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4 changes: 4 additions & 0 deletions python/src/coreai_models/export/_constants.py
Original file line number Diff line number Diff line change
Expand Up @@ -17,3 +17,7 @@
# Trace-time `input_ids` length and `position_ids` offset for export/quantization
QUANT_TRACE_QUERY_LEN = 16
QUANT_TRACE_OFFSET = 8

# Default max context length for iOS exports. Users can raise it via
# --max-context-length (up to the model's max_position_embeddings).
IOS_DEFAULT_MAX_CONTEXT_LENGTH = 4096
20 changes: 20 additions & 0 deletions python/src/coreai_models/export/pipeline.py
Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@
from transformers import AutoConfig, AutoTokenizer

from coreai_models.export._constants import (
IOS_DEFAULT_MAX_CONTEXT_LENGTH,
QUANT_TRACE_OFFSET,
QUANT_TRACE_QUERY_LEN,
TRACE_KV_CACHE_SEQ_LEN,
Expand Down Expand Up @@ -151,7 +152,26 @@ async def _async_export_model(config: ExportConfig) -> str:
# ---- 2. Load model ----
target_dtype = _resolve_precision(config.compute_precision)

# The model's native context window from its HuggingFace config. Any
# user-provided override must not exceed it.
native_max_ctx = getattr(hf_config, "max_position_embeddings", None)
Comment thread
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max_context_length = config.max_context_length
if max_context_length is None and config.variant == "iOS":
max_context_length = min(
IOS_DEFAULT_MAX_CONTEXT_LENGTH, native_max_ctx or IOS_DEFAULT_MAX_CONTEXT_LENGTH
)

if (
max_context_length is not None
and native_max_ctx is not None
and max_context_length > native_max_ctx
):
raise ValueError(
f"--max-context-length ({max_context_length}) exceeds the model's "
f"max_position_embeddings ({native_max_ctx}). Choose a value <= {native_max_ctx}."
)

if max_context_length is not None:
hf_config.max_position_embeddings = max_context_length
if config.num_layers is not None:
Expand Down
8 changes: 5 additions & 3 deletions python/src/coreai_models/model_registry.py
Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,8 @@
from dataclasses import asdict, dataclass
from pathlib import Path

from coreai_models.export._constants import IOS_DEFAULT_MAX_CONTEXT_LENGTH

# ---------------------------------------------------------------------------
# Data model
# ---------------------------------------------------------------------------
Expand Down Expand Up @@ -138,7 +140,7 @@ class UtilityModel:
"iOS",
"none",
"float16",
4096,
IOS_DEFAULT_MAX_CONTEXT_LENGTH,
compression_config="models/qwen3/qwen3_0_6b_mixed_4bit_8bit.yaml",
),
ModelPreset(
Expand All @@ -149,7 +151,7 @@ class UtilityModel:
"iOS",
"4bit_weight_palettized_group8",
"float16",
4096,
IOS_DEFAULT_MAX_CONTEXT_LENGTH,
),
ModelPreset(
"qwen3-4b",
Expand All @@ -159,7 +161,7 @@ class UtilityModel:
"iOS",
"none",
"float16",
4096,
IOS_DEFAULT_MAX_CONTEXT_LENGTH,
compression_config="models/qwen3/qwen3_4b_mixed_4bit_8bit.yaml",
),
]
Expand Down
131 changes: 131 additions & 0 deletions python/tests/test_model_conversion/test_infra.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,131 @@
# Copyright 2026 Apple Inc.
#
# Use of this source code is governed by a BSD-3-clause license that can
# be found in the LICENSE file or at https://opensource.org/licenses/BSD-3-Clause

