add clear memory note
This commit is contained in:
YanZhangADS
Родитель
e6ee0baa69
Коммит
6c362caa8a
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@ -252,25 +252,25 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(True, 'model_version', '2')"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"model_version = str(model.version)\n",
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"set_key(env_path, \"model_version\", model_version)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Clear GPU memory\n",
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"from keras import backend as K\n",
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"K.clear_session()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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@ -11,7 +11,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -19,25 +19,40 @@
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"from azureml.core.compute import AksCompute, ComputeTarget\n",
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"from azureml.core.webservice import Webservice, AksWebservice\n",
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"from azureml.core.image import Image\n",
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"from azureml.core.model import Model"
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"from azureml.core.model import Model\n",
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"from dotenv import set_key, get_key, find_dotenv\n",
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"import logging\n",
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"from testing_utilities import img_url_to_json"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.1.74\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import azureml.core\n",
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"print(azureml.core.VERSION)"
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"import keras\n",
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"import tensorflow\n",
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"print(\"Keras: \", keras.__version__)\n",
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"print(\"Tensorflow: \", tensorflow.__version__)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"env_path = find_dotenv(raise_error_if_not_found=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"_MODEL_NAME = get_key(env_path, 'model_name')"
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]
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},
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{
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@ -49,86 +64,112 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Writing driver.py\n"
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]
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}
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],
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"source": [
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"%%writefile driver.py\n",
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"def init():\n",
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" import tensorflow as tf\n",
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" from resnet152 import ResNet152\n",
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" from keras.preprocessing import image\n",
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" from keras.applications.imagenet_utils import preprocess_input, decode_predictions\n",
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"\n",
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" import numpy as np\n",
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" import timeit as t\n",
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" import base64\n",
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" import json\n",
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" from PIL import Image, ImageOps\n",
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" from io import BytesIO\n",
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" import logging\n",
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"\n",
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" global model\n",
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" model = ResNet152(weights='imagenet')\n",
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" print('Model loaded')\n",
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" \n",
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"def run(inputString):\n",
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" \n",
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" import tensorflow as tf\n",
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" from resnet152 import ResNet152\n",
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" from keras.preprocessing import image\n",
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" from keras.applications.imagenet_utils import preprocess_input, decode_predictions\n",
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"\n",
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" import numpy as np\n",
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" import timeit as t\n",
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" import base64\n",
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" import json\n",
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" from PIL import Image, ImageOps\n",
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" from io import BytesIO\n",
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" import logging \n",
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" \n",
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" model = ResNet152(weights='imagenet')\n",
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" print('Model loaded')\n",
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" \n",
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" responses = []\n",
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" base64Dict = json.loads(inputString)\n",
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"\n",
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" for k, v in base64Dict.items():\n",
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" img_file_name, base64Img = k, v\n",
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" decoded_img = base64.b64decode(base64Img)\n",
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" img_buffer = BytesIO(decoded_img)\n",
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" imageData = Image.open(img_buffer).convert(\"RGB\")\n",
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" \n",
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" # Evaluate the model using the input data\n",
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" img = ImageOps.fit(imageData, (224,224), Image.ANTIALIAS)\n",
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" img = np.array(img) # shape: (224, 224, 3)\n",
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" \n",
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" img = np.expand_dims(img, axis=0)\n",
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" img = preprocess_input(img)\n",
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" \n",
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" preds = model.predict(img)\n",
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" print('Predicted:', decode_predictions(preds, top=3))\n",
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" resp = {img_file_name: str(decode_predictions(preds, top=3))}\n",
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"\n",
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" responses.append(resp)\n",
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" return json.dumps(responses) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%run driver.py"
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"%%writefile driver.py\n",
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"\n",
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"import tensorflow as tf\n",
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"from resnet152 import ResNet152\n",
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"from keras.preprocessing import image\n",
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"from keras.applications.imagenet_utils import preprocess_input, decode_predictions\n",
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"\n",
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"from azureml.core.model import Model\n",
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"\n",
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"import numpy as np\n",
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"import timeit as t\n",
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"import base64\n",
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"import json\n",
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"from PIL import Image, ImageOps\n",
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"from io import BytesIO\n",
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"import logging\n",
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"\n",
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"number_results = 3\n",
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"logger = logging.getLogger(\"model_driver\")\n",
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"\n",
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"def _base64img_to_numpy(base64_img_string):\n",
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" decoded_img = base64.b64decode(base64_img_string)\n",
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" img_buffer = BytesIO(decoded_img)\n",
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" imageData = Image.open(img_buffer).convert(\"RGB\")\n",
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" img = ImageOps.fit(imageData, (224, 224), Image.ANTIALIAS)\n",
