def __call__(self, *args: Any, **kwargs: Any) -> ReturnValue:
if not self.fwd or not self.bwd:
msg = "No VJP defined for custom_vjp function {} using defvjp."
raise AttributeError(msg.format(self.__name__))
args = _resolve_kwargs(self.fun, args, kwargs)
if self.nondiff_argnums:
for i in self.nondiff_argnums:
_check_for_tracers(args[i])
nondiff_argnums = set(self.nondiff_argnums)
dyn_argnums = [
i for i in range(len(args)) if i not in nondiff_argnums
]
f_, dyn_args = argnums_partial(lu.wrap_init(self.fun), dyn_argnums,
args)
static_args = [args[i] for i in self.nondiff_argnums]
fwd, _ = argnums_partial(lu.wrap_init(self.fwd), dyn_argnums, args)
bwd = _add_args(lu.wrap_init(self.bwd), static_args)
else:
f_, dyn_args = lu.wrap_init(self.fun), args
fwd, bwd = lu.wrap_init(self.fwd), lu.wrap_init(self.bwd)
args_flat, in_tree = tree_flatten(dyn_args)
in_avals = [core.raise_to_shaped(core.get_aval(x)) for x in args_flat]
flat_fun, out_tree = flatten_fun_nokwargs(f_, in_tree)
flat_fwd, out_trees = _flatten_fwd(fwd, in_tree)
flat_bwd = _flatten_bwd(bwd, in_tree, in_avals, out_trees)
out_flat = custom_vjp_call_p.bind(flat_fun,
flat_fwd,
flat_bwd,
*args_flat,
out_trees=out_trees)
fst, aux = lu.merge_linear_aux(out_tree, out_trees)
out_tree = aux if fst else aux[0]
return tree_unflatten(out_tree, out_flat)
def __call__(self, *args: Any, **kwargs: Any) -> ReturnValue: # pytype: disable=invalid-annotation
if not self.jvp:
msg = "No JVP defined for custom_jvp function {} using defjvp."
raise AttributeError(msg.format(self.__name__))
args = _resolve_kwargs(self.fun, args, kwargs)
if self.nondiff_argnums:
nondiff_argnums = set(self.nondiff_argnums)
args = tuple(
_stop_gradient(x) if i in nondiff_argnums else x
for i, x in enumerate(args))
diff_argnums = [
i for i in range(len(args)) if i not in nondiff_argnums
]
f_, dyn_args = argnums_partial(lu.wrap_init(self.fun),
diff_argnums,
args,
require_static_args_hashable=False)
static_args = [args[i] for i in self.nondiff_argnums]
jvp = _add_args(lu.wrap_init(self.jvp), static_args)
else:
f_, dyn_args = lu.wrap_init(self.fun), args
jvp = lu.wrap_init(self.jvp)
args_flat, in_tree = tree_flatten(dyn_args)
flat_fun, out_tree1 = flatten_fun_nokwargs(f_, in_tree)
flat_jvp, out_tree2 = _flatten_jvp(jvp, in_tree)
out_flat = custom_jvp_call_p.bind(flat_fun, flat_jvp, *args_flat)
_, out_tree = lu.merge_linear_aux(out_tree1, out_tree2)
return tree_unflatten(out_tree, out_flat)
def process_custom_jvp_call(self, prim, fun, jvp, tracers):
in_vals = [t.val for t in tracers]
e = popattr(self.main, 'error')
msgs = tuple(e.msgs.items())
fun, msgs1 = checkify_subtrace(fun, self.main, msgs)
jvp, msgs2 = checkify_custom_jvp_subtrace(jvp, self.main, msgs)
err, code, *out_vals = prim.bind(fun, jvp, e.err, e.code, *in_vals)
fst, out_msgs = lu.merge_linear_aux(msgs1, msgs2)
setattr(self.main, 'error', Error(err, code, out_msgs))
return [CheckifyTracer(self, x) for x in out_vals]
def process_custom_jvp_call(self, prim, fun, jvp, tracers):
in_vals, in_dims = unzip2((t.val, t.batch_dim) for t in tracers)
fun, out_dims1 = batch_subtrace(fun, self.main, in_dims)
jvp, out_dims2 = batch_custom_jvp_subtrace(jvp, self.main, in_dims)
out_vals = prim.bind(fun, jvp, *in_vals)
fst, out_dims = lu.merge_linear_aux(out_dims1, out_dims2)
if not fst:
assert out_dims == out_dims[:len(out_dims) // 2] * 2
out_dims = out_dims[:len(out_dims) // 2]
return [BatchTracer(self, v, d) for v, d in zip(out_vals, out_dims)]
