updates

app.py

@@ -9,8 +9,8 @@ import tensorflow as tf, tf_keras
 import tensorflow_hub as hub
 from transformers import AutoTokenizer, TFAutoModelForSeq2SeqLM
 
-from modeling.official.projects.movinet.modeling import movinet
-from modeling.official.projects.movinet.modeling import movinet_model_a2_modified as movinet_model_modified
+from official.projects.movinet.modeling import movinet
+from official.projects.movinet.modeling import movinet_model_a2_modified as movinet_model_modified
 
 
 movinet_path = 'modeling/movinet_checkpoints_a2_epoch9'

modeling/official/core/__init__.py

@@ -1,31 +0,0 @@
-# Copyright 2023 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.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Core is shared by both `nlp` and `vision`."""
-
-from modeling.official.core import actions
-from modeling.official.core import base_task
-from modeling.official.core import base_trainer
-from modeling.official.core import config_definitions
-from modeling.official.core import exp_factory
-from modeling.official.core import export_base
-from modeling.official.core import file_writers
-from modeling.official.core import input_reader
-from modeling.official.core import registry
-from modeling.official.core import savedmodel_checkpoint_manager
-from modeling.official.core import task_factory
-from modeling.official.core import tf_example_builder
-from modeling.official.core import tf_example_feature_key
-from modeling.official.core import train_lib
-from modeling.official.core import train_utils

modeling/official/vision/configs/__init__.py

@@ -1,24 +0,0 @@
-# Copyright 2023 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.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Configs package definition."""
-
-from modeling.official.vision.configs import backbones
-from modeling.official.vision.configs import backbones_3d
-from modeling.official.vision.configs import common
-from modeling.official.vision.configs import image_classification
-from modeling.official.vision.configs import maskrcnn
-from modeling.official.vision.configs import retinanet
-from modeling.official.vision.configs import semantic_segmentation
-from modeling.official.vision.configs import video_classification

modeling/tensorflow_models/nlp/__init__.py

@@ -1,20 +0,0 @@
-# Copyright 2023 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.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""TensorFlow Models NLP Libraries."""
-
-from official.nlp import tasks
-from official.nlp.configs import encoders
-from official.nlp.modeling import *
-from official.nlp.serving import serving_modules

