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Stop using deprecated enum tf.lite.Optimize.OPTIMIZE_FOR_SIZE and some other clean up

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PiperOrigin-RevId: 313688439
Change-Id: Ice2c0d9aefc57681c20d11dade772251a9eab84e
This commit is contained in:
Khanh LeViet 2020-05-28 17:08:38 -07:00 committed by TensorFlower Gardener
parent 347fe6ece4
commit 5c9dd54540
3 changed files with 20 additions and 54 deletions
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32
tensorflow/lite/g3doc/performance/post_training_float16_quant.ipynb
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@ -61,6 +61,9 @@
" \u003ctd\u003e\n", " \u003ctd\u003e\n",
" \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/performance/post_training_float16_quant.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n", " \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/performance/post_training_float16_quant.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n",
" \u003c/td\u003e\n", " \u003c/td\u003e\n",
" \u003ctd\u003e\n",
" \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/tensorflow/lite/g3doc/performance/post_training_float16_quant.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" "\u003c/table\u003e"
] ]
}, },
@ -113,13 +116,7 @@
"import logging\n", "import logging\n",
"logging.getLogger(\"tensorflow\").setLevel(logging.DEBUG)\n", "logging.getLogger(\"tensorflow\").setLevel(logging.DEBUG)\n",
"\n", "\n",
"try:\n", "import tensorflow as tf\n",
" # %tensorflow_version only exists in Colab.\n",
" import tensorflow.compat.v2 as tf\n",
"except Exception:\n",
" pass\n",
"tf.enable_v2_behavior()\n",
"\n",
"from tensorflow import keras\n", "from tensorflow import keras\n",
"import numpy as np\n", "import numpy as np\n",
"import pathlib" "import pathlib"
@ -173,12 +170,12 @@
" keras.layers.Conv2D(filters=12, kernel_size=(3, 3), activation=tf.nn.relu),\n", " keras.layers.Conv2D(filters=12, kernel_size=(3, 3), activation=tf.nn.relu),\n",
" keras.layers.MaxPooling2D(pool_size=(2, 2)),\n", " keras.layers.MaxPooling2D(pool_size=(2, 2)),\n",
" keras.layers.Flatten(),\n", " keras.layers.Flatten(),\n",
" keras.layers.Dense(10, activation=tf.nn.softmax)\n", " keras.layers.Dense(10)\n",
"])\n", "])\n",
"\n", "\n",
"# Train the digit classification model\n", "# Train the digit classification model\n",
"model.compile(optimizer='adam',\n", "model.compile(optimizer='adam',\n",
" loss='sparse_categorical_crossentropy',\n", " loss=keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n",
" metrics=['accuracy'])\n", " metrics=['accuracy'])\n",
"model.fit(\n", "model.fit(\n",
" train_images,\n", " train_images,\n",
@ -597,28 +594,11 @@
"\n", "\n",
"Detailed documentation on the TFLite GPU delegate and how to use it in your application can be found [here](https://www.tensorflow.org/lite/performance/gpu_advanced?source=post_page---------------------------)" "Detailed documentation on the TFLite GPU delegate and how to use it in your application can be found [here](https://www.tensorflow.org/lite/performance/gpu_advanced?source=post_page---------------------------)"
] ]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"colab": {},
"colab_type": "code",
"id": "BeUSdwKVixvk"
},
"outputs": [],
"source": [
""
]
} }
], ],
"metadata": { "metadata": {
"colab": { "colab": {
"collapsed_sections": [], "collapsed_sections": [],
"last_runtime": {
"build_target": "//learning/brain/python/client:colab_notebook_py3",
"kind": "private"
},
"name": "post_training-float16-quant.ipynb", "name": "post_training-float16-quant.ipynb",
"private_outputs": true, "private_outputs": true,
"provenance": [], "provenance": [],

