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OpenCageData/python-opencage-geocoder | opencage/geocoder.py | OpenCageGeocode.geocode | def geocode(self, query, **kwargs):
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Given a string to search for, return the results from OpenCage's Geocoder.
:param string query: String to search for
:returns: Dict results
:raises InvalidInputError: if the query string is not a unicode string
:raises RateLimitEx... | python | def geocode(self, query, **kwargs):
"""
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OpenCageData/python-opencage-geocoder | opencage/geocoder.py | OpenCageGeocode.reverse_geocode | def reverse_geocode(self, lat, lng, **kwargs):
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zillow/ctds | src/ctds/pool/__init__.py | ConnectionPool.acquire | def acquire(self):
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This will return an existing connection, if one is available in the
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.. warning:: If the pool was created with `maxsize` and `block=True`,
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'''
Get a new connection from the pool.
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zillow/ctds | src/ctds/pool/__init__.py | ConnectionPool.release | def release(self, connection):
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.. note:: This must be called once for every successful call to
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'''
Return a connection back to the pool.
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zillow/ctds | src/ctds/pool/__init__.py | ConnectionPool.finalize | def finalize(self):
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sphinx-contrib/openapi | sphinxcontrib/openapi/openapi30.py | _dict_merge | def _dict_merge(dct, merge_dct):
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Convert a Schema Object to a Python object.
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"""
Convert a Schema Object to a Python object.
Args:
schema: An ``OrderedDict`` representing the schema object.
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sphinx-contrib/openapi | sphinxcontrib/openapi/openapi30.py | _example | def _example(media_type_objects, method=None, endpoint=None, status=None,
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Format examples in `Media Type Object` openapi v3 to HTTP request or
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Format examples in `Media Type Object` openapi v3 to HTTP request or
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sphinx-contrib/openapi | sphinxcontrib/openapi/utils.py | _resolve_refs | def _resolve_refs(uri, spec):
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rossmann-engineering/EasyModbusTCP.PY | easymodbus/modbusClient.py | convert_double_to_two_registers | def convert_double_to_two_registers(doubleValue):
"""
Convert 32 Bit Value to two 16 Bit Value to send as Modbus Registers
doubleValue: Value to be converted
return: 16 Bit Register values int[]
"""
myList = list()
myList.append(int(doubleValue & 0x0000FFFF)) #Append Least Signific... | python | def convert_double_to_two_registers(doubleValue):
"""
Convert 32 Bit Value to two 16 Bit Value to send as Modbus Registers
doubleValue: Value to be converted
return: 16 Bit Register values int[]
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rossmann-engineering/EasyModbusTCP.PY | easymodbus/modbusClient.py | convert_float_to_two_registers | def convert_float_to_two_registers(floatValue):
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Convert 32 Bit real Value to two 16 Bit Value to send as Modbus Registers
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rossmann-engineering/EasyModbusTCP.PY | easymodbus/modbusClient.py | convert_registers_to_float | def convert_registers_to_float(registers):
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registers: 16 Bit Registers
return: 32 bit value real
"""
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b [0] = registers[0] & 0xff
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rossmann-engineering/EasyModbusTCP.PY | easymodbus/modbusClient.py | ModbusClient.connect | def connect(self):
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Closes Serial port, or TCP-Socket connection
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rossmann-engineering/EasyModbusTCP.PY | easymodbus/modbusClient.py | ModbusClient.read_discreteinputs | def read_discreteinputs(self, starting_address, quantity):
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starting_address: First discrete input to be read
quantity: Numer of discrete Inputs to be read
returns: Boolean Array [0..quantity-1] which contains the discr... | python | def read_discreteinputs(self, starting_address, quantity):
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rossmann-engineering/EasyModbusTCP.PY | easymodbus/modbusClient.py | ModbusClient.write_single_coil | def write_single_coil(self, starting_address, value):
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Write single Coil to Master device (Function code 5)
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value: Coil Value to be written
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crunchyroll/ef-open | efopen/ef_service_registry.py | EFServiceRegistry.services | def services(self, service_group=None):
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crunchyroll/ef-open | efopen/ef_service_registry.py | EFServiceRegistry.valid_envs | def valid_envs(self, service_name):
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service_name: the name of the service in the service registry
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a list of strings - all the valid environments for 'service'
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penguinmenac3/starttf | starttf/estimators/tf_estimator.py | easy_train_and_evaluate | def easy_train_and_evaluate(hyper_params, Model=None, create_loss=None,
training_data=None, validation_data=None,
inline_plotting=False, session_config=None, log_suffix=None,
continue_training=False, continue_with_specific_checkpointpa... | python | def easy_train_and_evaluate(hyper_params, Model=None, create_loss=None,
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inline_plotting=False, session_config=None, log_suffix=None,
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penguinmenac3/starttf | starttf/estimators/tf_estimator.py | create_prediction_estimator | def create_prediction_estimator(hyper_params, model, checkpoint_path=None):
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:param model: The keras model.
