diff --git a/examples/broadcasting/main.py b/examples/broadcasting/main.py index a36c4fa..0ba65fd 100644 --- a/examples/broadcasting/main.py +++ b/examples/broadcasting/main.py @@ -1,24 +1,15 @@ """Broadcasting example script""" -import os -import sys - -sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) - import asyncio +import os import numpy as np -import py_nillion_client as nillion -from common.utils import compute, store_program, store_secret_array +import pytest from config import DIM -from cosmpy.aerial.client import LedgerClient -from cosmpy.aerial.wallet import LocalWallet -from cosmpy.crypto.keypairs import PrivateKey from dotenv import load_dotenv -from nillion_python_helpers import (create_nillion_client, - create_payments_config, get_quote, - get_quote_and_pay, pay_with_quote) -from py_nillion_client import NodeKey, UserKey +from nillion_client import (InputPartyBinding, Network, NilChainPayer, + NilChainPrivateKey, OutputPartyBinding, + Permissions, PrivateKey, SecretInteger, VmClient) import nada_numpy.client as na_client @@ -26,153 +17,120 @@ load_dotenv(f"{home}/.config/nillion/nillion-devnet.env") -# Main asynchronous function to coordinate the process -async def main() -> None: - """Main nada program""" +# 1 Party running simple addition on 1 stored secret and 1 compute time secret +async def main(): + # Use the devnet configuration generated by `nillion-devnet` + network = Network.from_config("devnet") - cluster_id = os.getenv("NILLION_CLUSTER_ID") - grpc_endpoint = os.getenv("NILLION_NILCHAIN_GRPC") - chain_id = os.getenv("NILLION_NILCHAIN_CHAIN_ID") - seed = "my_seed" - userkey = UserKey.from_seed((seed)) - nodekey = NodeKey.from_seed((seed)) - client = create_nillion_client(userkey, nodekey) - party_id = client.party_id - user_id = client.user_id + # Create payments config and set up Nillion wallet with a private key to pay for operations + nilchain_key: str = os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0") # type: ignore + payer = NilChainPayer( + network, + wallet_private_key=NilChainPrivateKey(bytes.fromhex(nilchain_key)), + gas_limit=10000000, + ) + # Use a random key to identify ourselves + signing_key = PrivateKey() + client = await VmClient.create(signing_key, network, payer) party_names = na_client.parties(3) program_name = "broadcasting" - program_mir_path = f"target/{program_name}.nada.bin" - - # Create payments config and set up Nillion wallet with a private key to pay for operations - payments_config = create_payments_config(chain_id, grpc_endpoint) - payments_client = LedgerClient(payments_config) - payments_wallet = LocalWallet( - PrivateKey(bytes.fromhex(os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0"))), - prefix="nillion", - ) + program_mir_path = f"./target/{program_name}.nada.bin" ##### STORE PROGRAM print("-----STORE PROGRAM") - program_id = await store_program( - client, - payments_wallet, - payments_client, - user_id, - cluster_id, - program_name, - program_mir_path, - ) + # Store program + program_mir = open( + os.path.join(os.path.dirname(os.path.abspath(__file__)), program_mir_path), "rb" + ).read() + program_id = await client.store_program(program_name, program_mir).invoke() - ##### STORE SECRETS - print("-----STORE SECRETS") - A = np.ones([DIM]) - C = np.ones([DIM]) + # Print details about stored program + print(f"Stored program_id: {program_id}") - # Create a permissions object to attach to the stored secret - permissions = nillion.Permissions.default_for_user(client.user_id) - permissions.add_compute_permissions({client.user_id: {program_id}}) + ##### STORE SECRETS + print("-----STORE SECRETS Party 0") # Create a secret - store_id_A = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - A, - "A", - nillion.SecretInteger, - 1, - permissions, - ) + A = na_client.array(np.ones([DIM]), "A", SecretInteger) + C = na_client.array(np.ones([DIM]), "C", SecretInteger) - store_id_C = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - C, - "C", - nillion.SecretInteger, - 1, - permissions, + # Create a permissions object to attach to the stored secret + permissions = Permissions.defaults_for_user(client.user_id).allow_compute( + client.user_id, program_id ) - # Create and store secrets for two parties + # Store a secret, passing in the receipt that shows proof of payment + values_A = await client.store_values( + A, ttl_days=5, permissions=permissions + ).invoke() - B = np.ones([DIM]) - D = np.ones([DIM]) + print("Stored values_A: ", values_A) - store_id_B = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - B, - "B", - nillion.SecretInteger, - 1, - permissions, - ) + values_C = await client.store_values( + C, ttl_days=5, permissions=permissions + ).invoke() - store_id_D = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - D, - "D", - nillion.SecretInteger, - 1, - permissions, + print("Stored values_C: ", values_C) + print("-----STORE SECRETS Party 1") + + # Create a secret + B = na_client.array(np.ones([DIM]), "B", SecretInteger) + D = na_client.array(np.ones([DIM]), "D", SecretInteger) + + # Create a permissions object to attach to the stored secret + permissions = Permissions.defaults_for_user(client.user_id).allow_compute( + client.user_id, program_id ) - # Set up the compute bindings for the parties - compute_bindings = nillion.ProgramBindings(program_id) + # Store a secret, passing in the receipt that shows proof of payment + values_B = await client.store_values( + B, ttl_days=5, permissions=permissions + ).invoke() - for party_name in party_names[:-1]: - compute_bindings.add_input_party(party_name, party_id) - compute_bindings.add_output_party(party_names[-1], party_id) + print("Stored values_B: ", values_B) - print(f"Computing using program {program_id}") - print( - f"Use secret store_id: {store_id_A}, {store_id_B}, {store_id_C}, {store_id_D}" - ) + values_D = await client.store_values( + D, ttl_days=5, permissions=permissions + ).invoke() + + print("Stored values_D: ", values_D) ##### COMPUTE print("-----COMPUTE") # Bind the parties in the computation to the client to set input and output parties - compute_bindings = nillion.ProgramBindings(program_id) - compute_bindings.add_input_party(party_names[0], party_id) - compute_bindings.add_input_party(party_names[1], party_id) - compute_bindings.add_output_party(party_names[2], party_id) + input_bindings = [ + InputPartyBinding(party_names[0], client.user_id), + InputPartyBinding(party_names[1], client.user_id), + ] + output_bindings = [OutputPartyBinding(party_names[2], [client.user_id])] # Create a computation time secret to use - computation_time_secrets = nillion.NadaValues({}) - - # Get cost quote, then pay for operation to compute + compute_time_values = { + # "my_int2": SecretInteger(10) + } - result = await compute( - client, - payments_wallet, - payments_client, - program_id, - cluster_id, - compute_bindings, - [store_id_A, store_id_B, store_id_C, store_id_D], - computation_time_secrets, - verbose=1, + # Compute, passing in the compute time values as well as the previously uploaded value. + print( + f"Invoking computation using program {program_id} and values id {values_A}, {values_B}, {values_C}, {values_D}" ) - + compute_id = await client.compute( + program_id, + input_bindings, + output_bindings, + values=compute_time_values, + value_ids=[values_A, values_B, values_C, values_D], + ).invoke() + + # Print compute result + print(f"The computation was sent to the network. compute_id: {compute_id}") + result = await client.retrieve_compute_results(compute_id).invoke() + print(f"✅ Compute complete for compute_id {compute_id}") + print(f"🖥️ The result is {result}") return result -# Run the main function if the script is executed directly if __name__ == "__main__": asyncio.run(main()) diff --git a/examples/dot_product/main.py b/examples/dot_product/main.py index 42a969e..372dbbe 100644 --- a/examples/dot_product/main.py +++ b/examples/dot_product/main.py @@ -1,24 +1,15 @@ """Dot Product example script""" -import os -import sys - -sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) - import asyncio +import os import numpy as np -import py_nillion_client as nillion -from common.utils import compute, store_program, store_secret_array +import pytest from config import DIM -from cosmpy.aerial.client import LedgerClient -from cosmpy.aerial.wallet import LocalWallet -from cosmpy.crypto.keypairs import PrivateKey from dotenv import load_dotenv -from nillion_python_helpers import (create_nillion_client, - create_payments_config, get_quote, - get_quote_and_pay, pay_with_quote) -from py_nillion_client import NodeKey, UserKey +from nillion_client import (InputPartyBinding, Network, NilChainPayer, + NilChainPrivateKey, OutputPartyBinding, + Permissions, PrivateKey, SecretInteger, VmClient) import nada_numpy.client as na_client @@ -26,113 +17,107 @@ load_dotenv(f"{home}/.config/nillion/nillion-devnet.env") -# Main asynchronous function to coordinate the process -async def main() -> None: - """Main nada program""" +# 1 Party running simple addition on 1 stored secret and 1 compute time secret +async def main(): + # Use the devnet configuration generated by `nillion-devnet` + network = Network.from_config("devnet") - cluster_id = os.getenv("NILLION_CLUSTER_ID") - grpc_endpoint = os.getenv("NILLION_NILCHAIN_GRPC") - chain_id = os.getenv("NILLION_NILCHAIN_CHAIN_ID") - seed = "my_seed" - userkey = UserKey.from_seed((seed)) - nodekey = NodeKey.from_seed((seed)) - client = create_nillion_client(userkey, nodekey) - party_id = client.party_id - user_id = client.user_id + # Create payments config and set up Nillion wallet with a private key to pay for operations + nilchain_key: str = os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0") # type: ignore + payer = NilChainPayer( + network, + wallet_private_key=NilChainPrivateKey(bytes.fromhex(nilchain_key)), + gas_limit=10000000, + ) + # Use a random key to identify ourselves + signing_key = PrivateKey() + client = await VmClient.create(signing_key, network, payer) party_names = na_client.parties(3) program_name = "dot_product" - program_mir_path = f"target/{program_name}.nada.bin" - - # Create payments config and set up Nillion wallet with a private key to pay for operations - payments_config = create_payments_config(chain_id, grpc_endpoint) - payments_client = LedgerClient(payments_config) - payments_wallet = LocalWallet( - PrivateKey(bytes.fromhex(os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0"))), - prefix="nillion", - ) + program_mir_path = f"./target/{program_name}.nada.bin" ##### STORE PROGRAM print("-----STORE PROGRAM") - program_id = await store_program( - client, - payments_wallet, - payments_client, - user_id, - cluster_id, - program_name, - program_mir_path, - ) + # Store program + program_mir = open( + os.path.join(os.path.dirname(os.path.abspath(__file__)), program_mir_path), "rb" + ).read() + program_id = await client.store_program(program_name, program_mir).invoke() - ##### STORE SECRETS - print("-----STORE SECRETS") - A = np.ones([DIM]) + # Print details about stored program + print(f"Stored program_id: {program_id}") - # Create a permissions object to attach to the stored secret - permissions = nillion.Permissions.default_for_user(client.user_id) - permissions.add_compute_permissions({client.user_id: {program_id}}) + ##### STORE SECRETS + print("-----STORE SECRETS Party 0") # Create a secret - store_id_A = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - A, - "A", - nillion.SecretInteger, - 1, - permissions, + A = na_client.array(np.ones([DIM]), "A", SecretInteger) + + # Create a permissions object to attach to the stored secret + permissions = Permissions.defaults_for_user(client.user_id).allow_compute( + client.user_id, program_id ) - # Create and store secrets for two parties + # Store a secret, passing in the receipt that shows proof of payment + values_A = await client.store_values( + A, ttl_days=5, permissions=permissions + ).invoke() - B = np.ones([DIM]) + print("Stored values_A: ", values_A) - store_id_B = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - B, - "B", - nillion.SecretInteger, - 1, - permissions, + print("-----STORE SECRETS Party 1") + + # Create a secret + B = na_client.array(np.ones([DIM]), "B", SecretInteger) + + # Create a permissions object to attach to the stored secret + permissions = Permissions.defaults_for_user(client.user_id).allow_compute( + client.user_id, program_id ) + # Store a secret, passing in the receipt that shows proof of payment + values_B = await client.store_values( + B, ttl_days=5, permissions=permissions + ).invoke() + + print("Stored values_B: ", values_B) + ##### COMPUTE print("-----COMPUTE") # Bind the parties in the computation to the client to set input and output parties - compute_bindings = nillion.ProgramBindings(program_id) - compute_bindings.add_input_party(party_names[0], party_id) - compute_bindings.add_input_party(party_names[1], party_id) - compute_bindings.add_output_party(party_names[2], party_id) + input_bindings = [ + InputPartyBinding(party_names[0], client.user_id), + InputPartyBinding(party_names[1], client.user_id), + ] + output_bindings = [OutputPartyBinding(party_names[2], [client.user_id])] # Create a computation time secret to use - computation_time_secrets = nillion.NadaValues({}) - - # Get cost quote, then pay for operation to compute + compute_time_values = { + # "my_int2": SecretInteger(10) + } - result = await compute( - client, - payments_wallet, - payments_client, - program_id, - cluster_id, - compute_bindings, - [store_id_A, store_id_B], - computation_time_secrets, - verbose=1, + # Compute, passing in the compute time values as well as the previously uploaded value. + print( + f"Invoking computation using program {program_id} and values id {values_A}, {values_B}" ) - + compute_id = await client.compute( + program_id, + input_bindings, + output_bindings, + values=compute_time_values, + value_ids=[values_A, values_B], + ).invoke() + + # Print compute result + print(f"The computation was sent to the network. compute_id: {compute_id}") + result = await client.retrieve_compute_results(compute_id).invoke() + print(f"✅ Compute complete for compute_id {compute_id}") + print(f"🖥️ The result is {result}") return result -# Run the main function if the script is executed directly if __name__ == "__main__": asyncio.run(main()) diff --git a/examples/linear_regression/linear_regression.ipynb b/examples/linear_regression/linear_regression.ipynb index d2c975d..2635ea7 100644 --- a/examples/linear_regression/linear_regression.ipynb +++ b/examples/linear_regression/linear_regression.ipynb @@ -1,510 +1,510 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "tOKatV-Av_7J" - }, - "source": [ - "# 👋 Welcome to Nillion's Nada Numpy Linear Regression Closed Form Training example" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "s1idKo5Rv_7K" - }, - "source": [ - "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NillionNetwork/nada-numpy/blob/main/examples/linear_regression/linear_regression.ipynb)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IeHr5pAHv_7K" - }, - "source": [ - "This notebook will get you familiar with linear regression closed-form training in `nada-numpy`, Nillion's data processing framework on top of the Nada dsl\n", - "\n", - "We are really excited for developers to build with our SDK, if you have any questions please do reach out to us on:\n", - "\n", - "[![Discord](https://img.shields.io/badge/Discord-nillionnetwork-%235865F2?logo=discord)](https://discord.gg/nillionnetwork)\n", - "[![GitHub Discussions](https://img.shields.io/badge/GitHub_Discussions-NillionNetwork-%23181717?logo=github)](https://github.com/orgs/NillionNetwork/discussions)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "gcgBmJtPv_7K" - }, - "source": [ - "# 1. Set up environment" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "vL85sjrzv_7K" - }, - "source": [ - "The boring part!\n", - "\n", - "Installs all required dependencies and spins up a local devnet that will run Nada programs" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "o4PXBlE2v_7K", - "outputId": "57adf7cd-0d00-4463-b993-45b2d0f3f904" - }, - "outputs": [], - "source": [ - "%%capture\n", - "!pip install nada-numpy" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "id": "rmTAavFov_7L" - }, - "outputs": [], - "source": [ - "import os\n", - "import time\n", - "import sys\n", - "import uuid" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# Configure telemetry settings\n", - "enable_telemetry = True #@param {type:\"boolean\"}\n", - "my_github_username = \"your-github-username\" #@param {type:\"string\"}" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "GcsYIHINv_7L", - "outputId": "8089b90e-0f5a-471c-a6b2-ee00acb6b825" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " % Total % Received % Xferd Average Speed Time Time Time Current\n", - " Dload Upload Total Spent Left Speed\n", - "100 7810 100 7810 0 0 15569 0 --:--:-- --:--:-- --:--:-- 15557\n", - "\n", - "nilup has been installed into /home/vscode/.nilup/bin.\n", - "\n", - "$PATH is already up-to-date. You may begin using nilup now!\n", - "\n", - "By providing your Ethereum wallet address, you consent to the collection of telemetry data by the Nillion Network.\n", - "That includes but is not limited to\n", - "- The version of the SDK you are using\n", - "- The OS you are using\n", - "- The Processor Architecture you are using\n", - "- The SDK binary that you are running and the subcommand\n", - "- The wallet address you provided\n", - "- The errors produced by the SDK\n", - "We collect this data to understand how the software is used, and to better assist you in case of issues.\n", - "While we will not collect any personal information, we still recommend using a new wallet address that cannot be linked to your identity by any third party.\n", - "For more information, our privacy policy is available at https://nillion.com/privacy/.\n", - "Do you consent to the collection of telemetry data? (yes/no)\n", - "Telemetry data collection enabled\n", - "SDK version latest already installed\n", - "Reinstalling SDK version latest\n", - "Installing SDK bins version latest\n", - "Downloading latest/nillion-sdk-bins-aarch64-unknown-linux-musl.tar.gz\n", - "SDK version latest installed\n", - "SDK version latest set as default\n", - "SDK version latest already installed\n", - "Reinstalling SDK version latest\n", - "Installing SDK bins version latest\n", - "Downloading latest/nillion-sdk-bins-aarch64-unknown-linux-musl.tar.gz\n", - "SDK version latest installed\n", - "SDK version latest set as default\n" - ] - } - ], - "source": [ - "# Install the nilup tool and then use that to install the Nillion SDK\n", - "!curl https://nilup.nilogy.xyz/install.sh | bash\n", - "\n", - "# Update Path if ran in colab\n", - "if \"google.colab\" in sys.modules:\n", - " os.environ[\"PATH\"] += \":/root/.nilup/bin\"\n", - " os.environ[\"PATH\"] += \":/root/.nilup/sdks/latest/\"\n", - "\n", - "# Set telemetry if opted in\n", - "if enable_telemetry:\n", - " identifier = f\"nada-numpy-linear-regression-cf-{str(uuid.uuid4())}-{my_github_username}\"\n", - " !echo 'yes' | nilup instrumentation enable --wallet {identifier}\n", - "\n", - "# Install the lastest SDK and initialise it\n", - "!nilup init\n", - "!nilup install latest\n", - "!nilup use latest" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "L3CluM_vv_7L", - "outputId": "cb33ce5c-ec8c-4cf9-f8c2-5213145b6d19" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ℹ️ cluster id is 9e68173f-9c23-4acc-ba81-4f079b639964\n", - "ℹ️ using 256 bit prime\n", - "ℹ️ storing state in /tmp/.tmphGXd3q (190.84Gbs available)\n", - "🏃 starting nilchain node in: /tmp/.tmphGXd3q/nillion-chain\n", - "⛓ nilchain JSON RPC available at http://127.0.0.1:48102\n", - "⛓ nilchain REST API available at http://localhost:26650\n", - "⛓ nilchain gRPC available at localhost:26649\n", - "🏃 starting node 12D3KooWMvw1hEqm7EWSDEyqTb6pNetUVkepahKY6hixuAuMZfJS\n", - "⏳ waiting until bootnode is up...\n", - "🏃 starting node 12D3KooWAiwGZUwSUaT2bYVxGS8jmfMrfsanZYkHwH3uL7WJPsFq\n", - "🏃 starting node 12D3KooWM3hsAswc7ZT6VpwQ1TCZU4GCYY55nLhcsxCcfjuixW57\n", - "👛 funding nilchain keys\n", - "📝 nillion CLI configuration written to /home/vscode/.config/nillion/nillion-cli.yaml\n", - "🌄 environment file written to /home/vscode/.config/nillion/nillion-devnet.env\n" - ] - } - ], - "source": [ - "# Spin up local Nillion devnet\n", - "os.system(\"nohup nillion-devnet &\")\n", - "\n", - "time.sleep(5) # Wait for devnet" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "4teHBr6W5_Mz", - "outputId": "c7b02148-dcff-49f2-b255-f34c8ad3cd30" - }, - "outputs": [], - "source": [ - "if 'google.colab' in sys.modules:\n", - " # If ran in Colab, clone the nada-numpy repo and navigate to the correct directory\n", - " if not os.path.exists(\"nada-numpy\"):\n", - " !git clone https://github.com/NillionNetwork/nada-numpy.git\n", - " os.chdir(\"nada-numpy/examples/linear_regression\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "QluoKNsev_7L" - }, - "source": [ - "# 2. Build Nada program" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rOUmgVosv_7L" - }, - "source": [ - "We will now build the Nada program specified under `src/linear_regression.py`\n", - "\n", - "You will see that it uses both our `nada-dsl` and `nada-numpy`." