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aa2b5e42
编写于
5月 10, 2021
作者:
A
A. Unique TensorFlower
浏览文件
操作
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差异文件
Internal change
PiperOrigin-RevId: 373084407
上级
3c575a70
变更
19
隐藏空白更改
内联
并排
Showing
19 changed file
with
130 addition
and
89 deletion
+130
-89
official/vision/beta/configs/backbones.py
official/vision/beta/configs/backbones.py
+4
-0
official/vision/beta/configs/maskrcnn.py
official/vision/beta/configs/maskrcnn.py
+9
-2
official/vision/beta/configs/retinanet.py
official/vision/beta/configs/retinanet.py
+14
-4
official/vision/beta/modeling/backbones/efficientnet.py
official/vision/beta/modeling/backbones/efficientnet.py
+4
-4
official/vision/beta/modeling/backbones/factory.py
official/vision/beta/modeling/backbones/factory.py
+20
-9
official/vision/beta/modeling/backbones/factory_test.py
official/vision/beta/modeling/backbones/factory_test.py
+10
-16
official/vision/beta/modeling/backbones/mobilenet.py
official/vision/beta/modeling/backbones/mobilenet.py
+4
-4
official/vision/beta/modeling/backbones/resnet.py
official/vision/beta/modeling/backbones/resnet.py
+4
-4
official/vision/beta/modeling/backbones/resnet_3d.py
official/vision/beta/modeling/backbones/resnet_3d.py
+6
-6
official/vision/beta/modeling/backbones/resnet_deeplab.py
official/vision/beta/modeling/backbones/resnet_deeplab.py
+5
-4
official/vision/beta/modeling/backbones/revnet.py
official/vision/beta/modeling/backbones/revnet.py
+5
-4
official/vision/beta/modeling/backbones/spinenet.py
official/vision/beta/modeling/backbones/spinenet.py
+7
-6
official/vision/beta/modeling/backbones/spinenet_mobile.py
official/vision/beta/modeling/backbones/spinenet_mobile.py
+7
-6
official/vision/beta/modeling/factory.py
official/vision/beta/modeling/factory.py
+12
-8
official/vision/beta/modeling/factory_3d.py
official/vision/beta/modeling/factory_3d.py
+3
-1
official/vision/beta/projects/assemblenet/modeling/assemblenet.py
.../vision/beta/projects/assemblenet/modeling/assemblenet.py
+7
-5
official/vision/beta/projects/deepmac_maskrcnn/tasks/deep_mask_head_rcnn.py
...ta/projects/deepmac_maskrcnn/tasks/deep_mask_head_rcnn.py
+3
-2
official/vision/beta/projects/simclr/tasks/simclr.py
official/vision/beta/projects/simclr/tasks/simclr.py
+2
-1
official/vision/beta/projects/yolo/modeling/backbones/darknet.py
...l/vision/beta/projects/yolo/modeling/backbones/darknet.py
+4
-3
未找到文件。
official/vision/beta/configs/backbones.py
浏览文件 @
aa2b5e42
...
...
@@ -67,6 +67,8 @@ class SpineNet(hyperparams.Config):
"""SpineNet config."""
model_id
:
str
=
'49'
stochastic_depth_drop_rate
:
float
=
0.0
min_level
:
int
=
3
max_level
:
int
=
7
@
dataclasses
.
dataclass
...
...
@@ -76,6 +78,8 @@ class SpineNetMobile(hyperparams.Config):
stochastic_depth_drop_rate
:
float
=
0.0
se_ratio
:
float
=
0.2
expand_ratio
:
int
=
6
min_level
:
int
=
3
max_level
:
int
=
7
@
dataclasses
.
dataclass
...
...
official/vision/beta/configs/maskrcnn.py
浏览文件 @
aa2b5e42
...
...
@@ -437,7 +437,12 @@ def maskrcnn_spinenet_coco() -> cfg.ExperimentConfig:
'instances_val2017.json'
),
model
=
MaskRCNN
(
backbone
=
backbones
.
