This was run in a Modal Notebook with Nvidia H100

flux1-schnell-deconstructed.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# FLUX.1 Schnell Experiment\n",
        "\n",
        "Going to try out working with the full source code of FLUX.1 Schnell."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "## First, let's check that weights have been downloaded.\n",
        "!ls -lh /mnt/notebook-flux1-schnell/"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total 23G\r\n",
            "-rw-r--r-- 1 root root 320M Jun 22 03:12 ae.safetensors\r\n",
            "-rw-r--r-- 1 root root  23G Jun 22 03:13 flux1-schnell.safetensors\r\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "%uv pip install einops"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2mUsing Python 3.12.6 environment at: /usr/local\u001b[0m\r\n",
            "\u001b[37m\u280b\u001b[0m \u001b[2mResolving dependencies...                                                     \u001b[0m\r\u001b[2K\u001b[37m\u280b\u001b[0m \u001b[2mResolving dependencies...                                                     \u001b[0m\r\u001b[2K\u001b[37m\u2819\u001b[0m \u001b[2mResolving dependencies...                                                     \u001b[0m\r\u001b[2K\u001b[37m\u2819\u001b[0m \u001b[2meinops==0.8.1                                                                 \u001b[0m\r\u001b[2K\u001b[37m\u2819\u001b[0m \u001b[2m                                                                              \u001b[0m\r\u001b[2K\u001b[2mResolved \u001b[1m1 package\u001b[0m \u001b[2min 169ms\u001b[0m\u001b[0m\r\n",
            "\u001b[37m\u280b\u001b[0m \u001b[2mPreparing packages...\u001b[0m (0/0)                                                   \r\u001b[2K\u001b[37m\u280b\u001b[0m \u001b[2mPreparing packages...\u001b[0m (0/1)                                                   \r\u001b[2K\u001b[37m\u2819\u001b[0m \u001b[2mPreparing packages...\u001b[0m (0/1)                                                   \r\u001b[2K\u001b[37m\u2819\u001b[0m \u001b[2mPreparing packages...\u001b[0m (0/1)\r\n",
            "\u001b[2meinops    \u001b[0m \u001b[32m\u001b[2m------------------------------\u001b[0m\u001b[0m     0 B/62.85 KiB                     \u001b[1A\r\u001b[2K\u001b[1B\r\u001b[2K\u001b[1A\u001b[37m\u2819\u001b[0m \u001b[2mPreparing packages...\u001b[0m (0/1)\r\n",
            "\u001b[2meinops    \u001b[0m \u001b[32m--------\u001b[2m----------------------\u001b[0m\u001b[0m 16.00 KiB/62.85 KiB                   \u001b[1A\r\u001b[2K\u001b[1B\r\u001b[2K\u001b[1A\u001b[37m\u2819\u001b[0m \u001b[2mPreparing packages...\u001b[0m (0/1)\r\n",
            "\u001b[2meinops    \u001b[0m \u001b[32m----------------\u001b[2m--------------\u001b[0m\u001b[0m 32.00 KiB/62.85 KiB                   \u001b[1A\r\u001b[2K\u001b[1B\r\u001b[2K\u001b[1A\u001b[37m\u2819\u001b[0m \u001b[2mPreparing packages...\u001b[0m (0/1)\r\n",
            "\u001b[2meinops    \u001b[0m \u001b[32m-----------------------\u001b[2m-------\u001b[0m\u001b[0m 48.00 KiB/62.85 KiB                   \u001b[1A\r\u001b[2K\u001b[1B\r\u001b[2K\u001b[1A\u001b[37m\u2819\u001b[0m \u001b[2mPreparing packages...\u001b[0m (0/1)\r\n",
            "\u001b[2meinops    \u001b[0m \u001b[32m------------------------------\u001b[2m\u001b[0m\u001b[0m 62.85 KiB/62.85 KiB                   \u001b[1A\r\u001b[2K\u001b[1B\r\u001b[2K\u001b[1A\u001b[37m\u2819\u001b[0m \u001b[2mPreparing packages...\u001b[0m (0/1)                                                   \r\u001b[2K\u001b[37m\u2819\u001b[0m \u001b[2m\u001b[0m (1/1)                                                                        \r\u001b[2K\u001b[2mPrepared \u001b[1m1 package\u001b[0m \u001b[2min 25ms\u001b[0m\u001b[0m\r\n",
            "\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591 [0/0] \u001b[2mInstalling wheels...                                 \u001b[0m\r\u001b[2K\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591 [0/1] \u001b[2mInstalling wheels...                                 \u001b[0m\r\u001b[2K\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591\u2591 [0/1] \u001b[2meinops==0.8.1                                        \u001b[0m\r\u001b[2K\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 [1/1] \u001b[2meinops==0.8.1                                        \u001b[0m\r\u001b[2K\u001b[2mInstalled \u001b[1m1 package\u001b[0m \u001b[2min 29ms\u001b[0m\u001b[0m\r\n",
            " \u001b[32m+\u001b[39m \u001b[1meinops\u001b[0m\u001b[2m==0.8.1\u001b[0m\r\n",
            "Note: you may need to restart the kernel to use updated packages.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "from dataclasses import dataclass\n",
        "\n",
        "import torch\n",
        "from einops import rearrange\n",
        "from torch import Tensor, nn\n",
        "\n",
        "\n",
        "@dataclass\n",
        "class AutoEncoderParams:\n",
        "    resolution: int\n",
        "    in_channels: int\n",
        "    ch: int\n",
        "    out_ch: int\n",
        "    ch_mult: list[int]\n",
        "    num_res_blocks: int\n",
        "    z_channels: int\n",
        "    scale_factor: float\n",
        "    shift_factor: float\n",
        "\n",
        "\n",
        "def swish(x: Tensor) -> Tensor:\n",
        "    return x * torch.sigmoid(x)\n",
        "\n",
        "\n",
        "class AttnBlock(nn.Module):\n",
        "    def __init__(self, in_channels: int):\n",
        "        super().__init__()\n",
        "        self.in_channels = in_channels\n",
        "\n",
        "        self.norm = nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True)\n",
        "\n",
        "        self.q = nn.Conv2d(in_channels, in_channels, kernel_size=1)\n",
        "        self.k = nn.Conv2d(in_channels, in_channels, kernel_size=1)\n",
        "        self.v = nn.Conv2d(in_channels, in_channels, kernel_size=1)\n",
        "        self.proj_out = nn.Conv2d(in_channels, in_channels, kernel_size=1)\n",
        "\n",
        "    def attention(self, h_: Tensor) -> Tensor:\n",
        "        h_ = self.norm(h_)\n",
        "        q = self.q(h_)\n",
        "        k = self.k(h_)\n",
        "        v = self.v(h_)\n",
        "\n",
        "        b, c, h, w = q.shape\n",
        "        q = rearrange(q, \"b c h w -> b 1 (h w) c\").contiguous()\n",
        "        k = rearrange(k, \"b c h w -> b 1 (h w) c\").contiguous()\n",
        "        v = rearrange(v, \"b c h w -> b 1 (h w) c\").contiguous()\n",
        "        h_ = nn.functional.scaled_dot_product_attention(q, k, v)\n",
        "\n",
        "        return rearrange(h_, \"b 1 (h w) c -> b c h w\", h=h, w=w, c=c, b=b)\n",
        "\n",
        "    def forward(self, x: Tensor) -> Tensor:\n",
        "        return x + self.proj_out(self.attention(x))\n",
        "\n",
        "\n",
        "class ResnetBlock(nn.Module):\n",
        "    def __init__(self, in_channels: int, out_channels: int):\n",
        "        super().__init__()\n",
        "        self.in_channels = in_channels\n",
