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# mypy: allow-untyped-defs
import operator
from typing import List
import torch
from torch._higher_order_ops.effects import _get_schema, with_effects
from .exported_program import ExportedProgram
from .graph_signature import (
CustomObjArgument,
InputKind,
InputSpec,
OutputKind,
OutputSpec,
TokenArgument,
)
def _remove_effect_tokens_from_graph_helper(
ep, num_tokens, input_token_names, output_token_names
):
inputs_to_lifted_custom_objs = ep.graph_signature.inputs_to_lifted_custom_objs
output_node = None
with_effect_nodes: List[torch.fx.Node] = []
# Output node need to check its args agianst output_token_names (collected from output_spec)
# Therefore, we only need to find the top-levele output node
output_node = next(reversed(ep.graph_module.graph.find_nodes(op="output")))
for module in ep.graph_module.modules():
if not isinstance(module, torch.fx.GraphModule):
continue
for node in module.graph.nodes:
if not (node.op == "call_function" and node.target is with_effects):
continue
with_effect_nodes.append(node)
# Remove tokens from outputs
assert output_node is not None
output_args = output_node.args[0]
assert len(output_args) >= num_tokens
out_token_nodes = output_args[:num_tokens]
output_node.args = (tuple(output_args[num_tokens:]),)
for out_token in out_token_nodes:
assert out_token.name in output_token_names
out_token.users.clear()
ep.graph.erase_node(out_token)
# Replace with_effects(token, func, args) with just func(args)
for node in reversed(with_effect_nodes):
func = node.args[1]
assert isinstance(func, (torch._ops.OpOverload, torch._ops.HigherOrderOperator))
if func == torch.ops.higher_order.call_torchbind:
custom_obj_meta = node.args[2].meta["val"]
assert isinstance(custom_obj_meta, CustomObjArgument)
if custom_obj_meta.fake_val:
custom_obj = custom_obj_meta.fake_val
elif node.args[2].name in inputs_to_lifted_custom_objs:
custom_obj = ep.constants[
inputs_to_lifted_custom_objs[node.args[2].name]
]
else:
raise RuntimeError(f"Unable to find custom obj for node {node}")
schema = _get_schema(func, (custom_obj,) + node.args[3:])
else:
schema = _get_schema(func, node.args[2:])
with ep.graph.inserting_before(node):
new_node = ep.graph.call_function(func, node.args[2:], node.kwargs)
for k, v in node.meta.items():
new_node.meta[k] = v
node.replace_all_uses_with(new_node)
# Update user getitem nodes
for user in list(new_node.users.keys()):
assert user.target == operator.getitem
# getitem(with_effects, 0) == token
if user.args[1] == 0:
ep.graph.erase_node(user)
if len(schema.returns) == 1:
# If the function has 1 return then it will just directly return the
# result -- we don't need a getitem. So we can replace all the
# getitem(with_effects, 1) with just the note itself.
for user in list(new_node.users.keys()):
assert user.args[1] == 1
user.replace_all_uses_with(new_node)
new_node.meta["val"] = node.meta["val"][1]
elif len(schema.returns) > 1:
# If the function has more than 1 return then since we got rid of
# the 1st return value (the token), we need to bump all the other
# getitem calls by 1 down
for user in list(new_node.users.keys()):
assert user.args[1] >= 1
user.args = (user.args[0], user.args[1] - 1)
new_node.meta["val"] = node.meta["val"][1:]
else:
assert len(schema.returns) == 0
assert len(new_node.users) == 0
new_node.meta["val"] = None
ep.graph.erase_node(node)
# Remove tokens from inputs
placeholders = [node for node in ep.graph.nodes if node.op == "placeholder"]
assert len(placeholders) >= num_tokens
inp_token_nodes = placeholders[:num_tokens]
for inp_token in inp_token_nodes:
assert inp_token.name in input_token_names
ep.graph.erase_node(inp_token)
ep.graph.eliminate_dead_code()
def _remove_effect_tokens(ep: ExportedProgram) -> ExportedProgram:
"""
Removes the existance of tokens from the exported program, including:
- Removes the input and output tokens
- Replaces with_effects(token, func, args) with just func(args)
This function does an inplace modification on the given ExportedProgram.
"""
num_tokens: int = 0
input_token_names: List[str] = []
new_input_specs: List[InputSpec] = []
for inp in ep.graph_signature.input_specs:
if inp.kind == InputKind.TOKEN:
num_tokens += 1
assert isinstance(inp.arg, TokenArgument)
input_token_names.append(inp.arg.name)
else:
new_input_specs.append(inp)
num_out_tokens: int = 0
new_output_specs: List[OutputSpec] = []
output_token_names: List[OutputSpec] = []
for out in ep.graph_signature.output_specs:
if out.kind == OutputKind.TOKEN:
num_out_tokens += 1
output_token_names.append(out.arg.name)
else:
new_output_specs.append(out)
# Update graph signature
ep.graph_signature.input_specs = new_input_specs
ep.graph_signature.output_specs = new_output_specs
assert num_tokens == num_out_tokens
with ep.graph_module._set_replace_hook(ep.graph_signature.get_replace_hook()):
_remove_effect_tokens_from_graph_helper(
ep, num_tokens, input_token_names, output_token_names
)
return ep
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