def check_iterative_process_compatible_with_map_reduce_form(
ip: iterative_process.IterativeProcess):
"""Tests compatibility with `tff.backends.mapreduce.MapReduceForm`.
Note: the conditions here are specified in the documentation for
`get_map_reduce_form_for_iterative_process`. Changes to this function should
be propagated to that documentation.
Args:
ip: An instance of `tff.templates.IterativeProcess` to check for
compatibility with `tff.backends.mapreduce.MapReduceForm`.
Returns:
TFF-internal building-blocks representing the validated and simplified
`initialize` and `next` computations.
Raises:
TypeError: If the arguments are of the wrong types.
"""
py_typecheck.check_type(ip, iterative_process.IterativeProcess)
initialize_tree = ip.initialize.to_building_block()
next_tree = ip.next.to_building_block()
init_type = initialize_tree.type_signature
_check_type_is_no_arg_fn(init_type, '`initialize`', TypeError)
if (not init_type.result.is_federated()
or init_type.result.placement != placements.SERVER):
raise TypeError(
'Expected `initialize` to return a single federated value '
'placed at server (type `T@SERVER`), found return type:\n'
f'{init_type.result}')
next_type = next_tree.type_signature
_check_type_is_fn(next_type, '`next`', TypeError)
if not next_type.parameter.is_struct() or len(next_type.parameter) != 2:
raise TypeError(
'Expected `next` to take two arguments, found parameter '
f' type:\n{next_type.parameter}')
if not next_type.result.is_struct() or len(next_type.result) != 2:
raise TypeError('Expected `next` to return two values, found result '
f'type:\n{next_type.result}')
initialize_tree, _ = intrinsic_reductions.replace_intrinsics_with_bodies(
initialize_tree)
next_tree, _ = intrinsic_reductions.replace_intrinsics_with_bodies(
next_tree)
next_tree = _replace_lambda_body_with_call_dominant_form(next_tree)
tree_analysis.check_contains_only_reducible_intrinsics(initialize_tree)
tree_analysis.check_contains_only_reducible_intrinsics(next_tree)
tree_analysis.check_broadcast_not_dependent_on_aggregate(next_tree)
return initialize_tree, next_tree
def test_federated_secure_select(self):
uri = intrinsic_defs.FEDERATED_SECURE_SELECT.uri
comp = building_blocks.Intrinsic(
uri,
computation_types.FunctionType(
[
computation_types.at_clients(tf.int32), # client_keys
computation_types.at_server(tf.int32), # max_key
computation_types.at_server(tf.float32), # server_state
computation_types.FunctionType([tf.float32, tf.int32],
tf.float32) # select_fn
],
computation_types.at_clients(
computation_types.SequenceType(tf.float32))))
self.assertGreater(_count_intrinsics(comp, uri), 0)
# First without secure intrinsics shouldn't modify anything.
reduced, modified = intrinsic_reductions.replace_intrinsics_with_bodies(
comp)
self.assertFalse(modified)
self.assertGreater(_count_intrinsics(comp, uri), 0)
self.assert_types_identical(comp.type_signature,
reduced.type_signature)
# Now replace bodies including secure intrinsics.
reduced, modified = intrinsic_reductions.replace_secure_intrinsics_with_insecure_bodies(
comp)
self.assertTrue(modified)
self.assert_types_identical(comp.type_signature,
reduced.type_signature)
self.assertGreater(
_count_intrinsics(reduced, intrinsic_defs.FEDERATED_SELECT.uri), 0)
def test_federated_secure_sum_bitwidth(self, value_dtype, bitwidth_type):
uri = intrinsic_defs.FEDERATED_SECURE_SUM_BITWIDTH.uri
comp = building_blocks.Intrinsic(
uri,
computation_types.FunctionType(
parameter=[
computation_types.at_clients(value_dtype),
computation_types.to_type(bitwidth_type)
],
result=computation_types.at_server(value_dtype)))
# First without secure intrinsics shouldn't modify anything.
reduced, modified = intrinsic_reductions.replace_intrinsics_with_bodies(
comp)
self.assertFalse(modified)
self.assertGreater(_count_intrinsics(comp, uri), 0)
self.assert_types_identical(comp.type_signature,
reduced.type_signature)
# Now replace bodies including secure intrinsics.
reduced, modified = intrinsic_reductions.replace_secure_intrinsics_with_insecure_bodies(
comp)
self.assertTrue(modified)
self.assert_types_identical(comp.type_signature,
reduced.type_signature)
self.assertGreater(
_count_intrinsics(reduced, intrinsic_defs.FEDERATED_AGGREGATE.uri),
0)
def test_federated_mean_reduces_to_aggregate(self):
uri = intrinsic_defs.FEDERATED_MEAN.uri
@computations.federated_computation(
computation_types.FederatedType(tf.float32,
placement_literals.CLIENTS))
def foo(x):
return intrinsics.federated_mean(x)
foo_building_block = building_blocks.ComputationBuildingBlock.from_proto(
foo._computation_proto)
count_means_before_reduction = _count_intrinsics(
foo_building_block, uri)
reduced, modified = intrinsic_reductions.replace_intrinsics_with_bodies(
foo_building_block)
count_means_after_reduction = _count_intrinsics(reduced, uri)
count_aggregations = _count_intrinsics(
reduced, intrinsic_defs.FEDERATED_AGGREGATE.uri)
count_means_after_reduction = _count_intrinsics(reduced, uri)
self.assertTrue(modified)
self.assert_types_identical(foo_building_block.type_signature,
reduced.type_signature)
self.assertGreater(count_means_before_reduction, 0)
self.assertEqual(count_means_after_reduction, 0)
self.assertGreater(count_aggregations, 0)
def test_federated_reduce_not_reduced(self):
