repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
sglang | python/sglang/multimodal_gen/test/unit/progressive_resolution/test_progressive.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Focused unit tests for the experimental progressive-resolution path."""
import argparse
import dataclasses
import unittest
from types import SimpleNamespace
import torch
from sglang.multimodal_gen.configs.sample.sampling_params import SamplingParams
from sglang.multimodal_gen... | 639 | 24,182 |
sglang | python/sglang/multimodal_gen/test/unit/manual/bench_patch_embed.py | .py | """
Benchmark: Conv3d vs reshape + F.linear PatchEmbed.
Matches the real e2e pipeline conditions:
- Conv3d weights are FP32 (no dtype passed to PatchEmbed.__init__)
- Input latents are BF16 (cast by denoising loop)
- torch.autocast(dtype=bf16) wraps the forward pass
- .flatten(2).transpose(1, 2) follows PatchE... | 208 | 7,234 |
sglang | python/sglang/multimodal_gen/test/unit/realtime/test_output_materialization.py | .py | # SPDX-License-Identifier: Apache-2.0
import numpy as np
import torch
from sglang.multimodal_gen.configs.sample.sampling_params import DataType
from sglang.multimodal_gen.runtime.entrypoints.utils import (
materialize_output_sample,
save_outputs,
)
from sglang.multimodal_gen.runtime.managers.gpu_worker import... | 174 | 5,188 |
sglang | python/sglang/multimodal_gen/test/unit/realtime/test_realtime_control_signals.py | .py | # SPDX-License-Identifier: Apache-2.0
from sglang.multimodal_gen.runtime.realtime.control_signals import (
ControlScriptQueue,
ControlSignal,
ControlSignalQueue,
ControlSignalSamplingParams,
ControlStateQueue,
ControlStateTransition,
parse_control_event_payload,
)
def test_control_signal_... | 295 | 8,774 |
sglang | python/sglang/multimodal_gen/test/unit/realtime/test_realtime_consistency_harness.py | .py | # SPDX-License-Identifier: Apache-2.0
import asyncio
import sys
from types import SimpleNamespace
import msgspec.msgpack
import numpy as np
import pytest
from sglang.multimodal_gen.runtime.utils.realtime_video import (
RAW_RGB_CONTENT_TYPE,
RAW_RGB_DELTA_GZIP_CONTENT_TYPE,
RAW_RGBA_DELTA_GZIP_CONTENT_TYP... | 565 | 17,020 |
sglang | python/sglang/multimodal_gen/test/unit/realtime/test_realtime_runtime.py | .py | # SPDX-License-Identifier: Apache-2.0
import asyncio
import time
from types import SimpleNamespace
import msgspec.msgpack
import numpy as np
import pytest
import torch
from sglang.multimodal_gen.configs.pipeline_configs.lingbot_world import (
LingBotWorldCausalDMDConfig,
_actions_to_c2ws,
)
from sglang.multi... | 1,104 | 35,552 |
sglang | python/sglang/multimodal_gen/test/unit/realtime/test_causal_denoising.py | .py | # SPDX-License-Identifier: Apache-2.0
from contextlib import nullcontext
from types import MethodType, SimpleNamespace
import torch
from sglang.multimodal_gen.runtime.layers.kvcache.causal_attention_cache import (
CausalSelfAttentionKVCache,
CrossAttentionKVCache,
)
from sglang.multimodal_gen.runtime.pipelin... | 635 | 20,818 |
sglang | python/sglang/multimodal_gen/test/unit/realtime/test_realtime_vae.py | .py | # SPDX-License-Identifier: Apache-2.0
from types import SimpleNamespace
import torch
from sglang.multimodal_gen.runtime.pipelines_core.stages.realtime.vae import (
CausalVaeDecodingStage,
RealtimeVAEDecodeState,
)
def test_realtime_vae_decode_state_clears_model_cache_on_dispose():
calls = []
state ... | 176 | 5,006 |
sglang | python/sglang/multimodal_gen/test/unit/realtime/test_realtime_output_transport.py | .py | # SPDX-License-Identifier: Apache-2.0
import asyncio
from types import SimpleNamespace
import msgspec.msgpack
import numpy as np
import torch
from sglang.multimodal_gen.runtime.entrypoints.openai.realtime import (
realtime_output_adapter,
)
from sglang.multimodal_gen.runtime.entrypoints.openai.realtime.realtime_... | 673 | 21,806 |
sglang | python/sglang/multimodal_gen/test/unit/realtime/test_lingbot_causal_denoising.py | .py | # SPDX-License-Identifier: Apache-2.0
from types import SimpleNamespace
import torch
from sglang.multimodal_gen.configs.pipeline_configs.lingbot_world import (
LingBotWorldCausalDMDConfig,
)
from sglang.multimodal_gen.configs.quantization.qvg_kv import QVGKVQuantArgs
from sglang.multimodal_gen.runtime.layers.kvc... | 948 | 33,367 |
sglang | python/sglang/multimodal_gen/test/unit/realtime/test_realtime_webui.py | .py | # SPDX-License-Identifier: Apache-2.0
from pathlib import Path
def test_realtime_webui_presets_do_not_emit_camera_scripts():
repo_root = Path(__file__).resolve().parents[6]
app_js = (
repo_root / "python/sglang/multimodal_gen/apps/realtime_webui/app.js"
).read_text()
index_html = (
re... | 110 | 5,340 |
sglang | python/sglang/multimodal_gen/test/unit/sana_wm/test_streaming_stage.py | .py | # SPDX-License-Identifier: Apache-2.0
"""S1c tests β streaming denoising stage: KV accumulator + chunk-loop composition.
