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Posted to github@beam.apache.org by GitBox <gi...@apache.org> on 2022/09/19 20:59:39 UTC
[GitHub] [beam] yeandy opened a new pull request, #23296: Add PytorchBatchConverter
yeandy opened a new pull request, #23296:
URL: https://github.com/apache/beam/pull/23296
Adding `PytorchBatchConverter` as [discussed](https://github.com/apache/beam/issues/21440#issuecomment-1239777760) in https://github.com/apache/beam/issues/21440 as an initial step to integrate Batched DoFns into RunInference.
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[GitHub] [beam] yeandy commented on pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
yeandy commented on PR #23296:
URL: https://github.com/apache/beam/pull/23296#issuecomment-1281240059
Thanks for the small fix and confirmation!
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[GitHub] [beam] yeandy commented on pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
yeandy commented on PR #23296:
URL: https://github.com/apache/beam/pull/23296#issuecomment-1251544546
R: @TheNeuralBit
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[GitHub] [beam] yeandy commented on a diff in pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
yeandy commented on code in PR #23296:
URL: https://github.com/apache/beam/pull/23296#discussion_r995937420
##########
sdks/python/apache_beam/typehints/batch.py:
##########
@@ -35,6 +35,7 @@
from typing import TypeVar
import numpy as np
+import torch
Review Comment:
Done.
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[GitHub] [beam] yeandy commented on a diff in pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
yeandy commented on code in PR #23296:
URL: https://github.com/apache/beam/pull/23296#discussion_r974687712
##########
sdks/python/apache_beam/typehints/batch_test.py:
##########
@@ -54,6 +64,17 @@
'element_typehint': str,
'batch': ["foo" * (i % 5) + str(i) for i in range(1000)],
},
+ {
+ 'batch_typehint': torch.Tensor,
+ 'element_typehint': torch.Tensor,
Review Comment:
A single element of a `Tensor` array is also a `Tensor`. e.g.
```
>>> a = torch.Tensor([1,2,3])
>>> a
tensor([1., 2., 3.])
>>> a[0]
tensor(1.)
>>> type(a)
<class 'torch.Tensor'>
>>> type(a[0])
<class 'torch.Tensor'>
```
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[GitHub] [beam] TheNeuralBit commented on pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
TheNeuralBit commented on PR #23296:
URL: https://github.com/apache/beam/pull/23296#issuecomment-1279487100
It looks like codecov is unhappy since this file looks untested. Presumably because we don't have pytorch installed in the run generating coverage data. I confirmed this test is exercised on Jenkins:
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[GitHub] [beam] TheNeuralBit merged pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
TheNeuralBit merged PR #23296:
URL: https://github.com/apache/beam/pull/23296
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[GitHub] [beam] TheNeuralBit commented on a diff in pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
TheNeuralBit commented on code in PR #23296:
URL: https://github.com/apache/beam/pull/23296#discussion_r996170680
##########
sdks/python/apache_beam/typehints/pytorch_type_compatibility_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""Unit tests for pytorch_type_compabitility."""
+
+import unittest
+
+import pytest
+from parameterized import parameterized
+from parameterized import parameterized_class
+
+from apache_beam.typehints import typehints
+from apache_beam.typehints.batch import BatchConverter
+from apache_beam.typehints.batch import N
+
+# Protect against environments where pytorch library is not available.
+# pylint: disable=wrong-import-order, wrong-import-position, ungrouped-imports
+try:
+ import torch
+ from apache_beam.typehints.pytorch_type_compatibility import PytorchTensor
+except ImportError:
+ raise unittest.SkipTest('PyTorch dependencies are not installed')
+
+
+@parameterized_class([
+ {
+ 'batch_typehint': torch.Tensor,
+ 'element_typehint': PytorchTensor[torch.int32, ()],
+ 'batch': torch.tensor(range(100), dtype=torch.int32)
+ },
+ {
+ 'batch_typehint': PytorchTensor[torch.int64, (N, 10)],
+ 'element_typehint': PytorchTensor[torch.int64, (10, )],
+ 'batch': torch.tensor([list(range(i, i + 10)) for i in range(100)],
+ dtype=torch.int64),
+ },
+])
+@pytest.mark.uses_pytorch
+class DataFrameBatchConverterTest(unittest.TestCase):
Review Comment:
nit: copy-paste error
```suggestion
class PytorchBatchConverterTest(unittest.TestCase):
```
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[GitHub] [beam] TheNeuralBit commented on a diff in pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
TheNeuralBit commented on code in PR #23296:
URL: https://github.com/apache/beam/pull/23296#discussion_r975656793
##########
sdks/python/apache_beam/typehints/batch.py:
##########
@@ -35,6 +35,7 @@
from typing import TypeVar
import numpy as np
+import torch
Review Comment:
Could you make this a separate module, following the pattern I just used for pandas: https://github.com/apache/beam/blob/master/sdks/python/apache_beam/typehints/pandas_type_compatibility.py
That way it can be separable from everything else here if `torch` is available.
##########
sdks/python/apache_beam/typehints/batch.py:
##########
@@ -35,6 +35,7 @@
from typing import TypeVar
import numpy as np
+import torch
Review Comment:
One issue with that is I haven't found a good way to re-use the BatchConverterTest logic, for now it's just duplicated in `pandas_type_compatibility_test`.
##########
sdks/python/apache_beam/typehints/batch_test.py:
##########
@@ -54,6 +64,17 @@
'element_typehint': str,
'batch': ["foo" * (i % 5) + str(i) for i in range(1000)],
},
+ {
+ 'batch_typehint': torch.Tensor,
+ 'element_typehint': torch.Tensor,
Review Comment:
Interesting. It could be problematic to allow this as an element type though, since it's unclear what data type is.
For now, could we always represent scalars as a 0-dim PytorchTensor? i.e. `PytorchTensor[torch.int32, (,)]`. There could also be a wrapper for this, like `PytorchScalar[torch.int32]`
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[GitHub] [beam] yeandy commented on pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
yeandy commented on PR #23296:
URL: https://github.com/apache/beam/pull/23296#issuecomment-1279220064
PTAL @TheNeuralBit
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[GitHub] [beam] github-actions[bot] commented on pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
github-actions[bot] commented on PR #23296:
URL: https://github.com/apache/beam/pull/23296#issuecomment-1251545630
Stopping reviewer notifications for this pull request: review requested by someone other than the bot, ceding control
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[GitHub] [beam] yeandy commented on a diff in pull request #23296: Add PytorchBatchConverter
Posted by GitBox <gi...@apache.org>.
yeandy commented on code in PR #23296:
URL: https://github.com/apache/beam/pull/23296#discussion_r976789614
##########
sdks/python/apache_beam/typehints/batch_test.py:
##########
@@ -54,6 +64,17 @@
'element_typehint': str,
'batch': ["foo" * (i % 5) + str(i) for i in range(1000)],
},
+ {
+ 'batch_typehint': torch.Tensor,
+ 'element_typehint': torch.Tensor,
Review Comment:
Yeah, let me try that
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