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Merged
sgugger merged 6 commits into from
Apr 4, 2023
Merged

Flax Regnet #21867

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94ca09e
initial commit
Shubhamai Mar 1, 2023
04798f7
Merge branch 'main' into flax-regnet
Shubhamai Mar 25, 2023
3313228
review changes
Shubhamai Mar 25, 2023
d972674
post model PR merge
Shubhamai Mar 26, 2023
a43f26c
updating doc
Shubhamai Mar 26, 2023
9fbae16
Merge branch 'huggingface:main' into flax-regnet
Shubhamai Apr 4, 2023
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2 changes: 1 addition & 1 deletion docs/source/de/index.mdx
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Expand Up @@ -281,7 +281,7 @@ Flax), PyTorch, und/oder TensorFlow haben.
| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
| REALM | ✅ | ✅ | ✅ | ❌ | ❌ |
| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ✅ |
| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| ResNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
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2 changes: 1 addition & 1 deletion docs/source/en/index.mdx
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Expand Up @@ -360,7 +360,7 @@ Flax), PyTorch, and/or TensorFlow.
| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
| REALM | ✅ | ✅ | ✅ | ❌ | ❌ |
| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ✅ |
| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| ResNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
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14 changes: 13 additions & 1 deletion docs/source/en/model_doc/regnet.mdx
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Expand Up @@ -67,4 +67,16 @@ If you're interested in submitting a resource to be included here, please feel f
## TFRegNetForImageClassification

[[autodoc]] TFRegNetForImageClassification
- call
- call


## FlaxRegNetModel

[[autodoc]] FlaxRegNetModel
- __call__


## FlaxRegNetForImageClassification

[[autodoc]] FlaxRegNetForImageClassification
- __call__
2 changes: 1 addition & 1 deletion docs/source/es/index.mdx
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Expand Up @@ -233,7 +233,7 @@ Flax), PyTorch y/o TensorFlow.
| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
| Realm | ✅ | ✅ | ✅ | ❌ | ❌ |
| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ❌ | ✅ |
Comment thread
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Outdated
| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| ResNet | ❌ | ❌ | ✅ | ❌ | ❌ |
| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
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2 changes: 1 addition & 1 deletion docs/source/fr/index.mdx
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Expand Up @@ -345,7 +345,7 @@ Le tableau ci-dessous représente la prise en charge actuelle dans la bibliothè
| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
| REALM | ✅ | ✅ | ✅ | ❌ | ❌ |
| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ✅ |
| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| ResNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
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2 changes: 1 addition & 1 deletion docs/source/it/index.mdx
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Expand Up @@ -250,7 +250,7 @@ tokenizer (chiamato "slow"). Un tokenizer "fast" supportato dalla libreria 🤗
| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
| Realm | ✅ | ✅ | ✅ | ❌ | ❌ |
| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ❌ | ✅ |
Comment thread
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Outdated
| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| ResNet | ❌ | ❌ | ✅ | ❌ | ❌ |
| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
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2 changes: 1 addition & 1 deletion docs/source/ja/index.mdx
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Expand Up @@ -336,7 +336,7 @@ specific language governing permissions and limitations under the License.
| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
| REALM | ✅ | ✅ | ✅ | ❌ | ❌ |
| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ✅ |
| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| ResNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
Expand Down
2 changes: 1 addition & 1 deletion docs/source/ko/index.mdx
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Expand Up @@ -305,7 +305,7 @@ specific language governing permissions and limitations under the License.
| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
| REALM | ✅ | ✅ | ✅ | ❌ | ❌ |
| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ✅ |
| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| ResNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
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2 changes: 1 addition & 1 deletion docs/source/pt/index.mdx
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Expand Up @@ -249,7 +249,7 @@ disso, são diferenciados pelo suporte em diferentes frameworks: JAX (por meio d
| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
| Realm | ✅ | ✅ | ✅ | ❌ | ❌ |
| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ❌ | ✅ |
Comment thread
Shubhamai marked this conversation as resolved.
Outdated
| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| ResNet | ❌ | ❌ | ✅ | ❌ | ❌ |
| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
Expand Down
2 changes: 1 addition & 1 deletion docs/source/zh/index.mdx
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Expand Up @@ -335,7 +335,7 @@ Flax), PyTorch, 和/或者 TensorFlow.
| RAG | ✅ | ❌ | ✅ | ✅ | ❌ |
| REALM | ✅ | ✅ | ✅ | ❌ | ❌ |
| Reformer | ✅ | ✅ | ✅ | ❌ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RegNet | ❌ | ❌ | ✅ | ✅ | ✅ |
| RemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| ResNet | ❌ | ❌ | ✅ | ✅ | ❌ |
| RetriBERT | ✅ | ✅ | ✅ | ❌ | ❌ |
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4 changes: 4 additions & 0 deletions src/transformers/__init__.py
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Expand Up @@ -3561,6 +3561,9 @@
"FlaxPegasusPreTrainedModel",
]
)
_import_structure["models.regnet"].extend(
["FlaxRegNetForImageClassification", "FlaxRegNetModel", "FlaxRegNetPreTrainedModel"]
)
_import_structure["models.roberta"].extend(
[
"FlaxRobertaForCausalLM",
Expand Down Expand Up @@ -6548,6 +6551,7 @@
from .models.mt5 import FlaxMT5EncoderModel, FlaxMT5ForConditionalGeneration, FlaxMT5Model
from .models.opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel
from .models.pegasus import FlaxPegasusForConditionalGeneration, FlaxPegasusModel, FlaxPegasusPreTrainedModel
from .models.regnet import FlaxRegNetForImageClassification, FlaxRegNetModel, FlaxRegNetPreTrainedModel
from .models.roberta import (
FlaxRobertaForCausalLM,
FlaxRobertaForMaskedLM,
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57 changes: 57 additions & 0 deletions src/transformers/modeling_flax_outputs.py
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Expand Up @@ -45,6 +45,63 @@ class FlaxBaseModelOutput(ModelOutput):
attentions: Optional[Tuple[jnp.ndarray]] = None


