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feat(dtype): expose packed FP4E2M1X2 carrier - #2832

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lyfne123 merged 8 commits into
hw-native-sys:mainfrom
yanghaoran29:feat/expose-fp4e2m1x2
Sep 21, 2026
Merged

lyfne123 merged 8 commits into
hw-native-sys:mainfrom
yanghaoran29:feat/expose-fp4e2m1x2

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@yanghaoran29

@yanghaoran29 yanghaoran29 commented Sep 20, 2026

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Summary

  • Expose DataType.FP4E2M1X2 / pl.FP4E2M1X2 as the packed PTOAS / Torch carrier (GetBit()==8) across IR, DSL, bindings, codegen, and backend gating.
  • Keep logical pl.FP4 but emit an English UserWarning preferring FP4E2M1X2 until PackFp4 lands (this PR does not include PackFp4).
  • Map torch.float4_e2m1fn_x2 to packed FP4E2M1X2 without last-dim expand; already-packed shapes are not halved at the call ABI.

Test plan

  • tests/ut/core/test_dtype.py (incl. FP4 entry warning)
  • tests/ut/ir/transforms/test_legalize_tile_cast.py
  • CI pre-commit / clang-tidy / unit tests

Add DataType.FP4E2M1X2 across IR/DSL/codegen/backend so hand-written
packed FP4 is usable. Keep logical pl.FP4 but warn Prefer FP4E2M1X2
until PackFp4 lands. Torch float4 maps to the packed carrier.
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📝 Walkthrough

Walkthrough

The PR adds the packed FP4E2M1X2 dtype, separates it from logical FP4, updates Python and compiler handling, adjusts packed cast geometry, adds backend restrictions and warnings, and documents the supported usage paths.

Changes

FP4 packed carrier support

Layer / File(s) Summary
Packed dtype contract and mappings
include/pypto/core/dtype.h, python/..., src/codegen/...
Adds FP4E2M1X2, public aliases, predicates, runtime mappings, and PTO representations.
Python dtype resolution and metadata
python/pypto/ir/..., python/pypto/jit/..., python/pypto/language/..., tests/ut/core/test_dtype.py
Distinguishes packed carrier shapes from logical FP4 shapes. Adds FP4 warnings and validates the new dtype and exports.
Packed cast geometry and memory validation
include/pypto/ir/type_inference.h, src/ir/op/...
Adjusts packed cast dimensions, valid shapes, and strides. Rejects FP4-family tile operations targeting cube memory.
Backend capability and cast diagnostics
include/pypto/backend/..., src/backend/..., src/ir/transforms/..., tests/ut/ir/transforms/...
Updates backend support and Ascend950 cast adjacency. FP4-family to FP8 legalization emits diagnostics, while FP4-family to BF16 remains silent.
FP4 documentation and navigation
docs/en/..., docs/zh/..., mkdocs.yml
Documents logical and packed FP4 units, cast behavior, support limits, examples, and navigation links.

Priority: ➖ Normal

Estimated code review effort: 4 (Complex) | ~45 minutes

Change: Feature

Sequence Diagram(s)

sequenceDiagram
  participant Torch
  participant JIT
  participant IR
  participant LegalizeTileCast
  Torch->>JIT: provide float4_e2m1fn_x2 tensor
  JIT->>IR: create FP4E2M1X2 metadata
  IR->>LegalizeTileCast: process FP4-family cast
  LegalizeTileCast->>IR: adjust packed dimensions and strides
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Merge Risk: 🟡 Moderate · up to ad7ac

Programs that directly cast between logical and packed FP4 may produce inconsistent IR after cast legalization. Reject this unsupported conversion until its packing contract is defined before merging.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name Status Explanation Resolution
Docstring Coverage ⚠️ Warning Docstring coverage is 50.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 70 functions across 24 files. (7 skipped:… Write docstrings for the functions missing them to satisfy the coverage threshold.
✅ Passed checks (4 passed)
Check name Status Explanation
Linked Issues check ✅ Passed Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check ✅ Passed Check skipped because no linked issues were found for this pull request.
Title check ✅ Passed The title clearly and concisely identifies the main change: exposing the packed FP4E2M1X2 carrier.
Description check ✅ Passed The description directly covers the packed FP4E2M1X2 carrier, logical FP4 warnings, Torch mapping, and test coverage described by the changeset.
Full details: Docstring Coverage

Explanation

Docstring coverage is 50.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 70 functions across 24 files. (7 skipped: 7 unsupported.)

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A rabbit packs two nibbles tight,
The carrier keeps each shape aligned,
BF16 casts expand the row,
FP8 warnings clearly show,
Tests guard every documented path.

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@yanghaoran29 yanghaoran29 changed the title feat(dtype): expose packed FP4E2M1X2 carrier without PackFp4 feat(dtype): expose packed FP4E2M1X2 carrier Sep 20, 2026
Add en/zh fp4.md with hand-written FP4E2M1X2→BF16/FP8 samples, wire
nav/types links, and assert the silent packed→BF16 last-axis expand.

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Actionable comments posted: 1

🧹 Nitpick comments (1)
python/pypto/jit/decorator.py (1)

301-310: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick win

Remove now-unreachable elif dtype == DataType.FP4 branch.