:param checkpoint_path: (Optional) Path to the specific checkpoint to use.
:return:
"""
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"""
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:param model: The keras model.
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crunchyroll/ef-open | efopen/ef_plugin.py | ef_plugin | def ef_plugin(service_name):
"""
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Args:
service_name (str): The name of the service being extended.
Example:
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class NewRelicPlugin(object):
def run(self... | python | def ef_plugin(service_name):
"""
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service_name (str): The name of the service being extended.
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crunchyroll/ef-open | efopen/ef_plugin.py | run_plugins | def run_plugins(context_obj, boto3_clients):
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"""
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boto3_clients (dict): Dictionary of boto3 clients created by ef_utils.create_aws_clients()
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penguinmenac3/starttf | starttf/estimators/keras_trainer.py | easy_train_and_evaluate | def easy_train_and_evaluate(hyper_params, Model=None, define_loss_fn=None,
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"""
... | python | def easy_train_and_evaluate(hyper_params, Model=None, define_loss_fn=None,
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penguinmenac3/starttf | starttf/utils/image_manipulation.py | rotate_img_and_crop | def rotate_img_and_crop(img, angle):
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crunchyroll/ef-open | efopen/ef_cf_diff.py | diff_string_templates | def diff_string_templates(string_a, string_b):
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crunchyroll/ef-open | efopen/ef_cf_diff.py | diff_sevice_by_text | def diff_sevice_by_text(service_name, service, environment, cf_client, repo_root):
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"""
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global ret_code
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crunchyroll/ef-open | efopen/ef_cf_diff.py | diff_sevice_by_changeset | def diff_sevice_by_changeset(service_name, service, environment, cf_client, repo_root):
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crunchyroll/ef-open | efopen/ef_cf_diff.py | get_cloudformation_client | def get_cloudformation_client(service_name, environment_name):
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region = service_registry.service_region(service_name)
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profile = get_... | python | def get_cloudformation_client(service_name, environment_name):
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crunchyroll/ef-open | efopen/ef_cf_diff.py | evaluate_service_changes | def evaluate_service_changes(services, envs, repo_root, func):
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crunchyroll/ef-open | efopen/ef_cf_diff.py | get_matching_service_template_file | def get_matching_service_template_file(service_name, template_files):
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crunchyroll/ef-open | efopen/ef_cf_diff.py | get_dict_registry_services | def get_dict_registry_services(registry, template_files, warn_missing_files=True):
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crunchyroll/ef-open | efopen/ef_cf_diff.py | scan_dir_for_template_files | def scan_dir_for_template_files(search_dir):
"""
Return a map of "likely service/template name" to "template file".
This includes all the template files in fixtures and in services.
"""
template_files = {}
cf_dir = os.path.join(search_dir, 'cloudformation')
for type in os.listdir(cf_dir):
... | python | def scan_dir_for_template_files(search_dir):
"""
Return a map of "likely service/template name" to "template file".