@flax.struct.dataclass
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class FlaxBaseModelOutputWithNoAttention(ModelOutput):
"""
Args:
Base class for model's outputs, with potential hidden states.
last_hidden_state (`jnp.ndarray` of shape `(batch_size, num_channels, height, width)`):
Sequence of hidden-states at the output of the last layer of the model.
hidden_states (`tuple(jnp.ndarray)`, *optional*, returned when `output_hidden_states=True` is passed or when
`config.output_hidden_states=True`):
Tuple of `jnp.ndarray` (one for the output of the embeddings, if the model has an embedding layer, + one
for the output of each layer) of shape `(batch_size, num_channels, height, width)`. Hidden-states of the
model at the output of each layer plus the optional initial embedding outputs.
"""

last_hidden_state: jnp.ndarray = None
hidden_states: Optional[Tuple[jnp.ndarray]] = None


@flax.struct.dataclass
class FlaxBaseModelOutputWithPoolingAndNoAttention(ModelOutput):
"""
Args:
Base class for model's outputs that also contains a pooling of the last hidden states.
last_hidden_state (`jnp.ndarray` of shape `(batch_size, num_channels, height, width)`):
Sequence of hidden-states at the output of the last layer of the model.
pooler_output (`jnp.ndarray` of shape `(batch_size, hidden_size)`):
Last layer hidden-state after a pooling operation on the spatial dimensions.
hidden_states (`tuple(jnp.ndarray)`, *optional*, returned when `output_hidden_states=True` is passed or when
`config.output_hidden_states=True`):
Tuple of `jnp.ndarray` (one for the output of the embeddings, if the model has an embedding layer, + one
for the output of each layer) of shape `(batch_size, num_channels, height, width)`. Hidden-states of the
model at the output of each layer plus the optional initial embedding outputs.
"""

last_hidden_state: jnp.ndarray = None
pooler_output: jnp.ndarray = None
hidden_states: Optional[Tuple[jnp.ndarray]] = None


@flax.struct.dataclass
class FlaxImageClassifierOutputWithNoAttention(ModelOutput):
"""
Args:
Base class for outputs of image classification models.
logits (`jnp.ndarray` of shape `(batch_size, config.num_labels)`):
Classification (or regression if config.num_labels==1) scores (before SoftMax).
hidden_states (`tuple(jnp.ndarray)`, *optional*, returned when `output_hidden_states=True` is passed or when
`config.output_hidden_states=True`):
Tuple of `jnp.ndarray` (one for the output of the embeddings, if the model has an embedding layer, + one
for the output of each stage) of shape `(batch_size, num_channels, height, width)`. Hidden-states (also
called feature maps) of the model at the output of each stage.
"""

logits: jnp.ndarray = None
hidden_states: Optional[Tuple[jnp.ndarray]] = None


@flax.struct.dataclass
class FlaxBaseModelOutputWithPast(ModelOutput):
"""
Expand Down
2 changes: 2 additions & 0 deletions src/transformers/models/auto/modeling_flax_auto.py
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Expand Up @@ -48,6 +48,7 @@
("mt5", "FlaxMT5Model"),
("opt", "FlaxOPTModel"),
("pegasus", "FlaxPegasusModel"),
("regnet", "FlaxRegNetModel"),
("roberta", "FlaxRobertaModel"),
("roberta-prelayernorm", "FlaxRobertaPreLayerNormModel"),
("roformer", "FlaxRoFormerModel"),
Expand Down Expand Up @@ -119,6 +120,7 @@
[
# Model for Image-classsification
("beit", "FlaxBeitForImageClassification"),
("regnet", "FlaxRegNetForImageClassification"),
("vit", "FlaxViTForImageClassification"),
]
)
Expand Down
32 changes: 31 additions & 1 deletion src/transformers/models/regnet/__init__.py
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Expand Up @@ -13,7 +13,13 @@
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)


_import_structure = {"configuration_regnet": ["REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "RegNetConfig"]}
Expand Down Expand Up @@ -44,6 +50,18 @@
"TFRegNetPreTrainedModel",
]

try:
if not is_flax_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["modeling_flax_regnet"] = [
"FlaxRegNetForImageClassification",
"FlaxRegNetModel",
"FlaxRegNetPreTrainedModel",
]


if TYPE_CHECKING:
from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig
Expand Down Expand Up @@ -74,6 +92,18 @@
TFRegNetPreTrainedModel,
)

try:
if not is_flax_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .modeling_flax_regnet import (
FlaxRegNetForImageClassification,
FlaxRegNetModel,
FlaxRegNetPreTrainedModel,
)


else:
import sys
Expand Down
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