Backbone
(
type
=
'spinenet'
,
spinenet
=
backbones
.
SpineNet
(
model_id
=
'49'
)),
type
=
'spinenet'
,
spinenet
=
backbones
.
SpineNet
(
model_id
=
'49'
,
min_level
=
3
,
max_level
=
7
,
)),
decoder
=
decoders
.
Decoder
(
type
=
'identity'
,
identity
=
decoders
.
Identity
()),
anchor
=
Anchor
(
anchor_size
=
3
),
...
...
@@ -491,6 +496,8 @@ def maskrcnn_spinenet_coco() -> cfg.ExperimentConfig:
})),
restrictions
=
[
'task.train_data.is_training != None'
,
'task.validation_data.is_training != None'
'task.validation_data.is_training != None'
,
'task.model.min_level == task,model.backbone.spinenet.min_level'
,
'task.model.max_level == task,model.backbone.spinenet.max_level'
,
])
return
config
official/vision/beta/configs/retinanet.py
浏览文件 @
aa2b5e42
...
...
@@ -248,7 +248,10 @@ def retinanet_spinenet_coco() -> cfg.ExperimentConfig:
backbone
=
backbones
.
Backbone
(
type
=
'spinenet'
,
spinenet
=
backbones
.
SpineNet
(
model_id
=
'49'
,
stochastic_depth_drop_rate
=
0.2
)),
model_id
=
'49'
,
stochastic_depth_drop_rate
=
0.2
,
min_level
=
3
,
max_level
=
7
)),
decoder
=
decoders
.
Decoder
(
type
=
'identity'
,
identity
=
decoders
.
Identity
()),
anchor
=
Anchor
(
anchor_size
=
3
),
...
...
@@ -306,7 +309,9 @@ def retinanet_spinenet_coco() -> cfg.ExperimentConfig:
})),
restrictions
=
[
'task.train_data.is_training != None'
,
'task.validation_data.is_training != None'
'task.validation_data.is_training != None'
,
'task.model.min_level == task,model.backbone.spinenet.min_level'
,
'task.model.max_level == task,model.backbone.spinenet.max_level'
,
])
return
config
...
...
@@ -329,7 +334,10 @@ def retinanet_spinenet_mobile_coco() -> cfg.ExperimentConfig:
backbone
=
backbones
.
Backbone
(
type
=
'spinenet_mobile'
,
spinenet_mobile
=
backbones
.
SpineNetMobile
(
model_id
=
'49'
,
stochastic_depth_drop_rate
=
0.2
)),
model_id
=
'49'
,
stochastic_depth_drop_rate
=
0.2
,
min_level
=
3
,
max_level
=
7
)),
decoder
=
decoders
.
Decoder
(
type
=
'identity'
,
identity
=
decoders
.
Identity
()),
head
=
RetinaNetHead
(
num_filters
=
48
,
use_separable_conv
=
True
),
...
...
@@ -388,7 +396,9 @@ def retinanet_spinenet_mobile_coco() -> cfg.ExperimentConfig:
})),
restrictions
=
[
'task.train_data.is_training != None'
,
'task.validation_data.is_training != None'
'task.validation_data.is_training != None'
,
'task.model.min_level == task,model.backbone.spinenet_mobile.min_level'
,
'task.model.max_level == task,model.backbone.spinenet_mobile.max_level'
,
])
return
config
official/vision/beta/modeling/backbones/efficientnet.py
浏览文件 @
aa2b5e42
...
...
@@ -297,12 +297,12 @@ class EfficientNet(tf.keras.Model):
@
factory
.
register_backbone_builder
(
'efficientnet'
)
def
build_efficientnet
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
:
hyperparams
.
Config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds EfficientNet backbone from a config."""
backbone_type
=
model_config
.
backbone
.
type
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_type
=
backbone_config
.
type
backbone_cfg
=
backbone_config
.
get
()
assert
backbone_type
==
'efficientnet'
,
(
f
'Inconsistent backbone type '
f
'
{
backbone_type
}
'
)
...
