diff --git a/README.md b/README.md index 5c6cdaa0954..5ef61f26a57 100644 --- a/README.md +++ b/README.md @@ -189,10 +189,51 @@ katib-ui-5767cfccdc-pwg2x 1/1 Running 0 36s For the Katib Experiments check the [complete examples list](./examples/v1beta1). +# Quickstart + +You can run your first HyperParameter Tuning Experiment using [Katib Python SDK](./sdk/python/v1beta1). + +In the following example we are going to maximize a simple objective function: +$F(a,b) = 4a - b^2$. The bigger $a$ and the lesser $b$ value, the bigger the function value $F$. + +```python +import kubeflow.katib as katib + +# Step 1. Create an objective function. +def objective(parameters): + # Import required packages. + import time + time.sleep(5) + # Calculate objective function. + result = 4 * int(parameters["a"]) - float(parameters["b"]) ** 2 + # Katib parses metrics in this format: =. + print(f"result={result}") + +# Step 2. Create HyperParameter search space. +parameters = { + "a": katib.search.int(min=10, max=20), + "b": katib.search.double(min=0.1, max=0.2) +} + +# Step 3. Create Katib Experiment. +katib_client = katib.KatibClient() +name = "tune-experiment" +katib_client.tune( + name=name, + objective=objective, + parameters=parameters, + objective_metric_name="result", + max_trial_count=12 +) + +# Step 4. Get the best HyperParameters. +print(katib_client.get_optimal_hyperparameters(name)) +``` + # Documentation -- Run your first Katib Experiment in the - [getting started guide](https://www.kubeflow.org/docs/components/katib/hyperparameter/#example-using-random-algorithm). +- Check + [the Katib getting started guide](https://www.kubeflow.org/docs/components/katib/hyperparameter/#example-using-random-search-algorithm). - Learn about Katib **Concepts** in this [guide](https://www.kubeflow.org/docs/components/katib/overview/#katib-concepts). diff --git a/examples/v1beta1/sdk/tune-train-from-func.ipynb b/examples/v1beta1/sdk/tune-train-from-func.ipynb new file mode 100644 index 00000000000..e98d11ff7a9 --- /dev/null +++ b/examples/v1beta1/sdk/tune-train-from-func.ipynb @@ -0,0 +1,788 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "bf9ab16d-fbf6-4385-a7f8-133e4562e1e7", + "metadata": { + "tags": [] + }, + "source": [ + "# Tune and Train with Kubeflow Katib and Training Operator\n", + " \n", + "In this Notebook we are going to do the following:\n", + "\n", + "- Train Tensorflow model using Kubeflow Notebook.\n", + "- Improve the model HyperParameters with [Kubeflow Katib](https://www.kubeflow.org/docs/components/katib/overview/).\n", + "- Use [Multi Worker Mirrored Strategy](https://www.tensorflow.org/api_docs/python/tf/distribute/experimental/MultiWorkerMirroredStrategy) to distributively train the model with [Kubeflow TFJob](https://www.kubeflow.org/docs/components/training/tftraining/)." + ] + }, + { + "cell_type": "markdown", + "id": "62d91e3d-904a-4a3c-b4e7-573324ba625e", + "metadata": {}, + "source": [ + "## Install Kubeflow Python SDKs\n", + "\n", + "You need to install Tensorflow package and Kubeflow SDKs to run this Notebook." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5de885ca-e96a-4d59-9e78-75f6fc6f5ce7", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install tensorflow==2.9.1\n", + "\n", + "# TODO (andreyvelich): Change to release version when SDK with the new APIs is published.\n", + "!pip install git+https://github.com/kubeflow/katib.git#subdirectory=sdk/python/v1beta1\n", + "!pip install git+https://github.com/kubeflow/training-operator.git#subdirectory=sdk/python" + ] + }, + { + "cell_type": "markdown", + "id": "881aae2f-d08e-4439-bef9-1684ff87556d", + "metadata": { + "tags": [] + }, + "source": [ + "## Create Train Script for CNN Model\n", + "\n", + "This is simple **Convolutional Neural Network (CNN)** model for recognizing hand-written digits using [MNIST Dataset](http://yann.lecun.com/exdb/mnist/). " + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "98a77484-cee4-4d77-bd76-915c469a242b", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-12T18:46:59.051290Z", + "iopub.status.busy": "2022-09-12T18:46:59.050544Z", + "iopub.status.idle": "2022-09-12T18:46:59.249456Z", + "shell.execute_reply": "2022-09-12T18:46:59.248292Z", + "shell.execute_reply.started": "2022-09-12T18:46:59.051211Z" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "def train_mnist_model(parameters):\n", + " import tensorflow as tf\n", + " import numpy as np\n", + " import logging\n", + "\n", + " logging.basicConfig(\n", + " format=\"%(asctime)s %(levelname)-8s %(message)s\",\n", + " datefmt=\"%Y-%m-%dT%H:%M:%SZ\",\n", + " level=logging.INFO,\n", + " )\n", + " logging.info(\"--------------------------------------------------------------------------------------\")\n", + " logging.info(f\"Input Parameters: {parameters}\")\n", + " logging.info(\"--------------------------------------------------------------------------------------\\n\\n\")\n", + "\n", + "\n", + " # Get HyperParameters from the input params dict.\n", + " lr = float(parameters[\"lr\"])\n", + " num_epoch = int(parameters[\"num_epoch\"])\n", + "\n", + " # Set dist parameters and strategy.\n", + " is_dist = parameters[\"is_dist\"]\n", + " num_workers = parameters[\"num_workers\"]\n", + " batch_size_per_worker = 64\n", + " batch_size_global = batch_size_per_worker * num_workers\n", + " strategy = tf.distribute.MultiWorkerMirroredStrategy(\n", + " communication_options=tf.distribute.experimental.CommunicationOptions(\n", + " implementation=tf.distribute.experimental.CollectiveCommunication.RING\n", + " )\n", + " )\n", + "\n", + " # Callback class for logging training.\n", + " # Katib parses metrics in this format: =.\n", + " class CustomCallback(tf.keras.callbacks.Callback):\n", + " def on_epoch_end(self, epoch, logs=None):\n", + " logging.info(\n", + " \"Epoch {}/{}. accuracy={:.4f} - loss={:.4f}\".format(\n", + " epoch+1, num_epoch, logs[\"accuracy\"], logs[\"loss\"]\n", + " )\n", + " )\n", + "\n", + " # Prepare MNIST Dataset.\n", + " def mnist_dataset(batch_size):\n", + " (x_train, y_train), _ = tf.keras.datasets.mnist.load_data()\n", + " x_train = x_train / np.float32(255)\n", + " y_train = y_train.astype(np.int64)\n", + " train_dataset = (\n", + " tf.data.Dataset.from_tensor_slices((x_train, y_train))\n", + " .shuffle(60000)\n", + " .repeat()\n", + " .batch(batch_size)\n", + " )\n", + " return train_dataset\n", + "\n", + " # Build and compile CNN Model.\n", + " def build_and_compile_cnn_model():\n", + " model = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.InputLayer(input_shape=(28, 28)),\n", + " tf.keras.layers.Reshape(target_shape=(28, 28, 1)),\n", + " tf.keras.layers.Conv2D(32, 3, activation=\"relu\"),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(128, activation=\"relu\"),\n", + " tf.keras.layers.Dense(10),\n", + " ]\n", + " )\n", + " model.compile(\n", + " loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n", + " optimizer=tf.keras.optimizers.SGD(learning_rate=lr),\n", + " metrics=[\"accuracy\"],\n", + " )\n", + " return model\n", + " \n", + " # Download Dataset.