# It is in general unsafe to attempt to decompose a federated_reduce into a
# federated_aggregate, as not every reduction function can be decomposed
# into accumulate and merge calls without writing fundamentally new logic,
# e.g. 'return 1 if both arguments are 0'.
uri = intrinsic_defs.FEDERATED_REDUCE.uri
@computations.tf_computation(tf.float32, tf.float32)
def add(x, y):
return x + y
@computations.federated_computation(
computation_types.FederatedType(tf.float32,
placement_literals.CLIENTS))
def foo(x):
return intrinsics.federated_reduce(x, 0., add)
foo_building_block = building_blocks.ComputationBuildingBlock.from_proto(
foo._computation_proto)
count_reduce_before_reduction = _count_intrinsics(
foo_building_block, uri)
reduced, _ = intrinsic_reductions.replace_intrinsics_with_bodies(
foo_building_block)
self.assert_types_identical(foo_building_block.type_signature,
reduced.type_signature)
count_reduce_after_reduction = _count_intrinsics(reduced, uri)
self.assertGreater(count_reduce_before_reduction, 0)
self.assertEqual(count_reduce_after_reduction,
count_reduce_before_reduction)
def get_broadcast_form_for_computation(
comp: computation_base.Computation,
grappler_config: tf.compat.v1.ConfigProto = _GRAPPLER_DEFAULT_CONFIG
) -> forms.BroadcastForm:
"""Constructs `tff.backends.mapreduce.BroadcastForm` given a computation.
Args:
comp: An instance of `tff.Computation` that is compatible with broadcast
form. Computations are only compatible if they take in a single value
placed at server, return a single value placed at clients, and do not
contain any aggregations.
grappler_config: An instance of `tf.compat.v1.ConfigProto` to configure
Grappler graph optimization of the Tensorflow graphs backing the resulting
`tff.backends.mapreduce.BroadcastForm`. These options are combined with a
set of defaults that aggressively configure Grappler. If
`grappler_config_proto` has
`graph_options.rewrite_options.disable_meta_optimizer=True`, Grappler is
bypassed.
Returns:
An instance of `tff.backends.mapreduce.BroadcastForm` equivalent to the
provided `tff.Computation`.
"""
py_typecheck.check_type(comp, computation_base.Computation)
_check_function_signature_compatible_with_broadcast_form(
comp.type_signature)
py_typecheck.check_type(grappler_config, tf.compat.v1.ConfigProto)
grappler_config = _merge_grappler_config_with_default(grappler_config)
bb = comp.to_building_block()
bb, _ = intrinsic_reductions.replace_intrinsics_with_bodies(bb)
bb = _replace_lambda_body_with_call_dominant_form(bb)
tree_analysis.check_contains_only_reducible_intrinsics(bb)
aggregations = tree_analysis.find_aggregations_in_tree(bb)
if aggregations:
raise ValueError(
f'`get_broadcast_form_for_computation` called with computation '
f'containing {len(aggregations)} aggregations, but broadcast form '
'does not allow aggregation. Full list of aggregations:\n{aggregations}'
)
before_broadcast, after_broadcast = _split_ast_on_broadcast(bb)
compute_server_context = _extract_compute_server_context(
before_broadcast, grappler_config)
client_processing = _extract_client_processing(after_broadcast,
grappler_config)
compute_server_context, client_processing = (
computation_wrapper_instances.building_block_to_computation(bb)
for bb in (compute_server_context, client_processing))
comp_param_names = structure.name_list_with_nones(
comp.type_signature.parameter)
server_data_label, client_data_label = comp_param_names
return forms.BroadcastForm(compute_server_context,
client_processing,
server_data_label=server_data_label,
client_data_label=client_data_label)
def test_generic_plus_reduces(self):
uri = intrinsic_defs.GENERIC_PLUS.uri
comp = building_blocks.Intrinsic(
uri, computation_types.FunctionType([tf.float32, tf.float32],
tf.float32))
count_before_reduction = _count_intrinsics(comp, uri)
reduced, modified = intrinsic_reductions.replace_intrinsics_with_bodies(
comp)
count_after_reduction = _count_intrinsics(reduced, uri)
self.assertTrue(modified)
self.assert_types_identical(comp.type_signature, reduced.type_signature)
self.assertGreater(count_before_reduction, 0)
self.assertEqual(count_after_reduction, 0)
tree_analysis.check_contains_only_reducible_intrinsics(reduced)
def test_federated_sum_reduces_to_aggregate(self):
uri = intrinsic_defs.FEDERATED_SUM.uri
comp = building_blocks.Intrinsic(
uri,
computation_types.FunctionType(
computation_types.at_clients(tf.float32),
computation_types.at_server(tf.float32)))
count_sum_before_reduction = _count_intrinsics(comp, uri)
reduced, modified = intrinsic_reductions.replace_intrinsics_with_bodies(
comp)
count_sum_after_reduction = _count_intrinsics(reduced, uri)
count_aggregations = _count_intrinsics(
reduced, intrinsic_defs.FEDERATED_AGGREGATE.uri)
self.assertTrue(modified)
self.assert_types_identical(comp.type_signature, reduced.type_signature)
self.assertGreater(count_sum_before_reduction, 0)
self.assertEqual(count_sum_after_reduction, 0)
self.assertGreater(count_aggregations, 0)
def test_raises_on_none(self):
with self.assertRaises(TypeError):
intrinsic_reductions.replace_intrinsics_with_bodies(None)