...
official/vision/beta/modeling/backbones/factory.py
浏览文件 @
aa2b5e42
...
...
@@ -42,6 +42,8 @@ in place that uses it.
"""
from
typing
import
Sequence
,
Union
# Import libraries
import
tensorflow
as
tf
...
...
@@ -81,22 +83,31 @@ def register_backbone_builder(key: str):
return
registry
.
register
(
_REGISTERED_BACKBONE_CLS
,
key
)
def
build_backbone
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
def
build_backbone
(
input_specs
:
Union
[
tf
.
keras
.
layers
.
InputSpec
,
Sequence
[
tf
.
keras
.
layers
.
InputSpec
]],
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
,
**
kwargs
)
->
tf
.
keras
.
Model
:
"""Builds backbone from a config.
Args:
input_specs: A `tf.keras.layers.InputSpec` of input.
model_config: A `OneOfConfig` of model config.
input_specs: A (sequence of) `tf.keras.layers.InputSpec` of input.
backbone_config: A `OneOfConfig` of backbone config.
norm_activation_config: A config for normalization/activation layer.
l2_regularizer: A `tf.keras.regularizers.Regularizer` object. Default to
None.
**kwargs: Additional keyword args to be passed to backbone builder.
Returns:
A `tf.keras.Model` instance of the backbone.
"""
backbone_builder
=
registry
.
lookup
(
_REGISTERED_BACKBONE_CLS
,
model_config
.
backbone
.
type
)
return
backbone_builder
(
input_specs
,
model_config
,
l2_regularizer
)
backbone_config
.
type
)
return
backbone_builder
(
input_specs
=
input_specs
,
backbone_config
=
backbone_config
,
norm_activation_config
=
norm_activation_config
,
l2_regularizer
=
l2_regularizer
,
**
kwargs
)
official/vision/beta/modeling/backbones/factory_test.py
浏览文件 @
aa2b5e42
...
...
@@ -22,7 +22,6 @@ from tensorflow.python.distribute import combinations
from
official.vision.beta.configs
import
backbones
as
backbones_cfg
from
official.vision.beta.configs
import
backbones_3d
as
backbones_3d_cfg
from
official.vision.beta.configs
import
common
as
common_cfg
from
official.vision.beta.configs
import
retinanet
as
retinanet_cfg
from
official.vision.beta.modeling
import
backbones
from
official.vision.beta.modeling.backbones
import
factory
...
...
@@ -42,12 +41,11 @@ class FactoryTest(tf.test.TestCase, parameterized.TestCase):
resnet
=
backbones_cfg
.
ResNet
(
model_id
=
model_id
,
se_ratio
=
0.0
))
norm_activation_config
=
common_cfg
.
NormActivation
(
norm_momentum
=
0.99
,
norm_epsilon
=
1e-5
,
use_sync_bn
=
False
)
model_config
=
retinanet_cfg
.
RetinaNet
(
backbone
=
backbone_config
,
norm_activation
=
norm_activation_config
)
factory_network
=
factory
.
build_backbone
(
input_specs
=
tf
.
keras
.
layers
.
InputSpec
(
shape
=
[
None
,
None
,
None
,
3
]),
model_config
=
model_config
)
backbone_config
=
backbone_config
,
norm_activation_config
=
norm_activation_config
)
network_config
=
network
.
get_config
()
factory_network_config
=
factory_network
.
get_config
()
...
...
@@ -74,12 +72,11 @@ class FactoryTest(tf.test.TestCase, parameterized.TestCase):
model_id
=
model_id
,
se_ratio
=
se_ratio
))
norm_activation_config
=
common_cfg
.
NormActivation
(
norm_momentum
=
0.99
,
norm_epsilon
=
1e-5
,
use_sync_bn
=
False
)
model_config
=
retinanet_cfg
.
RetinaNet
(
backbone
=
backbone_config
,
norm_activation
=
norm_activation_config
)
factory_network
=
factory
.
build_backbone
(
input_specs
=
tf
.
keras
.
layers
.
