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test_ops sinh/cosh/asinh/acosh/atanh (#3294)

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some have numerical issues at large input similar to sigmoid
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chenyu
2024-02-01 03:10:11 -05:00
committed by GitHub
parent 927f2dd24d
commit 9196b11dfb
1 changed files with 31 additions and 7 deletions
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38
test/test_ops.py
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@@ -23,13 +23,13 @@ def helper_test_op(shps, torch_fxn, tinygrad_fxn=None, atol=1e-6, rtol=1e-3, gra
ret = tinygrad_fxn(*tst).realize()
tinygrad_fp = time.monotonic() - st
def compare(s, x,y,atol,rtol):
if PRINT_TENSORS: print(s, x, y)
assert x.shape == y.shape, f"shape mismatch: tinygrad={x.shape} | torch={y.shape}"
def compare(s, tinygrad_output, torch_output, atol, rtol):
if PRINT_TENSORS: print(s, tinygrad_output, torch_output)
assert tinygrad_output.shape == torch_output.shape, f"shape mismatch: tinygrad={tinygrad_output.shape} | torch={torch_output.shape}"
try:
np.testing.assert_allclose(x,y, atol=atol, rtol=rtol)
except Exception:
raise Exception(f"{s} failed shape {x.shape}")
np.testing.assert_allclose(tinygrad_output, torch_output, atol=atol, rtol=rtol)
except Exception as e:
raise Exception(f"{s} failed shape {tinygrad_output.shape}: {e}")
if DEBUG >= 6:
np.set_printoptions(linewidth=200, suppress=True)
@@ -707,14 +707,38 @@ class TestOps(unittest.TestCase):
helper_test_op([(10,10,10)], lambda x: x.log_softmax(1), atol=1e-7, grad_atol=1e-7)
helper_test_op([(10,10,10)], lambda x: x.log_softmax(2), atol=1e-7, grad_atol=1e-7)
def test_sinh(self):
helper_test_op([(45,65)], lambda x: x.sinh(), atol=1e-6, grad_atol=1e-6)
# TODO: backward nan instead of inf
helper_test_op([(45,65)], lambda x: x.sinh(), atol=1e-6, grad_atol=1e-6, a=-100, forward_only=True)
helper_test_op([(45,65)], lambda x: x.sinh(), atol=1e-6, grad_atol=1e-6, a=100, forward_only=True)
def test_cosh(self):
helper_test_op([(45,65)], lambda x: x.cosh(), atol=1e-6, grad_atol=1e-6)
# TODO: backward nan instead of inf
helper_test_op([(45,65)], lambda x: x.cosh(), atol=1e-6, grad_atol=1e-6, a=-100, forward_only=True)
helper_test_op([(45,65)], lambda x: x.cosh(), atol=1e-6, grad_atol=1e-6, a=100, forward_only=True)
def test_tanh(self):
helper_test_op([(45,65)], lambda x: x.tanh(), atol=1e-6, grad_atol=1e-6)
helper_test_op([(45,65)], lambda x: x.tanh(), atol=1e-6, grad_atol=1e-6, a=-100)
helper_test_op([()], lambda x: x.tanh(), atol=1e-6, grad_atol=1e-6)
helper_test_op([(45,65)], lambda x: x.tanh(), atol=1e-6, grad_atol=1e-6, a=100)
def test_hardtanh(self):
for val in range(10, 30, 5):
helper_test_op([(45,65)], lambda x: torch.nn.functional.hardtanh(x, -val, val), lambda x: x.hardtanh(-val, val), atol=1e-6, grad_atol=1e-6)
helper_test_op([()], lambda x: torch.nn.functional.hardtanh(x, -val, val), lambda x: x.hardtanh(-val, val), atol=1e-6, grad_atol=1e-6)
def test_asinh(self):
helper_test_op([(45,65)], lambda x: x.asinh(), atol=1e-6, grad_atol=1e-6)
# NOTE: this one has larger atol
helper_test_op([(45,65)], lambda x: x.asinh(), atol=1e-2, grad_atol=1e-6, a=-100)
helper_test_op([(45,65)], lambda x: x.asinh(), atol=1e-6, grad_atol=1e-6, a=100)
def test_acosh(self):
helper_test_op([(45,65)], lambda x: x.acosh(), atol=1e-6, grad_atol=1e-6)
helper_test_op([(45,65)], lambda x: x.acosh(), atol=1e-6, grad_atol=1e-6, a=-100)
helper_test_op([(45,65)], lambda x: x.acosh(), atol=1e-6, grad_atol=1e-6, a=100)
def test_atanh(self):
helper_test_op([(45,65)], lambda x: x.atanh(), atol=1e-6, grad_atol=1e-6)
helper_test_op([(45,65)], lambda x: x.atanh(), atol=1e-6, grad_atol=1e-6, a=-100)
helper_test_op([(45,65)], lambda x: x.atanh(), atol=1e-6, grad_atol=1e-6, a=100)
def test_topo_sort(self):
helper_test_op([(45,65)], lambda x: (x+x)*x, atol=1e-6, grad_atol=1e-6)
helper_test_op([()], lambda x: (x+x)*x, atol=1e-6, grad_atol=1e-6)