{ "cells": [ { "cell_type": "code", "execution_count": 2, "id": "65b5bd15", "metadata": {}, "outputs": [], "source": [ "import torch" ] }, { "cell_type": "code", "execution_count": 3, "id": "bafde0b2", "metadata": {}, "outputs": [], "source": [ "freqs = 1.0 / (10000 ** (torch.arange(0, 6, 2).float() / 6))" ] }, { "cell_type": "code", "execution_count": 4, "id": "5312d72e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "tensor([1.0000, 0.0464, 0.0022])" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "freqs" ] }, { "cell_type": "code", "execution_count": 7, "id": "8551e607", "metadata": {}, "outputs": [], "source": [ "t = torch.arange(10).float()" ] }, { "cell_type": "code", "execution_count": 10, "id": "cd26f2a2", "metadata": {}, "outputs": [], "source": [ "angles = torch.outer(t, freqs)" ] }, { "cell_type": "code", "execution_count": 12, "id": "fbe2659f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "tensor([[0.0000e+00, 0.0000e+00, 0.0000e+00],\n", " [1.0000e+00, 4.6416e-02, 2.1544e-03],\n", " [2.0000e+00, 9.2832e-02, 4.3089e-03],\n", " [3.0000e+00, 1.3925e-01, 6.4633e-03],\n", " [4.0000e+00, 1.8566e-01, 8.6177e-03],\n", " [5.0000e+00, 2.3208e-01, 1.0772e-02],\n", " [6.0000e+00, 2.7850e-01, 1.2927e-02],\n", " [7.0000e+00, 3.2491e-01, 1.5081e-02],\n", " [8.0000e+00, 3.7133e-01, 1.7235e-02],\n", " [9.0000e+00, 4.1774e-01, 1.9390e-02]])" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "angles" ] }, { "cell_type": "code", "execution_count": 11, "id": "9c9c2c6c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(tensor([[ 1.0000, 1.0000, 1.0000],\n", " [ 0.5403, 0.9989, 1.0000],\n", " [-0.4161, 0.9957, 1.0000],\n", " [-0.9900, 0.9903, 1.0000],\n", " [-0.6536, 0.9828, 1.0000],\n", " [ 0.2837, 0.9732, 0.9999],\n", " [ 0.9602, 0.9615, 0.9999],\n", " [ 0.7539, 0.9477, 0.9999],\n", " [-0.1455, 0.9318, 0.9999],\n", " [-0.9111, 0.9140, 0.9998]]),\n", " tensor([[ 0.0000, 0.0000, 0.0000],\n", " [ 0.8415, 0.0464, 0.0022],\n", " [ 0.9093, 0.0927, 0.0043],\n", " [ 0.1411, 0.1388, 0.0065],\n", " [-0.7568, 0.1846, 0.0086],\n", " [-0.9589, 0.2300, 0.0108],\n", " [-0.2794, 0.2749, 0.0129],\n", " [ 0.6570, 0.3192, 0.0151],\n", " [ 0.9894, 0.3629, 0.0172],\n", " [ 0.4121, 0.4057, 0.0194]]))" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "angles.cos(), angles.sin()" ] }, { "cell_type": "code", "execution_count": 4, "id": "ccec4526", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "tensor([[[0., 0., 0., 0.],\n", " [0., 0., 0., 0.]],\n", "\n", " [[0., 0., 0., 0.],\n", " [0., 0., 0., 0.]],\n", "\n", " [[0., 0., 0., 0.],\n", " [0., 0., 0., 0.]],\n", "\n", " [[0., 0., 0., 0.],\n", " [0., 0., 0., 0.]],\n", "\n", " [[0., 0., 0., 0.],\n", " [0., 0., 0., 0.]],\n", "\n", " [[0., 0., 0., 0.],\n", " [0., 0., 0., 0.]]])" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "torch.zeros(6, 2, 4)" ] }, { "cell_type": "code", "execution_count": null, "id": "fa05b2dc", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "moe-null", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.6" } }, "nbformat": 4, "nbformat_minor": 5 }