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" img = image.img_to_array(img)\n",
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" return img\n",
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"\n",
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"def create_scoring_func():\n",
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" \"\"\" Initialize ResNet 152 Model \n",
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" \"\"\" \n",
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" start = t.default_timer()\n",
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" # model = ResNet152(weights='imagenet')\n",
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" model_name = 'resnet_model'\n",
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" model_path=Model.get_model_path(model_name)\n",
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" model = ResNet152()\n",
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" model.load_weights(model_path)\n",
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" end = t.default_timer()\n",
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" \n",
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" loadTimeMsg = \"Model loading time: {0} ms\".format(round((end-start)*1000, 2))\n",
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" logger.info(loadTimeMsg)\n",
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" \n",
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" def call_model(img_array):\n",
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" img_array = np.expand_dims(img_array, axis=0)\n",
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" img_array = preprocess_input(img_array)\n",
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" preds = model.predict(img_array)\n",
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" preds = decode_predictions(preds, top=number_results)[0] \n",
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" return preds\n",
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" \n",
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" return call_model \n",
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"\n",
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"\n",
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"def tuple_float_to_str(x):\n",
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" \"\"\"tuple x = ('n02127052', 'lynx', 0.9816483) convert the 3rd element type numpy.float32 to string\n",
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" return: ('n02127052', 'lynx', '0.9816483')\n",
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" \"\"\"\n",
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" a= list(x)\n",
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" a[2]= str(a[2])\n",
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" b= tuple(a)\n",
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" return b\n",
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" \n",
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"def get_model_api():\n",
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" logger = logging.getLogger(\"model_driver\")\n",
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" scoring_func = create_scoring_func()\n",
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" \n",
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" def process_and_score(inputString):\n",
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" \"\"\" Classify the input using the loaded model\n",
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" \"\"\"\n",
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" start = t.default_timer()\n",
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"\n",
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" base64Dict = json.loads(inputString) \n",
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" for k, v in base64Dict.items():\n",
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" img_file_name, base64Img = k, v \n",
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" img_array = _base64img_to_numpy(base64Img)\n",
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" preds = scoring_func(img_array)\n",
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" \n",
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" # convert the 3rd element type of preds items from numpy.float32 to string\n",
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" for i, s in enumerate(preds):\n",
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" preds[i] = tuple_float_to_str(s)\n",
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"\n",
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" responses = {img_file_name: preds}\n",
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" \n",
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" end = t.default_timer()\n",
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" \n",
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" logger.info(\"Predictions: {0}\".format(responses))\n",
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" logger.info(\"Predictions took {0} ms\".format(round((end-start)*1000, 2)))\n",
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" return (responses, \"Computed in {0} ms\".format(round((end-start)*1000, 2)))\n",
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" return process_and_score\n",
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"\n",
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"def version():\n",
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" return tf.__version__\n",
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"\n",
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"def init():\n",
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" \"\"\" Initialise the model and scoring function\n",
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" \"\"\"\n",
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" global process_and_score\n",
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" process_and_score = get_model_api()\n",
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" \n",
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"def run(raw_data):\n",
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" \"\"\" Make a prediction based on the data passed in using the preloaded model\n",
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" \"\"\"\n",
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" return process_and_score(json.dumps(json.loads(raw_data)['input']))"
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]
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},
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{
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@ -141,41 +182,93 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Using TensorFlow backend.\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Model loaded\n",
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"Predicted: [[('n02127052', 'lynx', 0.9816487), ('n02128385', 'leopard', 0.007744099), ('n02123159', 'tiger_cat', 0.0036861112)]]\n",
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"[{\"220px-Lynx_lynx_poing.jpg\": \"[[('n02127052', 'lynx', 0.9816487), ('n02128385', 'leopard', 0.007744099), ('n02123159', 'tiger_cat', 0.0036861112)]]\"}]\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"from io import BytesIO\n",
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"from PIL import Image, ImageOps\n",
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"import base64\n",
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"import json\n",
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"\n",
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"img_path = '220px-Lynx_lynx_poing.jpg'\n",
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"encoded = None\n",
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"with open(img_path, 'rb') as file:\n",
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" encoded = base64.b64encode(file.read())\n",
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"img_dict = {img_path: encoded.decode('utf-8')}\n",
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"body = json.dumps(img_dict)\n",
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"\n",
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"resp = run(body)\n",
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"print(resp)"
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"logging.basicConfig(level=logging.DEBUG)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%run driver.py"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's load the workspace."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"ws = Workspace.from_config()\n",
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"print(ws.name, ws.resource_group, ws.location, ws.subscription_id, sep=\"\\n\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"model_path = Model.get_model_path(_MODEL_NAME, _workspace=ws)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"IMAGEURL = \"https://upload.wikimedia.org/wikipedia/commons/thumb/6/68/Lynx_lynx_poing.jpg/220px-Lynx_lynx_poing.jpg\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Always make sure you don't have any lingering notebooks running.\n",
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"init()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"jsonimg = img_url_to_json(IMAGEURL)\n",
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"resp = run(jsonimg)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Clear GPU memory\n",
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"from keras import backend as K\n",
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"K.clear_session()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Next, we will [build a docker image with this modle driver and other supporting files](03__BuildImage.ipynb)."