InputSpec
(
shape
=
[
None
,
None
,
None
,
3
]),
model_config
=
model_config
)
backbone_config
=
backbone_config
,
norm_activation_config
=
norm_activation_config
)
network_config
=
network
.
get_config
()
factory_network_config
=
factory_network
.
get_config
()
...
...
@@ -108,12 +105,11 @@ class FactoryTest(tf.test.TestCase, parameterized.TestCase):
model_id
=
model_id
,
filter_size_scale
=
filter_size_scale
))
norm_activation_config
=
common_cfg
.
NormActivation
(
norm_momentum
=
0.99
,
norm_epsilon
=
1e-5
,
use_sync_bn
=
False
)
model_config
=
retinanet_cfg
.
RetinaNet
(
backbone
=
backbone_config
,
norm_activation
=
norm_activation_config
)
factory_network
=
factory
.
build_backbone
(
input_specs
=
tf
.
keras
.
layers
.
InputSpec
(
shape
=
[
None
,
None
,
None
,
3
]),
model_config
=
model_config
)
backbone_config
=
backbone_config
,
norm_activation_config
=
norm_activation_config
)
network_config
=
network
.
get_config
()
factory_network_config
=
factory_network
.
get_config
()
...
...
@@ -141,13 +137,12 @@ class FactoryTest(tf.test.TestCase, parameterized.TestCase):
spinenet
=
backbones_cfg
.
SpineNet
(
model_id
=
model_id
))
norm_activation_config
=
common_cfg
.
NormActivation
(
norm_momentum
=
0.99
,
norm_epsilon
=
1e-5
,
use_sync_bn
=
False
)
model_config
=
retinanet_cfg
.
RetinaNet
(
backbone
=
backbone_config
,
norm_activation
=
norm_activation_config
)
factory_network
=
factory
.
build_backbone
(
input_specs
=
tf
.
keras
.
layers
.
InputSpec
(
shape
=
[
None
,
input_size
,
input_size
,
3
]),
model_config
=
model_config
)
backbone_config
=
backbone_config
,
norm_activation_config
=
norm_activation_config
)
network_config
=
network
.
get_config
()
factory_network_config
=
factory_network
.
get_config
()
...
...
@@ -166,12 +161,11 @@ class FactoryTest(tf.test.TestCase, parameterized.TestCase):
revnet
=
backbones_cfg
.
RevNet
(
model_id
=
model_id
))
norm_activation_config
=
common_cfg
.
NormActivation
(
norm_momentum
=
0.99
,
norm_epsilon
=
1e-5
,
use_sync_bn
=
False
)
model_config
=
retinanet_cfg
.
RetinaNet
(
backbone
=
backbone_config
,
norm_activation
=
norm_activation_config
)
factory_network
=
factory
.
build_backbone
(
input_specs
=
tf
.
keras
.
layers
.
InputSpec
(
shape
=
[
None
,
None
,
None
,
3
]),
model_config
=
model_config
)
backbone_config
=
backbone_config
,
norm_activation_config
=
norm_activation_config
)
network_config
=
network
.
get_config
()
factory_network_config
=
factory_network
.
get_config
()
...
...
official/vision/beta/modeling/backbones/mobilenet.py
浏览文件 @
aa2b5e42
...
...
@@ -766,12 +766,12 @@ class MobileNet(tf.keras.Model):
@
factory
.
register_backbone_builder
(
'mobilenet'
)
def
build_mobilenet
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
:
hyperparams
.
Config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds MobileNet backbone from a config."""
backbone_type
=
model_config
.
backbone
.
type
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_type
=
backbone_config
.
type
backbone_cfg
=
backbone_config
.
get
()
assert
backbone_type
==
'mobilenet'
,
(
f
'Inconsistent backbone type '
f
'
{
backbone_type
}
'
)
...
...
official/vision/beta/modeling/backbones/resnet.py
浏览文件 @
aa2b5e42
...