modeling/tensorflow_models/tensorflow_models_pypi.ipynb

@@ -1,339 +0,0 @@
-{
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "bK-7g5sizhg5"
-      },
-      "source": [
-        "## Install Tensorflow-Models packages\n",
-        "\n",
-        "The notebook is tested with Google Colab sandbox.\n",
-        "\n"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "executionInfo": {
-          "elapsed": 9737,
-          "status": "ok",
-          "timestamp": 1650513863935,
-          "user": {
-            "displayName": "Hongkun Yu",
-            "userId": "12855578661733349593"
-          },
-          "user_tz": 420
-        },
-        "id": "eTz93_P2dMty",
-        "outputId": "d147b4b0-954f-4064-d179-bb82bc3ea4fe"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "\u001b[K     |████████████████████████████████| 21.8 MB 1.6 MB/s \n",
-            "\u001b[?25h"
-          ]
-        }
-      ],
-      "source": [
-        "!pip3 install -q tf-models-nightly\n",
-        "# Fix Colab default opencv problem\n",
-        "!pip3 install -q opencv-python-headless==4.1.2.30\n",
-        "\n",
-        "## Colab environment setup. To use a stable TF release version\n",
-        "##  because of the possible breakage in tf-nightly.\n",
-        "# !pip3 install -U numpy\u003e=1.20\n",
-        "# !pip3 install -q tensorflow==2.8.0"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "executionInfo": {
-          "elapsed": 2,
-          "status": "ok",
-          "timestamp": 1650513867685,
-          "user": {
-            "displayName": "Hongkun Yu",
-            "userId": "12855578661733349593"
-          },
-          "user_tz": 420
-        },
-        "id": "GHvGWdCcdQqG",
-        "outputId": "863683b2-6b70-4de9-98bc-5df743619ad5"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "1.21.6\n",
-            "2.10.0-dev20220420\n"
-          ]
-        }
-      ],
-      "source": [
-        "import numpy as np\n",
-        "import tensorflow as tf\n",
-        "print(np.__version__)\n",
-        "print(tf.__version__)\n",
-        "\n",
-        "import tensorflow_models as tfm"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "eYSeQJniztc8"
-      },
-      "source": [
-        "## Check out modules\n",
-        "\n",
-        "**Note: As the TensorFlow Models (NLP + Vision) 2.9 release which is tested for this notebook, we partially exported selected modules but the APIs are not stable. Also be aware that, the\n",
-        "modeling libraries are advancing very fast, so we generally don't guarantee compatability between versions.** "
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "executionInfo": {
-          "elapsed": 206,
-          "status": "ok",
-          "timestamp": 1650513874596,
-          "user": {
-            "displayName": "Hongkun Yu",
-            "userId": "12855578661733349593"
-          },
-          "user_tz": 420
-        },
-        "id": "Y1iEMMGTMrQu",
-        "outputId": "f3da68d7-ecda-471c-c27b-915b80b55131"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Top-level modules:  ['__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__spec__', 'core', 'hyperparams', 'nlp', 'optimization', 'utils', 'vision']\n",
-            "NLP modules:  ['__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__spec__', 'encoders', 'layers', 'losses', 'models', 'networks', 'ops', 'serving_modules', 'tasks']\n",
-            "Vision modules:  ['__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__spec__', 'anchor', 'anchor_generator', 'augment', 'backbones', 'box_matcher', 'box_ops', 'classification_model', 'configs', 'decoders', 'factory', 'factory_3d', 'heads', 'iou_similarity', 'layers', 'mask_ops', 'maskrcnn_model', 'nms', 'preprocess_ops', 'preprocess_ops_3d', 'retinanet_model', 'sampling_ops', 'segmentation_model', 'spatial_transform_ops', 'target_gather', 'video_classification_model']\n"
-          ]
-        }
-      ],
-      "source": [
-        "print(\"Top-level modules: \", dir(tfm))\n",
-        "print(\"NLP modules: \", dir(tfm.nlp))\n",
-        "print(\"Vision modules: \", dir(tfm.vision))"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "UMHeJmk_1yUf"
-      },
-      "source": [
-        "## Quick Examples\n",
-        "\n",
-        "### 1. Use a tfm.nlp Keras layer"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "executionInfo": {
-          "elapsed": 400,
-          "status": "ok",
-          "timestamp": 1650514040957,
-          "user": {
-            "displayName": "Hongkun Yu",
-            "userId": "12855578661733349593"
-          },
-          "user_tz": 420
-        },
-        "id": "XVWEUozQ1xQY",
-        "outputId": "5de2aa91-8c38-438e-80b6-481617917c08"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "transformer_encoder_block_1\n",
-            "tf.Tensor(\n",
-            "[[[-1.063648    1.4375787  -0.79198956  0.4180589 ]\n",
-            "  [-1.063648    1.4375787  -0.79198956  0.4180589 ]\n",
-            "  [-1.063648    1.4375787  -0.79198956  0.4180589 ]]\n",
-            "\n",
-            " [[-1.063648    1.4375787  -0.79198956  0.4180589 ]\n",
-            "  [-1.063648    1.4375787  -0.79198956  0.4180589 ]\n",
-            "  [-1.063648    1.4375787  -0.7919895   0.41805887]]], shape=(2, 3, 4), dtype=float32)\n"
-          ]
-        }
-      ],
-      "source": [
-        "encoder_block = tfm.nlp.layers.TransformerEncoderBlock(\n",
-        "        num_attention_heads=2, inner_dim=10, inner_activation='relu')\n",
-        "\n",
-        "batch, length, hidden_size = 2, 3, 4\n",
-        "qkv_inputs = tf.ones((batch, length, hidden_size), tf.float32)\n",
-        "attention_mask = None\n",
-        "outputs = encoder_block([qkv_inputs, attention_mask])\n",
-        "print(encoder_block.name)\n",
-        "print(outputs)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "AOOrWjKkSYM0"
-      },
-      "source": [
-        "### 2. Use a tfm.vision Backbone models"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "executionInfo": {
-          "elapsed": 5979,
-          "status": "ok",
-          "timestamp": 1650514078414,
-          "user": {
-            "displayName": "Hongkun Yu",
-            "userId": "12855578661733349593"
-          },
-          "user_tz": 420
-        },
-        "id": "xwD0UhUdSzNU",
-        "outputId": "770d46c0-8c71-4f59-ee0b-67430c791380"
-      },
-      "outputs": [
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "WARNING:absl:SpineNet output level out of range [min_level, max_level] = [4, 6] will not be used for further processing.\n",
-            "WARNING:absl:SpineNet output level out of range [min_level, max_level] = [4, 6] will not be used for further processing.\n",
-            "WARNING:absl:SpineNet output level out of range [min_level, max_level] = [4, 6] will not be used for further processing.\n"
-          ]
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "spine_net\n",
-            "{'4': \u003cKerasTensor: shape=(1, 8, 8, 128) dtype=float32 (created by layer 'spine_net')\u003e, '5': \u003cKerasTensor: shape=(1, 4, 4, 128) dtype=float32 (created by layer 'spine_net')\u003e, '6': \u003cKerasTensor: shape=(1, 2, 2, 128) dtype=float32 (created by layer 'spine_net')\u003e}\n"
-          ]
-        }
-      ],
-      "source": [
-        "input_size = 128\n",
-        "filter_size_scale, block_repeats, resample_alpha, endpoints_num_filters, min_level, max_level = 0.65, 1, 0.5, 128, 4, 6\n",
-        "input_specs = tf.keras.layers.InputSpec(\n",
-        "    shape=[None, input_size, input_size, 3])\n",
-        "model = tfm.vision.backbones.SpineNet(\n",
-        "    input_specs=input_specs,\n",
-        "    min_level=min_level,\n",
-        "    max_level=max_level,\n",
-        "    endpoints_num_filters=endpoints_num_filters,\n",
-        "    resample_alpha=resample_alpha,\n",
-        "    block_repeats=block_repeats,\n",
-        "    filter_size_scale=filter_size_scale,\n",
-        "    init_stochastic_depth_rate=0.2,\n",
-        ")\n",
-        "\n",
-        "inputs = tf.keras.Input(shape=(input_size, input_size, 3), batch_size=1)\n",
-        "endpoints = model(inputs)\n",
-        "print(model.name)\n",
-        "print(endpoints)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "HHJs4lRlTk8q"
-      },
-      "source": [
-        "### 3. Use Orbit package for advanced training loops"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "executionInfo": {
-          "elapsed": 215,
-          "status": "ok",
-          "timestamp": 1650514185283,
-          "user": {
-            "displayName": "Hongkun Yu",
-            "userId": "12855578661733349593"
-          },
-          "user_tz": 420
-        },
-        "id": "X4ek9IrJTkP_",
-        "outputId": "7b31de68-53a0-4b8a-d9ab-109e7c43c933"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Orbit modules:  ['AbstractEvaluator', 'AbstractTrainer', 'Action', 'Controller', 'StandardEvaluator', 'StandardEvaluatorOptions', 'StandardTrainer', 'StandardTrainerOptions', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__spec__', 'actions', 'controller', 'runner', 'standard_runner', 'utils']\n"
-          ]
-        }
-      ],
-      "source": [
-        "import orbit\n",
-        "print(\"Orbit modules: \", dir(orbit))"
-      ]
-    }
-  ],
-  "metadata": {
-    "colab": {
-      "collapsed_sections": [],
-      "name": "tensorflow_models_pypi",
-      "provenance": [
-        {
-          "file_id": "1dm1dUZ2Bo6S6Zom7GTQrIG78Xz7iFeZY",
-          "timestamp": 1650514452505
-        }
-      ]
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
-  "nbformat": 4,
-  "nbformat_minor": 0
-}

