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fix crash in multi-modal

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
This commit is contained in:
Wang, Yi A 2024-07-17 22:21:11 -07:00
parent da82c63a4f
commit d8e3a27648
3 changed files with 8 additions and 3 deletions
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3
server/text_generation_server/models/custom_modeling/flash_pali_gemma_modeling.py
View File

@ -24,6 +24,7 @@ from text_generation_server.models.custom_modeling.vlm import (
load_text_model,
load_vision_model,
)
from text_generation_server.layers.attention import Seqlen
class PaliGemmaForConditionalGeneration(nn.Module):
@ -92,7 +93,7 @@ class PaliGemmaForConditionalGeneration(nn.Module):
# insert image features into input embeddings
inputs_embeds[mask] = image_features.view(-1, image_features.shape[-1])
input_lengths = Seqlen(input_lengths=input_lengths)
hidden_states = self.text_model.model(
inputs_embeds=inputs_embeds,
position_ids=position_ids,

4
server/text_generation_server/models/custom_modeling/idefics2.py
View File

@ -35,6 +35,7 @@ from text_generation_server.layers import (
TensorParallelRowLinear,
)
from text_generation_server.utils.weights import DefaultWeightsLoader
from text_generation_server.layers.attention import Seqlen
def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
@ -824,7 +825,7 @@ class Idefics2ForConditionalGeneration(nn.Module):
inputs_embeds = self._merge_input_ids_with_image_features(
input_ids, inputs_embeds, image_hidden_states
)
input_lengths = Seqlen(input_lengths=input_lengths)
hidden_states = self.text_model.model(
inputs_embeds=inputs_embeds,
position_ids=position_ids,
@ -836,6 +837,7 @@ class Idefics2ForConditionalGeneration(nn.Module):
max_s=max_s,
true_max_s=max_s,
prefill_cache_indices=None,
adapter_data=adapter_data,
)
if lm_head_indices is not None:
hidden_states = hidden_states[lm_head_indices]

4
server/text_generation_server/models/custom_modeling/llava_next.py
View File

@ -31,6 +31,7 @@ from text_generation_server.layers import (
TensorParallelColumnLinear,
TensorParallelRowLinear,
)
from text_generation_server.layers.attention import Seqlen
def get_anyres_image_grid_shape(image_size, grid_pinpoints, patch_size):
@ -268,7 +269,7 @@ class LlavaNextForConditionalGeneration(nn.Module):
inputs_embeds = self._merge_input_ids_with_image_features(
input_ids, inputs_embeds, image_features
)
input_lengths = Seqlen(input_lengths=input_lengths)
hidden_states = self.text_model.model(
inputs_embeds=inputs_embeds,
position_ids=position_ids,
@ -280,6 +281,7 @@ class LlavaNextForConditionalGeneration(nn.Module):
max_s=max_s,
true_max_s=max_s,
prefill_cache_indices=None,
adapter_data=adapter_data,
)
if lm_head_indices is not None:
hidden_states = hidden_states[lm_head_indices]