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# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Output definitions for Cosmos-Embed1."""
from dataclasses import dataclass
from typing import Optional
import torch
from transformers.modeling_outputs import CausalLMOutputWithCrossAttentions, ModelOutput
@dataclass
class TextEmbedderOutput(ModelOutput):
"""Output of a video embedder branch `get_text_embeddings` function.
Attrs:
text_proj (`torch.FloatTensor` of shape `(batch_size, num_visual_embs, embed_dim)` or `(batch_size, embed_dim)`:
text (video-aligned) projected embeddings from text branch.
text_embs (`torch.FloatTensor` of shape `(batch_size, ...)`:
text tokens from text branch.
text_query_output (`transformer.modeling_outputs.CausalLMOutputWithCrossAttentions`):
Useful text branch intermediate outputs like hidden states, past key values, attentions etc.
"""
text_proj: Optional[torch.FloatTensor] = None
text_embs: Optional[torch.FloatTensor] = None
text_query_output: Optional[CausalLMOutputWithCrossAttentions] = None
@dataclass
class VideoEmbedderOutput(ModelOutput):
"""Output of a video embedder branch `get_video_embeddings` function.
Attrs:
visual_proj (`torch.FloatTensor` of shape `(batch_size, embed_dim)`):
visual (text-aligned) projected embeddings from visual branch.
visual_embs (`torch.FloatTensor` of shape `(batch_size, num_frames, height, width, encoder_dim)`):
per-frame dense visual embeddings from visual encoder.
visual_cls_tokens (`torch.FloatTensor` of shape `(batch_size, qformer_dim)`):
visual pooled tokens from visual branch prior to projection and normalization.
frame_cls_tokens (`torch.FloatTensor` of shape `(batch_size, num_frames, encoder_dim)`):
per-frame cls tokens from visual encoder.
visual_query_output (`transformer.modeling_outputs.CausalLMOutputWithCrossAttentions`):
Useful visual branch intermediate outputs like hidden states, past key values, attentions etc.
"""
visual_proj: Optional[torch.FloatTensor] = None
visual_embs: Optional[torch.FloatTensor] = None
visual_cls_tokens: Optional[torch.FloatTensor] = None
frame_cls_tokens: Optional[torch.FloatTensor] = None
visual_query_output: Optional[CausalLMOutputWithCrossAttentions] = None
@dataclass
class TextVideoEmbedderOutput(VideoEmbedderOutput, TextEmbedderOutput):
"""Merged class of `VideoEmbedderOutput` and `TextEmbedderOutput`."""
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