\n", + " dataset = mnist_dataset(batch_size_global)\n", + "\n", + " # For dist strategy we should build model under scope().\n", + " if is_dist:\n", + " logging.info(\"Running Distributed Training\")\n", + " logging.info(\"--------------------------------------------------------------------------------------\\n\\n\")\n", + " with strategy.scope():\n", + " model = build_and_compile_cnn_model()\n", + " else:\n", + " logging.info(\"Running Single Worker Training\")\n", + " logging.info(\"--------------------------------------------------------------------------------------\\n\\n\")\n", + " model = build_and_compile_cnn_model()\n", + " \n", + " # Start Training.\n", + " model.fit(\n", + " dataset,\n", + " epochs=num_epoch,\n", + " steps_per_epoch=70,\n", + " callbacks=[CustomCallback()],\n", + " verbose=0,\n", + " )" + ] + }, + { + "cell_type": "markdown", + "id": "38c81974-0ea6-480e-844d-03ad02f068fa", + "metadata": { + "tags": [] + }, + "source": [ + "## Run Training Locally in the Notebook\n", + "\n", + "We are going to download MNIST Dataset and start local training.\n", + "\n", + "Also, set `Epochs = 2` to reduce training time and avoid CPU overload. " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e23b92a7-d94f-43a9-a6f2-e4e9e79ace94", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-12T18:47:19.717477Z", + "iopub.status.busy": "2022-09-12T18:47:19.716773Z", + "iopub.status.idle": "2022-09-12T18:50:45.646239Z", + "shell.execute_reply": "2022-09-12T18:50:45.645056Z", + "shell.execute_reply.started": "2022-09-12T18:47:19.717438Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-09-12T18:47:45Z INFO --------------------------------------------------------------------------------------\n", + "2022-09-12T18:47:45Z INFO Input Parameters: {'lr': '0.1', 'num_epoch': '2', 'is_dist': False, 'num_workers': 1}\n", + "2022-09-12T18:47:45Z INFO --------------------------------------------------------------------------------------\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "INFO:tensorflow:Single-worker MultiWorkerMirroredStrategy with local_devices = ('/device:CPU:0',), communication = CommunicationImplementation.RING\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-09-12T18:47:45Z INFO Single-worker MultiWorkerMirroredStrategy with local_devices = ('/device:CPU:0',), communication = CommunicationImplementation.RING\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz\n", + "11490434/11490434 [==============================] - 1s 0us/step\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-09-12T18:47:51Z INFO Running Single Worker Training\n", + "2022-09-12T18:47:51Z INFO --------------------------------------------------------------------------------------\n", + "\n", + "\n", + "2022-09-12T18:49:24Z INFO Epoch 1/2. accuracy=0.7310 - loss=0.8630\n", + "2022-09-12T18:50:45Z INFO Epoch 2/2. accuracy=0.8862 - loss=0.3731\n" + ] + } + ], + "source": [ + "# Set Parameters for Local Training.\n", + "parameters = {\n", + " \"lr\": \"0.1\",\n", + " \"num_epoch\": \"2\",\n", + " \"is_dist\": False,\n", + " \"num_workers\": 1\n", + "}\n", + "\n", + "# Train Model locally in the Notebook.\n", + "train_mnist_model(parameters)" + ] + }, + { + "cell_type": "markdown", + "id": "05c878de-718f-4f5b-af52-7cb222f43dfd", + "metadata": { + "tags": [] + }, + "source": [ + "## Start Model Tuning with Katib\n", + "\n", + "If you want to improve your model, you can run HyperParameter tuning with Katib.\n", + "\n", + "The following example uses **Covariance Matrix Adaptation Evolution Strategy (CMA-ES)** algorithm to tune HyperParameters.\n", + "\n", + "We are going to tune `learning rate` and `number of epochs`." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "c1e479e7-7fe1-4d72-91ba-4d8e55321882", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-12T19:01:45.433380Z", + "iopub.status.busy": "2022-09-12T19:01:45.432517Z", + "iopub.status.idle": "2022-09-12T19:01:45.546553Z", + "shell.execute_reply": "2022-09-12T19:01:45.545424Z", + "shell.execute_reply.started": "2022-09-12T19:01:45.433308Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Experiment tune-mnist has been created\n" + ] + }, + { + "data": { + "text/html": [ + "Katib Experiment tune-mnist link here" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import kubeflow.katib as katib\n", + "\n", + "# Set parameters with their distribution for HyperParameter Tuning with Katib.\n", + "parameters = {\n", + " \"lr\": katib.search.double(min=0.1, max=0.2),\n", + " \"num_epoch\": katib.search.int(min=10, max=15),\n", + " \"is_dist\": False,\n", + " \"num_workers\": 1\n", + "}\n", + "\n", + "# Start the Katib Experiment.\n", + "exp_name = \"tune-mnist\"\n", + "katib_client = katib.KatibClient()\n", + "\n", + "katib_client.tune(\n", + " name=exp_name,\n", + " objective=train_mnist_model, # Objective function.\n", + " parameters=parameters, # HyperParameters to tune.\n", + " algorithm_name=\"cmaes\", # Alorithm to use.\n", + " objective_metric_name=\"accuracy\", # Katib is going to optimize \"accuracy\".\n", + " additional_metric_names=[\"loss\"], # Katib is going to collect these metrics in addition to the objective metric.\n", + " max_trial_count=12, # Trial Threshold.\n", + " parallel_trial_count=2,\n", + ")" + ] + }, + { + "attachments": { + "cdaf463d-28b3-4a98-bb4c-9613ca1bfa50.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "21f7c176-9168-454d-b90c-3221e2923898", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-01T15:51:29.342657Z", + "iopub.status.busy": "2022-09-01T15:51:29.251197Z", + "iopub.status.idle": "2022-09-01T15:51:29.445579Z", + "shell.execute_reply": "2022-09-01T15:51:29.443320Z", + "shell.execute_reply.started": "2022-09-01T15:51:29.342591Z" + }, + "tags": [] + }, + "source": [ + "### Access to Katib UI\n", + "\n", + "You can check created Experiment in the Katib UI.\n", + "\n", + "![Screenshot 2022-09-12 at 20.06.23.png](attachment:cdaf463d-28b3-4a98-bb4c-9613ca1bfa50.png)" + ] + }, + { + "cell_type": "markdown", + "id": "8e64470f-e80d-4230-bef1-ce31c81fc910", + "metadata": {}, + "source": [ + "### Get the Best HyperParameters from the Katib Experiment\n", + "\n", + "You can get the best HyperParameters from the most optimal Katib Trial." