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Deal with nested configs better in base class (#25237)

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* Deal better with nested configs

* Fixes

* More fixes

* Fix last test

* Clean up existing configs

* Remove hack in MPT Config

* Update src/transformers/configuration_utils.py

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Fix setting a nested config via dict in the kwargs

* Adapt common test

* Add test for nested config load with dict

---------

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
This commit is contained in:
Sylvain Gugger
2023-08-04 14:56:09 +02:00
committed by GitHub
parent aeb5a08abd
commit 29f04002e6
40 changed files with 62 additions and 566 deletions
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42
src/transformers/configuration_utils.py
View File

@@ -762,6 +762,10 @@ class PretrainedConfig(PushToHubMixin):
to_remove = []
for key, value in kwargs.items():
if hasattr(config, key):
current_attr = getattr(config, key)
# To authorize passing a custom subconfig as kwarg in models that have nested configs.
if isinstance(current_attr, PretrainedConfig) and isinstance(value, dict):
value = current_attr.__class__(**value)
setattr(config, key, value)
if key != "torch_dtype":
to_remove.append(key)
@@ -823,6 +827,18 @@ class PretrainedConfig(PushToHubMixin):
# only serialize values that differ from the default config
for key, value in config_dict.items():
if (
isinstance(getattr(self, key, None), PretrainedConfig)
and key in class_config_dict
and isinstance(class_config_dict[key], dict)
):
# For nested configs we need to clean the diff recursively
diff = recursive_diff_dict(value, class_config_dict[key], config_obj=getattr(self, key, None))
if "model_type" in value:
# Needs to be set even if it's not in the diff
diff["model_type"] = value["model_type"]
if len(diff) > 0:
serializable_config_dict[key] = diff
elif (
key not in default_config_dict
or key == "transformers_version"
or value != default_config_dict[key]
@@ -859,6 +875,14 @@ class PretrainedConfig(PushToHubMixin):
# Transformers version when serializing the model
output["transformers_version"] = __version__
for key, value in output.items():
# Deal with nested configs like CLIP
if isinstance(value, PretrainedConfig):
value = value.to_dict()
del value["transformers_version"]
output[key] = value
if hasattr(self, "quantization_config"):
output["quantization_config"] = (
self.quantization_config.to_dict()
@@ -1020,6 +1044,24 @@ def get_configuration_file(configuration_files: List[str]) -> str:
return configuration_file
def recursive_diff_dict(dict_a, dict_b, config_obj=None):
"""
Helper function to recursively take the diff between two nested dictionaries. The resulting diff only contains the
values from `dict_a` that are different from values in `dict_b`.
"""
diff = {}
default = config_obj.__class__().to_dict() if config_obj is not None else {}
for key, value in dict_a.items():
obj_value = getattr(config_obj, str(key), None)
if isinstance(obj_value, PretrainedConfig) and key in dict_b and isinstance(dict_b[key], dict):
diff_value = recursive_diff_dict(value, dict_b[key], config_obj=obj_value)
if len(diff_value) > 0:
diff[key] = diff_value
elif key not in dict_b or value != dict_b[key] or key not in default or value != default[key]:
diff[key] = value
return diff
PretrainedConfig.push_to_hub = copy_func(PretrainedConfig.push_to_hub)
if PretrainedConfig.push_to_hub.__doc__ is not None:
PretrainedConfig.push_to_hub.__doc__ = PretrainedConfig.push_to_hub.__doc__.format(

15
src/transformers/models/align/configuration_align.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" ALIGN model configuration"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
@@ -344,7 +343,6 @@ class AlignConfig(PretrainedConfig):
```"""
model_type = "align"
is_composition = True
def __init__(
self,
@@ -383,16 +381,3 @@ class AlignConfig(PretrainedConfig):
"""
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

15
src/transformers/models/altclip/configuration_altclip.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
""" AltCLIP model configuration"""
import copy
import os
from typing import Union
@@ -291,7 +290,6 @@ class AltCLIPConfig(PretrainedConfig):
```"""
model_type = "altclip"
is_composition = True
def __init__(
self, text_config=None, vision_config=None, projection_dim=768, logit_scale_init_value=2.6592, **kwargs
@@ -392,16 +390,3 @@ class AltCLIPConfig(PretrainedConfig):
"""
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

