-xnor/BMXNet | ed0b201da6667887222b8e4b5f997c4f6b61943d | python/mxnet/module/base_module.py | python | BaseModule.output_names | (self) | A list of names for the outputs of this module. | A list of names for the outputs of this module. | [
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"""A list of names for the outputs of this module."""
raise NotImplementedError() | [
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kevinlin311tw/Caffe-DeepBinaryCode | 9eaa7662be47d49f475ecbeea2bd51be105270d2 | python/caffe/net_spec.py | python | to_proto | (*tops) | return net | Generate a NetParameter that contains all layers needed to compute
all arguments. | Generate a NetParameter that contains all layers needed to compute
all arguments. | [
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"""Generate a NetParameter that contains all layers needed to compute
all arguments."""
layers = OrderedDict()
autonames = Counter()
for top in tops:
top.fn._to_proto(layers, {}, autonames)
net = caffe_pb2.NetParameter()
net.layer.extend(layers.values())
return net | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/propgrid.py | python | PyIntProperty.__init__ | (self, *args) | __init__(self, String label=(*wxPGProperty::sm_wxPG_LABEL), String name=(*wxPGProperty::sm_wxPG_LABEL),
long value=0) -> PyIntProperty
__init__(self, String label, String name, wxLongLong value) -> PyIntProperty | __init__(self, String label=(*wxPGProperty::sm_wxPG_LABEL), String name=(*wxPGProperty::sm_wxPG_LABEL),
long value=0) -> PyIntProperty
__init__(self, String label, String name, wxLongLong value) -> PyIntProperty | [
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etotheipi/BitcoinArmory | 2a6fc5355bb0c6fe26e387ccba30a5baafe8cd98 | osxbuild/build-app.py | python | getTarUnpackPath | (tarName, inDir=None) | return theDir | NOTE: THIS FUNCTION IS NOT RELIABLE. It only works if the tar file would
extract a single directory with all contents in that dir. If it
unpacks more than one file or directory, the output will be incomplete. | NOTE: THIS FUNCTION IS NOT RELIABLE. It only works if the tar file would
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"""
NOTE: THIS FUNCTION IS NOT RELIABLE. It only works if the tar file would
extract a single directory with all contents in that dir. If it
unpacks more than one file or directory, the output will be incomplete.
"""
tarPath = tarName
if inDir is not None:
tarPath = path.join(inDir, tarName)
# HACK: XZ support was added to tarfile.open() in Python 3.3. Can't use for
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# exited with status 254Child process exited with status 254"
if tarName == "Python-%s.tar.xz" % pythonVer:
theDir = "Python-%s" % pythonVer
else:
tar = tarfile.open(tarPath,'r')
theDir = tar.next().name.split('/')[0]
tar.close()
return theDir | [
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apache/singa | 93fd9da72694e68bfe3fb29d0183a65263d238a1 | python/singa/autograd.py | python | _not | (x) | return Not()(x)[0] | Return `np.logical_not(x)`, where x is Tensor. | Return `np.logical_not(x)`, where x is Tensor. | [
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"""
Return `np.logical_not(x)`, where x is Tensor.
"""
return Not()(x)[0] | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/contrib/tensor_forest/python/tensor_forest.py | python | RandomTreeGraphs.training_graph | (self, input_data, input_labels, random_seed,
data_spec, epoch=None) | return control_flow_ops.group(*updates) | Constructs a TF graph for training a random tree.
Args:
input_data: A tensor or SparseTensor or placeholder for input data.
input_labels: A tensor or placeholder for labels associated with
input_data.
random_seed: The random number generator seed to use for this tree. 0
means use the current time as the seed.
data_spec: A list of tf.dtype values specifying the original types of
each column.
epoch: A tensor or placeholder for the epoch the training data comes from.
Returns:
The last op in the random tree training graph. | Constructs a TF graph for training a random tree. | [
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"for",
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] | def training_graph(self, input_data, input_labels, random_seed,
data_spec, epoch=None):
"""Constructs a TF graph for training a random tree.
Args:
input_data: A tensor or SparseTensor or placeholder for input data.
input_labels: A tensor or placeholder for labels associated with
input_data.
random_seed: The random number generator seed to use for this tree. 0
means use the current time as the seed.
data_spec: A list of tf.dtype values specifying the original types of
each column.
epoch: A tensor or placeholder for the epoch the training data comes from.
Returns:
The last op in the random tree training graph.
"""
epoch = [0] if epoch is None else epoch
sparse_indices = []
sparse_values = []
sparse_shape = []
if isinstance(input_data, ops.SparseTensor):
sparse_indices = input_data.indices
sparse_values = input_data.values
sparse_shape = input_data.shape
input_data = []
# Count extremely random stats.
(node_sums, node_squares, splits_indices, splits_sums,
splits_squares, totals_indices, totals_sums,
totals_squares, input_leaves) = (
self.training_ops.count_extremely_random_stats(
input_data, sparse_indices, sparse_values, sparse_shape,
data_spec, input_labels, self.variables.tree,
self.variables.tree_thresholds,
self.variables.node_to_accumulator_map,
self.variables.candidate_split_features,
self.variables.candidate_split_thresholds,
self.variables.start_epoch, epoch,
num_classes=self.params.num_output_columns,
regression=self.params.regression))
node_update_ops = []
node_update_ops.append(
state_ops.assign_add(self.variables.node_sums, node_sums))
splits_update_ops = []
splits_update_ops.append(self.training_ops.scatter_add_ndim(
self.variables.candidate_split_sums,
splits_indices, splits_sums))
splits_update_ops.append(self.training_ops.scatter_add_ndim(
self.variables.accumulator_sums, totals_indices,
totals_sums))
if self.params.regression:
node_update_ops.append(state_ops.assign_add(self.variables.node_squares,
node_squares))
splits_update_ops.append(self.training_ops.scatter_add_ndim(
self.variables.candidate_split_squares,
splits_indices, splits_squares))
splits_update_ops.append(self.training_ops.scatter_add_ndim(
self.variables.accumulator_squares, totals_indices,
totals_squares))
# Sample inputs.
update_indices, feature_updates, threshold_updates = (
self.training_ops.sample_inputs(
input_data, sparse_indices, sparse_values, sparse_shape,
self.variables.node_to_accumulator_map,
input_leaves, self.variables.candidate_split_features,
self.variables.candidate_split_thresholds,
split_initializations_per_input=(
self.params.split_initializations_per_input),
split_sampling_random_seed=random_seed))
update_features_op = state_ops.scatter_update(
self.variables.candidate_split_features, update_indices,
feature_updates)
update_thresholds_op = state_ops.scatter_update(
self.variables.candidate_split_thresholds, update_indices,
threshold_updates)
# Calculate finished nodes.
with ops.control_dependencies(splits_update_ops):
children = array_ops.squeeze(array_ops.slice(
self.variables.tree, [0, 0], [-1, 1]), squeeze_dims=[1])
is_leaf = math_ops.equal(constants.LEAF_NODE, children)
leaves = math_ops.to_int32(array_ops.squeeze(array_ops.where(is_leaf),
squeeze_dims=[1]))
finished, stale = self.training_ops.finished_nodes(
leaves, self.variables.node_to_accumulator_map,
self.variables.candidate_split_sums,
self.variables.candidate_split_squares,
self.variables.accumulator_sums,
self.variables.accumulator_squares,
self.variables.start_epoch, epoch,
num_split_after_samples=self.params.split_after_samples,
min_split_samples=self.params.min_split_samples)
# Update leaf scores.
non_fertile_leaves = array_ops.boolean_mask(
leaves, math_ops.less(array_ops.gather(
self.variables.node_to_accumulator_map, leaves), 0))
# TODO(gilberth): It should be possible to limit the number of non
# fertile leaves we calculate scores for, especially since we can only take
# at most array_ops.shape(finished)[0] of them.
with ops.control_dependencies(node_update_ops):
sums = array_ops.gather(self.variables.node_sums, non_fertile_leaves)
if self.params.regression:
squares = array_ops.gather(self.variables.node_squares,
non_fertile_leaves)
non_fertile_leaf_scores = self._variance(sums, squares)
else:
non_fertile_leaf_scores = self._weighted_gini(sums)
# Calculate best splits.
with ops.control_dependencies(splits_update_ops):
split_indices = self.training_ops.best_splits(
finished, self.variables.node_to_accumulator_map,
self.variables.candidate_split_sums,
self.variables.candidate_split_squares,
self.variables.accumulator_sums,
self.variables.accumulator_squares,
regression=self.params.regression)
# Grow tree.
with ops.control_dependencies([update_features_op, update_thresholds_op]):
(tree_update_indices, tree_children_updates, tree_threshold_updates,
new_eot) = (self.training_ops.grow_tree(
self.variables.end_of_tree, self.variables.node_to_accumulator_map,
finished, split_indices, self.variables.candidate_split_features,
self.variables.candidate_split_thresholds))
tree_update_op = state_ops.scatter_update(
self.variables.tree, tree_update_indices, tree_children_updates)
thresholds_update_op = state_ops.scatter_update(
self.variables.tree_thresholds, tree_update_indices,
tree_threshold_updates)
# TODO(thomaswc): Only update the epoch on the new leaves.
new_epoch_updates = epoch * array_ops.ones_like(tree_threshold_updates,
dtype=dtypes.int32)
epoch_update_op = state_ops.scatter_update(
self.variables.start_epoch, tree_update_indices,
new_epoch_updates)
# Update fertile slots.
with ops.control_dependencies([tree_update_op]):
(node_map_updates, accumulators_cleared, accumulators_allocated) = (
self.training_ops.update_fertile_slots(
finished,
non_fertile_leaves,
non_fertile_leaf_scores,
self.variables.end_of_tree,
self.variables.accumulator_sums,
self.variables.node_to_accumulator_map,
stale,
regression=self.params.regression))
# Ensure end_of_tree doesn't get updated until UpdateFertileSlots has
# used it to calculate new leaves.
gated_new_eot, = control_flow_ops.tuple([new_eot],
control_inputs=[node_map_updates])
eot_update_op = state_ops.assign(self.variables.end_of_tree, gated_new_eot)
updates = []
updates.append(eot_update_op)
updates.append(tree_update_op)
updates.append(thresholds_update_op)
updates.append(epoch_update_op)
updates.append(state_ops.scatter_update(
self.variables.node_to_accumulator_map,
array_ops.squeeze(array_ops.slice(node_map_updates, [0, 0], [1, -1]),
squeeze_dims=[0]),
array_ops.squeeze(array_ops.slice(node_map_updates, [1, 0], [1, -1]),
squeeze_dims=[0])))
cleared_and_allocated_accumulators = array_ops.concat(
0, [accumulators_cleared, accumulators_allocated])