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]
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}
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],
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@ -195,7 +288,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.6"
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"version": "3.6.7"
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}
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},
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"nbformat": 4,
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@ -252,25 +252,25 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
|
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"(True, 'model_version', '2')"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
|
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"model_version = str(model.version)\n",
|
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"set_key(env_path, \"model_version\", model_version)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Clear GPU memory\n",
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"from keras import backend as K\n",
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"K.clear_session()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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|
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@ -11,7 +11,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -27,25 +27,9 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Using TensorFlow backend.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Keras: 2.2.0\n",
|
||||
"Tensorflow: 1.10.0\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import keras\n",
|
||||
"import tensorflow\n",
|
||||
|
|
@ -55,47 +39,20 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"env_path = find_dotenv(raise_error_if_not_found=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Let's load the workspace."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"_MODEL_NAME = 'resnet_model'"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'model_resnet_weights.h5'"
|
||||
]
|
||||
},
|
||||
"execution_count": 13,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"model_path"
|
||||
"_MODEL_NAME = get_key(env_path, 'model_name')"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -105,246 +62,11 @@
|
|||
"## Write and save driver script"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import tensorflow as tf\n",
|
||||
"from resnet152 import ResNet152\n",
|
||||
"from keras.preprocessing import image\n",
|
||||
"from keras.applications.imagenet_utils import preprocess_input, decode_predictions\n",
|
||||
"\n",
|
||||
"from azureml.core.model import Model\n",
|
||||
"\n",
|
||||
"import numpy as np\n",
|
||||
"import timeit as t\n",
|
||||
"import base64\n",
|
||||
"import json\n",
|
||||
"from PIL import Image, ImageOps\n",
|
||||
"from io import BytesIO\n",
|
||||
"\n",
|
||||
"def _base64img_to_numpy(base64_img_string):\n",
|
||||
" decoded_img = base64.b64decode(base64_img_string)\n",
|
||||
" img_buffer = BytesIO(decoded_img)\n",
|
||||
" imageData = Image.open(img_buffer).convert(\"RGB\")\n",
|
||||
" img = ImageOps.fit(imageData, (224, 224), Image.ANTIALIAS)\n",
|
||||
" img = image.img_to_array(img)\n",
|
||||
" return img\n",
|
||||
"\n",
|
||||
"def call_model(img_array, model, number_results):\n",
|
||||
" img_array = np.expand_dims(img_array, axis=0)\n",
|
||||
" img_array = preprocess_input(img_array)\n",
|
||||
" preds = model.predict(img_array)\n",
|
||||
" preds = decode_predictions(preds, top=number_results)[0] \n",
|
||||
" return preds\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"model = ResNet152(weights='imagenet')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 99,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"check 1.....\n",
|
||||
"<class 'list'>\n",
|
||||
"[('n02127052', 'lynx', 0.9816483), ('n02128385', 'leopard', 0.0077441484), ('n02123159', 'tiger_cat', 0.003686138)]\n",
|
||||
"check 2 ....\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"IMAGEURL = \"https://upload.wikimedia.org/wikipedia/commons/thumb/6/68/Lynx_lynx_poing.jpg/220px-Lynx_lynx_poing.jpg\"\n",
|
||||
"jsonimg = img_url_to_json(IMAGEURL)\n",
|
||||
"inputString = json.dumps(json.loads(jsonimg)['input'])\n",
|
||||
"\n",
|
||||
"base64Dict = json.loads(inputString) \n",
|
||||
"for k, v in base64Dict.items():\n",
|
||||
" img_file_name, base64Img = k, v \n",
|
||||
"img_array = _base64img_to_numpy(base64Img)\n",
|
||||
"\n",
|
||||
"preds = call_model(img_array, model,3)\n",
|
||||
"print(\"check 1.....\")\n",
|
||||
"print(type(preds))\n",
|
||||
"print(preds)\n",
|
||||
"print(\"check 2 ....\")\n",
|
||||
"responses = {img_file_name: preds}"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 20,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"numpy.float32"
|
||||
]
|
||||
},
|
||||
"execution_count": 20,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"type(preds[0][2])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 100,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[('n02127052', 'lynx', 0.9816483),\n",
|
||||