19
src/transformers/models/bark/configuration_bark.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" BARK model configuration"""
import copy
import os
from typing import Dict, Optional, Union
@@ -271,7 +270,6 @@ class BarkConfig(PretrainedConfig):
"""
model_type = "bark"
is_composition = True
def __init__(
self,
@@ -329,20 +327,3 @@ class BarkConfig(PretrainedConfig):
codec_config=codec_config.to_dict(),
**kwargs,
)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["semantic_config"] = self.semantic_config.to_dict()
output["coarse_acoustics_config"] = self.coarse_acoustics_config.to_dict()
output["fine_acoustics_config"] = self.fine_acoustics_config.to_dict()
output["codec_config"] = self.codec_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

15
src/transformers/models/blip/configuration_blip.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" Blip model configuration"""
import copy
import os
from typing import Union
@@ -325,7 +324,6 @@ class BlipConfig(PretrainedConfig):
```"""
model_type = "blip"
is_composition = True
def __init__(
self,
@@ -368,16 +366,3 @@ class BlipConfig(PretrainedConfig):
"""
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

16
src/transformers/models/blip_2/configuration_blip_2.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" BLIP-2 model configuration"""
import copy
import os
from typing import Union
@@ -302,7 +301,6 @@ class Blip2Config(PretrainedConfig):
```"""
model_type = "blip-2"
is_composition = True
def __init__(self, vision_config=None, qformer_config=None, text_config=None, num_query_tokens=32, **kwargs):
super().__init__(**kwargs)
@@ -355,17 +353,3 @@ class Blip2Config(PretrainedConfig):
text_config=text_config.to_dict(),
**kwargs,
)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["vision_config"] = self.vision_config.to_dict()
output["qformer_config"] = self.qformer_config.to_dict()
output["text_config"] = self.text_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

14
src/transformers/models/bridgetower/configuration_bridgetower.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" BridgeTower model configuration"""
import copy
import os
from typing import Union
@@ -349,16 +348,3 @@ class BridgeTowerConfig(PretrainedConfig):
"""
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

15
src/transformers/models/chinese_clip/configuration_chinese_clip.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" Chinese-CLIP model configuration"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
@@ -314,7 +313,6 @@ class ChineseCLIPConfig(PretrainedConfig):
```"""
model_type = "chinese_clip"
is_composition = True
def __init__(
self, text_config=None, vision_config=None, projection_dim=512, logit_scale_init_value=2.6592, **kwargs
@@ -417,19 +415,6 @@ class ChineseCLIPConfig(PretrainedConfig):
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output
class ChineseCLIPOnnxConfig(OnnxConfig):
@property

15
src/transformers/models/clap/configuration_clap.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" CLAP model configuration"""
import copy
import os
from typing import Union
@@ -382,7 +381,6 @@ class ClapConfig(PretrainedConfig):
```"""
model_type = "clap"
is_composition = True
def __init__(
self,
@@ -431,16 +429,3 @@ class ClapConfig(PretrainedConfig):
"""
return cls(text_config=text_config.to_dict(), audio_config=audio_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["audio_config"] = self.audio_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

15
src/transformers/models/clip/configuration_clip.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" CLIP model configuration"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
@@ -298,7 +297,6 @@ class CLIPConfig(PretrainedConfig):
```"""
model_type = "clip"
is_composition = True
def __init__(
self, text_config=None, vision_config=None, projection_dim=512, logit_scale_init_value=2.6592, **kwargs
@@ -400,19 +398,6 @@ class CLIPConfig(PretrainedConfig):
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output
class CLIPOnnxConfig(OnnxConfig):
@property

15
src/transformers/models/clipseg/configuration_clipseg.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" CLIPSeg model configuration"""
import copy
import os
from typing import Union
@@ -302,7 +301,6 @@ class CLIPSegConfig(PretrainedConfig):
```"""
model_type = "clipseg"
is_composition = True
def __init__(
self,
@@ -424,16 +422,3 @@ class CLIPSegConfig(PretrainedConfig):
"""
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