        "        out_channels = in_channels if out_channels is None else out_channels\n",
        "        self.out_channels = out_channels\n",
        "\n",
        "        self.norm1 = nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True)\n",
        "        self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=1, padding=1)\n",
        "        self.norm2 = nn.GroupNorm(num_groups=32, num_channels=out_channels, eps=1e-6, affine=True)\n",
        "        self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1, padding=1)\n",
        "        if self.in_channels != self.out_channels:\n",
        "            self.nin_shortcut = nn.Conv2d(in_channels, out_channels, kernel_size=1, stride=1, padding=0)\n",
        "\n",
        "    def forward(self, x):\n",
        "        h = x\n",
        "        h = self.norm1(h)\n",
        "        h = swish(h)\n",
        "        h = self.conv1(h)\n",
        "\n",
        "        h = self.norm2(h)\n",
        "        h = swish(h)\n",
        "        h = self.conv2(h)\n",
        "\n",
        "        if self.in_channels != self.out_channels:\n",
        "            x = self.nin_shortcut(x)\n",
        "\n",
        "        return x + h\n",
        "\n",
        "\n",
        "class Downsample(nn.Module):\n",
        "    def __init__(self, in_channels: int):\n",
        "        super().__init__()\n",
        "        # no asymmetric padding in torch conv, must do it ourselves\n",
        "        self.conv = nn.Conv2d(in_channels, in_channels, kernel_size=3, stride=2, padding=0)\n",
        "\n",
        "    def forward(self, x: Tensor):\n",
        "        pad = (0, 1, 0, 1)\n",
        "        x = nn.functional.pad(x, pad, mode=\"constant\", value=0)\n",
        "        x = self.conv(x)\n",
        "        return x\n",
        "\n",
        "\n",
        "class Upsample(nn.Module):\n",
        "    def __init__(self, in_channels: int):\n",
        "        super().__init__()\n",
        "        self.conv = nn.Conv2d(in_channels, in_channels, kernel_size=3, stride=1, padding=1)\n",
        "\n",
        "    def forward(self, x: Tensor):\n",
        "        x = nn.functional.interpolate(x, scale_factor=2.0, mode=\"nearest\")\n",
        "        x = self.conv(x)\n",
        "        return x\n",
        "\n",
        "\n",
        "class Encoder(nn.Module):\n",
        "    def __init__(\n",
        "        self,\n",
        "        resolution: int,\n",
        "        in_channels: int,\n",
        "        ch: int,\n",
        "        ch_mult: list[int],\n",
        "        num_res_blocks: int,\n",
        "        z_channels: int,\n",
        "    ):\n",
        "        super().__init__()\n",
        "        self.ch = ch\n",
        "        self.num_resolutions = len(ch_mult)\n",
        "        self.num_res_blocks = num_res_blocks\n",
        "        self.resolution = resolution\n",
        "        self.in_channels = in_channels\n",
        "        # downsampling\n",
        "        self.conv_in = nn.Conv2d(in_channels, self.ch, kernel_size=3, stride=1, padding=1)\n",
        "\n",
        "        curr_res = resolution\n",
        "        in_ch_mult = (1,) + tuple(ch_mult)\n",
        "        self.in_ch_mult = in_ch_mult\n",
        "        self.down = nn.ModuleList()\n",
        "        block_in = self.ch\n",
        "        for i_level in range(self.num_resolutions):\n",
        "            block = nn.ModuleList()\n",
        "            attn = nn.ModuleList()\n",
        "            block_in = ch * in_ch_mult[i_level]\n",
        "            block_out = ch * ch_mult[i_level]\n",
        "            for _ in range(self.num_res_blocks):\n",
        "                block.append(ResnetBlock(in_channels=block_in, out_channels=block_out))\n",
        "                block_in = block_out\n",
        "            down = nn.Module()\n",
        "            down.block = block\n",
        "            down.attn = attn\n",
        "            if i_level != self.num_resolutions - 1:\n",
        "                down.downsample = Downsample(block_in)\n",
        "                curr_res = curr_res // 2\n",
        "            self.down.append(down)\n",
        "\n",
        "        # middle\n",
        "        self.mid = nn.Module()\n",
        "        self.mid.block_1 = ResnetBlock(in_channels=block_in, out_channels=block_in)\n",
        "        self.mid.attn_1 = AttnBlock(block_in)\n",
        "        self.mid.block_2 = ResnetBlock(in_channels=block_in, out_channels=block_in)\n",
        "\n",
        "        # end\n",
        "        self.norm_out = nn.GroupNorm(num_groups=32, num_channels=block_in, eps=1e-6, affine=True)\n",
        "        self.conv_out = nn.Conv2d(block_in, 2 * z_channels, kernel_size=3, stride=1, padding=1)\n",
        "\n",
        "    def forward(self, x: Tensor) -> Tensor:\n",
        "        # downsampling\n",
        "        hs = [self.conv_in(x)]\n",
        "        for i_level in range(self.num_resolutions):\n",
        "            for i_block in range(self.num_res_blocks):\n",
        "                h = self.down[i_level].block[i_block](hs[-1])\n",
        "                if len(self.down[i_level].attn) > 0:\n",
        "                    h = self.down[i_level].attn[i_block](h)\n",
        "                hs.append(h)\n",
        "            if i_level != self.num_resolutions - 1:\n",
        "                hs.append(self.down[i_level].downsample(hs[-1]))\n",
        "\n",
        "        # middle\n",
        "        h = hs[-1]\n",
        "        h = self.mid.block_1(h)\n",
        "        h = self.mid.attn_1(h)\n",
        "        h = self.mid.block_2(h)\n",
        "        # end\n",
        "        h = self.norm_out(h)\n",
        "        h = swish(h)\n",
        "        h = self.conv_out(h)\n",
        "        return h\n",
        "\n",
        "\n",
        "class Decoder(nn.Module):\n",
        "    def __init__(\n",
        "        self,\n",
        "        ch: int,\n",
        "        out_ch: int,\n",
        "        ch_mult: list[int],\n",
        "        num_res_blocks: int,\n",
        "        in_channels: int,\n",
        "        resolution: int,\n",
        "        z_channels: int,\n",
        "    ):\n",
        "        super().__init__()\n",
        "        self.ch = ch\n",
        "        self.num_resolutions = len(ch_mult)\n",
        "        self.num_res_blocks = num_res_blocks\n",
        "        self.resolution = resolution\n",
        "        self.in_channels = in_channels\n",
        "        self.ffactor = 2 ** (self.num_resolutions - 1)\n",
        "\n",
        "        # compute in_ch_mult, block_in and curr_res at lowest res\n",
        "        block_in = ch * ch_mult[self.num_resolutions - 1]\n",
        "        curr_res = resolution // 2 ** (self.num_resolutions - 1)\n",
        "        self.z_shape = (1, z_channels, curr_res, curr_res)\n",
        "\n",
        "        # z to block_in\n",