" ('n02128385', 'leopard', 0.0077441484),\n",
|
||||
" ('n02123159', 'tiger_cat', 0.003686138)]"
|
||||
]
|
||||
},
|
||||
"execution_count": 100,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"preds"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 77,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def tuple_float_to_str(x):\n",
|
||||
" a= list(x)\n",
|
||||
" a[2]= str(a[2])\n",
|
||||
" b= tuple(a)\n",
|
||||
" return b"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 82,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"<class 'str'>\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"n=preds[0]\n",
|
||||
"m = tuple_float_to_str(n)\n",
|
||||
"print(type(m[1]))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 101,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"[('n02127052', 'lynx', '0.9816483'), ('n02128385', 'leopard', '0.0077441484'), ('n02123159', 'tiger_cat', '0.003686138')]\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"a = preds\n",
|
||||
"for i, s in enumerate(a):\n",
|
||||
" a[i] = tuple_float_to_str(s)\n",
|
||||
"print(a)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 98,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"str"
|
||||
]
|
||||
},
|
||||
"execution_count": 98,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"type(a[0][2])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 37,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"preds_str = list(map(str, [x[0:3] for x in preds]))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 38,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[\"('n02127052', 'lynx', 0.9816483)\",\n",
|
||||
" \"('n02128385', 'leopard', 0.0077441484)\",\n",
|
||||
" \"('n02123159', 'tiger_cat', 0.003686138)\"]"
|
||||
]
|
||||
},
|
||||
"execution_count": 38,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"preds_str"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 102,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Overwriting driver.py\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"%%writefile driver.py\n",
|
||||
"\n",
|
||||
|
|
@ -460,7 +182,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -469,7 +191,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -477,98 +199,17 @@
|
|||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"DEBUG:cli.azure.cli.core:Current cloud config:\n",
|
||||
"AzureCloud\n",
|
||||
"DEBUG:cli.azure.cli.core.util:attempting to read file /home/mylogin/.azure/accessTokens.json as utf-8-sig\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - Authority:Performing instance discovery: ...\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - Authority:Performing static instance discovery\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - Authority:Authority validated via static instance discovery\n",
|
||||
"INFO:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - TokenRequest:Getting token from cache with refresh if necessary.\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:finding with query keys: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Looking for potential cache entries: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Found 2 potential entries.\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Resource specific token found.\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Returning token from cache lookup, AccessTokenId: b'5Yp4aePv8wlOdT3DbuKlW6SWQkAdmB3i9YfdmTGXeZ8=', RefreshTokenId: b'8PFNusPOpR1LtpwD1CELDvT/Bphd26EJmfdAfj3G0Es='\n",
|
||||
"INFO:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Cached token is expired at 2018-12-18 17:31:28.243609. Refreshing\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - TokenRequest:called to refresh a token from the cache\n",
|
||||
"INFO:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - TokenRequest:Getting a new token from a refresh token\n",
|
||||
"DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): login.microsoftonline.com:443\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Found the config file in: /data/home/mylogin/notebooks/yanzrepo/DistributedDeepLearning/AKSDeploymentTutorial_AML/Keras_Tensorflow/aml_config/config.json\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"DEBUG:urllib3.connectionpool:https://login.microsoftonline.com:443 \"POST /72f988bf-86f1-41af-91ab-2d7cd011db47/oauth2/token HTTP/1.1\" 200 3304\n",
|
||||
"INFO:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - OAuth2Client:Get Token Server returned this correlation_id: 3e1f8a29-74f5-43f5-babe-db772eee2262\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Created new cache entry from refresh response.\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Removing entry.\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Adding entry AccessTokenId: b'4++Ojr5UOlnb/W1BfAzN6wNgMlDh4UpGKDzSwPkXnqM=', RefreshTokenId: b'y85yfXPddjM3gdr367feA0PQgfQvBbm8b+sK2JQYpsI='\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Updating 1 cached refresh tokens\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Remove many: 1\n",
|
||||
"DEBUG:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Add many: 1\n",
|
||||
