File size: 3,182 Bytes
02e9885 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
# 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.
from hydra.core.config_store import ConfigStore
from .ar_diffusion_decoder_network import DiffusionDecoderGeneralDIT
from .lazy_config_init import LazyCall as L
from .lazy_config_init import LazyDict
num_frames = 57
Cosmos_DiffusionDecoder_7B_INFERENCE_ONLY: LazyDict = LazyDict(
dict(
defaults=[
{"override /net": "faditv2_7b"},
{"override /tokenizer": "cosmos_video_tokenizer_res720_comp8x8x8_t121_ver092624"},
{"override /conditioner": "video_latent_diffusion_decoder_cond"},
{"override /tokenizer_corruptor": "cosmos_video_discrete_tokenizer_res720_comp8x16x16_t49_ver110224"},
"_self_",
],
job=dict(
group="diffusion_deocder_FT_7Bv1_001",
name="DD_FT_7Bv1_003_002_tokenizer888_spatch2_discrete_cond_on_token",
),
model=dict(
diffusion_decoder_cond_sigma_low=0.0,
diffusion_decoder_cond_sigma_high=0.0,
diffusion_decoder_corrupt_prob=0.0,
condition_on_tokenizer_corruptor_token=True,
latent_shape=[
16,
num_frames,
88,
160,
],
tokenizer_corruptor=dict(
pixel_chunk_duration=num_frames,
latent_chunk_duration=1 + (num_frames - 1) // 8,
),
net=L(DiffusionDecoderGeneralDIT)(
diffusion_decoder_condition_on_sigma=False,
max_img_h=240,
max_img_w=240,
rope_h_extrapolation_ratio=1.5,
rope_w_extrapolation_ratio=1.5,
rope_t_extrapolation_ratio=1,
block_x_format="THWBD",
is_diffusion_decoder=True,
patch_spatial=2,
diffusion_decoder_condition_on_token=True,
diffusion_decoder_token_condition_voc_size=64000,
diffusion_decoder_token_condition_dim=32,
),
tokenizer=dict(
video_vae=dict(
pixel_chunk_duration=num_frames,
)
),
conditioner=dict(
latent_condition=dict(
dropout_rate=0.2,
)
),
),
)
)
cs = ConfigStore.instance()
cs.store(
group="experiment",
package="_global_",
name=Cosmos_DiffusionDecoder_7B_INFERENCE_ONLY["job"]["name"],
node=Cosmos_DiffusionDecoder_7B_INFERENCE_ONLY,
)
|