        "        self.conv_in = nn.Conv2d(z_channels, block_in, kernel_size=3, stride=1, padding=1)\n",
        "\n",
        "        # middle\n",
        "        self.mid = nn.Module()\n",
        "        self.mid.block_1 = ResnetBlock(in_channels=block_in, out_channels=block_in)\n",
        "        self.mid.attn_1 = AttnBlock(block_in)\n",
        "        self.mid.block_2 = ResnetBlock(in_channels=block_in, out_channels=block_in)\n",
        "\n",
        "        # upsampling\n",
        "        self.up = nn.ModuleList()\n",
        "        for i_level in reversed(range(self.num_resolutions)):\n",
        "            block = nn.ModuleList()\n",
        "            attn = nn.ModuleList()\n",
        "            block_out = ch * ch_mult[i_level]\n",
        "            for _ in range(self.num_res_blocks + 1):\n",
        "                block.append(ResnetBlock(in_channels=block_in, out_channels=block_out))\n",
        "                block_in = block_out\n",
        "            up = nn.Module()\n",
        "            up.block = block\n",
        "            up.attn = attn\n",
        "            if i_level != 0:\n",
        "                up.upsample = Upsample(block_in)\n",
        "                curr_res = curr_res * 2\n",
        "            self.up.insert(0, up)  # prepend to get consistent order\n",
        "\n",
        "        # end\n",
        "        self.norm_out = nn.GroupNorm(num_groups=32, num_channels=block_in, eps=1e-6, affine=True)\n",
        "        self.conv_out = nn.Conv2d(block_in, out_ch, kernel_size=3, stride=1, padding=1)\n",
        "\n",
        "    def forward(self, z: Tensor) -> Tensor:\n",
        "        # get dtype for proper tracing\n",
        "        upscale_dtype = next(self.up.parameters()).dtype\n",
        "\n",
        "        # z to block_in\n",
        "        h = self.conv_in(z)\n",
        "\n",
        "        # middle\n",
        "        h = self.mid.block_1(h)\n",
        "        h = self.mid.attn_1(h)\n",
        "        h = self.mid.block_2(h)\n",
        "\n",
        "        # cast to proper dtype\n",
        "        h = h.to(upscale_dtype)\n",
        "        # upsampling\n",
        "        for i_level in reversed(range(self.num_resolutions)):\n",
        "            for i_block in range(self.num_res_blocks + 1):\n",
        "                h = self.up[i_level].block[i_block](h)\n",
        "                if len(self.up[i_level].attn) > 0:\n",
        "                    h = self.up[i_level].attn[i_block](h)\n",
        "            if i_level != 0:\n",
        "                h = self.up[i_level].upsample(h)\n",
        "\n",
        "        # end\n",
        "        h = self.norm_out(h)\n",
        "        h = swish(h)\n",
        "        h = self.conv_out(h)\n",
        "        return h\n",
        "\n",
        "\n",
        "class DiagonalGaussian(nn.Module):\n",
        "    def __init__(self, sample: bool = True, chunk_dim: int = 1):\n",
        "        super().__init__()\n",
        "        self.sample = sample\n",
        "        self.chunk_dim = chunk_dim\n",
        "\n",
        "    def forward(self, z: Tensor) -> Tensor:\n",
        "        mean, logvar = torch.chunk(z, 2, dim=self.chunk_dim)\n",
        "        if self.sample:\n",
        "            std = torch.exp(0.5 * logvar)\n",
        "            return mean + std * torch.randn_like(mean)\n",
        "        else:\n",
        "            return mean\n",
        "\n",
        "\n",
        "class AutoEncoder(nn.Module):\n",
        "    def __init__(self, params: AutoEncoderParams):\n",
        "        super().__init__()\n",
        "        self.params = params\n",
        "        self.encoder = Encoder(\n",
        "            resolution=params.resolution,\n",
        "            in_channels=params.in_channels,\n",
        "            ch=params.ch,\n",
        "            ch_mult=params.ch_mult,\n",
        "            num_res_blocks=params.num_res_blocks,\n",
        "            z_channels=params.z_channels,\n",
        "        )\n",
        "        self.decoder = Decoder(\n",
        "            resolution=params.resolution,\n",
        "            in_channels=params.in_channels,\n",
        "            ch=params.ch,\n",
        "            out_ch=params.out_ch,\n",
        "            ch_mult=params.ch_mult,\n",
        "            num_res_blocks=params.num_res_blocks,\n",
        "            z_channels=params.z_channels,\n",
        "        )\n",
        "        self.reg = DiagonalGaussian()\n",
        "\n",
        "        self.scale_factor = params.scale_factor\n",
        "        self.shift_factor = params.shift_factor\n",
        "\n",
        "    def encode(self, x: Tensor) -> Tensor:\n",
        "        z = self.reg(self.encoder(x))\n",
        "        z = self.scale_factor * (z - self.shift_factor)\n",
        "        return z\n",
        "\n",
        "    def decode(self, z: Tensor) -> Tensor:\n",
        "        z = z / self.scale_factor + self.shift_factor\n",
        "        return self.decoder(z)\n",
        "\n",
        "    def forward(self, x: Tensor) -> Tensor:\n",
        "        return self.decode(self.encode(x))"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "from safetensors.torch import load_file\n",
        "\n",
        "# schnell parameters\n",
        "\n",
        "ae_params = AutoEncoderParams(\n",
        "    resolution=256,\n",
        "    in_channels=3,\n",
        "    ch=128,\n",
        "    out_ch=3,\n",
        "    ch_mult=[1, 2, 4, 4],\n",
        "    num_res_blocks=2,\n",
        "    z_channels=16,\n",
        "    scale_factor=0.3611,\n",
        "    shift_factor=0.1159,\n",
        ")\n",
        "\n",
        "# Load parameters from checkpoint\n",
        "state_dict = load_file(\"/mnt/notebook-flux1-schnell/ae.safetensors\")\n",
        "\n",
        "ae = AutoEncoder(ae_params)\n",
        "ae.load_state_dict(state_dict)\n",
        "ae.cuda()\n",
        "\n",
        "ae"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 4,
          "data": {