"INFO:adal-python:3e1f8a29-74f5-43f5-babe-db772eee2262 - CacheDriver:Returning token refreshed after expiry.\n",
|
||||
"DEBUG:cli.azure.cli.core:Current cloud config:\n",
|
||||
"AzureCloud\n",
|
||||
"DEBUG:cli.azure.cli.core:Current cloud config:\n",
|
||||
"AzureCloud\n",
|
||||
"DEBUG:adal-python:9569e5f8-01af-45f3-8d37-f00532fa3ceb - Authority:Performing instance discovery: ...\n",
|
||||
"DEBUG:adal-python:9569e5f8-01af-45f3-8d37-f00532fa3ceb - Authority:Performing static instance discovery\n",
|
||||
"DEBUG:adal-python:9569e5f8-01af-45f3-8d37-f00532fa3ceb - Authority:Authority validated via static instance discovery\n",
|
||||
"INFO:adal-python:9569e5f8-01af-45f3-8d37-f00532fa3ceb - TokenRequest:Getting token from cache with refresh if necessary.\n",
|
||||
"DEBUG:adal-python:9569e5f8-01af-45f3-8d37-f00532fa3ceb - CacheDriver:finding with query keys: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:9569e5f8-01af-45f3-8d37-f00532fa3ceb - CacheDriver:Looking for potential cache entries: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:9569e5f8-01af-45f3-8d37-f00532fa3ceb - CacheDriver:Found 2 potential entries.\n",
|
||||
"DEBUG:adal-python:9569e5f8-01af-45f3-8d37-f00532fa3ceb - CacheDriver:Resource specific token found.\n",
|
||||
"DEBUG:adal-python:9569e5f8-01af-45f3-8d37-f00532fa3ceb - CacheDriver:Returning token from cache lookup, AccessTokenId: b'4++Ojr5UOlnb/W1BfAzN6wNgMlDh4UpGKDzSwPkXnqM=', RefreshTokenId: b'y85yfXPddjM3gdr367feA0PQgfQvBbm8b+sK2JQYpsI='\n",
|
||||
"DEBUG:cli.azure.cli.core:Current cloud config:\n",
|
||||
"AzureCloud\n",
|
||||
"DEBUG:adal-python:7227a363-36ec-4dba-b593-5b9c348f08b0 - Authority:Performing instance discovery: ...\n",
|
||||
"DEBUG:adal-python:7227a363-36ec-4dba-b593-5b9c348f08b0 - Authority:Performing static instance discovery\n",
|
||||
"DEBUG:adal-python:7227a363-36ec-4dba-b593-5b9c348f08b0 - Authority:Authority validated via static instance discovery\n",
|
||||
"INFO:adal-python:7227a363-36ec-4dba-b593-5b9c348f08b0 - TokenRequest:Getting token from cache with refresh if necessary.\n",
|
||||
"DEBUG:adal-python:7227a363-36ec-4dba-b593-5b9c348f08b0 - CacheDriver:finding with query keys: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:7227a363-36ec-4dba-b593-5b9c348f08b0 - CacheDriver:Looking for potential cache entries: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:7227a363-36ec-4dba-b593-5b9c348f08b0 - CacheDriver:Found 2 potential entries.\n",
|
||||
"DEBUG:adal-python:7227a363-36ec-4dba-b593-5b9c348f08b0 - CacheDriver:Resource specific token found.\n",
|
||||
"DEBUG:adal-python:7227a363-36ec-4dba-b593-5b9c348f08b0 - CacheDriver:Returning token from cache lookup, AccessTokenId: b'4++Ojr5UOlnb/W1BfAzN6wNgMlDh4UpGKDzSwPkXnqM=', RefreshTokenId: b'y85yfXPddjM3gdr367feA0PQgfQvBbm8b+sK2JQYpsI='\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:msrest.service_client:Accept header absent and forced to application/json\n",
|
||||
"DEBUG:msrest.universal_http:Configuring redirects: allow=True, max=30\n",
|
||||
"DEBUG:msrest.universal_http:Configuring request: timeout=100, verify=True, cert=None\n",
|
||||
"DEBUG:msrest.universal_http:Configuring proxies: ''\n",
|
||||
"DEBUG:msrest.universal_http:Evaluate proxies against ENV settings: True\n",
|
||||
"DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): management.azure.com:443\n",
|
||||
"DEBUG:urllib3.connectionpool:https://management.azure.com:443 \"GET /subscriptions/edf507a2-6235-46c5-b560-fd463ba2e771/resourceGroups/yanzamlworkspace/providers/Microsoft.MachineLearningServices/workspaces/yanzamlworkspace?api-version=2018-11-19 HTTP/1.1\" 200 None\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"yanzamlworkspace\n",
|
||||
"yanzamlworkspace\n",
|
||||
"eastus2\n",
|
||||
"edf507a2-6235-46c5-b560-fd463ba2e771\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"Let's load the workspace."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"ws = Workspace.from_config()\n",
|
||||
"print(ws.name, ws.resource_group, ws.location, ws.subscription_id, sep=\"\\n\")"
|
||||
|
|
@ -576,165 +217,16 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"DEBUG:azureml.core.run:Could not load run context Failed to load a submitted run, if outside of an execution context, use project.start_run to initialize an azureml.core.Run., switching offline: False\n",
|
||||
"DEBUG:azureml.core.run:Could not load the run context and allow_offline set to False\n",
|
||||
"DEBUG:azureml.core.model:RunEnvironmentException: Failed to load a submitted run, if outside of an execution context, use project.start_run to initialize an azureml.core.Run.\n",
|
||||
"DEBUG:cli.azure.cli.core:Current cloud config:\n",
|
||||
"AzureCloud\n",
|
||||
"DEBUG:adal-python:04afbf0b-b2bc-40ca-935f-91115e07403b - Authority:Performing instance discovery: ...\n",
|
||||
"DEBUG:adal-python:04afbf0b-b2bc-40ca-935f-91115e07403b - Authority:Performing static instance discovery\n",
|
||||
"DEBUG:adal-python:04afbf0b-b2bc-40ca-935f-91115e07403b - Authority:Authority validated via static instance discovery\n",
|
||||
"INFO:adal-python:04afbf0b-b2bc-40ca-935f-91115e07403b - TokenRequest:Getting token from cache with refresh if necessary.\n",
|
||||
