Spaces:
Runtime error
Runtime error
File size: 3,614 Bytes
5672777 93528c6 5672777 |
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 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 |
# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# 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.
"""3D Backbones configurations."""
from typing import Optional, Tuple
# Import libraries
import dataclasses
from official.modeling import hyperparams
@dataclasses.dataclass
class ResNet3DBlock(hyperparams.Config):
"""Configuration of a ResNet 3D block."""
temporal_strides: int = 1
temporal_kernel_sizes: Tuple[int, ...] = ()
use_self_gating: bool = False
@dataclasses.dataclass
class ResNet3D(hyperparams.Config):
"""ResNet config."""
model_id: int = 50
stem_type: str = 'v0'
stem_conv_temporal_kernel_size: int = 5
stem_conv_temporal_stride: int = 2
stem_pool_temporal_stride: int = 2
block_specs: Tuple[ResNet3DBlock, ...] = ()
stochastic_depth_drop_rate: float = 0.0
se_ratio: float = 0.0
@dataclasses.dataclass
class ResNet3D50(ResNet3D):
"""Block specifications of the Resnet50 (3D) model."""
model_id: int = 50
block_specs: Tuple[
ResNet3DBlock, ResNet3DBlock, ResNet3DBlock, ResNet3DBlock] = (
ResNet3DBlock(temporal_strides=1,
temporal_kernel_sizes=(3, 3, 3),
use_self_gating=True),
ResNet3DBlock(temporal_strides=1,
temporal_kernel_sizes=(3, 1, 3, 1),
use_self_gating=True),
ResNet3DBlock(temporal_strides=1,
temporal_kernel_sizes=(3, 1, 3, 1, 3, 1),
use_self_gating=True),
ResNet3DBlock(temporal_strides=1,
temporal_kernel_sizes=(1, 3, 1),
use_self_gating=True))
@dataclasses.dataclass
class ResNet3DRS(ResNet3D):
"""Block specifications of the ResNet-RS (3D) model."""
model_id: int = 50
stem_type: str = 'v1'
stem_conv_temporal_kernel_size: int = 5
stem_conv_temporal_stride: int = 2
stem_pool_temporal_stride: int = 2
stochastic_depth_drop_rate: float = 0.1
se_ratio: float = 0.2
block_specs: Tuple[
ResNet3DBlock, ResNet3DBlock, ResNet3DBlock, ResNet3DBlock] = (
ResNet3DBlock(temporal_strides=1,
temporal_kernel_sizes=(1,),
use_self_gating=True),
ResNet3DBlock(temporal_strides=1,
temporal_kernel_sizes=(1,),
use_self_gating=True),
ResNet3DBlock(temporal_strides=1,
temporal_kernel_sizes=(3,),
use_self_gating=True),
ResNet3DBlock(temporal_strides=1,
temporal_kernel_sizes=(3,),
use_self_gating=True))
@dataclasses.dataclass
class Backbone3D(hyperparams.OneOfConfig):
"""Configuration for backbones.
Attributes:
type: 'str', type of backbone be used, one of the fields below.
resnet_3d: resnet3d backbone config.
resnet_3d_rs: resnet3d-rs backbone config.
"""
type: Optional[str] = None
resnet_3d: ResNet3D = dataclasses.field(default_factory=ResNet3D50)
resnet_3d_rs: ResNet3D = dataclasses.field(default_factory=ResNet3DRS)
|