# Calculate values to put into scatter update for candidate counts.
# Candidate split counts are always reset back to 0 for both cleared
# and allocated accumulators. This means some accumulators might be doubly
# reset to 0 if the were released and not allocated, then later allocated.
split_values = array_ops.tile(
array_ops.expand_dims(array_ops.expand_dims(
array_ops.zeros_like(cleared_and_allocated_accumulators,
dtype=dtypes.float32), 1), 2),
[1, self.params.num_splits_to_consider, self.params.num_output_columns])
updates.append(state_ops.scatter_update(
self.variables.candidate_split_sums,
cleared_and_allocated_accumulators, split_values))
if self.params.regression:
updates.append(state_ops.scatter_update(
self.variables.candidate_split_squares,
cleared_and_allocated_accumulators, split_values))
# Calculate values to put into scatter update for total counts.
total_cleared = array_ops.tile(
array_ops.expand_dims(
math_ops.neg(array_ops.ones_like(accumulators_cleared,
dtype=dtypes.float32)), 1),
[1, self.params.num_output_columns])
total_reset = array_ops.tile(
array_ops.expand_dims(
array_ops.zeros_like(accumulators_allocated,
dtype=dtypes.float32), 1),
[1, self.params.num_output_columns])
accumulator_updates = array_ops.concat(0, [total_cleared, total_reset])
updates.append(state_ops.scatter_update(
self.variables.accumulator_sums,
cleared_and_allocated_accumulators, accumulator_updates))
if self.params.regression:
updates.append(state_ops.scatter_update(
self.variables.accumulator_squares,
cleared_and_allocated_accumulators, accumulator_updates))
# Calculate values to put into scatter update for candidate splits.
split_features_updates = array_ops.tile(
array_ops.expand_dims(
math_ops.neg(array_ops.ones_like(
cleared_and_allocated_accumulators)), 1),
[1, self.params.num_splits_to_consider])
updates.append(state_ops.scatter_update(
self.variables.candidate_split_features,
cleared_and_allocated_accumulators, split_features_updates))
updates += self.finish_iteration()
return control_flow_ops.group(*updates) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/pdfviewer/viewer.py | python | pypdfProcessor.ConvertCMYK | (self, operand) | return (r, g, b) | Convert CMYK values (0 to 1.0) in operand to nearest RGB | Convert CMYK values (0 to 1.0) in operand to nearest RGB | [
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r = round((1-c)*(1-k)*255)
b = round((1-y)*(1-k)*255)
g = round((1-m)*(1-k)*255)
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/cookies.py | python | get_cookie_header | (jar, request) | return r.get_new_headers().get('Cookie') | Produce an appropriate Cookie header string to be sent with `request`, or None.
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"""
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NVIDIA/MDL-SDK | aa9642b2546ad7b6236b5627385d882c2ed83c5d | src/mdl/jit/llvm/dist/utils/gdb-scripts/prettyprinters.py | python | TwinePrinter.string_from_pretty_printer_lookup | (self, val) | return s | Lookup the default pretty-printer for val and use it.
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pp = gdb.default_visualizer(val)
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# "type(s) == gdb.LazyString".
if 'LazyString' in type(s).__name__:
s = s.value().address.string()
else:
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/pubsub/core/topicobj.py | python | Topic.isValid | (self, listener) | return self.__validator.isValid(listener) | Return True only if listener could be subscribed to this topic,
otherwise returns False. Note that method raises TopicDefnError
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yrnkrn/zapcc | c6a8aa30006d997eff0d60fd37b0e62b8aa0ea50 | bindings/python/llvm/object.py | python | Section.address | (self) | return lib.LLVMGetSectionAddress(self) | The address of this section, in long bytes. | The address of this section, in long bytes. | [
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mysql/mysql-router | cc0179f982bb9739a834eb6fd205a56224616133 | ext/gmock/scripts/generator/cpp/ast.py | python | AstBuilder.GetName | (self, seq=None) | return tokens, next_token | Returns ([tokens], next_token_info). | Returns ([tokens], next_token_info). | [
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MegEngine/MegEngine | ce9ad07a27ec909fb8db4dd67943d24ba98fb93a | imperative/python/megengine/autodiff/grad_manager.py | python | GradManager.attached_tensors | (self) | return [spec.tensor() for spec in self._attach_specs.values()] | r"""Return attached tensor list from :meth:`attach`. | r"""Return attached tensor list from :meth:`attach`. | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/rds2/layer1.py | python | RDSConnection.revoke_db_security_group_ingress | (self, db_security_group_name,
cidrip=None,
ec2_security_group_name=None,
ec2_security_group_id=None,
ec2_security_group_owner_id=None) | return self._make_request(
action='RevokeDBSecurityGroupIngress',
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path='/', params=params) | Revokes ingress from a DBSecurityGroup for previously
authorized IP ranges or EC2 or VPC Security Groups. Required
parameters for this API are one of CIDRIP, EC2SecurityGroupId
for VPC, or (EC2SecurityGroupOwnerId and either
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authorized IP ranges or EC2 or VPC Security Groups. Required
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"""
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if cidrip is not None:
params['CIDRIP'] = cidrip
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params['EC2SecurityGroupName'] = ec2_security_group_name
if ec2_security_group_id is not None:
params['EC2SecurityGroupId'] = ec2_security_group_id
if ec2_security_group_owner_id is not None:
params['EC2SecurityGroupOwnerId'] = ec2_security_group_owner_id
return self._make_request(
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/itanium_mangler.py | python | mangle_args_c | (argtys) | return ''.join([mangle_type_c(t) for t in argtys]) | Mangle sequence of C type names | Mangle sequence of C type names | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/python/ops/nn_ops.py | python | conv1d | (value, filters, stride, padding,
use_cudnn_on_gpu=None, data_format=None,
name=None) | Computes a 1-D convolution given 3-D input and filter tensors.
Given an input tensor of shape [batch, in_width, in_channels]
and a filter / kernel tensor of shape
[filter_width, in_channels, out_channels], this op reshapes
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value: A 3D `Tensor`. Must be of type `float32` or `float64`.
filters: A 3D `Tensor`. Must have the same type as `input`.
stride: An `integer`. The number of entries by which
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padding: 'SAME' or 'VALID'
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name: A name for the operation (optional).
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value = array_ops.expand_dims(value, 1)
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filters = array_ops.expand_dims(filters, 0)
result = gen_nn_ops.conv2d(value, filters, [1, 1, stride, 1], padding,
use_cudnn_on_gpu=use_cudnn_on_gpu,
data_format=data_format)
return array_ops.squeeze(result, [1]) | [
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pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | lts/deps/v8/third_party/jinja2/compiler.py | python | CodeGenerator.push_parameter_definitions | (self, frame) | Pushes all parameter targets from the given frame into a local
stack that permits tracking of yet to be assigned parameters. In
particular this enables the optimization from `visit_Name` to skip
undefined expressions for parameters in macros as macros can reference
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self._param_def_block.append(frame.symbols.dump_param_targets()) | [
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okex/V3-Open-API-SDK | c5abb0db7e2287718e0055e17e57672ce0ec7fd9 | okex-python-sdk-api/venv/Lib/site-packages/pip-19.0.3-py3.8.egg/pip/_vendor/pyparsing.py | python | ParseBaseException.__getattr__ | ( self, aname ) | supported attributes by name are:
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CRYTEK/CRYENGINE | 232227c59a220cbbd311576f0fbeba7bb53b2a8c | Code/Tools/waf-1.7.13/crywaflib/default_settings.py | python | _validate_incredibuild_registry_settings | (ctx) | Helper function to verify the correct incredibuild settings | Helper function to verify the correct incredibuild settings | [
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""" Helper function to verify the correct incredibuild settings """
if Utils.unversioned_sys_platform() != 'win32':
return # Check windows registry only
if not ctx.is_option_true('use_incredibuild'):
return # No need to check IB settings if there is no IB
allowUserInput = True
if not ctx.is_option_true('ask_for_user_input'):
allowUserInput = False
if Options.options.execsolution:
allowUserInput = False
if ctx.is_option_true('internal_dont_check_recursive_execution'):
allowUserInput = False
try:
import _winreg
IB_settings_read_only = _winreg.OpenKey(_winreg.HKEY_LOCAL_MACHINE, "Software\\Wow6432Node\\Xoreax\\Incredibuild\\Builder", 0, _winreg.KEY_READ)
except:
Logs.warn('[WARNING] Cannot open registry entry "HKEY_LOCAL_MACHINE\\Software\\Wow6432Node\\Xoreax\\Incredibuild\\Builder" for reading, please check your incredibuild installation')
return
def _check_ib_setting(setting_name, required_value, desc):
""" Helper function to read (and potentially modify a registry setting for IB """
(data, type) = (None, _winreg.REG_SZ)
try:
(data,type) = _winreg.QueryValueEx(IB_settings_read_only, setting_name)
except:
import traceback
traceback.print_exc(file=sys.stdout)
Logs.warn('[WARNING] Cannot find a registry entry for "HKEY_LOCAL_MACHINE\\Software\\Wow6432Node\\Xoreax\\Incredibuild\\Builder\\%s"' % setting_name )