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "RT37dfFhv_7L", - "outputId": "14fd56cb-507c-46f9-b739-e42160135119" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Building program: \u001b[1m\u001b[32mdeterminant\u001b[39m\u001b[0m\n", - "\u001b[1;32mBuild complete!\u001b[0m\n", - "Building program: \u001b[1m\u001b[32mgauss_jordan\u001b[39m\u001b[0m\n", - "\u001b[1;32mBuild complete!\u001b[0m\n", - "Building program: \u001b[1m\u001b[32mmatrix_inverse\u001b[39m\u001b[0m\n", - "\u001b[1;32mBuild complete!\u001b[0m\n", - "Building program: \u001b[1m\u001b[32mlinear_regression_256\u001b[39m\u001b[0m\n", - "\u001b[1;32mBuild complete!\u001b[0m\n", - "Building program: \u001b[1m\u001b[32mmodular_inverse\u001b[39m\u001b[0m\n", - "\u001b[1;32mBuild complete!\u001b[0m\n", - "Building program: \u001b[1m\u001b[32mlinear_regression\u001b[39m\u001b[0m\n", - "\u001b[1;32mBuild complete!\u001b[0m\n" - ] - } - ], - "source": [ - "!nada build" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "TkWJ_oikv_7M", - "outputId": "bc0cb825-28d8-44ee-dbff-296902f070f8" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "linear_regression.nada.bin\n", - "linear_regression_256.nada.bin\n" - ] - } - ], - "source": [ - "# You will see that the program was compiled in a .nada.bin file\n", - "!ls target | grep linear_regression" - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "tOKatV-Av_7J" + }, + "source": [ + "# 👋 Welcome to Nillion's Nada Numpy Linear Regression Closed Form Training example" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "s1idKo5Rv_7K" + }, + "source": [ + "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NillionNetwork/nada-numpy/blob/main/examples/linear_regression/linear_regression.ipynb)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IeHr5pAHv_7K" + }, + "source": [ + "This notebook will get you familiar with linear regression closed-form training in `nada-numpy`, Nillion's data processing framework on top of the Nada dsl\n", + "\n", + "We are really excited for developers to build with our SDK, if you have any questions please do reach out to us on:\n", + "\n", + "[![Discord](https://img.shields.io/badge/Discord-nillionnetwork-%235865F2?logo=discord)](https://discord.gg/nillionnetwork)\n", + "[![GitHub Discussions](https://img.shields.io/badge/GitHub_Discussions-NillionNetwork-%23181717?logo=github)](https://github.com/orgs/NillionNetwork/discussions)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gcgBmJtPv_7K" + }, + "source": [ + "# 1. Set up environment" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vL85sjrzv_7K" + }, + "source": [ + "The boring part!\n", + "\n", + "Installs all required dependencies and spins up a local devnet that will run Nada programs" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, - { - "cell_type": "markdown", - "metadata": { - "id": "Y6uqc2ZJv_7M" - }, - "source": [ - "# 3. (optional) Test Nada program" - ] + "id": "o4PXBlE2v_7K", + "outputId": "57adf7cd-0d00-4463-b993-45b2d0f3f904" + }, + "outputs": [], + "source": [ + "%%capture\n", + "!pip install nada-numpy" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "rmTAavFov_7L" + }, + "outputs": [], + "source": [ + "import os\n", + "import time\n", + "import sys\n", + "import uuid" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Configure telemetry settings\n", + "enable_telemetry = True #@param {type:\"boolean\"}\n", + "my_github_username = \"your-github-username\" #@param {type:\"string\"}" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "GcsYIHINv_7L", + "outputId": "8089b90e-0f5a-471c-a6b2-ee00acb6b825" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "D0CCBvPhv_7M" - }, - "source": [ - "This step is optional but we can now test whether our newly compiled program behaves as expected!\n", - "\n", - "Under `tests/linear_regression.yaml`, you will see a test file with provided inputs and expected outputs. We will now test whether if we provide the program with those inputs, the program returns the expected outputs or not.\n", - "\n", - "*Note for the nerds: nada testing runs programs on a simulator instead of a network. This means that you can test programs without having a local devnet running!!*" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + " % Total % Received % Xferd Average Speed Time Time Time Current\n", + " Dload Upload Total Spent Left Speed\n", + "100 7810 100 7810 0 0 15569 0 --:--:-- --:--:-- --:--:-- 15557\n", + "\n", + "nilup has been installed into /home/vscode/.nilup/bin.\n", + "\n", + "$PATH is already up-to-date. You may begin using nilup now!\n", + "\n", + "By providing your Ethereum wallet address, you consent to the collection of telemetry data by the Nillion Network.\n", + "That includes but is not limited to\n", + "- The version of the SDK you are using\n", + "- The OS you are using\n", + "- The Processor Architecture you are using\n", + "- The SDK binary that you are running and the subcommand\n", + "- The wallet address you provided\n", + "- The errors produced by the SDK\n", + "We collect this data to understand how the software is used, and to better assist you in case of issues.\n", + "While we will not collect any personal information, we still recommend using a new wallet address that cannot be linked to your identity by any third party.\n", + "For more information, our privacy policy is available at https://nillion.com/privacy/.\n", + "Do you consent to the collection of telemetry data? (yes/no)\n", + "Telemetry data collection enabled\n", + "SDK version latest already installed\n", + "Reinstalling SDK version latest\n", + "Installing SDK bins version latest\n", + "Downloading latest/nillion-sdk-bins-aarch64-unknown-linux-musl.tar.gz\n", + "SDK version latest installed\n", + "SDK version latest set as default\n", + "SDK version latest already installed\n", + "Reinstalling SDK version latest\n", + "Installing SDK bins version latest\n", + "Downloading latest/nillion-sdk-bins-aarch64-unknown-linux-musl.tar.gz\n", + "SDK version latest installed\n", + "SDK version latest set as default\n" + ] + } + ], + "source": [ + "# Install the nilup tool and then use that to install the Nillion SDK\n", + "!curl https://nilup.nilogy.xyz/install.sh | bash\n", + "\n", + "# Update Path if ran in colab\n", + "if \"google.colab\" in sys.modules:\n", + " os.environ[\"PATH\"] += \":/root/.nilup/bin\"\n", + " os.environ[\"PATH\"] += \":/root/.nilup/sdks/latest/\"\n", + "\n", + "# Set telemetry if opted in\n", + "if enable_telemetry:\n", + " identifier = f\"nada-numpy-linear-regression-cf-{str(uuid.uuid4())}-{my_github_username}\"\n", + " !echo 'yes' | nilup instrumentation enable --wallet {identifier}\n", + "\n", + "# Install the lastest SDK and initialise it\n", + "!nilup init\n", + "!nilup install latest\n", + "!nilup use latest" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "L3CluM_vv_7L", + "outputId": "cb33ce5c-ec8c-4cf9-f8c2-5213145b6d19" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "PirYmsCTv_7M", - "outputId": "5bdba63c-6108-43da-eed5-ef547a4c9f85" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running test: \u001b[1m\u001b[32mgauss_jordan\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "gauss_jordan: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mmodular_inverse\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "modular_inverse: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mdeterminant-3\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "determinant-3: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mdeterminant_1\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "determinant_1: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mlinear_regression_256_1\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "linear_regression_256_1: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mlinear_regression_1\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "linear_regression_1: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mlinear_regression_2\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "linear_regression_2: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mlinear_regression_256_2\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "linear_regression_256_2: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mlinear_regression\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "linear_regression: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mdeterminant_2\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "determinant_2: \u001b[1;32mPASS\u001b[0m\n", - "\n", - "Running test: \u001b[1m\u001b[32mmatrix_inverse\u001b[39m\u001b[0m\n", - "Building ...\n", - "Running ...\n", - "matrix_inverse: \u001b[1;32mPASS\u001b[0m\n", - "\n" - ] - } - ], - "source": [ - "!nada test" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "ℹ️ cluster id is 9e68173f-9c23-4acc-ba81-4f079b639964\n", + "ℹ️ using 256 bit prime\n", + "ℹ️ storing state in /tmp/.tmphGXd3q (190.84Gbs available)\n", + "🏃 starting nilchain node in: /tmp/.tmphGXd3q/nillion-chain\n", + "⛓ nilchain JSON RPC available at http://127.0.0.1:48102\n", + "⛓ nilchain REST API available at http://localhost:26650\n", + "⛓ nilchain gRPC available at localhost:26649\n", + "🏃 starting node 12D3KooWMvw1hEqm7EWSDEyqTb6pNetUVkepahKY6hixuAuMZfJS\n", + "⏳ waiting until bootnode is up...