diff --git a/src/transformers/models/qwen2_vl/configuration_qwen2_vl.py b/src/transformers/models/qwen2_vl/configuration_qwen2_vl.py index 55042327de4ec3..ef98ae5e3f508f 100644 --- a/src/transformers/models/qwen2_vl/configuration_qwen2_vl.py +++ b/src/transformers/models/qwen2_vl/configuration_qwen2_vl.py @@ -163,6 +163,16 @@ class Qwen2VLConfig(PretrainedConfig): model_type = "qwen2_vl" sub_configs = {"vision_config": Qwen2VLVisionConfig} keys_to_ignore_at_inference = ["past_key_values"] + # Default tensor parallel plan for base model `Qwen2VL` + base_model_tp_plan = { + "layers.*.self_attn.q_proj": "colwise", + "layers.*.self_attn.k_proj": "colwise", + "layers.*.self_attn.v_proj": "colwise", + "layers.*.self_attn.o_proj": "rowwise", + "layers.*.mlp.gate_proj": "colwise", + "layers.*.mlp.up_proj": "colwise", + "layers.*.mlp.down_proj": "rowwise", + } def __init__( self, diff --git a/src/transformers/models/qwen2_vl/modeling_qwen2_vl.py b/src/transformers/models/qwen2_vl/modeling_qwen2_vl.py index 10c9b1638548ce..566141d3f75c27 100644 --- a/src/transformers/models/qwen2_vl/modeling_qwen2_vl.py +++ b/src/transformers/models/qwen2_vl/modeling_qwen2_vl.py @@ -547,9 +547,9 @@ def forward( key_states = self.k_proj(hidden_states) value_states = self.v_proj(hidden_states) - query_states = query_states.view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2) - key_states = key_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) - value_states = value_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) + query_states = query_states.view(bsz, q_len, -1, self.head_dim).transpose(1, 2) + key_states = key_states.view(bsz, q_len, -1, self.head_dim).transpose(1, 2) + value_states = value_states.view(bsz, q_len, -1, self.head_dim).transpose(1, 2) cos, sin = position_embeddings query_states, key_states = apply_multimodal_rotary_pos_emb( @@ -631,9 +631,9 @@ def forward( key_states = self.k_proj(hidden_states) value_states = self.v_proj(hidden_states) - query_states = query_states.view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2) - key_states = key_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) - value_states = value_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) + query_states = query_states.view(bsz, q_len, -1, self.head_dim).transpose(1, 2) + key_states = key_states.view(bsz, q_len, -1, self.head_dim).transpose(1, 2) + value_states = value_states.view(bsz, q_len, -1, self.head_dim).transpose(1, 2) # Because the input can be padded, the absolute sequence length depends on the max position id. cos, sin = position_embeddings @@ -750,9 +750,9 @@ def forward( key_states = self.k_proj(hidden_states) value_states = self.v_proj(hidden_states) - query_states = query_states.view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2) - key_states = key_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) - value_states = value_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) + query_states = query_states.view(bsz, q_len, -1, self.head_dim).transpose(1, 2) + key_states = key_states.view(bsz, q_len, -1, self.head_dim).transpose(1, 2) + value_states = value_states.view(bsz, q_len, -1, self.head_dim).transpose(1, 2) cos, sin = position_embeddings query_states, key_states = apply_multimodal_rotary_pos_emb(