# Do we have the right value?
if str(data) != required_value:
if not allowUserInput: # Dont try anything if no input is allowed
Logs.warn('[WARNING] "HKEY_LOCAL_MACHINE\\Software\\Wow6432Node\\Xoreax\\Incredibuild\\Builder\\%s" set to "%s" but should be "%s"; run WAF outside of Visual Studio to fix automatically' % (setting_name, data, required_value) )
return
try: # Try to open the registry for writing
IB_settings_writing = _winreg.OpenKey(_winreg.HKEY_LOCAL_MACHINE, "Software\\Wow6432Node\\Xoreax\\Incredibuild\\Builder", 0, _winreg.KEY_SET_VALUE | _winreg.KEY_READ)
except:
Logs.warn('[WARNING] Cannot access a registry entry "HKEY_LOCAL_MACHINE\\Software\\Wow6432Node\\Xoreax\\Incredibuild\\Builder\\%s" for writing.' % setting_name)
Logs.warn('[WARNING] Please run cry_waf.exe as an administrator or change the value to "%s" in the registry to ensure a correct operation of WAF' % required_value)
return
if data is None:
info_str = [('Should WAF create "HKEY_LOCAL_MACHINE\\Software\\Wow6432Node\\Xoreax\\Incredibuild\\Builder\\%s" with value "%s"?' % (setting_name, required_value) )]
else:
info_str = [('Should WAF change "HKEY_LOCAL_MACHINE\\Software\\Wow6432Node\\Xoreax\\Incredibuild\\Builder\\%s" from "%s" to "%s"?' % (setting_name, data, required_value) )]
info_str.append(desc)
# Get user choice
if not ctx.is_option_true('console_mode'): # gui
retVal = 'True' if ctx.gui_get_choice('\n'.join(info_str)) else 'False'
else: # console
Logs.info('\n'.join(info_str))
retVal = _get_boolean_value(ctx, 'Input', 'Yes')
if retVal == 'True' or retVal == 'Yes':
_winreg.SetValueEx(IB_settings_writing, setting_name,0, type, str(required_value))
else:
Logs.warn('[WARNING] WAF is running with "unsupported" IncrediBuild settings. Expect to encounter IncrediBuild errors during compilation.')
_check_ib_setting('MaxConcurrentPDBs', '0', '"MaxConcurrentPDBs" controls how many files can be processed in parallel (an optimization also useful for MSBuild)')
_check_ib_setting('AllowDoubleTargets', '0', '"AllowDoubleTargets" controls if remote processes can be restarted on local machine when possible\nThis option is mandatory since it causes compiler crashed with WAF') | [
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wenwei202/caffe | f54a74abaf6951d8485cbdcfa1d74a4c37839466 | scripts/cpp_lint.py | python | _CppLintState.PrintErrorCounts | (self) | Print a summary of errors by category, and the total. | Print a summary of errors by category, and the total. | [
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"""Print a summary of errors by category, and the total."""
for category, count in self.errors_by_category.iteritems():
sys.stderr.write('Category \'%s\' errors found: %d\n' %
(category, count))
sys.stderr.write('Total errors found: %d\n' % self.error_count) | [
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junhyukoh/caffe-lstm | 598d45456fa2a1b127a644f4aa38daa8fb9fc722 | scripts/cpp_lint.py | python | CheckCStyleCast | (filename, linenum, line, raw_line, cast_type, pattern,
error) | return True | Checks for a C-style cast by looking for the pattern.
Args:
filename: The name of the current file.
linenum: The number of the line to check.
line: The line of code to check.
raw_line: The raw line of code to check, with comments.
cast_type: The string for the C++ cast to recommend. This is either
reinterpret_cast, static_cast, or const_cast, depending.
pattern: The regular expression used to find C-style casts.
error: The function to call with any errors found.
Returns:
True if an error was emitted.
False otherwise. | Checks for a C-style cast by looking for the pattern. | [
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error):
"""Checks for a C-style cast by looking for the pattern.
Args:
filename: The name of the current file.
linenum: The number of the line to check.
line: The line of code to check.
raw_line: The raw line of code to check, with comments.
cast_type: The string for the C++ cast to recommend. This is either
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pattern: The regular expression used to find C-style casts.
error: The function to call with any errors found.
Returns:
True if an error was emitted.
False otherwise.
"""
match = Search(pattern, line)
if not match:
return False
# Exclude lines with sizeof, since sizeof looks like a cast.
sizeof_match = Match(r'.*sizeof\s*$', line[0:match.start(1) - 1])
if sizeof_match:
return False
# operator++(int) and operator--(int)
if (line[0:match.start(1) - 1].endswith(' operator++') or
line[0:match.start(1) - 1].endswith(' operator--')):
return False
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remainder = line[match.end(0):]
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return False
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matched_zero = Match(r'^\s=\s*(\S+)\s*;', remainder)
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# Don't warn on function pointer declarations. For this we need
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if Match(r'.*\)\s*$', line[0:match.start(0)]):
return False
# Don't warn if the parameter is named with block comments, e.g.:
# Function(int /*unused_param*/);
if '/*' in raw_line:
return False
# Passed all filters, issue warning here.
error(filename, linenum, 'readability/function', 3,
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return True
# At this point, all that should be left is actual casts.
error(filename, linenum, 'readability/casting', 4,
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | build/automationutils.py | python | dumpScreen | (utilityPath) | dumps a screenshot of the entire screen to a directory specified by
the MOZ_UPLOAD_DIR environment variable | dumps a screenshot of the entire screen to a directory specified by
the MOZ_UPLOAD_DIR environment variable | [
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"""dumps a screenshot of the entire screen to a directory specified by
the MOZ_UPLOAD_DIR environment variable"""
# Need to figure out which OS-dependent tool to use
if mozinfo.isUnix:
utility = [os.path.join(utilityPath, "screentopng")]
utilityname = "screentopng"
elif mozinfo.isMac:
utility = ['/usr/sbin/screencapture', '-C', '-x', '-t', 'png']
utilityname = "screencapture"
elif mozinfo.isWin:
utility = [os.path.join(utilityPath, "screenshot.exe")]
utilityname = "screenshot"
# Get dir where to write the screenshot file
parent_dir = os.environ.get('MOZ_UPLOAD_DIR', None)
if not parent_dir:
log.info('Failed to retrieve MOZ_UPLOAD_DIR env var')
return
# Run the capture
try:
tmpfd, imgfilename = tempfile.mkstemp(prefix='mozilla-test-fail-screenshot_', suffix='.png', dir=parent_dir)
os.close(tmpfd)
returncode = subprocess.call(utility + [imgfilename])
printstatus(returncode, utilityname)
except OSError, err:
log.info("Failed to start %s for screenshot: %s" %
utility[0], err.strerror)
return | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/plan/motionplanning.py | python | CSpaceInterface.setFeasibility | (self, pyFeas) | return _motionplanning.CSpaceInterface_setFeasibility(self, pyFeas) | Args:
pyFeas (:obj:`object`) | Args:
pyFeas (:obj:`object`) | [
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"""
Args:
pyFeas (:obj:`object`)
"""
return _motionplanning.CSpaceInterface_setFeasibility(self, pyFeas) | [
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AngoraFuzzer/Angora | 80e81c8590077bc0ac069dbd367da8ce405ff618 | llvm_mode/dfsan_rt/sanitizer_common/scripts/cpplint.py | python | CleansedLines.NumLines | (self) | return self.num_lines | Returns the number of lines represented. | Returns the number of lines represented. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_misc.py | python | Sound.IsOk | (*args, **kwargs) | return _misc_.Sound_IsOk(*args, **kwargs) | IsOk(self) -> bool | IsOk(self) -> bool | [
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"""IsOk(self) -> bool"""
return _misc_.Sound_IsOk(*args, **kwargs) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/richtext.py | python | RichTextCtrl.GetScaleX | (*args, **kwargs) | return _richtext.RichTextCtrl_GetScaleX(*args, **kwargs) | GetScaleX(self) -> double | GetScaleX(self) -> double | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/plat-mac/lib-scriptpackages/SystemEvents/Standard_Suite.py | python | Standard_Suite_Events.exists | (self, _object, _attributes={}, **_arguments) | exists: Verify if an object exists.
Required argument: the object for the command
Keyword argument _attributes: AppleEvent attribute dictionary
Returns: the reply for the command | exists: Verify if an object exists.
Required argument: the object for the command
Keyword argument _attributes: AppleEvent attribute dictionary
Returns: the reply for the command | [
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"""exists: Verify if an object exists.
