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fix(deps): breaking change from transformers 5.4.0

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Maximellerbach
2026-03-27 16:04:14 +01:00
committed by Steven Palma
parent 587aa82021
commit cf7f4fda52
2 changed files with 4 additions and 4 deletions
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src/lerobot/policies/wall_x/qwen_model/qwen2_5_vl_moe.py
+2 -2
View File
@@ -22,7 +22,7 @@ from transformers.utils import (
add_start_docstrings,
add_start_docstrings_to_model_forward,
is_flash_attn_2_available,
is_flash_attn_greater_or_equal_2_10,
is_flash_attn_greater_or_equal,
is_torchdynamo_compiling,
logging,
replace_return_docstrings,
@@ -890,7 +890,7 @@ class Qwen2_5_VLFlashAttention2(Qwen2_5_VLAttention):
# TODO: Should be removed once Flash Attention for RoCm is bumped to 2.1.
# flash_attn<2.1 generates top-left aligned causal mask, while what is needed here is bottom-right alignment, that was made default for flash_attn>=2.1. This attribute is used to handle this difference. Reference: https://github.com/Dao-AILab/flash-attention/releases/tag/v2.1.0.
# Beware that with flash_attn<2.1, using q_seqlen != k_seqlen (except for the case q_seqlen == 1) produces a wrong mask (top-left).
self._flash_attn_uses_top_left_mask = not is_flash_attn_greater_or_equal_2_10()
self._flash_attn_uses_top_left_mask = not is_flash_attn_greater_or_equal("2.10")
def forward(
self,
src/lerobot/policies/xvla/modeling_florence2.py
+2 -2
View File
@@ -45,7 +45,7 @@ from transformers.utils import (
add_start_docstrings,
add_start_docstrings_to_model_forward,
is_flash_attn_2_available,
is_flash_attn_greater_or_equal_2_10,
is_flash_attn_greater_or_equal,
logging,
replace_return_docstrings,
)
@@ -909,7 +909,7 @@ class Florence2FlashAttention2(Florence2Attention):
# TODO: Should be removed once Flash Attention for RoCm is bumped to 2.1.
# flash_attn<2.1 generates top-left aligned causal mask, while what is needed here is bottom-right alignment, that was made default for flash_attn>=2.1. This attribute is used to handle this difference. Reference: https://github.com/Dao-AILab/flash-attention/releases/tag/v2.1.0.
# Beware that with flash_attn<2.1, using q_seqlen != k_seqlen (except for the case q_seqlen == 1) produces a wrong mask (top-left).
self._flash_attn_uses_top_left_mask = not is_flash_attn_greater_or_equal_2_10()
self._flash_attn_uses_top_left_mask = not is_flash_attn_greater_or_equal("2.10")
def _reshape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
return tensor.view(bsz, seq_len, self.num_heads, self.head_dim)