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template_files = {}
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crunchyroll/ef-open | efopen/ef_password.py | generate_secret | def generate_secret(length=32):
"""
Generate a random secret consisting of mixed-case letters and numbers
Args:
length (int): Length of the generated password
Returns:
a randomly generated secret string
Raises:
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"""
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random_bytes = os.... | python | def generate_secret(length=32):
"""
Generate a random secret consisting of mixed-case letters and numbers
Args:
length (int): Length of the generated password
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a randomly generated secret string
Raises:
None
"""
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crunchyroll/ef-open | efopen/ef_password.py | generate_secret_file | def generate_secret_file(file_path, pattern, service, environment, clients):
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crunchyroll/ef-open | efopen/ef_password.py | handle_args_and_set_context | def handle_args_and_set_context(args):
"""
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a populated EFPWContext object
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penguinmenac3/starttf | starttf/layers/tile_2d.py | tile_2d | def tile_2d(input, k_x, k_y, name, reorder_required=True):
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:param input: Your input tensor.
:param k_x: The tiling factor in x direction.
:param k_y: The tiling factor in y direction.
:param name: The name of the layer.
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"""
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penguinmenac3/starttf | starttf/layers/tile_2d.py | inverse_tile_2d | def inverse_tile_2d(input, k_x, k_y, name):
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An inverse to the tiling layer can be of great use, since you can keep the resolution of your output low,
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penguinmenac3/starttf | starttf/layers/tile_2d.py | feature_passthrough | def feature_passthrough(early_feat, late_feat, filters, name, kernel_size=(1, 1)):
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A feature passthrough layer inspired by yolo9000 and the inverse tiling layer.
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penguinmenac3/starttf | starttf/layers/tile_2d.py | upsampling_feature_passthrough | def upsampling_feature_passthrough(early_feat, late_feat, filters, name, kernel_size=(1, 1)):
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crunchyroll/ef-open | efopen/ef_site_config.py | EFSiteConfig.load | def load(self):
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try:
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except (IOError, yaml.parser.ParserError) as error:
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sys.exit(1) | python | def load(self):
"""Loads the config"""
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penguinmenac3/starttf | starttf/losses/loss_processors.py | interpolate_loss | def interpolate_loss(labels, loss1, loss2, interpolation_values):
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penguinmenac3/starttf | starttf/losses/loss_processors.py | alpha_balance_loss | def alpha_balance_loss(labels, loss, alpha_weights):
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penguinmenac3/starttf | starttf/losses/loss_processors.py | batch_alpha_balance_loss | def batch_alpha_balance_loss(labels, loss):
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penguinmenac3/starttf | starttf/losses/loss_processors.py | mask_loss | def mask_loss(input_tensor, binary_tensor):
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penguinmenac3/starttf | starttf/losses/loss_processors.py | mean_on_masked | def mean_on_masked(loss, mask, epsilon=1e-8, axis=None):
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penguinmenac3/starttf | starttf/losses/loss_processors.py | mask_and_mean_loss | def mask_and_mean_loss(input_tensor, binary_tensor, axis=None):
"""
Mask a loss by using a tensor filled with 0 or 1 and average correctly.
:param input_tensor: A float tensor of shape [batch_size, ...] representing the loss/cross_entropy
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penguinmenac3/starttf | starttf/losses/loss_processors.py | variance_corrected_loss | def variance_corrected_loss(loss, sigma_2=None):
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When summing variance corrected losses you get the same as multiloss.
This is especially usefull for keras where when having multiple losses they are summed by keras.
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penguinmenac3/starttf | starttf/losses/loss_processors.py | focus_loss | def focus_loss(labels, probs, loss, gamma):
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See the focal loss paper: "Focal Loss for Dense Object Detection" [by Facebook AI Research]
:param labels: A float tensor of shape [batch_size, ..., num_classes] representing the label class probabilities.
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"""
Calculate the alpha balanced focal loss.
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penguinmenac3/starttf | starttf/layers/caffe_tensorflow.py | layer | def layer(op):
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penguinmenac3/starttf | starttf/layers/caffe_tensorflow.py | multi_output_layer | def multi_output_layer(op):
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ignore_missing: If true, serialized weights for missing layers are ignored.
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penguinmenac3/starttf | starttf/layers/caffe_tensorflow.py | Network.get_unique_name | def get_unique_name(self, prefix):
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ident = sum(t.startswith(prefix) for t, _ in self.layers.items()) + 1
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penguinmenac3/starttf | starttf/layers/caffe_tensorflow.py | Network.make_var | def make_var(self, op_name, name, shape):
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penguinmenac3/starttf | starttf/utils/misc.py | mode_to_str | def mode_to_str(mode):
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Implements an if condition in tensorflow.