...
@@ -372,12 +372,12 @@ class ResNet(tf.keras.Model):
@
factory
.
register_backbone_builder
(
'resnet'
)
def
build_resnet
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
:
hyperparams
.
Config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds ResNet backbone from a config."""
backbone_type
=
model_config
.
backbone
.
type
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_type
=
backbone_config
.
type
backbone_cfg
=
backbone_config
.
get
()
assert
backbone_type
==
'resnet'
,
(
f
'Inconsistent backbone type '
f
'
{
backbone_type
}
'
)
...
...
official/vision/beta/modeling/backbones/resnet_3d.py
浏览文件 @
aa2b5e42
...
...
@@ -378,11 +378,11 @@ class ResNet3D(tf.keras.Model):
@
factory
.
register_backbone_builder
(
'resnet_3d'
)
def
build_resnet3d
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds ResNet 3d backbone from a config."""
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_cfg
=
backbone_config
.
get
()
# Flatten configs before passing to the backbone.
temporal_strides
=
[]
...
...
@@ -416,11 +416,11 @@ def build_resnet3d(
@
factory
.
register_backbone_builder
(
'resnet_3d_rs'
)
def
build_resnet3d_rs
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
:
hyperparams
.
Config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds ResNet-3D-RS backbone from a config."""
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_cfg
=
backbone_config
.
get
()
# Flatten configs before passing to the backbone.
temporal_strides
=
[]
...
...
official/vision/beta/modeling/backbones/resnet_deeplab.py
浏览文件 @
aa2b5e42
...
...
@@ -18,6 +18,7 @@ from typing import Callable, Optional, Tuple, List
import
numpy
as
np
import
tensorflow
as
tf
from
official.modeling
import
hyperparams
from
official.modeling
import
tf_utils
from
official.vision.beta.modeling.backbones
import
factory
from
official.vision.beta.modeling.layers
import
nn_blocks
...
...
@@ -340,12 +341,12 @@ class DilatedResNet(tf.keras.Model):
@
factory
.
register_backbone_builder
(
'dilated_resnet'
)
def
build_dilated_resnet
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds ResNet backbone from a config."""
backbone_type
=
model_config
.
backbone
.
type
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_type
=
backbone_config
.
type
backbone_cfg
=
backbone_config
.
get
()
assert
backbone_type
==
'dilated_resnet'
,
(
f
'Inconsistent backbone type '
f
'
{
backbone_type
}
'
)
...
...
official/vision/beta/modeling/backbones/revnet.py
浏览文件 @
aa2b5e42
...
...
@@ -18,6 +18,7 @@
from
typing
import
Any
,
Callable
,
Dict
,
Optional
# Import libraries
import
tensorflow
as
tf
from
official.modeling
import
hyperparams
from
official.modeling
import
tf_utils
from
official.vision.beta.modeling.backbones
import
factory
from
official.vision.beta.modeling.layers
import
nn_blocks
...
...
@@ -213,12 +214,12 @@ class RevNet(tf.keras.Model):
@
factory
.
register_backbone_builder
(
'revnet'
)
def
build_revnet
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds RevNet backbone from a config."""
backbone_type
=
model_config
.
backbone
.
type
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_type
=
backbone_config
.
type
backbone_cfg
=
backbone_config
.
get
()
assert
backbone_type
==
'revnet'
,
(
f
'Inconsistent backbone type '
f
'
{
backbone_type
}
'
)
...
...
official/vision/beta/modeling/backbones/spinenet.py
浏览文件 @
aa2b5e42
...
...
@@ -22,6 +22,7 @@ from typing import Any, List, Optional, Tuple
from
absl
import
logging
import
tensorflow
as
tf
from
official.modeling
import
hyperparams
from
official.modeling
import
tf_utils
from
official.vision.beta.modeling.backbones
import
factory
from
official.vision.beta.modeling.layers
import
nn_blocks
...
...