Required argument: the object for the command
Keyword argument _attributes: AppleEvent attribute dictionary
Returns: the reply for the command
"""
_code = 'core'
_subcode = 'doex'
if _arguments: raise TypeError, 'No optional args expected'
_arguments['----'] = _object
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if _arguments.get('errn', 0):
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if _arguments.has_key('----'):
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htcondor/htcondor | 4829724575176d1d6c936e4693dfd78a728569b0 | src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/twitter.py | python | DirectMessage.SetRecipientId | (self, recipient_id) | Set the unique recipient id of this direct message.
Args:
recipient id: The unique recipient id of this direct message | Set the unique recipient id of this direct message. | [
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] | def SetRecipientId(self, recipient_id):
'''Set the unique recipient id of this direct message.
Args:
recipient id: The unique recipient id of this direct message
'''
self._recipient_id = recipient_id | [
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | python/configobj/validate.py | python | _is_num_param | (names, values, to_float=False) | return out_params | Return numbers from inputs or raise VdtParamError.
Lets ``None`` pass through.
Pass in keyword argument ``to_float=True`` to
use float for the conversion rather than int.
>>> _is_num_param(('', ''), (0, 1.0))
[0, 1]
>>> _is_num_param(('', ''), (0, 1.0), to_float=True)
[0.0, 1.0]
>>> _is_num_param(('a'), ('a'))
Traceback (most recent call last):
VdtParamError: passed an incorrect value "a" for parameter "a". | Return numbers from inputs or raise VdtParamError.
Lets ``None`` pass through.
Pass in keyword argument ``to_float=True`` to
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>>> _is_num_param(('', ''), (0, 1.0))
[0, 1]
>>> _is_num_param(('', ''), (0, 1.0), to_float=True)
[0.0, 1.0]
>>> _is_num_param(('a'), ('a'))
Traceback (most recent call last):
VdtParamError: passed an incorrect value "a" for parameter "a". | [
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Return numbers from inputs or raise VdtParamError.
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>>> _is_num_param(('a'), ('a'))
Traceback (most recent call last):
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"""
fun = to_float and float or int
out_params = []
for (name, val) in zip(names, values):
if val is None:
out_params.append(val)
elif isinstance(val, (int, long, float, basestring)):
try:
out_params.append(fun(val))
except ValueError, e:
raise VdtParamError(name, val)
else:
raise VdtParamError(name, val)
return out_params | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/calendar.py | python | CalendarEvent.__init__ | (self, *args, **kwargs) | __init__(self, Window win, DateTime dt, EventType type) -> CalendarEvent | __init__(self, Window win, DateTime dt, EventType type) -> CalendarEvent | [
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mickem/nscp | 79f89fdbb6da63f91bc9dedb7aea202fe938f237 | scripts/python/lib/google/protobuf/internal/python_message.py | python | _AddEnumValues | (descriptor, cls) | Sets class-level attributes for all enum fields defined in this message.
Args:
descriptor: Descriptor object for this message type.
cls: Class we're constructing for this message type. | Sets class-level attributes for all enum fields defined in this message. | [
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ArduPilot/ardupilot | 6e684b3496122b8158ac412b609d00004b7ac306 | libraries/AP_HAL_ChibiOS/hwdef/scripts/dma_resolver.py | python | sharing_allowed | (p1, p2) | return True | return true if sharing is allowed between p1 and p2 | return true if sharing is allowed between p1 and p2 | [
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if p1.endswith("_UP") and p2.endswith("_UP") and p1.startswith("TIM") and p2.startswith("TIM"):
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return True | [
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/mimetypes.py | python | MimeTypes.guess_all_extensions | (self, type, strict=True) | return extensions | Guess the extensions for a file based on its MIME type.
Return value is a list of strings giving the possible filename
extensions, including the leading dot ('.'). The extension is not
guaranteed to have been associated with any particular data stream,
but would be mapped to the MIME type `type' by guess_type().
Optional `strict' argument when false adds a bunch of commonly found,
but non-standard types. | Guess the extensions for a file based on its MIME type. | [
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] | def guess_all_extensions(self, type, strict=True):
"""Guess the extensions for a file based on its MIME type.
Return value is a list of strings giving the possible filename
extensions, including the leading dot ('.'). The extension is not
guaranteed to have been associated with any particular data stream,
but would be mapped to the MIME type `type' by guess_type().
Optional `strict' argument when false adds a bunch of commonly found,
but non-standard types.
"""
type = type.lower()
extensions = self.types_map_inv[True].get(type, [])
if not strict:
for ext in self.types_map_inv[False].get(type, []):
if ext not in extensions:
extensions.append(ext)
return extensions | [
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kushview/Element | 1cc16380caa2ab79461246ba758b9de1f46db2a5 | waflib/ConfigSet.py | python | ConfigSet.stash | (self) | Stores the object state to provide transactionality semantics::
env = ConfigSet()
env.stash()
try:
env.append_value('CFLAGS', '-O3')
call_some_method(env)
finally:
env.revert()
The history is kept in a stack, and is lost during the serialization by :py:meth:`ConfigSet.store` | Stores the object state to provide transactionality semantics:: | [
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"""
Stores the object state to provide transactionality semantics::
env = ConfigSet()
env.stash()
try:
env.append_value('CFLAGS', '-O3')
call_some_method(env)
finally:
env.revert()
The history is kept in a stack, and is lost during the serialization by :py:meth:`ConfigSet.store`
"""
orig = self.table
tbl = self.table = self.table.copy()
for x in tbl.keys():
tbl[x] = copy.deepcopy(tbl[x])
self.undo_stack = self.undo_stack + [orig] | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/re2/lib/codereview/codereview.py | python | undo | (ui, repo, clname, **opts) | return clpatch_or_undo(ui, repo, clname, opts, mode="undo") | undo the effect of a CL
Creates a new CL that undoes an earlier CL.
After creating the CL, opens the CL text for editing so that
you can add the reason for the undo to the description. | undo the effect of a CL
Creates a new CL that undoes an earlier CL.
After creating the CL, opens the CL text for editing so that
you can add the reason for the undo to the description. | [
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] | def undo(ui, repo, clname, **opts):
"""undo the effect of a CL
Creates a new CL that undoes an earlier CL.
After creating the CL, opens the CL text for editing so that
you can add the reason for the undo to the description.
"""
if repo[None].branch() != "default":
return "cannot run hg undo outside default branch"
return clpatch_or_undo(ui, repo, clname, opts, mode="undo") | [
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epiqc/ScaffCC | 66a79944ee4cd116b27bc1a69137276885461db8 | llvm/utils/lit/lit/Util.py | python | executeCommand | (command, cwd=None, env=None, input=None, timeout=0) | return out, err, exitCode | Execute command ``command`` (list of arguments or string) with.
* working directory ``cwd`` (str), use None to use the current
working directory
* environment ``env`` (dict), use None for none
* Input to the command ``input`` (str), use string to pass
no input.
* Max execution time ``timeout`` (int) seconds. Use 0 for no timeout.
Returns a tuple (out, err, exitCode) where
* ``out`` (str) is the standard output of running the command
* ``err`` (str) is the standard error of running the command
* ``exitCode`` (int) is the exitCode of running the command
If the timeout is hit an ``ExecuteCommandTimeoutException``
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"""Execute command ``command`` (list of arguments or string) with.
* working directory ``cwd`` (str), use None to use the current
working directory
* environment ``env`` (dict), use None for none
* Input to the command ``input`` (str), use string to pass
no input.
* Max execution time ``timeout`` (int) seconds. Use 0 for no timeout.
Returns a tuple (out, err, exitCode) where
* ``out`` (str) is the standard output of running the command
* ``err`` (str) is the standard error of running the command
* ``exitCode`` (int) is the exitCode of running the command
If the timeout is hit an ``ExecuteCommandTimeoutException``
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"""
if input is not None:
input = to_bytes(input)
p = subprocess.Popen(command, cwd=cwd,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
env=env, close_fds=kUseCloseFDs)
timerObject = None
# FIXME: Because of the way nested function scopes work in Python 2.x we
# need to use a reference to a mutable object rather than a plain
# bool. In Python 3 we could use the "nonlocal" keyword but we need
# to support Python 2 as well.
hitTimeOut = [False]
try:
if timeout > 0:
def killProcess():
# We may be invoking a shell so we need to kill the
# process and all its children.
hitTimeOut[0] = True
killProcessAndChildren(p.pid)
timerObject = threading.Timer(timeout, killProcess)
timerObject.start()
out, err = p.communicate(input=input)
exitCode = p.wait()
finally:
if timerObject != None:
timerObject.cancel()
# Ensure the resulting output is always of string type.
out = to_string(out)
err = to_string(err)
if hitTimeOut[0]:
raise ExecuteCommandTimeoutException(
msg='Reached timeout of {} seconds'.format(timeout),
out=out,
err=err,
exitCode=exitCode
)
# Detect Ctrl-C in subprocess.
if exitCode == -signal.SIGINT:
raise KeyboardInterrupt
return out, err, exitCode | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/py/interpreter.py | python | InterpreterAlaCarte.__init__ | (self, locals, rawin, stdin, stdout, stderr,
ps1='main prompt', ps2='continuation prompt') | Create an interactive interpreter object. | Create an interactive interpreter object. | [
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] | def __init__(self, locals, rawin, stdin, stdout, stderr,
ps1='main prompt', ps2='continuation prompt'):
"""Create an interactive interpreter object."""
