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Align backbone stage selection with out_indices & out_features (#27606)

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* Iteratre over out_features instead of stage_names

* Update for all backbones

* Add tests

* Fix

* Align timm backbone behaviour with other backbones

* Fix tests

* Stricter checks on set out_features and out_indices

* Revert back stage selection logic

* Remove out-of-order logic

* Document restriction in docstrings
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amyeroberts 2023-12-20 18:33:17 +00:00 committed by GitHub
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15 changed files with 125 additions and 34 deletions
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6
src/transformers/models/beit/configuration_beit.py
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@ -102,11 +102,13 @@ class BeitConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
add_fpn (`bool`, *optional*, defaults to `False`):
Whether to add a FPN as part of the backbone. Only relevant for [`BeitBackbone`].
reshape_hidden_states (`bool`, *optional*, defaults to `True`):

6
src/transformers/models/bit/configuration_bit.py
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@ -65,11 +65,13 @@ class BitConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:
```python

6
src/transformers/models/convnext/configuration_convnext.py
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@ -68,11 +68,13 @@ class ConvNextConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:
```python

6
src/transformers/models/convnextv2/configuration_convnextv2.py
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@ -60,11 +60,13 @@ class ConvNextV2Config(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:
```python

6
src/transformers/models/dinat/configuration_dinat.py
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@ -74,11 +74,13 @@ class DinatConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:

6
src/transformers/models/dinov2/configuration_dinov2.py
View File

@ -79,11 +79,13 @@ class Dinov2Config(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
apply_layernorm (`bool`, *optional*, defaults to `True`):
Whether to apply layer normalization to the feature maps in case the model is used as backbone.
reshape_hidden_states (`bool`, *optional*, defaults to `True`):

6
src/transformers/models/focalnet/configuration_focalnet.py
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@ -84,11 +84,13 @@ class FocalNetConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:

6
src/transformers/models/maskformer/configuration_maskformer_swin.py
View File

@ -70,11 +70,13 @@ class MaskFormerSwinConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:

6
src/transformers/models/nat/configuration_nat.py
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@ -72,11 +72,13 @@ class NatConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:

6
src/transformers/models/resnet/configuration_resnet.py
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@ -64,11 +64,13 @@ class ResNetConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:
```python

6
src/transformers/models/swin/configuration_swin.py
View File

@ -85,11 +85,13 @@ class SwinConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:

6
src/transformers/models/vitdet/configuration_vitdet.py
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@ -80,11 +80,13 @@ class VitDetConfig(BackboneConfigMixin, PretrainedConfig):
out_features (`List[str]`, *optional*):
If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc.
(depending on how many stages the model has). If unset and `out_indices` is set, will default to the
corresponding stages. If unset and `out_indices` is unset, will default to the last stage.
corresponding stages. If unset and `out_indices` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
out_indices (`List[int]`, *optional*):
If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how
many stages the model has). If unset and `out_features` is set, will default to the corresponding stages.
If unset and `out_features` is unset, will default to the last stage.
If unset and `out_features` is unset, will default to the last stage. Must be in the
same order as defined in the `stage_names` attribute.
Example:

21
src/transformers/utils/backbone_utils.py
View File

@ -36,15 +36,32 @@ def verify_out_features_out_indices(
if out_features is not None:
if not isinstance(out_features, (list,)):
raise ValueError(f"out_features must be a list {type(out_features)}")
raise ValueError(f"out_features must be a list got {type(out_features)}")
if any(feat not in stage_names for feat in out_features):
raise ValueError(f"out_features must be a subset of stage_names: {stage_names} got {out_features}")
if len(out_features) != len(set(out_features)):
raise ValueError(f"out_features must not contain any duplicates, got {out_features}")
if out_features != (sorted_feats := [feat for feat in stage_names if feat in out_features]):
raise ValueError(
f"out_features must be in the same order as stage_names, expected {sorted_feats} got {out_features}"
)
if out_indices is not None:
if not isinstance(out_indices, (list, tuple)):
raise ValueError(f"out_indices must be a list or tuple, got {type(out_indices)}")
if any(idx >= len(stage_names) for idx in out_indices):
# Convert negative indices to their positive equivalent: [-1,] -> [len(stage_names) - 1,]
positive_indices = tuple(idx % len(stage_names) if idx < 0 else idx for idx in out_indices)
if any(idx for idx in positive_indices if idx not in range(len(stage_names))):
raise ValueError(f"out_indices must be valid indices for stage_names {stage_names}, got {out_indices}")
if len(positive_indices) != len(set(positive_indices)):
msg = f"out_indices must not contain any duplicates, got {out_indices}"
msg += f"(equivalent to {positive_indices}))" if positive_indices != out_indices else ""
raise ValueError(msg)
if positive_indices != tuple(sorted(positive_indices)):
sorted_negative = tuple(idx for _, idx in sorted(zip(positive_indices, out_indices), key=lambda x: x[0]))
raise ValueError(
f"out_indices must be in the same order as stage_names, expected {sorted_negative} got {out_indices}"
)
if out_features is not None and out_indices is not None:
if len(out_features) != len(out_indices):