The accumulator is the load-bearing new logic: GDN/STATE blocks copy-forward the
previous chunk's recurrent state; softmax/CONCAT blocks concatenate the rolling
+ sink K/V along **dim=1** (our (B,N,... | 279 | 10,136 |
sglang | python/sglang/multimodal_gen/test/unit/sana_wm/test_streaming_cached.py | .py | # SPDX-License-Identifier: Apache-2.0
"""S1a-2a tests β chunk-causal cached scan combiners for streaming `forward_long`.
`_gdn_scan_cached` / `_single_path_delta_scan_cached` are the per-chunk combiners
the streaming path calls: a FORWARD (inclusive) pass that carries recurrent state
across chunks plus a BACKWARD (exc... | 278 | 9,709 |
sglang | python/sglang/multimodal_gen/test/unit/sana_wm/test_streaming_forward_long.py | .py | # SPDX-License-Identifier: Apache-2.0
"""S1a-2c tests β streaming `forward_long` assembly on the #26153 SANA-WM DiT.
Built up in stages, each pinned at fp64 / CPU / atol=1e-9:
Stage 0 β RoPE windowing: `WanRotaryPosEmbed` must produce freqs at GLOBAL
frame positions for a chunk `[start, end)`, equal to the corre... | 398 | 13,545 |
sglang | python/sglang/multimodal_gen/test/unit/sana_wm/test_realtime_chain.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Realtime chain stages β latent-prep plan arithmetic + noise discipline.
The chunk PLAN must reproduce the engine-era tick behavior exactly:
front-loaded segments within a fixed horizon (chunk 0 carries the remainder
and the conditioning frame), uniform chunks past the horizon (... | 214 | 6,825 |
sglang | python/sglang/multimodal_gen/test/unit/sana_wm/test_streaming_realtime_path.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Realtime (per-chunk) path of SanaWMStreamingDenoisingStage.
Successor of the retired SanaWMChunkGenerator tests: a tiny CPU-safe model is
ticked through stage.forward with a session attached (one chunk per call,
chunk noise supplied directly β the latent-prep stage is exercised... | 212 | 7,471 |
sglang | python/sglang/multimodal_gen/test/unit/sana_wm/test_streaming_vae.py | .py | # SPDX-License-Identifier: Apache-2.0
"""S2 tests β streaming causal-VAE decode: conv_cache + upsampler trim.
The streaming decode threads a per-conv `conv_cache` dict so a chunked causal
decode (carrying the cache across chunks) is bit-comparable to a monolithic
causal decode of the whole clip. The two logic-bearing ... | 105 | 3,515 |
sglang | python/sglang/multimodal_gen/test/unit/sana_wm/test_pipeline_config.py | .py | import argparse
import os
import sys
import tempfile
import types
import unittest
from types import SimpleNamespace
from unittest.mock import patch
import torch
from sglang.multimodal_gen.configs.models.dits.sana_wm import SanaWMConfig
from sglang.multimodal_gen.configs.pipeline_configs.base import ModelTaskType
from... | 1,518 | 57,803 |
sglang | python/sglang/multimodal_gen/test/runner/pytest_runner.py | .py | from __future__ import annotations
import subprocess
import sys
import xml.etree.ElementTree as ET
from pathlib import Path
from typing import Sequence
import tabulate
def collect_test_items(
files: Sequence[str], filter_expr: str | None = None
) -> list[str]:
"""Collect pytest node IDs from the given files... | 365 | 11,063 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_disagg_server.py | .py | """End-to-end tests for disaggregated diffusion.