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penguinmenac3/starttf | starttf/data/autorecords.py | _read_data_legacy | def _read_data_legacy(prefix, batch_size):
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:param batch_size: The batch size you want for the tensors.
:return: A feature tensor dict and a label tensor dict.
"""
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penguinmenac3/starttf | starttf/data/autorecords.py | _read_data | def _read_data(prefix, batch_size, augmentation=None):
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penguinmenac3/starttf | starttf/data/autorecords.py | create_input_fn | def create_input_fn(prefix, batch_size, augmentation=None):
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:param batch_size: The batch size you want for the tensors.
:param augmentation: An augmentation function.
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crunchyroll/ef-open | efopen/ef_context.py | EFContext.env | def env(self, value):
"""
Sets context.env, context.env_short, and context.account_alias if env is valid
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val... | python | def env(self, value):
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Sets context.env, context.env_short, and context.account_alias if env is valid
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crunchyroll/ef-open | efopen/ef_context.py | EFContext.service_registry | def service_registry(self, sr):
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Sets service registry object in context, doesn't check it
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sr: EFServiceRegistry object
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"""
Sets service registry object in context, doesn't check it
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sr: EFServiceRegistry object
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crunchyroll/ef-open | efopen/ef_context.py | EFContext.account_id | def account_id(self, value):
"""
Sets the current account id
Args:
value: current account id (string)
Returns:
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if type(value) is not str:
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self._account_id = value | python | def account_id(self, value):
"""
Sets the current account id
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value: current account id (string)
Returns:
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crunchyroll/ef-open | efopen/ef_context.py | EFContext.aws_client | def aws_client(self, client_id=None):
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Get AWS client if it exists (must have been formerly stored with set_aws_clients)
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crunchyroll/ef-open | efopen/ef_context.py | EFContext.set_aws_clients | def set_aws_clients(self, clients):
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Stash a dictionary of AWS clients in the context object
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clients: dictionary of clients
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Stash a dictionary of AWS clients in the context object
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clients: dictionary of clients
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crunchyroll/ef-open | efopen/ef_version.py | handle_args_and_set_context | def handle_args_and_set_context(args):
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Args:
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Returns:
a populated EFVersionContext object
"""
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parser.add_argument("key", h... | python | def handle_args_and_set_context(args):
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Args:
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a populated EFVersionContext object
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crunchyroll/ef-open | efopen/ef_version.py | validate_context | def validate_context(context):
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context: a populated EFVersionContext object
"""
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"""
Set the key for the current context.
Args:
context: a populated EFVersionContext object
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crunchyroll/ef-open | efopen/ef_version.py | precheck_ami_id | def precheck_ami_id(context):
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Args:
context: a populated EFVersionContext object
Returns:
True if ok to proceed
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crunchyroll/ef-open | efopen/ef_version.py | precheck_dist_hash | def precheck_dist_hash(context):
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crunchyroll/ef-open | efopen/ef_version.py | precheck | def precheck(context):
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crunchyroll/ef-open | efopen/ef_version.py | get_versions | def get_versions(context, return_stable=False):
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Get all versions of a key
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context: a populated EFVersionContext object
return_stable: (default:False) If True, stop fetching if 'stable' version is found; return only that version
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"""
Get all versions of a key
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context: a populated EFVersionContext object
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crunchyroll/ef-open | efopen/ef_version.py | get_version_by_value | def get_version_by_value(context, value):
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value: the value of the version to look for
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crunchyroll/ef-open | efopen/ef_version.py | cmd_rollback | def cmd_rollback(context):
"""
Roll back by finding the most recent "stable" tagged version, and putting it again, so that
it's the new "current" version.
Args:
context: a populated EFVersionContext object
"""
last_stable = get_versions(context, return_stable=True)
if len(last_stable) != 1:
fail("... | python | def cmd_rollback(context):
"""
Roll back by finding the most recent "stable" tagged version, and putting it again, so that
it's the new "current" version.
