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Move pytorch transforms from init method to transform method #1303

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Move pytorch transforms from init method to transform method #1303

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51c6f40
move pytorch transforms
mamtsing Sep 2, 2026
fc3f0a7
Merge branch 'main' into move_pt_transforms
quic-mamta Sep 6, 2026
6253af1
fix tests
mamtsing Sep 7, 2026
ed95a95
accept qaic_config only via compile and deprecate export as external …
mamtsing Sep 7, 2026
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3 changes: 1 addition & 2 deletions QEfficient/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,11 +73,10 @@ class HybridChunkedCache(HybridCache):
warnings.formatwarning = custom_format_warning


# Users can use QEfficient.export for exporting models to ONNX
# Backward-compatible deprecated alias for exporting models to ONNX. Prefer .compile().
export = qualcomm_efficient_converter
__all__ = [
"transform",
"export",
"compile",
"cloud_ai_100_exec_kv",
"QEFFAutoModel",
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16 changes: 16 additions & 0 deletions QEfficient/base/common.py
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Expand Up @@ -13,6 +13,7 @@
"""

import os
import warnings
from typing import Any

from transformers import AutoConfig
Expand Down Expand Up @@ -40,6 +41,14 @@ def from_pretrained(cls, pretrained_model_name_or_path: str, *args, **kwargs) ->
"""
Downloads HuggingFace model if already doesn't exist locally, returns QEFFAutoModel object based on type of model.
"""
qaic_config = kwargs.pop("qaic_config", None)
if qaic_config is not None:
warnings.warn(
"Passing `qaic_config` to `from_pretrained()` is deprecated and will be removed in a future "
"release. Pass `qaic_config` to `compile()` instead.",
DeprecationWarning,
stacklevel=2,
)
config = AutoConfig.from_pretrained(pretrained_model_name_or_path, *args, **kwargs)

class_name = (
Expand All @@ -66,4 +75,11 @@ def from_pretrained(cls, pretrained_model_name_or_path: str, *args, **kwargs) ->
continuous_batching=continuous_batching,
**kwargs,
)
if qaic_config is not None:
if hasattr(qeff_model, "_activate_qaic_config"):
qeff_model._activate_qaic_config(qaic_config)
elif hasattr(qeff_model, "_resolve_qaic_config"):
qeff_model._resolve_qaic_config(qaic_config)
elif hasattr(qeff_model, "_set_qaic_config"):
qeff_model._set_qaic_config(qaic_config)
return qeff_model
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