def master(self, task_type=None, task_index=None, rpc_layer=None):
"""Returns the master address to use when creating a session.
You must have set the task_type and task_index object properties before
calling this function, or pass in the `task_type` and `task_index`
parameters when using this function. If you do both, the function parameters
will override the object properties.
Args:
task_type: (Optional) The type of the TensorFlow task of the master.
task_index: (Optional) The index of the TensorFlow task of the master.
rpc_layer: (Optional) The RPC protocol for the given cluster.
Returns:
The name or URL of the session master.
"""
if task_type is not None and task_index is not None:
return format_master_url(
self.cluster_spec().task_address(task_type, task_index),
rpc_layer or self.rpc_layer)
if self.task_type is not None and self.task_index is not None:
return format_master_url(
self.cluster_spec().task_address(self.task_type, self.task_index),
rpc_layer or self.rpc_layer)
return ''
def master(self, task_type=None, task_index=None, rpc_layer=None):
"""Returns the master address to use when creating a session.
You must have set the task_type and task_index object properties before
calling this function, or pass in the `task_type` and `task_index`
parameters when using this function. If you do both, the function parameters
will override the object properties.
Args:
task_type: (Optional) The type of the TensorFlow task of the master.
task_index: (Optional) The index of the TensorFlow task of the master.
rpc_layer: (Optional) The RPC protocol for the given cluster.
Returns:
The name or URL of the session master.
"""
if task_type is not None and task_index is not None:
return format_master_url(
self.cluster_spec().task_address(task_type, task_index),
rpc_layer or self.rpc_layer)
if self.task_type is not None and self.task_index is not None:
return format_master_url(
self.cluster_spec().task_address(self.task_type,
self.task_index), rpc_layer
or self.rpc_layer)
return ''
def master(self, task_type=None, task_id=None, rpc_layer=None):
"""Get the Master string to be used for the session.
In the normal case, this returns the grpc path (grpc://1.2.3.4:8470) of
first instance in the ClusterSpec returned by the cluster_spec function.
If a non-TPU name is used when constructing a TPUClusterResolver, that will
be returned instead (e.g. If the tpus argument's value when constructing
this TPUClusterResolver was 'grpc://10.240.1.2:8470',
'grpc://10.240.1.2:8470' will be returned).
Args:
task_type: (Optional, string) The type of the TensorFlow task of the
master.
task_id: (Optional, integer) The index of the TensorFlow task of the
master.
rpc_layer: (Optional, string) The RPC protocol TensorFlow should use to
communicate with TPUs.
Returns:
string, the connection string to use when creating a session.
Raises:
ValueError: If none of the TPUs specified exists.
"""
if self._should_resolve():
# We are going to communicate with the Cloud TPU APIs to get a Cluster.
cluster_spec = self.cluster_spec()
if task_type is not None and task_id is not None:
# task_type and task_id is from the function parameter
master = cluster_spec.task_address(task_type, task_id)
elif self.task_type is not None and self.task_id is not None:
# task_type and task_id is from the object
master = cluster_spec.task_address(self.task_type,
self.task_id)
else:
# by default we take the first item in the cluster with the right name
job_tasks = cluster_spec.job_tasks(self.task_type)
if not job_tasks:
raise ValueError('No TPUs with the specified names exist.')
master = job_tasks[0]
else:
if isinstance(self._tpu, (bytes, bytearray)):
master = compat.as_text(
self._tpu).split(_ENDPOINTS_SEPARATOR)[0]
else:
master = self._tpu.split(_ENDPOINTS_SEPARATOR)[0]
return format_master_url(master, rpc_layer or self.rpc_layer)
def master(self, task_type=None, task_id=None, rpc_layer=None):
"""Get the Master string to be used for the session.
In the normal case, this returns the grpc path (grpc://1.2.3.4:8470) of
first instance in the ClusterSpec returned by the cluster_spec function.
If a non-TPU name is used when constructing a TPUClusterResolver, that will
be returned instead (e.g. If the tpus argument's value when constructing
this TPUClusterResolver was 'grpc://10.240.1.2:8470',
'grpc://10.240.1.2:8470' will be returned).
Args:
task_type: (Optional, string) The type of the TensorFlow task of the
master.
task_id: (Optional, integer) The index of the TensorFlow task of the
master.
rpc_layer: (Optional, string) The RPC protocol TensorFlow should use to
communicate with TPUs.
Returns:
string, the connection string to use when creating a session.
Raises:
ValueError: If none of the TPUs specified exists.
"""
if self._shouldResolve():
# We are going to communicate with the Cloud TPU APIs to get a Cluster.
cluster_spec = self.cluster_spec()
if task_type is not None and task_id is not None:
# task_type and task_id is from the function parameter
master = cluster_spec.task_address(task_type, task_id)
elif self.task_type is not None and self.task_id is not None:
# task_type and task_id is from the object
master = cluster_spec.task_address(self.task_type, self.task_id)
else:
# by default we take the first item in the cluster with the right name
job_tasks = cluster_spec.job_tasks(self.task_type)
if not job_tasks:
raise ValueError('No TPUs with the specified names exist.')
master = job_tasks[0]
else:
if isinstance(self._tpu, (bytes, bytearray)):
master = self._tpu.split(compat.as_bytes(_ENDPOINTS_SEPARATOR))[0]
else:
master = self._tpu.split(_ENDPOINTS_SEPARATOR)[0]
return format_master_url(master, rpc_layer or self.rpc_layer)
def master(self, task_type=None, task_id=None, rpc_layer=None):
"""Returns the master string for connecting to a TensorFlow master.
Args:
task_type: (Optional) Overrides the default auto-selected task type.
task_id: (Optional) Overrides the default auto-slected task index.
rpc_layer: (Optional) Overrides the default RPC protocol TensorFlow uses
to communicate across nodes.
Returns:
A connection string for connecting to a TensorFlow master.
"""
task_type = task_type if task_type is not None else self.task_type
task_id = task_id if task_id is not None else self.task_id
if task_type is not None and task_id is not None:
return format_master_url(
self.cluster_spec().task_address(task_type, task_id),
rpc_layer or self.rpc_layer)
return ''
def master(self, task_type=None, task_id=None, rpc_layer=None):
"""Returns the master string for connecting to a TensorFlow master.
Args:
task_type: (Optional) Overrides the default auto-selected task type.
task_id: (Optional) Overrides the default auto-slected task index.
rpc_layer: (Optional) Overrides the default RPC protocol TensorFlow uses
to communicate across nodes.
Returns:
A connection string for connecting to a TensorFlow master.
"""
task_type = task_type if task_type is not None else self.task_type
task_id = task_id if task_id is not None else self.task_id
if task_type is not None and task_id is not None:
return format_master_url(
self.cluster_spec().task_address(task_type, task_id), rpc_layer
or self.rpc_layer)
return ''
def master(self, task_type=None, task_id=None, rpc_layer=None):
"""Retrieves the name or URL of the session master.
Args:
task_type: (Optional) The type of the TensorFlow task of the master.
task_id: (Optional) The index of the TensorFlow task of the master.
rpc_layer: (Optional) The RPC protocol for the given cluster.
Returns:
The name or URL of the session master.
Implementors of this function must take care in ensuring that the master
returned is up-to-date at the time to calling this function. This usually
means retrieving the master every time this function is invoked.
"""
task_type = task_type if task_type is not None else self.task_type
task_id = task_id if task_id is not None else self.task_id
if task_type is not None and task_id is not None:
return format_master_url(
self.cluster_spec().task_address(task_type, task_id), rpc_layer
or self.rpc_layer)
return ''