            "text/plain": "AutoEncoder(\n  (encoder): Encoder(\n    (conv_in): Conv2d(3, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n    (down): ModuleList(\n      (0): Module(\n        (block): ModuleList(\n          (0-1): 2 x ResnetBlock(\n            (norm1): GroupNorm(32, 128, eps=1e-06, affine=True)\n            (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 128, eps=1e-06, affine=True)\n            (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n          )\n        )\n        (attn): ModuleList()\n        (downsample): Downsample(\n          (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2))\n        )\n      )\n      (1): Module(\n        (block): ModuleList(\n          (0): ResnetBlock(\n            (norm1): GroupNorm(32, 128, eps=1e-06, affine=True)\n            (conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 256, eps=1e-06, affine=True)\n            (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (nin_shortcut): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1))\n          )\n          (1): ResnetBlock(\n            (norm1): GroupNorm(32, 256, eps=1e-06, affine=True)\n            (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 256, eps=1e-06, affine=True)\n            (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n          )\n        )\n        (attn): ModuleList()\n        (downsample): Downsample(\n          (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2))\n        )\n      )\n      (2): Module(\n        (block): ModuleList(\n          (0): ResnetBlock(\n            (norm1): GroupNorm(32, 256, eps=1e-06, affine=True)\n            (conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 512, eps=1e-06, affine=True)\n            (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (nin_shortcut): Conv2d(256, 512, kernel_size=(1, 1), stride=(1, 1))\n          )\n          (1): ResnetBlock(\n            (norm1): GroupNorm(32, 512, eps=1e-06, affine=True)\n            (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 512, eps=1e-06, affine=True)\n            (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n          )\n        )\n        (attn): ModuleList()\n        (downsample): Downsample(\n          (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2))\n        )\n      )\n      (3): Module(\n        (block): ModuleList(\n          (0-1): 2 x ResnetBlock(\n            (norm1): GroupNorm(32, 512, eps=1e-06, affine=True)\n            (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 512, eps=1e-06, affine=True)\n            (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n          )\n        )\n        (attn): ModuleList()\n      )\n    )\n    (mid): Module(\n      (block_1): ResnetBlock(\n        (norm1): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n        (norm2): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n      )\n      (attn_1): AttnBlock(\n        (norm): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (q): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n        (k): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n        (v): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n        (proj_out): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n      )\n      (block_2): ResnetBlock(\n        (norm1): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n        (norm2): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n      )\n    )\n    (norm_out): GroupNorm(32, 512, eps=1e-06, affine=True)\n    (conv_out): Conv2d(512, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n  )\n  (decoder): Decoder(\n    (conv_in): Conv2d(16, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n    (mid): Module(\n      (block_1): ResnetBlock(\n        (norm1): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n        (norm2): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n      )\n      (attn_1): AttnBlock(\n        (norm): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (q): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n        (k): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n        (v): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n        (proj_out): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n      )\n      (block_2): ResnetBlock(\n        (norm1): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n        (norm2): GroupNorm(32, 512, eps=1e-06, affine=True)\n        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n      )\n    )\n    (up): ModuleList(\n      (0): Module(\n        (block): ModuleList(\n          (0): ResnetBlock(\n            (norm1): GroupNorm(32, 256, eps=1e-06, affine=True)\n            (conv1): Conv2d(256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 128, eps=1e-06, affine=True)\n            (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (nin_shortcut): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n          )\n          (1-2): 2 x ResnetBlock(\n            (norm1): GroupNorm(32, 128, eps=1e-06, affine=True)\n            (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 128, eps=1e-06, affine=True)\n            (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n          )\n        )\n        (attn): ModuleList()\n      )\n      (1): Module(\n        (block): ModuleList(\n          (0): ResnetBlock(\n            (norm1): GroupNorm(32, 512, eps=1e-06, affine=True)\n            (conv1): Conv2d(512, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 256, eps=1e-06, affine=True)\n            (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (nin_shortcut): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n          )\n          (1-2): 2 x ResnetBlock(\n            (norm1): GroupNorm(32, 256, eps=1e-06, affine=True)\n            (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 256, eps=1e-06, affine=True)\n            (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n          )\n        )\n        (attn): ModuleList()\n        (upsample): Upsample(\n          (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n        )\n      )\n      (2-3): 2 x Module(\n        (block): ModuleList(\n          (0-2): 3 x ResnetBlock(\n            (norm1): GroupNorm(32, 512, eps=1e-06, affine=True)\n            (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n            (norm2): GroupNorm(32, 512, eps=1e-06, affine=True)\n            (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n          )\n        )\n        (attn): ModuleList()\n        (upsample): Upsample(\n          (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n        )\n      )\n    )\n    (norm_out): GroupNorm(32, 128, eps=1e-06, affine=True)\n    (conv_out): Conv2d(128, 3, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n  )\n  (reg): DiagonalGaussian()\n)"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "from PIL import Image\n",
        "import numpy as np\n",
        "\n",
        "!curl -o test.jpeg https://i.imgur.com/n8nGkNF.jpeg\n",
        "\n",
        "# Get an image as a (C, H, W) torch tensor\n",
        "im = Image.open(\"test.jpeg\")\n",
        "\n",
        "im = im.resize((256, 256))\n",
        "im_tensor = torch.tensor(np.array(im)).permute(2, 0, 1).float() / 255.0 * 2.0 - 1.0\n",
        "im_tensor = im_tensor.unsqueeze(0).cuda()  # Add batch dimension and move to GPU\n",
        "\n",
        "print(\"Image tensor shape:\", im_tensor.shape)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\r\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\r\n",
            "\r  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\r100  899k  100  899k    0     0  8933k      0 --:--:-- --:--:-- --:--:-- 8999k\r\n",
            "Image tensor shape: torch.Size([1, 3, 256, 256])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.imshow(im_tensor[0].permute(1, 2, 0).cpu() * 0.5 + 0.5)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 9,
          "data": {