_extract_tensor_meta derives dtype only from tensor.dtype through _torch_dtype_to_pypto. The tensor argument, dynamic-dimension metadata, and layout annotation do not override it. _torch_dtype_to_pypto can return only values in _TORCH_DTYPE_MAP, where float4_e2m1fn_x2 maps to DataType.FP4E2M1X2, not DataType.FP4.

♻️ Proposed removal of dead code
         # Torch and IR both count packed x2 carriers for FP4E2M1X2; do not expand.
-    elif dtype == DataType.FP4:
-        if not extents:
-            raise TypeError("Packed torch.float4_e2m1fn_x2 tensors must have rank >= 1")
-        if extents[-1] <= 0:
-            raise TypeError(
-                "Packed torch.float4_e2m1fn_x2 tensors require a positive runtime x2 carrier last "
-                f"dimension; got shape {tuple(extents)}"
-            )
-        # Legacy logical FP4 path: expand carrier → nibble extents at the API boundary.
-        extents[-1] *= 2
     return _build_tensor_meta(extents, dtype, dyn_dims, layout)
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In `@python/pypto/jit/decorator.py` around lines 301 - 310, Remove the unreachable
elif dtype == DataType.FP4 branch from _extract_tensor_meta, including its
extent validation and expansion logic. Preserve the existing FP4E2M1X2
carrier-dimension handling and the final _build_tensor_meta return path
unchanged.

  • 🪄 Fix CodeRabbit comments on this PR
🤖 Prompt to fix review comments
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Inline comments:
In `@include/pypto/ir/type_inference.h`:
- Around line 963-967: Update DeduceTileCastType to reject direct casts between
logical FP4 and packed FP4E2M1X2 dtypes in either direction, in addition to its
existing same-dtype rejection. Reuse IsFp4PackedCastGeometryChange or the
visible FP4-family predicates to identify this pair before allowing unchanged
geometry, preventing LegalizeTileCast from producing an inconsistent final type.

---

Nitpick comments:
In `@python/pypto/jit/decorator.py`:
- Around line 301-310: Remove the unreachable elif dtype == DataType.FP4 branch
from _extract_tensor_meta, including its extent validation and expansion logic.
Preserve the existing FP4E2M1X2 carrier-dimension handling and the final
_build_tensor_meta return path unchanged.

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📥 Commits

Reviewing files that changed from the base of the PR and between 04f1f51 and ad7accc.

📒 Files selected for processing (31)
  • docs/en/dev/fp4.md
  • docs/en/dev/index.md
  • docs/en/user/language/00-types.md
  • docs/zh/dev/fp4.md
  • docs/zh/dev/index.md
  • docs/zh/user/language/00-types.md
  • include/pypto/backend/910B/backend_910b_handler.h
  • include/pypto/backend/950/backend_950_handler.h
  • include/pypto/core/dtype.h
  • include/pypto/ir/type_inference.h
  • mkdocs.yml
  • python/bindings/modules/core.cpp
  • python/pypto/__init__.py
  • python/pypto/ir/__init__.py
  • python/pypto/ir/__init__.pyi
  • python/pypto/ir/compiled_program.py
  • python/pypto/ir/param_info.py
  • python/pypto/jit/decorator.py
  • python/pypto/jit/specializer.py
  • python/pypto/language/__init__.py
  • python/pypto/language/parser/type_resolver.py
  • python/pypto/pypto_core/__init__.pyi
  • src/backend/950/backend_950_handler.cpp
  • src/codegen/codegen_base.cpp
  • src/codegen/pto/pto_type_utils.cpp
  • src/ir/op/tensor_ops/unary.cpp
  • src/ir/op/tile_ops/memory.cpp
  • src/ir/op/tile_ops/unary.cpp
  • src/ir/transforms/legalize_tile_cast_pass.cpp
  • tests/ut/core/test_dtype.py
  • tests/ut/ir/transforms/test_legalize_tile_cast.py

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Comment thread include/pypto/ir/type_inference.h
Expand FP4E2M1X2 make_tensor_view/partition last-axis to nibble units for
pto-isa, dual-path JIT by pl.FP4 vs FP4E2M1X2 annotation, reject family
casts and dynamic pack, and align tests/docs with carrier geometry.
Avoid DataType.__eq__(None) when unannotated FP32/FP16 tensors hit the
packed-FP4 shape check; include dtype.h for clang-tidy and skip MX on
GM last-axis expand to match make_tensor_view.
Drop the general annotation↔torch dtype mismatch path that rejected
pl.INDEX tensors carried as torch.int64; _param_dtypes only records
FP4/FP4E2M1X2 for the expand dual-path.
Align tensor.view ND/DN guard with IsFp4Family, extend matmul_mx cast
hints, stop calling packed x2 a 4-bit dtype on a2a3, and tighten
rank-3 GM expand shape/stride asserts.
Restore logical FP4 on Ascend950 SupportsIncoreDataType alongside packed
FP4E2M1X2 so existing mxfp4 ST and hand-written X2 paths both remain valid.
@yanghaoran29
yanghaoran29 force-pushed the feat/expose-fp4e2m1x2 branch 3 times, most recently from 3890d27 to 2def001 Compare September 20, 2026 09:54
Reject packed x2 non-ND annotations, [M,1] column-vector DN forcing, and
explicit tensor.view layout flips. Cast results use row-major strides from
the destination shape so non-contiguous sources stay dense after unpack.
@lyfne123
lyfne123 merged commit 33476ea into hw-native-sys:main Sep 21, 2026
21 checks passed
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