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import find_dotenv, load_dotenv
from giza_actions.task |
import task
from lp_tools |
import MAX_UINT_128
load_dotenv(find_dotenv())
dev_passphrase = os.environ.get("DEV_PASSPHRASE")
sepolia_rpc_url = os.environ.get("SEPOLIA_RPC_URL")
@task(name="Check allowance")
def check_allowance(token: ContractInstance, spender: str, account: str, amount: int):
return token.allowance(account, spender) >= amount
@task(name="Approve token spend")
def approve_token(token: ContractInstance, spender: str, amount: int):
return token.approve(spender, amount)
@task(name="Get mint parameters")
def get_mint_params(
user_address: str,
tokenA_address: str,
tokenB_address: str,
amount0: int,
amount1: int,
pool_fee: int,
lower_tick: int,
upper_tick: int,
deadline=None,
slippage_tolerance=0.01,
):
if deadline is None:
deadline = int(time.time()) + 60
mint_params = {
"token0": tokenA_address,
"token1": tokenB_address,
"fee": pool_fee,
"tickLower": lower_tick,
"tickUpper": upper_tick,
"amount0Desired": amount0,
"amount1Desired": amount1,
"amount0Min": 0,
"amount1Min": 0,
"recipient": user_address,
"deadline": deadline,
}
return tuple(mint_params.values())
@task(name="Get all user LP positions")
def get_all_user_positions(nft_manager: ContractInstance, user_address: str):
n_positions = nft_manager.balanceOf(user_address)
positions = []
for n in range(n_positions):
position = nft_manager.tokenOfOwnerByIndex(user_address, n)
positions.append(position)
return positions
def get_pos_liquidity(nft_manager: ContractInstance, nft_id: int):
(
nonce,
operator,
token0,
token1,
fee,
tickLower,
tickUpper,
liquidity,
feeGrowthInside0LastX128,
feeGrowthInside1LastX128,
tokensOwed0,
tokensOwed1,
) = nft_manager.positions(nft_id)
return liquidity
@task(name="Close the position")
def close_position(user_address: str, nft_manager: Co |
ntractInstance, nft_id: int):
liq = get_pos_liquidity(nft_manager, nft_id)
if liq > 0:
nft_manager.decreaseLiquidity((nft_id, liq, 0, 0, int(time.time() + 60)))
nft_manager.collect((nft_id, user_address, MAX_UINT_128, MAX_UINT_128)) |
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "04w3OowXkaQh"
},
"source": [
"
"\n",
"Orion is a dedicated Cairo-based library designed specifically to build machine learning models for ValidityML. Its purpose is to facilitate verifiable inference. For better performance we will operate with an 8-bit quantized model. In this tutorial, you will be guided on how to train your model using Quantized Aware Training using MNIST dataset, how to convert your pre-trained model to Cairo 1, and how to perform inference with Orion."
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"
"Let's start by installing all dependecies."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"id": "1Sfci39Llvii"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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]
}
],
"source": [
" |
import sys\n",
"!{sys.executable} -m pip install numpy tensorflow tensorflow_model_optimization matplotlib scipy"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "GwTsquVDEe4p"
},
"outputs": [],
"source": [
"!curl --proto '=https' --tlsv1.2 -sSf https:
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https:
},
"id": "uBsZQCRBExEc",
"outputId": "54cbbc65-854e-4afa-b809-d2fc838f6ecf"
},
"outputs": [],
"source": [
"
"! mkdir $HOME/.cairo\n",
"\n",
"! source \"$HOME/.cargo/env\"\n",
"\n",
"
"! cd $HOME/.cairo && git clone https:
"\n",
"
"
"! git fetch --all --tags\n",
"
"! git describe --tags `git rev-list --tags`\n",
"
"! git checkout tags/v1.1.0\n",
"\n",
"
"! cd $HOME/.cairo && $HOME/.cargo/bin/cargo build --all --release"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"
"! curl --proto '=https' --tlsv1.2 -sSf https:
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"
"In this section we will use Tensorflow to train and test a feedforward neural network with MNIST dataset."
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "nKiq8oKxklon"
},
"source": [
"
"Import the required libraries and load the dataset."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "4po2PWTAkWOR"
},
"outputs": [],
"source": [
"from tensorflow |
import keras\n",
"from keras.datasets |
import mnist\n",
"from scipy.ndimage |
import zoom\n",
" |
import numpy as np\n",
"\n",
"(x_train, y_train), (x_test, y_test) = mnist.load_data()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "NXigQHM_k0ux"
},
"source": [
"We have a total of 70,000 grayscale images, each with a dimension of 28 x 28 pixels. 60,000 images are for training and the remaining 10,000 are for testing. \n",
"\n",
"We now need to pre-process our data. For the purposes of this tutorial and performance, we'll resize the images to 14 x 14 pixels. You'll see later that the neural network's input layer supports a 1D tensor. We, therefore, need to flatten and normalize our data."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"id": "6AwxawnnkaA5"
},
"outputs": [],
"source": [
"from scipy.ndimage |
import zoom\n",
"\n",
"
"def resize_images(images):\n",
" return np.array([zoom(image, 0.5) for image in images])\n",
"\n",
"
"x_train = resize_images(x_train)\n",
"x_test = resize_images(x_test)\n",
"\n",
"
"x_train = x_train.reshape(60000, 14*14)\n",
"x_test = x_test.reshape(10000, 14*14)\n",
"x_train = x_train.astype('float32')\n",
"x_test = x_test.astype('float32')\n",
"\n",
"
"x_train /= 255\n",
"x_test /= 255"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "ix3qnUgElDlB"
},
"source": [
"
"We will design a straightforward feedforward neural network."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"id": "7gilDCS6k9-u"
},
"outputs": [],
"source": [
"from tensorflow.keras |
import layers\n",
"\n",
"num_classes = 10\n",
"\n",
"model = keras.Sequential([\n",
" keras.layers.InputLayer(input_shape=(14*14,)),\n",
" keras.layers.Dense(10, activation='relu'), \n",
" keras.layers.Dense(10, activation='softmax')\n",
"])\n",
"\n",
"model.compile(optimizer='adam', \n",
" loss='sparse_categorical_crossentropy', \n",
" metrics=['accuracy'])\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "BFUZZOudlQmP"
},
"source": [
"Now let's train this model on our training data."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"id": "jjkH102GlOd2"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"1500/1500 [==============================] - 1s 449us/step - loss: 0.8094 - accuracy: 0.7795 - val_loss: 0.3885 - val_accuracy: 0.8953\n",
"Epoch 2/10\n",
"1500/1500 [==============================] - 1s 399us/step - loss: 0.3693 - accuracy: 0.8961 - val_loss: 0.3152 - val_accuracy: 0.9122\n",
"Epoch 3/10\n",