def bind(self, fun, jvp, *args):
args = map(core.full_lower, args)
top_trace = core.find_top_trace(args)
fun, env_trace_todo1 = core.process_env_traces(
fun, self, top_trace and top_trace.level, (), None)
jvp, env_trace_todo2 = core.process_env_traces(
jvp, self, top_trace and top_trace.level, (), None)
tracers = map(top_trace.full_raise, args) # type: ignore
outs = top_trace.process_custom_jvp_call(self, fun, jvp, tracers) # type: ignore
_, env_trace_todo = lu.merge_linear_aux(env_trace_todo1, env_trace_todo2)
return _apply_todos(env_trace_todo, map(core.full_lower, outs))
def process_custom_vjp_call(self, prim, fun, fwd, bwd, tracers, *, out_trees):
in_vals, in_dims = unzip2((t.val, t.batch_dim) for t in tracers)
axis_size, = {x.shape[d] for x, d in zip(in_vals, in_dims)
if d is not not_mapped}
fun, out_dims1 = batch_subtrace(fun, self.main, in_dims)
fwd, out_dims2 = batch_subtrace(fwd, self.main, in_dims)
bwd = batch_custom_vjp_bwd(bwd, self.axis_name, axis_size,
out_dims2, in_dims, self.main.trace_type)
out_vals = prim.bind(fun, fwd, bwd, *in_vals, out_trees=out_trees)
fst, out_dims = lu.merge_linear_aux(out_dims1, out_dims2)
if not fst:
out_dims = out_dims[-len(out_vals) % len(out_dims):]
src = source_info_util.current()
return [BatchTracer(self, v, d, src) for v, d in zip(out_vals, out_dims)]
def bind(self, fun, fwd, bwd, *args, out_trees):
args = map(core.full_lower, args)
top_trace = core.find_top_trace(args)
fun, env_trace_todo1 = core.process_env_traces(
fun, self, top_trace and top_trace.level, (), None)
fwd, env_trace_todo2 = core.process_env_traces(
fwd, self, top_trace and top_trace.level, (), None)
tracers = map(top_trace.full_raise, args) # type: ignore
with core.maybe_new_sublevel(top_trace):
outs = top_trace.process_custom_vjp_call(self,
fun,
fwd,
bwd,
tracers,
out_trees=out_trees)
_, env_trace_todo = lu.merge_linear_aux(env_trace_todo1,
env_trace_todo2)
return _apply_todos(env_trace_todo, map(core.full_lower, outs))
def bind(self, fun, fwd, bwd, *args, out_trees):
args = map(core.full_lower, args)
top_trace = core.find_top_trace(args)
fun, env_trace_todo1 = process_env_traces(
fun, self, top_trace and top_trace.level, False)
fwd, env_trace_todo2 = process_env_traces_fwd(
fwd, top_trace and top_trace.level, out_trees)
tracers = map(top_trace.full_raise, args) # type: ignore
bwd_ = lu.wrap_init(lambda *args: bwd.call_wrapped(*args))
outs = top_trace.process_custom_vjp_call(self, fun, fwd, bwd_, tracers,
out_trees=out_trees)
fst, env_trace_todo = lu.merge_linear_aux(env_trace_todo1, env_trace_todo2)
if fst:
return _apply_todos(env_trace_todo, map(core.full_lower, outs))
else:
env_trace_todo, bwd_transform = env_trace_todo
bwd = _apply_bwd_transform(bwd_transform, bwd)
return _apply_todos(env_trace_todo, map(core.full_lower, outs))
def process_custom_vjp_call(self, prim, fun, fwd, bwd, tracers, out_trees):
in_vals = [t.val for t in tracers]
e = popattr(self.main, 'error')
msgs = tuple(e.msgs.items())
fun, msgs1 = checkify_subtrace(fun, self.main, msgs)
fwd, msgs2 = checkify_custom_vjp_subtrace(fwd, self.main, msgs)
out = prim.bind(fun,
fwd,
bwd,
e.err,
e.code,
*in_vals,
out_trees=out_trees)
fst, out_msgs = lu.merge_linear_aux(msgs1, msgs2)
if fst:
err, code, *out = out
else:
err, code = e.err, e.code # forward input error values to output
setattr(self.main, 'error', Error(err, code, out_msgs))
return [CheckifyTracer(self, x) for x in out]
