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Fix SoftmaxGrad failure with constant dy in numba backend #435

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Merged
merged 1 commit into from
Sep 12, 2023
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Fix SoftmaxGrad failure with constant dy in numba backend #435

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7 changes: 6 additions & 1 deletion pytensor/link/numba/dispatch/elemwise.py
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Original file line number Diff line number Diff line change
Expand Up @@ -925,7 +925,12 @@ def softmax_grad_py_fn(dy, sm):
dx = dy_times_sm - sum_dy_times_sm * sm
return dx

softmax_grad = jit_compile_reducer(node, softmax_grad_py_fn)
# The signature inferred by jit_compile_reducer is wrong when dy is a constant (readonly=True)
# softmax_grad = jit_compile_reducer(node, softmax_grad_py_fn)
softmax_grad = numba_njit(
boundscheck=False,
fastmath=config.numba__fastmath,
)(softmax_grad_py_fn)

return softmax_grad

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10 changes: 10 additions & 0 deletions tests/link/numba/test_elemwise.py
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Expand Up @@ -445,6 +445,16 @@ def test_SoftmaxGrad(dy, sm, axis, exc):
)


def test_SoftMaxGrad_constant_dy():
dy = at.constant(np.zeros((3,), dtype=config.floatX))
sm = at.vector(shape=(3,))

g = SoftmaxGrad(axis=None)(dy, sm)
g_fg = FunctionGraph(outputs=[g])

compare_numba_and_py(g_fg, [np.ones((3,), dtype=config.floatX)])


@pytest.mark.parametrize(
"x, axis, exc",
[
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