"1500/1500 [==============================] - 1s 402us/step - loss: 0.3239 - accuracy: 0.9072 - val_loss: 0.2905 - val_accuracy: 0.9185\n",
"Epoch 4/10\n",
"1500/1500 [==============================] - 1s 403us/step - loss: 0.3041 - accuracy: 0.9130 - val_loss: 0.2842 - val_accuracy: 0.9192\n",
"Epoch 5/10\n",
"1500/1500 [==============================] - 1s 428us/step - loss: 0.2931 - accuracy: 0.9162 - val_loss: 0.2716 - val_accuracy: 0.9237\n",
"Epoch 6/10\n",
"1500/1500 [==============================] - 1s 406us/step - loss: 0.2849 - accuracy: 0.9193 - val_loss: 0.2689 - val_accuracy: 0.9228\n",
"Epoch 7/10\n", |
"1500/1500 [==============================] - 1s 407us/step - loss: 0.2791 - accuracy: 0.9202 - val_loss: 0.2645 - val_accuracy: 0.9259\n",
"Epoch 8/10\n",
"1500/1500 [==============================] - 1s 401us/step - loss: 0.2747 - accuracy: 0.9215 - val_loss: 0.2608 - val_accuracy: 0.9269\n",
"Epoch 9/10\n",
"1500/1500 [==============================] - 1s 401us/step - loss: 0.2705 - accuracy: 0.9226 - val_loss: 0.2585 - val_accuracy: 0.9283\n",
"Epoch 10/10\n",
"1500/1500 [==============================] - 1s 401us/step - loss: 0.2674 - accuracy: 0.9236 - val_loss: 0.2582 - val_accuracy: 0.9283\n"
]
}
],
"source": [
"batch_size = 256\n",
"epochs = 10\n",
"history = model.fit(x_train, y_train,\n",
" epochs=epochs,\n",
" validation_split=0.2)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "uNRdKGpflar4"
},
"source": [
"At this point, we have trained a regular model.\n",
"\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "7Bu55FCqlbj4"
},
"source": [
"
"Now, let's transform our model into a quantization aware model. We use the TensorFlow Model Optimization Toolkit for this.\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"id": "iAZYo9vKlTHK"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model: \"sequential\"\n",
"_________________________________________________________________\n",
" Layer (type) Output Shape Param
"=================================================================\n",
" quantize_layer (QuantizeLa (None, 196) 3 \n", |
" yer) \n",
" \n",
" quant_dense (QuantizeWrapp (None, 10) 1975 \n",
" erV2) \n",
" \n",
" quant_dense_1 (QuantizeWra (None, 10) 115 \n",
" pperV2) \n",
" \n",
"=================================================================\n",
"Total params: 2093 (8.18 KB)\n",
"Trainable params: 2080 (8.12 KB)\n",
"Non-trainable params: 13 (52.00 Byte)\n",
"_________________________________________________________________\n"
]
}
],
"source": [
" |
import tensorflow_model_optimization as tfmot\n",
"\n",
"
"quantize_model = tfmot.quantization.keras.quantize_model\n",
"\n",
"
"q_aware_model = quantize_model(model)\n",
"\n",
"
"q_aware_model.compile(optimizer='adam',\n",
" loss='sparse_categorical_crossentropy',\n",
" metrics=['accuracy'])\n",
"\n",
"q_aware_model.summary()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "eYPUWWwTl_np"
},
"source": [
"We have now created a new model, q_aware_model, which is a quantization aware version of our original model. Now we can train this model exactly like our original model."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"id": "U-t5MPhGlqoI"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"1500/1500 [==============================] - 1s 526us/step - loss: 0.2671 - accuracy: 0.9236 - val_loss: 0.2581 - val_accuracy: 0.9283\n",
"Epoch 2/10\n",
"1500/1500 [==============================] - 1s 478us/step - loss: 0.2625 - accuracy: 0.9235 - val_loss: 0.2538 - val_accuracy: 0.9293\n",
"Epoch 3/10\n",
"1500/1500 [==============================] - 1s 491us/step - loss: 0.2602 - accuracy: 0.9246 - val_loss: 0.2521 - val_accuracy: 0.9308\n",
"Epoch 4/10\n",
"1500/1500 [==============================] - 1s 481us/step - loss: 0.2579 - accuracy: 0.9265 - val_loss: 0.2541 - val_accuracy: 0.9296\n",
"Epoch 5/10\n",
"1500/1500 [==============================] - 1s 481us/step - loss: 0.2557 - accuracy: 0.9271 - val_loss: 0.2490 - val_accuracy: 0.9317\n",
"Epoch 6/10\n",
"1500/1500 [==============================] - 1s 482us/step - loss: 0.2540 - a |
ccuracy: 0.9274 - val_loss: 0.2492 - val_accuracy: 0.9313\n",
"Epoch 7/10\n",
"1500/1500 [==============================] - 1s 497us/step - loss: 0.2522 - accuracy: 0.9277 - val_loss: 0.2495 - val_accuracy: 0.9296\n",
"Epoch 8/10\n",
"1500/1500 [==============================] - 1s 491us/step - loss: 0.2505 - accuracy: 0.9277 - val_loss: 0.2472 - val_accuracy: 0.9306\n",
"Epoch 9/10\n",
"1500/1500 [==============================] - 1s 479us/step - loss: 0.2491 - accuracy: 0.9288 - val_loss: 0.2461 - val_accuracy: 0.9337\n",
"Epoch 10/10\n",
"1500/1500 [==============================] - 1s 483us/step - loss: 0.2477 - accuracy: 0.9285 - val_loss: 0.2444 - val_accuracy: 0.9325\n",
"Test loss: 0.25082069635391235\n",
"Test accuracy: 0.9277999997138977\n"
]
}
],
"source": [
"batch_size = 256\n",
"epochs = 10\n",
"history = q_aware_model.fit(x_train, y_train,\n",
" epochs=epochs,\n",
" validation_split=0.2)\n",
"\n",
"scores, acc = q_aware_model.evaluate(x_test, y_test, verbose=0)\n",
"print('Test loss:', scores)\n",
"print('Test accuracy:', acc)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "XhbweTQEmWN-"
},
"source": [
"
"Now, we will convert our model to TFLite format, which is a format optimized for on-device machine learning."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"id": "uOwZiCRWmHDT"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: /var/folders/s3/6c0gmns50x36dt6vvfhv6jhc0000gn/T/tmpwwestso3/assets\n"
]
},
{
"name": "stderr", |
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: /var/folders/s3/6c0gmns50x36dt6vvfhv6jhc0000gn/T/tmpwwestso3/assets\n",
"/Users/raphaeldoukhan/Desktop/Orion-Giza/Academy/Tutorials/orion_tutorials/.conda/lib/python3.10/site-packages/tensorflow/lite/python/convert.py:887: UserWarning: Statistics for quantized inputs were expected, but not specified; continuing anyway.\n",
" warnings.warn(\n",
"2023-09-08 08:57:11.760815: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:364] Ignored output_format.\n",
"2023-09-08 08:57:11.760826: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:367] Ignored drop_control_dependency.\n",
"2023-09-08 08:57:11.761006: I tensorflow/cc/saved_model/reader.cc:45] Reading SavedModel from: /var/folders/s3/6c0gmns50x36dt6vvfhv6jhc0000gn/T/tmpwwestso3\n",
"2023-09-08 08:57:11.761945: I tensorflow/cc/saved_model/reader.cc:91] Reading meta graph with tags { serve }\n",
"2023-09-08 08:57:11.761951: I tensorflow/cc/saved_model/reader.cc:132] Reading SavedModel debug info (if present) from: /var/folders/s3/6c0gmns50x36dt6vvfhv6jhc0000gn/T/tmpwwestso3\n",
