replaced call to _prepare_4d_causal_attention_mask

src/petals/__init__.py

@@ -17,13 +17,7 @@ from petals.models import *
 from petals.utils import *
 from petals.utils.logging import initialize_logs as _initialize_logs
 
-__version__ = "2.3.0.dev1"
-
-
-if not os.getenv("PETALS_IGNORE_DEPENDENCY_VERSION"):
-    assert (
-        version.parse("4.32.0") <= version.parse(transformers.__version__) < version.parse("4.35.0")
-    ), "Please install a proper transformers version: pip install transformers>=4.32.0,<4.35.0"
+__version__ = "2.3.0.dev2"
 
 
 def _override_bfloat16_mode_default():

src/petals/models/llama/block.py

@@ -9,6 +9,7 @@ from typing import Optional, Tuple
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
+from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask
 from transformers.models.llama.modeling_llama import (
     LlamaAttention,
     LlamaConfig,
@@ -244,8 +245,8 @@ class WrappedLlamaBlock(OptimizedLlamaDecoderLayer):
             attention_mask = torch.ones(
                 (batch_size, seq_length_with_past), dtype=torch.bool, device=hidden_states.device
             )
-        attention_mask = LlamaModel._prepare_decoder_attention_mask(
-            None, attention_mask, (batch_size, seq_length), hidden_states, past_key_values_length
+        attention_mask = _prepare_4d_causal_attention_mask(
+            attention_mask, (batch_size, seq_length), hidden_states, past_key_values_length
         )
 
         outputs = super().forward(