fix: enable torch.autocast for TP parallelism without FSDP

[eous]

Remove overly conservative restriction that disabled mixed precision for TP-only configurations. torch.autocast operates at the operator level and is orthogonal to tensor parallelism.

Before: TP-only training would show warning and disable mixed precision
After: TP-only training uses torch.autocast for mixed precision

Note: PP-only training uses schedule-based execution and doesn't use maybe_enable_amp (unchanged by this PR).

Affected configurations:

• TP-only (now enabled)
• DDP-only (was already enabled)
• Single-device (was already enabled)
• FSDP/HSDP (unchanged - handled internally by fully_shard)

[Copilot]

Pull request overview

This PR removes an overly conservative restriction that disabled mixed precision training for Tensor Parallelism (TP) configurations without FSDP. The change enables torch.autocast for TP-only training, recognizing that autocast operates at the operator level and is orthogonal to the parallelism strategy.

Key changes:

• Simplified maybe_enable_amp function logic to enable autocast for all non-FSDP configurations
• Improved code comments to clarify when mixed precision is handled by FSDP vs AMP
• Added explanation that PP uses schedule-based execution and doesn't utilize this context

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[tianyu-l]

Have you verified it works properly? Could you show evidence, in terms of param / activation / grad dtype, and throughput comparison with mixed precision off?

I vaguely remember that I've tried it before and it didn't work as expected.

[eous]

Have you verified it works properly? Could you show evidence, in terms of param / activation / grad dtype, and throughput comparison with mixed precision off?

I vaguely remember that I've tried it before and it didn't work as expected.

https://huggingface.co/eousphoros/persona_eta_20b_131k This model was trained with TP=4 no fdsp. The output with autocast was inline with what I expected though I lack the depth of knowledge to formerly confirm this.