23
tensorflow/lite/g3doc/performance/post_training_integer_quant.ipynb
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@ -61,6 +61,9 @@
" \u003ctd\u003e\n", " \u003ctd\u003e\n",
" \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/performance/post_training_integer_quant.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n", " \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/performance/post_training_integer_quant.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n",
" \u003c/td\u003e\n", " \u003c/td\u003e\n",
" \u003ctd\u003e\n",
" \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/tensorflow/lite/g3doc/performance/post_training_integer_quant.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" "\u003c/table\u003e"
] ]
}, },
@ -114,13 +117,7 @@
"import logging\n", "import logging\n",
"logging.getLogger(\"tensorflow\").setLevel(logging.DEBUG)\n", "logging.getLogger(\"tensorflow\").setLevel(logging.DEBUG)\n",
"\n", "\n",
"try:\n", "import tensorflow as tf\n",
" # %tensorflow_version only exists in Colab.\n",
" import tensorflow.compat.v2 as tf\n",
"except Exception:\n",
" pass\n",
"tf.enable_v2_behavior()\n",
"\n",
"from tensorflow import keras\n", "from tensorflow import keras\n",
"import numpy as np\n", "import numpy as np\n",
"import pathlib" "import pathlib"
@ -158,15 +155,15 @@
"model = keras.Sequential([\n", "model = keras.Sequential([\n",
" keras.layers.InputLayer(input_shape=(28, 28)),\n", " keras.layers.InputLayer(input_shape=(28, 28)),\n",
" keras.layers.Reshape(target_shape=(28, 28, 1)),\n", " keras.layers.Reshape(target_shape=(28, 28, 1)),\n",
" keras.layers.Conv2D(filters=12, kernel_size=(3, 3), activation=tf.nn.relu),\n", " keras.layers.Conv2D(filters=12, kernel_size=(3, 3), activation='relu'),\n",
" keras.layers.MaxPooling2D(pool_size=(2, 2)),\n", " keras.layers.MaxPooling2D(pool_size=(2, 2)),\n",
" keras.layers.Flatten(),\n", " keras.layers.Flatten(),\n",
" keras.layers.Dense(10, activation=tf.nn.softmax)\n", " keras.layers.Dense(10)\n",
"])\n", "])\n",
"\n", "\n",
"# Train the digit classification model\n", "# Train the digit classification model\n",
"model.compile(optimizer='adam',\n", "model.compile(optimizer='adam',\n",
" loss='sparse_categorical_crossentropy',\n", " loss=keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n",
" metrics=['accuracy'])\n", " metrics=['accuracy'])\n",
"model.fit(\n", "model.fit(\n",
" train_images,\n", " train_images,\n",
@ -277,7 +274,7 @@
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]" "converter.optimizations = [tf.lite.Optimize.DEFAULT]"
] ]
}, },
{ {
@ -655,10 +652,6 @@
"metadata": { "metadata": {
"colab": { "colab": {
"collapsed_sections": [], "collapsed_sections": [],
"last_runtime": {
"build_target": "//learning/brain/python/client:colab_notebook_py3",
"kind": "private"
},
"name": "post_training_integer_quant.ipynb", "name": "post_training_integer_quant.ipynb",
"private_outputs": true, "private_outputs": true,
"provenance": [], "provenance": [],

19
tensorflow/lite/g3doc/performance/post_training_quant.ipynb
View File

@ -61,6 +61,9 @@
" \u003ctd\u003e\n", " \u003ctd\u003e\n",
" \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/performance/post_training_quant.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n", " \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/performance/post_training_quant.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n",
" \u003c/td\u003e\n", " \u003c/td\u003e\n",
" \u003ctd\u003e\n",
" \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/tensorflow/lite/g3doc/performance/post_training_quant.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" "\u003c/table\u003e"
] ]
}, },
@ -134,13 +137,7 @@
"import logging\n", "import logging\n",
"logging.getLogger(\"tensorflow\").setLevel(logging.DEBUG)\n", "logging.getLogger(\"tensorflow\").setLevel(logging.DEBUG)\n",
"\n", "\n",
"try:\n", "import tensorflow as tf\n",
" # %tensorflow_version only exists in Colab.\n",
" import tensorflow.compat.v2 as tf\n",
"except Exception:\n",
" pass\n",
"tf.enable_v2_behavior()\n",
"\n",
"from tensorflow import keras\n", "from tensorflow import keras\n",
"import numpy as np\n", "import numpy as np\n",
"import pathlib" "import pathlib"
@ -181,12 +178,12 @@
" keras.layers.Conv2D(filters=12, kernel_size=(3, 3), activation=tf.nn.relu),\n", " keras.layers.Conv2D(filters=12, kernel_size=(3, 3), activation=tf.nn.relu),\n",
" keras.layers.MaxPooling2D(pool_size=(2, 2)),\n", " keras.layers.MaxPooling2D(pool_size=(2, 2)),\n",
" keras.layers.Flatten(),\n", " keras.layers.Flatten(),\n",
" keras.layers.Dense(10, activation=tf.nn.softmax)\n", " keras.layers.Dense(10)\n",
"])\n", "])\n",
"\n", "\n",
"# Train the digit classification model\n", "# Train the digit classification model\n",
"model.compile(optimizer='adam',\n", "model.compile(optimizer='adam',\n",
" loss='sparse_categorical_crossentropy',\n", " loss=keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n",
" metrics=['accuracy'])\n", " metrics=['accuracy'])\n",
"model.fit(\n", "model.fit(\n",
" train_images,\n", " train_images,\n",
@ -620,10 +617,6 @@
"metadata": { "metadata": {
"colab": { "colab": {
"collapsed_sections": [], "collapsed_sections": [],
"last_runtime": {
"build_target": "//learning/brain/python/client:colab_notebook_py3",
"kind": "private"
},
"name": "post_training_quant.ipynb", "name": "post_training_quant.ipynb",
"private_outputs": true, "private_outputs": true,
"provenance": [], "provenance": [],