mirror of https://github.com/tracel-ai/burn.git
140 lines
3.3 KiB
Plaintext
140 lines
3.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# This notebook demonstrates basic tensor operations in Burn."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "rust"
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}
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},
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"outputs": [],
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"source": [
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"// Dependency declarations for the notebook. WARNING: It may take a while to compile the first time.\n",
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"\n",
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"// The syntax is similar to the one used in the Cargo.toml file. Just prefix with :dep\n",
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"// See: https://github.com/evcxr/evcxr/blob/main/COMMON.md\n",
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"\n",
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":dep burn = {path = \"../../crates/burn\"}\n",
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":dep burn-ndarray = {path = \"../../crates/burn-ndarray\"}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "rust"
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}
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},
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"outputs": [],
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"source": [
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"// Import packages\n",
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"use burn::prelude::*;\n",
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"use burn_ndarray::NdArray;\n",
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"\n",
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"// Type alias for the backend\n",
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"type B = NdArray<f32>;"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Tensor creation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "rust"
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}
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},
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"outputs": [],
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"source": [
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"// A device the tensors will be stored on\n",
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"let device = <B as Backend>::Device::default();\n",
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"// Create an empty tensor for a given shape\n",
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"let tensor: Tensor<B, 3> = Tensor::empty([1, 2, 3], &device);\n",
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"println!(\"Empty tensor: {}\", tensor);\n",
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"\n",
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"// Create a tensor from a slice of floats\n",
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"let tensor: Tensor<B, 2> = Tensor::from_floats([1.0, 2.0, 3.0, 4.0], &device).reshape([2, 2]);\n",
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"println!(\"Tensor from slice: {}\", tensor);\n",
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"\n",
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"// Create a random tensor\n",
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"use burn::tensor::Distribution;\n",
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"let tensor: Tensor<B, 1> = Tensor::random([5], Distribution::Default, &device);\n",
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"println!(\"Random tensor: {}\", tensor);\n",
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"\n",
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"// Create a tensor using fill values, zeros, or ones\n",
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"let tensor: Tensor<B,2> = Tensor::full([2, 2], 7.0, &device);\n",
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"let tensor: Tensor<B,2> = Tensor::zeros([2, 2], &device);\n",
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"let tensor: Tensor<B,2> = Tensor::ones([2, 2], &device);\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Tensor Operations\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "rust"
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}
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},
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"outputs": [],
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"source": [
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"let x1: Tensor<B,2> = Tensor::ones([2, 2], &device);\n",
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"let x2: Tensor<B,2> = Tensor::full([2, 2], 7.0, &device);\n",
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"\n",
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"let x3 = x1 + x2;\n",
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"\n",
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"println!(\"x3 = {}\", x3);"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "rust"
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}
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Rust",
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"language": "rust",
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"name": "rust"
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},
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"language_info": {
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"codemirror_mode": "rust",
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"file_extension": ".rs",
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"mimetype": "text/rust",
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"name": "Rust",
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"pygment_lexer": "rust",
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"version": ""
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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