modeling/tensorflow_models/tensorflow_models_test.py

@@ -1,40 +0,0 @@
-# Copyright 2023 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.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Tests for tensorflow_models imports."""
-
-import tensorflow as tf, tf_keras
-import tensorflow_models as tfm
-
-
-class TensorflowModelsTest(tf.test.TestCase):
-
-  def testVisionImport(self):
-    _ = tfm.vision.layers.SqueezeExcitation(
-        in_filters=8, out_filters=4, se_ratio=1)
-    _ = tfm.vision.configs.image_classification.Losses()
-
-  def testNLPImport(self):
-    _ = tfm.nlp.layers.TransformerEncoderBlock(
-        num_attention_heads=2, inner_dim=10, inner_activation='relu')
-    _ = tfm.nlp.tasks.TaggingTask(params=tfm.nlp.tasks.TaggingConfig())
-
-  def testCommonImports(self):
-    _ = tfm.hyperparams.Config()
-    _ = tfm.optimization.LinearWarmup(
-        after_warmup_lr_sched=0.0, warmup_steps=10, warmup_learning_rate=0.1)
-
-
-if __name__ == '__main__':
-  tf.test.main()

{modeling/tensorflow_models → official/core}/__init__.py

@@ -12,12 +12,20 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-"""TensorFlow Models Libraries."""
-# pylint: disable=wildcard-import
-from tensorflow_models import nlp
-from tensorflow_models import vision
+"""Core is shared by both `nlp` and `vision`."""
 
-from official import core
-from official.modeling import hyperparams
-from official.modeling import optimization
-from official.modeling import tf_utils as utils
+from official.core import actions
+from official.core import base_task
+from official.core import base_trainer
+from official.core import config_definitions
+from official.core import exp_factory
+from official.core import export_base
+from official.core import file_writers
+from official.core import input_reader
+from official.core import registry
+from official.core import savedmodel_checkpoint_manager
+from official.core import task_factory
+from official.core import tf_example_builder
+from official.core import tf_example_feature_key
+from official.core import train_lib
+from official.core import train_utils

{modeling/official → official}/core/actions.py

@@ -19,12 +19,12 @@ from typing import List
 from absl import logging
 
 import gin
-import modeling.orbit
+import orbit
 import tensorflow as tf, tf_keras
 