\n", + "🏃 starting node 12D3KooWAiwGZUwSUaT2bYVxGS8jmfMrfsanZYkHwH3uL7WJPsFq\n", + "🏃 starting node 12D3KooWM3hsAswc7ZT6VpwQ1TCZU4GCYY55nLhcsxCcfjuixW57\n", + "👛 funding nilchain keys\n", + "📝 nillion CLI configuration written to /home/vscode/.config/nillion/nillion-cli.yaml\n", + "🌄 environment file written to /home/vscode/.config/nillion/nillion-devnet.env\n" + ] + } + ], + "source": [ + "# Spin up local Nillion devnet\n", + "os.system(\"nohup nillion-devnet &\")\n", + "\n", + "time.sleep(5) # Wait for devnet" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, - { - "cell_type": "markdown", - "metadata": { - "id": "xZUGIJWyv_7M" - }, - "source": [ - "# 4. Run Nada program" - ] + "id": "4teHBr6W5_Mz", + "outputId": "c7b02148-dcff-49f2-b255-f34c8ad3cd30" + }, + "outputs": [], + "source": [ + "if 'google.colab' in sys.modules:\n", + " # If ran in Colab, clone the nada-numpy repo and navigate to the correct directory\n", + " if not os.path.exists(\"nada-numpy\"):\n", + " !git clone https://github.com/NillionNetwork/nada-numpy.git\n", + " os.chdir(\"nada-numpy/examples/linear_regression\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "QluoKNsev_7L" + }, + "source": [ + "# 2. Build Nada program" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rOUmgVosv_7L" + }, + "source": [ + "We will now build the Nada program specified under `src/linear_regression.py`\n", + "\n", + "You will see that it uses both our `nada-dsl` and `nada-numpy`." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "RT37dfFhv_7L", + "outputId": "14fd56cb-507c-46f9-b739-e42160135119" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "UGiCRTDOv_7M" - }, - "source": [ - "The time has come to take our Nada program for a spin!\n", - "\n", - "You will see that `main.py` contains some python logic that wants to interface with our brand spanking new Nada program. It uses Nillion's Python SDK to store and run the program on a local devnet." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Building program: \u001b[1m\u001b[32mdeterminant\u001b[39m\u001b[0m\n", + "\u001b[1;32mBuild complete!\u001b[0m\n", + "Building program: \u001b[1m\u001b[32mgauss_jordan\u001b[39m\u001b[0m\n", + "\u001b[1;32mBuild complete!\u001b[0m\n", + "Building program: \u001b[1m\u001b[32mmatrix_inverse\u001b[39m\u001b[0m\n", + "\u001b[1;32mBuild complete!\u001b[0m\n", + "Building program: \u001b[1m\u001b[32mlinear_regression_256\u001b[39m\u001b[0m\n", + "\u001b[1;32mBuild complete!\u001b[0m\n", + "Building program: \u001b[1m\u001b[32mmodular_inverse\u001b[39m\u001b[0m\n", + "\u001b[1;32mBuild complete!\u001b[0m\n", + "Building program: \u001b[1m\u001b[32mlinear_regression\u001b[39m\u001b[0m\n", + "\u001b[1;32mBuild complete!\u001b[0m\n" + ] + } + ], + "source": [ + "!nada build" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "TkWJ_oikv_7M", + "outputId": "bc0cb825-28d8-44ee-dbff-296902f070f8" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "pg15Av1Fv_7M", - "outputId": "66158a03-a0df-41b9-84e1-68b965e6b162" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-----STORE PROGRAM\n", - "Getting quote for operation...\n", - "Submitting payment receipt 2 unil, tx hash 739B6965814F546C0BD863F11F46F6441A64579B6D4135D77DDA52085F77CE0D\n", - "Stored program. action_id: 3rgqxWd47e171EUwe4RXP9hm45tmoXfuF8fC52S7jcFoQTnU8wPiL7hqWzyV1muak6bEg7iWhudwg4t2pM9XnXcp/linear_regression_256\n", - "Stored program_id: 3rgqxWd47e171EUwe4RXP9hm45tmoXfuF8fC52S7jcFoQTnU8wPiL7hqWzyV1muak6bEg7iWhudwg4t2pM9XnXcp/linear_regression_256\n", - "-----STORE SECRETS\n", - "[[-256 -199 -142]\n", - " [ -85 -28 28]\n", - " [ 85 142 256]]\n", - "[-256 -199 -142]\n", - "Getting quote for operation...\n", - "Quote cost is 866 unil\n", - "Submitting payment receipt 866 unil, tx hash CE43BFB06691648708025CF7E62045275DA167690199F0966DA4957A84473582\n", - "Getting quote for operation...\n", - "Quote cost is 290 unil\n", - "Submitting payment receipt 290 unil, tx hash C75D3FD188EE5892744BFED97F134124BD68308491DCD4D39669F6D8757D12FF\n", - "-----COMPUTE\n", - "Getting quote for operation...\n", - "Quote cost is 251 unil\n", - "Submitting payment receipt 251 unil, tx hash 2EB3F5EA7514E835ED8185C875C514AB05E0B3FA448430A1DC89A60C2C80F618\n", - "✅ Compute complete for compute_id ca66680f-64c2-4e54-99ee-5ec022cbd65a\n", - "🖥️ The result is {'b': 330643400256, 'w_2': 1868226984, 'w_1': -993683999568, 'w_0': 1102041164640}\n", - "--------------------\n", - "🔍 Expected Coefficients: [ 3.33333333e+00 -3.00000000e+00 -2.09082751e-13]\n", - "✅ Coefficients: [ 3.3330203 -3.0053042 0.00565028]\n" - ] - } - ], - "source": [ - "!python3 main.py" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "linear_regression.nada.bin\n", + "linear_regression_256.nada.bin\n" + ] + } + ], + "source": [ + "# You will see that the program was compiled in a .nada.bin file\n", + "!ls target | grep linear_regression" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Y6uqc2ZJv_7M" + }, + "source": [ + "# 3. (optional) Test Nada program" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "D0CCBvPhv_7M" + }, + "source": [ + "This step is optional but we can now test whether our newly compiled program behaves as expected!\n", + "\n", + "Under `tests/linear_regression.yaml`, you will see a test file with provided inputs and expected outputs. We will now test whether if we provide the program with those inputs, the program returns the expected outputs or not.\n", + "\n", + "*Note for the nerds: nada testing runs programs on a simulator instead of a network. This means that you can test programs without having a local devnet running!!*" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "PirYmsCTv_7M", + "outputId": "5bdba63c-6108-43da-eed5-ef547a4c9f85" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "Xsjs6dTlv_7M" - }, - "source": [ - "Excuse my French but voilà, we did it!!\n", - "\n", - "To recap, in this example we:\n", - "- Set up and installed all necessary Nillion libraries and dependencies.\n", - "- Created and built a Nada program using Nillion's `nada-dsl` and the `nada-numpy` library.\n", - "- Tested the behaviour of the Nada program.\n", - "- Ran a Python script that ran a Nada program on a local devnet using Nillion's `py_nillion_client`." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Running test: \u001b[1m\u001b[32mgauss_jordan\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "gauss_jordan: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mmodular_inverse\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "modular_inverse: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mdeterminant-3\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "determinant-3: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mdeterminant_1\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "determinant_1: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mlinear_regression_256_1\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "linear_regression_256_1: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mlinear_regression_1\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "linear_regression_1: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mlinear_regression_2\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "linear_regression_2: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mlinear_regression_256_2\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "linear_regression_256_2: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mlinear_regression\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "linear_regression: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mdeterminant_2\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "determinant_2: \u001b[1;32mPASS\u001b[0m\n", + "\n", + "Running test: \u001b[1m\u001b[32mmatrix_inverse\u001b[39m\u001b[0m\n", + "Building ...\n", + "Running ...\n", + "matrix_inverse: \u001b[1;32mPASS\u001b[0m\n", + "\n" + ] } - ], - "metadata": { + ], + "source": [ + "!nada test" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xZUGIJWyv_7M" + }, + "source": [ + "# 4. Run Nada program" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UGiCRTDOv_7M" + }, + "source": [ + "The time has come to take our Nada program for a spin!\n", + "\n", + "You will see that `main.py` contains some python logic that wants to interface with our brand spanking new Nada program. It uses Nillion's Python SDK to store and run the program on a local devnet." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { "colab": { - "provenance": [] + "base_uri": "https://localhost:8080/" }, - "kernelspec": { - "display_name": "venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.2" + "id": "pg15Av1Fv_7M", + "outputId": "66158a03-a0df-41b9-84e1-68b965e6b162" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-----STORE PROGRAM\n", + "Getting quote for operation...\n", + "Submitting payment receipt 2 unil, tx hash 739B6965814F546C0BD863F11F46F6441A64579B6D4135D77DDA52085F77CE0D\n", + "Stored program. action_id: 3rgqxWd47e171EUwe4RXP9hm45tmoXfuF8fC52S7jcFoQTnU8wPiL7hqWzyV1muak6bEg7iWhudwg4t2pM9XnXcp/linear_regression_256\n", + "Stored program_id: 3rgqxWd47e171EUwe4RXP9hm45tmoXfuF8fC52S7jcFoQTnU8wPiL7hqWzyV1muak6bEg7iWhudwg4t2pM9XnXcp/linear_regression_256\n", + "-----STORE SECRETS\n", + "[[-256 -199 -142]\n", + " [ -85 -28 28]\n", + " [ 85 142 256]]\n", + "[-256 -199 -142]\n", + "Getting quote for operation...\n", + "Quote cost is 866 unil\n", + "Submitting payment receipt 866 unil, tx hash CE43BFB06691648708025CF7E62045275DA167690199F0966DA4957A84473582\n", + "Getting quote for operation...\n", + "Quote cost is 290 unil\n", + "Submitting payment receipt 290 unil, tx hash C75D3FD188EE5892744BFED97F134124BD68308491DCD4D39669F6D8757D12FF\n", + "-----COMPUTE\n", + "Getting quote for operation...\n", + "Quote cost is 251 unil\n", + "Submitting payment receipt 251 unil, tx hash 2EB3F5EA7514E835ED8185C875C514AB05E0B3FA448430A1DC89A60C2C80F618\n", + "✅ Compute complete for compute_id ca66680f-64c2-4e54-99ee-5ec022cbd65a\n", + "🖥️ The result is {'b': 330643400256, 'w_2': 1868226984, 'w_1': -993683999568, 'w_0': 1102041164640}\n", + "--------------------\n", + "🔍 Expected Coefficients: [ 3.33333333e+00 -3.00000000e+00 -2.09082751e-13]\n", + "✅ Coefficients: [ 3.3330203 -3.0053042 0.00565028]\n" + ] } + ], + "source": [ + "!python3 main.py" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Xsjs6dTlv_7M" + }, + "source": [ + "Excuse my French but voilà, we did it!!\n", + "\n", + "To recap, in this example we:\n", + "- Set up and installed all necessary Nillion libraries and dependencies.\n", + "- Created and built a Nada program using Nillion's `nada-dsl` and the `nada-numpy` library.\n", + "- Tested the behaviour of the Nada program.