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Commit
ed94a7c
1 Parent(s): 1392c84
Files changed (4) hide show
  1. config.json +26 -0
  2. configuration_resnet.py +35 -0
  3. modeling_resnet.py +50 -0
  4. pytorch_model.bin +3 -0
config.json ADDED
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+ {
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+ "architectures": [
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+ "ResnetModelForImageClassification"
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+ ],
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+ "auto_map": {
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+ "AutoConfig": "configuration_resnet.ResnetConfig",
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+ "AutoModelForImageClassification": "modeling_resnet.ResnetModelForImageClassification"
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+ },
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+ "avg_down": true,
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+ "base_width": 64,
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+ "block_type": "bottleneck",
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+ "cardinality": 1,
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+ "input_channels": 3,
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+ "layers": [
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+ 3,
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+ 4,
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+ 6,
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+ 3
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+ ],
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+ "model_type": "resnet",
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+ "num_classes": 1000,
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+ "stem_type": "deep",
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+ "stem_width": 32,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.17.0.dev0"
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+ }
configuration_resnet.py ADDED
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+ from transformers import PretrainedConfig
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+ from typing import List
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+
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+
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+ class ResnetConfig(PretrainedConfig):
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+ model_type="resnet"
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+
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+ def __init__(
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+ self,
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+ block_type="bottleneck",
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+ layers: List[int] = [3, 4, 6, 3],
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+ num_classes: int = 1000,
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+ input_channels: int = 3,
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+ cardinality: int = 1,
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+ base_width: int = 64,
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+ stem_width: int = 64,
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+ stem_type: str = "",
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+ avg_down: bool = False,
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+ **kwargs,
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+ ):
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+ if block_type not in ["basic", "bottleneck"]:
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+ raise ValueError(f"`block` must be 'basic' or bottleneck', got {block}.")
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+ if stem_type not in ["", "deep", "deep-tiered"]:
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+ raise ValueError(f"`stem_type` must be '', 'deep' or 'deep-tiered', got {block}.")
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+
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+ self.block_type = block_type
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+ self.layers = layers
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+ self.num_classes=num_classes
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+ self.input_channels=input_channels
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+ self.cardinality = cardinality
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+ self.base_width = base_width
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+ self.stem_width = stem_width
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+ self.stem_type = stem_type
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+ self.avg_down = avg_down
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+ super().__init__(**kwargs)
modeling_resnet.py ADDED
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+ from transformers import PreTrainedModel
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+ from timm.models.resnet import BasicBlock, Bottleneck, ResNet
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+ from .configuration_resnet import ResnetConfig
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+
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+
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+ BLOCK_MAPPING = {"basic": BasicBlock, "bottleneck": Bottleneck}
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+
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+
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+ class ResnetModel(PreTrainedModel):
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+ config_class = ResnetConfig
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+
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+ def __init__(self, config):
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+ super().__init__(config)
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+ block_layer = BLOCK_MAPPING[config.block_type]
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+ self.model = ResNet(
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+ block_layer,
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+ config.layers,
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+ num_classes=config.num_classes,
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+ in_chans=config.input_channels,
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+ cardinality=config.cardinality,
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+ base_width=config.base_width,
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+ stem_width=config.stem_width,
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+ stem_type=config.stem_type,
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+ avg_down=config.avg_down,
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+ )
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+
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+ def forward(self, tensor):
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+ return self.model.forward_features(tensor)
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+
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+
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+ class ResnetModelForImageClassification(PreTrainedModel):
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+ config_class = ResnetConfig
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+
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+ def __init__(self, config):
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+ super().__init__(config)
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+ block_layer = BLOCK_MAPPING[config.block_type]
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+ self.model = ResNet(
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+ block_layer,
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+ config.layers,
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+ num_classes=config.num_classes,
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+ in_chans=config.input_channels,
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+ cardinality=config.cardinality,
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+ base_width=config.base_width,
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+ stem_width=config.stem_width,
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+ stem_type=config.stem_type,
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+ avg_down=config.avg_down,
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+ )
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+
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+ def forward(self, tensor):
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+ return self.model(tensor)
pytorch_model.bin ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:25a41ac7007f542318ceaadf94bf3d75c55d1813219a634b35d6722f10fc91c2
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+ size 102626153