def test_match_with_resolver(self):
# Test matching with a resolver function
# This is a contrived resolver which combines the A... and
# B typevars in a way that cannot be done with simple pattern
# matching. While not a useful example in and of itself, it
# exhibits the needed behavior in reduction function signature
# matching.
def resolver(tvar, tvdict):
if tvar == T.Ellipsis(T.TypeVar('R')):
a = tvdict[T.Ellipsis(T.TypeVar('A'))]
b = tvdict[T.TypeVar('B')]
result = [b]
for x in a:
result.extend([x, b])
return result
elif tvar == T.TypeVar('T'):
return T.int16
at = dshape('(5 * int32, 4 * float64)')
sig = dshape('(B * int32, A... * float64) -> R... * T')
self.assertEqual(match_argtypes_to_signature(at, sig, resolver),
(dshape('(5 * int32, 4 * float64) -> 5 * 4 * 5 * int16')[0],
0.25))
at = dshape('(5 * var * 2 * int32, 4 * float64)')
sig = dshape('(A... * int32, B * float64) -> R... * 2 * T')
self.assertEqual(match_argtypes_to_signature(at, sig, resolver),
(dshape('(5 * var * 2 * int32, 4 * float64) ->' +
' 4 * 5 * 4 * var * 4 * 2 * 4 * 2 * int16')[0],
0.25))
def test_match_with_resolver(self):
# Test matching with a resolver function
# This is a contrived resolver which combines the A... and
# B typevars in a way that cannot be done with simple pattern
# matching. While not a useful example in and of itself, it
# exhibits the needed behavior in reduction function signature
# matching.
def resolver(tvar, tvdict):
if tvar == T.Ellipsis(T.TypeVar('R')):
a = tvdict[T.Ellipsis(T.TypeVar('A'))]
b = tvdict[T.TypeVar('B')]
result = [b]
for x in a:
result.extend([x, b])
return result
elif tvar == T.TypeVar('T'):
return T.int16
at = dshape('(5 * int32, 4 * float64)')
sig = dshape('(B * int32, A... * float64) -> R... * T')
self.assertEqual(match_argtypes_to_signature(at, sig, resolver),
(dshape('(5 * int32, 4 * float64) -> 5 * 4 * 5 * int16')[0],
0.25))
at = dshape('(5 * var * 2 * int32, 4 * float64)')
sig = dshape('(A... * int32, B * float64) -> R... * 2 * T')
self.assertEqual(match_argtypes_to_signature(at, sig, resolver),
(dshape('(5 * var * 2 * int32, 4 * float64) ->' +
' 4 * 5 * 4 * var * 4 * 2 * 4 * 2 * int16')[0],
0.25))
def test_dshape_matches_concrete(self):
# Exact match, same signature and zero cost
at = dshape('(3 * int32, 2 * var * float64)')
sig = dshape('(3 * int32, 2 * var * float64) -> 4 * int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], 0))
# Requires broadcasting
at = dshape('(1 * int32, 2 * 4 * float64)')
sig = dshape('(3 * int32, 2 * var * float64) -> 4 * int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], max(dim_coercion_cost(T.Fixed(1), T.Fixed(3)),
dim_coercion_cost(T.Fixed(4), T.Var()))))
def test_dshape_matches_concrete(self):
# Exact match, same signature and zero cost
at = dshape('(3 * int32, 2 * var * float64)')
sig = dshape('(3 * int32, 2 * var * float64) -> 4 * int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], 0))
# Requires broadcasting
at = dshape('(1 * int32, 2 * 4 * float64)')
sig = dshape('(3 * int32, 2 * var * float64) -> 4 * int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], max(dim_coercion_cost(T.Fixed(1), T.Fixed(3)),
dim_coercion_cost(T.Fixed(4), T.Var()))))
def test_broadcast_vs_not(self):
# Single dimension type variables must match up exactly
at = dshape('(int32, float64)')
sig_scalar = dshape('(float64, float64) -> int16')
sig_bcast = dshape('(A... * float64, A... * float64) -> A... * int16')
match_scalar = match_argtypes_to_signature(at, sig_scalar)
match_bcast = match_argtypes_to_signature(at, sig_bcast)
self.assertEqual(match_scalar[0],
dshape('(float64, float64) -> int16')[0])
self.assertEqual(match_bcast[0],
dshape('(float64, float64) -> int16')[0])
# Should be cheaper to match without the broadcasting
self.assertTrue(match_scalar[1] < match_bcast[1])
def test_broadcast_vs_not(self):
# Single dimension type variables must match up exactly
at = dshape('(int32, float64)')
sig_scalar = dshape('(float64, float64) -> int16')
sig_bcast = dshape('(A... * float64, A... * float64) -> A... * int16')
match_scalar = match_argtypes_to_signature(at, sig_scalar)
match_bcast = match_argtypes_to_signature(at, sig_bcast)
self.assertEqual(match_scalar[0],
dshape('(float64, float64) -> int16')[0])
self.assertEqual(match_bcast[0],
dshape('(float64, float64) -> int16')[0])
# Should be cheaper to match without the broadcasting
self.assertTrue(match_scalar[1] < match_bcast[1])
def test_dtype_matches_typevar(self):
