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the dynamic has a result, but the static inference shape reports an error #20242

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the dynamic has a result, but the static inference shape reports an error #20242

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the dynamic has a result, but the static inference shape reports an e…
mehtamansi29 Sep 9, 2024
de9a169
Updated failed testcases
mehtamansi29 Sep 9, 2024
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9 changes: 3 additions & 6 deletions keras/src/ops/nn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -799,12 +799,9 @@ def average_pool(
data_format = standardize_data_format(data_format)
padding = padding.lower()
if any_symbolic_tensors((inputs,)):
return AveragePool(
pool_size,
strides,
padding,
data_format,
).symbolic_call(inputs)
return operation_utils.compute_pooling_output_shape(
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This is incorrect, the symbolic call should return a KerasTensor instance.

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@fchollet - Thanks for update. Let me have a resolve it and commit again.

inputs.shape, pool_size, strides, padding, data_format
)
return backend.nn.average_pool(
inputs, pool_size, strides, padding, data_format
)
Expand Down
20 changes: 10 additions & 10 deletions keras/src/ops/nn_test.py
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Expand Up @@ -167,11 +167,11 @@ def test_average_pool(self):
input_shape = (None, 3, 8)
x = KerasTensor(input_shape)
self.assertEqual(
knn.average_pool(x, 2, 1).shape,
knn.average_pool(x, 2, 1),
(None, 7, 3) if data_format == "channels_last" else (None, 3, 7),
)
self.assertEqual(
knn.average_pool(x, 2, 2, padding="same").shape,
knn.average_pool(x, 2, 2, padding="same"),
(None, 4, 3) if data_format == "channels_last" else (None, 3, 4),
)

Expand All @@ -181,23 +181,23 @@ def test_average_pool(self):
input_shape = (None, 3, 8, None)
x = KerasTensor(input_shape)
self.assertEqual(
knn.average_pool(x, 2, 1).shape,
knn.average_pool(x, 2, 1),
(
(None, 7, None, 3)
if data_format == "channels_last"
else (None, 3, 7, None)
),
)
self.assertEqual(
knn.average_pool(x, 2, 2, padding="same").shape,
knn.average_pool(x, 2, 2, padding="same"),
(
(None, 4, None, 3)
if data_format == "channels_last"
else (None, 3, 4, None)
),
)
self.assertEqual(
knn.average_pool(x, (2, 2), (2, 2), padding="same").shape,
knn.average_pool(x, (2, 2), (2, 2), padding="same"),
(
(None, 4, None, 3)
if data_format == "channels_last"
Expand Down Expand Up @@ -780,11 +780,11 @@ def test_average_pool(self):
input_shape = (1, 3, 8)
x = KerasTensor(input_shape)
self.assertEqual(
knn.average_pool(x, 2, 1).shape,
knn.average_pool(x, 2, 1),
(1, 7, 3) if data_format == "channels_last" else (1, 3, 7),
)
self.assertEqual(
knn.average_pool(x, 2, 2, padding="same").shape,
knn.average_pool(x, 2, 2, padding="same"),
(1, 4, 3) if data_format == "channels_last" else (1, 3, 4),
)

Expand All @@ -794,15 +794,15 @@ def test_average_pool(self):
input_shape = (1, 3, 8, 8)
x = KerasTensor(input_shape)
self.assertEqual(
knn.average_pool(x, 2, 1).shape,
knn.average_pool(x, 2, 1),
(1, 7, 7, 3) if data_format == "channels_last" else (1, 3, 7, 7),
)
self.assertEqual(
knn.average_pool(x, 2, 2, padding="same").shape,
knn.average_pool(x, 2, 2, padding="same"),
(1, 4, 4, 3) if data_format == "channels_last" else (1, 3, 4, 4),
)
self.assertEqual(
knn.average_pool(x, (2, 2), (2, 2), padding="same").shape,
knn.average_pool(x, (2, 2), (2, 2), padding="same"),
(1, 4, 4, 3) if data_format == "channels_last" else (1, 3, 4, 4),
)

Expand Down