def _matchaxis_symbolic_zeros(sz, name, src, dst, x, sum_match=False):
# Just like `matchaxis`, but handles symbolic zeros using ad_util.py
if isinstance(x, Zero):
if src == dst:
return x
elif type(src) == type(dst) == int:
aval = core.mapped_aval(sz, src, x.aval)
return Zero(core.unmapped_aval(sz, name, dst, aval))
elif src is not_mapped and dst is not not_mapped:
return Zero(core.unmapped_aval(sz, name, dst, x.aval))
elif dst is not_mapped and sum_match:
return Zero(core.mapped_aval(sz, src, x.aval))
else:
raise ValueError((x, src, dst))
else:
return matchaxis(sz, src, dst, x, sum_match=sum_match)
def _flatten_bwd(in_tree, in_avals, out_trees, *args):
out_tree, res_tree = out_trees()
assert len(args) == res_tree.num_leaves + out_tree.num_leaves
res, cts_out = split_list(args, [res_tree.num_leaves])
py_res = tree_unflatten(res_tree, res)
py_cts_out = tree_unflatten(out_tree, cts_out)
py_cts_in = yield (py_res, py_cts_out), {}
# For each None in py_cts_in, indicating an argument for which the rule
# produces no cotangent, we replace it with a pytree with the structure of the
# corresponding subtree of in_tree and with leaves of a non-pytree sentinel
# object, to be replaced with Nones in the final returned result.
zero = object() # non-pytree sentinel to replace Nones in py_cts_in
dummy = tree_unflatten(in_tree, [object()] * in_tree.num_leaves)
cts_in_flat = []
append = lambda x, d: cts_in_flat.extend([x] * len(tree_flatten(d)[0])) or x
try:
if not isinstance(py_cts_in, tuple):
raise ValueError
tree_map(append,
tuple(zero if ct is None else ct for ct in py_cts_in), dummy)
except ValueError:
_, in_tree2 = tree_flatten(py_cts_in)
msg = ("Custom VJP rule must produce an output with the same container "
"(pytree) structure as the args tuple of the primal function, "
"and in particular must produce a tuple of length equal to the "
"number of arguments to the primal function, but got VJP output "
"structure {} for primal input structure {}.")
raise TypeError(msg.format(in_tree2, in_tree)) from None
# Ignore any None cotangents, and any corresponding to inputs for which the
# type doesn't equal the tangent type (i.e. float0s)
# TODO(mattjj): change this to check if tangent type represents 0dim vspace
yield [Zero(a.at_least_vspace()) if ct is zero or a != a.at_least_vspace()
else ct for a, ct in zip(in_avals, cts_in_flat)]
def unmap_zero(zero, in_axis):
return (zero if in_axis is None else
Zero(core.unmapped_aval(params['axis_size'], params['axis_name'], in_axis, zero.aval)))
def lift(self, val): tangent_zero = Zero(get_aval(val).at_least_vspace()) return JVPTracer(self, val, tangent_zero)
def read_cotangent(v): return ct_env.pop(v, Zero(v.aval))
def backward_pass(jaxpr: core.Jaxpr, reduce_axes, transform_stack,
consts, primals_in, cotangents_in):
if all(type(ct) is Zero for ct in cotangents_in):
return map(lambda v: Zero(v.aval), jaxpr.invars)
def write_cotangent(prim, v, ct):
# assert v not in primal_env
assert ct is not Zero, (prim, v.aval) # check for an old harmless type error
if ct is None or type(v) is Literal:
return
if type(ct) is Zero:
# FIXME: This triggers a lot of failures!
# assert v.aval == ct.aval, (prim, v.aval, ct.aval)
return
axes_to_reduce = tuple(axis_name for axis_name in reduce_axes
if axis_name in core.get_aval(ct).named_shape
and axis_name not in v.aval.named_shape)
if axes_to_reduce:
ct = jax.lax.psum(ct, axis_name=axes_to_reduce)
ct_env[v] = add_tangents(ct_env[v], ct) if v in ct_env else ct
if config.jax_enable_checks:
ct_aval = core.get_aval(ct_env[v])
joined_aval = core.lattice_join(v.aval, ct_aval).strip_weak_type().strip_named_shape()
assert v.aval.strip_weak_type().strip_named_shape() == joined_aval, (prim, v.aval, ct_aval)
def read_cotangent(v):
return ct_env.pop(v, Zero(v.aval))
def read_primal(v):
if type(v) is Literal:
return v.val
else:
return primal_env.get(v, UndefinedPrimal(v.aval))
def write_primal(v, val):
if not is_undefined_primal(val):
primal_env[v] = val
primal_env: Dict[Any, Any] = {}
write_primal(core.unitvar, core.unit)
map(write_primal, jaxpr.constvars, consts)