Interpreter.__init__(self, locals=locals, rawin=rawin,
stdin=stdin, stdout=stdout, stderr=stderr)
sys.ps1 = ps1
sys.ps2 = ps2 | [
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opengm/opengm | decdacf4caad223b0ab5478d38a855f8767a394f | src/interfaces/python/opengm/__init__.py | python | loadGm | (f, d='gm', operator='adder') | return gm | save a graphical model to a hdf5 file:
Args:
f : filepath
g : dataset (defaut : 'gm')
operator : operator of the graphical model ('adder' / 'multiplier') | save a graphical model to a hdf5 file:
Args:
f : filepath
g : dataset (defaut : 'gm')
operator : operator of the graphical model ('adder' / 'multiplier') | [
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""" save a graphical model to a hdf5 file:
Args:
f : filepath
g : dataset (defaut : 'gm')
operator : operator of the graphical model ('adder' / 'multiplier')
"""
if(operator=='adder'):
gm=adder.GraphicalModel()
elif(operator=='multiplier'):
gm=multiplier.GraphicalModel()
else:
raise RuntimeError("unknown operator: "+ operator)
hdf5.loadGraphicalModel(gm,f,d)
return gm | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/protorpc/protorpc/util.py | python | positional | (max_positional_args) | A decorator to declare that only the first N arguments may be positional.
This decorator makes it easy to support Python 3 style keyword-only
parameters. For example, in Python 3 it is possible to write:
def fn(pos1, *, kwonly1=None, kwonly1=None):
...
All named parameters after * must be a keyword:
fn(10, 'kw1', 'kw2') # Raises exception.
fn(10, kwonly1='kw1') # Ok.
Example:
To define a function like above, do:
@positional(1)
def fn(pos1, kwonly1=None, kwonly2=None):
...
If no default value is provided to a keyword argument, it becomes a required
keyword argument:
@positional(0)
def fn(required_kw):
...
This must be called with the keyword parameter:
fn() # Raises exception.
fn(10) # Raises exception.
fn(required_kw=10) # Ok.
When defining instance or class methods always remember to account for
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class MyClass(object):
@positional(2)
def my_method(self, pos1, kwonly1=None):
...
@classmethod
@positional(2)
def my_method(cls, pos1, kwonly1=None):
...
One can omit the argument to 'positional' altogether, and then no
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default values, and no argument is given to 'positional', an error
is raised.
@positional
def fn(arg1, arg2, required_kw1=None, required_kw2=0):
...
fn(1, 3, 5) # Raises exception.
fn(1, 3) # Ok.
fn(1, 3, required_kw1=5) # Ok.
Args:
max_positional_arguments: Maximum number of positional arguments. All
parameters after the this index must be keyword only.
Returns:
A decorator that prevents using arguments after max_positional_args from
being used as positional parameters.
Raises:
TypeError if a keyword-only argument is provided as a positional parameter.
ValueError if no maximum number of arguments is provided and the function
has no arguments with default values. | A decorator to declare that only the first N arguments may be positional. | [
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"""A decorator to declare that only the first N arguments may be positional.
This decorator makes it easy to support Python 3 style keyword-only
parameters. For example, in Python 3 it is possible to write:
def fn(pos1, *, kwonly1=None, kwonly1=None):
...
All named parameters after * must be a keyword:
fn(10, 'kw1', 'kw2') # Raises exception.
fn(10, kwonly1='kw1') # Ok.
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...
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class MyClass(object):
@positional(2)
def my_method(self, pos1, kwonly1=None):
...
@classmethod
@positional(2)
def my_method(cls, pos1, kwonly1=None):
...
One can omit the argument to 'positional' altogether, and then no
arguments with default values may be passed positionally. This
would be equivalent to placing a '*' before the first argument
with a default value in Python 3. If there are no arguments with
default values, and no argument is given to 'positional', an error
is raised.
@positional
def fn(arg1, arg2, required_kw1=None, required_kw2=0):
...
fn(1, 3, 5) # Raises exception.
fn(1, 3) # Ok.
fn(1, 3, required_kw1=5) # Ok.
Args:
max_positional_arguments: Maximum number of positional arguments. All
parameters after the this index must be keyword only.
Returns:
A decorator that prevents using arguments after max_positional_args from
being used as positional parameters.
Raises:
TypeError if a keyword-only argument is provided as a positional parameter.
ValueError if no maximum number of arguments is provided and the function
has no arguments with default values.
"""
def positional_decorator(wrapped):
def positional_wrapper(*args, **kwargs):
if len(args) > max_positional_args:
plural_s = ''
if max_positional_args != 1:
plural_s = 's'
raise TypeError('%s() takes at most %d positional argument%s '
'(%d given)' % (wrapped.__name__,
max_positional_args,
plural_s, len(args)))
return wrapped(*args, **kwargs)
return positional_wrapper
if isinstance(max_positional_args, six.integer_types):
return positional_decorator
else:
args, _, _, defaults = inspect.getargspec(max_positional_args)
if defaults is None:
raise ValueError(
'Functions with no keyword arguments must specify '
'max_positional_args')
return positional(len(args) - len(defaults))(max_positional_args) | [
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Yelp/MOE | 5b5a6a2c6c3cf47320126f7f5894e2a83e347f5c | moe/optimal_learning/python/comparison.py | python | EqualityComparisonMixin._get_comparable_members | (self) | return [(field, value) for field, value in members if not(field.startswith('__') and field.endswith('__'))] | r"""Return a list of fields to use in comparing two ``EqualityComparisonMixin`` subclasses for equality.
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/idlelib/TreeWidget.py | python | listicons | (icondir=ICONDIR) | Utility to display the available icons. | Utility to display the available icons. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/wizard.py | python | WizardPage.GetBitmap | (*args, **kwargs) | return _wizard.WizardPage_GetBitmap(*args, **kwargs) | GetBitmap(self) -> Bitmap | GetBitmap(self) -> Bitmap | [
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/ros_comm/rospy/src/rospy/impl/masterslave.py | python | ROSHandler.remappings | (cls, methodName) | @internal
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D-X-Y/caffe-faster-rcnn | eb50c97ff48f3df115d0e85fe0a32b0c7e2aa4cb | scripts/cpp_lint.py | python | FileInfo.FullName | (self) | return os.path.abspath(self._filename).replace('\\', '/') | Make Windows paths like Unix. | Make Windows paths like Unix. | [
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hpi-xnor/BMXNet | ed0b201da6667887222b8e4b5f997c4f6b61943d | python/mxnet/gluon/data/dataloader.py | python | default_mp_batchify_fn | (data) | Collate data into batch. Use shared memory for stacking. | Collate data into batch. Use shared memory for stacking. | [
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strukturag/libheif | 0082fea96ee70a20c8906a0373bedec0c01777bc | scripts/cpplint.py | python | CheckHeaderFileIncluded | (filename, include_state, error) | Logs an error if a .cc file does not include its header. | Logs an error if a .cc file does not include its header. | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/pkg_resources/_vendor/appdirs.py | python | user_log_dir | (appname=None, appauthor=None, version=None, opinion=True) | return path | r"""Return full path to the user-specific log dir for this application.
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BitMEX/api-connectors | 37a3a5b806ad5d0e0fc975ab86d9ed43c3bcd812 | auto-generated/python/swagger_client/models/instrument.py | python | Instrument.open_interest | (self) | return self._open_interest | Gets the open_interest of this Instrument. # noqa: E501
:return: The open_interest of this Instrument. # noqa: E501
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/tornado/tornado-6/tornado/web.py | python | RequestHandler.settings | (self) | return self.application.settings | An alias for `self.application.settings <Application.settings>`. | An alias for `self.application.settings <Application.settings>`. | [
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bcrusco/Forward-Plus-Renderer | 1f130f1ae58882f651d94695823044f9833cfa30 | Forward-Plus/Forward-Plus/external/assimp-3.1.1/port/PyAssimp/scripts/fixed_pipeline_3d_viewer.py | python | GLRenderer.prepare_gl_buffers | (self, mesh) | Creates 3 buffer objets for each mesh,
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pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | torch/ao/quantization/fx/prepare.py | python | is_output_dtype_supported_by_backend | (
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node_name_to_target_dtype: Dict[str, Dict[str, Optional[torch.dtype]]],
dtype_config: Dict[str, torch.dtype],
) | return output_dtype is None or \
output_dtype == node_name_to_target_dtype[node.name]["output_activation_dtype"] | Check if the configured qconfig for the output
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"""
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ValveSoftware/source-sdk-2013 | 0d8dceea4310fde5706b3ce1c70609d72a38efdf | sp/src/thirdparty/protobuf-2.3.0/python/google/protobuf/reflection.py | python | _IsPresent | (item) | Given a (FieldDescriptor, value) tuple from _fields, return true if the
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apache/incubator-mxnet | f03fb23f1d103fec9541b5ae59ee06b1734a51d9 | python/mxnet/gluon/probability/distributions/normal.py | python | Normal.sample | (self, size=None) | return np.random.normal(self.loc, self.scale, size) | r"""Generate samples of `size` from the normal distribution
parameterized by `self._loc` and `self._scale`
Parameters
----------
size : Tuple, Scalar, or None
Size of samples to be generated. If size=None, the output shape
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size : Tuple, Scalar, or None
Size of samples to be generated. If size=None, the output shape
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PlatformLab/RAMCloud | b1866af19124325a6dfd8cbc267e2e3ef1f965d1 | scripts/recoverymetrics.py | python | values | (s) | return [p[1] for p in s] | Return a sequence of the second items from a sequence. | Return a sequence of the second items from a sequence. | [
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AojunZhou/Incremental-Network-Quantization | c7f6a609d5817d8424ce224209cf4c50f1e4de50 | tools/extra/resize_and_crop_images.py | python | OpenCVResizeCrop.resize_and_crop_image | (self, input_file, output_file, output_side_length = 256) | Takes an image name, resize it and crop the center square | Takes an image name, resize it and crop the center square | [
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img = cv2.imread(input_file)
height, width, depth = img.shape
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new_width = output_side_length
if height > width:
new_height = output_side_length * height / width
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height_offset = (new_height - output_side_length) / 2
width_offset = (new_width - output_side_length) / 2
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py | python | SBCommunication.IsValid | (self) | return _lldb.SBCommunication_IsValid(self) | IsValid(self) -> bool | IsValid(self) -> bool | [
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google/llvm-propeller | 45c226984fe8377ebfb2ad7713c680d652ba678d | llvm/bindings/python/llvm/common.py | python | LLVMObject.from_param | (self) | return self._as_parameter_ | ctypes function that converts this object to a function parameter. | ctypes function that converts this object to a function parameter. | [
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py | python | SBValue.GetStaticValue | (self) | return _lldb.SBValue_GetStaticValue(self) | GetStaticValue(self) -> SBValue | GetStaticValue(self) -> SBValue | [
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cvmfs/cvmfs | 4637bdb5153178eadf885c1acf37bdc5c685bf8a | cpplint.py | python | CheckRValueReference | (filename, clean_lines, linenum, nesting_state, error) | Check for rvalue references.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
nesting_state: A NestingState instance which maintains information about
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linenum: The number of the line to check.
