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Return ValueError in case of empty list input for tf.map_fn #39241

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Jun 30, 2020
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Return ValueError in case of empty list input for tf.map_fn #39241

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0ee6b3a
Return ValueError in case of empty list input for tf.map_fn
yongtang May 6, 2020
ad4323e
Update tf.map_fn to specify that at least one tensor must be present
yongtang May 7, 2020
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6 changes: 6 additions & 0 deletions tensorflow/python/kernel_tests/map_fn_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -217,6 +217,12 @@ def testMapEmptyTensor(self):
self.assertAllEqual([0, 3, 2], map_return.get_shape().dims)
self.assertAllEqual([0, 3, 2], self.evaluate(map_return).shape)

@test_util.run_in_graph_and_eager_modes
def testMapEmptyList(self):
x = []
with self.assertRaisesRegexp(
ValueError, r"elems must be a Tensor or"):
_ = map_fn.map_fn(lambda e: e, x)

if __name__ == "__main__":
test.main()
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11 changes: 9 additions & 2 deletions tensorflow/python/ops/map_fn.py
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Expand Up @@ -267,7 +267,7 @@ def map_fn(fn,
elems: A tensor or (possibly nested) sequence of tensors, each of which will
be unstacked along their first dimension. `fn` will be applied to the
nested sequence of the resulting slices. `elems` may include ragged and
sparse tensors.
sparse tensors. `elems` must consist of at least one tensor.
dtype: Deprecated: Equivalent to `fn_output_signature`.
parallel_iterations: (optional) The number of iterations allowed to run in
parallel. When graph building, the default value is 10. While executing
Expand Down Expand Up @@ -296,7 +296,7 @@ def map_fn(fn,
TypeError: if `fn` is not callable or the structure of the output of
`fn` and `fn_output_signature` do not match.
ValueError: if the lengths of the output of `fn` and `fn_output_signature`
do not match.
do not match, or if the `elems` does not contain any tensor.

Examples:

Expand Down Expand Up @@ -375,6 +375,13 @@ def map_fn(fn,

# Flatten the input tensors, and get the TypeSpec for each one.
elems_flat = nest.flatten(elems)

# Check in case this is an empty list
if len(elems_flat) == 0:
raise ValueError(
"elems must be a Tensor or (possibly nested) sequence of Tensors. "
"Got {}, which does not contain any Tensors.".format(elems))

elems_flat_signature = [type_spec.type_spec_from_value(e) for e in elems_flat]
elems_unflatten = lambda x: nest.pack_sequence_as(elems, x)

Expand Down