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Fixes #854 #2693

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Fixes #854 #2693

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31 changes: 17 additions & 14 deletions onnxscript/function_libs/torch_lib/ops/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4984,30 +4984,33 @@ def aten_linspace(
pin_memory: bool = False,
) -> TensorType:
"""linspace(Scalar start, Scalar end, int steps, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"""

if dtype == -1 or dtype is None:
dtype = FLOAT.dtype

# Reference: https://github.com/pytorch/pytorch/blob/b35ca2cb941b5ba90858322810ca85c31e4541fd/torch/_refs/__init__.py#L4896
if steps == 0:
return aten_full(op.Constant(value_ints=[0]), 0.0, dtype=dtype)
if steps == 1:
return aten_full(op.Constant(value_ints=[steps]), start, dtype=dtype)

rg = aten_arange_start(0, steps, dtype=dtype)
start = op.Cast(start, to=dtype)
end = op.Cast(end, to=dtype)
steps_float = op.Cast(steps, to=dtype)
one = op.Cast(1.0, to=dtype)
two = op.Cast(2.0, to=dtype)
steps_minus_1 = op.Cast(steps - 1, to=dtype)
step = op.Div(op.Sub(end, start), steps_minus_1)
return op.Where(
rg < op.Div(steps_float, two),
start + step * rg,
end - step * (steps_float - one - rg),
compute_dtype = FLOAT.dtype

rg = aten_arange_start(0, steps, dtype=compute_dtype)
start_f = op.Cast(start, to=compute_dtype)
end_f = op.Cast(end, to=compute_dtype)
steps_f = op.Cast(steps, to=compute_dtype)
one = op.Cast(1.0, to=compute_dtype)
two = op.Cast(2.0, to=compute_dtype)
steps_minus_1 = op.Sub(steps_f, one)
step = op.Div(op.Sub(end_f, start_f), steps_minus_1)

lin_vals = op.Where(
rg < op.Div(steps_f, two),
op.Add(start_f, op.Mul(step, rg)),
op.Sub(end_f, op.Mul(step, op.Sub(op.Sub(steps_f, one), rg))),
)

return op.Cast(lin_vals, to=dtype)


@torch_op("aten::log", trace_only=True)
def aten_log(self: TFloat) -> TFloat:
Expand Down