Merge branch 'tensorflow:master' into master

docs/README.md

@@ -1,7 +1,7 @@
 # Public docs for TensorFlow Models
 
 This directory contains the top-level public documentation for
-[TensorFlow Models](https://github.com/tensorflow/models)
+[TensorFlow Models](https://github.com/tensorflow/models).
 
 This directory is mirrored to https://tensorflow.org/tfmodels, and is mainly
 concerned with documenting the tools provided in the `tensorflow_models` pip

docs/nlp/fine_tune_bert.ipynb

@@ -884,7 +884,7 @@
         "id": "2oHOql35k3Dd"
       },
       "source": [
-        "Note: The pretrained `TransformerEncoder` is also available on [TensorFlow Hub](https://tensorflow.org/hub). Go to the [TF Hub appendix](#hub_bert) for details."
+        "Note: The pre-trained `TransformerEncoder` is also available on [TensorFlow Hub](https://tensorflow.org/hub). Go to the [TF Hub appendix](#hub_bert) for details."
       ]
     },
     {
@@ -1148,8 +1148,8 @@
         "\n",
         "First, build a wrapper class to export the model. This wrapper does two things:\n",
         "\n",
-        "- First it packages `bert_inputs_processor` and `bert_classifier` together into a single `tf.Module`, so you can export all the functionalities.\n",
-        "- Second it defines a `tf.function` that implements the end-to-end execution of the model.\n",
+        "- First, it packages `bert_inputs_processor` and `bert_classifier` together into a single `tf.Module`, so you can export all the functionalities.\n",
+        "- Second, it defines a `tf.function` that implements the end-to-end execution of the model.\n",
         "\n",
         "Setting the `input_signature` argument of `tf.function` lets you define a fixed signature for the `tf.function`. This can be less surprising than the default automatic retracing behavior."
       ]
@@ -1189,7 +1189,7 @@
         "id": "qnxysGUfIgFQ"
       },
       "source": [
-        "Create an instance of this export-model and save it:"
+        "Create an instance of this exported model and save it:"
       ]
     },
     {
@@ -1280,7 +1280,7 @@
         "id": "CPsg7dZwfBM2"
       },
       "source": [
-        "Congratulations! You've used `tensorflow_models` to build a BERT-classifier, train it, and export for later use."
+        "Congratulations! You've used `tensorflow_models` to build a BERT-classifier, train it, and export it for later use."
       ]
     },
     {
@@ -1391,7 +1391,7 @@
         "id": "cjojn8SmLSRI"
       },
       "source": [
-        "At this point it would be simple to add a classification head yourself.\n",
+        "At this point, it would be simple to add a classification head yourself.\n",
         "\n",
         "The Model Garden `tfm.nlp.models.BertClassifier` class can also build a classifier onto the TF Hub encoder:"
       ]
@@ -1429,7 +1429,7 @@
         "id": "u_IqwXjRV1vd"
       },
       "source": [
-        "For concrete examples of this approach, refer to [Solve Glue tasks using BERT](https://www.tensorflow.org/text/tutorials/bert_glue)."
+        "For concrete examples of this approach, refer to [Solve Glue tasks using the BERT](https://www.tensorflow.org/text/tutorials/bert_glue)."
       ]
     },
     {
@@ -1494,7 +1494,7 @@
         "id": "ywn5miD_dnuh"
       },
       "source": [
-        "The advantage to using `config` objects is that they don't contain any complicated TensorFlow objects, and can be easily serialized to JSON, and rebuilt. Here's the JSON for the above `tfm.optimization.OptimizationConfig`:"
+        "The advantage of using `config` objects is that they don't contain any complicated TensorFlow objects, and can be easily serialized to JSON, and rebuilt. Here's the JSON for the above `tfm.optimization.OptimizationConfig`:"
       ]
     },
     {