Launches encoder / denoiser / decoder role instances plus a DiffusionServer
head, sends a generation request through the HTTP front-end, and verifies
that a non-empty output comes back.
Two configurations are covered:
1. :class:`TestDisaggZImage1Rank` β 1 rank per rol... | 559 | 19,182 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_diffusion_bcg_tp2_zimage_turbo.py | .py | """Breakable CUDA graph must survive tensor parallelism.
With ``--tp-size > 1`` every ``RowParallelLinear`` issues a per-block all-reduce
that lands *inside* a captured BCG segment (BCG's break points are the attention
modules, so everything else is captured). Custom all-reduce hands the captured
kernel a rank-data sl... | 161 | 5,861 |
sglang | python/sglang/multimodal_gen/test/single_test_file/cli_generate_common.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
"""
Common generate cli test, one test for image and video each
"""
import os
import shlex
import tempfile
import unittest
from typing import Any
from PIL import Image
def run_command(command: list[str]) -> bool:
from sglang.multimodal_gen.test... | 120 | 3,589 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_generate_zimage_turbo_cli.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
import os
import shlex
import unittest
from PIL import Image
from sglang.multimodal_gen.configs.sample.sampling_params import DataType
from sglang.multimodal_gen.test.single_test_file.cli_generate_common import (
CLIBase,
check_image_size,
)
... | 46 | 1,334 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_dp_serving_2_gpu.py | .py | """Data-parallel serving must route, replicate, and agree.
Launches one server with --dp-size 2 (one GPU per replica) and checks the three
properties that make DP real rather than a parsed flag: both replica drivers
bind their own ingress, both replicas serve traffic (round-robin means two
sequential requests land on ... | 151 | 5,112 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_pi05_e2e.py | .py | # SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import json
import os
import statistics
import time
from pathlib import Path
import numpy as np
import pytest
from sglang.multimodal_gen.runtime.entrypoints.diffusion_generator import DiffGenerator
pytestmark = pytest.mark.skipif(
os.gete... | 213 | 7,582 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_pynccl_a2a_capture_2_gpu.py | .py | """A pynccl all-to-all must be replay-safe inside a CUDA graph.
ProcessGroupNCCL's collectives are not: their host-side per-op bookkeeping
advances once at capture, so replays leave the ranks disagreeing about which
collective is in flight and both hang. That is why the full-forward DiT graph
cannot capture `dist.all_... | 165 | 5,772 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_update_weights_from_disk.py | .py | """Tests for diffusion `update_weights_from_disk`.
This module verifies the ability to update model weights in place without restarting
the server, which is critical for RL workflows and iterative fine-tuning scenarios.
Author:
Menyang Liu, https://github.com/dreamyang-liu
Chenyang Zhao, https://github.com/zhaocheny... | 649 | 24,638 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_generate_i2i.py | .py | import os
import unittest
from PIL import Image
from sglang.multimodal_gen.configs.sample.sampling_params import DataType
from sglang.multimodal_gen.test.single_test_file.cli_generate_common import (
CLIBase,
run_command,
)
from sglang.multimodal_gen.test.test_utils import (
DEFAULT_QWEN_IMAGE_EDIT_2511_M... | 136 | 4,259 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_ipc_a2a_2_gpu.py | .py | """The CUDA-IPC all-to-all must match NCCL bit for bit.
This transport only activates on 2 ranks with peer-to-peer access, so nothing in
the single-GPU suite reaches it. Without this test a regression in the IPC path
lands silently.
Runs the whole USPAttention A2A family twice per shape -- once over NCCL, once
over I... | 229 | 8,802 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_usp_replicated_parity_2_gpu.py | .py | """USPAttention replicated prefix/suffix must match a single-rank reference.
The suffix path keeps the replicated tokens at the sequence tail so every
query scans K/V in the same order as a single rank β bitwise-stable across SP
degrees. A rotate-to-front implementation is numerically valid but reorders
the reduction,... | 156 | 5,152 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_diffusion_bcg_zimage_turbo.py | .py | import json
import os
import subprocess
import tempfile
import unittest
from pathlib import Path
from openai import OpenAI
from sglang.multimodal_gen.test.server.test_server_utils import ServerManager
from sglang.multimodal_gen.test.test_utils import (
DEFAULT_SMALL_MODEL_NAME_FOR_TEST,
get_dynamic_server_por... | 173 | 5,845 |
sglang | python/sglang/multimodal_gen/test/single_test_file/test_ar_models.py | .py | """End-to-end tests for diffusion models with AR stage.
