def _eliminate_loop_cond_nodes(tf_ssa, fn):
"""
Eliminate loop condition nodes, such as loop_counters, max_iterations from
the cond sub-graph and body sub-graph of tf.while_loop.
Parameters
----------
tf_ssa: NetworkEnsemble
An object that contains multiple functions / sub-graphs.
fn: SSAFunction
Function that contains graph to operate on.
Examples
--------
Input:
Before pass "main" graph:
[while/maximum_iterations] -----\
[while/loop_counter] -------> [while] --> [identity]
[placeholder/args_0] ----------/
Before pass "cond" graph:
[const/mean] -------\
[placeholder] --> [mean] --> [greater]
[const/greater/y] --------------/
[while_maximum_iterations], [while_loop_counter] (not connected)
Before pass "body" graph:
[const/sub/y] ------\
[placeholder] ---> [sub]
[const/add/y] ------------\
[while_loop_counter] --> [add]
[while_maximum_iterations] (not connected)
Output:
After pass "main" graph:
[placeholder/args_0] --> [while] --> [identity]
After pass "cond" graph:
[const/mean] -------\
[placeholder] --> [mean] --> [greater]
[const/greater/y] --------------/
After pass "body" graph:
[const/sub/y] ------\
[placeholder] ---> [sub]
"""
for name, node in fn.graph.copy().items():
if node.op not in {"StatelessWhile", "While"}:
continue
cond_fn = tf_ssa.functions.get(node.attr.get("cond"))
body_fn = tf_ssa.functions.get(node.attr.get("body"))
cond_lc_nodes = {cond_fn.inputs.pop(0), cond_fn.inputs.pop(0)}
logging.info("Removing {} from cond graph".format(cond_lc_nodes))
for n in cond_lc_nodes:
delete_node(cond_fn.graph, n)
body_lc_nodes = {body_fn.inputs.pop(0), body_fn.inputs.pop(0)}
q = list(body_lc_nodes)
# delete entire sub-fn
while len(q) > 0:
n = body_fn.graph[q.pop(0)]
for o in n.outputs:
if o not in body_lc_nodes:
q.append(o)
body_lc_nodes.add(o)
for i in body_fn.graph[o].inputs:
if i not in body_lc_nodes:
q.append(i)
body_lc_nodes.add(i)
# remove if in outputs
for n in body_lc_nodes:
if n in body_fn.outputs:
msg = "Removing '{}' ({}) from body fn outputs"
logging.info(msg.format(n, body_fn.graph[n].op))
body_fn.outputs.remove(n)
logging.info("Removing {} from body graph".format(body_lc_nodes))
for n in body_lc_nodes:
delete_node(body_fn.graph, n)
def _rewrite_while_loop_functions(tf_ssa, fn):
"""
Rewrite tf.while_loop's sub-graphs with get_tuple, make_tuple,
function_entry and return ops. This rewrite is required in order to convert
functional form control flow v2 nodes 'StatelessWhile' and 'While'.
Parameters
----------
tf_ssa: NetworkEnsemble
An object that contains multiple functions / sub-graphs.
fn: SSAFunction
Function that contains graph to operate on.
Example
-------
Input:
Before pass "main" graph:
[placeholder/args_0] --> [while] --> [identity]
Before pass "cond" graph:
[const/mean] -------\
[placeholder] --> [mean] --> [greater]
[const/greater/y] --------------/
Before pass "body" graph:
[const/sub/y] ------\
[placeholder] ---> [sub]
Output:
After pass "main" graph:
[placeholder/args_0] --> [make_tuple] --> [while] --> [get_tuple] --> [identity]
After pass "cond" graph:
[const/mean] ------\
[entry] -> [get_tuple] -> [placeholder] -> [mean] -> [greater] -> [make_tuple] -> [return]
[const/greater/y] ------------/
After pass "body" graph:
[const/sub/y] ----\
[entry] -> [get_tuple] -> [placeholder] -> [sub] -> [make_tuple] -> [return]
"""
for while_name, while_node in fn.graph.copy().items():
if while_node.op not in {"StatelessWhile", "While"}:
continue
cond_fn_name = while_node.attr.get("cond")
body_fn_name = while_node.attr.get("body")
msg = "Rewriting '{}' ({}) sub-graphs: cond '{}', body '{}'"
logging.info(
msg.format(while_node.name, while_node.op, cond_fn_name,
body_fn_name))
cond_fn = tf_ssa.functions.get(cond_fn_name)
body_fn = tf_ssa.functions.get(body_fn_name)
# insert function entry nodes
cond_entry = _insert_function_entry(cond_fn)
body_entry = _insert_function_entry(body_fn)
# pack node inputs to a single tuple
while_input_tuple = _insert_make_tuple(
fn, "make_tuple/{}".format(while_name))
for wi in while_node.inputs:
disconnect_edge(fn.graph, wi, while_node.name)
connect_edge(fn.graph, wi, while_input_tuple)
connect_edge(fn.graph, while_input_tuple, while_node.name)
# unpack node outputs to multiple get_tuples
for i, wo in enumerate(while_node.outputs):
