def lookup(self, keys, name=None):
"""Looks up `keys` in a table, outputs the corresponding values.
The `default_value` is used for keys not present in the table.
Args:
keys: Keys to look up. Can be a tensor of any shape. Must match the
table's key_dtype.
name: A name for the operation (optional).
Returns:
A tensor containing the values in the same shape as `keys` using the
table's value type.
Raises:
TypeError: when `keys` do not match the table data types.
"""
with ops.name_scope(name, "%s_lookup_table_find" % self.name,
[self.resource_handle, keys]) as name:
keys = ops.convert_to_tensor(keys,
dtype=self._key_dtype,
name="keys")
with ops.colocate_with(self.resource_handle):
values = gen_lookup_ops.lookup_table_find_v2(
self.resource_handle, keys, self._default_value, name=name)
return values
def lookup(self, keys, name=None):
"""Looks up `keys` in a table, outputs the corresponding values.
The `default_value` is used for keys not present in the table.
Args:
keys: Keys to look up. Can be a tensor of any shape. Must match the
table's key_dtype.
name: A name for the operation (optional).
Returns:
A tensor containing the values in the same shape as `keys` using the
table's value type.
Raises:
TypeError: when `keys` do not match the table data types.
"""
with ops.name_scope(name, "%s_lookup_table_find" % self._name,
[self._table_ref, keys]) as name:
keys = ops.convert_to_tensor(keys, dtype=self._key_dtype, name="keys")
with ops.colocate_with(self._table_ref):
values = gen_lookup_ops.lookup_table_find_v2(
self._table_ref, keys, self._default_value, name=name)
return values
def lookup(self, keys, name=None):
"""Looks up `keys` in a table, outputs the corresponding values.
The `default_value` is used for keys not present in the table.
Args:
keys: Keys to look up. May be either a `SparseTensor` or dense `Tensor`.
name: A name for the operation (optional).
Returns:
A `SparseTensor` if keys are sparse, otherwise a dense `Tensor`.
Raises:
TypeError: when `keys` or `default_value` doesn't match the table data
types.
"""
key_tensor = keys
if isinstance(keys, sparse_tensor.SparseTensor):
key_tensor = keys.values
if keys.dtype.base_dtype != self._key_dtype:
raise TypeError("Signature mismatch. Keys must be dtype %s, got %s." %
(self._key_dtype, keys.dtype))
with ops.name_scope(
name, "%s_Lookup" % self.name,
(self.resource_handle, key_tensor, self._default_value)) as scope:
values = gen_lookup_ops.lookup_table_find_v2(
self.resource_handle, key_tensor, self._default_value, name=scope)
values.set_shape(key_tensor.get_shape())
if isinstance(keys, sparse_tensor.SparseTensor):
return sparse_tensor.SparseTensor(keys.indices, values, keys.dense_shape)
else:
return values
def lookup(self, keys, name=None):
"""Looks up `keys` in a table, outputs the corresponding values.
The `default_value` is used for keys not present in the table.
Args:
keys: Keys to look up. Can be a tensor of any shape. Must match the
table's key_dtype.
name: A name for the operation (optional).
Returns:
A tensor containing the values in the same shape as `keys` using the
table's value type.
Raises:
TypeError: when `keys` do not match the table data types.
"""
if keys.dtype.base_dtype != self._key_dtype:
raise TypeError("Signature mismatch. Keys must be dtype %s, got %s." %
(self._key_dtype, keys.dtype))
with ops.name_scope(name, "%s_lookup_table_find" % self._name,
[self._table_ref, keys]) as name:
with ops.colocate_with(self._table_ref):
values = gen_lookup_ops.lookup_table_find_v2(
self._table_ref, keys, self._default_value, name=name)
if keys.get_shape().ndims is not None and keys.get_shape().ndims > 0:
values.set_shape(
tensor_shape.TensorShape([keys.get_shape().dims[0]]).concatenate(
self._value_shape))
return values
def lookup(self, keys, name=None):
"""Looks up `keys` in a table, outputs the corresponding values.
The `default_value` is used for keys not present in the table.
Args:
keys: Keys to look up. Can be a tensor of any shape. Must match the
table's key_dtype.
name: A name for the operation (optional).
Returns:
A tensor containing the values in the same shape as `keys` using the
table's value type.
Raises:
TypeError: when `keys` do not match the table data types.
"""
if keys.dtype.base_dtype != self._key_dtype:
raise TypeError("Signature mismatch. Keys must be dtype %s, got %s." %
(self._key_dtype, keys.dtype))
with ops.name_scope(name, "%s_lookup_table_find" % self._name,
[self._table_ref, keys]) as name:
with ops.colocate_with(self._table_ref):
values = gen_lookup_ops.lookup_table_find_v2(
self._table_ref, keys, self._default_value, name=name)
if keys.get_shape().ndims is not None and keys.get_shape().ndims > 0:
values.set_shape(
tensor_shape.TensorShape([keys.get_shape().dims[0]]).concatenate(
self._value_shape))
return values
def lookup(self, keys, name=None):
"""Looks up `keys` in a table, outputs the corresponding values.
The `default_value` is used for keys not present in the table.
Args:
keys: Keys to look up. May be either a `SparseTensor` or dense `Tensor`.
name: A name for the operation (optional).
Returns:
A `SparseTensor` if keys are sparse, otherwise a dense `Tensor`.
Raises:
TypeError: when `keys` or `default_value` doesn't match the table data
types.
"""
key_tensor = keys
if isinstance(keys, sparse_tensor.SparseTensor):
key_tensor = keys.values
if keys.dtype.base_dtype != self._key_dtype:
raise TypeError("Signature mismatch. Keys must be dtype %s, got %s." %
(self._key_dtype, keys.dtype))
with ops.name_scope(
name, "%s_Lookup" % self.name,
(self.resource_handle, key_tensor, self._default_value)) as scope:
values = gen_lookup_ops.lookup_table_find_v2(
self.resource_handle, key_tensor, self._default_value, name=scope)
values.set_shape(key_tensor.get_shape())
if isinstance(keys, sparse_tensor.SparseTensor):
return sparse_tensor.SparseTensor(keys.indices, values, keys.dense_shape)
else:
return values
def lookup(self, keys, default):
return gen_lookup_ops.lookup_table_find_v2(self.table_ref, keys,
default)
def lookup(self, keys, default): return gen_lookup_ops.lookup_table_find_v2(self.table_ref, keys, default)