            "text/plain": "<matplotlib.image.AxesImage at 0x2b691f3ce5a0>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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",
            "text/plain": "<Figure size 640x480 with 1 Axes>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "with torch.no_grad():\n",
        "    im_encoded = ae.encode(im_tensor)\n",
        "\n",
        "im_encoded.shape"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 10,
          "data": {
            "text/plain": "torch.Size([1, 16, 32, 32])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "import seaborn as sns\n",
        "\n",
        "def plot_latents(latents: torch.Tensor):\n",
        "    plt.figure(figsize=(10, 10))\n",
        "    plt.suptitle(\"16 Encoded Channels\")\n",
        "    plt.axis('off')\n",
        "\n",
        "    for i in range(16):\n",
        "        row, col = divmod(i, 4)\n",
        "        plt.subplot(4, 4, i + 1)\n",
        "        plt.title(f\"Channel {i}\")\n",
        "        plt.imshow(latents[0, i].to(torch.float32).cpu(), cmap='inferno')\n",
        "        plt.axis('off')\n",
        "\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "plot_latents(im_encoded)"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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",
            "text/plain": "<Figure size 1000x1000 with 17 Axes>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "# Great, that's the latent space of the image. Now try decoding.\n",
        "\n",
        "with torch.no_grad():\n",
        "    im_decoded = ae.decode(im_encoded)\n",
        "\n",
        "im_diff = (im_decoded - im_tensor)\n",
        "im_diff.abs().sum() / im_diff.numel()\n",
        "\n",
        "# avg about 0.02 absolute error per pixel, or ~2 hex values off since [-1, 1] -> [0, 255]"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 25,
          "data": {
            "text/plain": "tensor(0.0252, device='cuda:0')"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "plt.imshow((im_decoded[0] * 0.5 + 0.5).permute(1, 2, 0).cpu().clamp(0, 1))"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 26,
          "data": {
            "text/plain": "<matplotlib.image.AxesImage at 0x2b6c0400bfe0>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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",
            "text/plain": "<Figure size 640x480 with 1 Axes>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "# Heatmap of the difference!\n",
        "# It appears that some higher-frequency areas have information lost, which\n",
        "# makes sense, that probably gets squashed out by the autoencoder.\n",
        "sns.heatmap(im_diff[0].mean(dim=0).cpu(), cmap='RdBu_r', center=0, square=True)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 27,
          "data": {
            "text/plain": "<Axes: >"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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",
            "text/plain": "<Figure size 640x480 with 2 Axes>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "im_diff.shape"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 28,
          "data": {
            "text/plain": "torch.Size([1, 3, 256, 256])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Rotary positional embeddings\n",
        "\n",
        "`flux.math` module has a quick implementation of rotary positional embeddings.\n",
        "\n",
        "This is in terms of einops, they rotate the q/k tensors in pairs based\n",
        "on absolute positions, and then when they're multiplied, it cancels each other\n",
        "out and ends up only being dependent on relative positions."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "from torch import Tensor\n",
        "\n",
        "def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor) -> Tensor:\n",
        "    q, k = apply_rope(q, k, pe)\n",
        "\n",
        "    x = torch.nn.functional.scaled_dot_product_attention(q, k, v)\n",
        "    x = rearrange(x, \"B H L D -> B L (H D)\")\n",
        "\n",
        "    return x\n",
        "\n",
        "\n",
        "def rope(pos: Tensor, dim: int, theta: int) -> Tensor:\n",
        "    assert dim % 2 == 0\n",
        "    scale = torch.arange(0, dim, 2, dtype=pos.dtype, device=pos.device) / dim\n",
        "    omega = 1.0 / (theta**scale)\n",
        "    out = torch.einsum(\"...n,d->...nd\", pos, omega)\n",
        "    out = torch.stack([torch.cos(out), -torch.sin(out), torch.sin(out), torch.cos(out)], dim=-1)\n",
        "    out = rearrange(out, \"b n d (i j) -> b n d i j\", i=2, j=2)\n",
        "    return out.float()\n",
        "\n",
        "\n",
        "def apply_rope(xq: Tensor, xk: Tensor, freqs_cis: Tensor) -> tuple[Tensor, Tensor]:\n",
        "    xq_ = xq.float().reshape(*xq.shape[:-1], -1, 1, 2)\n",
        "    xk_ = xk.float().reshape(*xk.shape[:-1], -1, 1, 2)\n",
        "    xq_out = freqs_cis[..., 0] * xq_[..., 0] + freqs_cis[..., 1] * xq_[..., 1]\n",
        "    xk_out = freqs_cis[..., 0] * xk_[..., 0] + freqs_cis[..., 1] * xk_[..., 1]\n",
        "    return xq_out.reshape(*xq.shape).type_as(xq), xk_out.reshape(*xk.shape).type_as(xk)"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "with torch.no_grad():\n",
        "    print(rope(\n",
        "        pos=torch.arange(100).unsqueeze(0),\n",
        "        dim=72,\n",
        "        theta=10_000,\n",
        "    ).shape)  # (batch, seq_len, dim/2, 2, 2) \u2014 ok this makes sense!"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "torch.Size([1, 100, 36, 2, 2])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Layers"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "import math\n",
        "from torch import nn\n",
        "\n",
        "class EmbedND(nn.Module):\n",
        "    def __init__(self, dim: int, theta: int, axes_dim: list[int]):\n",
        "        super().__init__()\n",
        "        self.dim = dim\n",
        "        self.theta = theta\n",
        "        self.axes_dim = axes_dim\n",
        "\n",
        "    def forward(self, ids: Tensor) -> Tensor:\n",
        "        n_axes = ids.shape[-1]\n",
        "        emb = torch.cat(\n",
        "            [rope(ids[..., i], self.axes_dim[i], self.theta) for i in range(n_axes)],\n",
        "            dim=-3,\n",
        "        )\n",
        "\n",
        "        return emb.unsqueeze(1)\n",
        "\n",
        "\n",
        "def timestep_embedding(t: Tensor, dim, max_period=10000, time_factor: float = 1000.0):\n",
        "    \"\"\"\n",
        "    Create sinusoidal timestep embeddings.\n",
        "    :param t: a 1-D Tensor of N indices, one per batch element.\n",
        "                      These may be fractional.\n",
        "    :param dim: the dimension of the output.\n",
        "    :param max_period: controls the minimum frequency of the embeddings.\n",
        "    :return: an (N, D) Tensor of positional embeddings.\n",
        "    \"\"\"\n",