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "c01fba11-3627-4a6d-88a6-3f1508637934", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-12T19:08:48.997327Z", + "iopub.status.busy": "2022-09-12T19:08:48.995976Z", + "iopub.status.idle": "2022-09-12T19:08:49.144874Z", + "shell.execute_reply": "2022-09-12T19:08:49.143625Z", + "shell.execute_reply.started": "2022-09-12T19:08:48.997288Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Katib Experiment status: Succeeded\n", + "\n", + "Current Optimal Trial\n", + "\n", + "{\n", + " \"currentOptimalTrial\": {\n", + " \"bestTrialName\": \"tune-mnist-svnwmmmv\",\n", + " \"observation\": {\n", + " \"metrics\": [\n", + " {\n", + " \"latest\": \"0.0992\",\n", + " \"max\": \"0.8749\",\n", + " \"min\": \"0.0992\",\n", + " \"name\": \"loss\"\n", + " },\n", + " {\n", + " \"latest\": \"0.9714\",\n", + " \"max\": \"0.9714\",\n", + " \"min\": \"0.7176\",\n", + " \"name\": \"accuracy\"\n", + " }\n", + " ]\n", + " },\n", + " \"parameterAssignments\": [\n", + " {\n", + " \"name\": \"lr\",\n", + " \"value\": \"0.17016692449867332\"\n", + " },\n", + " {\n", + " \"name\": \"num_epoch\",\n", + " \"value\": \"13\"\n", + " }\n", + " ]\n", + " }\n", + "}\n" + ] + } + ], + "source": [ + "status = katib_client.get_experiment_status(exp_name)\n", + "print(f\"Katib Experiment status: {status}\\n\")\n", + "\n", + "best_hps = katib_client.get_optimal_hyperparameters(exp_name)\n", + "\n", + "if best_hps != {}:\n", + " import json\n", + " print(\"Current Optimal Trial\\n\")\n", + " print(json.dumps(best_hps, indent=4))\n", + " \n", + " for hp in best_hps[\"currentOptimalTrial\"][\"parameterAssignments\"]:\n", + " if hp[\"name\"] == \"lr\":\n", + " best_lr = hp[\"value\"]\n", + " else:\n", + " best_num_epoch = hp[\"value\"]" + ] + }, + { + "cell_type": "markdown", + "id": "1ee6b88d-6dfa-4924-8c67-86e019c78012", + "metadata": { + "tags": [] + }, + "source": [ + "## Start Distributive Training with TFJob\n", + "\n", + "Use the best HyperParameters (`learning rate` and `number of epochs`) from the Katib Experiment and run the TFJob." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "6289e27f-325d-4433-9379-7e97bc8aae69", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-12T19:08:51.055746Z", + "iopub.status.busy": "2022-09-12T19:08:51.054605Z", + "iopub.status.idle": "2022-09-12T19:08:51.246141Z", + "shell.execute_reply": "2022-09-12T19:08:51.244919Z", + "shell.execute_reply.started": "2022-09-12T19:08:51.055713Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-09-12T19:08:51Z INFO TFJob train-mnist has been created\n" + ] + } + ], + "source": [ + "from kubeflow.training import TFJobClient\n", + "\n", + "# Set Parameters for Distributed Training with TFJob.\n", + "parameters = {\n", + " \"lr\": best_lr,\n", + " \"num_epoch\": best_num_epoch,\n", + " \"is_dist\": True,\n", + " \"num_workers\": 5\n", + "}\n", + "\n", + "# Start TFJob Training.\n", + "tfjob_name = \"train-mnist\"\n", + "tfjob_client = TFJobClient()\n", + "\n", + "tfjob_client.create_tfjob_from_func(\n", + " name=tfjob_name,\n", + " func=train_mnist_model,\n", + " parameters=parameters, # Input parameters for the train function.\n", + " num_worker_replicas=5, # How many TFJob Workers will be run.\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "d5d465e8-0310-4c72-ad36-209259ad5c34", + "metadata": {}, + "source": [ + "### Get TFJob Status and Training Logs\n", + "\n", + "You can check the TFJob status and logs." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "53859cf4-7a35-4fc4-b5ee-9ba774635df0", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-12T19:10:06.862146Z", + "iopub.status.busy": "2022-09-12T19:10:06.861177Z", + "iopub.status.idle": "2022-09-12T19:10:06.945011Z", + "shell.execute_reply": "2022-09-12T19:10:06.943629Z", + "shell.execute_reply.started": "2022-09-12T19:10:06.862104Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TFJob status: Succeeded\n" + ] + } + ], + "source": [ + "print(f\"TFJob status: {tfjob_client.get_job_status(tfjob_name)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "f247670e-0bd4-4336-a40c-605ce32fad23", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-12T19:10:11.765592Z", + "iopub.status.busy": "2022-09-12T19:10:11.764384Z", + "iopub.status.idle": "2022-09-12T19:10:14.249858Z", + "shell.execute_reply": "2022-09-12T19:10:14.248518Z", + "shell.execute_reply.started": "2022-09-12T19:10:11.765560Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-09-12T19:10:11Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:53Z INFO --------------------------------------------------------------------------------------\n", + "2022-09-12T19:10:11Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:53Z INFO Input Parameters: {'lr': '0.17016692449867332', 'num_epoch': '13', 'is_dist': True, 'num_workers': 5}\n", + "2022-09-12T19:10:11Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:53Z INFO --------------------------------------------------------------------------------------\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12 19:08:53.988515: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F FMA\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12 19:08:54.008619: I tensorflow/core/distributed_runtime/rpc/grpc_channel.cc:272] Initialize GrpcChannelCache for job worker -> {0 -> train-mnist-worker-0.kubeflow-andrey.svc:2222, 1 -> train-mnist-worker-1.kubeflow-andrey.svc:2222, 2 -> train-mnist-worker-2.kubeflow-andrey.svc:2222, 3 -> train-mnist-worker-3.kubeflow-andrey.svc:2222, 4 -> train-mnist-worker-4.kubeflow-andrey.svc:2222}\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12 19:08:54.008700: I tensorflow/core/distributed_runtime/rpc/grpc_channel.cc:272] Initialize GrpcChannelCache for job worker -> {0 -> train-mnist-worker-0.kubeflow-andrey.svc:2222, 1 -> train-mnist-worker-1.kubeflow-andrey.svc:2222, 2 -> train-mnist-worker-2.kubeflow-andrey.svc:2222, 3 -> train-mnist-worker-3.kubeflow-andrey.svc:2222, 4 -> train-mnist-worker-4.kubeflow-andrey.svc:2222}\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12 19:08:54.009579: I tensorflow/core/distributed_runtime/rpc/grpc_server_lib.cc:438] Started server with target: grpc://train-mnist-worker-0.kubeflow-andrey.svc:2222\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Enabled multi-worker collective ops with available devices: ['/job:worker/replica:0/task:0/device:CPU:0', '/job:worker/replica:0/task:4/device:CPU:0', '/job:worker/replica:0/task:2/device:CPU:0', '/job:worker/replica:0/task:3/device:CPU:0', '/job:worker/replica:0/task:1/device:CPU:0']\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:54Z INFO Enabled multi-worker collective ops with available devices: ['/job:worker/replica:0/task:0/device:CPU:0', '/job:worker/replica:0/task:4/device:CPU:0', '/job:worker/replica:0/task:2/device:CPU:0', '/job:worker/replica:0/task:3/device:CPU:0', '/job:worker/replica:0/task:1/device:CPU:0']\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Check health not enabled.\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:54Z INFO Check health not enabled.