def create_resource(self):
# The table must be shared if checkpointing is requested for multi-worker
# training to work correctly. Use the node name if no shared_name has been
# explicitly specified.
use_node_name_sharing = self._checkpoint and self._shared_name is None
if self._default_value.get_shape().ndims == 0:
table_ref = gen_lookup_ops.mutable_hash_table_v2(
shared_name=self._shared_name,
use_node_name_sharing=use_node_name_sharing,
key_dtype=self._key_dtype,
value_dtype=self._value_dtype,
name=self._name)
else:
table_ref = gen_lookup_ops.mutable_hash_table_of_tensors_v2(
shared_name=self._shared_name,
use_node_name_sharing=use_node_name_sharing,
key_dtype=self._key_dtype,
value_dtype=self._value_dtype,
value_shape=self._default_value.get_shape(),
name=self._name)
if context.executing_eagerly():
self._table_name = None
else:
self._table_name = table_ref.op.name.split("/")[-1]
return table_ref
def create_resource(self):
# The table must be shared if checkpointing is requested for multi-worker
# training to work correctly. Use the node name if no shared_name has been
# explicitly specified.
use_node_name_sharing = self._checkpoint and self._shared_name is None
if self._default_value.get_shape().ndims == 0:
table_ref = gen_lookup_ops.mutable_hash_table_v2(
shared_name=self._shared_name,
use_node_name_sharing=use_node_name_sharing,
key_dtype=self._key_dtype,
value_dtype=self._value_dtype,
name=self._name)
else:
table_ref = gen_lookup_ops.mutable_hash_table_of_tensors_v2(
shared_name=self._shared_name,
use_node_name_sharing=use_node_name_sharing,
key_dtype=self._key_dtype,
value_dtype=self._value_dtype,
value_shape=self._default_value.get_shape(),
name=self._name)
if context.executing_eagerly():
self._table_name = None
else:
self._table_name = table_ref.op.name.split("/")[-1]
return table_ref
def __init__(self,
key_dtype,
value_dtype,
default_value,
shared_name=None,
name="MutableHashTable",
checkpoint=True):
"""Creates an empty `MutableHashTable` object.
Creates a table, the type of its keys and values are specified by key_dtype
and value_dtype, respectively.
Args:
key_dtype: the type of the key tensors.
value_dtype: the type of the value tensors.
default_value: The value to use if a key is missing in the table.
shared_name: If non-empty, this table will be shared under
the given name across multiple sessions.
name: A name for the operation (optional).
checkpoint: if True, the contents of the table are saved to and restored
from checkpoints. If `shared_name` is empty for a checkpointed table, it
is shared using the table node name.
Returns:
A `MutableHashTable` object.
Raises:
ValueError: If checkpoint is True and no name was specified.
"""
self._default_value = ops.convert_to_tensor(default_value,
dtype=value_dtype)
self._value_shape = self._default_value.get_shape()
# The table must be shared if checkpointing is requested for multi-worker
# training to work correctly. Use the node name if no shared_name has been
# explicitly specified.
use_node_name_sharing = checkpoint and shared_name is None
if self._default_value.get_shape().ndims == 0:
self._table_ref = gen_lookup_ops.mutable_hash_table_v2(
shared_name=shared_name,
use_node_name_sharing=use_node_name_sharing,
key_dtype=key_dtype,
value_dtype=value_dtype,
name=name)
else:
self._table_ref = gen_lookup_ops.mutable_hash_table_of_tensors_v2(
shared_name=shared_name,
use_node_name_sharing=use_node_name_sharing,
key_dtype=key_dtype,
value_dtype=value_dtype,
value_shape=self._default_value.get_shape(),
name=name)
super(MutableHashTable, self).__init__(key_dtype, value_dtype,
self._table_ref.op.name.split(
"/")[-1])
if checkpoint:
saveable = MutableHashTable._Saveable(self, name)
ops.add_to_collection(ops.GraphKeys.SAVEABLE_OBJECTS, saveable)
def __init__(self,
key_dtype,
value_dtype,
default_value,
shared_name=None,
name="MutableHashTable",
checkpoint=True):
"""Creates an empty `MutableHashTable` object.
Creates a table, the type of its keys and values are specified by key_dtype
and value_dtype, respectively.
Args:
key_dtype: the type of the key tensors.
value_dtype: the type of the value tensors.
default_value: The value to use if a key is missing in the table.
shared_name: If non-empty, this table will be shared under
the given name across multiple sessions.
name: A name for the operation (optional).
checkpoint: if True, the contents of the table are saved to and restored
from checkpoints. If `shared_name` is empty for a checkpointed table, it
is shared using the table node name.
Returns:
A `MutableHashTable` object.
Raises:
ValueError: If checkpoint is True and no name was specified.
"""
self._default_value = ops.convert_to_tensor(default_value,
dtype=value_dtype)
self._value_shape = self._default_value.get_shape()
# The table must be shared if checkpointing is requested for multi-worker
# training to work correctly. Use the node name if no shared_name has been
# explicitly specified.
use_node_name_sharing = checkpoint and shared_name is None
if self._default_value.get_shape().ndims == 0:
self._table_ref = gen_lookup_ops.mutable_hash_table_v2(
shared_name=shared_name,
use_node_name_sharing=use_node_name_sharing,
key_dtype=key_dtype,
value_dtype=value_dtype,
name=name)
else:
self._table_ref = gen_lookup_ops.mutable_hash_table_of_tensors_v2(
shared_name=shared_name,
use_node_name_sharing=use_node_name_sharing,
key_dtype=key_dtype,
value_dtype=value_dtype,
value_shape=self._default_value.get_shape(),
name=name)
super(MutableHashTable, self).__init__(key_dtype, value_dtype,
self._table_ref.op.name.split(
"/")[-1])
if checkpoint:
saveable = MutableHashTable._Saveable(self, name)
ops.add_to_collection(ops.GraphKeys.SAVEABLE_OBJECTS, saveable)
def __init__(self, name, table_ref=None):
if table_ref is None:
self.table_ref = gen_lookup_ops.mutable_hash_table_v2(
key_dtype=dtypes.string, value_dtype=dtypes.float32, name=name)
else:
self.table_ref = table_ref
self._name = name
if not context.executing_eagerly():
self._saveable = CheckpointedOp.CustomSaveable(self, name)
ops_lib.add_to_collection(ops_lib.GraphKeys.SAVEABLE_OBJECTS,
self._saveable)
def __init__(self, name, table_ref=None):
if table_ref is None:
self.table_ref = gen_lookup_ops.mutable_hash_table_v2(
key_dtype=dtypes.string, value_dtype=dtypes.float32, name=name)
else:
self.table_ref = table_ref
self._name = name
if not context.executing_eagerly():
self._saveable = CheckpointedOp.CustomSaveable(self, name)
ops_lib.add_to_collection(ops_lib.GraphKeys.SAVEABLE_OBJECTS,
self._saveable)