-from modeling.official.core import base_trainer
-from modeling.official.core import config_definitions
-from modeling.official.modeling import optimization
+from official.core import base_trainer
+from official.core import config_definitions
+from official.modeling import optimization
 
 
 class PruningAction:

{modeling/official → official}/core/base_task.py

@@ -20,11 +20,11 @@ from typing import Optional
 from absl import logging
 import tensorflow as tf, tf_keras
 
-from modeling.official.core import config_definitions
-from modeling.official.modeling import optimization
-from modeling.official.modeling import performance
-from modeling.official.modeling.privacy import configs
-from modeling.official.modeling.privacy import ops
+from official.core import config_definitions
+from official.modeling import optimization
+from official.modeling import performance
+from official.modeling.privacy import configs
+from official.modeling.privacy import ops
 
 OptimizationConfig = optimization.OptimizationConfig
 RuntimeConfig = config_definitions.RuntimeConfig

{modeling/official → official}/core/base_trainer.py

@@ -22,12 +22,12 @@ import functools
 from typing import Union, Optional
 from absl import logging
 import gin
-import modeling.orbit as orbit
+import orbit
 import tensorflow as tf, tf_keras
 
-from modeling.official.core import base_task
-from modeling.official.core import config_definitions
-from modeling.official.modeling import optimization
+from official.core import base_task
+from official.core import config_definitions
+from official.modeling import optimization
 
 ExperimentConfig = config_definitions.ExperimentConfig
 TrainerConfig = config_definitions.TrainerConfig

{modeling/official → official}/core/config_definitions.py

@@ -17,9 +17,9 @@
 import dataclasses
 from typing import Optional, Sequence, Union
 
-from modeling.official.modeling.hyperparams import base_config
-from modeling.official.modeling.optimization.configs import optimization_config
-from modeling.official.modeling.privacy import configs as dp_configs
+from official.modeling.hyperparams import base_config
+from official.modeling.optimization.configs import optimization_config
+from official.modeling.privacy import configs as dp_configs
 
 OptimizationConfig = optimization_config.OptimizationConfig
 

{modeling/official → official}/core/exp_factory.py

@@ -14,8 +14,8 @@
 
 """Experiment factory methods."""
 
-from modeling.official.core import config_definitions as cfg
-from modeling.official.core import registry
+from official.core import config_definitions as cfg
+from official.core import registry
 
 
 _REGISTERED_CONFIGS = {}

{modeling/official → official}/core/export_base_test.py

@@ -18,7 +18,7 @@ from typing import Any, Dict, Mapping, Text
 
 import tensorflow as tf, tf_keras
 
-from modeling.official.core import export_base
+from official.core import export_base
 
 
 class TestModule(export_base.ExportModule):

{modeling/official → official}/core/input_reader.py

@@ -21,7 +21,7 @@ from absl import logging
 import tensorflow as tf, tf_keras
 import tensorflow_datasets as tfds
 
-from modeling.official.core import config_definitions as cfg
+from official.core import config_definitions as cfg
 
 
 def _get_random_integer():

{modeling/official → official}/core/task_factory.py

@@ -14,7 +14,7 @@
 
 """A global factory to register and access all registered tasks."""
 
-from modeling.official.core import registry
+from official.core import registry
 
 _REGISTERED_TASK_CLS = {}
 

{modeling/official → official}/core/train_lib.py

@@ -21,14 +21,14 @@ from typing import Any, List, Mapping, Optional, Tuple
 # Import libraries
 
 from absl import logging
-import modeling.orbit
+import orbit
 import tensorflow as tf, tf_keras
 
-from modeling.official.core import actions
-from modeling.official.core import base_task
-from modeling.official.core import base_trainer
-from modeling.official.core import config_definitions
-from modeling.official.core import train_utils
+from official.core import actions
+from official.core import base_task
+from official.core import base_trainer
+from official.core import config_definitions
+from official.core import train_utils
 
 maybe_create_best_ckpt_exporter = train_utils.maybe_create_best_ckpt_exporter
 

{modeling/official → official}/core/train_utils.py

@@ -24,18 +24,18 @@ from typing import Any, Callable, Dict, List, Optional, Union
 from absl import logging
 import gin
 import numpy as np
-import modeling.orbit
+import orbit
 import tensorflow as tf, tf_keras
 
 # pylint: disable=g-direct-tensorflow-import
 from tensorflow.python.framework import ops
 from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2_as_graph
 # pylint: enable=g-direct-tensorflow-import
-from modeling.official.core import base_task
-from modeling.official.core import base_trainer
-from modeling.official.core import config_definitions
-from modeling.official.core import exp_factory
-from modeling.official.modeling import hyperparams
+from official.core import base_task
+from official.core import base_trainer
+from official.core import config_definitions
+from official.core import exp_factory
+from official.modeling import hyperparams
 
 
 BEST_CHECKPOINT_NAME = 'best_ckpt'