Args:
context: a populated EFVersionContext object
"""
last_stable = get_versions(context, return_stable=True)
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crunchyroll/ef-open | efopen/ef_version.py | cmd_rollback_to | def cmd_rollback_to(context):
"""
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Args:
context: a populated EFVersionContext object
"""
version = get_version_by_value(context, context.rollback_to)
context.value = version.value
context... | python | def cmd_rollback_to(context):
"""
Roll back by finding a specific version in the history of the service and
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context: a populated EFVersionContext object
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version = get_version_by_value(context, context.rollback_to)
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crunchyroll/ef-open | efopen/ef_version.py | cmd_set | def cmd_set(context):
"""
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Args:
context: a populated EFVersionContext object
"""
# If ke... | python | def cmd_set(context):
"""
Set the new "current" value for a key.
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context: a populated EFVersionContext object
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crunchyroll/ef-open | efopen/ef_version.py | Version.to_json | def to_json(self):
"""
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"""
return {
"build_number": self._build_number,
"commit_hash": self._commit_hash,
"last_modified": self._last_modif... | python | def to_json(self):
"""
called by VersionEncoder.default() when doing json.dumps() on the object
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return {
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penguinmenac3/starttf | starttf/rl/agents/agent.py | Agent.learn | def learn(self, steps=1, **kwargs):
"""
Train the model using the environment and the agent.
Note that the model might be shared between multiple agents (which most probably are of the same type)
at the same time.
:param steps: The number of steps to train for.
"""
... | python | def learn(self, steps=1, **kwargs):
"""
Train the model using the environment and the agent.
Note that the model might be shared between multiple agents (which most probably are of the same type)
at the same time.
:param steps: The number of steps to train for.
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symbol: the key to resolve
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"""
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symbol: the key to resolve
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penguinmenac3/starttf | starttf/losses/utils.py | overlay_classification_on_image | def overlay_classification_on_image(classification, rgb_image, scale=1):
"""
Overlay a classification either 1 channel or 3 channels on an input image.
:param classification: The classification tensor of shape [bach_size, v, u, 1] or [batch_size, v, u, 3].
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Overlay a classification either 1 channel or 3 channels on an input image.
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penguinmenac3/starttf | starttf/losses/utils.py | inflate_to_one_hot | def inflate_to_one_hot(tensor, classes):
"""
Converts a tensor with index form to a one hot tensor.
:param tensor: A tensor of shape [batch, h, w, 1]
:param classes: The number of classes that exist. (length of one hot encoding)
:return: A tensor of shape [batch, h, w, classes].
"""
one_hot ... | python | def inflate_to_one_hot(tensor, classes):
"""
Converts a tensor with index form to a one hot tensor.
:param tensor: A tensor of shape [batch, h, w, 1]
:param classes: The number of classes that exist. (length of one hot encoding)
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crunchyroll/ef-open | efopen/ef_config_resolver.py | EFConfigResolver.accountaliasofenv | def accountaliasofenv(self, lookup, default=None):
"""
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lookup: ENV_SHORT name of an env, such as: 'prod' or 'proto'
default: the optional value to return if lookup failed; returns None if not set
Returns:
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"""
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lookup: ENV_SHORT name of an env, such as: 'prod' or 'proto'
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crunchyroll/ef-open | efopen/ef_config_resolver.py | EFConfigResolver.customdata | def customdata(self, lookup, default=None):
"""
Args:
lookup: the custom data file
default: the optional value to return if lookup failed; returns None if not set
Returns:
The custom data returned from the file 'lookup' or default/None if no match found
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"""
Args:
lookup: the custom data file
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crunchyroll/ef-open | efopen/ef_utils.py | fail | def fail(message, exception_data=None):
"""
Print a failure message and exit nonzero
"""
print(message, file=sys.stderr)
if exception_data:
print(repr(exception_data))
sys.exit(1) | python | def fail(message, exception_data=None):
"""
Print a failure message and exit nonzero
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crunchyroll/ef-open | efopen/ef_utils.py | http_get_metadata | def http_get_metadata(metadata_path, timeout=__HTTP_DEFAULT_TIMEOUT_SEC):
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Fetch AWS metadata from http://169.254.169.254/latest/meta-data/<metadata_path>
ARGS:
metadata_path - the optional path and required key to the EC2 metadata (e.g. "instance-id")
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response content on success
RAISE:
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"""
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metadata_path - the optional path and required key to the EC2 metadata (e.g. "instance-id")
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response content on success
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crunchyroll/ef-open | efopen/ef_utils.py | is_in_virtualbox | def is_in_virtualbox():
"""
Is the current environment a virtualbox instance?