# utilize FunctionDef's ret to make sure function outputs and
# node outputs order matches when multiple outputs are there.
o_original = fn.graph[wo].original_node
while_input = [
n for n in o_original.input if str(n).startswith(while_name)
][0]
while_index = while_input.split(":")[-1]
if while_index != 0:
identity_postfix = "identity_{}".format(while_index)
else: # access identity "0"
identity_postfix = "identity"
identity_keys = [
t for t in body_fn.ret.keys() if t.endswith(identity_postfix)
]
if len(identity_keys) != 1:
raise NotImplementedError("Branch not found.")
mapped_name = body_fn.ret[identity_keys[0]].split(":")[0]
idx = body_fn.outputs.index(mapped_name)
loop_output = _insert_get_tuple(
fn, "get_tuple/{}/{}".format(idx, while_input), idx)
edge_idx = fn.graph[wo].inputs.index(while_node.name)
replace_dest(fn.graph, while_node, wo, loop_output)
connect_edge_at_index(fn.graph, loop_output, wo, edge_idx)
# fetch inputs using get_tuple for cond fn
for i, ci in enumerate(cond_fn.inputs):
cond_input = _insert_get_tuple(cond_fn,
"get_tuple/{}/{}".format(i, ci), i)
connect_edge(cond_fn.graph, cond_entry, cond_input)
replace_node(cond_fn.graph, ci, cond_input)
delete_node(cond_fn.graph, ci)
# fetch inputs using get_tuple for body fn
for i, bi in enumerate(body_fn.inputs):
new_name = "get_tuple/{}/{}".format(i, bi)
if bi in body_fn.outputs: # input is also an output
body_fn.outputs[body_fn.outputs.index(bi)] = new_name
body_input = _insert_get_tuple(body_fn, new_name, i)
connect_edge(body_fn.graph, body_entry, body_input)
replace_node(body_fn.graph, bi, body_input)
delete_node(body_fn.graph, bi)
# returns a tuple of value(s) as output for cond fn
cond_output = _insert_make_tuple(cond_fn)
for co in cond_fn.outputs:
connect_edge(cond_fn.graph, co, cond_output.name)
cond_return = _insert_return(cond_fn)
connect_edge(cond_fn.graph, cond_output.name, cond_return.name)
# returns a tuple of value(s) as output for body branch
body_output = _insert_make_tuple(body_fn)
for bo in body_fn.outputs:
connect_edge(body_fn.graph, bo, body_output.name)
body_return = _insert_return(body_fn)
connect_edge(body_fn.graph, body_output.name, body_return.name)
def _rewrite_cond_functions(tf_ssa, fn):
r"""
Rewrite tf.cond's sub-graphs with get_tuple, make_tuple, function_entry and
return ops. This rewrite is required in order to convert functional form
control flow v2 nodes 'StatelessIf' and 'If'.
Parameters
----------
tf_ssa: NetworkEnsemble
An object that contains multiple functions / sub-graphs.
fn: SSAFunction
Function that contains graph to operate on.
