def __init__(self,
key_dtype,
value_dtype,
default_value,
empty_key,
initial_num_buckets=None,
shared_name=None,
name="MutableDenseHashTable",
checkpoint=True):
"""Creates an empty `MutableDenseHashTable` 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.
empty_key: the key to use to represent empty buckets internally. Must not
be used in insert or lookup operations.
initial_num_buckets: the initial number of buckets.
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
empty_key = ops.convert_to_tensor(empty_key, dtype=key_dtype)
self._table_ref = gen_lookup_ops.mutable_dense_hash_table_v2(
empty_key=empty_key,
shared_name=shared_name,
use_node_name_sharing=use_node_name_sharing,
value_dtype=value_dtype,
value_shape=self._value_shape,
initial_num_buckets=initial_num_buckets,
name=name)
super(MutableDenseHashTable,
self).__init__(key_dtype, value_dtype,
self._table_ref.op.name.split("/")[-1])
if checkpoint:
saveable = MutableDenseHashTable._Saveable(self, name)
ops.add_to_collection(ops.GraphKeys.SAVEABLE_OBJECTS, saveable)
def __init__(self,
key_dtype,
value_dtype,
default_value,
empty_key,
initial_num_buckets=None,
shared_name=None,
name="MutableDenseHashTable",
checkpoint=True):
"""Creates an empty `MutableDenseHashTable` 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.
empty_key: the key to use to represent empty buckets internally. Must not
be used in insert or lookup operations.
initial_num_buckets: the initial number of buckets.
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, name="default_value")
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
empty_key = ops.convert_to_tensor(
empty_key, dtype=key_dtype, name="empty_key")
self._table_ref = gen_lookup_ops.mutable_dense_hash_table_v2(
empty_key=empty_key,
shared_name=shared_name,
use_node_name_sharing=use_node_name_sharing,
value_dtype=value_dtype,
value_shape=self._value_shape,
initial_num_buckets=initial_num_buckets,
name=name)
super(MutableDenseHashTable, self).__init__(
key_dtype, value_dtype, self._table_ref.op.name.split("/")[-1])
if checkpoint:
saveable = MutableDenseHashTable._Saveable(self, name)
ops.add_to_collection(ops.GraphKeys.SAVEABLE_OBJECTS, saveable)
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
table_ref = gen_lookup_ops.mutable_dense_hash_table_v2(
empty_key=self._empty_key,
deleted_key=self._deleted_key,
shared_name=self._shared_name,
use_node_name_sharing=use_node_name_sharing,
value_dtype=self._value_dtype,
value_shape=self._value_shape,
initial_num_buckets=self._initial_num_buckets,
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
table_ref = gen_lookup_ops.mutable_dense_hash_table_v2(
empty_key=self._empty_key,
deleted_key=self._deleted_key,
shared_name=self._shared_name,
use_node_name_sharing=use_node_name_sharing,
value_dtype=self._value_dtype,
value_shape=self._value_shape,
initial_num_buckets=self._initial_num_buckets,
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,
empty_key,
deleted_key,
initial_num_buckets=None,
shared_name=None,
name="MutableDenseHashTable",
checkpoint=True):
"""Creates an empty `MutableDenseHashTable` 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.
empty_key: the key to use to represent empty buckets internally. Must not
be used in insert, remove or lookup operations.
initial_num_buckets: the initial number of buckets.
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.
deleted_key: the key to use to represent deleted buckets internally. Must
not be used in insert, remove or lookup operations and be different from
the empty_key.
Returns:
A `MutableDenseHashTable` object.
Raises:
ValueError: If checkpoint is True and no name was specified.
"""
self._default_value = ops.convert_to_tensor(default_value,
dtype=value_dtype,
name="default_value")
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
empty_key = ops.convert_to_tensor(empty_key,
dtype=key_dtype,
name="empty_key")
deleted_key = ops.convert_to_tensor(deleted_key,
dtype=key_dtype,
name="deleted_key")
executing_eagerly = context.executing_eagerly()
if executing_eagerly and shared_name is None:
# TODO(allenl): This will leak memory due to kernel caching by the
# shared_name attribute value (but is better than the alternative of
# sharing everything by default when executing eagerly; hopefully creating
# tables in a loop is uncommon).
shared_name = "table_%d" % (ops.uid(), )
self._table_ref = gen_lookup_ops.mutable_dense_hash_table_v2(
empty_key=empty_key,
deleted_key=deleted_key,
shared_name=shared_name,
use_node_name_sharing=use_node_name_sharing,
value_dtype=value_dtype,
value_shape=self._value_shape,
initial_num_buckets=initial_num_buckets,
name=name)
if executing_eagerly:
op_name = None
else:
op_name = self._table_ref.op.name.split("/")[-1]
super(MutableDenseHashTable, self).__init__(key_dtype, value_dtype,
op_name)
if checkpoint:
saveable = MutableDenseHashTable._Saveable(self, name)
ops.add_to_collection(ops.GraphKeys.SAVEABLE_OBJECTS, saveable)