Launches AR model instances plus a DiffusionServer,
sends a generation request through the HTTP front-end, and verifies
that a non-empty output comes back.
Run directly:
pytest -v python/sglang/multimodal_gen/test/server/test_ar_models.py
pytest -v ... ... | 181 | 5,571 |
sglang | python/sglang/multimodal_gen/test/single_test_file/component_accuracy/utils.py | .py | from __future__ import annotations
import json
import os
import shlex
from contextlib import nullcontext
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Tuple
import torch
import torch.nn as nn
from safetensors.torch import load_file as safetensors_load_file
from torch.distributed.tens... | 925 | 31,268 |
sglang | python/sglang/multimodal_gen/test/single_test_file/component_accuracy/test_component_accuracy_1_gpu.py | .py | import pytest
from sglang.multimodal_gen.test.single_test_file.component_accuracy.config import (
ComponentType,
get_skip_reason,
should_skip_component,
)
from sglang.multimodal_gen.test.single_test_file.component_accuracy.engine import (
AccuracyEngine,
)
from sglang.multimodal_gen.test.single_test_fi... | 90 | 2,955 |
sglang | python/sglang/multimodal_gen/test/single_test_file/component_accuracy/hooks.py | .py | from __future__ import annotations
import inspect
from dataclasses import dataclass, field
from typing import Any, Callable, Dict, Optional
import torch
import torch.nn as nn
from sglang.multimodal_gen.test.single_test_file.component_accuracy.config import (
DEFAULT_TIMESTEP,
I2V_IMAGE_DIM,
TIMESTEP_NORM... | 679 | 24,151 |
sglang | python/sglang/multimodal_gen/test/single_test_file/component_accuracy/test_component_accuracy_2_gpu.py | .py | import pytest
from sglang.multimodal_gen.test.single_test_file.component_accuracy.config import (
ComponentType,
get_skip_reason,
should_skip_component,
)
from sglang.multimodal_gen.test.single_test_file.component_accuracy.engine import (
AccuracyEngine,
)
from sglang.multimodal_gen.test.single_test_fi... | 90 | 2,960 |
sglang | python/sglang/multimodal_gen/test/single_test_file/component_accuracy/engine.py | .py | from __future__ import annotations
import gc
import os
from contextlib import contextmanager
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Tuple
import diffusers
import torch
import torch.nn as nn
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
... | 769 | 28,153 |
sglang | python/sglang/multimodal_gen/test/single_test_file/component_accuracy/config.py | .py | from __future__ import annotations
from dataclasses import dataclass
from enum import Enum
from typing import Dict, Optional
from sglang.multimodal_gen.test.server.testcase_configs import DiffusionTestCase
class ComponentType(str, Enum):
VAE = "vae"
TRANSFORMER = "transformer"
TEXT_ENCODER = "text_encod... | 357 | 17,340 |
sglang | python/sglang/multimodal_gen/test/single_test_file/component_accuracy/testcase_configs.py | .py | from __future__ import annotations
from sglang.multimodal_gen.test.server.gpu_cases import (
ONE_GPU_CASES,
TWO_GPU_CASES,
)
from sglang.multimodal_gen.test.server.testcase_configs import DiffusionTestCase
from sglang.multimodal_gen.test.single_test_file.component_accuracy.config import (
ComponentType,
... | 79 | 2,549 |
sglang | python/sglang/multimodal_gen/configs/utils.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
import argparse
from typing import Any
def update_config_from_args(
config: Any, args_dict: dict[str, Any], prefix: str = "", pop_args: bool = False
) -> bool:
"""
Update configuration object from arguments dictionary.
Args:
... | 63 | 2,119 |
sglang | python/sglang/multimodal_gen/configs/quantization/qvg_kv.py | .py | # SPDX-License-Identifier: Apache-2.0
"""CLI-facing configuration for Quant-VideoGen PRQ KV-cache quantization.
Mirrors the SRT `--kv-cache-dtype` pattern: the on/off + tuning knobs live on a
typed config object carried by ServerArgs (see `kv_cache_quant_config`), instead
of a pile of raw environment variables.