14
src/transformers/models/conditional_detr/configuration_conditional_detr.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
""" Conditional DETR model configuration"""
import copy
from collections import OrderedDict
from typing import Mapping
@@ -238,19 +237,6 @@ class ConditionalDetrConfig(PretrainedConfig):
def hidden_size(self) -> int:
return self.d_model
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
if self.backbone_config is not None:
output["backbone_config"] = self.backbone_config.to_dict()
output["model_type"] = self.__class__.model_type
return output
class ConditionalDetrOnnxConfig(OnnxConfig):
torch_onnx_minimum_version = version.parse("1.11")

14
src/transformers/models/deformable_detr/configuration_deformable_detr.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
""" Deformable DETR model configuration"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -261,16 +260,3 @@ class DeformableDetrConfig(PretrainedConfig):
@property
def hidden_size(self) -> int:
return self.d_model
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
if self.backbone_config is not None:
output["backbone_config"] = self.backbone_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

11
src/transformers/models/deta/configuration_deta.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" DETA model configuration"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -230,13 +229,3 @@ class DetaConfig(PretrainedConfig):
@property
def hidden_size(self) -> int:
return self.d_model
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["backbone_config"] = self.backbone_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

14
src/transformers/models/detr/configuration_detr.py
View File

@@ -14,9 +14,8 @@
# limitations under the License.
""" DETR model configuration"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from typing import Mapping
from packaging import version
@@ -248,17 +247,6 @@ class DetrConfig(PretrainedConfig):
"""
return cls(backbone_config=backbone_config, **kwargs)
def to_dict(self) -> Dict[str, any]:
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
if output["backbone_config"] is not None:
output["backbone_config"] = self.backbone_config.to_dict()
output["model_type"] = self.__class__.model_type
return output
class DetrOnnxConfig(OnnxConfig):
torch_onnx_minimum_version = version.parse("1.11")

14
src/transformers/models/encoder_decoder/configuration_encoder_decoder.py
View File

@@ -14,7 +14,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -104,16 +103,3 @@ class EncoderDecoderConfig(PretrainedConfig):
decoder_config.add_cross_attention = True
return cls(encoder=encoder_config.to_dict(), decoder=decoder_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default *to_dict()* from *PretrainedConfig*.
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["encoder"] = self.encoder.to_dict()
output["decoder"] = self.decoder.to_dict()
output["model_type"] = self.__class__.model_type
return output

17
src/transformers/models/flava/configuration_flava.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" FLAVA model configurations"""
import copy
import os
from typing import Any, Dict, Union
@@ -536,7 +535,6 @@ class FlavaConfig(PretrainedConfig):
"""
model_type = "flava"
is_composition = True
def __init__(
self,
@@ -764,18 +762,3 @@ class FlavaConfig(PretrainedConfig):
image_codebook_config=image_codebook_config.to_dict(),
**kwargs,
)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["image_config"] = self.image_config.to_dict()
output["text_config"] = self.text_config.to_dict()
output["multimodal_config"] = self.multimodal_config.to_dict()
output["image_codebook_config"] = self.image_codebook_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

14
src/transformers/models/fsmt/configuration_fsmt.py
View File

@@ -15,8 +15,6 @@
""" FSMT configuration"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -216,15 +214,3 @@ class FSMTConfig(PretrainedConfig):
early_stopping=early_stopping,
**common_kwargs,
)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default *to_dict()* from *PretrainedConfig*.
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["decoder"] = self.decoder.to_dict()
output["model_type"] = self.__class__.model_type
return output

11
src/transformers/models/git/configuration_git.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import copy
import os
from typing import Union
@@ -239,13 +238,3 @@ class GitConfig(PretrainedConfig):
self.bos_token_id = bos_token_id
self.eos_token_id = eos_token_id
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

15
src/transformers/models/groupvit/configuration_groupvit.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" GroupViT model configuration"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
@@ -296,7 +295,6 @@ class GroupViTConfig(PretrainedConfig):
"""
model_type = "groupvit"
is_composition = True
def __init__(
self,
@@ -407,19 +405,6 @@ class GroupViTConfig(PretrainedConfig):
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output
class GroupViTOnnxConfig(OnnxConfig):
@property