nesting_state: A NestingState instance which maintains information about
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PX4/PX4-Autopilot | 0b9f60a0370be53d683352c63fd92db3d6586e18 | Tools/ecl_ekf/analysis/detectors.py | python | InAirDetector.log_start | (self) | return self._log_start | log start
:return: the start time of the log. | log start
:return: the start time of the log. | [
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] | def log_start(self) -> Optional[float]:
"""
log start
:return: the start time of the log.
"""
return self._log_start | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_core.py | python | Window.DragAcceptFiles | (*args, **kwargs) | return _core_.Window_DragAcceptFiles(*args, **kwargs) | DragAcceptFiles(self, bool accept)
Enables or disables eligibility for drop file events, EVT_DROP_FILES. | DragAcceptFiles(self, bool accept) | [
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] | def DragAcceptFiles(*args, **kwargs):
"""
DragAcceptFiles(self, bool accept)
Enables or disables eligibility for drop file events, EVT_DROP_FILES.
"""
return _core_.Window_DragAcceptFiles(*args, **kwargs) | [
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rdkit/rdkit | ede860ae316d12d8568daf5ee800921c3389c84e | rdkit/ML/Data/Stats.py | python | R2 | (orig, residSum) | return 1. - residSum / oVar | returns the R2 value for a set of predictions | returns the R2 value for a set of predictions | [
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""" returns the R2 value for a set of predictions """
# FIX: this just is not right
#
# A correct formulation of this (from Excel) for 2 variables is:
# r2 = [n*(Sxy) - (Sx)(Sy)]^2 / ([n*(Sx2) - (Sx)^2]*[n*(Sy2) - (Sy)^2])
#
#
vect = numpy.array(orig)
n = vect.shape[0]
if n <= 0:
return 0., 0.
oMean = sum(vect) / n
v = vect - oMean
oVar = sum(v * v)
return 1. - residSum / oVar | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_vendor/idna/intranges.py | python | intranges_contain | (int_, ranges) | return False | Determine if `int_` falls into one of the ranges in `ranges`. | Determine if `int_` falls into one of the ranges in `ranges`. | [
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] | def intranges_contain(int_, ranges):
"""Determine if `int_` falls into one of the ranges in `ranges`."""
tuple_ = _encode_range(int_, 0)
pos = bisect.bisect_left(ranges, tuple_)
# we could be immediately ahead of a tuple (start, end)
# with start < int_ <= end
if pos > 0:
left, right = _decode_range(ranges[pos-1])
if left <= int_ < right:
return True
# or we could be immediately behind a tuple (int_, end)
if pos < len(ranges):
left, _ = _decode_range(ranges[pos])
if left == int_:
return True
return False | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/ultimatelistctrl.py | python | UltimateListMainWindow.GetFirstGradientColour | (self) | return self._firstcolour | Returns the first gradient colour for gradient-style selections. | Returns the first gradient colour for gradient-style selections. | [
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] | def GetFirstGradientColour(self):
""" Returns the first gradient colour for gradient-style selections. """
return self._firstcolour | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | NewEventType | (*args) | return _core_.NewEventType(*args) | NewEventType() -> EventType | NewEventType() -> EventType | [
"NewEventType",
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"-",
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] | def NewEventType(*args):
"""NewEventType() -> EventType"""
return _core_.NewEventType(*args) | [
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openthread/openthread | 9fcdbed9c526c70f1556d1ed84099c1535c7cd32 | tools/harness-thci/OpenThread_WpanCtl.py | python | OpenThread_WpanCtl.getGlobal | (self) | return globalAddrs | get global unicast IPv6 address set
if configuring multiple entries | get global unicast IPv6 address set
if configuring multiple entries | [
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"global",
"unicast",
"IPv6",
"address",
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] | def getGlobal(self):
"""get global unicast IPv6 address set
if configuring multiple entries
"""
print('%s call getGlobal' % self.port)
globalAddrs = []
mleid = self.__stripValue(self.__sendCommand(self.wpan_cmd_prefix + 'getprop -v IPv6:MeshLocalAddress')[0])
mleid = ModuleHelper.GetFullIpv6Address(mleid).lower()
addrs = self.__sendCommand(self.wpan_cmd_prefix + 'getprop -v IPv6:AllAddresses')
# find rloc address firstly as a reference for current mesh local prefix as for some TCs,
# mesh local prefix may be updated through pending dataset management.
for ip6AddrItem in addrs:
if re.match(r'\[|\]', ip6AddrItem):
continue
if re.match(self.prompt, ip6AddrItem, re.M | re.I):
break
ip6AddrItem = ip6AddrItem.strip()
ip6Addr = self.__stripValue(ip6AddrItem).split(' ')[0]
fullIp = ModuleHelper.GetFullIpv6Address(ip6Addr).lower()
print('fullip %s' % fullIp)
if fullIp.startswith('fe80'):
continue
if fullIp.startswith(mleid[0:19]):
continue
print('global')
globalAddrs.append(fullIp)
return globalAddrs | [
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miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/contrib/learn/python/learn/graph_actions.py | python | infer | (restore_checkpoint_path, output_dict, feed_dict=None) | return run_feeds(output_dict=output_dict,
feed_dicts=[feed_dict] if feed_dict is not None else [None],
restore_checkpoint_path=restore_checkpoint_path)[0] | Restore graph from `restore_checkpoint_path` and run `output_dict` tensors.
If `restore_checkpoint_path` is supplied, restore from checkpoint. Otherwise,
init all variables.
Args:
restore_checkpoint_path: A string containing the path to a checkpoint to
restore.
output_dict: A `dict` mapping string names to `Tensor` objects to run.
Tensors must all be from the same graph.
feed_dict: `dict` object mapping `Tensor` objects to input values to feed.
Returns:
Dict of values read from `output_dict` tensors. Keys are the same as
`output_dict`, values are the results read from the corresponding `Tensor`
in `output_dict`.
Raises:
ValueError: if `output_dict` or `feed_dicts` is None or empty. | Restore graph from `restore_checkpoint_path` and run `output_dict` tensors. | [
"Restore",
"graph",
"from",
"restore_checkpoint_path",
"and",
"run",
"output_dict",
"tensors",
"."
] | def infer(restore_checkpoint_path, output_dict, feed_dict=None):
"""Restore graph from `restore_checkpoint_path` and run `output_dict` tensors.
If `restore_checkpoint_path` is supplied, restore from checkpoint. Otherwise,
init all variables.
Args:
restore_checkpoint_path: A string containing the path to a checkpoint to
restore.
output_dict: A `dict` mapping string names to `Tensor` objects to run.
Tensors must all be from the same graph.
feed_dict: `dict` object mapping `Tensor` objects to input values to feed.
Returns:
Dict of values read from `output_dict` tensors. Keys are the same as
`output_dict`, values are the results read from the corresponding `Tensor`
in `output_dict`.
Raises:
ValueError: if `output_dict` or `feed_dicts` is None or empty.
"""
return run_feeds(output_dict=output_dict,
feed_dicts=[feed_dict] if feed_dict is not None else [None],
restore_checkpoint_path=restore_checkpoint_path)[0] | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/setuptools/py3/setuptools/extension.py | python | _have_cython | () | return False | Return True if Cython can be imported. | Return True if Cython can be imported. | [
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"Cython",
"can",
"be",
"imported",
"."
] | def _have_cython():
"""
Return True if Cython can be imported.
