Allow all imports from transformers (#17050)

docs/source/en/model_doc/cpm.mdx

@@ -38,3 +38,7 @@ Note: We only have a tokenizer here, since the model architecture is the same as
 ## CpmTokenizer
 
 [[autodoc]] CpmTokenizer
+
+## CpmTokenizerFast
+
+[[autodoc]] CpmTokenizerFast

src/transformers/__init__.py

@@ -168,7 +168,7 @@ _import_structure = {
     ],
     "models.convbert": ["CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvBertConfig", "ConvBertTokenizer"],
     "models.convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig"],
-    "models.cpm": ["CpmTokenizer"],
+    "models.cpm": [],
     "models.ctrl": ["CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP", "CTRLConfig", "CTRLTokenizer"],
     "models.data2vec": [
         "DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP",
@@ -197,7 +197,7 @@ _import_structure = {
     "models.electra": ["ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP", "ElectraConfig", "ElectraTokenizer"],
     "models.encoder_decoder": ["EncoderDecoderConfig"],
     "models.flaubert": ["FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "FlaubertConfig", "FlaubertTokenizer"],
-    "models.fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FNetConfig", "FNetTokenizer"],
+    "models.fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FNetConfig"],
     "models.fsmt": ["FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP", "FSMTConfig", "FSMTTokenizer"],
     "models.funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig", "FunnelTokenizer"],
     "models.glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"],
@@ -419,7 +419,9 @@ if is_sentencepiece_available():
     _import_structure["models.bert_generation"].append("BertGenerationTokenizer")
     _import_structure["models.big_bird"].append("BigBirdTokenizer")
     _import_structure["models.camembert"].append("CamembertTokenizer")
+    _import_structure["models.cpm"].append("CpmTokenizer")
     _import_structure["models.deberta_v2"].append("DebertaV2Tokenizer")
+    _import_structure["models.fnet"].append("FNetTokenizer")
     _import_structure["models.layoutxlm"].append("LayoutXLMTokenizer")
     _import_structure["models.m2m_100"].append("M2M100Tokenizer")
     _import_structure["models.marian"].append("MarianTokenizer")
@@ -457,6 +459,7 @@ if is_tokenizers_available():
     _import_structure["models.camembert"].append("CamembertTokenizerFast")
     _import_structure["models.clip"].append("CLIPTokenizerFast")
     _import_structure["models.convbert"].append("ConvBertTokenizerFast")
+    _import_structure["models.cpm"].append("CpmTokenizerFast")
     _import_structure["models.deberta"].append("DebertaTokenizerFast")
     _import_structure["models.deberta_v2"].append("DebertaV2TokenizerFast")
     _import_structure["models.distilbert"].append("DistilBertTokenizerFast")
@@ -2575,7 +2578,6 @@ if TYPE_CHECKING:
     )
     from .models.convbert import CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvBertConfig, ConvBertTokenizer
     from .models.convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig
-    from .models.cpm import CpmTokenizer
     from .models.ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig, CTRLTokenizer
     from .models.data2vec import (
         DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
@@ -2605,7 +2607,7 @@ if TYPE_CHECKING:
     from .models.electra import ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP, ElectraConfig, ElectraTokenizer
     from .models.encoder_decoder import EncoderDecoderConfig
     from .models.flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertTokenizer
-    from .models.fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig, FNetTokenizer
+    from .models.fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig
     from .models.fsmt import FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP, FSMTConfig, FSMTTokenizer
     from .models.funnel import FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP, FunnelConfig, FunnelTokenizer
     from .models.glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig
@@ -2809,7 +2811,9 @@ if TYPE_CHECKING:
         from .models.bert_generation import BertGenerationTokenizer
         from .models.big_bird import BigBirdTokenizer
         from .models.camembert import CamembertTokenizer
+        from .models.cpm import CpmTokenizer
         from .models.deberta_v2 import DebertaV2Tokenizer
+        from .models.fnet import FNetTokenizer
         from .models.layoutxlm import LayoutXLMTokenizer
         from .models.m2m_100 import M2M100Tokenizer
         from .models.marian import MarianTokenizer
@@ -2840,6 +2844,7 @@ if TYPE_CHECKING:
         from .models.camembert import CamembertTokenizerFast
         from .models.clip import CLIPTokenizerFast
         from .models.convbert import ConvBertTokenizerFast
+        from .models.cpm import CpmTokenizerFast
         from .models.deberta import DebertaTokenizerFast
         from .models.deberta_v2 import DebertaV2TokenizerFast
         from .models.distilbert import DistilBertTokenizerFast

src/transformers/models/fnet/__init__.py

@@ -17,14 +17,18 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
+from transformers import is_sentencepiece_available
+
 from ...utils import _LazyModule, is_tokenizers_available, is_torch_available
 
 
 _import_structure = {
     "configuration_fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FNetConfig"],
-    "tokenization_fnet": ["FNetTokenizer"],
 }
 
+if is_sentencepiece_available():
+    _import_structure["tokenization_fnet"] = ["FNetTokenizer"]
+
 if is_tokenizers_available():
     _import_structure["tokenization_fnet_fast"] = ["FNetTokenizerFast"]
 
@@ -46,7 +50,9 @@ if is_torch_available():
 
 if TYPE_CHECKING:
     from .configuration_fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig
-    from .tokenization_fnet import FNetTokenizer
+
+    if is_sentencepiece_available():
+        from .tokenization_fnet import FNetTokenizer
 
     if is_tokenizers_available():
         from .tokenization_fnet_fast import FNetTokenizerFast

src/transformers/utils/dummy_sentencepiece_objects.py

@@ -45,6 +45,13 @@ class CamembertTokenizer(metaclass=DummyObject):
         requires_backends(self, ["sentencepiece"])
 
 
+class CpmTokenizer(metaclass=DummyObject):
+    _backends = ["sentencepiece"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["sentencepiece"])
+
+
 class DebertaV2Tokenizer(metaclass=DummyObject):
     _backends = ["sentencepiece"]
 
@@ -52,6 +59,13 @@ class DebertaV2Tokenizer(metaclass=DummyObject):
         requires_backends(self, ["sentencepiece"])
 
 
+class FNetTokenizer(metaclass=DummyObject):
+    _backends = ["sentencepiece"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["sentencepiece"])
+
+
 class LayoutXLMTokenizer(metaclass=DummyObject):
     _backends = ["sentencepiece"]
 

src/transformers/utils/dummy_tokenizers_objects.py

@@ -73,6 +73,13 @@ class ConvBertTokenizerFast(metaclass=DummyObject):
         requires_backends(self, ["tokenizers"])
 
 
+class CpmTokenizerFast(metaclass=DummyObject):
+    _backends = ["tokenizers"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["tokenizers"])
+
+
 class DebertaTokenizerFast(metaclass=DummyObject):
     _backends = ["tokenizers"]