"2023-09-08 08:57:11.764080: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:375] MLIR V1 optimization pass is not enabled\n",
"2023-09-08 08:57:11.765054: I tensorflow/cc/saved_model/loader.cc:231] Restoring SavedModel bundle.\n",
"2023-09-08 08:57:11.795103: I tensorflow/cc/saved_model/loader.cc:215] Running initialization op on SavedModel bundle at path: /var/folders/s3/6c0gmns50x36dt6vvfhv6jhc0000gn/T/tmpwwestso3\n",
"2023-09-08 08:57:11.804542: I tensorflow/cc/saved_model/loader.cc:314] SavedModel load for tags { serve }; Status: success: OK. Took 43536 microseconds.\n",
"2023-09-08 08:57:11.814757: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:255] disabling MLIR crash reproducer, set env |
var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.\n",
"fully_quantize: 0, inference_type: 6, input_inference_type: INT8, output_inference_type: INT8\n"
]
},
{
"data": {
"text/plain": [
"4312"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
" |
import tensorflow as tf\n",
"\n",
"
"converter = tf.lite.TFLiteConverter.from_keras_model(q_aware_model)\n",
"\n",
"
"
"converter.optimizations = [tf.lite.Optimize.DEFAULT]\n",
"\n",
"
"def representative_data_gen():\n",
" for i in range(500):\n",
" yield [x_test[i:i+1]]\n",
"\n",
"
"converter.representative_dataset = representative_data_gen\n",
"\n",
"
"converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]\n",
"\n",
"
"converter.inference_input_type = tf.int8\n",
"converter.inference_output_type = tf.int8\n",
"\n",
"
"tflite_model = converter.convert()\n",
"\n",
"
"open(\"q_aware_model.tflite\", \"wb\").write(tflite_model)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "zxGWitSs3MAH"
},
"source": [
"
"Now that we have trained a quantization-aware model and converted it to the TFLite format, we can now perform inference using the TensorFlow Lite interpreter.\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "8qbfjJFa3Zy7"
},
"source": [
"We first load the TFLite model and allocate the required tensors. The Interpreter class provides methods for loading a model and running inferences.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"id": "sXEM3WEv3SSt"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO: Created TensorFlow Lite XNNPACK delegate for CPU.\n"
]
}
],
"source": [
"
"interpreter = tf.lite.Interpreter(model_path=\"q_aware_model.tflite\")\n",
"interpreter.allocate_tensors()"
]
},
{ |
"cell_type": "markdown",
"metadata": {
"id": "mP6WRo1L3dZp"
},
"source": [
"Next, we get the details of the input and output tensors. Each tensor in a TensorFlow Lite model has a name, index, shape, data type, and quantization parameters. These can be accessed via the input_details and output_details methods."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"id": "T7r8JFTC3Xxe"
},
"outputs": [],
"source": [
"
"input_details = interpreter.get_input_details()\n",
"output_details = interpreter.get_output_details()\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ofFMDXq13ix7"
},
"source": [
"Before performing the inference, we need to normalize the input to match the data type of our model's input tensor, which in our case is int8. Then, we use the set_tensor method to provide the input data to the model. We perform the inference using the invoke method."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"id": "-1yOJjl83b9i"
},
"outputs": [],
"source": [
"
"input_shape = input_details[0]['shape']\n",
"input_data = np.array(x_test[0:1], dtype=np.int8)\n",
"interpreter.set_tensor(input_details[0]['index'], input_data)\n",
"\n",
"
"interpreter.invoke()\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ge-Y3K1J3oWs"
},
"source": [
"After the inference, we get the output data from the model's output tensor.\n",
"\n",
"Now, we are going to run the inference for the entire test set:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"id": "MtfTBPCl3iKm"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [ |
"[[-122 -128 -22 -67 -128 -47 -128 -127 -128 -128]]\n"
]
}
],
"source": [
"
"output_data = interpreter.get_tensor(output_details[0]['index'])\n",
"print(output_data)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "JO9fwtAF3sRP"
},
"source": [
"We normalize the entire test set and initialize an array to store the predictions.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"id": "B5fDA1Vt3num"
},
"outputs": [],
"source": [
"(_, _), (x_test_image, y_test_label) = mnist.load_data()\n",
"\n",
"
"x_test_image = resize_images(x_test_image)\n",
"x_test_image_norm = (x_test_image / 255.0 * 255 - 128).astype(np.int8)\n",
"\n",
"
"predictions = []\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "l1PzXSuj3uy9"
},
"source": [
"We then iterate over the test set, making predictions for each image. For each image, we flatten the image, normalize it, and then expand its dimensions to match the shape of our model's input tensor.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"id": "z1Clh4Kt3fuF"
},
"outputs": [],
"source": [
"
"for i in range(len(x_test_image_norm)):\n",
" test_image = np.expand_dims(x_test_image_norm[i].flatten(), axis=0)\n",
" \n",
"
" interpreter.set_tensor(input_details[0]['index'], test_image)\n",
" \n",
"
" interpreter.invoke()\n",
"\n",
" output = interpreter.get_tensor(output_details[0]['index'])\n",
" predictions.append(output)\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [ |
"Finally, we use a function to plot the test images along with their predicted labels. This will give us a visual representation of how well our model is performing."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"id": "5wWyve_E3uL8"
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA7YAAARDCAYAAABcAr28AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABojklEQVR4nO3de5zWZZ0
"text/plain": [
"<Figure size 1200x1400 with 25 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" |
import matplotlib.pyplot as plt\n",
"\n",
"def plot_images_labels_prediction(images,labels,idx,num=10):\n",
" fig=plt.gcf()\n",
" fig.set_size_inches(12, 14)\n",
" if num > 25: num=25\n",
" for i in range(0, num):\n",
" ax=plt.subplot(5, 5, i+1)\n",
" ax.imshow(images[idx], cmap='binary')\n",
" title=\"label=\" + str(labels[idx])\n",
" ax.set_title(title, fontsize=10)\n",
" ax.set_xticks([]);\n",
" ax.set_yticks([]);\n",
" idx += 1\n",
" plt.show()\n",
"\n",
"plot_images_labels_prediction(x_test_image, y_test_label, 0, 25)\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "VOHKHUMp30j8"
},
"source": [
"That's it! We have successfully trained a quantization-aware model, converted it to the TFLite format, and performed inference using the TensorFlow Lite interpreter."
