[data] Tensor Type __repr__ should be custom tensor types#56457
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bveeramani merged 18 commits intoray-project:masterfrom Sep 23, 2025
Merged
[data] Tensor Type __repr__ should be custom tensor types#56457bveeramani merged 18 commits intoray-project:masterfrom
bveeramani merged 18 commits intoray-project:masterfrom
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Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
…nhsu/ray into jhsu/do-not-impersonate-schema-type
Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
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This pull request updates the string representation of TensorDtype to show TensorDtype(...) instead of numpy.ndarray(...). It also introduces a DataContext flag, pandas_block_ignore_metadata, to handle incorrect behavior in older pyarrow versions when converting Arrow tables with extension types to pandas DataFrames. A new test for string tensor roundtrips is also added.
My main feedback is that the new DataContext flag should have a version-dependent default value to automatically apply the fix for users with older pyarrow versions. The rest of the changes look good.
Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
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Signed-off-by: iamjustinhsu <[email protected]>
Signed-off-by: iamjustinhsu <[email protected]>
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alexeykudinkin
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LGTM. Thanks for the change @iamjustinhsu. Dumb question: Are there any changes in our Ray data pipelines?
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…t#56457) <!-- Thank you for your contribution! Please review https://github.com/ray-project/ray/blob/master/CONTRIBUTING.rst before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? When specifying batch_format="pandas" in map_batches, we convert to and from pandas blocks. With tensor extensions, we impersonate the types as numpy arrays, when they should be objects. This can cause confusion + lead to random errors in conversion, since pyarrow will use the dtype to reconstruct the object Old PR: iamjustinhsu#3 <!-- Please give a short summary of the change and the problem this solves. --> ## Related issue number <!-- For example: "Closes ray-project#1234" --> ## Checks - [ ] I've signed off every commit(by using the -s flag, i.e., `git commit -s`) in this PR. - [ ] I've run `scripts/format.sh` to lint the changes in this PR. - [ ] I've included any doc changes needed for https://docs.ray.io/en/master/. - [ ] I've added any new APIs to the API Reference. For example, if I added a method in Tune, I've added it in `doc/source/tune/api/` under the corresponding `.rst` file. - [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/ - Testing Strategy - [ ] Unit tests - [ ] Release tests - [ ] This PR is not tested :( --------- Signed-off-by: iamjustinhsu <[email protected]> Signed-off-by: zac <[email protected]>
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<!-- Thank you for your contribution! Please review https://github.com/ray-project/ray/blob/master/CONTRIBUTING.rst before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? When specifying batch_format="pandas" in map_batches, we convert to and from pandas blocks. With tensor extensions, we impersonate the types as numpy arrays, when they should be objects. This can cause confusion + lead to random errors in conversion, since pyarrow will use the dtype to reconstruct the object Old PR: iamjustinhsu#3 <!-- Please give a short summary of the change and the problem this solves. --> ## Related issue number <!-- For example: "Closes #1234" --> ## Checks - [ ] I've signed off every commit(by using the -s flag, i.e., `git commit -s`) in this PR. - [ ] I've run `scripts/format.sh` to lint the changes in this PR. - [ ] I've included any doc changes needed for https://docs.ray.io/en/master/. - [ ] I've added any new APIs to the API Reference. For example, if I added a method in Tune, I've added it in `doc/source/tune/api/` under the corresponding `.rst` file. - [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/ - Testing Strategy - [ ] Unit tests - [ ] Release tests - [ ] This PR is not tested :( --------- Signed-off-by: iamjustinhsu <[email protected]> Signed-off-by: elliot-barn <[email protected]>
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…t#56457) <!-- Thank you for your contribution! Please review https://github.com/ray-project/ray/blob/master/CONTRIBUTING.rst before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? When specifying batch_format="pandas" in map_batches, we convert to and from pandas blocks. With tensor extensions, we impersonate the types as numpy arrays, when they should be objects. This can cause confusion + lead to random errors in conversion, since pyarrow will use the dtype to reconstruct the object Old PR: iamjustinhsu#3 <!-- Please give a short summary of the change and the problem this solves. --> ## Related issue number <!-- For example: "Closes ray-project#1234" --> ## Checks - [ ] I've signed off every commit(by using the -s flag, i.e., `git commit -s`) in this PR. - [ ] I've run `scripts/format.sh` to lint the changes in this PR. - [ ] I've included any doc changes needed for https://docs.ray.io/en/master/. - [ ] I've added any new APIs to the API Reference. For example, if I added a method in Tune, I've added it in `doc/source/tune/api/` under the corresponding `.rst` file. - [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/ - Testing Strategy - [ ] Unit tests - [ ] Release tests - [ ] This PR is not tested :( --------- Signed-off-by: iamjustinhsu <[email protected]> Signed-off-by: Marco Stephan <[email protected]>
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<!-- Thank you for your contribution! Please review https://github.com/ray-project/ray/blob/master/CONTRIBUTING.rst before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? When specifying batch_format="pandas" in map_batches, we convert to and from pandas blocks. With tensor extensions, we impersonate the types as numpy arrays, when they should be objects. This can cause confusion + lead to random errors in conversion, since pyarrow will use the dtype to reconstruct the object Old PR: iamjustinhsu#3 <!-- Please give a short summary of the change and the problem this solves. --> ## Related issue number <!-- For example: "Closes #1234" --> ## Checks - [ ] I've signed off every commit(by using the -s flag, i.e., `git commit -s`) in this PR. - [ ] I've run `scripts/format.sh` to lint the changes in this PR. - [ ] I've included any doc changes needed for https://docs.ray.io/en/master/. - [ ] I've added any new APIs to the API Reference. For example, if I added a method in Tune, I've added it in `doc/source/tune/api/` under the corresponding `.rst` file. - [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/ - Testing Strategy - [ ] Unit tests - [ ] Release tests - [ ] This PR is not tested :( --------- Signed-off-by: iamjustinhsu <[email protected]> Signed-off-by: elliot-barn <[email protected]>
