forked from xuewujiao/Paddle
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Add IntermediateLayerGetter (PaddlePaddle#47908)
- Loading branch information
1 parent
84be82b
commit 1059564
Showing
5 changed files
with
202 additions
and
34 deletions.
There are no files selected for viewing
92 changes: 92 additions & 0 deletions
92
python/paddle/fluid/tests/unittests/test_IntermediateLayerGetter.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,92 @@ | ||
# Copyright (c) 2018 PaddlePaddle 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. | ||
|
||
import random | ||
import unittest | ||
|
||
import paddle | ||
from paddle.vision.models._utils import IntermediateLayerGetter | ||
|
||
|
||
class TestBase: | ||
def setUp(self): | ||
|
||
self.init_model() | ||
self.model.eval() | ||
|
||
self.layer_names = [ | ||
(order, name) | ||
for order, (name, _) in enumerate(self.model.named_children()) | ||
] | ||
# choose two layer children of model randomly | ||
self.start, self.end = sorted( | ||
random.sample(self.layer_names, 2), key=lambda x: x[0] | ||
) | ||
|
||
self.return_layers_dic = {self.start[1]: "feat1", self.end[1]: "feat2"} | ||
self.new_model = IntermediateLayerGetter( | ||
self.model, self.return_layers_dic | ||
) | ||
|
||
def init_model(self): | ||
self.model = None | ||
|
||
@paddle.no_grad() | ||
def test_inter_result(self): | ||
|
||
inp = paddle.randn([1, 3, 80, 80]) | ||
inter_oup = self.new_model(inp) | ||
|
||
for layer_name, layer in self.model.named_children(): | ||
|
||
if (isinstance(layer, paddle.nn.Linear) and inp.ndim == 4) or ( | ||
len(layer.sublayers()) > 0 | ||
and isinstance(layer.sublayers()[0], paddle.nn.Linear) | ||
and inp.ndim == 4 | ||
): | ||
inp = paddle.flatten(inp, 1) | ||
|
||
inp = layer(inp) | ||
if layer_name in self.return_layers_dic: | ||
feat_name = self.return_layers_dic[layer_name] | ||
self.assertTrue((inter_oup[feat_name] == inp).all()) | ||
|
||
|
||
class TestIntermediateLayerGetterResNet18(TestBase, unittest.TestCase): | ||
def init_model(self): | ||
self.model = paddle.vision.models.resnet18(pretrained=False) | ||
|
||
|
||
class TestIntermediateLayerGetterDenseNet121(TestBase, unittest.TestCase): | ||
def init_model(self): | ||
self.model = paddle.vision.models.densenet121(pretrained=False) | ||
|
||
|
||
class TestIntermediateLayerGetterVGG11(TestBase, unittest.TestCase): | ||
def init_model(self): | ||
self.model = paddle.vision.models.vgg11(pretrained=False) | ||
|
||
|
||
class TestIntermediateLayerGetterMobileNetV3Small(TestBase, unittest.TestCase): | ||
def init_model(self): | ||
self.model = paddle.vision.models.MobileNetV3Small() | ||
|
||
|
||
class TestIntermediateLayerGetterShuffleNetV2(TestBase, unittest.TestCase): | ||
def init_model(self): | ||
self.model = paddle.vision.models.shufflenet_v2_x0_25() | ||
|
||
|
||
if __name__ == "__main__": | ||
unittest.main() |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,108 @@ | ||
# Copyright (c) 2022 PaddlePaddle 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. | ||
|
||
from collections import OrderedDict | ||
from typing import Dict | ||
|
||
import paddle | ||
import paddle.nn as nn | ||
|
||
|
||
def _make_divisible(v, divisor=8, min_value=None): | ||
""" | ||
This function ensures that all layers have a channel number that is divisible by divisor | ||
You can also see at https://github.com/keras-team/keras/blob/8ecef127f70db723c158dbe9ed3268b3d610ab55/keras/applications/mobilenet_v2.py#L505 | ||
Args: | ||
divisor (int): The divisor for number of channels. Default: 8. | ||
min_value (int, optional): The minimum value of number of channels, if it is None, | ||
the default is divisor. Default: None. | ||
""" | ||
if min_value is None: | ||
min_value = divisor | ||
new_v = max(min_value, int(v + divisor / 2) // divisor * divisor) | ||
# Make sure that round down does not go down by more than 10%. | ||
if new_v < 0.9 * v: | ||
new_v += divisor | ||
return new_v | ||
|
||
|
||
class IntermediateLayerGetter(nn.LayerDict): | ||
""" | ||
Layer wrapper that returns intermediate layers from a model. | ||
It has a strong assumption that the layers have been registered into the model in the | ||
same order as they are used. This means that one should **not** reuse the same nn.Layer | ||
twice in the forward if you want this to work. | ||
Additionally, it is only able to query sublayer that are directly assigned to the model. | ||
So if `model` is passed, `model.feature1` can be returned, but not `model.feature1.layer2`. | ||
Args: | ||
model (nn.Layer): model on which we will extract the features | ||
return_layers (Dict[name, new_name]): a dict containing the names of the layers for | ||
which the activations will be returned as the key of the dict, and the value of the | ||
dict is the name of the returned activation (which the user can specify). | ||
Examples: | ||
.. code-block:: python | ||
import paddle | ||
m = paddle.vision.models.resnet18(pretrained=False) | ||
# extract layer1 and layer3, giving as names `feat1` and feat2` | ||
new_m = paddle.vision.models._utils.IntermediateLayerGetter(m, | ||
{'layer1': 'feat1', 'layer3': 'feat2'}) | ||
out = new_m(paddle.rand([1, 3, 224, 224])) | ||
print([(k, v.shape) for k, v in out.items()]) | ||
# [('feat1', [1, 64, 56, 56]), ('feat2', [1, 256, 14, 14])] | ||
""" | ||
|
||
__annotations__ = { | ||
"return_layers": Dict[str, str], | ||
} | ||
|
||
def __init__(self, model: nn.Layer, return_layers: Dict[str, str]) -> None: | ||
if not set(return_layers).issubset( | ||
[name for name, _ in model.named_children()] | ||
): | ||
raise ValueError("return_layers are not present in model") | ||
orig_return_layers = return_layers | ||
return_layers = {str(k): str(v) for k, v in return_layers.items()} | ||
layers = OrderedDict() | ||
for name, module in model.named_children(): | ||
layers[name] = module | ||
if name in return_layers: | ||
del return_layers[name] | ||
if not return_layers: | ||
break | ||
|
||
super(IntermediateLayerGetter, self).__init__(layers) | ||
self.return_layers = orig_return_layers | ||
|
||
def forward(self, x): | ||
out = OrderedDict() | ||
for name, module in self.items(): | ||
|
||
if (isinstance(module, nn.Linear) and x.ndim == 4) or ( | ||
len(module.sublayers()) > 0 | ||
and isinstance(module.sublayers()[0], nn.Linear) | ||
and x.ndim == 4 | ||
): | ||
x = paddle.flatten(x, 1) | ||
|
||
x = module(x) | ||
if name in self.return_layers: | ||
out_name = self.return_layers[name] | ||
out[out_name] = x | ||
return out |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file was deleted.
Oops, something went wrong.