\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:MultiWorkerMirroredStrategy with cluster_spec = {'worker': ['train-mnist-worker-0.kubeflow-andrey.svc:2222', 'train-mnist-worker-1.kubeflow-andrey.svc:2222', 'train-mnist-worker-2.kubeflow-andrey.svc:2222', 'train-mnist-worker-3.kubeflow-andrey.svc:2222', 'train-mnist-worker-4.kubeflow-andrey.svc:2222']}, task_type = 'worker', task_id = 0, num_workers = 5, local_devices = ('/job:worker/task:0/device:CPU:0',), communication = CommunicationImplementation.RING\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:54Z INFO MultiWorkerMirroredStrategy with cluster_spec = {'worker': ['train-mnist-worker-0.kubeflow-andrey.svc:2222', 'train-mnist-worker-1.kubeflow-andrey.svc:2222', 'train-mnist-worker-2.kubeflow-andrey.svc:2222', 'train-mnist-worker-3.kubeflow-andrey.svc:2222', 'train-mnist-worker-4.kubeflow-andrey.svc:2222']}, task_type = 'worker', task_id = 0, num_workers = 5, local_devices = ('/job:worker/task:0/device:CPU:0',), communication = CommunicationImplementation.RING\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz\n", + "11490434/11490434 [==============================] - 0s 0us/step\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:56Z INFO Running Distributed Training\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:56Z INFO --------------------------------------------------------------------------------------\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: 2022-09-12 19:08:56.666389: W tensorflow/core/grappler/optimizers/data/auto_shard.cc:776] AUTO sharding policy will apply DATA sharding policy as it failed to apply FILE sharding policy because of the following reason: Found an unshardable source dataset: name: \"TensorSliceDataset/_2\"\n", + "2022-09-12T19:10:12Z INFO [Pod train-mnist-worker-0]: op: \"TensorSliceDataset\"\n", + 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TFT_FLOAT\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: }\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: }\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: args {\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: type_id: TFT_TENSOR\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: args {\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: type_id: TFT_INT64\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: }\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: }\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: }\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: }\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: }\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12 19:08:56.901683: W tensorflow/core/framework/dataset.cc:768] Input of GeneratorDatasetOp::Dataset will not be optimized because the dataset does not implement the AsGraphDefInternal() method needed to apply optimizations.\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 6 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:57Z INFO Collective all_reduce tensors: 6 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:57Z INFO Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:57Z INFO Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:57Z INFO Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:57Z INFO Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:57Z INFO Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 6 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:58Z INFO Collective all_reduce tensors: 6 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:58Z INFO Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:58Z INFO Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:58Z INFO Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: INFO:tensorflow:Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:13Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:08:58Z INFO Collective all_reduce tensors: 1 all_reduces, num_devices = 1, group_size = 5, implementation = CommunicationImplementation.RING, num_packs = 1\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:04Z INFO Epoch 1/13. accuracy=0.7755 - loss=0.7565\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:09Z INFO Epoch 2/13. accuracy=0.9104 - loss=0.2964\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:13Z INFO Epoch 3/13. accuracy=0.9371 - loss=0.2100\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:18Z INFO Epoch 4/13. accuracy=0.9475 - loss=0.1756\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:23Z INFO Epoch 5/13. accuracy=0.9505 - loss=0.1612\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:27Z INFO Epoch 6/13. accuracy=0.9608 - loss=0.1309\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:32Z INFO Epoch 7/13. accuracy=0.9613 - loss=0.1298\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:37Z INFO Epoch 8/13. accuracy=0.9645 - loss=0.1165\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:41Z INFO Epoch 9/13. accuracy=0.9717 - loss=0.0962\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:46Z INFO Epoch 10/13. accuracy=0.9719 - loss=0.0920\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:51Z INFO Epoch 11/13. accuracy=0.9743 - loss=0.0873\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:09:55Z INFO Epoch 12/13. accuracy=0.9751 - loss=0.0831\n", + "2022-09-12T19:10:14Z INFO [Pod train-mnist-worker-0]: 2022-09-12T19:10:00Z INFO Epoch 13/13. accuracy=0.9765 - loss=0.0803\n" + ] + } + ], + "source": [ + "tfjob_client.get_logs(name=tfjob_name, master=True, follow=True)" + ] + }, + { + "cell_type": "markdown", + "id": "227c0a9a-fdf5-4047-b0e2-ec15d3c120ac", + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-09T23:50:29.596391Z", + "iopub.status.busy": "2022-08-09T23:50:29.596145Z", + "iopub.status.idle": "2022-08-09T23:50:29.599222Z", + "shell.execute_reply": "2022-08-09T23:50:29.598674Z", + "shell.execute_reply.started": "2022-08-09T23:50:29.596363Z" + } + }, + "source": [ + "## Delete Katib Experiment and TFJob\n", + "\n", + "When jobs are finished, you can delete the resources." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "dd24acd8-4305-463e-a6e6-eed16d8a7c51", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-12T19:10:19.053646Z", + "iopub.status.busy": "2022-09-12T19:10:19.052424Z", + "iopub.status.idle": "2022-09-12T19:10:19.144593Z", + "shell.execute_reply": "2022-09-12T19:10:19.143396Z", + "shell.execute_reply.started": "2022-09-12T19:10:19.053607Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Experiment tune-mnist has been deleted\n" + ] + } + ], + "source": [ + "katib_client.delete_experiment(exp_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "025fa4af-256d-4027-99ba-ba44c1409541", + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-12T19:10:19.532471Z", + "iopub.status.busy": "2022-09-12T19:10:19.531949Z", + "iopub.status.idle": "2022-09-12T19:10:19.550331Z", + "shell.execute_reply": "2022-09-12T19:10:19.549103Z", + "shell.execute_reply.started": "2022-09-12T19:10:19.532441Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-09-12T19:10:19Z INFO TFJob train-mnist has been deleted\n" + ] + } + ], + "source": [ + "tfjob_client.delete(tfjob_name)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e238a638-cf77-423f-a346-f763fc8b1582", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Kubeflow Tensorflow", + "language": "python", + "name": "kurek2tw49o8" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/hack/gen-python-sdk/post_gen.py b/hack/gen-python-sdk/post_gen.py index 638f3d11c40..1bb88b3c1fb 100644 --- a/hack/gen-python-sdk/post_gen.py +++ b/hack/gen-python-sdk/post_gen.py @@ -37,10 +37,17 @@ def _rewrite_helper(input_file, output_file, rewrite_rules): if not any(l in line for l in IGNORE_LINES): lines.append(line) - # Add Katib client to init file. + # Add Katib APIs to the init file. if (output_file == "sdk/python/v1beta1/kubeflow/katib/__init__.py"): lines.append("# Import Katib API client.\n") lines.append("from kubeflow.katib.api.katib_client import KatibClient\n") + lines.append("# Import Katib helper functions.