Fix TF exports >= 2GB (#6292)

* Fix exporting saved_model: pb exceeds 2GB

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Replace TF v1.x API with TF v2.x API for saved_model export

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Clean up

* Remove lambda in tf.function()

* Revert "Remove lambda in tf.function()" to be compatible with TF v2.4

This reverts commit 46c7931f11dfdea6ae340c77287c35c30b9e0779.

* Fix for pre-commit.ci

* Cleanup1

* Cleanup2

* Backwards compatibility update

* Update common.py

* Update common.py

* Cleanup3

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

models/common.py

@@ -359,7 +359,8 @@ class DetectMultiBackend(nn.Module):
             if saved_model:  # SavedModel
                 LOGGER.info(f'Loading {w} for TensorFlow SavedModel inference...')
                 import tensorflow as tf
-                model = tf.keras.models.load_model(w)
+                keras = False  # assume TF1 saved_model
+                model = tf.keras.models.load_model(w) if keras else tf.saved_model.load(w)
             elif pb:  # GraphDef https://www.tensorflow.org/guide/migrate#a_graphpb_or_graphpbtxt
                 LOGGER.info(f'Loading {w} for TensorFlow GraphDef inference...')
                 import tensorflow as tf
@@ -431,7 +432,7 @@ class DetectMultiBackend(nn.Module):
         else:  # TensorFlow (SavedModel, GraphDef, Lite, Edge TPU)
             im = im.permute(0, 2, 3, 1).cpu().numpy()  # torch BCHW to numpy BHWC shape(1,320,192,3)
             if self.saved_model:  # SavedModel
-                y = self.model(im, training=False).numpy()
+                y = (self.model(im, training=False) if self.keras else self.model(im)[0]).numpy()
             elif self.pb:  # GraphDef
                 y = self.frozen_func(x=self.tf.constant(im)).numpy()
             elif self.tflite:  # Lite