Comments (4)
You can try running third_party/pypa/generate_workspace.sh
, adding -r ml-dtypes=0.2.0
, and see if the constraints are met.
See tools/pypi_solver/main.py, which has a number of options to attempt to get compatible versions.
from tensorstore.
Sorry, I'm not sure I understand. If I want to install tensorstore and TensorFlow via pip (i.e., I have tensorflow == 2.15.0
and tensorstore == 0.1.51
in my requirements.txt
), how can I do that without causing a version conflict? I'm not familiar with how generate_workspace.sh
would become part of that workflow.
The reality of what's happening is actually more sinister: I have a chain of several dependencies that ends with tensorstore, but I also need TensorFlow, so the version of several other packages is silently "capped" by this ml-dtypes conflict. It seems like ml-types >= 0.3.1
was only added for float8 and int4 integration, which I definitely don't need. I would like to be able to get the most up-to-date version of tensorstore, as well as those other packages, without resorting to some complex pip install --no-deps
shenanigans.
from tensorstore.
Currently we do specifically depend on 0.3.1 because certain data types were added in that version, and tensorstore will not work with an earlier version.
We could potentially change tensorstore to just skip support for missing data types, but it would instead be better to just change the version requirement for tensorflow, since I'm pretty sure it will in fact work with a newer version of ml-dtypes.
from tensorstore.
Ok thanks, I guess I'm off to try and convince the TensorFlow maintainers then
from tensorstore.
Related Issues (20)
- AWS S3 authentication issues HOT 6
- Please create a pre-built PyPI wheel for linux arm64 HOT 7
- Support of large files for grpc_kvstore HOT 1
- S3 kvstore driver not being recognized HOT 3
- downsample driver produces repeating patterns HOT 8
- Debug logs for S3 driver, log requests and responses HOT 9
- Cache pool context from multiple python processes HOT 2
- Error while installing "tensorstore" on jetson linux (jetpack) HOT 1
- Assertion `IsUnmodified()' failed HOT 6
- How to use a custom bazel installation? HOT 2
- Building on linux with ppc64le arch
- Specify S3 credentials directly HOT 3
- Transactional/ACID semantics HOT 1
- Failing to build tensorestore as a cmake project HOT 4
- Using s3 kvstore with minio HOT 3
- Error reading shard index, Requested byte range... was not satisfied by response with byte range ... HOT 4
- Unable to include tensorstore as a cmake dependency
- Question: does tensorstore support array with multiple dynamic dimensions? HOT 2
- Clarify in documentation if the C++ API is thread safe HOT 2
- Writing local files fails on Windows 11 HOT 3
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from tensorstore.