docs/vision/semantic_segmentation.ipynb

@@ -39,20 +39,20 @@
       "source": [
         "# Semantic Segmentation with Model Garden\n",
         "\n",
-        "\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
-        "  \u003ctd\u003e\n",
-        "    \u003ca target=\"_blank\" href=\"https://www.tensorflow.org/tfmodels/vision/semantic_segmentation\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eView on TensorFlow.org\u003c/a\u003e\n",
-        "  \u003c/td\u003e\n",
-        "  \u003ctd\u003e\n",
-        "    \u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/models/blob/master/docs/vision/semantic_segmentation.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003eRun in Google Colab\u003c/a\u003e\n",
-        "  \u003c/td\u003e\n",
-        "  \u003ctd\u003e\n",
-        "    \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/models/blob/master/docs/vision/semantic_segmentation.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView on GitHub\u003c/a\u003e\n",
-        "  \u003c/td\u003e\n",
-        "  \u003ctd\u003e\n",
-        "    \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/models/docs/vision/semantic_segmentation.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003eDownload notebook\u003c/a\u003e\n",
-        "  \u003c/td\u003e\n",
-        "\u003c/table\u003e"
+        "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
+        "  <td>\n",
+        "    <a target=\"_blank\" href=\"https://www.tensorflow.org/tfmodels/vision/semantic_segmentation\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" />View on TensorFlow.org</a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/models/blob/master/docs/vision/semantic_segmentation.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a target=\"_blank\" href=\"https://github.com/tensorflow/models/blob/master/docs/vision/semantic_segmentation.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View on GitHub</a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a href=\"https://storage.googleapis.com/tensorflow_docs/models/docs/vision/semantic_segmentation.ipynb\"><img src=\"https://www.tensorflow.org/images/download_logo_32px.png\" />Download notebook</a>\n",
+        "  </td>\n",
+        "</table>"
       ]
     },
     {
@@ -95,7 +95,7 @@
       },
       "outputs": [],
       "source": [
-        "!pip install -U -q \"tensorflow\u003e=2.9.2\" \"tf-models-official\""
+        "!pip install -U -q \"tf-models-official\""
       ]
     },
     {
@@ -138,6 +138,7 @@
         "import orbit\n",
         "import tensorflow_models as tfm\n",
         "from official.vision.data import tfrecord_lib\n",
+        "from official.vision.utils import summary_manager\n",
         "from official.vision.serving import export_saved_model_lib\n",
         "from official.vision.utils.object_detection import visualization_utils\n",
         "\n",
@@ -428,7 +429,8 @@
         "exp_config.task.validation_data.output_size = [HEIGHT, WIDTH]\n",
         "exp_config.task.validation_data.preserve_aspect_ratio = False\n",
         "exp_config.task.validation_data.groundtruth_padded_size = [HEIGHT, WIDTH]\n",
-        "exp_config.task.validation_data.seed = 21 # Reproducable Validation Data"
+        "exp_config.task.validation_data.seed = 21 # Reproducable Validation Data\n",
+        "exp_config.task.validation_data.resize_eval_groundtruth = True # To enable validation loss"
       ]
     },
     {
@@ -540,7 +542,7 @@
       "source": [
         "## Create the `Task` object (`tfm.core.base_task.Task`) from the `config_definitions.TaskConfig`.\n",
         "\n",
-        "The `Task` object has all the methods necessary for building the dataset, building the model, and running training \u0026 evaluation. These methods are driven by `tfm.core.train_lib.run_experiment`."
+        "The `Task` object has all the methods necessary for building the dataset, building the model, and running training & evaluation. These methods are driven by `tfm.core.train_lib.run_experiment`."
       ]
     },
     {
@@ -597,7 +599,7 @@
       },
       "outputs": [],
       "source": [
-        "def display(display_list):\n",
+        "def plot_masks(display_list):\n",
         "  plt.figure(figsize=(15, 15))\n",
         "\n",
         "  title = ['Input Image', 'True Mask', 'Predicted Mask']\n",
@@ -636,7 +638,7 @@
         "num_examples = 3\n",
         "\n",
         "for images, masks in task.build_inputs(exp_config.task.train_data).take(num_examples):\n",
-        "  display([images[0], masks['masks'][0]])"
+        "  plot_masks([images[0], masks['masks'][0]])"
       ]
     },
     {
@@ -657,12 +659,15 @@
       },
       "outputs": [],
       "source": [
+        "\n",
         "model, eval_logs = tfm.core.train_lib.run_experiment(\n",
         "    distribution_strategy=distribution_strategy,\n",
         "    task=task,\n",
         "    mode='train_and_eval',\n",
         "    params=exp_config,\n",
         "    model_dir=model_dir,\n",
+        "    eval_summary_manager=summary_manager.maybe_build_eval_summary_manager(\n",
+        "              params=exp_config, model_dir=model_dir),\n",
         "    run_post_eval=True)"
       ]
     },
@@ -764,7 +769,7 @@
         "  image = tf.cast(image, dtype=tf.uint8)\n",
         "  mask = tf.image.resize(record['segmentation_mask'], size=[HEIGHT, WIDTH])\n",
         "  predicted_mask = model_fn(tf.expand_dims(record['image'], axis=0))\n",
-        "  display([image, mask, create_mask(predicted_mask['logits'])])"
+        "  plot_masks([image, mask, create_mask(predicted_mask['logits'])])"
       ]
     }
   ],