16
src/transformers/models/instructblip/configuration_instructblip.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" InstructBLIP model configuration"""
import copy
import os
from typing import Union
@@ -305,7 +304,6 @@ class InstructBlipConfig(PretrainedConfig):
```"""
model_type = "instructblip"
is_composition = True
def __init__(self, vision_config=None, qformer_config=None, text_config=None, num_query_tokens=32, **kwargs):
super().__init__(**kwargs)
@@ -358,17 +356,3 @@ class InstructBlipConfig(PretrainedConfig):
text_config=text_config.to_dict(),
**kwargs,
)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["vision_config"] = self.vision_config.to_dict()
output["qformer_config"] = self.qformer_config.to_dict()
output["text_config"] = self.text_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

29
src/transformers/models/jukebox/configuration_jukebox.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" Jukebox configuration"""
import copy
import os
from typing import List, Union
@@ -369,18 +368,6 @@ class JukeboxPriorConfig(PretrainedConfig):
return cls.from_dict(config_dict, **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["encoder_config"] = self.encoder_config.to_dict() if self.encoder_config is not None else None
output["model_type"] = self.__class__.model_type
return output
class JukeboxVQVAEConfig(PretrainedConfig):
"""
@@ -561,7 +548,6 @@ class JukeboxConfig(PretrainedConfig):
"""
model_type = "jukebox"
is_composition = True
def __init__(
self,
@@ -620,18 +606,3 @@ class JukeboxConfig(PretrainedConfig):
"""
prior_config_list = [config.to_dict() for config in prior_configs]
return cls(prior_config_list=prior_config_list, vqvae_config_dict=vqvae_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
for i, config in enumerate(output.pop("prior_configs")):
output[f"prior_{i}"] = config.to_dict()
output["vqvae_config"] = self.vqvae_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

13
src/transformers/models/mask2former/configuration_mask2former.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
""" Mask2Former model configuration"""
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
@@ -230,15 +229,3 @@ class Mask2FormerConfig(PretrainedConfig):
backbone_config=backbone_config,
**kwargs,
)
def to_dict(self) -> Dict[str, any]:
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["backbone_config"] = self.backbone_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

14
src/transformers/models/maskformer/configuration_maskformer.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
""" MaskFormer model configuration"""
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
@@ -200,16 +199,3 @@ class MaskFormerConfig(PretrainedConfig):
decoder_config=decoder_config,
**kwargs,
)
def to_dict(self) -> Dict[str, any]:
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["backbone_config"] = self.backbone_config.to_dict()
output["decoder_config"] = self.decoder_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

39
src/transformers/models/mpt/configuration_mpt.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
""" Mpt configuration"""
import copy
from typing import TYPE_CHECKING, Optional, Union
@@ -197,7 +196,6 @@ class MptConfig(PretrainedConfig):
"hidden_size": "d_model",
"num_hidden_layers": "n_layers",
}
is_composition = True
def __init__(
self,
@@ -222,6 +220,11 @@ class MptConfig(PretrainedConfig):
initializer_range=0.02,
**kwargs,
):
if attn_config is None:
self.attn_config = MptAttentionConfig()
elif isinstance(attn_config, dict):
self.attn_config = MptAttentionConfig(**attn_config)
else:
self.attn_config = attn_config
self.d_model = d_model
self.n_heads = n_heads
@@ -242,35 +245,3 @@ class MptConfig(PretrainedConfig):
self.use_cache = use_cache
self.initializer_range = initializer_range
super().__init__(**kwargs)
@property
def attn_config(self):
return self._attn_config
@attn_config.setter
def attn_config(self, attn_config):
if attn_config is None:
self._attn_config = MptAttentionConfig()
elif isinstance(attn_config, dict):
self._attn_config = MptAttentionConfig(**attn_config)
elif isinstance(attn_config, MptAttentionConfig):
self._attn_config = attn_config
else:
raise ValueError(
f"`attn_config` has to be either a `MptAttentionConfig` or a dictionary. Received: {type(attn_config)}"
)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["attn_config"] = (
self._attn_config.to_dict() if not isinstance(self.attn_config, dict) else self.attn_config
)
del output["_attn_config"]
output["model_type"] = self.__class__.model_type
return output

15
src/transformers/models/musicgen/configuration_musicgen.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
""" MusicGen model configuration"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -227,17 +226,3 @@ class MusicgenConfig(PretrainedConfig):
decoder=decoder_config.to_dict(),
**kwargs,
)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_encoder"] = self.text_encoder.to_dict()
output["audio_encoder"] = self.audio_encoder.to_dict()
output["decoder"] = self.decoder.to_dict()
output["model_type"] = self.__class__.model_type
return output

11
src/transformers/models/oneformer/configuration_oneformer.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
"""OneFormer model configuration"""
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
@@ -250,13 +249,3 @@ class OneFormerConfig(PretrainedConfig):
self.num_hidden_layers = decoder_layers
super().__init__(**kwargs)
def to_dict(self) -> Dict[str, any]:
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["backbone_config"] = self.backbone_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

15
src/transformers/models/owlvit/configuration_owlvit.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" OWL-ViT model configuration"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
@@ -274,7 +273,6 @@ class OwlViTConfig(PretrainedConfig):
"""
model_type = "owlvit"
is_composition = True
def __init__(
self,
@@ -332,19 +330,6 @@ class OwlViTConfig(PretrainedConfig):
return cls.from_dict(config_dict, **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output
class OwlViTOnnxConfig(OnnxConfig):
@property

15
src/transformers/models/pix2struct/configuration_pix2struct.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" Pix2Struct model configuration"""
import copy
import os
from typing import Union
@@ -338,7 +337,6 @@ class Pix2StructConfig(PretrainedConfig):
```"""
model_type = "pix2struct"
is_composition = True
def __init__(
self,
@@ -389,16 +387,3 @@ class Pix2StructConfig(PretrainedConfig):
"""
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