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "ywhXM1mA-a7F"
},
"source": [
"
"In this section you will generate Cairo files for each bias and weight of the model. "
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"id": "wP_kVSuEKA1U"
},
"outputs": [],
"source": [
" |
import numpy as np\n",
" |
import tensorflow as tf\n",
" |
import os\n",
"\n",
"\n",
"
"interpreter = tf.lite.Interpreter(model_path=\"q_aware_model.tflite\")\n",
"interpreter.allocate_tensors()\n",
"\n",
"
"tensors = {\n",
" \"input\": x_test_image[0].flatten(),
" \"fc1_weights\": interpreter.get_tensor(1), \n",
" \"fc1_bias\": interpreter.get_tensor(2), \n",
" \"fc2_weights\": interpreter.get_tensor(4), \n",
" \"fc2_bias\": interpreter.get_tensor(5)\n",
"}\n",
"\n",
"
"os.makedirs('src/generated', exist_ok=True)\n",
"\n",
"for tensor_name, tensor in tensors.items():\n",
" with open(os.path.join('src', 'generated', f\"{tensor_name}.cairo\"), \"w\") as f:\n",
" f.write(\n",
" \"use array::ArrayTrait;\\n\" +\n",
" \"use orion::operators::tensor::{TensorTrait, Tensor, I32Tensor};\\n\" +\n",
" \"use orion::numbers::i32;\\n\\n\" +\n",
" \"\\nfn {0}() -> Tensor<i32> \".format(tensor_name) + \"{\\n\" +\n",
" \" let mut shape = ArrayTrait::<usize>::new();\\n\"\n",
" )\n",
" for dim in tensor.shape:\n",
" f.write(\" shape.append({0});\\n\".format(dim))\n",
" f.write(\n",
" \" let mut data = ArrayTrait::<i32>::new();\\n\"\n",
" )\n",
" for val in np.nditer(tensor.flatten()):\n",
" f.write(\" data.append(i32 {{ mag: {0}, sign: {1} }});\\n\".format(abs(int(val)), str(val < 0).lower()))\n",
" f.write(\n",
" \" TensorTrait::new(shape.span(), data.span())\\n\" +\n",
" \"}\\n\"\n",
" )\n",
" \n",
"with open(os.path.join('src', 'generated.cairo'), 'w') as f:\n",
" for param_name in tensors.keys():\n",
" f.write(f\"mod {param_name};\\n\")\n" |
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "iobaWNzdW4Jq"
},
"source": [
"
"In this section you will perform inference with Cairo and Orion.\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"Create the `nn.cairo` file in which we'll build the neural network functions."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"id": "x2slaqnnUWlB"
},
"outputs": [],
"source": [
"! touch src/nn.cairo"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's create the two dense layer functions of the neural network: `fc1` and `fc2`."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"id": "UMF0u2gcUko9"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Overwriting src/nn.cairo\n"
]
}
],
"source": [
"%%writefile src/nn.cairo\n",
"use orion::operators::tensor::core::Tensor;\n",
"use orion::numbers::signed_integer::{integer_trait::IntegerTrait, i32::i32};\n",
"use orion::operators::nn::{NNTrait, I32NN};\n",
"\n",
"fn fc1(i: Tensor<i32>, w: Tensor<i32>, b: Tensor<i32>) -> Tensor<i32> {\n",
" let x = NNTrait::linear(i, w, b);\n",
" NNTrait::relu(@x)\n",
"}\n",
"\n",
"fn fc2(i: Tensor<i32>, w: Tensor<i32>, b: Tensor<i32>) -> Tensor<i32> {\n",
" NNTrait::linear(i, w, b)\n",
"}\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"We will make predictions in a test. First, create the testing file."
]
},
{
"cell_type": "code",
"execution |
_count": 21,
"metadata": {
"id": "OF8ANN0IU0BL"
},
"outputs": [],
"source": [
"! touch src/test.cairo"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's now define the input data and parameters generated earlier, and set the neural network.\n",
"The input data represents the number 7. The probability at index 7 must therefore be close to 1."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"id": "FsWjlfyeWJF8"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Overwriting src/test.cairo\n"
]
}
],
"source": [
"%%writefile src/test.cairo\n",
"use core::array::SpanTrait;\n",
"\n",
"use mnist_nn::nn::fc1;\n",
"use mnist_nn::nn::fc2;\n",
"use mnist_nn::generated::input::input;\n",
"use mnist_nn::generated::fc1_bias::fc1_bias;\n",
"use mnist_nn::generated::fc1_weights::fc1_weights;\n",
"use mnist_nn::generated::fc2_bias::fc2_bias;\n",
"use mnist_nn::generated::fc2_weights::fc2_weights;\n",
"\n",
"use orion::operators::tensor::I32Tensor;\n",
"\n",
"
"
" |
fn mnist_nn_test() {\n",
" let input = input();\n",
" let fc1_bias = fc1_bias();\n",
" let fc1_weights = fc1_weights();\n",
" let fc2_bias = fc2_bias();\n",
" let fc2_weights = fc2_weights();\n",
"\n",
" let x = fc1(input, fc1_weights, fc1_bias);\n",
" let x = fc2(x, fc2_weights, fc2_bias);\n",
"\n",
" let x = *x.argmax(0, Option::None(()), Option::None(())).data.at(0);\n",
"\n",
" assert(x == 7, 'should predict 7');\n",
"}\n",
"\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"Run the following cell to test your file."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "lkep4mVkWMtS"
},
"outputs": [],
"source": [
"! scarb run test"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"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": "3.10.11"
}
},
"nbformat": 4,
"nbformat_minor": 0
} |
mod input;
mod fc1_weights;
mod fc1_bias;
mod fc2_weights;
mod fc2_bias;
|
use array::ArrayTrait;
use orion::operators::tensor::{TensorTrait, Tensor, I32Tensor};
use orion::numbers::i32;
fn fc1_bias() -> Tensor<i32> {
let mut shape = ArrayTrait::<usize>::new();
shape.append(10);
let mut data = ArrayTrait::<i32>::new();
data.append(i32 { mag: 1287, sign: false });
data.append(i32 { mag: 3667, sign: true });
data.append(i32 { mag: 2954, sign: false });
data.append(i32 { mag: 7938, sign: false });
data.append(i32 { mag: 3959, sign: false });
data.append(i32 { mag: 5862, sign: true });
data.append(i32 { mag: 4886, sign: false });
data.append(i32 { mag: 4992, sign: false });
data.append(i32 { mag: 10126, sign: false });
data.append(i32 { mag: 2237, sign: true });
TensorTrait::new(shape.span(), data.span())
}
|
use array::ArrayTrait;
use orion::operators::tensor::{TensorTrait, Tensor, I32Tensor};
use orion::numbers::i32;
fn fc1_weights() -> Tensor<i32> {
let mut shape = ArrayTrait::<usize>::new();
shape.append(10);
shape.append(196);
let mut data = ArrayTrait::<i32>::new();
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 25, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 55, sign: false });
data.append(i32 { mag: 46, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 42, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 31, sign: false });
data.appe |
nd(i32 { mag: 53, sign: false });
data.append(i32 { mag: 51, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 25, sign: true });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 75, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 57, sign: true });
data.append(i32 { mag: 44, sign: true });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 45, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 53, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 10, sign: |
true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 32, sign: true });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 46, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 35, sign: true });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 50, sign: false });
data.append(i32 { mag: 45, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 37, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 19, sign: true |
});
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 41, sign: false });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 34, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 61, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 71, sign: true });
data.append(i32 { mag: 78, sign: true });
data.appe |
nd(i32 { mag: 63, sign: true });
data.append(i32 { mag: 74, sign: true });
data.append(i32 { mag: 49, sign: true });
data.append(i32 { mag: 54, sign: true });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 37, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 19, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 38, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 19, sign: false }); |
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 37, sign: false });
data.append(i32 { mag: 25, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 31, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 25, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 1, sign: true });