official/README-TPU.md

@@ -2,28 +2,28 @@
 
 ## Natural Language Processing
 
-*   [bert](nlp/bert): A powerful pre-trained language representation model:
+*   [bert](https://arxiv.org/abs/1810.04805): A powerful pre-trained language representation model:
     BERT, which stands for Bidirectional Encoder Representations from
     Transformers.
-    [BERT FineTuning with Cloud TPU](https://cloud.google.com/tpu/docs/tutorials/bert-2.x) provides step by step instructions on Cloud TPU training. You can look [Bert MNLI Tensorboard.dev metrics](https://tensorboard.dev/experiment/LijZ1IrERxKALQfr76gndA) for MNLI fine tuning task.
+    [BERT FineTuning with Cloud TPU](https://cloud.google.com/ai-platform/training/docs/algorithms/bert-start) provides step by step instructions on Cloud TPU training. You can look [Bert MNLI Tensorboard.dev metrics](https://tensorboard.dev/experiment/LijZ1IrERxKALQfr76gndA) for MNLI fine tuning task.
 *   [transformer](nlp/transformer): A transformer model to translate the WMT
     English to German dataset.
         [Training transformer on Cloud TPU](https://cloud.google.com/tpu/docs/tutorials/transformer-2.x) for step by step instructions on Cloud TPU training.
 
 ## Computer Vision
 
-*   [efficientnet](vision/image_classification): A family of convolutional
+*   [efficientnet](https://github.com/tensorflow/models/blob/master/official/vision/modeling/backbones/efficientnet.py): A family of convolutional
     neural networks that scale by balancing network depth, width, and
     resolution and can be used to classify ImageNet's dataset of 1000 classes.
     See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/KnaWjrq5TXGfv0NW5m7rpg/#scalars).
-*   [mnist](vision/image_classification): A basic model to classify digits
+*   [mnist](https://www.tensorflow.org/datasets/catalog/mnist): A basic model to classify digits
     from the MNIST dataset. See [Running MNIST on Cloud TPU](https://cloud.google.com/tpu/docs/tutorials/mnist-2.x) tutorial and [Tensorboard.dev metrics](https://tensorboard.dev/experiment/mIah5lppTASvrHqWrdr6NA).
-*   [mask-rcnn](vision/detection): An object detection and instance segmentation model. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/LH7k0fMsRwqUAcE09o9kPA).
-*   [resnet](vision/image_classification): A deep residual network that can
+*   [mask-rcnn](https://www.tensorflow.org/api_docs/python/tfm/vision/configs/maskrcnn/MaskRCNN): An object detection and instance segmentation model. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/LH7k0fMsRwqUAcE09o9kPA).
+*   [resnet]((https://www.tensorflow.org/api_docs/python/tfm/vision/configs/image_classification/image_classification_imagenet)): A deep residual network that can
     be used to classify ImageNet's dataset of 1000 classes.
     See [Training ResNet on Cloud TPU](https://cloud.google.com/tpu/docs/tutorials/resnet-2.x) tutorial and [Tensorboard.dev metrics](https://tensorboard.dev/experiment/CxlDK8YMRrSpYEGtBRpOhg).
-*   [retinanet](vision/detection): A fast and powerful object detector. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/b8NRnWU3TqG6Rw0UxueU6Q).
-*   [shapemask](vision/detection): An object detection and instance segmentation model using shape priors. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/ZbXgVoc6Rf6mBRlPj0JpLA).
+*   [retinanet](https://www.tensorflow.org/api_docs/python/tfm/vision/retinanet): A fast and powerful object detector. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/b8NRnWU3TqG6Rw0UxueU6Q).
+*   [shapemask](https://cloud.google.com/tpu/docs/tutorials/shapemask-2.x): An object detection and instance segmentation model using shape priors. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/ZbXgVoc6Rf6mBRlPj0JpLA).
 
 ## Recommendation
 *   [dlrm](recommendation/ranking): [Deep Learning Recommendation Model for

official/__init__.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/common/__init__.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/common/dataset_fn.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/common/distribute_utils.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/common/distribute_utils_test.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/common/flags.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/common/registry_imports.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/common/streamz_counters.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/__init__.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/actions.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/actions_test.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/base_task.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/base_trainer.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/base_trainer_test.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/config_definitions.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -55,6 +55,8 @@ class DataConfig(base_config.Config):
       interleaving files.
     block_length: The number of consecutive elements to produce from each input
       element before cycling to another input element when interleaving files.
+    ram_budget: RAM budget for tf.data service in GB. If None, tf.data will use
+      50% of the available host RAM.
     deterministic: A boolean controlling whether determinism should be enforced.
     sharding: Whether sharding is used in the input pipeline.
     enable_tf_data_service: A boolean indicating whether to enable tf.data
@@ -117,6 +119,7 @@ class DataConfig(base_config.Config):
   cache: bool = False
   cycle_length: Optional[int] = None
   block_length: int = 1
+  ram_budget: Optional[int] = None
   deterministic: Optional[bool] = None
   sharding: bool = True
   enable_tf_data_service: bool = False

official/core/exp_factory.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/export_base.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/export_base_test.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/file_writers.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

official/core/file_writers_test.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.