"""
cython_impl = 'Cython.Distutils.build_ext'
try:
# from (cython_impl) import build_ext
__import__(cython_impl, fromlist=['build_ext']).build_ext
return True
except Exception:
pass
return False | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/idlelib/aboutDialog.py | python | AboutDialog.__init__ | (self, parent, title, _htest=False) | _htest - bool, change box location when running htest | _htest - bool, change box location when running htest | [
"_htest",
"-",
"bool",
"change",
"box",
"location",
"when",
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] | def __init__(self, parent, title, _htest=False):
"""
_htest - bool, change box location when running htest
"""
Toplevel.__init__(self, parent)
self.configure(borderwidth=5)
# place dialog below parent if running htest
self.geometry("+%d+%d" % (
parent.winfo_rootx()+30,
parent.winfo_rooty()+(30 if not _htest else 100)))
self.bg = "#707070"
self.fg = "#ffffff"
self.CreateWidgets()
self.resizable(height=FALSE, width=FALSE)
self.title(title)
self.transient(parent)
self.grab_set()
self.protocol("WM_DELETE_WINDOW", self.Ok)
self.parent = parent
self.buttonOk.focus_set()
self.bind('<Return>',self.Ok) #dismiss dialog
self.bind('<Escape>',self.Ok) #dismiss dialog
self.wait_window() | [
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BitMEX/api-connectors | 37a3a5b806ad5d0e0fc975ab86d9ed43c3bcd812 | auto-generated/python/swagger_client/models/margin.py | python | Margin.amount | (self) | return self._amount | Gets the amount of this Margin. # noqa: E501
:return: The amount of this Margin. # noqa: E501
:rtype: float | Gets the amount of this Margin. # noqa: E501 | [
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"the",
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] | def amount(self):
"""Gets the amount of this Margin. # noqa: E501
:return: The amount of this Margin. # noqa: E501
:rtype: float
"""
return self._amount | [
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protocolbuffers/protobuf | b5ab0b7a18b7336c60130f4ddb2d97c51792f896 | python/mox.py | python | Mox.ResetAll | (self) | Call reset on all mock objects. This does not unset stubs. | Call reset on all mock objects. This does not unset stubs. | [
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for mock_obj in self._mock_objects:
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/grid.py | python | GridCellEditor.Show | (*args, **kwargs) | return _grid.GridCellEditor_Show(*args, **kwargs) | Show(self, bool show, GridCellAttr attr=None) | Show(self, bool show, GridCellAttr attr=None) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/email/headerregistry.py | python | Address.addr_spec | (self) | return lp | The addr_spec (username@domain) portion of the address, quoted
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libornovax/master_thesis_code | 6eca474ed3cae673afde010caef338cf7349f839 | scripts/data/kitti2pgp.py | python | read_camera_matrix | (line) | return P | Reads a camera matrix P (3x4) stored in the row-major scheme.
Input:
line: Row-major stored matrix separated by spaces, first element is the matrix name
Returns:
camera matrix P 4x4 | Reads a camera matrix P (3x4) stored in the row-major scheme. | [
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"""
Reads a camera matrix P (3x4) stored in the row-major scheme.
Input:
line: Row-major stored matrix separated by spaces, first element is the matrix name
Returns:
camera matrix P 4x4
"""
data = line.split(' ')
if data[0] != 'P2:':
print('ERROR: We need left camera matrix (P2)!')
exit(1)
P = np.asmatrix([[float(data[1]), float(data[2]), float(data[3]), float(data[4])],
[float(data[5]), float(data[6]), float(data[7]), float(data[8])],
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/dataview.py | python | DataViewListCtrl.PrependColumn | (*args, **kwargs) | return _dataview.DataViewListCtrl_PrependColumn(*args, **kwargs) | PrependColumn(self, DataViewColumn column, String varianttype="string") -> bool | PrependColumn(self, DataViewColumn column, String varianttype="string") -> bool | [
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netket/netket | 0d534e54ecbf25b677ea72af6b85947979420652 | netket/operator/_abstract_operator.py | python | AbstractOperator.hilbert | (self) | return self._hilbert | r"""The hilbert space associated to this operator. | r"""The hilbert space associated to this operator. | [
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/boost_1_66_0/tools/build/src/build/property.py | python | PropertyMap.find | (self, properties) | return self.find_replace (properties) | Return the value associated with properties
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assert is_iterable_typed(properties, basestring)
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pip/_vendor/distlib/_backport/tarfile.py | python | TarFile.addfile | (self, tarinfo, fileobj=None) | Add the TarInfo object `tarinfo' to the archive. If `fileobj' is
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You can create TarInfo objects using gettarinfo().
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You can create TarInfo objects using gettarinfo().
On Windows platforms, `fileobj' should always be opened with mode
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eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/contributed/sumopy/coremodules/demand/turnflows.py | python | Turnflows.estimate_entered | (self) | return ids_edge, entered_vec | Estimates the entered number of vehicles for each edge
generated by turnflow definitions. Bases are the only the
turnflows, not the generated flows (which are not entering an edge).
returns ids_edge and entered_vec | Estimates the entered number of vehicles for each edge
generated by turnflow definitions. Bases are the only the
turnflows, not the generated flows (which are not entering an edge). | [
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"""
Estimates the entered number of vehicles for each edge
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returns ids_edge and entered_vec
"""
counter = np.zeros(np.max(self.get_edges().get_ids())+1, int)
for id_inter in self.get_ids():
self.turnflowmodes[id_inter].count_entered(counter)
ids_edge = np.flatnonzero(counter)
entered_vec = counter[ids_edge].copy()
return ids_edge, entered_vec | [
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NVIDIAGameWorks/kaolin | e5148d05e9c1e2ce92a07881ce3593b1c5c3f166 | kaolin/metrics/render.py | python | mask_iou | (lhs_mask, rhs_mask) | return mask_loss | r"""Compute the Intersection over Union of two segmentation masks.
Args:
lhs_mask (torch.FloatTensor):
A segmentation mask, of shape
:math:`(\text{batch_size}, \text{height}, \text{width})`.
rhs_mask (torch.FloatTensor):
A segmentation mask, of shape
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r"""Compute the Intersection over Union of two segmentation masks.
Args:
lhs_mask (torch.FloatTensor):
A segmentation mask, of shape
:math:`(\text{batch_size}, \text{height}, \text{width})`.
rhs_mask (torch.FloatTensor):
A segmentation mask, of shape
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Returns:
(torch.FloatTensor): The IoU loss, as a torch scalar.
"""
batch_size, height, width = lhs_mask.shape
assert rhs_mask.shape == lhs_mask.shape
sil_mul = lhs_mask * rhs_mask
sil_add = lhs_mask + rhs_mask
iou_up = torch.sum(sil_mul.reshape(batch_size, -1), dim=1)
iou_down = torch.sum((sil_add - sil_mul).reshape(batch_size, -1), dim=1)
iou_neg = iou_up / (iou_down + 1e-10)
mask_loss = 1.0 - torch.mean(iou_neg)
return mask_loss | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/aui.py | python | AuiToolBarItem.SetId | (*args, **kwargs) | return _aui.AuiToolBarItem_SetId(*args, **kwargs) | SetId(self, int newId) | SetId(self, int newId) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/turtle.py | python | TurtleScreen.clear | (self) | Delete all drawings and all turtles from the TurtleScreen.
Reset empty TurtleScreen to its initial state: white background,
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No argument.
Example (for a TurtleScreen instance named screen):
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No argument.
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self._delayvalue = _CFG["delay"]
self._colormode = _CFG["colormode"]
self._delete("all")
self._bgpic = self._createimage("")
self._bgpicname = "nopic"
self._tracing = 1
self._updatecounter = 0
self._turtles = []
self.bgcolor("white")
for btn in 1, 2, 3:
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_core.py | python | BookCtrlBase.GetSelection | (*args, **kwargs) | return _core_.BookCtrlBase_GetSelection(*args, **kwargs) | GetSelection(self) -> int | GetSelection(self) -> int | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/pydoc.py | python | describe | (thing) | return type(thing).__name__ | Produce a short description of the given thing. | Produce a short description of the given thing. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/ed_i18n.py | python | LangListCombo.__init__ | (self, parent, id_, default=None) | Creates a combobox with a list of all translations for the
editor as well as displaying the countries flag next to the item
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | python/psutil/psutil/_psbsd.py | python | Process.get_open_files | (self) | Return files opened by process as a list of namedtuples. | Return files opened by process as a list of namedtuples. | [
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"""Return files opened by process as a list of namedtuples."""
# XXX - C implementation available on FreeBSD >= 8 only
# else fallback on lsof parser
if hasattr(_psutil_bsd, "get_process_open_files"):
rawlist = _psutil_bsd.get_process_open_files(self.pid)
return [nt_openfile(path, fd) for path, fd in rawlist]
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lsof = _psposix.LsofParser(self.pid, self._process_name)
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SGL-UT/GPSTk | 2340ec1cbdbd0b80a204920127798697bc616b30 | swig/doxy2swig.py | python | Doxy2SWIG.generate | (self) | Parses the file set in the initialization. The resulting
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openvinotoolkit/openvino | dedcbeafa8b84cccdc55ca64b8da516682b381c7 | tools/mo/openvino/tools/mo/utils/runtime_info.py | python | RTInfoElement.get_name | (self) | Get name of RTInfoElement. | Get name of RTInfoElement. | [
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intel/llvm | e6d0547e9d99b5a56430c4749f6c7e328bf221ab | lldb/examples/python/in_call_stack.py | python | in_call_stack | (frame, bp_loc, arg_dict, _) | return False | Only break if the given name is in the current call stack. | Only break if the given name is in the current call stack. | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/io/formats/latex.py | python | RowStringConverter.index_levels | (self) | return self.frame.index.nlevels | Integer number of levels in index. | Integer number of levels in index. | [
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qgis/QGIS | 15a77662d4bb712184f6aa60d0bd663010a76a75 | python/plugins/MetaSearch/util.py | python | normalize_text | (text) | return text.replace('\n', '') | tidy up string | tidy up string | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/weakref.py | python | finalize.__call__ | (self, _=None) | If alive then mark as dead and return func(*args, **kwargs);
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/node-10.15.3/tools/jinja2/runtime.py | python | BlockReference.super | (self) | return BlockReference(self.name, self._context, self._stack,
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swift/swift | 12d031cf8177fdec0137f9aa7e2912fa23c4416b | 3rdParty/SCons/scons-3.0.1/engine/SCons/Tool/MSCommon/common.py | python | is_win64 | () | return _is_win64 | Return true if running on windows 64 bits.