@@ -527,12 +528,12 @@ class SpineNet(tf.keras.Model):
@
factory
.
register_backbone_builder
(
'spinenet'
)
def
build_spinenet
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds SpineNet backbone from a config."""
backbone_type
=
model_config
.
backbone
.
type
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_type
=
backbone_config
.
type
backbone_cfg
=
backbone_config
.
get
()
assert
backbone_type
==
'spinenet'
,
(
f
'Inconsistent backbone type '
f
'
{
backbone_type
}
'
)
...
...
@@ -544,8 +545,8 @@ def build_spinenet(
return
SpineNet
(
input_specs
=
input_specs
,
min_level
=
model_confi
g
.
min_level
,
max_level
=
model_confi
g
.
max_level
,
min_level
=
backbone_cf
g
.
min_level
,
max_level
=
backbone_cf
g
.
max_level
,
endpoints_num_filters
=
scaling_params
[
'endpoints_num_filters'
],
resample_alpha
=
scaling_params
[
'resample_alpha'
],
block_repeats
=
scaling_params
[
'block_repeats'
],
...
...
official/vision/beta/modeling/backbones/spinenet_mobile.py
浏览文件 @
aa2b5e42
...
...
@@ -36,6 +36,7 @@ from typing import Any, List, Optional, Tuple
from
absl
import
logging
import
tensorflow
as
tf
from
official.modeling
import
hyperparams
from
official.modeling
import
tf_utils
from
official.vision.beta.modeling.backbones
import
factory
from
official.vision.beta.modeling.layers
import
nn_blocks
...
...
@@ -501,12 +502,12 @@ class SpineNetMobile(tf.keras.Model):
@
factory
.
register_backbone_builder
(
'spinenet_mobile'
)
def
build_spinenet_mobile
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds Mobile SpineNet backbone from a config."""
backbone_type
=
model_config
.
backbone
.
type
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_type
=
backbone_config
.
type
backbone_cfg
=
backbone_config
.
get
()
assert
backbone_type
==
'spinenet_mobile'
,
(
f
'Inconsistent backbone type '
f
'
{
backbone_type
}
'
)
...
...
@@ -518,8 +519,8 @@ def build_spinenet_mobile(
return
SpineNetMobile
(
input_specs
=
input_specs
,
min_level
=
model_confi
g
.
min_level
,
max_level
=
model_confi
g
.
max_level
,
min_level
=
backbone_cf
g
.
min_level
,
max_level
=
backbone_cf
g
.
max_level
,
endpoints_num_filters
=
scaling_params
[
'endpoints_num_filters'
],
block_repeats
=
scaling_params
[
'block_repeats'
],
filter_size_scale
=
scaling_params
[
'filter_size_scale'
],
...
...
official/vision/beta/modeling/factory.py
浏览文件 @
aa2b5e42
...
...
@@ -44,12 +44,13 @@ def build_classification_model(
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
,
skip_logits_layer
:
bool
=
False
)
->
tf
.
keras
.
Model
:
"""Builds the classification model."""
norm_activation_config
=
model_config
.
norm_activation
backbone
=
backbones
.
factory
.
build_backbone
(
input_specs
=
input_specs
,
model_config
=
model_config
,
backbone_config
=
model_config
.
backbone
,
norm_activation_config
=
norm_activation_config
,
l2_regularizer
=
l2_regularizer
)
norm_activation_config
=
model_config
.
norm_activation
model
=
classification_model
.
ClassificationModel
(
backbone
=
backbone
,
num_classes
=
model_config
.
num_classes
,
...
...
@@ -69,9 +70,11 @@ def build_maskrcnn(
model_config
:
maskrcnn_cfg
.
MaskRCNN
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds Mask R-CNN model."""
norm_activation_config
=
model_config
.
norm_activation
backbone
=
backbones
.
factory
.
build_backbone
(
input_specs
=
input_specs
,
model_config
=
model_config
,
backbone_config
=
model_config
.
backbone
,
norm_activation_config
=
norm_activation_config
,
l2_regularizer
=
l2_regularizer
)
decoder
=
decoder_factory
.
build_decoder
(
...