data.a |
ppend(i32 { mag: 8, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 42, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 34, sign: false });
data.append(i32 { mag: 45, sign: false });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 39, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 32, sign: true });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 49, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 65, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 41, sign: true });
data.append(i32 { mag: 25, sign: true });
data.append(i32 { mag: 27, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 |
{ mag: 9, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 53, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 41, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 44, sign: true }); |
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 37, sign: true });
data.append(i32 { mag: 32, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: |
3, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 42, sign: false });
data.append(i32 { mag: 55, sign: false });
data.append(i32 { mag: 97, sign: false });
data.append(i32 { mag: 125, sign: false });
data.append(i32 { mag: 68, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 47, sign: false });
data.append(i32 { mag: 42, sign: false });
data.append(i32 { mag: 46, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 25, sign |
: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 44, sign: false });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 19, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 32, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 38, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 27, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 9, sign: true });
data.ap |
pend(i32 { mag: 24, sign: false });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 50, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 39, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 54, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 43, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 56, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 44, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { ma |
g: 40, sign: false });
data.append(i32 { mag: 34, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 42, sign: false });
data.append(i32 { mag: 37, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 80, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 27, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 44, sign: false });
data.append(i32 { mag: 68, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { m |
ag: 31, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 26, sign: true });
data.append(i32 { mag: 46, sign: true });
data.append(i32 { mag: 60, sign: true });
data.append(i32 { mag: 84, sign: true });
data.append(i32 { mag: 84, sign: true });
data.append(i32 { mag: 95, sign: true });
data.append(i32 { mag: 70, sign: true });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 26, sign: true });
data.append(i32 { mag: 38, sign: true });
data.append(i32 { mag: 39, sign: true });
data.append(i32 { mag: 27, sign: false });
data. |
append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 49, sign: true });
data.append(i32 { mag: 63, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 35, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 34, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 34, sign: true });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 34, sign: false });
data.append(i32 { mag: 33, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 66, sign: false });
data.append(i32 { mag: 121, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i |
32 { mag: 14, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 41, sign: false });
data.append(i32 { mag: 39, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 43, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 42, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 33, sign: false });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: |
2, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 38, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 24, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 24, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 19, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 14, sign: false });
data. |
append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 127, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 54, sign: false });
data.append(i32 { mag: 47, sign: false });
data.append(i32 { mag: 55, sign: false });
data.append(i32 { mag: 62, sign: false });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 51, sign: false });
data.append(i32 { mag: 67, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 3, |
sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 41, sign: true });
data.append(i32 { mag: 24, sign: true });
data.append(i32 { mag: 83, sign: true });
data.append(i32 { mag: 71, sign: true });
data.append(i32 { mag: 27, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 33, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 60, sign: true });
data.append(i32 { mag: 65, sign: true });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 46, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 42, sign: true });
data.append(i32 { mag: 43, sign: true });
data.append(i32 { mag: 55, sign: true });
data.append(i32 { mag: 44, sign: true });
data.append(i32 { mag: 26, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 21, sign: false });
da |
ta.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 41, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 52, sign: true });
data.append(i32 { mag: 55, sign: true });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 53, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 66, sign: true });
data.append(i32 { mag: 70, sign: true });
data.append(i32 { mag: 58, sign: true });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 37, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 34, sign: true });
data.append(i32 { mag: 27, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 45, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 37, sign: false });
data.append(i32 { mag: 45, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 89, sign: true });
data.append(i32 { |
mag: 8, sign: true });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 50, sign: true });
data.append(i32 { mag: 27, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 33, sign: false });
data.append(i32 { mag: 37, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 45, sign: true });
data.append(i32 { mag: 84, sign: true });
data.append(i32 { mag: 71, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 27, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 25, sign: true });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 24, sign: true });
data.append(i32 { mag: 37, sign: true });
data.append(i32 { mag: 34, sign: true });
data.append(i32 { mag: 32, sign: true });
data.append(i32 { mag: 53, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 78, sign: true });
data.append(i32 { mag: 39, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 33, sign: true }); |
data.append(i32 { mag: 26, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 24, sign: true });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 49, sign: true });
data.append(i32 { mag: 37, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 1, |
sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 19, sign: true });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 31, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 46, sign: true });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { ma |
g: 20, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 24, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 73, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 19, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 80, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 49, sign: true });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 26, sign: false }); |