Defau... | 102 | 4,336 |
sglang | python/sglang/multimodal_gen/configs/quantization/nunchaku.py | .py | # SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import os
import re
from dataclasses import dataclass, replace
from typing import Any
import torch
from sglang.multimodal_gen.runtime.layers.quantization.configs.nunchaku_config import (
NunchakuConfig,
is_nunchaku_available,
)
from sg... | 223 | 8,500 |
sglang | python/sglang/multimodal_gen/configs/post_training/__init__.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Configuration for post-training and RL-related features (e.g. rollout)."""
from sglang.multimodal_gen.configs.post_training.rl_rollout import RLRolloutArgs
__all__ = ["RLRolloutArgs"]
| 8 | 228 |
sglang | python/sglang/multimodal_gen/configs/post_training/rl_rollout.py | .py | # SPDX-License-Identifier: Apache-2.0
"""CLI- and API-facing configuration for diffusion post-training / rollout paths."""
from __future__ import annotations
import argparse
import math
from dataclasses import dataclass
from typing import Any, Callable
from sglang.multimodal_gen.utils import StoreBoolean
_VALID_RO... | 122 | 4,322 |
sglang | python/sglang/multimodal_gen/configs/post_training/pipeline_configs/qwen_image_rollout_pipeline_mixin.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Rollout / RL hooks for Qwen-Image pipeline configs."""
from __future__ import annotations
import torch
from sglang.multimodal_gen.runtime.post_training.sp_utils import (
all_gather_if_sp_sharded,
maybe_trim_sp_rope_seq_for_batch,
)
class QwenImageRolloutPipelineMixi... | 28 | 911 |
sglang | python/sglang/multimodal_gen/configs/post_training/pipeline_configs/__init__.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Rollout / RL hooks mixed into multimodal pipeline configs."""
from sglang.multimodal_gen.configs.post_training.pipeline_configs.qwen_image_rollout_pipeline_mixin import (
QwenImageRolloutPipelineMixin,
)
from sglang.multimodal_gen.configs.post_training.pipeline_configs.zima... | 15 | 475 |
sglang | python/sglang/multimodal_gen/configs/post_training/pipeline_configs/zimage_rollout_pipeline_mixin.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Rollout / RL hooks for Z-Image pipeline configs."""
from __future__ import annotations
import torch
from sglang.multimodal_gen.runtime.post_training.sp_utils import (
all_gather_if_sp_sharded,
maybe_trim_sp_rope_seq_for_batch,
)
class ZImageRolloutPipelineMixin:
... | 28 | 889 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/qwen_image.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
from dataclasses import dataclass, field
from typing import Callable
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.qwenimage import (
QwenImageDitC... | 862 | 32,128 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/diffusers_generic.py | .py | # SPDX-License-Identifier: Apache-2.0
"""
Generic pipeline configuration for diffusers backend.
This module provides a minimal pipeline configuration that works with the diffusers backend.
Since diffusers handles its own model loading and configuration, this config is intentionally minimal.
"""
from dataclasses impor... | 130 | 4,401 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/mova.py | .py | # SPDX-License-Identifier: Apache-2.0
"""
MOVA pipeline configuration.
"""
from dataclasses import dataclass, field
import numpy as np
import torch
import torch.nn.functional as F
from PIL import Image
from sglang.multimodal_gen.configs.models.dits import MOVAAudioConfig, MOVAVideoConfig
from sglang.multimodal_gen.c... | 197 | 7,358 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/hunyuan.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
# SPDX-License-Identifier: Apache-2.0
from collections.abc import Callable
from dataclasses import dataclass, field
from typing import TypedDict
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sg... | 170 | 6,055 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/joy_image.py | .py | import math
from dataclasses import dataclass, field
from typing import Callable, Tuple
import torch
import torchvision.transforms.functional as TF
from einops import rearrange
from PIL import Image
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs... | 431 | 15,267 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/glm_image.py | .py | from dataclasses import dataclass, field
import torch
from diffusers.image_processor import VaeImageProcessor
from sglang.multimodal_gen.configs.models import DiTConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.glmimage import GlmImageDitConfig
from sglang.multimodal_gen.configs.models.encoders.base i... | 121 | 4,635 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/cosmos3.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Cosmos3 pipeline configuration.