...
@@ -85,7 +88,6 @@ def build_maskrcnn(
roi_aligner_config
=
model_config
.
roi_aligner
detection_head_config
=
model_config
.
detection_head
generator_config
=
model_config
.
detection_generator
norm_activation_config
=
model_config
.
norm_activation
num_anchors_per_location
=
(
len
(
model_config
.
anchor
.
aspect_ratios
)
*
model_config
.
anchor
.
num_scales
)
...
...
@@ -242,9 +244,11 @@ def build_retinanet(
model_config
:
retinanet_cfg
.
RetinaNet
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds RetinaNet model."""
norm_activation_config
=
model_config
.
norm_activation
backbone
=
backbones
.
factory
.
build_backbone
(
input_specs
=
input_specs
,
model_config
=
model_config
,
backbone_config
=
model_config
.
backbone
,
norm_activation_config
=
norm_activation_config
,
l2_regularizer
=
l2_regularizer
)
decoder
=
decoder_factory
.
build_decoder
(
...
...
@@ -254,7 +258,6 @@ def build_retinanet(
head_config
=
model_config
.
head
generator_config
=
model_config
.
detection_generator
norm_activation_config
=
model_config
.
norm_activation
num_anchors_per_location
=
(
len
(
model_config
.
anchor
.
aspect_ratios
)
*
model_config
.
anchor
.
num_scales
)
...
...
@@ -301,9 +304,11 @@ def build_segmentation_model(
model_config
:
segmentation_cfg
.
SemanticSegmentationModel
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds Segmentation model."""
norm_activation_config
=
model_config
.
norm_activation
backbone
=
backbones
.
factory
.
build_backbone
(
input_specs
=
input_specs
,
model_config
=
model_config
,
backbone_config
=
model_config
.
backbone
,
norm_activation_config
=
norm_activation_config
,
l2_regularizer
=
l2_regularizer
)
decoder
=
decoder_factory
.
build_decoder
(
...
...
@@ -312,7 +317,6 @@ def build_segmentation_model(
l2_regularizer
=
l2_regularizer
)
head_config
=
model_config
.
head
norm_activation_config
=
model_config
.
norm_activation
head
=
segmentation_heads
.
SegmentationHead
(
num_classes
=
model_config
.
num_classes
,
...
...
official/vision/beta/modeling/factory_3d.py
浏览文件 @
aa2b5e42
...
...
@@ -85,9 +85,11 @@ def build_video_classification_model(
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds the video classification model."""
input_specs_dict
=
{
'image'
:
input_specs
}
norm_activation_config
=
model_config
.
norm_activation
backbone
=
backbones
.
factory
.
build_backbone
(
input_specs
=
input_specs
,
model_config
=
model_config
,
backbone_config
=
model_config
.
backbone
,
norm_activation_config
=
norm_activation_config
,
l2_regularizer
=
l2_regularizer
)
model
=
video_classification_model
.
VideoClassificationModel
(
...
...
official/vision/beta/projects/assemblenet/modeling/assemblenet.py
浏览文件 @
aa2b5e42
...
...
@@ -54,6 +54,7 @@ from absl import logging
import
numpy
as
np
import
tensorflow
as
tf
from
official.modeling
import
hyperparams
from
official.vision.beta.modeling
import
factory_3d
as
model_factory
from
official.vision.beta.modeling.backbones
import
factory
as
backbone_factory
from
official.vision.beta.projects.assemblenet.configs
import
assemblenet
as
cfg
...
...
@@ -1015,14 +1016,14 @@ def assemblenet_v1(assemblenet_depth: int,
@
backbone_factory
.
register_backbone_builder
(
'assemblenet'
)
def
build_assemblenet_v1
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
:
cfg
.