"DEBUG:adal-python:04afbf0b-b2bc-40ca-935f-91115e07403b - CacheDriver:finding with query keys: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:04afbf0b-b2bc-40ca-935f-91115e07403b - CacheDriver:Looking for potential cache entries: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:04afbf0b-b2bc-40ca-935f-91115e07403b - CacheDriver:Found 2 potential entries.\n",
|
||||
"DEBUG:adal-python:04afbf0b-b2bc-40ca-935f-91115e07403b - CacheDriver:Resource specific token found.\n",
|
||||
"DEBUG:adal-python:04afbf0b-b2bc-40ca-935f-91115e07403b - CacheDriver:Returning token from cache lookup, AccessTokenId: b'4++Ojr5UOlnb/W1BfAzN6wNgMlDh4UpGKDzSwPkXnqM=', RefreshTokenId: b'y85yfXPddjM3gdr367feA0PQgfQvBbm8b+sK2JQYpsI='\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:azureml._restclient.clientbase.WorkerPool:Found extra key word arguments: {'max_workers': None}\n",
|
||||
"INFO:azureml._restclient.clientbase:Created a worker pool for first use\n",
|
||||
"DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): eastus2.modelmanagement.azureml.net:443\n",
|
||||
"DEBUG:urllib3.connectionpool:https://eastus2.modelmanagement.azureml.net:443 \"GET /api/subscriptions/edf507a2-6235-46c5-b560-fd463ba2e771/resourceGroups/yanzamlworkspace/providers/Microsoft.MachineLearningServices/workspaces/yanzamlworkspace/models?api-version=2018-11-19&orderBy=CreatedAtDesc&count=1&name=resnet_model HTTP/1.1\" 200 None\n",
|
||||
"DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): eastus2.modelmanagement.azureml.net:443\n",
|
||||
"DEBUG:urllib3.connectionpool:https://eastus2.modelmanagement.azureml.net:443 \"GET /api/subscriptions/edf507a2-6235-46c5-b560-fd463ba2e771/resourceGroups/yanzamlworkspace/providers/Microsoft.MachineLearningServices/workspaces/yanzamlworkspace/models?api-version=2018-11-19&orderBy=CreatedAtDesc&count=1&name=resnet_model&$skipToken=K1JJRDpoMkpyQUliMjBnaGQ1Z0lBQUFBQUFBPT0jUlQ6MSNUUkM6MSNSVEQ6eC9VeU1ERTRMVEV4TFRJM1ZERTFPak0wT2pNeExqRTNORGs1TWlzd01Eb3dNQT09I0ZQQzpBZ0VMRVFzR0FGMm1XWUIza2c4SUFGbVpRU1lFQVVpQUVCUUFMSUFSZ0NTT080a0NnTCtBazRDVWdMU0Npb0lSQmdDd2lkR0FVb0E9 HTTP/1.1\" 200 None\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:azureml.core.model:Found model version 2\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:msrest.service_client:Accept header absent and forced to application/json\n",
|
||||
"DEBUG:cli.azure.cli.core:Current cloud config:\n",
|
||||
"AzureCloud\n",
|
||||
"DEBUG:adal-python:7d78a8bf-a075-4dcf-b372-5eac03904170 - Authority:Performing instance discovery: ...\n",
|
||||
"DEBUG:adal-python:7d78a8bf-a075-4dcf-b372-5eac03904170 - Authority:Performing static instance discovery\n",
|
||||
"DEBUG:adal-python:7d78a8bf-a075-4dcf-b372-5eac03904170 - Authority:Authority validated via static instance discovery\n",
|
||||
"INFO:adal-python:7d78a8bf-a075-4dcf-b372-5eac03904170 - TokenRequest:Getting token from cache with refresh if necessary.\n",
|
||||
"DEBUG:adal-python:7d78a8bf-a075-4dcf-b372-5eac03904170 - CacheDriver:finding with query keys: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:7d78a8bf-a075-4dcf-b372-5eac03904170 - CacheDriver:Looking for potential cache entries: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:7d78a8bf-a075-4dcf-b372-5eac03904170 - CacheDriver:Found 2 potential entries.\n",
|
||||
"DEBUG:adal-python:7d78a8bf-a075-4dcf-b372-5eac03904170 - CacheDriver:Resource specific token found.\n",
|
||||
"DEBUG:adal-python:7d78a8bf-a075-4dcf-b372-5eac03904170 - CacheDriver:Returning token from cache lookup, AccessTokenId: b'4++Ojr5UOlnb/W1BfAzN6wNgMlDh4UpGKDzSwPkXnqM=', RefreshTokenId: b'y85yfXPddjM3gdr367feA0PQgfQvBbm8b+sK2JQYpsI='\n",
|
||||
"DEBUG:msrest.http_logger:Request URL: 'https://eastus2.modelmanagement.azureml.net/api/subscriptions/edf507a2-6235-46c5-b560-fd463ba2e771/resourceGroups/yanzamlworkspace/providers/Microsoft.MachineLearningServices/workspaces/yanzamlworkspace/assets/faf941d054554c89a57df701b07c2039?api-version=2018-03-01-preview'\n",
|
||||
"DEBUG:msrest.http_logger:Request method: 'GET'\n",
|
||||
"DEBUG:msrest.http_logger:Request headers:\n",
|
||||
"DEBUG:msrest.http_logger: 'Accept': 'application/json'\n",
|
||||
"DEBUG:msrest.http_logger: 'Content-Type': 'application/json; charset=utf-8'\n",
|
||||
"DEBUG:msrest.http_logger: 'User-Agent': 'python/3.6.7 (Linux-4.15.0-1023-azure-x86_64-with-debian-stretch-sid) msrest/0.6.2 azureml._restclient/core.1.0.2'\n",
|
||||
"DEBUG:msrest.http_logger:Request body:\n",
|
||||
"DEBUG:msrest.http_logger:None\n",
|
||||
"DEBUG:msrest.universal_http:Configuring redirects: allow=True, max=30\n",
|
||||
"DEBUG:msrest.universal_http:Configuring request: timeout=100, verify=True, cert=None\n",
|
||||
"DEBUG:msrest.universal_http:Configuring proxies: ''\n",
|
||||
"DEBUG:msrest.universal_http:Evaluate proxies against ENV settings: True\n",
|
||||
"DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): eastus2.modelmanagement.azureml.net:443\n",
|
||||
"DEBUG:urllib3.connectionpool:https://eastus2.modelmanagement.azureml.net:443 \"GET /api/subscriptions/edf507a2-6235-46c5-b560-fd463ba2e771/resourceGroups/yanzamlworkspace/providers/Microsoft.MachineLearningServices/workspaces/yanzamlworkspace/assets/faf941d054554c89a57df701b07c2039?api-version=2018-03-01-preview HTTP/1.1\" 200 None\n",
