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Fix complex vjps for the inverse trig and hyperbolic ops #3779

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Fix complex vjps for the inverse trig and hyperbolic ops #3779

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30 changes: 24 additions & 6 deletions mlx/primitives.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -390,7 +390,10 @@ std::vector<array> ArcCos::vjp(
const std::vector<array>& cotangents,
const std::vector<int>& argnums,
const std::vector<array>&) {
return jvp(primals, cotangents, argnums);
// The vjp conjugates the jvp's multiplier (a no-op for real inputs).
return {conjugate(
jvp(primals, {conjugate(cotangents[0], stream())}, argnums)[0],
stream())};
}

std::vector<array> ArcCos::jvp(
Expand Down Expand Up @@ -418,7 +421,10 @@ std::vector<array> ArcCosh::vjp(
const std::vector<array>& cotangents,
const std::vector<int>& argnums,
const std::vector<array>&) {
return jvp(primals, cotangents, argnums);
// The vjp conjugates the jvp's multiplier (a no-op for real inputs).
return {conjugate(
jvp(primals, {conjugate(cotangents[0], stream())}, argnums)[0],
stream())};
}

std::vector<array> ArcCosh::jvp(
Expand All @@ -445,7 +451,10 @@ std::vector<array> ArcSin::vjp(
const std::vector<array>& cotangents,
const std::vector<int>& argnums,
const std::vector<array>&) {
return jvp(primals, cotangents, argnums);
// The vjp conjugates the jvp's multiplier (a no-op for real inputs).
return {conjugate(
jvp(primals, {conjugate(cotangents[0], stream())}, argnums)[0],
stream())};
}

std::vector<array> ArcSin::jvp(
Expand All @@ -472,7 +481,10 @@ std::vector<array> ArcSinh::vjp(
const std::vector<array>& cotangents,
const std::vector<int>& argnums,
const std::vector<array>&) {
return jvp(primals, cotangents, argnums);
// The vjp conjugates the jvp's multiplier (a no-op for real inputs).
return {conjugate(
jvp(primals, {conjugate(cotangents[0], stream())}, argnums)[0],
stream())};
}

std::vector<array> ArcSinh::jvp(
Expand All @@ -499,7 +511,10 @@ std::vector<array> ArcTan::vjp(
const std::vector<array>& cotangents,
const std::vector<int>& argnums,
const std::vector<array>&) {
return jvp(primals, cotangents, argnums);
// The vjp conjugates the jvp's multiplier (a no-op for real inputs).
return {conjugate(
jvp(primals, {conjugate(cotangents[0], stream())}, argnums)[0],
stream())};
}

std::vector<array> ArcTan::jvp(
Expand Down Expand Up @@ -587,7 +602,10 @@ std::vector<array> ArcTanh::vjp(
const std::vector<array>& cotangents,
const std::vector<int>& argnums,
const std::vector<array>&) {
return jvp(primals, cotangents, argnums);
// The vjp conjugates the jvp's multiplier (a no-op for real inputs).
return {conjugate(
jvp(primals, {conjugate(cotangents[0], stream())}, argnums)[0],
stream())};
}

std::vector<array> ArcTanh::jvp(
Expand Down
25 changes: 25 additions & 0 deletions python/tests/test_autograd.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1388,6 +1388,31 @@ def test_complex_unary_vjps(self):
expected = cotangent * mx.conj(deriv(z))
self.assertTrue(mx.allclose(vjp, expected, atol=1e-5), msg=str(fn))

def test_complex_inverse_trig_vjps(self):
# Same conjugate fix for the inverse trig / hyperbolic ops. Use small
# magnitudes to stay away from the branch cuts.
mx.random.seed(0)
z = 0.3 * mx.random.normal((3, 4, 5), dtype=mx.complex64)
cotangent = mx.random.normal((3, 4, 5), dtype=mx.complex64)

ops = {
mx.arcsin: lambda x: 1 / mx.sqrt(1 - x**2),
mx.arccos: lambda x: -1 / mx.sqrt(1 - x**2),
mx.arctan: lambda x: 1 / (1 + x**2),
mx.arcsinh: lambda x: 1 / mx.sqrt(1 + x**2),
mx.arctanh: lambda x: 1 / (1 - x**2),
}
for fn, deriv in ops.items():
_, (vjp,) = mx.vjp(fn, [z], [cotangent])
expected = cotangent * mx.conj(deriv(z))
self.assertTrue(mx.allclose(vjp, expected, atol=1e-5), msg=str(fn))

# arccosh's branch cut is on (-inf, 1]; evaluate to the right of it.
zc = 1.5 + 0.3 * mx.random.normal((3, 4, 5), dtype=mx.complex64)
_, (vjp,) = mx.vjp(mx.arccosh, [zc], [cotangent])
expected = cotangent * mx.conj(1 / mx.sqrt(zc**2 - 1))
self.assertTrue(mx.allclose(vjp, expected, atol=1e-5))

def test_complex_abs_grad(self):
mx.random.seed(0)
primal = mx.random.normal((3, 4, 5), dtype=mx.complex64)
Expand Down