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 84, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 47, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 34, sign: false });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 38, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 39, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 45, sign: false });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i3 |
2 { mag: 15, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 25, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 25, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 7, sign: fa |
lse });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 74, sign: true });
data.append(i32 { mag: 48, sign: true });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 37, sign: true });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 38, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 40, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag |
: 5, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 65, sign: false });
data.append(i32 { mag: 104, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 26, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 19, sign: true });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 5, sig |
n: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 55, sign: true });
data.append(i32 { mag: 42, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 43, sign: true });
data.append(i32 { mag: 85, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 53, sign: false });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 41, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 71, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 34, sign: true });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 44, sign: false }); |
data.append(i32 { mag: 48, sign: false });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 44, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 27, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 44, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 52, sign: true });
data.append(i32 { mag: 37, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 32, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 35, sign: true });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append |
(i32 { mag: 34, sign: true });
data.append(i32 { mag: 40, sign: true });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 43, sign: true });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 24, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 38, sign: false });
data.append(i32 { mag: 48, sign: false });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 7, sign: true }); |
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 35, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 32, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 50, sign: true });
data.append(i32 { mag: 95, sign: true });
data.append(i32 { mag: 60, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 45, sign: false });
data.append(i32 { mag: 45, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 6 |
, sign: false });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 78, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 19, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 53, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 33, sign: true });
data.append(i32 { mag: 39, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 15, sign: false });
data |
.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 49, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 19, sign: true });
data.append(i32 { mag: 65, sign: true });
data.append(i32 { mag: 56, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 57, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 35, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 79, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 39, sign: true });
data.append(i32 |
{ mag: 34, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 93, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 22, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 109, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 48, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 52, sign: false });
data.append(i32 { mag: 52, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 8, |
sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 41, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 39, sign: false });
data.append(i32 { mag: 47, sign: false });
data.append(i32 { mag: 63, sign: false });
data.append(i32 { mag: 37, sign: false });
data.a |
ppend(i32 { mag: 54, sign: false });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 61, sign: true });
data.append(i32 { mag: 25, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 7, sign: fa |
lse });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 38, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 45, sign: false });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 26, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 46, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 32, sign: true });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 50, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 37, sign: true });
data.append(i32 { mag: 35, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 49, sign: false });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 38, sign: true }); |
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 54, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag |
: 2, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 14, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 26, sign: true });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 39, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 23, sign: true });
dat |
a.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 41, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 45, sign: false });
data.append(i32 { mag: 30, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 68, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 38, sign: false });
data.append(i32 { mag: 44, sign: false });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 40, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 57, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 41, sign: false });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i |
32 { mag: 5, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 44, sign: false });
data.append(i32 { mag: 69, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 73, sign: false });
data.append(i32 { mag: 37, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 7, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 34, sign: false });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 74, sign: true });
data.append(i32 { mag: 89, sign: true });
data.append(i32 { mag: 60, sign: true });
data.append(i32 { mag: 68, sign: true });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 15, sign: true });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: |
49, sign: true });
data.append(i32 { mag: 41, sign: false });
data.append(i32 { mag: 8, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 29, sign: true });
data.append(i32 { mag: 45, sign: true });
data.append(i32 { mag: 53, sign: true });
data.append(i32 { mag: 42, sign: true });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 39, sign: false });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 23, sign: true });
data.append(i32 { mag: 20, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 74, sign: false });
data.append(i32 { mag: 37, sign: false });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 18, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 38, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 6, sign: true });
data.append(i32 { mag: 11, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 39, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 49, sign: false });
data.append(i32 { mag: 56, sign: false });
data.append(i32 { mag: 3, sign: tr |
ue });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 58, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 39, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 25, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 10, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 33, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 36, sign: false });
