def get_seed(op_seed):
"""Returns the local seeds an operation should use given an op-specific seed.
Given operation-specific seed, `op_seed`, this helper function returns two
seeds derived from graph-level and op-level seeds. Many random operations
internally use the two seeds to allow user to change the seed globally for a
graph, or for only specific operations.
For details on how the graph-level seed interacts with op seeds, see
`tf.compat.v1.random.set_random_seed`.
Args:
op_seed: integer.
Returns:
A tuple of two integers that should be used for the local seed of this
operation.
"""
eager = context.executing_eagerly()
if eager:
global_seed = context.global_seed()
else:
global_seed = ops.get_default_graph().seed
if global_seed is not None:
if op_seed is None:
# pylint: disable=protected-access
if hasattr(ops.get_default_graph(), '_seed_used'):
ops.get_default_graph()._seed_used = True
if eager:
op_seed = context.internal_operation_seed()
else:
op_seed = _graph_to_seed_dict.setdefault(
ops.get_default_graph(), 0)
_graph_to_seed_dict[ops.get_default_graph()] += 1
seeds = _truncate_seed(global_seed), _truncate_seed(op_seed)
else:
if op_seed is not None:
seeds = DEFAULT_GRAPH_SEED, _truncate_seed(op_seed)
else:
seeds = None, None
if seeds == (None, None) and config.deterministic_ops_enabled():
raise RuntimeError( # pylint: disable=g-doc-exception
'Random ops require a seed to be set when determinism is enabled. '
'Please set a seed before running the op, e.g. by calling '
'tf.random.set_seed(1).')
# Avoid (0, 0) as the C++ ops interpret it as nondeterminism, which would
# be unexpected since Python docs say nondeterminism is (None, None).
if seeds == (0, 0):
return (0, _MAXINT32)
return seeds
def get_seed(op_seed):
"""Returns the local seeds an operation should use given an op-specific seed.
Given operation-specific seed, `op_seed`, this helper function returns two
seeds derived from graph-level and op-level seeds. Many random operations
internally use the two seeds to allow user to change the seed globally for a
graph, or for only specific operations.
For details on how the graph-level seed interacts with op seeds, see
`tf.random.set_random_seed`.
Args:
op_seed: integer.
Returns:
A tuple of two integers that should be used for the local seed of this
operation.
"""
eager = context.executing_eagerly()
if eager:
global_seed = context.global_seed()
else:
global_seed = ops.get_default_graph().seed
if global_seed is not None:
if op_seed is None:
# pylint: disable=protected-access
if hasattr(ops.get_default_graph(), '_seed_used'):
ops.get_default_graph()._seed_used = True
if eager:
op_seed = context.internal_operation_seed()
else:
op_seed = ops.get_default_graph()._last_id
seeds = _truncate_seed(global_seed), _truncate_seed(op_seed)
else:
if op_seed is not None:
seeds = DEFAULT_GRAPH_SEED, _truncate_seed(op_seed)
else:
seeds = None, None
# Avoid (0, 0) as the C++ ops interpret it as nondeterminism, which would
# be unexpected since Python docs say nondeterminism is (None, None).
if seeds == (0, 0):
return (0, _MAXINT32)
return seeds
def get_seed(op_seed):
"""Returns the local seeds an operation should use given an op-specific seed.
Given operation-specific seed, `op_seed`, this helper function returns two
seeds derived from graph-level and op-level seeds. Many random operations
internally use the two seeds to allow user to change the seed globally for a
graph, or for only specific operations.
For details on how the graph-level seed interacts with op seeds, see
`tf.compat.v1.random.set_random_seed`.
Args:
op_seed: integer.
Returns:
A tuple of two integers that should be used for the local seed of this
operation.
"""
eager = context.executing_eagerly()
if eager:
global_seed = context.global_seed()
else:
global_seed = ops.get_default_graph().seed
if global_seed is not None:
if op_seed is None:
# pylint: disable=protected-access
if hasattr(ops.get_default_graph(), '_seed_used'):
ops.get_default_graph()._seed_used = True
if eager:
op_seed = context.internal_operation_seed()
else:
op_seed = ops.get_default_graph()._last_id
seeds = _truncate_seed(global_seed), _truncate_seed(op_seed)
else:
if op_seed is not None:
seeds = DEFAULT_GRAPH_SEED, _truncate_seed(op_seed)
else:
seeds = None, None
# Avoid (0, 0) as the C++ ops interpret it as nondeterminism, which would
# be unexpected since Python docs say nondeterminism is (None, None).
if seeds == (0, 0):
return (0, _MAXINT32)
return seeds
def SecureGetRandomSeed(op_seed=None):
"""Returns the local seeds an operation should use given an op-specific seed.
Args:
op_seed: integer.
Returns:
A tuple of two integers that should be used for the local seed of this
operation.
"""
eager = context.executing_eagerly()
if eager:
global_seed = context.global_seed()
else:
global_seed = ops.get_default_graph().seed
seeds = (0, 0)
if global_seed is not None:
if op_seed is None:
# pylint: disable=protected-access
if hasattr(ops.get_default_graph(), '_seed_used'):
ops.get_default_graph()._seed_used = True
if eager:
op_seed = context.internal_operation_seed()
else:
op_seed = ops.get_default_graph()._last_id
seeds = random_seed._truncate_seed(
global_seed), random_seed._truncate_seed(op_seed)
else:
if op_seed is not None:
seeds = random_seed.DEFAULT_GRAPH_SEED, random_seed._truncate_seed(
op_seed)
else:
if py_protocol_handler.is_activated():
seeds = py_protocol_handler.rand_seed(
0), py_protocol_handler.rand_seed(0)
# Avoid (0, 0) as the C++ ops interpret it as nondeterminism, which would
# random_seedbe unexpected since Python docs say nondeterminism is (None, None).
if seeds == (0, 0):
return (0, random_seed._MAXINT32)
return seeds