"""Export-pipeline infrastructure tests"""

import asyncio
from pathlib import Path

import pytest
from coreai.authoring import AIModelAsset
from transformers.models.qwen3.modeling_qwen3 import (
Qwen3Config,
)
from transformers.models.qwen3.modeling_qwen3 import (
Qwen3ForCausalLM as HFQwen3ForCausalLM,
)

from coreai_models.export import pipeline as export_pipeline
from coreai_models.export._constants import IOS_DEFAULT_MAX_CONTEXT_LENGTH
from coreai_models.export.ios import KEY_CACHE_INPUT_NAME, VALUE_CACHE_INPUT_NAME
from coreai_models.export.pipeline import ExportConfig, _async_export_model


def _tiny_qwen3_config(max_position_embeddings: int) -> Qwen3Config:
"""A small, randomly-initialized Qwen3 config for fast pipeline exports."""
return Qwen3Config(
vocab_size=256,
hidden_size=64,
intermediate_size=128,
num_hidden_layers=2,
num_attention_heads=4,
num_key_value_heads=2,
head_dim=16,
max_position_embeddings=max_position_embeddings,
tie_word_embeddings=True,
)


def _save_tiny_qwen3(config: Qwen3Config, dest: Path) -> str:
"""Instantiate a Qwen3 model from ``config`` and save it so the pipeline can
load it via ``from_pretrained``. Returns the model directory path."""
model = HFQwen3ForCausalLM(config)
model.save_pretrained(str(dest))
return str(dest)


def _cache_context_length(descriptor_type: str) -> int:
"""Extract the context-length (last) dimension from a state descriptor's
type string, e.g. ``"NDArray (Float16, 2 × 1 × 32 × 1 × 2048)"`` -> 2048."""
inside = descriptor_type[descriptor_type.index("(") + 1 : descriptor_type.rindex(")")]
shape_part = inside.split(",", 1)[1]
dims = [int(dim.strip()) for dim in shape_part.split("×")]
return dims[-1]


class TestIOSPipelineMaxContextLength:
@staticmethod
def test_rejects_context_length_above_hf_config(tmp_path: Path) -> None:
"""The pipeline must reject a --max-context-length larger than the
model's ``max_position_embeddings`` from its HuggingFace config."""
native_max = 4096
config = _tiny_qwen3_config(max_position_embeddings=native_max)
model_dir = _save_tiny_qwen3(config, tmp_path / "model")

export_config = ExportConfig(
hf_model_id=model_dir,
variant="iOS",
max_context_length=native_max + 1,
compute_precision="float16",
compression="none",
output_dir=str(tmp_path / "out"),
overwrite=True,
)

with pytest.raises(ValueError, match="max_position_embeddings"):
asyncio.run(_async_export_model(export_config))

@staticmethod
def test_defaults_ios_context_length_to_4096(
tmp_path: Path, monkeypatch: pytest.MonkeyPatch
) -> None:
"""With no explicit --max-context-length, iOS exports default to 4096.

Loads the dumped program and checks every function's KV-cache states:
the context-length dim must match between key/value caches, and the
maximum context length across all cache-bearing functions must be 4096.
"""
# Native context window well above the iOS default so we know the cap
# (4096) — not the model's own limit — is what bounds the export.
config = _tiny_qwen3_config(max_position_embeddings=8192)
model_dir = _save_tiny_qwen3(config, tmp_path / "model")

# The tokenizer/metadata bundling step is unrelated to what we assert
# here and would require tokenizer files for this synthetic model.
monkeypatch.setattr(export_pipeline, "bundle_llm_asset", lambda **kwargs: None)

export_config = ExportConfig(
hf_model_id=model_dir,
variant="iOS",
max_context_length=None,
compute_precision="float16",
compression="none",
output_dir=str(tmp_path / "out"),
overwrite=True,
)

bundle_path = asyncio.run(_async_export_model(export_config))

aimodel_path = next(Path(bundle_path).glob("*.aimodel"))
summary = AIModelAsset.load(aimodel_path).summary(include_statistics=False)

max_context_length = 0
functions_with_cache = 0
for function_name in summary.function_names:
states = dict(summary.function_states(function_name))
if KEY_CACHE_INPUT_NAME not in states or VALUE_CACHE_INPUT_NAME not in states:
continue
functions_with_cache += 1

key_ctx = _cache_context_length(states[KEY_CACHE_INPUT_NAME])
value_ctx = _cache_context_length(states[VALUE_CACHE_INPUT_NAME])
assert key_ctx == value_ctx, (
f"{function_name}: key/value cache context-length dims differ "
f"({key_ctx} vs {value_ctx})"
)
max_context_length = max(max_context_length, key_ctx)

assert functions_with_cache > 0, "expected at least one function with KV-cache states"
assert max_context_length == IOS_DEFAULT_MAX_CONTEXT_LENGTH == 4096