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fix transformers 5.x API breaks #125

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fix transformers 5.x API breaks #125

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1 change: 1 addition & 0 deletions qwen_asr/core/transformers_backend/configuration_qwen3_asr.py
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Original file line number Diff line number Diff line change
Expand Up @@ -321,6 +321,7 @@ class Qwen3ASRThinkerConfig(PretrainedConfig):
model_type = "qwen3_asr_thinker"

attribute_map = {}
pad_token_id = None
sub_configs = {
"audio_config": Qwen3ASRAudioEncoderConfig,
"text_config": Qwen3ASRTextConfig,
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20 changes: 18 additions & 2 deletions qwen_asr/core/transformers_backend/modeling_qwen3_asr.py
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Expand Up @@ -38,7 +38,13 @@
from transformers.processing_utils import Unpack
from transformers.utils import auto_docstring, can_return_tuple
from transformers.utils.deprecation import deprecate_kwarg
from transformers.utils.generic import TransformersKwargs, check_model_inputs
from transformers.utils.generic import TransformersKwargs

try:
from transformers.utils.generic import check_model_inputs
except ImportError:
def check_model_inputs(func=None, **_kw):
return (lambda f: f) if func is None else func

from .configuration_qwen3_asr import (
Qwen3ASRAudioEncoderConfig,
Expand Down Expand Up @@ -791,14 +797,24 @@ def __init__(self, config: Qwen3ASRConfig, device=None):
self.original_max_seq_len = config.max_position_embeddings

self.config = config
self.rope_init_fn = ROPE_INIT_FUNCTIONS[self.rope_type]
if self.rope_type not in ROPE_INIT_FUNCTIONS:
self.rope_init_fn = self._compute_default_rope_parameters
else:
self.rope_init_fn = ROPE_INIT_FUNCTIONS[self.rope_type]

inv_freq, self.attention_scaling = self.rope_init_fn(self.config, device)
self.register_buffer("inv_freq", inv_freq, persistent=False)
self.original_inv_freq = self.inv_freq

self.mrope_section = config.rope_scaling.get("mrope_section", [24, 20, 20])

@staticmethod
def _compute_default_rope_parameters(config, device=None, seq_len=None, **_kw):
base = getattr(config, "rope_theta", 10000.0)
dim = getattr(config, "head_dim", config.hidden_size // config.num_attention_heads)
inv_freq = 1.0 / (base ** (torch.arange(0, dim, 2, dtype=torch.float32).to(device) / dim))
return inv_freq, 1.0

def apply_interleaved_mrope(self, freqs, mrope_section):
"""Apply interleaved MRoPE to 3D rotary embeddings.
Reorganizes frequency layout from chunked [TTT...HHH...WWW] to
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