|
||||
"DEBUG:msrest.http_logger:Response status: 200\n",
|
||||
"DEBUG:msrest.http_logger:Response headers:\n",
|
||||
"DEBUG:msrest.http_logger: 'Date': 'Tue, 18 Dec 2018 18:07:25 GMT'\n",
|
||||
"DEBUG:msrest.http_logger: 'Content-Type': 'application/json; charset=utf-8'\n",
|
||||
"DEBUG:msrest.http_logger: 'Transfer-Encoding': 'chunked'\n",
|
||||
"DEBUG:msrest.http_logger: 'Connection': 'keep-alive'\n",
|
||||
"DEBUG:msrest.http_logger: 'api-supported-versions': '2018-03-01-preview, 2018-11-19'\n",
|
||||
"DEBUG:msrest.http_logger: 'x-ms-client-request-id': 'd00238067df743aba4af3bd937c77de2'\n",
|
||||
"DEBUG:msrest.http_logger: 'x-ms-client-session-id': ''\n",
|
||||
"DEBUG:msrest.http_logger: 'Strict-Transport-Security': 'max-age=15724800; includeSubDomains; preload'\n",
|
||||
"DEBUG:msrest.http_logger: 'X-Content-Type-Options': 'nosniff'\n",
|
||||
"DEBUG:msrest.http_logger: 'Content-Encoding': 'gzip'\n",
|
||||
"DEBUG:msrest.http_logger:Response content:\n",
|
||||
"DEBUG:msrest.http_logger:{\"id\":\"faf941d054554c89a57df701b07c2039\",\"name\":\"resnet_model\",\"description\":\"resnet_model saved during run None in project None\",\"artifacts\":[{\"id\":null,\"prefix\":\"LocalUpload/181210T175931-c14a35b2/resnet_model.tar.gz\"}],\"tags\":null,\"kvTags\":{},\"properties\":{},\"runid\":null,\"projectid\":null,\"meta\":null,\"createdTime\":\"2018-12-10T17:59:37.0837561Z\"}\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:azureml.core.model:Asset has artifact {'additional_properties': {}, 'id': None, 'prefix': 'LocalUpload/181210T175931-c14a35b2/resnet_model.tar.gz'}\n",
|
||||
"DEBUG:azureml.core.model:Artifact has prefix id LocalUpload/181210T175931-c14a35b2/resnet_model.tar.gz\n",
|
||||
"DEBUG:azureml.ArtifactsClient:Fetching files for prefix in LocalUpload, 181210T175931-c14a35b2, resnet_model.tar.gz\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"DEBUG:azureml._restclient.clientbase.WorkerPool.CreateFutureFunc: _execute_with_base_arguments:[START]\n",
|
||||
"DEBUG:msrest.service_client:Accept header absent and forced to application/json\n",
|
||||
"DEBUG:azureml._restclient.clientbase.WorkerPool.CreateFutureFunc: _execute_with_base_arguments:[STOP]\n",
|
||||
"DEBUG:msrest.universal_http.requests:Configuring retry: max_retries=3, backoff_factor=0.8, max_backoff=90\n",
|
||||
"DEBUG:azureml.ArtifactsClient.list_sas_by_prefix:Using basic handler - no exception handling\n",
|
||||
"DEBUG:azureml.ArtifactsClient.list_sas_by_prefix.WaitingTask:[START]\n",
|
||||
"DEBUG:cli.azure.cli.core:Current cloud config:\n",
|
||||
"AzureCloud\n",
|
||||
"DEBUG:adal-python:bb575216-752c-4bf6-829c-ce186798c44e - Authority:Performing instance discovery: ...\n",
|
||||
"DEBUG:adal-python:bb575216-752c-4bf6-829c-ce186798c44e - Authority:Performing static instance discovery\n",
|
||||
"DEBUG:adal-python:bb575216-752c-4bf6-829c-ce186798c44e - Authority:Authority validated via static instance discovery\n",
|
||||
"INFO:adal-python:bb575216-752c-4bf6-829c-ce186798c44e - TokenRequest:Getting token from cache with refresh if necessary.\n",
|
||||
"DEBUG:adal-python:bb575216-752c-4bf6-829c-ce186798c44e - CacheDriver:finding with query keys: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:bb575216-752c-4bf6-829c-ce186798c44e - CacheDriver:Looking for potential cache entries: {'_clientId': '...', 'userId': '...'}\n",
|
||||
"DEBUG:adal-python:bb575216-752c-4bf6-829c-ce186798c44e - CacheDriver:Found 2 potential entries.\n",
|
||||
"DEBUG:adal-python:bb575216-752c-4bf6-829c-ce186798c44e - CacheDriver:Resource specific token found.\n",
|
||||
"DEBUG:adal-python:bb575216-752c-4bf6-829c-ce186798c44e - CacheDriver:Returning token from cache lookup, AccessTokenId: b'4++Ojr5UOlnb/W1BfAzN6wNgMlDh4UpGKDzSwPkXnqM=', RefreshTokenId: b'y85yfXPddjM3gdr367feA0PQgfQvBbm8b+sK2JQYpsI='\n",
|
||||
"DEBUG:msrest.http_logger:Request URL: 'https://eastus2.experiments.azureml.net/artifact/v1.0/subscriptions/edf507a2-6235-46c5-b560-fd463ba2e771/resourceGroups/yanzamlworkspace/providers/Microsoft.MachineLearningServices/workspaces/yanzamlworkspace/artifacts/prefix/contentinfo/LocalUpload/181210T175931-c14a35b2/resnet_model.tar.gz'\n",
|
||||
"DEBUG:msrest.http_logger:Request method: 'GET'\n",
|
||||
"DEBUG:msrest.http_logger:Request headers:\n",
|
||||
"DEBUG:msrest.http_logger: 'Accept': 'application/json'\n",
|
||||
"DEBUG:msrest.http_logger: 'Content-Type': 'application/json; charset=utf-8'\n",
|
||||
"DEBUG:msrest.http_logger: 'User-Agent': 'python/3.6.7 (Linux-4.15.0-1023-azure-x86_64-with-debian-stretch-sid) msrest/0.6.2 azureml._restclient/core.1.0.2'\n",
|
||||
"DEBUG:msrest.http_logger:Request body:\n",
|
||||
"DEBUG:msrest.http_logger:None\n",
|
||||
"DEBUG:msrest.universal_http:Configuring redirects: allow=True, max=30\n",
|
||||
"DEBUG:msrest.universal_http:Configuring request: timeout=100, verify=True, cert=None\n",
|
||||
"DEBUG:msrest.universal_http:Configuring proxies: ''\n",
|
||||
"DEBUG:msrest.universal_http:Evaluate proxies against ENV settings: True\n",
|
||||
"DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): eastus2.experiments.azureml.net:443\n",
|
||||
"DEBUG:urllib3.connectionpool:https://eastus2.experiments.azureml.net:443 \"GET /artifact/v1.0/subscriptions/edf507a2-6235-46c5-b560-fd463ba2e771/resourceGroups/yanzamlworkspace/providers/Microsoft.MachineLearningServices/workspaces/yanzamlworkspace/artifacts/prefix/contentinfo/LocalUpload/181210T175931-c14a35b2/resnet_model.tar.gz HTTP/1.1\" 200 None\n",
|
||||
"DEBUG:msrest.http_logger:Response status: 200\n",
|
||||
"DEBUG:msrest.http_logger:Response headers:\n",
|
||||
"DEBUG:msrest.http_logger: 'Date': 'Tue, 18 Dec 2018 18:07:25 GMT'\n",
|
||||
"DEBUG:msrest.http_logger: 'Content-Type': 'application/json; charset=utf-8'\n",
|
||||
"DEBUG:msrest.http_logger: 'Transfer-Encoding': 'chunked'\n",
|
||||
"DEBUG:msrest.http_logger: 'Connection': 'keep-alive'\n",
|
||||
"DEBUG:msrest.http_logger: 'Request-Context': 'appId=cid-v1:2d2e8e63-272e-4b3c-8598-4ee570a0e70d'\n",
|
||||
"DEBUG:msrest.http_logger: 'x-ms-client-request-id': '41d3c9294171489ca254f13bd4a70dbf'\n",
|
||||
"DEBUG:msrest.http_logger: 'x-ms-client-session-id': ''\n",
|
||||
"DEBUG:msrest.http_logger: 'Strict-Transport-Security': 'max-age=15724800; includeSubDomains; preload'\n",
|
||||
"DEBUG:msrest.http_logger: 'X-Content-Type-Options': 'nosniff'\n",
|
||||
"DEBUG:msrest.http_logger: 'Content-Encoding': 'gzip'\n",
|
||||
"DEBUG:msrest.http_logger:Response content:\n",
|
||||
"DEBUG:msrest.http_logger:{\n",
|
||||
" \"value\": [\n",
|
||||
" {\n",
|
||||
" \"contentUri\": \"https://yanzamlwstorageyotvwlmq.blob.core.windows.net/azureml/LocalUpload/181210T175931-c14a35b2/resnet_model.tar.gz?sv=2018-03-28&sr=b&sig=EFDXCi1Jzt5VmRRjvxnQ9HwrBxmgG084NGXE954nMxc%3D&st=2018-12-18T17%3A57%3A25Z&se=2018-12-19T02%3A07%3A25Z&sp=r\",\n",
|
||||
" \"origin\": \"LocalUpload\",\n",
|
||||
" \"container\": \"181210T175931-c14a35b2\",\n",
|
||||
" \"path\": \"resnet_model.tar.gz\"\n",
|
||||
" }\n",
|
||||
" ],\n",
|
||||
" \"continuationToken\": null,\n",
|
||||
" \"count\": null\n",
|
||||
"}\n",
|
||||
"DEBUG:azureml.ArtifactsClient.list_sas_by_prefix.WaitingTask:[STOP]\n",
|
||||
"DEBUG:azureml.core.model:prefix id LocalUpload/181210T175931-c14a35b2/resnet_model.tar.gz has path resnet_model.tar.gz\n",
|
||||
"DEBUG:azureml.core.model:prefix to strip from path resnet_model.tar.gz is \n",
|
||||
"DEBUG:azureml.core.model:sas_to_download_path map is OrderedDict([('https://yanzamlwstorageyotvwlmq.blob.core.windows.net/azureml/LocalUpload/181210T175931-c14a35b2/resnet_model.tar.gz?sv=2018-03-28&sr=b&sig=EFDXCi1Jzt5VmRRjvxnQ9HwrBxmgG084NGXE954nMxc%3D&st=2018-12-18T17%3A57%3A25Z&se=2018-12-19T02%3A07%3A25Z&sp=r', 'resnet_model.tar.gz')])\n",
|
||||
"DEBUG:azureml._file_utils.file_utils:downloading file to azureml-models/resnet_model/2/resnet_model.tar.gz, with max_retries: 0, stream: True, and protocol: https\n",
|
||||
"DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): yanzamlwstorageyotvwlmq.blob.core.windows.net:443\n",
|
||||
"DEBUG:urllib3.connectionpool:https://yanzamlwstorageyotvwlmq.blob.core.windows.net:443 \"GET /azureml/LocalUpload/181210T175931-c14a35b2/resnet_model.tar.gz?sv=2018-03-28&sr=b&sig=EFDXCi1Jzt5VmRRjvxnQ9HwrBxmgG084NGXE954nMxc%3D&st=2018-12-18T17%3A57%3A25Z&se=2018-12-19T02%3A07%3A25Z&sp=r HTTP/1.1\" 200 224608891\n",
|
||||
"DEBUG:azureml.core.model:Unpacking model azureml-models/resnet_model/2/resnet_model.tar.gz\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"model_path = Model.get_model_path(_MODEL_NAME, _workspace=ws)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -745,20 +237,9 @@
|
|||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"DEBUG:azureml.core.run:Could not load run context Failed to load a submitted run, if outside of an execution context, use project.start_run to initialize an azureml.core.Run., switching offline: False\n",
|
||||
"DEBUG:azureml.core.run:Could not load the run context and allow_offline set to False\n",
|
||||
"DEBUG:azureml.core.model:RunEnvironmentException: Failed to load a submitted run, if outside of an execution context, use project.start_run to initialize an azureml.core.Run.\n",
|
||||
"DEBUG:azureml.core.model:version is None. Latest version is 2\n",
|
||||
"DEBUG:azureml.core.model:Found model path at azureml-models/resnet_model/2/model_resnet_weights.h5\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Always make sure you don't have any lingering notebooks running.\n",
|
||||
"init()"
|
||||
]
|
||||
},
|
||||
|
|
@ -772,31 +253,23 @@
|
|||
"resp = run(jsonimg)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"jsonimg = img_url_to_json(IMAGEURL)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"with open(\"jsonimg\", \"w\") as f:\n",
|
||||
" f.write(jsonimg)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
"source": [
|
||||
"# Clear GPU memory\n",
|
||||
"from keras import backend as K\n",
|
||||
"K.clear_session()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Next, we will [build a docker image with this modle driver and other supporting files](03__BuildImage.ipynb)."
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
|
|
|||
Загрузка…
Ссылка в новой задаче