        "    t = time_factor * t\n",
        "    half = dim // 2\n",
        "    freqs = torch.exp(-math.log(max_period) * torch.arange(start=0, end=half, dtype=torch.float32) / half).to(\n",
        "        t.device\n",
        "    )\n",
        "\n",
        "    args = t[:, None].float() * freqs[None]\n",
        "    embedding = torch.cat([torch.cos(args), torch.sin(args)], dim=-1)\n",
        "    if dim % 2:\n",
        "        embedding = torch.cat([embedding, torch.zeros_like(embedding[:, :1])], dim=-1)\n",
        "    if torch.is_floating_point(t):\n",
        "        embedding = embedding.to(t)\n",
        "    return embedding\n",
        "\n",
        "\n",
        "class MLPEmbedder(nn.Module):\n",
        "    def __init__(self, in_dim: int, hidden_dim: int):\n",
        "        super().__init__()\n",
        "        self.in_layer = nn.Linear(in_dim, hidden_dim, bias=True)\n",
        "        self.silu = nn.SiLU()\n",
        "        self.out_layer = nn.Linear(hidden_dim, hidden_dim, bias=True)\n",
        "\n",
        "    def forward(self, x: Tensor) -> Tensor:\n",
        "        return self.out_layer(self.silu(self.in_layer(x)))\n",
        "\n",
        "\n",
        "class RMSNorm(torch.nn.Module):\n",
        "    def __init__(self, dim: int):\n",
        "        super().__init__()\n",
        "        self.scale = nn.Parameter(torch.ones(dim))\n",
        "\n",
        "    def forward(self, x: Tensor):\n",
        "        x_dtype = x.dtype\n",
        "        x = x.float()\n",
        "        rrms = torch.rsqrt(torch.mean(x**2, dim=-1, keepdim=True) + 1e-6)\n",
        "        return (x * rrms).to(dtype=x_dtype) * self.scale\n",
        "\n",
        "\n",
        "class QKNorm(torch.nn.Module):\n",
        "    def __init__(self, dim: int):\n",
        "        super().__init__()\n",
        "        self.query_norm = RMSNorm(dim)\n",
        "        self.key_norm = RMSNorm(dim)\n",
        "\n",
        "    def forward(self, q: Tensor, k: Tensor, v: Tensor) -> tuple[Tensor, Tensor]:\n",
        "        q = self.query_norm(q)\n",
        "        k = self.key_norm(k)\n",
        "        return q.to(v), k.to(v)\n",
        "\n",
        "\n",
        "class SelfAttention(nn.Module):\n",
        "    def __init__(self, dim: int, num_heads: int = 8, qkv_bias: bool = False):\n",
        "        super().__init__()\n",
        "        self.num_heads = num_heads\n",
        "        head_dim = dim // num_heads\n",
        "\n",
        "        self.qkv = nn.Linear(dim, dim * 3, bias=qkv_bias)\n",
        "        self.norm = QKNorm(head_dim)\n",
        "        self.proj = nn.Linear(dim, dim)\n",
        "\n",
        "    def forward(self, x: Tensor, pe: Tensor) -> Tensor:\n",
        "        qkv = self.qkv(x)\n",
        "        q, k, v = rearrange(qkv, \"B L (K H D) -> K B H L D\", K=3, H=self.num_heads)\n",
        "        q, k = self.norm(q, k, v)\n",
        "        x = attention(q, k, v, pe=pe)\n",
        "        x = self.proj(x)\n",
        "        return x\n",
        "\n",
        "\n",
        "@dataclass\n",
        "class ModulationOut:\n",
        "    shift: Tensor\n",
        "    scale: Tensor\n",
        "    gate: Tensor\n",
        "\n",
        "\n",
        "class Modulation(nn.Module):\n",
        "    def __init__(self, dim: int, double: bool):\n",
        "        super().__init__()\n",
        "        self.is_double = double\n",
        "        self.multiplier = 6 if double else 3\n",
        "        self.lin = nn.Linear(dim, self.multiplier * dim, bias=True)\n",
        "\n",
        "    def forward(self, vec: Tensor) -> tuple[ModulationOut, ModulationOut | None]:\n",
        "        out = self.lin(nn.functional.silu(vec))[:, None, :].chunk(self.multiplier, dim=-1)\n",
        "\n",
        "        return (\n",
        "            ModulationOut(*out[:3]),\n",
        "            ModulationOut(*out[3:]) if self.is_double else None,\n",
        "        )\n",
        "\n",
        "\n",
        "class DoubleStreamBlock(nn.Module):\n",
        "    def __init__(self, hidden_size: int, num_heads: int, mlp_ratio: float, qkv_bias: bool = False):\n",
        "        super().__init__()\n",
        "\n",
        "        mlp_hidden_dim = int(hidden_size * mlp_ratio)\n",
        "        self.num_heads = num_heads\n",
        "        self.hidden_size = hidden_size\n",
        "        self.img_mod = Modulation(hidden_size, double=True)\n",
        "        self.img_norm1 = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)\n",
        "        self.img_attn = SelfAttention(dim=hidden_size, num_heads=num_heads, qkv_bias=qkv_bias)\n",
        "\n",
        "        self.img_norm2 = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)\n",
        "        self.img_mlp = nn.Sequential(\n",
        "            nn.Linear(hidden_size, mlp_hidden_dim, bias=True),\n",
        "            nn.GELU(approximate=\"tanh\"),\n",
        "            nn.Linear(mlp_hidden_dim, hidden_size, bias=True),\n",
        "        )\n",
        "\n",
        "        self.txt_mod = Modulation(hidden_size, double=True)\n",
        "        self.txt_norm1 = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)\n",
        "        self.txt_attn = SelfAttention(dim=hidden_size, num_heads=num_heads, qkv_bias=qkv_bias)\n",
        "\n",
        "        self.txt_norm2 = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)\n",
        "        self.txt_mlp = nn.Sequential(\n",
        "            nn.Linear(hidden_size, mlp_hidden_dim, bias=True),\n",
        "            nn.GELU(approximate=\"tanh\"),\n",
        "            nn.Linear(mlp_hidden_dim, hidden_size, bias=True),\n",
        "        )\n",
        "\n",
        "    def forward(self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor) -> tuple[Tensor, Tensor]:\n",
        "        img_mod1, img_mod2 = self.img_mod(vec)\n",
        "        txt_mod1, txt_mod2 = self.txt_mod(vec)\n",
        "\n",
        "        # prepare image for attention\n",
        "        img_modulated = self.img_norm1(img)\n",
        "        img_modulated = (1 + img_mod1.scale) * img_modulated + img_mod1.shift\n",
        "        img_qkv = self.img_attn.qkv(img_modulated)\n",
        "        img_q, img_k, img_v = rearrange(img_qkv, \"B L (K H D) -> K B H L D\", K=3, H=self.num_heads)\n",
        "        img_q, img_k = self.img_attn.norm(img_q, img_k, img_v)\n",
        "\n",
        "        # prepare txt for attention\n",
        "        txt_modulated = self.txt_norm1(txt)\n",
        "        txt_modulated = (1 + txt_mod1.scale) * txt_modulated + txt_mod1.shift\n",
        "        txt_qkv = self.txt_attn.qkv(txt_modulated)\n",
        "        txt_q, txt_k, txt_v = rearrange(txt_qkv, \"B L (K H D) -> K B H L D\", K=3, H=self.num_heads)\n",
        "        txt_q, txt_k = self.txt_attn.norm(txt_q, txt_k, txt_v)\n",
        "\n",
        "        # run actual attention\n",
        "        q = torch.cat((txt_q, img_q), dim=2)\n",