\n") + lines.append("import kubeflow.katib.api.search as search\n") + lines.append("# Import Katib helper constants.\n") + lines.append("from kubeflow.katib.constants.constants import BASE_IMAGE_TENSORFLOW\n") + lines.append("from kubeflow.katib.constants.constants import BASE_IMAGE_TENSORFLOW_GPU\n") + lines.append("from kubeflow.katib.constants.constants import BASE_IMAGE_PYTORCH\n") + lines.append("from kubeflow.katib.constants.constants import BASE_IMAGE_MXNET\n") # Add Kubernetes models to proper deserialization of Katib models. if (output_file == "sdk/python/v1beta1/kubeflow/katib/models/__init__.py"): diff --git a/sdk/python/v1beta1/.gitignore b/sdk/python/v1beta1/.gitignore new file mode 100644 index 00000000000..97c5614a935 --- /dev/null +++ b/sdk/python/v1beta1/.gitignore @@ -0,0 +1,2 @@ +# Distribution / packaging +dist/ diff --git a/sdk/python/v1beta1/kubeflow/katib/__init__.py b/sdk/python/v1beta1/kubeflow/katib/__init__.py index a8b1253551f..a949c8567e1 100644 --- a/sdk/python/v1beta1/kubeflow/katib/__init__.py +++ b/sdk/python/v1beta1/kubeflow/katib/__init__.py @@ -71,3 +71,10 @@ # Import Katib API client. from kubeflow.katib.api.katib_client import KatibClient +# Import Katib helper functions. +import kubeflow.katib.api.search as search +# Import Katib helper constants. +from kubeflow.katib.constants.constants import BASE_IMAGE_TENSORFLOW +from kubeflow.katib.constants.constants import BASE_IMAGE_TENSORFLOW_GPU +from kubeflow.katib.constants.constants import BASE_IMAGE_PYTORCH +from kubeflow.katib.constants.constants import BASE_IMAGE_MXNET diff --git a/sdk/python/v1beta1/kubeflow/katib/api/katib_client.py b/sdk/python/v1beta1/kubeflow/katib/api/katib_client.py index 99c79bbfe0a..941213df61a 100644 --- a/sdk/python/v1beta1/kubeflow/katib/api/katib_client.py +++ b/sdk/python/v1beta1/kubeflow/katib/api/katib_client.py @@ -13,9 +13,11 @@ # limitations under the License. import multiprocessing +from typing import Callable, List, Dict, Any +import inspect +import textwrap -from kubeflow.katib import V1beta1Experiment -from kubeflow.katib import V1beta1Trial +from kubeflow.katib import models from kubeflow.katib.api_client import ApiClient from kubeflow.katib.constants import constants from kubeflow.katib.utils import utils @@ -23,9 +25,13 @@ class KatibClient(object): - - def __init__(self, config_file=None, context=None, - client_configuration=None, persist_config=True): + def __init__( + self, + config_file=None, + context=None, + client_configuration=None, + persist_config=True, + ): """KatibClient constructor. :param config_file: Name of the kube-config file. Defaults to ~/.kube/config. @@ -40,7 +46,8 @@ def __init__(self, config_file=None, context=None, config_file=config_file, context=context, client_configuration=client_configuration, - persist_config=persist_config) + persist_config=persist_config, + ) self.in_cluster = False else: config.load_incluster_config() @@ -53,6 +60,7 @@ def _is_ipython(self): """Returns whether we are running in notebook.""" try: import IPython + ipy = IPython.get_ipython() if ipy is None: return False @@ -60,40 +68,234 @@ def _is_ipython(self): return False return True - def create_experiment(self, exp_object, namespace=None): + def create_experiment( + self, exp_object, namespace=utils.get_default_target_namespace() + ): """Create the Katib Experiment. :param exp_object: Experiment object. :param namespace: Experiment namespace. If the namespace is None, it takes namespace from the Experiment or "default". - - :return: Created Experiment. - :rtype: dict """ - if namespace is None: - namespace = utils.set_katib_namespace(exp_object) try: - outputs = self.api_instance.create_namespaced_custom_object( + self.api_instance.create_namespaced_custom_object( constants.KUBEFLOW_GROUP, constants.KATIB_VERSION, namespace, constants.EXPERIMENT_PLURAL, - exp_object) + exp_object, + ) except client.rest.ApiException as e: raise RuntimeError( "Exception when calling CustomObjectsApi->create_namespaced_custom_object:\ - %s\n" % e) + %s\n" + % e + ) + + # TODO (andreyvelich): Use proper logger. + print("Experiment {} has been created".format(exp_object.metadata.name)) if self._is_ipython(): if self.in_cluster: import IPython - IPython.display.display(IPython.display.HTML( - 'Katib Experiment {} ' - 'link here'.format( - exp_object.metadata.name, namespace, exp_object.metadata.name) - )) - return outputs + + IPython.display.display( + IPython.display.HTML( + "Katib Experiment {} " + 'link here'.format( + exp_object.metadata.name, + namespace, + exp_object.metadata.name, + ) + ) + ) + + def tune( + self, + # TODO (andreyvelich): How to be consistent with other APIs (name) ? + name: str, + objective: Callable, + parameters: Dict[str, Any], + base_image: str = constants.BASE_IMAGE_TENSORFLOW, + namespace: str = utils.get_default_target_namespace(), + algorithm_name: str = "random", + objective_metric_name: str = None, + additional_metric_names: List[str] = [], + objective_type: str = "maximize", + objective_goal: float = None, + max_trial_count: int = None, + parallel_trial_count: int = None, + max_failed_trial_count: int = None, + retain_trials: bool = False, + packages_to_install: List[str] = None, + pip_index_url: str = "https://pypi.org/simple", + ): + """Create HyperParameter Tuning Katib Experiment from the objective function. + + Args: + name: Name for the Experiment. + objective: Objective function that Katib uses to train the model. + This function must be Callable and it must have only one dict argument. + Katib uses this argument to send HyperParameters to the function. + The function should not use any code declared outside of the function + definition. Import statements must be added inside the function. + parameters: Dict of HyperParameters to tune your Experiment. You + should use Katib SDK to define the search space for these parameters. + + For example: `parameters = {"lr": katib.search.double(min=0.1, max=0.2)}` + + Also, you can use these parameters to define input for your + objective function. + base_image: Image to use when executing the objective function. + namespace: Namespace for the Experiment. + algorithm_name: Search algorithm for the HyperParameter tuning. + objective_metric_name: Objective metric that Katib optimizes. + additional_metric_names: List of metrics that Katib collects from the + objective function in addition to objective metric. + objective_type: Type for the Experiment optimization for the objective metric. + Must be one of `minimize` or `maximize`. + objective_goal: Objective goal that Experiment should reach to be Succeeded. + max_trial_count: Maximum number of Trials to run. For the default + values check this doc: https://www.kubeflow.org/docs/components/katib/experiment/#configuration-spec. + parallel_trial_count: Number of Trials that Experiment runs in parallel. + max_failed_trial_count: Maximum number of Trials allowed to fail. + retain_trials: Whether Trials' resources (e.g. pods) are deleted after Succeeded state. + packages_to_install: List of