# FIXME: invars can contain both primal and tangent values, and this line
# forces primal_in to contain UndefinedPrimals for tangent values!
map(write_primal, jaxpr.invars, primals_in)
ct_env: Dict[Any, Any] = {}
ctx = (source_info_util.transform_name_stack('transpose') if transform_stack
else contextlib.nullcontext())
with ctx:
map(partial(write_cotangent, 'outvars'), jaxpr.outvars, cotangents_in)
for eqn in jaxpr.eqns[::-1]:
# FIXME: Some invars correspond to tangents
invals = map(read_primal, eqn.invars)
if eqn.primitive.multiple_results:
cts_in = map(read_cotangent, eqn.outvars)
else:
cts_in, = map(read_cotangent, eqn.outvars)
name_stack = source_info_util.current_name_stack() + eqn.source_info.name_stack
with source_info_util.user_context(eqn.source_info.traceback, name_stack=name_stack):
if eqn.primitive.call_primitive or eqn.primitive.map_primitive:
cts_in_avals = [v.aval for v in eqn.outvars]
params = dict(eqn.params)
call_jaxpr = params.pop('call_jaxpr')
cts_out = get_primitive_transpose(eqn.primitive)(
params, call_jaxpr, invals, cts_in, cts_in_avals, reduce_axes)
elif eqn.primitive in reducing_transposes:
cts_out = reducing_transposes[eqn.primitive](
reduce_axes, cts_in, *invals, **eqn.params)
else:
cts_out = get_primitive_transpose(eqn.primitive)(
cts_in, *invals, **eqn.params)
cts_out = [Zero(v.aval) for v in eqn.invars] if cts_out is Zero else cts_out
# FIXME: Some invars correspond to primals!
map(partial(write_cotangent, eqn.primitive), eqn.invars, cts_out)
cotangents_out = map(read_cotangent, jaxpr.invars)
return cotangents_out
def recast_to_float0(primal, tangent):
if core.primal_dtype_to_tangent_dtype(dtype(primal)) == float0:
return Zero(get_aval(primal).at_least_vspace())
else:
return tangent
def backward_pass(jaxpr: core.Jaxpr, consts, primals_in, cotangents_in):
if all(type(ct) is Zero for ct in cotangents_in):
return map(lambda v: Zero(v.aval), jaxpr.invars)
def write_cotangent(prim, v, ct):
# assert v not in primal_env
assert ct is not Zero, (prim, v.aval
) # check for an old harmless type error
if ct is None or type(v) is Literal:
return
if type(ct) is Zero:
# FIXME: This triggers a lot of failures!
# assert v.aval == ct.aval, (prim, v.aval, ct.aval)
return
ct_env[v] = add_tangents(ct_env[v], ct) if v in ct_env else ct
if config.jax_enable_checks:
ct_aval = core.get_aval(ct_env[v])
joined_aval = core.lattice_join(
v.aval, ct_aval).strip_weak_type().strip_named_shape()
assert v.aval.strip_weak_type().strip_named_shape(
) == joined_aval, (prim, v.aval, ct_aval)
def read_cotangent(v):
return ct_env.pop(v, Zero(v.aval))
def read_primal(v):
if type(v) is Literal:
return v.val
else:
return primal_env.get(v, UndefinedPrimal(v.aval))
def write_primal(v, val):
if not is_undefined_primal(val):
primal_env[v] = val
primal_env: Dict[Any, Any] = {}
write_primal(core.unitvar, core.unit)
map(write_primal, jaxpr.constvars, consts)
# FIXME: invars can contain both primal and tangent values, and this line
# forces primal_in to contain UndefinedPrimals for tangent values!
map(write_primal, jaxpr.invars, primals_in)
ct_env: Dict[Any, Any] = {}
map(partial(write_cotangent, 'outvars'), jaxpr.outvars, cotangents_in)
for eqn in jaxpr.eqns[::-1]:
# FIXME: Some invars correspond to tangents
invals = map(read_primal, eqn.invars)
if eqn.primitive.multiple_results:
cts_in = map(read_cotangent, eqn.outvars)
else:
cts_in, = map(read_cotangent, eqn.outvars)
with source_info_util.user_context(eqn.source_info):
if eqn.primitive.call_primitive or eqn.primitive.map_primitive:
cts_in_avals = [v.aval for v in eqn.outvars]
call_jaxpr, params = core.extract_call_jaxpr(
eqn.primitive, eqn.params)
cts_out = get_primitive_transpose(eqn.primitive)(params,
call_jaxpr,
invals,
cts_in,
cts_in_avals)
else:
cts_out = get_primitive_transpose(eqn.primitive)(cts_in,
*invals,
**eqn.params)
cts_out = [Zero(v.aval)
for v in eqn.invars] if cts_out is Zero else cts_out
# FIXME: Some invars correspond to primals!
map(partial(write_cotangent, eqn.primitive), eqn.invars, cts_out)
cotangents_out = map(read_cotangent, jaxpr.invars)
return cotangents_out