\n", + "- Ran a Python script that ran a Nada program on a local devnet using Nillion's `py_nillion_client`." + ] + } + ], + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 0 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.15" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/examples/linear_regression/main.py b/examples/linear_regression/main.py index d1a185e..d4e313d 100644 --- a/examples/linear_regression/main.py +++ b/examples/linear_regression/main.py @@ -1,23 +1,14 @@ """Linear Regression example script""" -import os -import sys - -sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) - import asyncio +import os import numpy as np -import py_nillion_client as nillion -from common.utils import compute, store_program, store_secret_array -from cosmpy.aerial.client import LedgerClient -from cosmpy.aerial.wallet import LocalWallet -from cosmpy.crypto.keypairs import PrivateKey +import pytest from dotenv import load_dotenv -from nillion_python_helpers import (create_nillion_client, - create_payments_config, get_quote, - get_quote_and_pay, pay_with_quote) -from py_nillion_client import NodeKey, UserKey +from nillion_client import (InputPartyBinding, Network, NilChainPayer, + NilChainPrivateKey, OutputPartyBinding, + Permissions, PrivateKey, SecretInteger, VmClient) from sklearn.linear_model import Ridge import nada_numpy.client as na_client @@ -26,49 +17,42 @@ load_dotenv(f"{home}/.config/nillion/nillion-devnet.env") -# Main asynchronous function to coordinate the process -async def main() -> None: - """Main nada program""" +# 1 Party running simple addition on 1 stored secret and 1 compute time secret +async def main(): + # Use the devnet configuration generated by `nillion-devnet` + network = Network.from_config("devnet") - cluster_id = os.getenv("NILLION_CLUSTER_ID") - grpc_endpoint = os.getenv("NILLION_NILCHAIN_GRPC") - chain_id = os.getenv("NILLION_NILCHAIN_CHAIN_ID") - seed = "my_seed" - userkey = UserKey.from_seed((seed)) - nodekey = NodeKey.from_seed((seed)) - client = create_nillion_client(userkey, nodekey) - party_id = client.party_id - user_id = client.user_id + # Create payments config and set up Nillion wallet with a private key to pay for operations + nilchain_key: str = os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0") # type: ignore + payer = NilChainPayer( + network, + wallet_private_key=NilChainPrivateKey(bytes.fromhex(nilchain_key)), + gas_limit=10000000, + ) + # Use a random key to identify ourselves + signing_key = PrivateKey() + client = await VmClient.create(signing_key, network, payer) party_names = na_client.parties(3) program_name = "linear_regression_256" program_mir_path = f"target/{program_name}.nada.bin" - # Create payments config and set up Nillion wallet with a private key to pay for operations - payments_config = create_payments_config(chain_id, grpc_endpoint) - payments_client = LedgerClient(payments_config) - payments_wallet = LocalWallet( - PrivateKey(bytes.fromhex(os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0"))), - prefix="nillion", - ) - ##### STORE PROGRAM print("-----STORE PROGRAM") - program_id = await store_program( - client, - payments_wallet, - payments_client, - user_id, - cluster_id, - program_name, - program_mir_path, - ) + # Store program + program_mir = open( + os.path.join(os.path.dirname(os.path.abspath(__file__)), program_mir_path), "rb" + ).read() + program_id = await client.store_program(program_name, program_mir).invoke() + + # Print details about stored program + print(f"Stored program_id: {program_id}") ##### STORE SECRETS - print("-----STORE SECRETS") + print("-----STORE SECRETS Party 0") - # Input data + # Create a secret A = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 10.0]]) b = np.array([1.0, 2.0, 3.0]) @@ -89,70 +73,62 @@ async def main() -> None: A = np.round(A * SCALE).astype(np.int64) b = np.round(b * SCALE).astype(np.int64) - print(A) - print(b) + A = na_client.array(A, "A", SecretInteger) + b = na_client.array(b, "b", SecretInteger) # Create a permissions object to attach to the stored secret - permissions = nillion.Permissions.default_for_user(client.user_id) - permissions.add_compute_permissions({client.user_id: {program_id}}) - - # Create a secret - store_id_A = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - A, - "A", - nillion.SecretInteger, - 1, - permissions, + permissions = Permissions.defaults_for_user(client.user_id).allow_compute( + client.user_id, program_id ) - # Create and store secrets for two parties - store_id_B = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - b, - "b", - nillion.SecretInteger, - 1, - permissions, - ) + # Store a secret, passing in the receipt that shows proof of payment + values_A = await client.store_values( + A, ttl_days=5, permissions=permissions + ).invoke() + + print("Stored values_A: ", values_A) + + # Store a secret, passing in the receipt that shows proof of payment + values_B = await client.store_values( + b, ttl_days=5, permissions=permissions + ).invoke() + + print("Stored values_B: ", values_B) ##### COMPUTE print("-----COMPUTE") # Bind the parties in the computation to the client to set input and output parties - compute_bindings = nillion.ProgramBindings(program_id) - compute_bindings.add_input_party(party_names[0], party_id) - compute_bindings.add_input_party(party_names[1], party_id) - compute_bindings.add_output_party(party_names[2], party_id) + input_bindings = [ + InputPartyBinding(party_names[0], client.user_id), + InputPartyBinding(party_names[1], client.user_id), + ] + output_bindings = [OutputPartyBinding(party_names[2], [client.user_id])] # Create a computation time secret to use - computation_time_secrets = nillion.NadaValues({}) - - # Get cost quote, then pay for operation to compute + compute_time_values = { + # "my_int2": SecretInteger(10) + } - result = await compute( - client, - payments_wallet, - payments_client, - program_id, - cluster_id, - compute_bindings, - [store_id_A, store_id_B], - computation_time_secrets, - verbose=1, + # Compute, passing in the compute time values as well as the previously uploaded value. + print( + f"Invoking computation using program {program_id} and values id {values_A}, {values_B}" ) + compute_id = await client.compute( + program_id, + input_bindings, + output_bindings, + values=compute_time_values, + value_ids=[values_A, values_B], + ).invoke() + + # Print compute result + print(f"The computation was sent to the network. compute_id: {compute_id}") + result = await client.retrieve_compute_results(compute_id).invoke() - w_0 = result["w_0"] - w_1 = result["w_1"] - w_2 = result["w_2"] - b = result["b"] + w_0 = result["w_0"].value + w_1 = result["w_1"].value + w_2 = result["w_2"].value + b = result["b"].value coeff = np.array([w_0, w_1, w_2]) / b @@ -162,6 +138,5 @@ async def main() -> None: return coeff -# Run the main function if the script is executed directly if __name__ == "__main__": asyncio.run(main()) diff --git a/examples/linear_regression/src/matrix_inverse.py b/examples/linear_regression/src/matrix_inverse.py index 8e50d01..b8e5931 100644 --- a/examples/linear_regression/src/matrix_inverse.py +++ b/examples/linear_regression/src/matrix_inverse.py @@ -133,7 +133,7 @@ def gauss_jordan_zn(mat: na.NadaArray, modulo: int): # Forward elimination for i in range(rows): - + # Scale pivot row to have leading 1 diagonal_element = mat[i][i] pivot_inv = public_modular_inverse(diagonal_element, modulo) diff --git a/examples/linear_regression/tests/matrix_inverse.py b/examples/linear_regression/tests/matrix_inverse.py index 9ab7832..54787f8 100644 --- a/examples/linear_regression/tests/matrix_inverse.py +++ b/examples/linear_regression/tests/matrix_inverse.py @@ -1,7 +1,10 @@ -from nada_test import nada_test, NadaTest import sys -import nada_numpy.client as na + import numpy as np +from nada_test import NadaTest, nada_test + +import nada_numpy.client as na + # Functional style test @nada_test(program="matrix_inverse") @@ -20,5 +23,5 @@ def my_test(): assert value == 1, f"Expected 1 {output}, got {value}" else: assert value == 0, f"Expected 0 {output}, got {value}" - - #assert outputs["my_output"] == a + b \ No newline at end of file + + # assert outputs["my_output"] == a + b diff --git a/examples/matrix_multiplication/main.py b/examples/matrix_multiplication/main.py index 63f020d..c3712c4 100644 --- a/examples/matrix_multiplication/main.py +++ b/examples/matrix_multiplication/main.py @@ -1,24 +1,15 @@ """Matrix Multiplication example script""" -import os -import sys - -sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) - import asyncio +import os import numpy as np -import py_nillion_client as nillion -from common.utils import compute, store_program, store_secret_array +import pytest from config import DIM -from cosmpy.aerial.client import LedgerClient -from cosmpy.aerial.wallet import LocalWallet -from cosmpy.crypto.keypairs import PrivateKey from dotenv import load_dotenv -from nillion_python_helpers import (create_nillion_client, - create_payments_config, get_quote, - get_quote_and_pay, pay_with_quote) -from py_nillion_client import NodeKey, UserKey +from nillion_client import (InputPartyBinding, Network, NilChainPayer, + NilChainPrivateKey, OutputPartyBinding, + Permissions, PrivateKey, SecretInteger, VmClient) import nada_numpy.client as na_client @@ -26,113 +17,107 @@ load_dotenv(f"{home}/.config/nillion/nillion-devnet.env") -# Main asynchronous function to coordinate the process -async def main() -> None: - """Main nada program""" +# 1 Party running simple addition on 1 stored secret and 1 compute time secret +async def main(): + # Use the devnet configuration generated by `nillion-devnet` + network = Network.from_config("devnet") - cluster_id = os.getenv("NILLION_CLUSTER_ID") - grpc_endpoint = os.getenv("NILLION_NILCHAIN_GRPC") - chain_id = os.getenv("NILLION_NILCHAIN_CHAIN_ID") - seed = "my_seed" - userkey = UserKey.from_seed((seed)) - nodekey = NodeKey.from_seed((seed)) - client = create_nillion_client(userkey, nodekey) - party_id = client.party_id - user_id = client.user_id + # Create payments config and set up Nillion wallet with a private key to pay for operations + nilchain_key: str = os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0") # type: ignore + payer = NilChainPayer( + network, + wallet_private_key=NilChainPrivateKey(bytes.fromhex(nilchain_key)), + gas_limit=10000000, + ) + # Use a random key to identify ourselves + signing_key = PrivateKey() + client = await VmClient.create(signing_key, network, payer) party_names = na_client.parties(3) program_name = "matrix_multiplication" - program_mir_path = f"target/{program_name}.nada.bin" - - # Create payments config and set up Nillion wallet with a private key to pay for operations - payments_config = create_payments_config(chain_id, grpc_endpoint) - payments_client = LedgerClient(payments_config) - payments_wallet = LocalWallet( - PrivateKey(bytes.fromhex(os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0"))), - prefix="nillion", - ) + program_mir_path = f"./target/{program_name}.nada.bin" ##### STORE PROGRAM print("-----STORE PROGRAM") - program_id = await store_program( - client, - payments_wallet, - payments_client, - user_id, - cluster_id, - program_name, - program_mir_path, - ) + # Store program + program_mir = open( + os.path.join(os.path.dirname(os.path.abspath(__file__)), program_mir_path), "rb" + ).read() + program_id = await client.store_program(program_name, program_mir).invoke() - ##### STORE SECRETS - print("-----STORE SECRETS") - A = np.ones(DIM) + # Print details about stored program + print(f"Stored program_id: {program_id}") - # Create a permissions object to attach to the stored secret - permissions = nillion.Permissions.default_for_user(client.user_id) - permissions.add_compute_permissions({client.user_id: {program_id}}) + ##### STORE SECRETS + print("-----STORE SECRETS Party 0") # Create a secret - store_id_A = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - A, - "A", - nillion.SecretInteger, - 1, - permissions, + A = na_client.array(np.ones(DIM), "A", SecretInteger) + + # Create a permissions object to attach to the stored secret + permissions = Permissions.defaults_for_user(client.user_id).allow_compute( + client.user_id, program_id ) - # Create and store secrets for two parties + # Store a secret, passing in the receipt that shows proof of payment + values_A = await client.store_values( + A, ttl_days=5, permissions=permissions + ).invoke() - B = np.ones(DIM) + print("Stored values_A: ", values_A) - store_id_B = await store_secret_array( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - B, - "B", - nillion.SecretInteger, - 1, - permissions, + print("-----STORE SECRETS Party 1") + + # Create a secret + B = na_client.array(np.ones(DIM), "B", SecretInteger) + + # Create a permissions object to attach to the stored secret + permissions = Permissions.defaults_for_user(client.user_id).allow_compute( + client.user_id, program_id ) + # Store a secret, passing in the receipt that shows proof of payment + values_B = await client.store_values( + B, ttl_days=5, permissions=permissions + ).invoke() + + print("Stored values_B: ", values_B) + ##### COMPUTE print("-----COMPUTE") # Bind the parties in the computation to the client to set input and output parties - compute_bindings = nillion.ProgramBindings(program_id) - compute_bindings.add_input_party(party_names[0], party_id) - compute_bindings.add_input_party(party_names[1], party_id) - compute_bindings.add_output_party(party_names[2], party_id) + input_bindings = [ + InputPartyBinding(party_names[0], client.user_id), + InputPartyBinding(party_names[1], client.user_id), + ] + output_bindings = [OutputPartyBinding(party_names[2], [client.user_id])] # Create a computation time secret to use - computation_time_secrets = nillion.NadaValues({}) - - # Get cost quote, then pay for operation to compute + compute_time_values = { + # "my_int2": SecretInteger(10) + } - result = await compute( - client, - payments_wallet, - payments_client, - program_id, - cluster_id, - compute_bindings, - [store_id_A, store_id_B], - computation_time_secrets, - verbose=1, + # Compute, passing in the compute time values as well as the previously uploaded value. + print( + f"Invoking computation using program {program_id} and values id {values_A}, {values_B}" ) - + compute_id = await client.compute( + program_id, + input_bindings, + output_bindings, + values=compute_time_values, + value_ids=[values_A, values_B], + ).invoke() + + # Print compute result + print(f"The computation was sent to the network. compute_id: {compute_id}") + result = await client.retrieve_compute_results(compute_id).invoke() + print(f"✅ Compute complete for compute_id {compute_id}") + print(f"🖥️ The result is {result}") return result -# Run the main function if the script is executed directly if __name__ == "__main__": asyncio.run(main()) diff --git a/examples/rational_numbers/main.py b/examples/rational_numbers/main.py index 3746b35..3814a20 100644 --- a/examples/rational_numbers/main.py +++ b/examples/rational_numbers/main.py @@ -1,22 +1,14 @@ """Broadcasting example script""" -import os -import sys - -sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) - import asyncio +import os import numpy as np -import py_nillion_client as nillion -from common.utils import compute, store_program, store_secret_value -from cosmpy.aerial.client import LedgerClient -from cosmpy.aerial.wallet import LocalWallet -from cosmpy.crypto.keypairs import PrivateKey +import pytest from dotenv import load_dotenv -from nillion_python_helpers import (create_nillion_client, - create_payments_config) -from py_nillion_client import NodeKey, UserKey +from nillion_client import (InputPartyBinding, Network, NilChainPayer, + NilChainPrivateKey, OutputPartyBinding, + Permissions, PrivateKey, SecretInteger, VmClient) import nada_numpy.client as na_client @@ -24,116 +16,98 @@ load_dotenv(f"{home}/.config/nillion/nillion-devnet.env") -# Main asynchronous function to coordinate the process -async def main() -> None: - """Main nada program""" +# 1 Party running simple addition on 1 stored secret and 1 compute time secret +async def main(): + # Use the devnet configuration generated by `nillion-devnet` + network = Network.from_config("devnet") - cluster_id = os.getenv("NILLION_CLUSTER_ID") - grpc_endpoint = os.getenv("NILLION_NILCHAIN_GRPC") - chain_id = os.getenv("NILLION_NILCHAIN_CHAIN_ID") - seed = "my_seed" - userkey = UserKey.from_seed((seed)) - nodekey = NodeKey.from_seed((seed)) - client = create_nillion_client(userkey, nodekey) - party_id = client.party_id - user_id = client.user_id + # Create payments config and set up Nillion wallet with a private key to pay for operations + nilchain_key: str = os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0") # type: ignore + payer = NilChainPayer( + network, + wallet_private_key=NilChainPrivateKey(bytes.fromhex(nilchain_key)), + gas_limit=10000000, + ) + # Use a random key to identify ourselves + signing_key = PrivateKey() + client = await VmClient.create(signing_key, network, payer) party_names = na_client.parties(3) program_name = "rational_numbers" - program_mir_path = f"target/{program_name}.nada.bin" - - # Create payments config and set up Nillion wallet with a private key to pay for operations - payments_config = create_payments_config(chain_id, grpc_endpoint) - payments_client = LedgerClient(payments_config) - payments_wallet = LocalWallet( - PrivateKey(bytes.fromhex(os.getenv("NILLION_NILCHAIN_PRIVATE_KEY_0"))), - prefix="nillion", - ) + program_mir_path = f"./target/{program_name}.nada.bin" ##### STORE PROGRAM print("-----STORE PROGRAM") - program_id = await store_program( - client, - payments_wallet, - payments_client, - user_id, - cluster_id, - program_name, - program_mir_path, - ) + # Store program + program_mir = open( + os.path.join(os.path.dirname(os.path.abspath(__file__)), program_mir_path), "rb" + ).read() + program_id = await client.store_program(program_name, program_mir).invoke() + + # Print details about stored program + print(f"Stored program_id: {program_id}") ##### STORE SECRETS print("-----STORE SECRETS") - A = 3.2 + my_input_0 = {"my_input_0": na_client.secret_rational(3.2)} # Create a permissions object to attach to the stored secret - permissions = nillion.Permissions.default_for_user(client.user_id) - permissions.add_compute_permissions({client.user_id: {program_id}}) - - # Create a secret - store_id_A = await store_secret_value( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - A, - "my_input_0", - na_client.SecretRational, - 1, - permissions, + permissions = Permissions.defaults_for_user(client.user_id).allow_compute( + client.user_id, program_id ) - # Create and store secrets for two parties + # Store a secret, passing in the receipt that shows proof of payment + values_0 = await client.store_values( + my_input_0, ttl_days=5, permissions=permissions + ).invoke() - B = 2.3 + print("Stored values_0: ", values_0) - store_id_B = await store_secret_value( - client, - payments_wallet, - payments_client, - cluster_id, - program_id, - B, - "my_input_1", - na_client.SecretRational, - 1, - permissions, - ) + my_input_1 = {"my_input_1": na_client.secret_rational(2.3)} + # Store a secret, passing in the receipt that shows proof of payment + values_1 = await client.store_values( + my_input_1, ttl_days=5, permissions=permissions + ).invoke() + + print("Stored values_1: ", values_1) ##### COMPUTE print("-----COMPUTE") # Bind the parties in the computation to the client to set input and output parties - compute_bindings = nillion.ProgramBindings(program_id) - compute_bindings.add_input_party(party_names[0], party_id) - compute_bindings.add_input_party(party_names[1], party_id) - compute_bindings.add_output_party(party_names[2], party_id) + input_bindings = [ + InputPartyBinding(party_names[0], client.user_id), + InputPartyBinding(party_names[1], client.user_id), + ] + output_bindings = [OutputPartyBinding(party_names[2], [client.user_id])] # Create a computation time secret to use - computation_time_secrets = nillion.NadaValues({}) - - # Get cost quote, then pay for operation to compute + compute_time_values = { + # "my_int2": SecretInteger(10) + } - result = await compute( - client, - payments_wallet, - payments_client, - program_id, - cluster_id, - compute_bindings, - [store_id_A, store_id_B], - computation_time_secrets, - verbose=1, + # Compute, passing in the compute time values as well as the previously uploaded value. + print( + f"Invoking computation using program {program_id} and values id {values_0}, {values_1}" ) - output = na_client.float_from_rational(result["my_output"]) - print("✅ Compute complete") - print("🖥️ The result is", output) - return output + compute_id = await client.compute( + program_id, + input_bindings, + output_bindings, + values=compute_time_values, + value_ids=[values_0, values_1], + ).invoke() + + # Print compute result + print(f"The computation was sent to the network. compute_id: {compute_id}") + result = await client.retrieve_compute_results(compute_id).invoke() + + output = na_client.float_from_rational(result["my_output"].value) + print(f"✅ Compute complete for compute_id {compute_id}") + print(f"🖥️ The result is {output}") return result -# Run the main function if the script is executed