Examples
--------
Input:
Before pass "main" graph:
[const/greater/y] ---------\
[placeholder/args_0] -> [greater] -> [if] -> [identity]
\------------------/ \--> [identity]
[placeholder/args_1] ----------------/
Before pass "then" graph:
[const/sub/y] ---------------\
[placeholder/sub_args_0] -> [sub]
[placeholder/sub_args_1] -> [identity]
Before pass "else" graph:
[const/add/y] ---------------\
[placeholder/add_args_0] -> [add]
[const/mul/y] ---------------\
[placeholder/add_args_1] -> [mul]
Output:
After pass "main" graph:
[const/greater/y] ---------\
[placeholder/args_0] -> [greater] -> [make_tuple] -> [if] -> [get_tuple] -> [identity]
\---------------------/ \--> [get_tuple] -> [identity]
[placeholder/args_1] -------------------/
After pass "then" graph:
[const/sub/y] ---------------\
[entry] -> [get_tuple] -> [placeholder/sub_args_0] -> [sub] -> [make_tuple] -> [return]
-> [get_tuple] -> [placeholder/sub_args_1] -----------------/
After pass "else" graph:
[const/add/y] ---------------\
[entry] -> [get_tuple] -> [placeholder/add_args_0] -> [add] -> [make_tuple] -> [return]
-> [get_tuple] -> [placeholder/add_args_1] -> [mul] --------/
[const/mul/y] ---------------/
"""
for cond_name, cond_node in fn.graph.copy().items():
if cond_node.op not in {"StatelessIf", "If"}:
continue
then_fn_name = cond_node.attr.get("then_branch")
else_fn_name = cond_node.attr.get("else_branch")
msg = "Rewriting '{}' ({}) sub-graphs: then '{}', else '{}'"
logging.info(
msg.format(cond_node.name, cond_node.op, then_fn_name,
else_fn_name))
then_fn = tf_ssa.functions.get(then_fn_name)
else_fn = tf_ssa.functions.get(else_fn_name)
# insert function entry nodes
then_entry = _insert_function_entry(then_fn)
else_entry = _insert_function_entry(else_fn)
# pack node inputs to a single tuple
cond_input = _insert_make_tuple(fn, "make_tuple/{}".format(cond_name))
for ci in cond_node.inputs:
disconnect_edge(fn.graph, ci, cond_node.name)
connect_edge(fn.graph, ci, cond_input)
connect_edge(fn.graph, cond_input, cond_node.name)
# unpack node outputs to multiple get_tuples
for i, co in enumerate(cond_node.outputs):
# utilize FunctionDef's ret to make sure function outputs and
# node outputs order matches when multiple outputs are there.
# Fallback to use original cond_node.outputs order if fails.
o_original = fn.graph[co].original_node
if o_original:
c_input = [
n for n in o_original.input if str(n).startswith(cond_name)
][0]
if ":" in c_input:
identity_postfix = "identity_{}".format(
c_input.split(":")[-1])
else: # access identity "0"
identity_postfix = "identity"
identity_keys = [
t for t in then_fn.ret.keys()
if t.endswith(identity_postfix)
]
if len(identity_keys) != 1:
raise NotImplementedError("Branch not found.")
mapped_name = then_fn.ret[identity_keys[0]].split(":")[0]
if mapped_name in then_fn.outputs:
idx = then_fn.outputs.index(mapped_name)
else: # in else_fn.outputs
idx = else_fn.outputs.index(mapped_name)
else:
idx = i
cond_output = _insert_get_tuple(
fn, "get_tuple/{}/{}".format(idx, cond_name), idx)
edge_idx = fn.graph[co].inputs.index(cond_node.name)
replace_dest(fn.graph, cond_node, co, cond_output)
connect_edge_at_index(fn.graph, cond_output, co, edge_idx)
# fetch inputs using get_tuple for then branch
for i, ti in enumerate(then_fn.inputs):
then_input = _insert_get_tuple(then_fn,
"get_tuple/{}/{}".format(i,
ti), i + 1)
connect_edge(then_fn.graph, then_entry, then_input)
replace_node(then_fn.graph, ti, then_input)
delete_node(then_fn.graph, ti)
# fetch inputs using get_tuple for else branch
for i, ei in enumerate(else_fn.inputs):
else_input = _insert_get_tuple(else_fn,
"get_tuple/{}/{}".format(i,
ei), i + 1)
connect_edge(else_fn.graph, else_entry, else_input)
replace_node(else_fn.graph, ei, else_input)
delete_node(else_fn.graph, ei)
# returns a tuple of value(s) as output for then branch
then_output = _insert_make_tuple(then_fn)
for to in then_fn.outputs:
if to not in then_fn.graph.keys():
# from identity, map back to get_tuple node
to = "get_tuple/{}/{}".format(then_fn.inputs.index(to), to)
connect_edge(then_fn.graph, to, then_output.name)
then_return = _insert_return(then_fn)
connect_edge(then_fn.graph, then_output.name, then_return.name)
# returns a tuple of value(s) as output for else branch
else_output = _insert_make_tuple(else_fn)
for eo in else_fn.outputs:
if eo not in else_fn.graph.keys():
# from identity, map back to get_tuple node
eo = "get_tuple/{}/{}".format(else_fn.inputs.index(eo), eo)
connect_edge(else_fn.graph, eo, else_output.name)
else_return = _insert_return(else_fn)
connect_edge(else_fn.graph, else_output.name, else_return.name)