        "        k = torch.cat((txt_k, img_k), dim=2)\n",
        "        v = torch.cat((txt_v, img_v), dim=2)\n",
        "\n",
        "        attn = attention(q, k, v, pe=pe)\n",
        "        txt_attn, img_attn = attn[:, : txt.shape[1]], attn[:, txt.shape[1] :]\n",
        "\n",
        "        # calculate the img bloks\n",
        "        img = img + img_mod1.gate * self.img_attn.proj(img_attn)\n",
        "        img = img + img_mod2.gate * self.img_mlp((1 + img_mod2.scale) * self.img_norm2(img) + img_mod2.shift)\n",
        "\n",
        "        # calculate the txt bloks\n",
        "        txt = txt + txt_mod1.gate * self.txt_attn.proj(txt_attn)\n",
        "        txt = txt + txt_mod2.gate * self.txt_mlp((1 + txt_mod2.scale) * self.txt_norm2(txt) + txt_mod2.shift)\n",
        "        return img, txt\n",
        "\n",
        "\n",
        "class SingleStreamBlock(nn.Module):\n",
        "    \"\"\"\n",
        "    A DiT block with parallel linear layers as described in\n",
        "    https://arxiv.org/abs/2302.05442 and adapted modulation interface.\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(\n",
        "        self,\n",
        "        hidden_size: int,\n",
        "        num_heads: int,\n",
        "        mlp_ratio: float = 4.0,\n",
        "        qk_scale: float | None = None,\n",
        "    ):\n",
        "        super().__init__()\n",
        "        self.hidden_dim = hidden_size\n",
        "        self.num_heads = num_heads\n",
        "        head_dim = hidden_size // num_heads\n",
        "        self.scale = qk_scale or head_dim**-0.5\n",
        "\n",
        "        self.mlp_hidden_dim = int(hidden_size * mlp_ratio)\n",
        "        # qkv and mlp_in\n",
        "        self.linear1 = nn.Linear(hidden_size, hidden_size * 3 + self.mlp_hidden_dim)\n",
        "        # proj and mlp_out\n",
        "        self.linear2 = nn.Linear(hidden_size + self.mlp_hidden_dim, hidden_size)\n",
        "\n",
        "        self.norm = QKNorm(head_dim)\n",
        "\n",
        "        self.hidden_size = hidden_size\n",
        "        self.pre_norm = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)\n",
        "\n",
        "        self.mlp_act = nn.GELU(approximate=\"tanh\")\n",
        "        self.modulation = Modulation(hidden_size, double=False)\n",
        "\n",
        "    def forward(self, x: Tensor, vec: Tensor, pe: Tensor) -> Tensor:\n",
        "        mod, _ = self.modulation(vec)\n",
        "        x_mod = (1 + mod.scale) * self.pre_norm(x) + mod.shift\n",
        "        qkv, mlp = torch.split(self.linear1(x_mod), [3 * self.hidden_size, self.mlp_hidden_dim], dim=-1)\n",
        "\n",
        "        q, k, v = rearrange(qkv, \"B L (K H D) -> K B H L D\", K=3, H=self.num_heads)\n",
        "        q, k = self.norm(q, k, v)\n",
        "\n",
        "        # compute attention\n",
        "        attn = attention(q, k, v, pe=pe)\n",
        "        # compute activation in mlp stream, cat again and run second linear layer\n",
        "        output = self.linear2(torch.cat((attn, self.mlp_act(mlp)), 2))\n",
        "        return x + mod.gate * output\n",
        "\n",
        "\n",
        "class LastLayer(nn.Module):\n",
        "    def __init__(self, hidden_size: int, patch_size: int, out_channels: int):\n",
        "        super().__init__()\n",
        "        self.norm_final = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)\n",
        "        self.linear = nn.Linear(hidden_size, patch_size * patch_size * out_channels, bias=True)\n",
        "        self.adaLN_modulation = nn.Sequential(nn.SiLU(), nn.Linear(hidden_size, 2 * hidden_size, bias=True))\n",
        "\n",
        "    def forward(self, x: Tensor, vec: Tensor) -> Tensor:\n",
        "        shift, scale = self.adaLN_modulation(vec).chunk(2, dim=1)\n",
        "        x = (1 + scale[:, None, :]) * self.norm_final(x) + shift[:, None, :]\n",
        "        x = self.linear(x)\n",
        "        return x"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Flux model code\n",
        "\n",
        "LoRA layers have been removed."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "@dataclass\n",
        "class FluxParams:\n",
        "    in_channels: int\n",
        "    out_channels: int\n",
        "    vec_in_dim: int\n",
        "    context_in_dim: int\n",
        "    hidden_size: int\n",
        "    mlp_ratio: float\n",
        "    num_heads: int\n",
        "    depth: int\n",
        "    depth_single_blocks: int\n",
        "    axes_dim: list[int]\n",
        "    theta: int\n",
        "    qkv_bias: bool\n",
        "    guidance_embed: bool\n",
        "\n",
        "\n",
        "class Flux(nn.Module):\n",
        "    \"\"\"\n",
        "    Transformer model for flow matching on sequences.\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(self, params: FluxParams):\n",
        "        super().__init__()\n",
        "\n",
        "        self.params = params\n",
        "        self.in_channels = params.in_channels\n",
        "        self.out_channels = params.out_channels\n",
        "        if params.hidden_size % params.num_heads != 0:\n",
        "            raise ValueError(\n",
        "                f\"Hidden size {params.hidden_size} must be divisible by num_heads {params.num_heads}\"\n",
        "            )\n",
        "        pe_dim = params.hidden_size // params.num_heads\n",
        "        if sum(params.axes_dim) != pe_dim:\n",
        "            raise ValueError(f\"Got {params.axes_dim} but expected positional dim {pe_dim}\")\n",
        "        self.hidden_size = params.hidden_size\n",
        "        self.num_heads = params.num_heads\n",
        "        self.pe_embedder = EmbedND(dim=pe_dim, theta=params.theta, axes_dim=params.axes_dim)\n",
        "        self.img_in = nn.Linear(self.in_channels, self.hidden_size, bias=True)\n",
        "        self.time_in = MLPEmbedder(in_dim=256, hidden_dim=self.hidden_size)\n",
        "        self.vector_in = MLPEmbedder(params.vec_in_dim, self.hidden_size)\n",
        "        self.guidance_in = (\n",
        "            MLPEmbedder(in_dim=256, hidden_dim=self.hidden_size) if params.guidance_embed else nn.Identity()\n",
        "        )\n",
        "        self.txt_in = nn.Linear(params.context_in_dim, self.hidden_size)\n",
        "\n",
        "        self.double_blocks = nn.ModuleList(\n",
        "            [\n",
        "                DoubleStreamBlock(\n",
        "                    self.hidden_size,\n",
        "                    self.num_heads,\n",
        "                    mlp_ratio=params.mlp_ratio,\n",
        "                    qkv_bias=params.qkv_bias,\n",
        "                )\n",
        "                for _ in range(params.depth)\n",
        "            ]\n",
        "        )\n",
        "\n",
        "        self.single_blocks = nn.ModuleList(\n",
        "            [\n",