directly if __name__ == "__main__": asyncio.run(main()) diff --git a/nada_numpy/client.py b/nada_numpy/client.py index 4394057..80ef20d 100644 --- a/nada_numpy/client.py +++ b/nada_numpy/client.py @@ -7,8 +7,8 @@ import numpy as np # pylint:disable=no-name-in-module -from py_nillion_client import (Integer, SecretInteger, SecretUnsignedInteger, - UnsignedInteger) +from nillion_client import (Integer, SecretInteger, SecretUnsignedInteger, + UnsignedInteger) from nada_numpy.types import Rational, SecretRational, get_log_scale @@ -66,6 +66,7 @@ def array( nada_type = public_rational # type: ignore elif nada_type == SecretRational: nada_type = secret_rational # type: ignore + arr = np.round(arr) return { f"{prefix}_{i}": (nada_type(int(arr[i]))) for i in range(arr.shape[0]) # type: ignore } diff --git a/nada_numpy/legacy_client.py b/nada_numpy/legacy_client.py new file mode 100644 index 0000000..b1281b5 --- /dev/null +++ b/nada_numpy/legacy_client.py @@ -0,0 +1,155 @@ +""" +This module provides functions to work with the Python Nillion Client for handling +secret and public variable integers and generating named party objects and input dictionaries. +""" + +# pylint:disable=R0801 + +import logging +from typing import Dict, List, Optional, Union + +import numpy as np +# pylint:disable=no-name-in-module +from py_nillion_client import (Integer, SecretInteger, SecretUnsignedInteger, + UnsignedInteger) + +from nada_numpy.types import Rational, SecretRational, get_log_scale + +logging.warning( + "[DEPRECATED] The legacy_client module is deprecated" + "and will be removed in a future release." + "Use nada-numpy.client instead." +) + +__all__ = [ + "parties", + "array", + "concat", + "public_rational", + "secret_rational", + "float_from_rational", +] + + +def parties(num: int, prefix: str = "Party") -> List: + """ + Creates a list of party name strings. + + Args: + num (int): The number of parties to create. + prefix (str, optional): The prefix to use for party names. Defaults to "Party". + + Returns: + List: A list of party name strings in the format "{prefix}{i}". + """ + return [f"{prefix}{i}" for i in range(num)] + + +def array( + arr: np.ndarray, + prefix: str, + nada_type: Union[ + SecretInteger, + SecretUnsignedInteger, + Integer, + UnsignedInteger, + Rational, + SecretRational, + ], +) -> Dict: + """ + Recursively generates a dictionary of Nillion input objects for each element + in the given array. + + Args: + arr (np.ndarray): The input array. + prefix (str): The prefix to be added to the output names. + nada_type (type): The type of the values introduced. + + Returns: + Dict: A dictionary mapping generated names to Nillion input objects. + """ + # TODO: Use this version when check for zero values is removed + if len(arr.shape) == 1: + if nada_type == Rational: + nada_type = public_rational # type: ignore + elif nada_type == SecretRational: + nada_type = secret_rational # type: ignore + return { + f"{prefix}_{i}": (nada_type(int(arr[i]))) for i in range(arr.shape[0]) # type: ignore + } + return { + k: v + for i in range(arr.shape[0]) + for k, v in array(arr[i], f"{prefix}_{i}", nada_type).items() + } + + +def concat(list_dict: List[Dict]) -> Dict: + """ + Combines a list of dictionaries into a single dictionary. + + Note: This function will overwrite values for duplicate keys. + + Args: + list_dict (List[Dict]): A list of dictionaries. + + Returns: + Dict: A single merged dictionary. + """ + return {k: v for d in list_dict for k, v in d.items()} + + +def __rational(value: Union[float, int]) -> int: + """ + Returns the integer representation of the given float value. + + Args: + value (Union[float, int]): The input value. + + Returns: + int: The integer representation of the input value. + """ + return round(value * (1 << get_log_scale())) + + +def public_rational(value: Union[float, int]) -> Integer: + """ + Returns the integer representation of the given float value. + + Args: + value (Union[float, int]): The input value. + + Returns: + int: The integer representation of the input value. + """ + return Integer(__rational(value)) + + +def secret_rational(value: Union[float, int]) -> SecretInteger: + """ + Returns the integer representation of the given float value. + + Args: + value (Union[float, int]): The input value. + + Returns: + int: The integer representation of the input value. + """ + return SecretInteger(__rational(value)) + + +def float_from_rational(value: int, log_scale: Optional[int] = None) -> float: + """ + Returns the float representation of the given rational value. + + Args: + value (int): The output Rational value to convert. + log_scale (int, optional): The log scale to use for conversion. Defaults to None. + + Returns: + float: The float representation of the input value. + """ + if log_scale is None: + log_scale = get_log_scale() + return value / (1 << log_scale) diff --git a/nada_numpy/types.py b/nada_numpy/types.py index 84bf6b8..085ffc1 100644 --- a/nada_numpy/types.py +++ b/nada_numpy/types.py @@ -24,7 +24,7 @@ ] -class SecretBoolean(dsl.SecretBoolean): # pylint:disable=too-many-ancestors +class SecretBoolean(dsl.SecretBoolean): # pylint:disable=too-many-ancestors """SecretBoolean rational wrapper""" def __init__(self, value: dsl.SecretBoolean) -> None: @@ -80,7 +80,7 @@ def if_else( return result -class PublicBoolean(dsl.PublicBoolean): # pylint:disable=too-many-ancestors +class PublicBoolean(dsl.PublicBoolean): # pylint:disable=too-many-ancestors """PublicBoolean rational wrapper""" def __init__(self, value: dsl.PublicBoolean) -> None: diff --git a/poetry.lock b/poetry.lock index eab3b84..d856aa7 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,14 +1,14 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. 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+[package.extras] +doc = ["reno", "sphinx"] +test = ["pytest", "tornado (>=4.5)", "typeguard"] + [[package]] name = "threadpoolctl" version = "3.5.0" @@ -1182,13 +1735,13 @@ files = [ [[package]] name = "tomli" -version = "2.0.1" +version = "2.1.0" description = "A lil' TOML parser" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"}, - {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"}, + {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"}, + {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"}, ] [[package]] @@ -1237,4 +1790,4 @@ linter = ["black", "isort"] [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "2a8caf5f826dcc51363c5ee9f6c5e82452dfe780d95b2e4e487e3ef61eac32ad" +content-hash = "10578a1b9b8334d823fb36f21fea28a7c0bef0438d13b4ff1c5fb12d8655d5cf" diff --git a/pyproject.toml b/pyproject.toml index efae330..e9f4f30 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "nada-numpy" -version = "0.5.3" +version = "0.6.0" description = "Nada-Numpy is a Python library designed for algebraic operations on NumPy-like array objects on top of Nada DSL and Nillion Network." authors = ["José Cabrero-Holgueras "] readme = "README.md" @@ -8,13 +8,14 @@ readme = "README.md" [tool.poetry.dependencies] python = "^3.10" numpy = "^1.26.4" -nada-dsl = "^0.6.3" +nada-dsl = "^0.7.1" py-nillion-client = "^0.6.0" nillion-python-helpers = "^0.3.0" black = {version="24.8.0", optional=true} isort = {version="^5.13.2", optional=true} scikit-learn = {version="^1.5.1", optional=true} nada-test = "^0.6.0" +nillion-client = "^0.1.0" [tool.poetry.group.dev.dependencies] pytest = "^8.2.0" diff --git a/tests/nada-tests/src/array_matrix_inverse.py b/tests/nada-tests/src/array_matrix_inverse.py new file mode 100644 index 0000000..08b3145 --- /dev/null +++ b/tests/nada-tests/src/array_matrix_inverse.py @@ -0,0 +1,14 @@ +from nada_dsl import * + +import nada_numpy as na + + +def nada_main(): + parties = na.parties(2) + + a = na.array([3, 3], parties[0], "A", SecretInteger) + + a_inv = a.inv() + res = a @ a_inv + + return res.output(parties[1], "my_output") diff --git a/tests/nada-tests/src/base.py b/tests/nada-tests/src/base.py index 951f8f5..53b73d1 100644 --- a/tests/nada-tests/src/base.py +++ b/tests/nada-tests/src/base.py @@ -1,13 +1,46 @@ +import numpy as np from nada_dsl import * import nada_numpy as na +DIM1 = 10 +DIM2 = 4 +DIM3 = 7 + +DIM4 = DIM1 + DIM2 + DIM3 + + +def bubble_sort(array: na.NadaArray): + size = DIM4 + for i in range(size): + for j in range(0, size - i - 1): + condition = array[j] > array[j + 1] + res1 = condition.if_else(array[j + 1], array[j]) + res2 = condition.if_else(array[j], array[j + 1]) + array[j] = res1 + array[j + 1] = res2 + def nada_main(): - parties = na.parties(2) + party1 = Party(name="Party1") + party1 = Party(name="Party2") + party1 = Party(name="Party3") + party4 = Party(name="Party4") + + array1 = na.array([DIM1], party1, "array1", SecretInteger) + array2 = na.array([DIM2], party1, "array2", SecretInteger) + array3 = na.array([DIM3], party1, "array3", SecretInteger) + + array4 = np.concatenate((np.concatenate((array1, array2)), array3)) + + bubble_sort(array4) + + outs = [] + for i in range(DIM4): + outs.append(Output(array4[i], "out_array_" + str(i), party4)) - a = na.array([3], parties[0], "A", SecretInteger) + return outs - a += Integer(0) - return a.output(parties[1], "my_output") +if __name__ == "__main__": + nada_main() diff --git a/tests/nada-tests/src/reveal.py b/tests/nada-tests/src/reveal.py index 67e52df..71a4351 100644 --- a/tests/nada-tests/src/reveal.py +++ b/tests/nada-tests/src/reveal.py @@ -20,11 +20,6 @@ def nada_main(): assert d.dtype == NadaRational, d.dtype assert d.shape == b.shape - with pytest.raises(Exception): - c.to_public() - with pytest.raises(Exception): - d.to_public() - return na.output(c, parties[2], "my_output_A") + na.output( d, parties[2], "my_output_B" ) diff --git a/tests/nada-tests/tests/base.yaml b/tests/nada-tests/tests/base.yaml index 668096c..b679bcf 100644 --- a/tests/nada-tests/tests/base.yaml +++ b/tests/nada-tests/tests/base.yaml @@ -1,9 +1,49 @@ +--- program: base inputs: - A_1: 3 - A_2: 3 - A_0: 3 + array1_0: 5 + array1_1: 3 + array1_2: 42 + array1_3: -12 + array1_4: 3 + array1_5: 1 + array1_6: -5 + array1_7: 3 + array1_8: 1 + array1_9: 23 + + array2_0: 1 + array2_1: 2 + array2_2: -52 + array2_3: 11 + + array3_0: 53 + array3_1: 2 + array3_2: 15 + array3_3: 37 + array3_4: -1 + array3_5: 1 + array3_6: -2 + expected_outputs: - my_output_0: 3 - my_output_1: 3 - my_output_2: 3 + out_array_0: -52 + out_array_1: -12 + out_array_2: -5 + out_array_3: -2 + out_array_4: -1 + out_array_5: 1 + out_array_6: 1 + out_array_7: 1 + out_array_8: 1 + out_array_9: 2 + out_array_10: 2 + out_array_11: 3 + out_array_12: 3 + out_array_13: 3 + out_array_14: 5 + out_array_15: 11 + out_array_16: 15 + out_array_17: 23 + out_array_18: 37 + out_array_19: 42 + out_array_20: 53 \ No newline at end of file diff --git a/tests/python-tests/test_client.py b/tests/python-tests/test_client.py index 47b7a98..83ef03d 100644 --- a/tests/python-tests/test_client.py +++ b/tests/python-tests/test_client.py @@ -1,7 +1,7 @@ """Nada numpy client unit tests""" +import nillion_client as nillion import numpy as np -import py_nillion_client as nillion import pytest import nada_numpy as na @@ -26,34 +26,37 @@ def test_array_3(self): input_arr = np.array([0]) nada_array_1 = na_client.array(input_arr, "test", nillion.SecretInteger) - assert isinstance(nada_array_1["test_0"], nillion.SecretInteger), type( - nada_array_1["test_0"] - ) + assert isinstance( + nada_array_1["test_0"], nillion.SecretInteger + ), f"SecretInteger should be SecretInteger but got {type(nada_array_1['test_0'])}" nada_array_2 = na_client.array(input_arr, "test", nillion.SecretUnsignedInteger) - assert isinstance(nada_array_2["test_0"], nillion.SecretUnsignedInteger), type( - nada_array_2["test_0"] - ) + assert isinstance( + nada_array_2["test_0"], nillion.SecretUnsignedInteger + ), f"SecretUnsignedInteger should be SecretUnsignedInteger but got {type(nada_array_2['test_0'])}" nada_array_3 = na_client.array(input_arr, "test", nillion.Integer) - assert isinstance(nada_array_3["test_0"], nillion.Integer), type( - nada_array_3["test_0"] - ) + assert isinstance( + nada_array_3["test_0"], nillion.Integer + ), f"Integer should be Integer but got {type(nada_array_3['test_0'])}" - nada_array_4 = na_client.array(input_arr, "test", nillion.UnsignedInteger) - assert isinstance(nada_array_4["test_0"], nillion.UnsignedInteger), type( - nada_array_4["test_0"] - ) + nada_array_4 = na_client.array(input_arr, "test", nillion.Integer) + assert isinstance( + nada_array_4["test_0"], nillion.Integer + ), f"Integer should be Integer but got {type(nada_array_4['test_0'])}" nada_array_5 = na_client.array(input_arr, "test", na.Rational) - assert isinstance(nada_array_5["test_0"], nillion.Integer), type( - nada_array_5["test_0"] - ) + assert isinstance( + nada_array_5["test_0"], nillion.Integer + ), f"Rational should be Integer but got {type(nada_array_5['test_0'])}" nada_array_6 = na_client.array(input_arr, "test", na.SecretRational) - assert isinstance(nada_array_6["test_0"], nillion.SecretInteger), type( - nada_array_6["test_0"] - ) + assert ( + type(nada_array_6["test_0"]) == nillion.SecretInteger + ), f"SecretRational should be SecretInteger but got {type(nada_array_6['test_0'])}" + assert isinstance( + nada_array_6["test_0"], nillion.SecretInteger + ), f"SecretRational should be SecretInteger but got {type(nada_array_6['test_0'])}" def test_array_4(self): input_arr = np.array([0]) diff --git a/tests/python-tests/test_client_legacy.py b/tests/python-tests/test_client_legacy.py new file mode 100644 index 0000000..3b15ea7 --- /dev/null +++ b/tests/python-tests/test_client_legacy.py @@ -0,0 +1,178 @@ +"""Nada numpy client unit tests""" + +import numpy as np +import py_nillion_client as nillion +import pytest + +import nada_numpy as na +import nada_numpy.legacy_client as na_client + + +class TestClient: + + def test_array_1(self): + input_arr = np.array([1]) + nada_array = na_client.array(input_arr, "test", na.Rational) + + assert list(nada_array.keys()) == ["test_0"] + + def test_array_2(self): + input_arr = np.array([0]) + nada_array = na_client.array(input_arr, "test", na.SecretRational) + + assert list(nada_array.keys()) == ["test_0"] + + def test_array_3(self): + input_arr = np.array([0]) + + nada_array_1 = na_client.array(input_arr, "test", nillion.SecretInteger) + assert isinstance( + nada_array_1["test_0"], nillion.SecretInteger + ), f"SecretInteger should be SecretInteger but got {type(nada_array_1['test_0'])}" + + nada_array_2 = na_client.array(input_arr, "test", nillion.SecretUnsignedInteger) + assert isinstance( + nada_array_2["test_0"], nillion.SecretUnsignedInteger + ), f"SecretUnsignedInteger should be SecretUnsignedInteger but got {type(nada_array_2['test_0'])}" + + nada_array_3 = na_client.array(input_arr, "test", nillion.Integer) + assert isinstance( + nada_array_3["test_0"], nillion.Integer + ), f"Integer should be Integer but got {type(nada_array_3['test_0'])}" + + nada_array_4 = na_client.array(input_arr, "test", nillion.Integer) + assert isinstance( + nada_array_4["test_0"], nillion.Integer + ), f"Integer should be Integer but got {type(nada_array_4['test_0'])}" + + nada_array_5 = na_client.array(input_arr, "test", na.Rational) + assert isinstance( + nada_array_5["test_0"], nillion.Integer + ), f"Rational should be Integer but got {type(nada_array_5['test_0'])}" + + nada_array_6 = na_client.array(input_arr, "test", na.SecretRational) + assert ( + type(nada_array_6["test_0"]) == nillion.SecretInteger + ), f"SecretRational should be SecretInteger but got {type(nada_array_6['test_0'])}" + assert isinstance( + nada_array_6["test_0"], nillion.SecretInteger + ), f"SecretRational should be SecretInteger but got {type(nada_array_6['test_0'])}" + + def test_array_4(self): + input_arr = np.array([0]) + nada_array = na_client.array(input_arr, "test", nillion.Integer) + + assert list(nada_array.keys()) == ["test_0"] + + def test_array_5(self): + input_arr = np.random.randn(3) + nada_array = na_client.array(input_arr, "test", nillion.SecretInteger) + + assert list(nada_array.keys()) == ["test_0", "test_1", "test_2"] + + def test_array_6(self): + input_arr = np.random.randn(2, 3) + nada_array = na_client.array(input_arr, "test", nillion.SecretInteger) + + assert list(sorted(nada_array.keys())) == [ + "test_0_0", + "test_0_1", + "test_0_2", + "test_1_0", + "test_1_1", + "test_1_2", + ] + + def test_array_7(self): + input_arr = np.array([]) + + supported_types = [ + nillion.SecretInteger, + nillion.SecretUnsignedInteger, + nillion.Integer, + nillion.UnsignedInteger, + na.Rational, + na.SecretRational, + ] + for supported_type in supported_types: + nada_array = na_client.array(input_arr, "test", supported_type) + assert nada_array == {} + + def test_array_8(self): + with pytest.raises(TypeError): + na_client.array(np.array([1]), "my_array") # no nada_type provided + + def test_concat_1(self): + dict_1 = {"a": 1, "b": 2} + dict_2 = {"c": 3} + + dict_comb = na_client.concat([dict_1, dict_2]) + + assert dict_comb == {"a": 1, "b": 2, "c": 3} + + def test_concat_2(self): + dict_1 = {"a": 1, "b": 2} + dict_2 = {"b": 3} + + dict_comb = na_client.concat([dict_1, dict_2]) + + assert dict_comb == {"a": 1, "b": 3} + + def test_secret_rational_1(self): + test_value = 1 + + rational = na_client.secret_rational(test_value) + + assert isinstance(rational, nillion.SecretInteger) + + rational_value = rational.value + + assert rational_value == test_value * 2 ** na.get_log_scale() + + def test_secret_rational_2(self): + test_value = 2.5 + + rational = na_client.secret_rational(test_value) + + assert isinstance(rational, nillion.SecretInteger) + + rational_value = rational.value + + assert rational_value == test_value * 2 ** na.get_log_scale() + + def test_public_rational_1(self): + test_value = 1 + + rational = na_client.public_rational(test_value) + + assert isinstance(rational, nillion.Integer) + + rational_value = rational.value + + assert rational_value == test_value * 2 ** na.get_log_scale() + + def test_public_rational_2(self): + test_value = 2.5 + + rational = na_client.public_rational(test_value) + + assert isinstance(rational, nillion.Integer) + + rational_value = rational.value + + assert rational_value == test_value * 2 ** na.get_log_scale() + + def test_parties_1(self): + parties = na_client.parties(2) + + assert list(sorted(parties)) == ["Party0", "Party1"] + + def test_parties_2(self): + parties = na_client.parties(0) + + assert parties == [] + + def test_parties_3(self): + parties = na_client.parties(3, "my_party") + + assert parties == ["my_party0", "my_party1", "my_party2"] diff --git a/tests/test_all.py b/tests/test_all.py index 205de46..9c552f3 100644 --- a/tests/test_all.py +++ b/tests/test_all.py @@ -47,10 +47,8 @@ "type_guardrails", "shape", "get_vec", - # Not supported yet - # "unsigned_matrix_inverse", + "unsigned_matrix_inverse", "private_inverse", - # "unsigned_matrix_inverse_2", "fxpmath_funcs", "fxpmath_arrays", "fxpmath_methods", @@ -94,9 +92,6 @@ def build_nada(test_dir): ["nada", "build", test_dir[1]], cwd=test_dir[0], capture_output=True, text=True ) err = result.stderr.lower() + result.stdout.lower() - if test_dir[1] == "determinant" and test_dir[0] == "examples/": - print(err) - raise Exception("Error") if result.returncode != 0 or "error" in err or "fail" in err: pytest.fail(f"Build {test_dir}:\n{result.stdout + result.stderr}") @@ -126,8 +121,8 @@ def test_run(self, testname): def test_client(): + import nillion_client as nillion import numpy as np - import py_nillion_client as nillion import nada_numpy.client as na_client # For use with Python Client @@ -135,38 +130,34 @@ def test_client(): assert parties is not None - secrets = nillion.NadaValues( - na_client.concat( - [ - na_client.array(np.ones((3, 3)), "A", nillion.SecretInteger), - na_client.array(np.ones((3, 3)), "B", nillion.SecretUnsignedInteger), - ] - ) + secrets = na_client.concat( + [ + na_client.array(np.ones((3, 3)), "A", nillion.SecretInteger), + na_client.array(np.ones((3, 3)), "B", nillion.SecretUnsignedInteger), + ] ) assert secrets is not None - public_variables = nillion.NadaValues( - na_client.concat( - [ - na_client.array(np.zeros((4, 4)), "C", nillion.Integer), - na_client.array(np.zeros((3, 3)), "D", nillion.UnsignedInteger), - ] - ) + public_variables = na_client.concat( + [ + na_client.array(np.zeros((4, 4)), "C", nillion.Integer), + na_client.array(np.zeros((3, 3)), "D", nillion.UnsignedInteger), + ] ) assert public_variables is not None def test_rational_client(): - import py_nillion_client as nillion + import nillion_client as nillion import nada_numpy.client as na_client # For use with Python Client secret_rational = na_client.secret_rational(3.2) - assert type(secret_rational) == nillion.SecretInteger + assert isinstance(secret_rational, nillion.SecretInteger) rational = na_client.public_rational(1.7) - assert type(rational) == nillion.Integer + assert isinstance(rational, nillion.Integer)