[CharlelieLrt]

Description

This PR introduces the alpha DistillationLoss API for training existing
PhysicsNeMo models with sCM or MeanFlow. Users install the optional
diffusion-fastgen extra, create a loss object, and call it from their own
optimizer loop:

loss_fn = DistillationLoss(student, scheduler, method="MeanFlow", teacher=teacher)
losses = loss_fn(x0, condition=condition, step=step)
losses["total_loss"].backward()

WeightedDistillationLoss supports pixel masks and soft weights, while the
BaseDistillationLoss contract lets users define native methods without FastGen.
The adapters remain private, so users continue to work with PhysicsNeMo models
and noise schedulers. The loss does not load teacher weights or manage
optimizers, and inference continues to use PhysicsNeMo samplers.

MeanFlow students receive (t, DiffusionExtraTimes(r=r, batch_size=[B])).
For sCM, models return their prediction paired with
DiffusionExtraOutputs(logvar=logvar, batch_size=[B]). Every forward call
returns a prediction tensor.

Checklist

• This PR follows the contribution guidelines.
• The documentation describes the API and its role in the stack.
• This PR remains a draft.

Dependencies

• Depends on

  • PhysicsNeMo #2200 adds inverse SNR and TrigFlow components. This is the immediate prerequisite.

• Earlier prerequisites

  • PhysicsNeMo #2199 adds named diffusion inputs and outputs.

• Depends on this PR

  • PhysicsNeMo #2202 extends the loss API to DMD2 and f-distill. It follows this PR directly in the stack.

• Later follow-ups

  • PhysicsNeMo #2203 adds checkpoint bundles for restarting distillation.
  • PhysicsNeMo #2204 adds the optional training strategy and the grouped changelog entry.

• Parallel FastGen work

  • FastGen #43 allows the NumPy 2 dependency used by PhysicsNeMo. PhysicsNeMo Add sCM and MeanFlow distillation losses #2201 uses an immutable fork pin, so it does not need to wait for this proposal to merge.
  • FastGen #44 provides shared loss hooks for external training loops. The initial PhysicsNeMo integration does not require these hooks.

• Conditional follow-up

  • PhysicsNeMo #2205 replaces local compatibility code with the proposed FastGen loss hooks. It depends on PhysicsNeMo Add optional diffusion distillation strategy #2204 and FastGen [other] Add modulus.models.fcn_mip_plugin #44, not the other way around.

If FastGen maintainers decline FastGen #44, we would close PhysicsNeMo #2205.
The preceding PhysicsNeMo stack would remain available.

Review process

This draft replaces PhysicsNeMo #2096 and comes from the personal fork. This migration preserves the implementation. The first commit also includes the requested documentation clarifications.

Review the isolated commit diff for this layer. Each branch adds one commit to its prerequisite branch. All replacement PRs target upstream main, so later PRs include prerequisite commits awaiting merge in their Files changed tab. After prerequisites merge, update the remaining branches to remove them from those diffs.

[copy-pr-bot]

This pull request requires additional validation before any workflows can run on NVIDIA's runners.

Pull request vetters can view their responsibilities here.

Contributors can view more details about this message here.

[github-actions]

CODEOWNERS review map

Current for commit c9526daa29fa. An approval covers every file listed for that owner; one owner is sufficient for shared files.

⏳ @CharlelieLrt — 49 file(s)

• docs/api/diffusion/distillation.rst
• docs/api/diffusion/introduction.rst
• docs/api/diffusion/models.rst
• docs/api/diffusion/noise_schedulers.rst
• docs/api/diffusion/preconditioners.rst
• physicsnemo/diffusion/init.py
• physicsnemo/diffusion/_fastgen.py
• physicsnemo/diffusion/base.py
• physicsnemo/diffusion/distillation/init.py
• physicsnemo/diffusion/distillation/_fastgen.py
• physicsnemo/diffusion/distillation/base.py
• physicsnemo/diffusion/distillation/losses.py
• physicsnemo/diffusion/distillation/methods/init.py
• physicsnemo/diffusion/distillation/methods/meanflow/init.py
• physicsnemo/diffusion/distillation/methods/meanflow/_fastgen.py
• physicsnemo/diffusion/distillation/methods/scm/init.py
• physicsnemo/diffusion/distillation/methods/scm/_fastgen.py
• physicsnemo/diffusion/metrics/losses.py
• physicsnemo/diffusion/noise_schedulers/init.py
• physicsnemo/diffusion/noise_schedulers/_fastgen.py
• physicsnemo/diffusion/noise_schedulers/edm.py
• physicsnemo/diffusion/noise_schedulers/iddpm.py
• physicsnemo/diffusion/noise_schedulers/linear_gaussian.py
• physicsnemo/diffusion/noise_schedulers/rectified_flow.py
• physicsnemo/diffusion/noise_schedulers/trigflow.py
• physicsnemo/diffusion/noise_schedulers/ve.py
• physicsnemo/diffusion/noise_schedulers/vp.py
• physicsnemo/diffusion/preconditioners/init.py
• physicsnemo/diffusion/preconditioners/preconditioners.py
• physicsnemo/diffusion/utils/model_wrappers.py
• test/diffusion/data/distillation_meanflow_weighted.pth
• test/diffusion/data/distillation_scm_weighted.pth
• test/diffusion/data/trigflow_precond_conv.mdlus
• test/diffusion/data/trigflow_precond_conv_coefficients.pth
• test/diffusion/data/trigflow_precond_conv_forward.pth
• test/diffusion/data/trigflow_precond_conv_sigma.pth
• test/diffusion/data/trigflow_precond_linear.mdlus
• test/diffusion/data/trigflow_precond_linear_coefficients.pth
• test/diffusion/data/trigflow_precond_linear_forward.pth
• test/diffusion/data/trigflow_precond_linear_sigma.pth
• test/diffusion/helpers.py
• test/diffusion/test_distillation_api.py
• test/diffusion/test_distillation_losses.py
• test/diffusion/test_fastgen_network.py
• test/diffusion/test_fastgen_noise_scheduler.py
• test/diffusion/test_model_io.py
• test/diffusion/test_noise_schedulers.py
• test/diffusion/test_preconditioners.py
• test/diffusion/test_trigflow.py

⏳ @coreyjadams — 1 file(s)

• pyproject.toml

⏳ @ktangsali — 2 file(s)

• docs/api_diffusion.rst
• pyproject.toml

⏳ @megnvidia — 6 file(s)

• docs/api/diffusion/distillation.rst
• docs/api/diffusion/introduction.rst
• docs/api/diffusion/models.rst
• docs/api/diffusion/noise_schedulers.rst
• docs/api/diffusion/preconditioners.rst
• docs/api_diffusion.rst

No CODEOWNER

• .importlinter
• CHANGELOG.md
• uv.lock

Comment /codeowners-info to refresh.