data.append(i32 { mag: 38, sign: false });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 17, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 18, sign: false });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 38, sign: true });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 23, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 8, sign: false });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 40, sign: true });
data.append(i32 { mag: 59, sign: true });
data.append(i32 { mag: 16, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 5, sign: true }); |
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 4, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 7, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 4, sign: false });
data.append(i32 { mag: 9, sign: true });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 7, sign: true });
TensorTrait::new(shape.span(), data.span())
} |
use array::ArrayTrait;
use orion::operators::tensor::{TensorTrait, Tensor, I32Tensor};
use orion::numbers::i32;
fn fc2_bias() -> Tensor<i32> {
let mut shape = ArrayTrait::<usize>::new();
shape.append(10);
let mut data = ArrayTrait::<i32>::new();
data.append(i32 { mag: 313, sign: true });
data.append(i32 { mag: 1064, sign: false });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 184, sign: true });
data.append(i32 { mag: 1012, sign: true });
data.append(i32 { mag: 1885, sign: false });
data.append(i32 { mag: 787, sign: true });
data.append(i32 { mag: 835, sign: false });
data.append(i32 { mag: 1819, sign: true });
data.append(i32 { mag: 208, sign: false });
TensorTrait::new(shape.span(), data.span())
}
|
use array::ArrayTrait;
use orion::operators::tensor::{TensorTrait, Tensor, I32Tensor};
use orion::numbers::i32;
fn fc2_weights() -> Tensor<i32> {
let mut shape = ArrayTrait::<usize>::new();
shape.append(10);
shape.append(10);
let mut data = ArrayTrait::<i32>::new();
data.append(i32 { mag: 42, sign: true });
data.append(i32 { mag: 41, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 27, sign: true });
data.append(i32 { mag: 58, sign: true });
data.append(i32 { mag: 71, sign: false });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 50, sign: true });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 38, sign: true });
data.append(i32 { mag: 67, sign: true });
data.append(i32 { mag: 35, sign: true });
data.append(i32 { mag: 112, sign: true });
data.append(i32 { mag: 95, sign: false });
data.append(i32 { mag: 78, sign: false });
data.append(i32 { mag: 15, sign: false });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 64, sign: false });
data.append(i32 { mag: 49, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 69, sign: true });
data.append(i32 { mag: 53, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 62, sign: true });
data.append(i32 { mag: 47, sign: false });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 70, sign: true });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 48, sign: false });
data.append(i32 { mag: 69, sign: true });
data.append(i32 { mag: 21, sign: true });
data.append(i32 { mag: 35, sign: false });
data.append(i32 { mag: 38, sign: true });
data.append(i32 { mag: 100, sign: true });
data.append(i32 { mag: 41, sign: true });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 78, sign: false }) |
;
data.append(i32 { mag: 12, sign: true });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 59, sign: false });
data.append(i32 { mag: 49, sign: true });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 19, sign: true });
data.append(i32 { mag: 99, sign: true });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 11, sign: false });
data.append(i32 { mag: 29, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 2, sign: true });
data.append(i32 { mag: 127, sign: true });
data.append(i32 { mag: 117, sign: true });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 39, sign: false });
data.append(i32 { mag: 17, sign: true });
data.append(i32 { mag: 67, sign: false });
data.append(i32 { mag: 9, sign: false });
data.append(i32 { mag: 42, sign: false });
data.append(i32 { mag: 112, sign: true });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 10, sign: true });
data.append(i32 { mag: 1, sign: true });
data.append(i32 { mag: 73, sign: true });
data.append(i32 { mag: 21, sign: false });
data.append(i32 { mag: 65, sign: true });
data.append(i32 { mag: 76, sign: true });
data.append(i32 { mag: 5, sign: true });
data.append(i32 { mag: 90, sign: true });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 75, sign: true });
data.append(i32 { mag: 36, sign: true });
data.append(i32 { mag: 71, sign: false });
data.append(i32 { mag: 45, sign: true });
data.append(i32 { mag: 82, sign: false });
data.append(i32 { mag: 13, sign: false });
data.append(i32 { mag: 5, sign: false });
data.append(i32 { mag: 81, sign: false }); |
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 13, sign: true });
data.append(i32 { mag: 22, sign: false });
data.append(i32 { mag: 28, sign: true });
data.append(i32 { mag: 46, sign: true });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 110, sign: true });
data.append(i32 { mag: 3, sign: true });
data.append(i32 { mag: 82, sign: true });
data.append(i32 { mag: 16, sign: false });
data.append(i32 { mag: 32, sign: false });
data.append(i32 { mag: 12, sign: false });
data.append(i32 { mag: 31, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 45, sign: false });
data.append(i32 { mag: 30, sign: true });
data.append(i32 { mag: 87, sign: true });
data.append(i32 { mag: 125, sign: true });
TensorTrait::new(shape.span(), data.span())
} |
use array::ArrayTrait;
use orion::operators::tensor::{TensorTrait, Tensor, I32Tensor};
use orion::numbers::i32;
fn input() -> Tensor<i32> {
let mut shape = ArrayTrait::<usize>::new();
shape.append(196);
let mut data = ArrayTrait::<i32>::new();
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false |
});
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 14, sign: false });
data.append(i32 { mag: 24, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 220, sign: false });
data.append(i32 { mag: 216, sign: false });
data.append(i32 { mag: 255, sign: false });
data.append(i32 { mag: 240, sign: false });
data.append(i32 { mag: 246, sign: false });
data.append(i32 { mag: 245, sign: false });
data.append(i32 { mag: 237, sign: false });
data.append(i32 { mag: 114, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 27, sign: false });
data.append(i32 { mag: 26, sign: false });
data.append(i32 { mag: 171, sign: false });
data.append(i32 { mag: 108, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false |
});
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 19, sign: false });
data.append(i32 { mag: 255, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 207, sign: false });
data.append(i32 { mag: 72, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 1, sign: false });
data.append(i32 { mag: 20, sign: false });
data.append(i32 { mag: 255, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.ap |
pend(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 244, sign: false });
data.append(i32 { mag: 73, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 3, sign: false });
data.append(i32 { mag: 120, sign: false });
data.append(i32 { mag: 187, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 28, sign: false });
data.append(i32 { mag: 255, sign: false });
data.append(i32 { mag: 6, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag |
: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 179, sign: false });
data.append(i32 { mag: 255, sign: false });
data.append(i32 { mag: 2, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
data.append(i32 { mag: 0, sign: false });
TensorTrait::new(shape.span(), data.span())
} |
// use orion::operators::tensor::core::TensorTrait;
// use core::array::{SpanTrait, ArrayTrait};
// use mnist_nn::nn::fc1;
// use mnist_nn::nn::fc2;
// use mnist_nn::generated::input::input;
// use mnist_nn::generated::fc1_bias::fc1_bias;
// use mnist_nn::generated::fc1_weights::fc1_weights;
// use mnist_nn::generated::fc2_bias::fc2_bias;
