Update tensordict requirement from !=0.9.0,<=0.10.0,>=0.8.0 to >=0.8.0,!=0.9.0,<=0.12.0

[dependabot]

Updates the requirements on tensordict to permit the latest version.

Release notes

Sourced from tensordict's releases.

TensorDict v0.12.0

Highlights

TensorDict v0.12.0 introduces TypedTensorDict for schema-enforced tensor dictionaries, a full distributed collectives suite (broadcast, all_reduce, all_gather, scatter), TensorDictStore with Redis/Dragonfly/KeyDB backends, and major torch.compile and performance improvements. The UnbatchedTensor has been rewritten as a proper tensor subclass, and state_dict handling has been overhauled for consistency.

Breaking Changes

• UnbatchedTensor is now a __torch_dispatch__-based tensor subclass (was previously a wrapper) (#1638, #1648)
• state_dict is now flat by default, with auto-detection in load_state_dict for backwards compatibility
• TensorClass state_dict now uses logical keys

Features

• TypedTensorDict: Schema-enforced TensorDicts with type annotations, cross-class compatibility, and torch.compile support (#1657, #1659, #1660, #1662, #1663)
• TensorDictStore: Redis/Dragonfly/KeyDB-backed TensorDict with TensorClass support, lazy stack storage, and optimized indexed ops
• Distributed collectives: broadcast, all_reduce, all_gather, scatter, consolidated send/recv and init_remote/from_remote_init with UCXX transport support (#1611)
• set_printoptions: Configurable TensorDict repr with verbose mode (#1654, #1655, #1665)
• torch.func support: jacrev, jacfwd, and hessian now work with TensorDict (#1613)
• vmap with unbatched data: TensorDicts containing unbatched tensors can now be vmapped (#1625)
• TensorClass.select(as_tensordict=...) parameter (#1544)
• TensorDictBase.is_non_tensor(key) for consistent non-tensor key detection

Bug Fixes

• Fix HigherOrderOperator support in __torch_function__ (#1668)
• Fix td[key] = [] handling (#1666)
• Fix UnbatchedTensor.tolist() (#1664)
• Fix UnbatchedTensor CUDA pickling for multiprocessing (#1656)
• Fix UnbatchedTensor indexing without batch dim, GPU failures, getitem/stack (#1607, #1626, #1633)
• Fix replace() recompiles under torch.compile (#1605)
• Fix auto_batch_size regression with NonTensorStack (#1609)
• Fix NonTensorData positional args causing graph breaks under torch.compile (#1630)
• Fix state_dict error messages, params forwarding, detach
• Pin pybind11>=2.13 for Python 3.13 compatibility

Performance

• Speed up TensorDict.__init__ by bypassing set() dispatch chain (#1551)
• Speed up TensorClass.__init__ by bypassing __setattr__ and dataclass __init__ (#1552)
• Use CUDA event sync instead of torch.cuda.synchronize() in .to() (#1545)
• Reduce guards and recompiles for TensorDict under torch.compile (#1636)
• Compile-friendly TensorDict build (#1624)

Commits

• bb8825e [CI] Also disable ROCm wheel builds (tensordict is CPU-only)
• 015507b [CI] Disable CUDA wheel builds (tensordict is CPU-only) (#1672)
• 3f84f8d [CI] Fix wheel builds (#1671)
• b0ebe66 [Release] Bump version to 0.12.0 (#1670)
• 31b5ef5 [BugFix] Support HigherOrderOperator in torch_function (#1668)
• 962bf40 [BugFix] Handle td[key] = [] properly (#1666)
• fb51ac7 [Feature] set_printoptions(verbose=False) (#1665)
• 32d9fb6 [BugFix] Fix UnbatchedTensor.tolist() (#1664)
• 45424d7 [Refactor] Use torch_dispatch for UnbatchedTensor (#1648)
• 4df757c [Feature] torch.compile compatibility for TypedTensorDict (#1659)
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[dependabot]

Superseded by #9.