Merge pull request #16421 from sayakpaul:feat/convnext

PiperOrigin-RevId: 447824881
keras-team · May 10, 2022 · 3ff21f8 · 3ff21f8
2 parents 874557a + c9e5b0d
commit 3ff21f8
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Showing 11 changed files with 839 additions and 1 deletion.
diff --git a/keras/api/BUILD b/keras/api/BUILD
@@ -21,6 +21,7 @@ exports_files(
 keras_packages = [
     "keras",
     "keras.activations",
+    "keras.applications.convnext",
     "keras.applications.densenet",
     "keras.applications.efficientnet",
     "keras.applications.efficientnet_v2",

diff --git a/keras/api/api_init_files.bzl b/keras/api/api_init_files.bzl
@@ -12,6 +12,7 @@ KERAS_API_INIT_FILES = [
     "keras/__internal__/utils/__init__.py",
     "keras/activations/__init__.py",
     "keras/applications/__init__.py",
+    "keras/applications/convnext/__init__.py",
     "keras/applications/densenet/__init__.py",
     "keras/applications/efficientnet/__init__.py",
     "keras/applications/efficientnet_v2/__init__.py",
@@ -85,6 +86,7 @@ KERAS_API_INIT_FILES_V1 = [
     "keras/__internal__/legacy/rnn_cell/__init__.py",
     "keras/activations/__init__.py",
     "keras/applications/__init__.py",
+    "keras/applications/convnext/__init__.py",
     "keras/applications/densenet/__init__.py",
     "keras/applications/efficientnet/__init__.py",
     "keras/applications/efficientnet_v2/__init__.py",

diff --git a/keras/api/golden/v1/tensorflow.keras.applications.convnext.pbtxt b/keras/api/golden/v1/tensorflow.keras.applications.convnext.pbtxt
@@ -0,0 +1,31 @@
+path: "tensorflow.keras.applications.convnext"
+tf_module {
+  member_method {
+    name: "ConvNeXtBase"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_base\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtLarge"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_large\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtSmall"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_small\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtTiny"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_tiny\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtXLarge"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_xlarge\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "decode_predictions"
+    argspec: "args=[\'preds\', \'top\'], varargs=None, keywords=None, defaults=[\'5\'], "
+  }
+  member_method {
+    name: "preprocess_input"
+    argspec: "args=[\'x\', \'data_format\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/keras/api/golden/v1/tensorflow.keras.applications.pbtxt b/keras/api/golden/v1/tensorflow.keras.applications.pbtxt
@@ -1,5 +1,9 @@
 path: "tensorflow.keras.applications"
 tf_module {
+  member {
+    name: "convnext"
+    mtype: "<type \'module\'>"
+  }
   member {
     name: "densenet"
     mtype: "<type \'module\'>"
@@ -72,6 +76,26 @@ tf_module {
     name: "xception"
     mtype: "<type \'module\'>"
   }
+  member_method {
+    name: "ConvNeXtBase"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_base\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtLarge"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_large\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtSmall"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_small\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtTiny"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_tiny\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtXLarge"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_xlarge\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
   member_method {
     name: "DenseNet121"
     argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "

diff --git a/keras/api/golden/v2/tensorflow.keras.applications.convnext.pbtxt b/keras/api/golden/v2/tensorflow.keras.applications.convnext.pbtxt
@@ -0,0 +1,31 @@
+path: "tensorflow.keras.applications.convnext"
+tf_module {
+  member_method {
+    name: "ConvNeXtBase"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_base\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtLarge"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_large\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtSmall"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_small\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtTiny"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_tiny\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtXLarge"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_xlarge\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "decode_predictions"
+    argspec: "args=[\'preds\', \'top\'], varargs=None, keywords=None, defaults=[\'5\'], "
+  }
+  member_method {
+    name: "preprocess_input"
+    argspec: "args=[\'x\', \'data_format\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/keras/api/golden/v2/tensorflow.keras.applications.pbtxt b/keras/api/golden/v2/tensorflow.keras.applications.pbtxt
@@ -1,5 +1,9 @@
 path: "tensorflow.keras.applications"
 tf_module {
+  member {
+    name: "convnext"
+    mtype: "<type \'module\'>"
+  }
   member {
     name: "densenet"
     mtype: "<type \'module\'>"
@@ -72,6 +76,26 @@ tf_module {
     name: "xception"
     mtype: "<type \'module\'>"
   }
+  member_method {
+    name: "ConvNeXtBase"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_base\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtLarge"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_large\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtSmall"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_small\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtTiny"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_tiny\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
+  member_method {
+    name: "ConvNeXtXLarge"
+    argspec: "args=[\'model_name\', \'include_top\', \'include_preprocessing\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'convnext_xlarge\', \'True\', \'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "
+  }
   member_method {
     name: "DenseNet121"
     argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'classes\', \'classifier_activation\'], varargs=None, keywords=None, defaults=[\'True\', \'imagenet\', \'None\', \'None\', \'None\', \'1000\', \'softmax\'], "

diff --git a/keras/applications/BUILD b/keras/applications/BUILD
@@ -15,6 +15,7 @@ py_library(
     name = "applications",
     srcs = [
         "__init__.py",
+        "convnext.py",
         "densenet.py",
         "efficientnet.py",
         "efficientnet_v2.py",
@@ -270,6 +271,24 @@ tf_py_test(
     ],
 )
 
