Add standard resnet models

classy_vision/models/resnext.py

@@ -9,7 +9,7 @@
 """
 
 import math
-from typing import Any, Dict
+from typing import Any, Dict, List, Optional, Tuple, Union
 
 import torch.nn as nn
 from classy_vision.generic.util import is_pos_int
@@ -228,13 +228,13 @@ class ResNeXt(ClassyModel):
     def __init__(
         self,
         num_blocks,
-        init_planes,
-        reduction,
-        small_input,
-        zero_init_bn_residuals,
-        base_width_and_cardinality,
-        basic_layer,
-        final_bn_relu,
+        init_planes: int = 64,
+        reduction: int = 4,
+        small_input: bool = False,
+        zero_init_bn_residuals: bool = False,
+        base_width_and_cardinality: Optional[Union[Tuple, List]] = None,
+        basic_layer: bool = False,
+        final_bn_relu: bool = True,
     ):
         """
             Implementation of `ResNeXt <https://arxiv.org/pdf/1611.05431.pdf>`_.
@@ -414,3 +414,108 @@ def output_shape(self):
     @property
     def model_depth(self):
         return sum(self.num_blocks)
+
+
+@register_model("resnet18")
+class ResNet18(ResNeXt):
+    def __init__(self):
+        super().__init__(
+            num_blocks=[2, 2, 2, 2], basic_layer=True, zero_init_bn_residuals=True
+        )
+
+    @classmethod
+    def from_config(cls, config: Dict[str, Any]) -> "ResNeXt":
+        return cls()
+
+
+@register_model("resnet34")
+class ResNet34(ResNeXt):
+    def __init__(self):
+        super().__init__(
+            num_blocks=[3, 4, 6, 3], basic_layer=True, zero_init_bn_residuals=True
+        )
+
+    @classmethod
+    def from_config(cls, config: Dict[str, Any]) -> "ResNeXt":
+        return cls()
+
+
+@register_model("resnet50")
+class ResNet50(ResNeXt):
+    def __init__(self):
+        super().__init__(
+            num_blocks=[3, 4, 6, 3], basic_layer=False, zero_init_bn_residuals=True
+        )
+
+    @classmethod
+    def from_config(cls, config: Dict[str, Any]) -> "ResNeXt":
+        return cls()
+
+
+@register_model("resnet101")
+class ResNet101(ResNeXt):
+    def __init__(self):
+        super().__init__(
+            num_blocks=[3, 4, 23, 3], basic_layer=False, zero_init_bn_residuals=True
+        )
+
+    @classmethod
+    def from_config(cls, config: Dict[str, Any]) -> "ResNeXt":
+        return cls()
+
+
+@register_model("resnet152")
+class ResNet152(ResNeXt):
+    def __init__(self):
+        super().__init__(
+            num_blocks=[3, 8, 36, 3], basic_layer=False, zero_init_bn_residuals=True
+        )
+
+    @classmethod
+    def from_config(cls, config: Dict[str, Any]) -> "ResNeXt":
+        return cls()
+
+
+@register_model("resnext50_32x4d")
+class ResNeXt50(ResNeXt):
+    def __init__(self):
+        super().__init__(
+            num_blocks=[3, 4, 6, 3],
+            basic_layer=False,
+            zero_init_bn_residuals=True,
+            base_width_and_cardinality=(4, 32),
+        )
+
+    @classmethod
+    def from_config(cls, config: Dict[str, Any]) -> "ResNeXt":
+        return cls()
+
+
+@register_model("resnext101_32x4d")
+class ResNeXt101(ResNeXt):
+    def __init__(self):
+        super().__init__(
+            num_blocks=[3, 4, 23, 3],
+            basic_layer=False,
+            zero_init_bn_residuals=True,
+            base_width_and_cardinality=(4, 32),
+        )
+
+    @classmethod
+    def from_config(cls, config: Dict[str, Any]) -> "ResNeXt":
+        return cls()
+
+
+@register_model("resnext152_32x4d")
+class ResNeXt152(ResNeXt):
+    def __init__(self):
+        super().__init__(
+            num_blocks=[3, 8, 36, 3],
+            basic_layer=False,
+            zero_init_bn_residuals=True,
+            base_width_and_cardinality=(4, 32),
+        )
+
+    @classmethod
+    def from_config(cls, config: Dict[str, Any]) -> "ResNeXt":
+        return cls()