Python packages to install in addition + to the base image packages. These packages are installed before + executing the objective function. + pip_index_url: The PyPI url from which to install Python packages. + """ + + # Create Katib Experiment template. + experiment = models.V1beta1Experiment( + api_version=f"{constants.KUBEFLOW_GROUP}/{constants.KATIB_VERSION}", + kind=constants.EXPERIMENT_KIND, + metadata=models.V1ObjectMeta(name=name, namespace=namespace), + spec=models.V1beta1ExperimentSpec(), + ) + + # Add Objective to the Katib Experiment. + experiment.spec.objective = models.V1beta1ObjectiveSpec( + type=objective_type, + objective_metric_name=objective_metric_name, + additional_metric_names=additional_metric_names, + ) + if objective_goal is not None: + experiment.spec.objective.goal = objective_goal + + # Add Algorithm to the Katib Experiment. + experiment.spec.algorithm = models.V1beta1AlgorithmSpec( + algorithm_name=algorithm_name + ) + + # Add Trial budget to the Katib Experiment. + if max_trial_count is not None: + experiment.spec.max_trial_count = max_trial_count + if parallel_trial_count is not None: + experiment.spec.parallel_trial_count = parallel_trial_count + if max_failed_trial_count is not None: + experiment.spec.max_failed_trial_count = max_failed_trial_count + + # Validate objective function. + utils.validate_objective_function(objective) + + # Extract objective function implementation. + objective_code = inspect.getsource(objective) + + # Objective function might be defined in some indented scope + # (e.g. in another function). We need to dedent the function code. + objective_code = textwrap.dedent(objective_code) + + # Iterate over input parameters. + input_params = {} + experiment_params = [] + trial_params = [] + for p_name, p_value in parameters.items(): + # If input parameter value is Katib Experiment parameter sample. + if isinstance(p_value, models.V1beta1ParameterSpec): + # Wrap value for the function input. + input_params[p_name] = f"${{trialParameters.{p_name}}}" + + # Add value to the Katib Experiment parameters. + p_value.name = p_name + experiment_params.append(p_value) + + # Add value to the Katib Experiment's Trial parameters. + trial_params.append( + models.V1beta1TrialParameterSpec(name=p_name, reference=p_name) + ) + else: + # Otherwise, add value to the function input. + input_params[p_name] = p_value + + # Wrap objective function to execute it from the file. For example + # def objective(parameters): + # print(f'Parameters are {parameters}') + # objective({'lr': '${trialParameters.lr}', 'epochs': '${trialParameters.epochs}', 'is_dist': False}) + objective_code = f"{objective_code}\n{objective.__name__}({input_params})\n" + + # Prepare execute script template. + exec_script = textwrap.dedent( + """ + program_path=$(mktemp -d) + read -r -d '' SCRIPT << EOM\n + {objective_code} + EOM + printf "%s" "$SCRIPT" > $program_path/ephemeral_objective.py + python3 -u $program_path/ephemeral_objective.py""" + ) + + # Add objective code to the execute script. + exec_script = exec_script.format(objective_code=objective_code) + + # Install Python packages if that is required. + if packages_to_install is not None: + exec_script = ( + utils.get_script_for_python_packages(packages_to_install, pip_index_url) + + exec_script + ) + + # Create Trial specification. + trial_spec = client.V1Job( + api_version="batch/v1", + kind="Job", + spec=client.V1JobSpec( + template=client.V1PodTemplateSpec( + metadata=models.V1ObjectMeta( + annotations={"sidecar.istio.io/inject": "false"} + ), + spec=client.V1PodSpec( + restart_policy="Never", + containers=[ + client.V1Container( + name=constants.DEFAULT_PRIMARY_CONTAINER_NAME, + image=base_image, + command=["bash", "-c"], + args=[exec_script], + ) + ], + ), + ) + ), + ) + + # Create Trial template. + trial_template = models.V1beta1TrialTemplate( + primary_container_name=constants.DEFAULT_PRIMARY_CONTAINER_NAME, + retain=retain_trials, + trial_parameters=trial_params, + trial_spec=trial_spec, + ) + + # Add parameters to the Katib Experiment. + experiment.spec.parameters = experiment_params + + # Add Trial template to the Katib Experiment. + experiment.spec.trial_template = trial_template + + # Create the Katib Experiment. + self.create_experiment(exp_object=experiment) # TODO (andreyvelich): Get Experiment should always return one Experiment. # Use list_experiments to return Experiment list. @@ -120,7 +322,8 @@ def get_experiment(self, name=None, namespace=None): namespace, constants.EXPERIMENT_PLURAL, name, - async_req=True) + async_req=True, + ) katibexp = None try: @@ -130,11 +333,16 @@ def get_experiment(self, name=None, namespace=None): except client.rest.ApiException as e: raise RuntimeError( "Exception when calling CustomObjectsApi->get_namespaced_custom_object:\ - %s\n" % e) + %s\n" + % e + ) except Exception as e: raise RuntimeError( "There was a problem to get experiment {0} in namespace {1}. Exception: \ - {2} ".format(name, namespace, e)) + {2} ".format( + name, namespace, e + ) + ) else: thread = self.api_instance.list_namespaced_custom_object( @@ -142,7 +350,8 @@ def get_experiment(self, name=None, namespace=None): constants.KATIB_VERSION, namespace, constants.EXPERIMENT_PLURAL, - async_req=True) + async_req=True, + ) katibexp = None try: @@ -152,11 +361,16 @@ def get_experiment(self, name=None, namespace=None): except client.rest.ApiException as e: raise RuntimeError( "Exception when calling CustomObjectsApi->list_namespaced_custom_object:\ - %s\n" % e) + %s\n" + % e + ) except Exception as e: raise RuntimeError( "There was a problem to get experiment in namespace {0}. \ - Exception: {1} ".format(namespace, e)) + Exception: {1} ".format( + namespace, e + ) + ) return katibexp @@ -182,7 +396,8 @@ def get_suggestion(self, name=None, namespace=None): namespace, constants.SUGGESTION_PLURAL, name, - async_req=True) + async_req=True, + ) katib_suggestion = None try: @@ -192,11 +407,16 @@ def get_suggestion(self, name=None, namespace=None): except client.rest.ApiException as e: raise RuntimeError( "Exception when calling CustomObjectsApi->get_namespaced_custom_object:\ - %s\n" % e) + %s\n" + % e + ) except Exception as e: raise RuntimeError( "There was a problem to get suggestion {0} in namespace {1}. Exception: \ - {2} ".format(name, namespace, e)) + {2} ".format( + name, namespace, e + ) + ) else: thread = self.api_instance.list_namespaced_custom_object( @@ -204,7 +424,8 @@ def get_suggestion(self, name=None, namespace=None): constants.KATIB_VERSION, namespace, constants.SUGGESTION_PLURAL, - async_req=True) + async_req=True, + ) katib_suggestion = None try: @@ -214,39 +435,45 @@ def get_suggestion(self, name=None, namespace=None): except client.rest.ApiException as e: raise RuntimeError( "Exception when calling CustomObjectsApi->list_namespaced_custom_object:\ - %s\n" % e) + %s\n" + % e + ) except Exception as e: raise RuntimeError( "There was a problem to get suggestions in namespace {0}. \ - Exception: {1} ".format(namespace, e)) + Exception: {1} ".format( + namespace, e + ) + ) return katib_suggestion - def delete_experiment(self, name, namespace=None): + def delete_experiment(self, name, namespace=utils.get_default_target_namespace()): """Delete the Katib Experiment. :param name: Experiment name. :param namespace: Experiment namespace. If the namespace is None, it takes namespace from the Experiment object or "default". - - :return: Deleted Experiment object. - :rtype: dict """ - if namespace is None: - namespace = utils.get_default_target_namespace() try: - return self.api_instance.delete_namespaced_custom_object( + self.api_instance.delete_namespaced_custom_object( constants.KUBEFLOW_GROUP, constants.KATIB_VERSION, namespace, constants.EXPERIMENT_PLURAL, name, - body=client.V1DeleteOptions()) + body=client.V1DeleteOptions(), + ) except client.rest.ApiException as e: raise RuntimeError( "Exception when calling CustomObjectsApi->delete_namespaced_custom_object:\ - %s\n" % e) + %s\n" + % e + ) + + # TODO (andreyvelich): Use proper logger. + print("Experiment {} has been deleted".format(name)) def list_experiments(self, namespace=None): """List all Katib Experiments. @@ -265,14 +492,17 @@ def list_experiments(self, namespace=None): constants.KATIB_VERSION, namespace=namespace, plural=constants.EXPERIMENT_PLURAL, - async_req=True) + async_req=True, + ) katibexp = None result = [] try: katibexp = thread.get(constants.APISERVER_TIMEOUT) result = [ - self.api_client.deserialize(utils.FakeResponse(item), V1beta1Experiment) + self.api_client.deserialize( + utils.FakeResponse(item), models.V1beta1Experiment + ) for item in katibexp.get("items") ] @@ -281,11 +511,16 @@ def list_experiments(self, namespace=None): except client.rest.ApiException as e: raise RuntimeError( "Exception when calling CustomObjectsApi->get_namespaced_custom_object:\ - %s\n" % e) + %s\n" + % e + ) except Exception as e: raise RuntimeError( "There was a problem to get experiments in namespace {0}. Exception: \ - {1} ".format(namespace, e)) + {1} ".format( + namespace, e + ) + ) return result def get_experiment_status(self, name, namespace=None): @@ -315,8 +550,7 @@ def is_experiment_succeeded(self, name, namespace=None): :return: Whether Experiment has succeeded or not. :rtype: bool """ - experiment_status = self.get_experiment_status( - name, namespace=namespace) + experiment_status = self.get_experiment_status(name, namespace=namespace) return experiment_status.lower() == "succeeded" def list_trials(self, name=None, namespace=None): @@ -337,28 +571,42 @@ def list_trials(self, name=None, namespace=None): constants.KATIB_VERSION, namespace=namespace, plural=constants.TRIAL_PLURAL, - async_req=True) + async_req=True, + ) katibtrial = None result = [] try: katibtrial = thread.get(constants.APISERVER_TIMEOUT) - + for item in katibtrial.get("items"): - if name is not None and item.get("metadata", {}).get("ownerReferences")[0].get("name") != name: + if ( + name is not None + and item.get("metadata", {}).get("ownerReferences")[0].get("name") + != name + ): continue - - result.append(self.api_client.deserialize(utils.FakeResponse(item), V1beta1Trial)) + + result.append( + self.api_client.deserialize( + utils.FakeResponse(item), models.V1beta1Trial + ) + ) except multiprocessing.TimeoutError: raise RuntimeError("Timeout trying to get katib experiment.") except client.rest.ApiException as e: raise RuntimeError( "Exception when calling CustomObjectsApi->list_namespaced_custom_object:\ - %s\n" % e) + %s\n" + % e + ) except Exception as e: raise RuntimeError( "There was a problem to get experiment {0} in namespace {1}. Exception: \ - {2} ".format(name, namespace, e)) + {2} ".format( + name, namespace, e + ) + ) return result def get_success_trial_details(self, name=None, namespace=None): @@ -379,41 +627,53 @@ def get_success_trial_details(self, name=None, namespace=None): constants.KATIB_VERSION, namespace=namespace, plural=constants.TRIAL_PLURAL, - async_req=True) + async_req=True, + ) katibtrial = None result = [] try: katibtrial = thread.get(constants.APISERVER_TIMEOUT) - + for item in katibtrial.get("items"): status = item.get("status", {}).get("conditions", [])[-1].get("type") if status != "Succeeded": continue - - if name is not None and item.get("metadata", {}).get("ownerReferences")[0].get("name") != name: + + if ( + name is not None + and item.get("metadata", {}).get("ownerReferences")[0].get("name") + != name + ): continue - + output = {} output["name"] = item.get("metadata", {}).get("name") - output["hyperparameters"] = item.get("spec", {}).get("parameterAssignments", []) + output["hyperparameters"] = item.get("spec", {}).get( + "parameterAssignments", [] + ) output["metrics"] = ( - item.get("status", {}) - .get("observation", {}) - .get("metrics", []) + item.get("status", {}).get("observation", {}).get("metrics", []) ) result.append(output) except multiprocessing.TimeoutError: - raise RuntimeError("Timeout trying to get succeeded trials of the katib experiment.") + raise RuntimeError( + "Timeout trying to get succeeded trials of the katib experiment." + ) except client.rest.ApiException as e: raise RuntimeError( "Exception when calling CustomObjectsApi->list_namespaced_custom_object:\ - %s\n" % e) + %s\n" + % e + ) except Exception as e: raise RuntimeError( "There was a problem to get experiment {0} in namespace {1}. Exception: \ - {2} ".format(name, namespace, e)) - + {2} ".format( + name, namespace, e + ) + ) + return result def get_optimal_hyperparameters(self, name=None, namespace=None): @@ -430,7 +690,8 @@ def get_optimal_hyperparameters(self, name=None, namespace=None): katibexp = self.get_experiment(name, namespace=namespace) result = {} - result["currentOptimalTrial"] = katibexp.get( - "status", {}).get("currentOptimalTrial") + result["currentOptimalTrial"] = katibexp.get("status", {}).get( + "currentOptimalTrial" + ) return result diff --git a/sdk/python/v1beta1/kubeflow/katib/api/search.py b/sdk/python/v1beta1/kubeflow/katib/api/search.py new file mode 100644 index 00000000000..83204c3d43f --- /dev/null +++ b/sdk/python/v1beta1/kubeflow/katib/api/search.py @@ -0,0 +1,64 @@ +# Copyright 2022 The Kubeflow Authors. +# +# 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. + +from kubeflow.katib import models +from typing import List + + +def double(min: float, max: float, step: float = None): + """Sample a float value uniformly between `min` and `max`. + + Args: + min: Lower boundary for the float value. + max: Upper boundary for the float value. + step: Step between float values. + """ + + parameter = models.V1beta1ParameterSpec( + parameter_type="double", + feasible_space=models.V1beta1FeasibleSpace(min=str(min), max=str(max)), + ) + if step is not None: + parameter.feasible_space.step = str(step) + return parameter + + +def int(min: int, max: int, step: int = None): + """Sample an integer value uniformly between `min` and `max`. + + Args: + min: Lower boundary for the integer value. + max: Upper boundary for the integer value. + step: Step between integer values. + """ + + parameter = models.V1beta1ParameterSpec( + parameter_type="int", + feasible_space=models.V1beta1FeasibleSpace(min=str(min), max=str(max)), + ) + if