24
tests/test_backbone_common.py
View File

@ -201,3 +201,27 @@ class BackboneTesterMixin:
if self.has_attentions:
outputs = backbone(**inputs_dict, output_attentions=True)
self.assertIsNotNone(outputs.attentions)
def test_backbone_stage_selection(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
batch_size = inputs_dict["pixel_values"].shape[0]
for backbone_class in self.all_model_classes:
config.out_indices = [-2, -1]
backbone = backbone_class(config)
backbone.to(torch_device)
backbone.eval()
outputs = backbone(**inputs_dict)
# Test number of feature maps returned
self.assertIsInstance(outputs.feature_maps, tuple)
self.assertTrue(len(outputs.feature_maps) == 2)
# Order of channels returned is same as order of channels iterating over stage names
channels_from_stage_names = [
backbone.out_feature_channels[name] for name in backbone.stage_names if name in backbone.out_features
]
self.assertEqual(backbone.channels, channels_from_stage_names)
for feature_map, n_channels in zip(outputs.feature_maps, backbone.channels):
self.assertTrue(feature_map.shape[:2], (batch_size, n_channels))

42
tests/utils/test_backbone_utils.py
View File

@ -14,6 +14,8 @@
import unittest
import pytest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
@ -47,37 +49,61 @@ class BackboneUtilsTester(unittest.TestCase):
def test_verify_out_features_out_indices(self):
# Stage names must be set
with self.assertRaises(ValueError):
with pytest.raises(ValueError, match="Stage_names must be set for transformers backbones"):
verify_out_features_out_indices(["a", "b"], (0, 1), None)
# Out features must be a list
with self.assertRaises(ValueError):
with pytest.raises(ValueError, match="out_features must be a list got <class 'tuple'>"):
verify_out_features_out_indices(("a", "b"), (0, 1), ["a", "b"])
# Out features must be a subset of stage names
with self.assertRaises(ValueError):
with pytest.raises(
ValueError, match=r"out_features must be a subset of stage_names: \['a'\] got \['a', 'b'\]"
):
verify_out_features_out_indices(["a", "b"], (0, 1), ["a"])
# Out features must contain no duplicates
with pytest.raises(ValueError, match=r"out_features must not contain any duplicates, got \['a', 'a'\]"):
verify_out_features_out_indices(["a", "a"], None, ["a"])
# Out indices must be a list or tuple
with self.assertRaises(ValueError):
with pytest.raises(ValueError, match="out_indices must be a list or tuple, got <class 'int'>"):
verify_out_features_out_indices(None, 0, ["a", "b"])
# Out indices must be a subset of stage names
with self.assertRaises(ValueError):
with pytest.raises(
ValueError, match=r"out_indices must be valid indices for stage_names \['a'\], got \(0, 1\)"
):
verify_out_features_out_indices(None, (0, 1), ["a"])
# Out indices must contain no duplicates
with pytest.raises(ValueError, match=r"out_indices must not contain any duplicates, got \(0, 0\)"):
verify_out_features_out_indices(None, (0, 0), ["a"])
# Out features and out indices must be the same length
with self.assertRaises(ValueError):
with pytest.raises(
ValueError, match="out_features and out_indices should have the same length if both are set"
):
verify_out_features_out_indices(["a", "b"], (0,), ["a", "b", "c"])
# Out features should match out indices
with self.assertRaises(ValueError):
with pytest.raises(
ValueError, match="out_features and out_indices should correspond to the same stages if both are set"
):
verify_out_features_out_indices(["a", "b"], (0, 2), ["a", "b", "c"])
# Out features and out indices should be in order
with self.assertRaises(ValueError):
with pytest.raises(
ValueError,
match=r"out_features must be in the same order as stage_names, expected \['a', 'b'\] got \['b', 'a'\]",
):
verify_out_features_out_indices(["b", "a"], (0, 1), ["a", "b"])
with pytest.raises(
ValueError, match=r"out_indices must be in the same order as stage_names, expected \(-2, 1\) got \(1, -2\)"
):
verify_out_features_out_indices(["a", "b"], (1, -2), ["a", "b"])
# Check passes with valid inputs
verify_out_features_out_indices(["a", "b", "d"], (0, 1, -1), ["a", "b", "c", "d"])