+tf_py_test(
+    name = "applications_load_weight_test_convnext",
+    size = "large",
+    srcs = ["applications_load_weight_test.py"],
+    args = ["--module=convnext"],
+    main = "applications_load_weight_test.py",
+    tags = [
+        "no_oss",
+        "no_pip",
+    ],
+    deps = [
+        ":applications",
+        "//:expect_absl_installed",
+        "//:expect_tensorflow_installed",
+        "//keras/preprocessing",
+    ],
+)
+
 tf_py_test(
     name = "applications_load_weight_test_densenet",
     size = "large",

diff --git a/keras/applications/__init__.py b/keras/applications/__init__.py
@@ -15,6 +15,12 @@
 """Keras Applications are premade architectures with pre-trained weights."""
 # pylint: disable=g-bad-import-order
 
+from keras.applications.convnext import ConvNeXtTiny
+from keras.applications.convnext import ConvNeXtSmall
+from keras.applications.convnext import ConvNeXtBase
+from keras.applications.convnext import ConvNeXtLarge
+from keras.applications.convnext import ConvNeXtXLarge
+
 from keras.applications.densenet import DenseNet121
 from keras.applications.densenet import DenseNet169
 from keras.applications.densenet import DenseNet201

diff --git a/keras/applications/applications_load_weight_test.py b/keras/applications/applications_load_weight_test.py
@@ -20,6 +20,7 @@
 from absl.testing import parameterized
 import numpy as np
 
+from keras.applications import convnext
 from keras.applications import densenet
 from keras.applications import efficientnet
 from keras.applications import efficientnet_v2
@@ -55,6 +56,10 @@
     'mobilenet_v2': (mobilenet_v2, [mobilenet_v2.MobileNetV2]),
     'mobilenet_v3_small': (mobilenet_v3, [mobilenet_v3.MobileNetV3Small]),
     'mobilenet_v3_large': (mobilenet_v3, [mobilenet_v3.MobileNetV3Large]),
+    'convnext': 
+        (convnext, 
+        [convnext.ConvNeXtTiny, convnext.ConvNeXtSmall, convnext.ConvNeXtBase,
+        convnext.ConvNeXtLarge, convnext.ConvNeXtXLarge]),
     'densenet':
         (densenet,
          [densenet.DenseNet121, densenet.DenseNet169, densenet.DenseNet201]),

diff --git a/keras/applications/applications_test.py b/keras/applications/applications_test.py
@@ -16,6 +16,7 @@
 
 from absl.testing import parameterized
 from keras import backend
+from keras.applications import convnext
 from keras.applications import densenet
 from keras.applications import efficientnet
 from keras.applications import efficientnet_v2
@@ -32,6 +33,7 @@
 from keras.applications import vgg16
 from keras.applications import vgg19
 from keras.applications import xception
+from keras import utils
 import tensorflow.compat.v2 as tf
 
 MODEL_LIST_NO_NASNET = [(resnet.ResNet50, 2048), (resnet.ResNet101, 2048),
@@ -45,6 +47,11 @@
                         (mobilenet_v2.MobileNetV2, 1280),
                         (mobilenet_v3.MobileNetV3Small, 576),
                         (mobilenet_v3.MobileNetV3Large, 960),
+                        (convnext.ConvNeXtTiny, 768),
+                        (convnext.ConvNeXtSmall, 768),
+                        (convnext.ConvNeXtBase, 1024),
+                        (convnext.ConvNeXtLarge, 1536),
+                        (convnext.ConvNeXtXLarge, 2048),
                         (densenet.DenseNet121, 1024),
                         (densenet.DenseNet169, 1664),
                         (densenet.DenseNet201, 1920),
@@ -124,7 +131,12 @@ def test_application_base(self, app, _):
     model = app(weights=None)
     # Can be serialized and deserialized
     config = model.get_config()
-    reconstructed_model = model.__class__.from_config(config)
+    if "ConvNeXt" in app.__name__:
+      custom_objects = {"LayerScale": convnext.LayerScale}
+      with utils.custom_object_scope(custom_objects):
+        reconstructed_model = model.__class__.from_config(config)
+    else:
+      reconstructed_model = model.__class__.from_config(config)
     self.assertEqual(len(model.weights), len(reconstructed_model.weights))
     backend.clear_session()