14
src/transformers/models/rag/configuration_rag.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" RAG model configuration"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
@@ -179,16 +178,3 @@ class RagConfig(PretrainedConfig):
[`EncoderDecoderConfig`]: An instance of a configuration object
"""
return cls(question_encoder=question_encoder_config.to_dict(), generator=generator_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["question_encoder"] = self.question_encoder.to_dict()
output["generator"] = self.generator.to_dict()
output["model_type"] = self.__class__.model_type
return output

16
src/transformers/models/sam/configuration_sam.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" SAM model configuration"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -286,7 +285,6 @@ class SamConfig(PretrainedConfig):
```"""
model_type = "sam"
is_composition = True
def __init__(
self,
@@ -312,17 +310,3 @@ class SamConfig(PretrainedConfig):
self.prompt_encoder_config = SamPromptEncoderConfig(**prompt_encoder_config)
self.mask_decoder_config = SamMaskDecoderConfig(**mask_decoder_config)
self.initializer_range = initializer_range
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["vision_config"] = self.vision_config.to_dict()
output["prompt_encoder_config"] = self.prompt_encoder_config.to_dict()
output["mask_decoder_config"] = self.mask_decoder_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

14
src/transformers/models/speech_encoder_decoder/configuration_speech_encoder_decoder.py
View File

@@ -14,7 +14,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -106,16 +105,3 @@ class SpeechEncoderDecoderConfig(PretrainedConfig):
decoder_config.add_cross_attention = True
return cls(encoder=encoder_config.to_dict(), decoder=decoder_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default *to_dict()* from *PretrainedConfig*.
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["encoder"] = self.encoder.to_dict()
output["decoder"] = self.decoder.to_dict()
output["model_type"] = self.__class__.model_type
return output

14
src/transformers/models/table_transformer/configuration_table_transformer.py
View File

@@ -13,9 +13,8 @@
# See the License for the specific language governing permissions and
# limitations under the License.
""" Table Transformer model configuration"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from typing import Mapping
from packaging import version
@@ -237,17 +236,6 @@ class TableTransformerConfig(PretrainedConfig):
def hidden_size(self) -> int:
return self.d_model
def to_dict(self) -> Dict[str, any]:
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
if output["backbone_config"] is not None:
output["backbone_config"] = self.backbone_config.to_dict()
output["model_type"] = self.__class__.model_type
return output
# Copied from transformers.models.detr.configuration_detr.DetrOnnxConfig
class TableTransformerOnnxConfig(OnnxConfig):

11
src/transformers/models/upernet/configuration_upernet.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" UperNet model configuration"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -108,13 +107,3 @@ class UperNetConfig(PretrainedConfig):
self.auxiliary_num_convs = auxiliary_num_convs
self.auxiliary_concat_input = auxiliary_concat_input
self.loss_ignore_index = loss_ignore_index
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["backbone_config"] = self.backbone_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

14
src/transformers/models/vision_encoder_decoder/configuration_vision_encoder_decoder.py