step is not None: + parameter.feasible_space.step = str(step) + return parameter + + +def categorical(list: List): + """Sample a categorical value from the `list`. + + Args: + list: List of categorical values. + """ + + return models.V1beta1ParameterSpec( + parameter_type="categorical", feasible_space=models.V1beta1FeasibleSpace(list), + ) diff --git a/sdk/python/v1beta1/kubeflow/katib/constants/constants.py b/sdk/python/v1beta1/kubeflow/katib/constants/constants.py index 1b49fd477c9..833897f6b45 100644 --- a/sdk/python/v1beta1/kubeflow/katib/constants/constants.py +++ b/sdk/python/v1beta1/kubeflow/katib/constants/constants.py @@ -13,15 +13,29 @@ # limitations under the License. import os +from typing import Final + +# How long to wait in seconds for requests to the ApiServer +APISERVER_TIMEOUT: Final[int] = 120 # Global CRD version -KATIB_VERSION = os.environ.get('EXPERIMENT_VERSION', 'v1beta1') +KATIB_VERSION: Final[str] = os.environ.get("EXPERIMENT_VERSION", "v1beta1") # Katib K8S constants -KUBEFLOW_GROUP = 'kubeflow.org' -EXPERIMENT_PLURAL = 'experiments' -SUGGESTION_PLURAL = 'suggestions' -TRIAL_PLURAL = 'trials' +KUBEFLOW_GROUP: Final[str] = "kubeflow.org" +EXPERIMENT_KIND: Final[str] = "Experiment" +EXPERIMENT_PLURAL: Final[str] = "experiments" +SUGGESTION_PLURAL: Final[str] = "suggestions" +TRIAL_PLURAL: Final[str] = "trials" -# How long to wait in seconds for requests to the ApiServer -APISERVER_TIMEOUT = 120 + +DEFAULT_PRIMARY_CONTAINER_NAME: Final[str] = "training-container" + +# Supported base images for the Katib Trials. +# TODO (andreyvelich): Implement list_base_images function to get each image description. +BASE_IMAGE_TENSORFLOW: Final[str] = "docker.io/tensorflow/tensorflow:2.9.1" +BASE_IMAGE_TENSORFLOW_GPU: Final[str] = "docker.io/tensorflow/tensorflow:2.9.1-gpu" +BASE_IMAGE_PYTORCH: Final[ + str +] = "docker.io/pytorch/pytorch:1.12.1-cuda11.3-cudnn8-runtime" +BASE_IMAGE_MXNET: Final[str] = "docker.io/mxnet/python:1.9.1_native_py3" diff --git a/sdk/python/v1beta1/kubeflow/katib/utils/utils.py b/sdk/python/v1beta1/kubeflow/katib/utils/utils.py index 08370eeaa7c..3946f381332 100644 --- a/sdk/python/v1beta1/kubeflow/katib/utils/utils.py +++ b/sdk/python/v1beta1/kubeflow/katib/utils/utils.py @@ -14,20 +14,23 @@ import json import os +import textwrap +from typing import Callable +import inspect def is_running_in_k8s(): - return os.path.isdir('/var/run/secrets/kubernetes.io/') + return os.path.isdir("/var/run/secrets/kubernetes.io/") def get_current_k8s_namespace(): - with open('/var/run/secrets/kubernetes.io/serviceaccount/namespace', 'r') as f: + with open("/var/run/secrets/kubernetes.io/serviceaccount/namespace", "r") as f: return f.readline() def get_default_target_namespace(): if not is_running_in_k8s(): - return 'default' + return "default" return get_current_k8s_namespace() @@ -36,10 +39,49 @@ def set_katib_namespace(katib): namespace = katib_namespace or get_default_target_namespace() return namespace + +def validate_objective_function(objective: Callable): + + # Check if objective function is callable. + if not callable(objective): + raise ValueError( + f"Objective function must be callable, got function type: {type(objective)}" + ) + + # Verify the objective function arguments. + objective_signature = inspect.signature(objective) + try: + objective_signature.bind({}) + except Exception: + raise ValueError( + "Invalid args in the Objective function. " + "The function args must have only 'parameters' dictionary. " + f"Current Objective arguments: {objective_signature}" + ) + + +def get_script_for_python_packages(packages_to_install, pip_index_url): + packages_str = " ".join([str(package) for package in packages_to_install]) + + script_for_python_packages = textwrap.dedent( + f""" + if ! [ -x "$(command -v pip)" ]; then + python3 -m ensurepip || python3 -m ensurepip --user || apt-get install python3-pip + fi + + PIP_DISABLE_PIP_VERSION_CHECK=1 python3 -m pip install --quiet \ + --no-warn-script-location --index-url {pip_index_url} {packages_str} + """ + ) + + return script_for_python_packages + + class FakeResponse: """Fake object of RESTResponse to deserialize Ref) https://github.com/kubeflow/katib/pull/1630#discussion_r697877815 Ref) https://github.com/kubernetes-client/python/issues/977#issuecomment-592030030 """ + def __init__(self, obj): self.data = json.dumps(obj) diff --git a/sdk/python/v1beta1/requirements.txt b/sdk/python/v1beta1/requirements.txt deleted file mode 100644 index 3a454769530..00000000000 --- a/sdk/python/v1beta1/requirements.txt +++ /dev/null @@ -1,5 +0,0 @@ -certifi>=14.05.14 -six>=1.10 -setuptools>=21.0.0 -urllib3>=1.15.1 -kubernetes>=12.0.0 diff --git a/sdk/python/v1beta1/setup.py b/sdk/python/v1beta1/setup.py index 6f0f9163404..c61dea35ad6 100644 --- a/sdk/python/v1beta1/setup.py +++ b/sdk/python/v1beta1/setup.py @@ -14,40 +14,44 @@ import setuptools -with open('requirements.txt') as f: - REQUIRES = f.readlines() +REQUIRES = [ + "certifi>=14.05.14", + "six>=1.10", + "setuptools>=21.0.0", + "urllib3>=1.15.1", + "kubernetes>=23.6.0", +] setuptools.setup( - name='kubeflow-katib', - version='0.14.0', + name="kubeflow-katib", + version="0.14.0", author="Kubeflow Authors", - author_email='premnath.vel@gmail.com', + author_email="premnath.vel@gmail.com", license="Apache License Version 2.0", url="https://github.com/kubeflow/katib/tree/master/sdk/python/v1beta1", description="Katib Python SDK for APIVersion v1beta1", long_description="Katib Python SDK for APIVersion v1beta1", - packages=setuptools.find_packages( - include=("kubeflow*")), + packages=setuptools.find_packages(include=("kubeflow*")), package_data={}, include_package_data=False, zip_safe=False, classifiers=[ - 'Intended Audience :: Developers', - 'Intended Audience :: Education', - 'Intended Audience :: Science/Research', - 'Programming Language :: Python :: 3', - 'Programming Language :: Python :: 3 :: Only', - 'Programming Language :: Python :: 3.7', - 'Programming Language :: Python :: 3.8', - 'Programming Language :: Python :: 3.9', - 'Programming Language :: Python :: 3.10', + "Intended Audience :: Developers", + "Intended Audience :: Education", + "Intended Audience :: Science/Research", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3 :: Only", + "Programming Language :: Python :: 3.7", + "Programming Language :: Python :: 3.8", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", "License :: OSI Approved :: Apache Software License", "Operating System :: OS Independent", - 'Topic :: Scientific/Engineering', - 'Topic :: Scientific/Engineering :: Artificial Intelligence', - 'Topic :: Software Development', - 'Topic :: Software Development :: Libraries', - 'Topic :: Software Development :: Libraries :: Python Modules', + "Topic :: Scientific/Engineering", + "Topic :: Scientific/Engineering :: Artificial Intelligence", + "Topic :: Software Development", + "Topic :: Software Development :: Libraries", + "Topic :: Software Development :: Libraries :: Python Modules", ], - install_requires=REQUIRES + install_requires=REQUIRES, )