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Works whether python itself runs in 64 bits or 32 bits."""
# Unfortunately, python does not provide a useful way to determine
# if the underlying Windows OS is 32-bit or 64-bit. Worse, whether
# the Python itself is 32-bit or 64-bit affects what it returns,
# so nothing in sys.* or os.* help.
# Apparently the best solution is to use env vars that Windows
# sets. If PROCESSOR_ARCHITECTURE is not x86, then the python
# process is running in 64 bit mode (on a 64-bit OS, 64-bit
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# If this python is 32-bit but the OS is 64, Windows will set
# ProgramW6432 and PROCESSOR_ARCHITEW6432 to non-null.
# (Checking for HKLM\Software\Wow6432Node in the registry doesn't
# work, because some 32-bit installers create it.)
global _is_win64
if _is_win64 is None:
# I structured these tests to make it easy to add new ones or
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if os.environ.get('PROCESSOR_ARCHITEW6432'):
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_is_win64 = True
return _is_win64 | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/framework/convert_to_constants.py | python | convert_variables_to_constants_from_session_graph | (
session,
graph_def,
output_node_names,
variable_names_allowlist=None,
variable_names_denylist=None) | return graph_def | Replaces all the variables in a graph with constants of the same values.
This function works similarly to convert_variables_to_constants_v2, but it
retrieves the constant values from a Session instead of from a
ConcreteFunction. This is useful when converting graphs generated from
TensorFlow V1, where ConcreteFunctions are not available. This also differs
from graph_util.convert_variables_to_constants in that it supports resource
variables when V2 control flow constructions are present.
Args:
session: Active TensorFlow session containing the variables.
graph_def: A GraphDef to convert.
output_node_names: List of name strings for the result nodes of the graph.
variable_names_allowlist: The set of variable names to convert (by default,
all variables are converted).
variable_names_denylist: The set of variable names to omit converting to
constants.
Returns:
An optimized GraphDef. | Replaces all the variables in a graph with constants of the same values. | [
"Replaces",
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] | def convert_variables_to_constants_from_session_graph(
session,
graph_def,
output_node_names,
variable_names_allowlist=None,
variable_names_denylist=None):
"""Replaces all the variables in a graph with constants of the same values.
This function works similarly to convert_variables_to_constants_v2, but it
retrieves the constant values from a Session instead of from a
ConcreteFunction. This is useful when converting graphs generated from
TensorFlow V1, where ConcreteFunctions are not available. This also differs
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variables when V2 control flow constructions are present.
Args:
session: Active TensorFlow session containing the variables.
graph_def: A GraphDef to convert.
output_node_names: List of name strings for the result nodes of the graph.
variable_names_allowlist: The set of variable names to convert (by default,
all variables are converted).
variable_names_denylist: The set of variable names to omit converting to
constants.
Returns:
An optimized GraphDef.
"""
# TODO(b/176982859): Find a more satisfying way to update shape information
# than clearing it, or migrate users to a workflow that does not require
# freezing.
for function in graph_def.library.function:
if "_input_shapes" in function.attr:
for input_arg, shape_attribute in zip(
function.signature.input_arg,
function.attr["_input_shapes"].list.shape):
if dtypes.as_dtype(input_arg.type) == dtypes.resource:
shape_attribute.unknown_rank = True
graph_def, _ = _replace_variables_by_constants(
converter_data=_SessionConverterData(
session=session,
graph_def=graph_def,
output_node_names=output_node_names,
variable_names_allowlist=variable_names_allowlist,
variable_names_denylist=variable_names_denylist))
return graph_def | [
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nileshkulkarni/csm | 0e6e0e7d4f725fd36f2414c0be4b9d83197aa1fc | csm/nnutils/train_utils.py | python | Trainer.define_criterion | (self) | Should be implemented by the child class. | Should be implemented by the child class. | [
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] | def define_criterion(self):
'''Should be implemented by the child class.'''
raise NotImplementedError | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/hmac.py | python | HMAC.digest | (self) | return h.digest() | Return the hash value of this hashing object.
This returns a string containing 8-bit data. The object is
not altered in any way by this function; you can continue
updating the object after calling this function. | Return the hash value of this hashing object. | [
"Return",
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] | def digest(self):
"""Return the hash value of this hashing object.
This returns a string containing 8-bit data. The object is
not altered in any way by this function; you can continue
updating the object after calling this function.
"""
h = self._current()
return h.digest() | [
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apple/swift-lldb | d74be846ef3e62de946df343e8c234bde93a8912 | scripts/Python/static-binding/lldb.py | python | SBDebugger.RunCommandInterpreter | (self, auto_handle_events, spawn_thread, options, num_errors, quit_requested, stopped_for_crash) | return _lldb.SBDebugger_RunCommandInterpreter(self, auto_handle_events, spawn_thread, options, num_errors, quit_requested, stopped_for_crash) | RunCommandInterpreter(SBDebugger self, bool auto_handle_events, bool spawn_thread, SBCommandInterpreterRunOptions options, int & num_errors, bool & quit_requested, bool & stopped_for_crash)
Launch a command interpreter session. Commands are read from standard input or
from the input handle specified for the debugger object. Output/errors are
similarly redirected to standard output/error or the configured handles.
@param[in] auto_handle_events If true, automatically handle resulting events.
@param[in] spawn_thread If true, start a new thread for IO handling.
@param[in] options Parameter collection of type SBCommandInterpreterRunOptions.
@param[in] num_errors Initial error counter.
@param[in] quit_requested Initial quit request flag.
@param[in] stopped_for_crash Initial crash flag.
@return
A tuple with the number of errors encountered by the interpreter, a boolean
indicating whether quitting the interpreter was requested and another boolean
set to True in case of a crash.
Example:
# Start an interactive lldb session from a script (with a valid debugger object
# created beforehand):
n_errors, quit_requested, has_crashed = debugger.RunCommandInterpreter(True,
False, lldb.SBCommandInterpreterRunOptions(), 0, False, False) | RunCommandInterpreter(SBDebugger self, bool auto_handle_events, bool spawn_thread, SBCommandInterpreterRunOptions options, int & num_errors, bool & quit_requested, bool & stopped_for_crash) | [
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"""
RunCommandInterpreter(SBDebugger self, bool auto_handle_events, bool spawn_thread, SBCommandInterpreterRunOptions options, int & num_errors, bool & quit_requested, bool & stopped_for_crash)
Launch a command interpreter session. Commands are read from standard input or
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similarly redirected to standard output/error or the configured handles.
@param[in] auto_handle_events If true, automatically handle resulting events.
@param[in] spawn_thread If true, start a new thread for IO handling.
@param[in] options Parameter collection of type SBCommandInterpreterRunOptions.
@param[in] num_errors Initial error counter.
@param[in] quit_requested Initial quit request flag.
@param[in] stopped_for_crash Initial crash flag.
@return
A tuple with the number of errors encountered by the interpreter, a boolean
indicating whether quitting the interpreter was requested and another boolean
set to True in case of a crash.
Example:
# Start an interactive lldb session from a script (with a valid debugger object
# created beforehand):
n_errors, quit_requested, has_crashed = debugger.RunCommandInterpreter(True,
False, lldb.SBCommandInterpreterRunOptions(), 0, False, False)
"""
return _lldb.SBDebugger_RunCommandInterpreter(self, auto_handle_events, spawn_thread, options, num_errors, quit_requested, stopped_for_crash) | [
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | src/external/coremltools_wrap/coremltools/coremltools/converters/mil/frontend/tensorflow2/load.py | python | TF2Loader._graph_def_from_model | (self, outputs=None) | Overwrites TFLoader._graph_def_from_model() | Overwrites TFLoader._graph_def_from_model() | [
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] | def _graph_def_from_model(self, outputs=None):
"""Overwrites TFLoader._graph_def_from_model()"""
msg = (
"Expected model format: [SavedModel | [concrete_function] | "
"tf.keras.Model | .h5], got {}"
)
if (
isinstance(self.model, list)
or isinstance(self.model, _tf.keras.Model)
or isinstance(self.model, _string_types)
):
cfs = []
if isinstance(self.model, list):
cfs = self.model
if isinstance(self.model, _tf.keras.Model):
cfs = self._concrete_fn_from_tf_keras_or_h5(self.model)
elif isinstance(self.model, _string_types):
if not _os_path.exists(self.model):
raise ValueError(
'Input model "{}" does not exist'.format(self.model)
)
elif _os_path.isfile(self.model) and self.model.endswith(".h5"):
cfs = self._concrete_fn_from_tf_keras_or_h5(self.model)
elif _os_path.isdir(self.model):
saved_model = _tf.saved_model.load(self.model)
sv = saved_model.signatures.values()
cfs = sv if isinstance(sv, list) else list(sv)
else:
raise NotImplementedError(msg.format(self.model))
graph_def = self._graph_def_from_concrete_fn(cfs)
return self.extract_sub_graph(graph_def, outputs)
else:
raise NotImplementedError(msg.format(self.model)) | [
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