Backbone3D
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds assemblenet backbone."""
del
l2_regularizer
backbone_type
=
model_config
.
backbone
.
type
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_type
=
backbone_config
.
type
backbone_cfg
=
backbone_config
.
get
()
assert
backbone_type
==
'assemblenet'
assemblenet_depth
=
int
(
backbone_cfg
.
model_id
)
...
...
@@ -1060,7 +1061,8 @@ def build_assemblenet_model(
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
):
"""Builds assemblenet model."""
input_specs_dict
=
{
'image'
:
input_specs
}
backbone
=
build_assemblenet_v1
(
input_specs
,
model_config
,
l2_regularizer
)
backbone
=
build_assemblenet_v1
(
input_specs
,
model_config
.
backbone
,
model_config
.
norm_activation
,
l2_regularizer
)
backbone_cfg
=
model_config
.
backbone
.
get
()
model_structure
,
_
=
cfg
.
blocks_to_flat_lists
(
backbone_cfg
.
blocks
)
model
=
AssembleNetModel
(
...
...
official/vision/beta/projects/deepmac_maskrcnn/tasks/deep_mask_head_rcnn.py
浏览文件 @
aa2b5e42
...
...
@@ -37,9 +37,11 @@ def build_maskrcnn(input_specs: tf.keras.layers.InputSpec,
model_config
:
deep_mask_head_rcnn_config
.
DeepMaskHeadRCNN
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
):
"""Builds Mask R-CNN model."""
norm_activation_config
=
model_config
.
norm_activation
backbone
=
backbones
.
factory
.
build_backbone
(
input_specs
=
input_specs
,
model_config
=
model_config
,
backbone_config
=
model_config
.
backbone
,
norm_activation_config
=
norm_activation_config
,
l2_regularizer
=
l2_regularizer
)
decoder
=
decoder_factory
.
build_decoder
(
...
...
@@ -53,7 +55,6 @@ def build_maskrcnn(input_specs: tf.keras.layers.InputSpec,
roi_aligner_config
=
model_config
.
roi_aligner
detection_head_config
=
model_config
.
detection_head
generator_config
=
model_config
.
detection_generator
norm_activation_config
=
model_config
.
norm_activation
num_anchors_per_location
=
(
len
(
model_config
.
anchor
.
aspect_ratios
)
*
model_config
.
anchor
.
num_scales
)
...
...
official/vision/beta/projects/simclr/tasks/simclr.py
浏览文件 @
aa2b5e42
...
...
@@ -110,7 +110,8 @@ class SimCLRPretrainTask(base_task.Task):
# Build backbone
backbone
=
backbones
.
factory
.
build_backbone
(
input_specs
=
input_specs
,
model_config
=
model_config
,
backbone_config
=
model_config
.
backbone
,
norm_activation_config
=
model_config
.
norm_activation
,
l2_regularizer
=
l2_regularizer
)
# Build projection head
...
...
official/vision/beta/projects/yolo/modeling/backbones/darknet.py
浏览文件 @
aa2b5e42
...
...
@@ -40,6 +40,7 @@ import collections
import
tensorflow
as
tf
from
official.modeling
import
hyperparams
from
official.vision.beta.modeling.backbones
import
factory
from
official.vision.beta.projects.yolo.modeling.layers
import
nn_blocks
...
...
@@ -428,12 +429,12 @@ class Darknet(tf.keras.Model):
@
factory
.
register_backbone_builder
(
"darknet"
)
def
build_darknet
(
input_specs
:
tf
.
keras
.
layers
.
InputSpec
,
model_config
,
backbone_config
:
hyperparams
.
Config
,
norm_activation_config
:
hyperparams
.
Config
,
l2_regularizer
:
tf
.
keras
.
regularizers
.
Regularizer
=
None
)
->
tf
.
keras
.
Model
:
"""Builds darknet backbone."""
backbone_cfg
=
model_config
.
backbone
.
get
()
norm_activation_config
=
model_config
.
norm_activation
backbone_cfg
=
backbone_config
.
get
()
model
=
Darknet
(
model_id
=
backbone_cfg
.
model_id
,
input_shape
=
input_specs
,
...
...
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