A single config serves T2V, I2V, and T2I β same checkpoint, same DiT, same
VAE. ``task_type`` is ``TI2V`` so the request validator accepts an optional
``image_path`` (for I2V) without requiring it. Per-modality dispatch happens
in the stages from... | 168 | 6,782 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/longlive2.py | .py | # SPDX-License-Identifier: Apache-2.0
# Adapted from https://github.com/NVlabs/LongLive
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models import DiTConfig
from sglang.multimodal_gen.configs.models.dits.longlive2 import LongLive2VideoConfig
from sglang.multimodal_gen.configs.pipeline_c... | 61 | 2,215 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/ltx_2.py | .py | import dataclasses
from dataclasses import field
from typing import Callable, Optional
import torch
from sglang.multimodal_gen.configs.models.dits.ltx_2 import LTX2Config
from sglang.multimodal_gen.configs.models.encoders import (
BaseEncoderOutput,
EncoderConfig,
)
from sglang.multimodal_gen.configs.models.e... | 726 | 28,854 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/flux.py | .py | import math
from dataclasses import dataclass, field
from typing import Callable, List, Optional
import PIL
import torch
from diffusers.image_processor import VaeImageProcessor
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.flux impo... | 826 | 29,280 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/pi05.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.pipeline_configs.base import (
ModelTaskType,
PipelineConfig,
)
from sglang.multimodal_gen.configs.pipeline_configs.model_deployment_config import (
ModelDeploymentConfig,
)
@dataclass
class... | 105 | 3,720 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/helios.py | .py | # SPDX-License-Identifier: Apache-2.0
from collections.abc import Callable
from dataclasses import dataclass, field
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.helios import HeliosConfig
from sglang.multimodal_gen.con... | 121 | 4,112 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/__init__.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
from sglang.multimodal_gen.configs.pipeline_configs.base import (
PipelineConfig,
SlidingTileAttnConfig,
)
from sglang.multimodal_gen.configs.pipeline_configs.cosmos3 import Cosmos3Config
from sglang.multimodal_gen.configs.pipeline_configs.diff... | 102 | 3,328 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/longcat_image.py | .py | from dataclasses import dataclass, field
from typing import Callable
import numpy as np
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.longcat_image import (
LongCatImageDitConfig,
)
from sglang.multimodal_gen.config... | 419 | 16,372 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/krea2.py | .py | # Krea-2 (K2) pipeline config.
from dataclasses import dataclass, field
import torch
from diffusers.image_processor import VaeImageProcessor
from sglang.multimodal_gen.configs.models import DiTConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.krea2 import Krea2DitConfig
from sglang.multimodal_gen.confi... | 166 | 7,076 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/ltx_2_5.py | .py | # SPDX-License-Identifier: Apache-2.0
import dataclasses
from dataclasses import field
from sglang.multimodal_gen.configs.models.dits.ltx_2_5 import LTX25Config
from sglang.multimodal_gen.configs.models.encoders import (
EncoderConfig,
Gemma4UnifiedConfig,
)
from sglang.multimodal_gen.configs.models.vaes.ltx_2... | 58 | 2,123 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/sana.py | .py | # SPDX-License-Identifier: Apache-2.0
#
# Pipeline configuration for SANA text-to-image generation.
#
# SANA produces 4D spatial latents (B, C, H', W') directly β unlike Flux/QwenImage
# which use packed token-style latents (B, S, D). This means:
# - We inherit SpatialImagePipelineConfig (not ImagePipelineConfig)
# ... | 131 | 5,199 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/wan.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
# SPDX-License-Identifier: Apache-2.0
from collections.abc import Callable
from dataclasses import dataclass, field
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.m... | 314 | 9,849 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/joy_echo.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from typing import Optional
from sglang.multimodal_gen.configs.models.dits.joy_echo import JoyEchoConfig
from sglang.multimodal_gen.configs.models.vaes.ltx_video import LTXVideoVAEConfig
from sglang.multimodal_gen.configs.pipeline_configs.b... | 61 | 1,798 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/minimax_h3.py | .py | # SPDX-License-Identifier: Apache-2.0
import os
from dataclasses import dataclass, field
import torch
from sglang.multimodal_gen.configs.models.dits.minimax_h3 import MiniMaxH3DiTConfig
from sglang.multimodal_gen.configs.models.encoders.minimax_h3_qwen3vl import (
MiniMaxH3Qwen3VLConfig,
)
from sglang.multimodal_... | 212 | 8,241 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/ideogram.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.ideogram import (
Ideogram4DistilledDiTConfig,
Ideogram4DiTConfig,
)
from sglang.multimodal_gen.con... | 311 | 6,083 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/model_deployment_config.py | .py | """
ModelDeploymentConfig provides model-specific config on how to deploy a model optimally
"""
from dataclasses import dataclass
from typing import Literal
OffloadComponentName = Literal["dit", "text_encoder", "image_encoder", "vae"]
@dataclass(frozen=True)
class ModelDeploymentConfig:
dit_layerwise_offload_m... | 37 | 1,605 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/sana_wm.py | .py | # SPDX-License-Identifier: Apache-2.0
from collections.abc import Callable
from dataclasses import dataclass, field
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.sana_wm import SanaWMConfig
from sglang.multimodal_gen.configs.models.... | 336 | 14,457 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/zimage.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
import math
from dataclasses import dataclass, field
from typing import Callable
import torch
import torch.distributed as dist
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.mode... | 518 | 19,275 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/lingbot_world.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
# Adapted from: https://github.com/Robbyant/lingbot-world
# SPDX-License-Identifier: Apache-2.0
import html
import re
from collections.abc import Callable
from dataclasses import dataclass, field
from typing import Any
import numpy as np
import torch
... | 451 | 15,178 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/stablediffusion3.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Stable Diffusion 3 pipeline configuration."""
