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Add UperNet (#20648)

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* First draft

* More improvements

* Add convnext backbone

* Add conversion script

* Add more improvements

* Comment out to_dict

* Add to_dict method

* Add default config

* Fix config

* Fix backbone

* Fix backbone some more

* Add docs, auto mapping, tests

* Fix some tests

* Fix more tests

* Fix more tests

* Add conversion script

* Improve conversion script

* Add support for getting reshaped undownsampled hidden states

* Fix forward pass

* Add print statements

* Comment out set_shift_and_window_size

* More improvements

* Correct downsampling layers conversion

* Fix style

* First draft

* Fix conversion script

* Remove config attribute

* Fix more tests

* Update READMEs

* Update ConvNextBackbone

* Fix ConvNext tests

* Align ConvNext with Swin

* Remove files

* Fix index

* Improve docs

* Add output_attentions to model forward

* Add backbone mixin, improve tests

* More improvements

* Update init_weights

* Fix interpolation of logits

* Add UperNetImageProcessor

* Improve image processor

* Fix image processor

* Remove print statements

* Remove script

* Update import

* Add image processor tests

* Remove print statements

* Fix test

* Add integration test

* Add convnext integration test

* Update docstring

* Fix README

* Simplify config

* Apply suggestions

* Improve docs

* Rename class

* Fix test_initialization

* Fix import

* Address review

* Fix confg

* Convert all checkpoints

* Fix default backbone

* Usage same processor as segformer

* Apply suggestions

* Fix init_weights, update conversion scripts

* Improve config

* Use Auto API instead of creating a new image processor

* Fix docs

* Add doctests

* Remove ResNetConfig dependency

* Add always_partition argument

* Fix rebaseé

* Improve docs

* Convert checkpoints

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>
This commit is contained in:
NielsRogge
2023-01-16 09:39:13 +01:00
committed by GitHub
parent 5db9abde43
commit 4ed89d48ab
34 changed files with 1770 additions and 49 deletions
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50
tests/models/convnext/test_modeling_convnext.py
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@@ -29,7 +29,7 @@ from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
if is_torch_available():
import torch
from transformers import ConvNextForImageClassification, ConvNextModel
from transformers import ConvNextBackbone, ConvNextForImageClassification, ConvNextModel
from transformers.models.convnext.modeling_convnext import CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST
@@ -53,9 +53,9 @@ class ConvNextModelTester:
use_labels=True,
intermediate_size=37,
hidden_act="gelu",
type_sequence_label_size=10,
num_labels=10,
initializer_range=0.02,
num_labels=3,
out_features=["stage2", "stage3", "stage4"],
scope=None,
):
self.parent = parent
@@ -69,8 +69,9 @@ class ConvNextModelTester:
self.use_labels = use_labels
self.intermediate_size = intermediate_size
self.hidden_act = hidden_act
self.type_sequence_label_size = type_sequence_label_size
self.num_labels = num_labels
self.initializer_range = initializer_range
self.out_features = out_features
self.scope = scope
def prepare_config_and_inputs(self):
@@ -78,7 +79,7 @@ class ConvNextModelTester:
labels = None
if self.use_labels:
labels = ids_tensor([self.batch_size], self.type_sequence_label_size)
labels = ids_tensor([self.batch_size], self.num_labels)
config = self.get_config()
@@ -93,6 +94,8 @@ class ConvNextModelTester:
hidden_act=self.hidden_act,
is_decoder=False,
initializer_range=self.initializer_range,
out_features=self.out_features,
num_labels=self.num_labels,
)
def create_and_check_model(self, config, pixel_values, labels):
@@ -107,12 +110,40 @@ class ConvNextModelTester:
)
def create_and_check_for_image_classification(self, config, pixel_values, labels):
config.num_labels = self.type_sequence_label_size
model = ConvNextForImageClassification(config)
model.to(torch_device)
model.eval()
result = model(pixel_values, labels=labels)
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.type_sequence_label_size))
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.num_labels))
def create_and_check_backbone(self, config, pixel_values, labels):
model = ConvNextBackbone(config=config)
model.to(torch_device)
model.eval()
result = model(pixel_values)
# verify hidden states
self.parent.assertEqual(len(result.feature_maps), len(config.out_features))
self.parent.assertListEqual(list(result.feature_maps[0].shape), [self.batch_size, self.hidden_sizes[1], 4, 4])
# verify channels
self.parent.assertEqual(len(model.channels), len(config.out_features))
self.parent.assertListEqual(model.channels, config.hidden_sizes[1:])
# verify backbone works with out_features=None
config.out_features = None
model = ConvNextBackbone(config=config)
model.to(torch_device)
model.eval()
result = model(pixel_values)
# verify feature maps
self.parent.assertEqual(len(result.feature_maps), 1)
self.parent.assertListEqual(list(result.feature_maps[0].shape), [self.batch_size, self.hidden_sizes[-1], 1, 1])
# verify channels
self.parent.assertEqual(len(model.channels), 1)
self.parent.assertListEqual(model.channels, [config.hidden_sizes[-1]])
def prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs()
@@ -132,6 +163,7 @@ class ConvNextModelTest(ModelTesterMixin, unittest.TestCase):
(
ConvNextModel,
ConvNextForImageClassification,
ConvNextBackbone,
)
if is_torch_available()
else ()
@@ -167,6 +199,10 @@ class ConvNextModelTest(ModelTesterMixin, unittest.TestCase):
def test_model_common_attributes(self):
pass
@unittest.skip(reason="ConvNext does not use feedforward chunking")
def test_feed_forward_chunking(self):
pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()