// use mnist_nn::generated::fc2_weights::fc2_weights;
// use orion::operators::tensor::implementations::impl_tensor_fp::Tensor_fp;
// fn main() -> u32 {
// let input = input();
// let fc1_bias = fc1_bias();
// let fc1_weights = fc1_weights();
// let fc2_bias = fc2_bias();
// let fc2_weights = fc2_weights();
// let x = fc1(input, fc1_weights, fc1_bias);
// let x = fc2(x, fc2_weights, fc2_bias);
// let x = *x.argmax(0, Option::None(()), Option::None(())).data.at(0);
// x
// } |
mod generated;
mod nn;
mod test;
mod inference; |
use orion::operators::tensor::core::Tensor;
use orion::numbers::signed_integer::{integer_trait::IntegerTrait, i32::i32};
use orion::operators::nn::{NNTrait, I32NN};
fn fc1(i: Tensor<i32>, w: Tensor<i32>, b: Tensor<i32>) -> Tensor<i32> {
let x = NNTrait::linear(i, w, b);
NNTrait::relu(@x)
}
fn fc2(i: Tensor<i32>, w: Tensor<i32>, b: Tensor<i32>) -> Tensor<i32> {
NNTrait::linear(i, w, b)
}
|
use core::array::SpanTrait;
use mnist_nn::nn::fc1;
use mnist_nn::nn::fc2;
use mnist_nn::generated::input::input;
use mnist_nn::generated::fc1_bias::fc1_bias;
use mnist_nn::generated::fc1_weights::fc1_weights;
use mnist_nn::generated::fc2_bias::fc2_bias;
use mnist_nn::generated::fc2_weights::fc2_weights;
use orion::operators::tensor::{I32Tensor, Tensor};
use orion::numbers::i32;
#[test]
#[available_gas(99999999999999999)]
fn mnist_nn_test() {
let input = input();
let fc1_bias = fc1_bias();
let fc1_weights = fc1_weights();
let fc2_bias = fc2_bias();
let fc2_weights = fc2_weights();
let x = fc1(input, fc1_weights, fc1_bias);
let x = fc2(x, fc2_weights, fc2_bias);
let x = *x.argmax(0, Option::None(()), Option::None(())).data.at(0);
assert(x == 7, 'should predict 7');
} |
{
"cells": [
{
"cell_type": "code",
"execution_count": 7,
"id": "c7d8c871",
"metadata": {},
"outputs": [],
"source": [
"def fp16x16_to_decimal(fp_number):\n",
" whole_number = (fp_number >> 16) & 0xFFFF\n",
" fractional_part = fp_number & 0xFFFF\n",
" decimal_value = whole_number + (fractional_part / 65536)
" return decimal_value\n",
"\n",
"def decimal_to_fp16x16(decimal_number):\n",
" whole_number = int(decimal_number)\n",
" fractional_part = int((decimal_number - whole_number) * 65536)
" fp_number = (whole_number << 16) + fractional_part\n",
" return fp_number\n",
"\n",
"def hex_to_decimal(hex_string):\n",
" try:\n",
" decimal_number = int(hex_string, 16)\n",
" return decimal_number\n",
" except ValueError:\n",
" return \"Invalid hexadecimal input\"\n",
" \n",
"def fp16x16_hex_to_decimal(hex_string):\n",
" hex_to_decimal_variable = hex_to_decimal(hex_string)\n",
" decimal_value = fp16x16_to_decimal(hex_to_decimal_variable)\n",
" return decimal_value\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "b0d907a8",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"38.45289611816406"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"felt_to_number(\"0x2673f1\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9fe1872d",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
} |
{
"cells": [
{
"cell_type": "markdown",
"id": "4a28cde5",
"metadata": {},
"source": [
"
"\n",
"Simple Linear Regression model is a foundational technique used to determine the linear relationship between an independent variables (predictors) and a dependent variable (outcome) . By identifying the line of best fit, we can make informed predictions based on new data points or decipher how changes in one variable may lead to changes in another. \n",
"\n",
"The following is a small run through of the implementation of a Simple Linear Regression model using <b>Ordinary Least Squares</b> (OLS) in python, which we will in later stages convert it to Cairo to turn it into a <b>\"Verifiable Linear Regression model\" </b>. By utilysing the <b>Orion's</b> library we will be able to add an extra layer of transparency and robustness enabling us to make <b>verifiable inferences</b> which can be easily <b>proved</b> using the LambdaClass STARK Prover.\n",
"\n",
"In this particular exercise, we'll replicate the entire linear regression model in Cairo. This approach will not only enable us to validate each individual inference made to the model but also allow us to verify all the steps executed during the model's construction phase also. This is to provide an opportunity to get familiar with Orion's main functions and operators along the process. \n"
]
},
{
"cell_type": "markdown",
"id": "2d479a73",
"metadata": {},
"source": [
"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "f60750c4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"X values = [-0.5 -0.49328859 -0.48657718 -0.47986577 -0.47315436 -0.46644295\n",
" -0.45973154 -0.45302013 -0.44630872 -0.43959732 -0.43288591 -0.4261745\n",
" -0.41946309 -0.41275168 -0.40604027 -0.39932886 -0.39261745 -0.38590604\n",
" -0.37919463 -0.37248322 -0.36577181 -0.3590604 -0.35234899 -0.34563758\n", |
" -0.33892617 -0.33221477 -0.32550336 -0.31879195 -0.31208054 -0.30536913\n",
" -0.29865772 -0.29194631 -0.2852349 -0.27852349 -0.27181208 -0.26510067\n",
" -0.25838926 -0.25167785 -0.24496644 -0.23825503 -0.23154362 -0.22483221\n",
" -0.21812081 -0.2114094 -0.20469799 -0.19798658 -0.19127517 -0.18456376\n",
" -0.17785235 -0.17114094 -0.16442953 -0.15771812 -0.15100671 -0.1442953\n",
" -0.13758389 -0.13087248 -0.12416107 -0.11744966 -0.11073826 -0.10402685\n",
" -0.09731544 -0.09060403 -0.08389262 -0.07718121 -0.0704698 -0.06375839\n",
" -0.05704698 -0.05033557 -0.04362416 -0.03691275 -0.03020134 -0.02348993\n",
" -0.01677852 -0.01006711 -0.0033557 0.0033557 0.01006711 0.01677852\n",
" 0.02348993 0.03020134 0.03691275 0.04362416 0.05033557 0.05704698\n",
" 0.06375839 0.0704698 0.07718121 0.08389262 0.09060403 0.09731544\n",
" 0.10402685 0.11073826 0.11744966 0.12416107 0.13087248 0.13758389\n",
" 0.1442953 0.15100671 0.15771812 0.16442953 0.17114094 0.17785235\n",
" 0.18456376 0.19127517 0.19798658 0.20469799 0.2114094 0.21812081\n",
" 0.22483221 0.23154362 0.23825503 0.24496644 0.25167785 0.25838926\n",
" 0.26510067 0.27181208 0.27852349 0.2852349 0.29194631 0.29865772\n",
" 0.30536913 0.31208054 0.31879195 0.32550336 0.33221477 0.33892617\n",
" 0.34563758 0.35234899 0.3590604 0.36577181 0.37248322 0.37919463\n",
" 0.38590604 0.39261745 0.39932886 0.40604027 0.41275168 0.41946309\n",
" 0.4261745 0.43288591 0.43959732 0.44630872 0.45302013 0.45973154\n",
" 0.46644295 0.47315436 0.47986577 0.48657718 0.49328859 0.5 ]\n",
"y values = [4.04967142 3.99959639 4.09161449 4.19257144 4.03027594 4.0437004\n",
" 4.23845819 4.1707032 4.06043511 4.17506137 4.08788642 4.10107803\n",
" 4.18527005 3.98316862 4.01542768 4.14511353 4.11348199 4.25961265\n",
" 4.15080833 4.11380319 4.41502125 |
4.25930156 4.30205483 4.16625001\n",
" 4.26770938 4.34666273 4.23389393 4.39998591 4.31577506 4.36009237\n",
" 4.3425139 4.6013352 4.42818048 4.33718193 4.53863033 4.34771429\n",
" 4.50410784 4.30067728 4.37724851 4.54317606 4.61075941 4.5674724\n",
" 4.55219356 4.54707084 4.44275183 4.53204242 4.57138579 4.73658471\n",
" 4.67865713 4.48141411 4.70354934 4.64605553 4.63029438 4.77257702\n",
" 4.82793217 4.83138305 4.6677561 4.73417943 4.81164983 4.88950082\n",
" 4.7574517 4.80022605 4.72158127 4.72601692 4.94031298 5.00810722\n",
" 4.87870503 4.99968215 4.94891528 4.86166252 4.97573688 5.10682379\n",
" 4.96286035 5.13633014 4.73131408 5.08890166 5.02883894 5.00365631\n",
" 5.05615594 4.86164579 5.05185831 5.12295958 5.24846055 5.06226694\n",
" 5.04666742 5.09076389 5.24590263 5.20066035 5.12823203 5.24595762\n",
" 5.21776145 5.31834101 5.16469402 5.21555593 5.22253415 5.12881629\n",
" 5.31820263 5.32811895 5.31594759 5.30540035 5.2007448 5.31364017\n",
" 5.33485607 5.30232261 5.37984458 5.44980106 5.61143738 5.45369939\n",
" 5.47541947 5.45564266 5.28463295 5.4872815 5.50937873 5.76310273\n",
" 5.51096525 5.5737789 5.5535758 5.45360199 5.6981749 5.67250874\n",
" 5.68984145 5.53322233 5.77786332 5.51082161 5.72311524 5.89689791\n",
" 5.59222154 5.64806821 5.72808594 5.68119606 5.5899001 5.76524556\n",
" 5.66558171 5.83259414 5.70671529 5.96707398 5.74717803 5.80672002\n",
" 5.93370072 5.74268538 5.90194062 6.02333173 5.74529195 5.93792647\n",
" 5.95887419 6.02449101 5.83603647 5.8411087 6.03877134 6.02969847]\n"
]
}
],
"source": [
" |
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