[Feature] Add set_at_, set_, update_ methods to ReplayBuffer

[jashshah999]

Summary

buffer[index]["key"] = value silently fails because tensor indexing returns a copy, not a view. This adds three in-place write methods to ReplayBuffer following the TensorDict nomenclature as suggested by @vmoens:

• set_at_(key, value, index) -- set a key at specific indices
• set_(key, value) -- set a key across the entire buffer
• update_(input_dict_or_td) -- batch update multiple keys in-place

All methods acquire _replay_lock and write through directly to the underlying storage TensorDict.

Changes

• Add set_at_, set_, update_ to ReplayBuffer in replay_buffers.py
• Add tests for all three methods

Fixes #2810

[pytorch-bot]

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❌ 2 New Failures, 1 Cancelled Job

As of commit babe1c9 with merge base e2c8a8d ():

NEW FAILURES - The following jobs have failed:

• Continuous Benchmark (PR) / CPU Pytest benchmark (gh)
  Workflow failed! Resource not accessible by integration
• Unit-tests on Linux / tests-olddeps (3.10, 11.8) / linux-job (gh)
  RuntimeError: Command docker exec -t 045638a3bb7cc8ba7f3b9b9ea84985addaa0458fc57c56c24fe4eee6f7e7d68a /exec failed with exit code 1

CANCELLED JOB - The following job was cancelled. Please retry:

• Continuous Benchmark (PR) / GPU Pytest benchmark (gh)
  ##[error]The operation was canceled.

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[vmoens]

LGTM thanks for this!