Returns a boolean
Raises IOError if the necessary tooling isn't available
"""
if not isfile(__VIRT_WHAT) or not access(__VIRT_WHAT, X_OK):
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"""
Is the current environment a virtualbox instance?
Returns a boolean
Raises IOError if the necessary tooling isn't available
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if not isfile(__VIRT_WHAT) or not access(__VIRT_WHAT, X_OK):
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Returns a boolean
Raises IOError if the necessary tooling isn't available | [
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crunchyroll/ef-open | efopen/ef_utils.py | whereami | def whereami():
"""
Determine if this is an ec2 instance or "running locally"
Returns:
"ec2" - this is an ec2 instance
"virtualbox-kvm" - kernel VM (virtualbox with vagrant)
"local" - running locally and not in a known VM
"unknown" - I have no idea where I am
"""
# If the metadata endpoint res... | python | def whereami():
"""
Determine if this is an ec2 instance or "running locally"
Returns:
"ec2" - this is an ec2 instance
"virtualbox-kvm" - kernel VM (virtualbox with vagrant)
"local" - running locally and not in a known VM
"unknown" - I have no idea where I am
"""
# If the metadata endpoint res... | [
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"local" - running locally and not in a known VM
"unknown" - I have no idea where I am | [
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crunchyroll/ef-open | efopen/ef_utils.py | http_get_instance_env | def http_get_instance_env():
"""
Returns: just the env this ec2 instance is in. Doesn't require API access like get_instance_aws_context does
Example return value: "staging"
"""
try:
info = json.loads(http_get_metadata('iam/info'))
except Exception as error:
raise IOError("Error looking up metadata:... | python | def http_get_instance_env():
"""
Returns: just the env this ec2 instance is in. Doesn't require API access like get_instance_aws_context does
Example return value: "staging"
"""
try:
info = json.loads(http_get_metadata('iam/info'))
except Exception as error:
raise IOError("Error looking up metadata:... | [
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crunchyroll/ef-open | efopen/ef_utils.py | get_instance_aws_context | def get_instance_aws_context(ec2_client):
"""
Returns: a dictionary of aws context
dictionary will contain these entries:
region, instance_id, account, role, env, env_short, service
Raises: IOError if couldn't read metadata or lookup attempt failed
"""
result = {}
try:
result["region"] = http_ge... | python | def get_instance_aws_context(ec2_client):
"""
Returns: a dictionary of aws context
dictionary will contain these entries:
region, instance_id, account, role, env, env_short, service
Raises: IOError if couldn't read metadata or lookup attempt failed
"""
result = {}
try:
result["region"] = http_ge... | [
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dictionary will contain these entries:
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Raises: IOError if couldn't read metadata or lookup attempt failed | [
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crunchyroll/ef-open | efopen/ef_utils.py | pull_repo | def pull_repo():
"""
Pulls latest version of EF_REPO_BRANCH from EF_REPO (as set in ef_config.py) if client is in EF_REPO
and on the branch EF_REPO_BRANCH
Raises:
RuntimeError with message if not in the correct repo on the correct branch
"""
try:
current_repo = subprocess.check_output(["git", "remot... | python | def pull_repo():
"""
Pulls latest version of EF_REPO_BRANCH from EF_REPO (as set in ef_config.py) if client is in EF_REPO
and on the branch EF_REPO_BRANCH
Raises:
RuntimeError with message if not in the correct repo on the correct branch
"""
try:
current_repo = subprocess.check_output(["git", "remot... | [
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and on the branch EF_REPO_BRANCH
Raises:
RuntimeError with message if not in the correct repo on the correct branch | [
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