import os
from dataclasses import dataclass, field
from typing import Callable
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits import... | 203 | 6,598 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/ernie_image.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from typing import Callable
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.ernie_image import ErnieImageDitConfig
from sglang.multimodal_gen... | 261 | 9,920 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/hunyuan3d.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from typing import Optional
from sglang.multimodal_gen.configs.models import DiTConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.hunyuan3d import Hunyuan3DDiTConfig
from sglang.multimodal_gen.configs.models.encoders.clip imp... | 81 | 2,762 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/lingbot_video_moe.py | .py | # SPDX-License-Identifier: Apache-2.0
from collections.abc import Callable
from dataclasses import dataclass, field
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits import LingBotVideoMoEConfig
from sglang.multimodal_gen.... | 87 | 3,075 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/base.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
# SPDX-License-Identifier: Apache-2.0
import json
import math
import os
from collections.abc import Callable
from dataclasses import asdict, dataclass, field, fields
from enum import Enum, auto
from typing import Any
import numpy as np
import PIL
impo... | 1,313 | 51,630 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/sana_video.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Pipeline configuration for SANA-Video text-to-video generation."""
from collections.abc import Callable
from dataclasses import dataclass, field
import torch
from sglang.multimodal_gen.configs.models import DiTConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.s... | 119 | 4,089 |
sglang | python/sglang/multimodal_gen/configs/pipeline_configs/flux_finetuned.py | .py | """
Pipeline configuration for Flux fine-tuned/distilled models.
This module provides specialized handling for Flux fine-tuned models from HuggingFace,
such as fal/FLUX.2-Tiny-AutoEncoder and other community fine-tuned variants.
Key differences from standard Flux2PipelineConfig:
- Handles custom VAE architectures loa... | 117 | 4,621 |
sglang | python/sglang/multimodal_gen/configs/models/base.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
# SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field, fields
from typing import Any, Dict
from sglang.multimodal_gen.runtime.utils.logging_utils import init_logger
logger = init_logger(__name__)
@dataclass
class ArchConfig... | 103 | 3,665 |
sglang | python/sglang/multimodal_gen/configs/models/fsdp.py | .py | # SPDX-License-Identifier: Apache-2.0
def is_module_list_entry(name: str, container_name: str) -> bool:
# Match only direct block entries, not their inner submodules.
parts = name.split(".")
return len(parts) >= 2 and parts[-2] == container_name and parts[-1].isdigit()
def is_module_list_entry_in(name: ... | 81 | 2,390 |
sglang | python/sglang/multimodal_gen/configs/models/dits/joy_image.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class JoyImageArchConfig(DiTArchConfig):
param_names_mapping: dict = field(
default_factory=lambda: {
# Condition embe... | 63 | 3,337 |
sglang | python/sglang/multimodal_gen/configs/models/dits/sana_wm_refiner.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class SanaWMRefinerArchConfig(DiTArchConfig):
# Core dims
in_channels: int = 128
out_channels: int = 128
patch_size: int = 1
... | 62 | 2,061 |
sglang | python/sglang/multimodal_gen/configs/models/dits/mova_video.py | .py | # Copied and adapted from: mossVG/mova/diffusion/models/wan_video_dit.py
# SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class MOVAVideoArchConfig(DiTArchConfig):
param_names_mapping: di... | 61 | 2,293 |
sglang | python/sglang/multimodal_gen/configs/models/dits/longlive2.py | .py | # SPDX-License-Identifier: Apache-2.0
# Adapted from https://github.com/NVlabs/LongLive
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig
from sglang.multimodal_gen.configs.models.dits.wanvideo import (
WanVideoArchConfig,
WanVideoConfig,
)
@da... | 86 | 5,117 |
sglang | python/sglang/multimodal_gen/configs/models/dits/qwenimage.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
# SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from typing import Tuple
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class QwenImageArchConfig(DiTArchConfig):
patc... | 64 | 1,960 |
sglang | python/sglang/multimodal_gen/configs/models/dits/ltx_2.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from enum import Enum
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
class LTXModelType(Enum):
"""
Model type enum mirroring upstream `LTXModelType`.
