MobileViT¶
MobileViT backbone based on MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer.
MobileViT was introduced by combining inverted residual blocks with transformer-based MobileViT blocks. In line with this, it is possible to select between inverted residual blocks (as mv2) and MobileViT models for each stage of the backbone with detailed configurations according to each block type.
Field list¶
| Field |
Description |
|---|---|
name |
(str) Name must be "mobilevit" to use MobileViT backbone. |
params.patch_size |
(int) Patch size for MobileViT blocks. |
params.num_attention_heads |
(int) The number of heads in the multi-head attention. |
params.attention_dropout_prob |
(float) Dropout probability in the attention. |
params.ffn_dropout_prob |
(float) Dropout probability in the feed-forward network inside of the attention block. |
params.output_expansion_ratio |
(int) Expansion ratio for computing output dimension of the model. If expanded dimension is bigger than 960, it is set to 960. |
params.use_fusion_layer |
(bool) Whether to use fusion layer for MobileViT blocks. |
stage_params[n].block_type |
(str) Determines which block to use, "mv2" or "mobilevit". |
stage_params[n].out_channels |
(int) Output dimension of the block. |
stage_params[n].num_blocks |
(int) The number of blocks in the stage. Note that if block_type is mobilevit, an extra inverted residual block is added before MobileViT blocks. |
stage_params[n].stride |
(int) Stride value for the block. |
stage_params[n].attention_channels |
(int) Dimension for the attention block. If is used only block_type is "mobilevit". |
stage_params[n].ffn_intermediate_channels |
(int) Intermediate dimension for the feed forward network inside of the attention block. |
stage_params[n].dilate |
(bool) Whether to replace stride as dilated convolution. It is used only block_type is mobilevit. |
stage_params[n].ir_expansion_ratio |
(int) Dimension expansion ratio for inverted residual block. |
Model configuration examples¶
MobileViT-xxs
model:
architecture:
backbone:
name: mobilevit
params:
patch_size: 2
num_attention_heads: 4 # num_heads
attention_dropout_prob: 0.1
ffn_dropout_prob: 0.0
output_expansion_ratio: 4
use_fusion_layer: True
stage_params:
-
block_type: 'mv2'
out_channels: 16
num_blocks: 1
stride: 1
ir_expansion_ratio: 2
-
block_type: 'mv2'
out_channels: 24
num_blocks: 3
stride: 2
ir_expansion_ratio: 2
-
block_type: 'mobilevit'
out_channels: 48
num_blocks: 2
stride: 2
attention_channels: 64
ffn_intermediate_channels: 128
dilate: False
ir_expansion_ratio: 2
-
block_type: 'mobilevit'
out_channels: 64
num_blocks: 4
stride: 2
attention_channels: 80
ffn_intermediate_channels: 160
dilate: False
ir_expansion_ratio: 2
-
block_type: 'mobilevit'
out_channels: 80
num_blocks: 3
stride: 2
attention_channels: 96
ffn_intermediate_channels: 192
dilate: False
ir_expansion_ratio: 2
MobileViT-xs
model:
architecture:
backbone:
name: mobilevit
params:
patch_size: 2
num_attention_heads: 4 # num_heads
attention_dropout_prob: 0.1
ffn_dropout_prob: 0.0
output_expansion_ratio: 4
use_fusion_layer: True
stage_params:
-
block_type: 'mv2'
out_channels: 32
num_blocks: 1
stride: 1
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4
-
block_type: 'mv2'
out_channels: 48
num_blocks: 3
stride: 2
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4
-
block_type: 'mobilevit'
out_channels: 64
num_blocks: 2
stride: 2
attention_channels: 96
ffn_intermediate_channels: 192
dilate: False
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4
-
block_type: 'mobilevit'
out_channels: 80
num_blocks: 4
stride: 2
attention_channels: 120
ffn_intermediate_channels: 240
dilate: False
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4
-
block_type: 'mobilevit'
out_channels: 96
num_blocks: 3
stride: 2
attention_channels: 144
ffn_intermediate_channels: 288
dilate: False
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4
MobileViT-s
model:
architecture:
backbone:
name: mobilevit
params:
patch_size: 2
num_attention_heads: 4 # num_heads
attention_dropout_prob: 0.1
ffn_dropout_prob: 0.0
output_expansion_ratio: 4
use_fusion_layer: True
stage_params:
-
block_type: 'mv2'
out_channels: 32
num_blocks: 1
stride: 1
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4
-
block_type: 'mv2'
out_channels: 64
num_blocks: 3
stride: 2
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4
-
block_type: 'mobilevit'
out_channels: 96
num_blocks: 2
stride: 2
attention_channels: 144
ffn_intermediate_channels: 288
dilate: False
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4
-
block_type: 'mobilevit'
out_channels: 128
num_blocks: 4
stride: 2
attention_channels: 192
ffn_intermediate_channels: 384
dilate: False
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4
-
block_type: 'mobilevit'
out_channels: 160
num_blocks: 3
stride: 2
attention_channels: 240
ffn_intermediate_channels: 480
dilate: False
ir_expansion_ratio: 4 # [mv2_exp_mult] * 4