【昇腾AI创新大赛】 poolformer (#1158)

Author: zhouyifeng888

mindnlp/transformers/models/__init__.py

@@ -107,6 +107,7 @@
     pegasus,
     phi,
     phi3,
+    poolformer,
     pop2piano,
     qwen2,
     qwen2_moe,
@@ -228,6 +229,7 @@
 from .pegasus import *
 from .phi import *
 from .phi3 import *
+from .poolformer import *
 from .pop2piano import *
 from .qwen2 import *
 from .qwen2_moe import *
@@ -349,6 +351,7 @@
 __all__.extend(pegasus.__all__)
 __all__.extend(phi.__all__)
 __all__.extend(phi3.__all__)
+__all__.extend(poolformer.__all__)
 __all__.extend(pop2piano.__all__)
 __all__.extend(qwen2.__all__)
 __all__.extend(qwen2_moe.__all__)

mindnlp/transformers/models/poolformer/__init__.py

@@ -0,0 +1,29 @@
+# Copyright 2024 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================
+"""
+PoolFormer Model init
+"""
+from .import configuration_poolformer, feature_extraction_poolformer, image_processing_poolformer, modeling_poolformer
+
+from .configuration_poolformer import *
+from .feature_extraction_poolformer import *
+from .image_processing_poolformer import *
+from .modeling_poolformer import *
+
+__all__ = []
+__all__.extend(configuration_poolformer.__all__)
+__all__.extend(feature_extraction_poolformer.__all__)
+__all__.extend(image_processing_poolformer.__all__)
+__all__.extend(modeling_poolformer.__all__)

mindnlp/transformers/models/poolformer/configuration_poolformer.py

@@ -0,0 +1,124 @@
+# Copyright 2024 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================
+"""PoolFormer model configuration"""
+
+from ...configuration_utils import PretrainedConfig
+
+
+class PoolFormerConfig(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of [`PoolFormerModel`]. It is used to instantiate a
+    PoolFormer model according to the specified arguments, defining the model architecture. Instantiating a
+    configuration with the defaults will yield a similar configuration to that of the PoolFormer
+    [sail/poolformer_s12](https://huggingface.co/sail/poolformer_s12) architecture.
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+
+    Args:
+        num_channels (`int`, *optional*, defaults to 3):
+            The number of channels in the input image.
+        patch_size (`int`, *optional*, defaults to 16):
+            The size of the input patch.
+        stride (`int`, *optional*, defaults to 16):
+            The stride of the input patch.
+        pool_size (`int`, *optional*, defaults to 3):
+            The size of the pooling window.
+        mlp_ratio (`float`, *optional*, defaults to 4.0):
+            The ratio of the number of channels in the output of the MLP to the number of channels in the input.
+        depths (`list`, *optional*, defaults to `[2, 2, 6, 2]`):
+            The depth of each encoder block.
+        hidden_sizes (`list`, *optional*, defaults to `[64, 128, 320, 512]`):
+            The hidden sizes of each encoder block.
+        patch_sizes (`list`, *optional*, defaults to `[7, 3, 3, 3]`):
+            The size of the input patch for each encoder block.
+        strides (`list`, *optional*, defaults to `[4, 2, 2, 2]`):
+            The stride of the input patch for each encoder block.
+        padding (`list`, *optional*, defaults to `[2, 1, 1, 1]`):
+            The padding of the input patch for each encoder block.
+        num_encoder_blocks (`int`, *optional*, defaults to 4):
+            The number of encoder blocks.
+        drop_path_rate (`float`, *optional*, defaults to 0.0):
+            The dropout rate for the dropout layers.
+        hidden_act (`str`, *optional*, defaults to `"gelu"`):
+            The activation function for the hidden layers.
+        use_layer_scale (`bool`, *optional*, defaults to `True`):
+            Whether to use layer scale.
+        layer_scale_init_value (`float`, *optional*, defaults to 1e-05):
+            The initial value for the layer scale.
+        initializer_range (`float`, *optional*, defaults to 0.02):
+            The initializer range for the weights.
+
+    Example:
+
+    ```python
+    >>> from transformers import PoolFormerConfig, PoolFormerModel
+
+    >>> # Initializing a PoolFormer sail/poolformer_s12 style configuration
+    >>> configuration = PoolFormerConfig()
+
+    >>> # Initializing a model (with random weights) from the sail/poolformer_s12 style configuration
+    >>> model = PoolFormerModel(configuration)
+
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+    ```
+    """
+
+    model_type = "poolformer"
+
+    def __init__(
+        self,
+        num_channels=3,
+        patch_size=16,
+        stride=16,
+        pool_size=3,
+        mlp_ratio=4.0,
+        depths=[2, 2, 6, 2],
+        hidden_sizes=[64, 128, 320, 512],
+        patch_sizes=[7, 3, 3, 3],
+        strides=[4, 2, 2, 2],
+        padding=[2, 1, 1, 1],
+        num_encoder_blocks=4,
+        drop_path_rate=0.0,
+        hidden_act="gelu",
+        use_layer_scale=True,
+        layer_scale_init_value=1e-5,
+        initializer_range=0.02,
+        **kwargs,
+    ):
+        self.num_channels = num_channels
+        self.patch_size = patch_size
+        self.stride = stride
+        self.padding = padding
+        self.pool_size = pool_size
+        self.hidden_sizes = hidden_sizes
+        self.mlp_ratio = mlp_ratio
+        self.depths = depths
+        self.patch_sizes = patch_sizes
+        self.strides = strides
+        self.num_encoder_blocks = num_encoder_blocks
+        self.drop_path_rate = drop_path_rate
+        self.hidden_act = hidden_act
+        self.use_layer_scale = use_layer_scale
+        self.layer_scale_init_value = layer_scale_init_value
+        self.initializer_range = initializer_range
+        super().__init__(**kwargs)
+
+
+__all__ = [
+    "PoolFormerConfig",
+]

mindnlp/transformers/models/poolformer/feature_extraction_poolformer.py

@@ -0,0 +1,34 @@
+# Copyright 2024 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================
+"""Feature extractor class for PoolFormer."""
+
+import warnings
+
+from .image_processing_poolformer import PoolFormerImageProcessor
+
+
+class PoolFormerFeatureExtractor(PoolFormerImageProcessor):
+    def __init__(self, *args, **kwargs) -> None:
+        warnings.warn(
+            "The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
+            " Please use PoolFormerImageProcessor instead.",
+            FutureWarning,
+        )
+        super().__init__(*args, **kwargs)
+
+
+__all__ = [
+    "PoolFormerFeatureExtractor",
+]