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…t#56457) <!-- Thank you for your contribution! Please review https://github.com/ray-project/ray/blob/master/CONTRIBUTING.rst before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? When specifying batch_format="pandas" in map_batches, we convert to and from pandas blocks. With tensor extensions, we impersonate the types as numpy arrays, when they should be objects. This can cause confusion + lead to random errors in conversion, since pyarrow will use the dtype to reconstruct the object Old PR: iamjustinhsu#3 <!-- Please give a short summary of the change and the problem this solves. --> ## Related issue number <!-- For example: "Closes ray-project#1234" --> ## Checks - [ ] I've signed off every commit(by using the -s flag, i.e., `git commit -s`) in this PR. - [ ] I've run `scripts/format.sh` to lint the changes in this PR. - [ ] I've included any doc changes needed for https://docs.ray.io/en/master/. - [ ] I've added any new APIs to the API Reference. For example, if I added a method in Tune, I've added it in `doc/source/tune/api/` under the corresponding `.rst` file. - [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/ - Testing Strategy - [ ] Unit tests - [ ] Release tests - [ ] This PR is not tested :( --------- Signed-off-by: iamjustinhsu <[email protected]> Signed-off-by: Douglas Strodtman <[email protected]>
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…t#56457) <!-- Thank you for your contribution! Please review https://github.com/ray-project/ray/blob/master/CONTRIBUTING.rst before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? When specifying batch_format="pandas" in map_batches, we convert to and from pandas blocks. With tensor extensions, we impersonate the types as numpy arrays, when they should be objects. This can cause confusion + lead to random errors in conversion, since pyarrow will use the dtype to reconstruct the object Old PR: iamjustinhsu#3 <!-- Please give a short summary of the change and the problem this solves. --> ## Related issue number <!-- For example: "Closes ray-project#1234" --> ## Checks - [ ] I've signed off every commit(by using the -s flag, i.e., `git commit -s`) in this PR. - [ ] I've run `scripts/format.sh` to lint the changes in this PR. - [ ] I've included any doc changes needed for https://docs.ray.io/en/master/. - [ ] I've added any new APIs to the API Reference. For example, if I added a method in Tune, I've added it in `doc/source/tune/api/` under the corresponding `.rst` file. - [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/ - Testing Strategy - [ ] Unit tests - [ ] Release tests - [ ] This PR is not tested :( --------- Signed-off-by: iamjustinhsu <[email protected]>
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…t#56457) <!-- Thank you for your contribution! Please review https://github.com/ray-project/ray/blob/master/CONTRIBUTING.rst before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? When specifying batch_format="pandas" in map_batches, we convert to and from pandas blocks. With tensor extensions, we impersonate the types as numpy arrays, when they should be objects. This can cause confusion + lead to random errors in conversion, since pyarrow will use the dtype to reconstruct the object Old PR: iamjustinhsu#3 <!-- Please give a short summary of the change and the problem this solves. --> ## Related issue number <!-- For example: "Closes ray-project#1234" --> ## Checks - [ ] I've signed off every commit(by using the -s flag, i.e., `git commit -s`) in this PR. - [ ] I've run `scripts/format.sh` to lint the changes in this PR. - [ ] I've included any doc changes needed for https://docs.ray.io/en/master/. - [ ] I've added any new APIs to the API Reference. For example, if I added a method in Tune, I've added it in `doc/source/tune/api/` under the corresponding `.rst` file. - [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/ - Testing Strategy - [ ] Unit tests - [ ] Release tests - [ ] This PR is not tested :( --------- Signed-off-by: iamjustinhsu <[email protected]>
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…t#56457) <!-- Thank you for your contribution! Please review https://github.com/ray-project/ray/blob/master/CONTRIBUTING.rst before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? When specifying batch_format="pandas" in map_batches, we convert to and from pandas blocks. With tensor extensions, we impersonate the types as numpy arrays, when they should be objects. This can cause confusion + lead to random errors in conversion, since pyarrow will use the dtype to reconstruct the object Old PR: iamjustinhsu#3 <!-- Please give a short summary of the change and the problem this solves. --> ## Related issue number <!-- For example: "Closes ray-project#1234" --> ## Checks - [ ] I've signed off every commit(by using the -s flag, i.e., `git commit -s`) in this PR. - [ ] I've run `scripts/format.sh` to lint the changes in this PR. - [ ] I've included any doc changes needed for https://docs.ray.io/en/master/. - [ ] I've added any new APIs to the API Reference. For example, if I added a method in Tune, I've added it in `doc/source/tune/api/` under the corresponding `.rst` file. - [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/ - Testing Strategy - [ ] Unit tests - [ ] Release tests - [ ] This PR is not tested :( --------- Signed-off-by: iamjustinhsu <[email protected]> Signed-off-by: Future-Outlier <[email protected]>
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Why are these changes needed?
When specifying batch_format="pandas" in map_batches, we convert to and from pandas blocks. With tensor extensions, we impersonate the types as numpy arrays, when they should be objects. This can cause confusion + lead to random errors in conversion, since pyarrow will use the dtype to reconstruct the object
Old PR: iamjustinhsu#3
Related issue number
Checks
git commit -s) in this PR.scripts/format.shto lint the changes in this PR.method in Tune, I've added it in
doc/source/tune/api/under thecorresponding
.rstfile.