View File

@@ -14,7 +14,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
@@ -114,19 +113,6 @@ class VisionEncoderDecoderConfig(PretrainedConfig):
return cls(encoder=encoder_config.to_dict(), decoder=decoder_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default *to_dict()* from *PretrainedConfig*.
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["encoder"] = self.encoder.to_dict()
output["decoder"] = self.decoder.to_dict()
output["model_type"] = self.__class__.model_type
return output
class VisionEncoderDecoderEncoderOnnxConfig(OnnxConfig):
torch_onnx_minimum_version = version.parse("1.11")

14
src/transformers/models/vision_text_dual_encoder/configuration_vision_text_dual_encoder.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" VisionTextDualEncoder model configuration"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -113,16 +112,3 @@ class VisionTextDualEncoderConfig(PretrainedConfig):
"""
return cls(vision_config=vision_config.to_dict(), text_config=text_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["vision_config"] = self.vision_config.to_dict()
output["text_config"] = self.text_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

12
src/transformers/models/vit_hybrid/configuration_vit_hybrid.py
View File

@@ -14,8 +14,6 @@
# limitations under the License.
""" ViT Hybrid model configuration"""
import copy
from typing import Dict
from ...configuration_utils import PretrainedConfig
from ...utils import logging
@@ -146,13 +144,3 @@ class ViTHybridConfig(PretrainedConfig):
self.patch_size = patch_size
self.num_channels = num_channels
self.qkv_bias = qkv_bias
def to_dict(self) -> Dict[str, any]:
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["backbone_config"] = self.backbone_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

15
src/transformers/models/x_clip/configuration_x_clip.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" X-CLIP model configuration"""
import copy
import os
from typing import Union
@@ -299,7 +298,6 @@ class XCLIPConfig(PretrainedConfig):
"""
model_type = "xclip"
is_composition = True
def __init__(
self,
@@ -417,16 +415,3 @@ class XCLIPConfig(PretrainedConfig):
"""
return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)
def to_dict(self):
"""
Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
Returns:
`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
"""
output = copy.deepcopy(self.__dict__)
output["text_config"] = self.text_config.to_dict()
output["vision_config"] = self.vision_config.to_dict()
output["model_type"] = self.__class__.model_type
return output

4
tests/test_configuration_common.py
View File

@@ -118,7 +118,9 @@ class ConfigTester(object):
def check_config_can_be_init_without_params(self):
if self.config_class.is_composition:
return
with self.parent.assertRaises(ValueError):
config = self.config_class()
else:
config = self.config_class()
self.parent.assertIsNotNone(config)

7
tests/test_configuration_utils.py
View File

@@ -210,6 +210,13 @@ class ConfigTestUtils(unittest.TestCase):
f" {', '.join(keys_with_defaults)}."
)
def test_nested_config_load_from_dict(self):
config = AutoConfig.from_pretrained(
"hf-internal-testing/tiny-random-CLIPModel", text_config={"num_hidden_layers": 2}
)
self.assertNotIsInstance(config.text_config, dict)
self.assertEqual(config.text_config.__class__.__name__, "CLIPTextConfig")
def test_from_pretrained_subfolder(self):
with self.assertRaises(OSError):
# config is in subfolder, the following should not work without specifying the subfolder