# Exact match, and zero cost
at = dshape('(int32, float64)')
sig = dshape('(int32, T) -> T')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(int32, float64) -> float64')[0], 0.125))
# Type promotion between the inputs
at = dshape('(int32, float64)')
sig = dshape('(T, T) -> T')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(float64, float64) -> float64')[0], 0.125))
# Type promotion between the inputs
at = dshape('(int32, bool, float64)')
sig = dshape('(T, S, T) -> S')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(float64, bool, float64) -> bool')[0], 0.125))
def test_dtype_matches_concrete(self):
# Exact match, same signature and zero cost
at = dshape('(int32, float64)')
sig = dshape('(int32, float64) -> int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], 0))
# Requires a coercion, cost is that of the coercion
at = dshape('(int32, int32)')
sig = dshape('(int32, float64) -> int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], dtype_coercion_cost(T.int32, T.float64)))
# Requires two coercions, cost is maximum of the two
at = dshape('(int16, int32)')
sig = dshape('(int32, float64) -> int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], dtype_coercion_cost(T.int32, T.float64)))
def test_dtype_matches_typevar(self):
# Exact match, and zero cost
at = dshape('(int32, float64)')
sig = dshape('(int32, T) -> T')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(int32, float64) -> float64')[0], 0.125))
# Type promotion between the inputs
at = dshape('(int32, float64)')
sig = dshape('(T, T) -> T')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(float64, float64) -> float64')[0], 0.125))
# Type promotion between the inputs
at = dshape('(int32, bool, float64)')
sig = dshape('(T, S, T) -> S')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(float64, bool, float64) -> bool')[0], 0.125))
def test_dtype_matches_concrete(self):
# Exact match, same signature and zero cost
at = dshape('(int32, float64)')
sig = dshape('(int32, float64) -> int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], 0))
# Requires a coercion, cost is that of the coercion
at = dshape('(int32, int32)')
sig = dshape('(int32, float64) -> int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], dtype_coercion_cost(T.int32, T.float64)))
# Requires two coercions, cost is maximum of the two
at = dshape('(int16, int32)')
sig = dshape('(int32, float64) -> int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(sig[0], dtype_coercion_cost(T.int32, T.float64)))
def test_dshape_matches_typevar(self):
# Arrays with matching size
at = dshape('(5 * int32, 5 * float64)')
sig = dshape('(N * int32, N * float64) -> N * int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(5 * int32, 5 * float64) -> 5 * int16')[0],
0.125))
# Matrix multiplication
at = dshape('(3 * 5 * float64, 5 * 6 * float32)')
sig = dshape('(M * N * A, N * R * A) -> M * R * A')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(3 * 5 * float64, 5 * 6 * float64) ->' +
' 3 * 6 * float64')[0], 0.375))
# Broadcasted matrix multiplication
at = dshape('(20 * 3 * 5 * float64, 3 * 1 * 5 * 6 * float32)')
sig = dshape('(Dims... * M * N * A, Dims... * N * R * A) ->' +
' Dims... * M * R * A')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(20 * 3 * 5 * float64,' +
' 3 * 1 * 5 * 6 * float64) ->' +
' 3 * 20 * 3 * 6 * float64')[0], 0.625))
def test_dshape_matches_typevar(self):
# Arrays with matching size
at = dshape('(5 * int32, 5 * float64)')
sig = dshape('(N * int32, N * float64) -> N * int16')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(5 * int32, 5 * float64) -> 5 * int16')[0],
0.125))
# Matrix multiplication
at = dshape('(3 * 5 * float64, 5 * 6 * float32)')
sig = dshape('(M * N * A, N * R * A) -> M * R * A')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(3 * 5 * float64, 5 * 6 * float64) ->' +
' 3 * 6 * float64')[0], 0.375))
# Broadcasted matrix multiplication
at = dshape('(20 * 3 * 5 * float64, 3 * 1 * 5 * 6 * float32)')
sig = dshape('(Dims... * M * N * A, Dims... * N * R * A) ->' +
' Dims... * M * R * A')
self.assertEqual(match_argtypes_to_signature(at, sig),
(dshape('(20 * 3 * 5 * float64,' +
' 3 * 1 * 5 * 6 * float64) ->' +
' 3 * 20 * 3 * 6 * float64')[0], 0.625))
def test_tv_matches_struct(self):
at = dshape('(3 * {x: int, y: string}, 3 * bool)')
sig = dshape('(M * T, M * bool) -> var * T')
match = match_argtypes_to_signature(at, sig)
self.assertEqual(match[0],
dshape('(3 * {x: int, y: string}, 3 * bool) -> var * {x: int, y: string}')[0])