Upstream reference:
- `LTX-2/pac... | 193 | 7,233 |
sglang | python/sglang/multimodal_gen/configs/models/dits/flux.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
# SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from typing import Tuple
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class FluxArchConfig(DiTArchConfig):
patch_siz... | 117 | 7,579 |
sglang | python/sglang/multimodal_gen/configs/models/dits/helios.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class HeliosArchConfig(DiTArchConfig):
param_names_mapping: dict = field(
default_factory=lambda: {
# Patch embeddings
... | 75 | 3,146 |
sglang | python/sglang/multimodal_gen/configs/models/dits/__init__.py | .py | # Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
from sglang.multimodal_gen.configs.models.dits.cosmos3video import Cosmos3VideoConfig
from sglang.multimodal_gen.configs.models.dits.helios import HeliosConfig
from sglang.multimodal_gen.configs.models.dits.hunyuan3d import Hunyuan3DDiTConfig
from sgla... | 44 | 1,749 |
sglang | python/sglang/multimodal_gen/configs/models/dits/longcat_image.py | .py | from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class LongCatImageArchConfig(DiTArchConfig):
patch_size: int = 1
in_channels: int = 64 # packed: 16 * 4
num_layers: int = 19
num_single_layers: int = 38
attenti... | 29 | 889 |
sglang | python/sglang/multimodal_gen/configs/models/dits/krea2.py | .py | # Krea-2 (K2) single-stream MMDiT architecture config.
#
# Parameter names follow the released K2 checkpoint, so the MMDiT safetensors load
# without remapping (identity `param_names_mapping`).
from dataclasses import dataclass, field
from typing import Tuple
from sglang.multimodal_gen.configs.models.dits.base import ... | 78 | 2,904 |
sglang | python/sglang/multimodal_gen/configs/models/dits/ltx_2_5.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.ltx_2 import (
LTX2_PARAM_NAMES_MAPPING,
LTX2_REVERSE_PARAM_NAMES_MAPPING,
LTX2ArchConfig,
LTX2Config,
LTX2RopeType,
)
# LTX-2.5 renames the prompt adaLN modules and adds t... | 75 | 2,505 |
sglang | python/sglang/multimodal_gen/configs/models/dits/sana.py | .py | # SPDX-License-Identifier: Apache-2.0
#
# Architecture and model configuration for SANA DiT (Diffusion Transformer).
#
# SANA uses a linear-attention-based transformer that replaces standard
# quadratic self-attention with ReLU-based linear attention, enabling
# efficient high-resolution image synthesis. Cross-attentio... | 65 | 2,398 |
sglang | python/sglang/multimodal_gen/configs/models/dits/mova_audio.py | .py | # Copied and adapted from: mossVG/mova/diffusion/models/wan_audio_dit.py
# SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class MOVAAudioArchConfig(DiTArchConfig):
param_names_mapping: di... | 62 | 2,322 |
sglang | python/sglang/multimodal_gen/configs/models/dits/joy_echo.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.ltx_2 import (
LTX2ArchConfig,
LTX2Config,
)
@dataclass
class JoyEchoArchConfig(LTX2ArchConfig):
"""JoyEcho DiT architecture config (LTX-2.3 AV base)."""
caption_proj_before_... | 23 | 573 |
sglang | python/sglang/multimodal_gen/configs/models/dits/cosmos3video.py | .py | # SPDX-License-Identifier: Apache-2.0
"""Cosmos3 video DiT architecture configuration."""
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
def _build_cosmos3_param_names_mapping(gated_mlp: bool = True) -> dict:
"""Map diffusers-format C... | 225 | 9,374 |
sglang | python/sglang/multimodal_gen/configs/models/dits/minimax_h3.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
MINIMAX_H3_PACKED_SEQUENCE_ALIGNMENT = 64
MINIMAX_H3_ADALN_MODALITY_NUM = 3
@dataclass
class MiniMaxH3DiTArchConfig(DiTArchConfig):
# accept Diffuser... | 107 | 4,464 |
sglang | python/sglang/multimodal_gen/configs/models/dits/ideogram.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class Ideogram4DiTArchConfig(DiTArchConfig):
adaln_dim: int = 512
attention_head_dim: int = 256
in_channels: int = 128
interme... | 61 | 1,963 |
sglang | python/sglang/multimodal_gen/configs/models/dits/sana_wm.py | .py | # SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
@dataclass
class SanaWMArchConfig(DiTArchConfig):
# --- Core dims (upstream: depth=20, hidden=2240, heads=20, linear_head_dim=112) ---
patch_size... | 106 | 3,848 |
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