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Allow default_output to be any valid Python index #274

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Merged
merged 1 commit into from
Apr 13, 2023
Merged

Allow default_output to be any valid Python index #274

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8 changes: 3 additions & 5 deletions pytensor/graph/basic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -193,11 +193,9 @@ def default_output(self):
if len(self.outputs) == 1:
return self.outputs[0]
else:
raise ValueError(f"{self.op}.default_output should be an output index.")
elif not isinstance(do, int):
raise ValueError(f"{self.op}.default_output should be an int or long")
elif do < 0 or do >= len(self.outputs):
raise ValueError(f"{self.op}.default_output is out of range.")
Comment on lines -198 to -200
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I think Python error messages do a good enough job here when indexing is not valid or out of bounds. No need to reinvent the wheel.

raise ValueError(
f"Multi-output Op {self.op} default_output not specified"
)
return self.outputs[do]

def __str__(self):
Expand Down
2 changes: 1 addition & 1 deletion pytensor/tensor/basic.py
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Expand Up @@ -80,7 +80,7 @@ def _as_tensor_Apply(x, name, ndim, **kwargs):
# use Apply's default output mechanism
if (x.op.default_output is None) and (len(x.outputs) != 1):
raise TypeError(
"Multi-output Op encountered. "
"Multi-output Op without default_output encountered. "
"Retry using only one of the outputs directly."
)

Expand Down
31 changes: 21 additions & 10 deletions tests/tensor/test_basic.py
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Expand Up @@ -500,12 +500,13 @@ def test_infer_shape(self):


class ApplyDefaultTestOp(Op):
def __init__(self, id):
def __init__(self, id, n_outs=1):
self.default_output = id
self.n_outs = n_outs

def make_node(self, x):
x = at.as_tensor_variable(x)
return Apply(self, [x], [x.type()])
return Apply(self, [x], [x.type() for _ in range(self.n_outs)])

def perform(self, *args, **kwargs):
raise NotImplementedError()
Expand Down Expand Up @@ -556,16 +557,26 @@ def test_tensor_from_scalar(self):
y = as_tensor_variable(aes.int8())
assert isinstance(y.owner.op, TensorFromScalar)

def test_multi_outputs(self):
good_apply_var = ApplyDefaultTestOp(0).make_node(self.x)
as_tensor_variable(good_apply_var)
def test_default_output(self):
good_apply_var = ApplyDefaultTestOp(0, n_outs=1).make_node(self.x)
as_tensor_variable(good_apply_var) is good_apply_var

bad_apply_var = ApplyDefaultTestOp(-1).make_node(self.x)
with pytest.raises(ValueError):
good_apply_var = ApplyDefaultTestOp(-1, n_outs=1).make_node(self.x)
as_tensor_variable(good_apply_var) is good_apply_var

bad_apply_var = ApplyDefaultTestOp(1, n_outs=1).make_node(self.x)
with pytest.raises(IndexError):
_ = as_tensor_variable(bad_apply_var)

bad_apply_var = ApplyDefaultTestOp(2).make_node(self.x)
with pytest.raises(ValueError):
bad_apply_var = ApplyDefaultTestOp(2.0, n_outs=1).make_node(self.x)
with pytest.raises(TypeError):
_ = as_tensor_variable(bad_apply_var)

good_apply_var = ApplyDefaultTestOp(1, n_outs=2).make_node(self.x)
as_tensor_variable(good_apply_var) is good_apply_var.outputs[1]

bad_apply_var = ApplyDefaultTestOp(None, n_outs=2).make_node(self.x)
with pytest.raises(TypeError, match="Multi-output Op without default_output"):
_ = as_tensor_variable(bad_apply_var)

def test_list(self):
Expand All @@ -578,7 +589,7 @@ def test_list(self):
_ = as_tensor_variable(y)

bad_apply_var = ApplyDefaultTestOp([0, 1]).make_node(self.x)
with pytest.raises(ValueError):
with pytest.raises(TypeError):
as_tensor_variable(bad_apply_var)

def test_ndim_strip_leading_broadcastable(self):
Expand Down