        "                SingleStreamBlock(self.hidden_size, self.num_heads, mlp_ratio=params.mlp_ratio)\n",
        "                for _ in range(params.depth_single_blocks)\n",
        "            ]\n",
        "        )\n",
        "\n",
        "        self.final_layer = LastLayer(self.hidden_size, 1, self.out_channels)\n",
        "\n",
        "    def forward(\n",
        "        self,\n",
        "        img: Tensor,\n",
        "        img_ids: Tensor,\n",
        "        txt: Tensor,\n",
        "        txt_ids: Tensor,\n",
        "        timesteps: Tensor,\n",
        "        y: Tensor,\n",
        "        guidance: Tensor | None = None,\n",
        "    ) -> Tensor:\n",
        "        if img.ndim != 3 or txt.ndim != 3:\n",
        "            raise ValueError(\"Input img and txt tensors must have 3 dimensions.\")\n",
        "\n",
        "        # running on sequences img\n",
        "        img = self.img_in(img)\n",
        "        vec = self.time_in(timestep_embedding(timesteps, 256))\n",
        "        if self.params.guidance_embed:\n",
        "            if guidance is None:\n",
        "                raise ValueError(\"Didn't get guidance strength for guidance distilled model.\")\n",
        "            vec = vec + self.guidance_in(timestep_embedding(guidance, 256))\n",
        "        vec = vec + self.vector_in(y)\n",
        "        txt = self.txt_in(txt)\n",
        "\n",
        "        ids = torch.cat((txt_ids, img_ids), dim=1)\n",
        "        pe = self.pe_embedder(ids)\n",
        "\n",
        "        for block in self.double_blocks:\n",
        "            img, txt = block(img=img, txt=txt, vec=vec, pe=pe)\n",
        "\n",
        "        img = torch.cat((txt, img), 1)\n",
        "        for block in self.single_blocks:\n",
        "            img = block(img, vec=vec, pe=pe)\n",
        "        img = img[:, txt.shape[1] :, ...]\n",
        "\n",
        "        img = self.final_layer(img, vec)  # (N, T, patch_size ** 2 * out_channels)\n",
        "        return img"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "# FLUX.1 Schnell\n",
        "params = FluxParams(\n",
        "    in_channels=64,\n",
        "    out_channels=64,\n",
        "    vec_in_dim=768,\n",
        "    context_in_dim=4096,\n",
        "    hidden_size=3072,\n",
        "    mlp_ratio=4.0,\n",
        "    num_heads=24,\n",
        "    depth=19,\n",
        "    depth_single_blocks=38,\n",
        "    axes_dim=[16, 56, 56],\n",
        "    theta=10_000,\n",
        "    qkv_bias=True,\n",
        "    guidance_embed=False,\n",
        ")"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "model = Flux(params).to(torch.bfloat16)\n",
        "\n",
        "# Load weights. This takes a while, 22 GB.\n",
        "state_dict = load_file(\"/mnt/notebook-flux1-schnell/flux1-schnell.safetensors\")\n",
        "model.load_state_dict(state_dict, assign=True)\n",
        "model.cuda()"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 34,
          "data": {
            "text/plain": "Flux(\n  (pe_embedder): EmbedND()\n  (img_in): Linear(in_features=64, out_features=3072, bias=True)\n  (time_in): MLPEmbedder(\n    (in_layer): Linear(in_features=256, out_features=3072, bias=True)\n    (silu): SiLU()\n    (out_layer): Linear(in_features=3072, out_features=3072, bias=True)\n  )\n  (vector_in): MLPEmbedder(\n    (in_layer): Linear(in_features=768, out_features=3072, bias=True)\n    (silu): SiLU()\n    (out_layer): Linear(in_features=3072, out_features=3072, bias=True)\n  )\n  (guidance_in): Identity()\n  (txt_in): Linear(in_features=4096, out_features=3072, bias=True)\n  (double_blocks): ModuleList(\n    (0-18): 19 x DoubleStreamBlock(\n      (img_mod): Modulation(\n        (lin): Linear(in_features=3072, out_features=18432, bias=True)\n      )\n      (img_norm1): LayerNorm((3072,), eps=1e-06, elementwise_affine=False)\n      (img_attn): SelfAttention(\n        (qkv): Linear(in_features=3072, out_features=9216, bias=True)\n        (norm): QKNorm(\n          (query_norm): RMSNorm()\n          (key_norm): RMSNorm()\n        )\n        (proj): Linear(in_features=3072, out_features=3072, bias=True)\n      )\n      (img_norm2): LayerNorm((3072,), eps=1e-06, elementwise_affine=False)\n      (img_mlp): Sequential(\n        (0): Linear(in_features=3072, out_features=12288, bias=True)\n        (1): GELU(approximate='tanh')\n        (2): Linear(in_features=12288, out_features=3072, bias=True)\n      )\n      (txt_mod): Modulation(\n        (lin): Linear(in_features=3072, out_features=18432, bias=True)\n      )\n      (txt_norm1): LayerNorm((3072,), eps=1e-06, elementwise_affine=False)\n      (txt_attn): SelfAttention(\n        (qkv): Linear(in_features=3072, out_features=9216, bias=True)\n        (norm): QKNorm(\n          (query_norm): RMSNorm()\n          (key_norm): RMSNorm()\n        )\n        (proj): Linear(in_features=3072, out_features=3072, bias=True)\n      )\n      (txt_norm2): LayerNorm((3072,), eps=1e-06, elementwise_affine=False)\n      (txt_mlp): Sequential(\n        (0): Linear(in_features=3072, out_features=12288, bias=True)\n        (1): GELU(approximate='tanh')\n        (2): Linear(in_features=12288, out_features=3072, bias=True)\n      )\n    )\n  )\n  (single_blocks): ModuleList(\n    (0-37): 38 x SingleStreamBlock(\n      (linear1): Linear(in_features=3072, out_features=21504, bias=True)\n      (linear2): Linear(in_features=15360, out_features=3072, bias=True)\n      (norm): QKNorm(\n        (query_norm): RMSNorm()\n        (key_norm): RMSNorm()\n      )\n      (pre_norm): LayerNorm((3072,), eps=1e-06, elementwise_affine=False)\n      (mlp_act): GELU(approximate='tanh')\n      (modulation): Modulation(\n        (lin): Linear(in_features=3072, out_features=9216, bias=True)\n      )\n    )\n  )\n  (final_layer): LastLayer(\n    (norm_final): LayerNorm((3072,), eps=1e-06, elementwise_affine=False)\n    (linear): Linear(in_features=3072, out_features=64, bias=True)\n    (adaLN_modulation): Sequential(\n      (0): SiLU()\n      (1): Linear(in_features=3072, out_features=6144, bias=True)\n    )\n  )\n)"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "model.img_in.weight.dtype"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 35,
          "data": {
            "text/plain": "torch.bfloat16"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## T5 and CLIP conditioning\n",
        "\n",
        "These are text embeddings directly from HuggingFace, let's take it."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "from torch import Tensor, nn\n",
        "from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer\n",
        "\n",
        "\n",
        "class HFEmbedder(nn.Module):\n",
        "    def __init__(self, version: str, max_length: int, **hf_kwargs):\n",
        "        super().__init__()\n",
        "        self.is_clip = version.startswith(\"openai\")\n",
        "        self.max_length = max_length\n",
        "        self.output_key = \"pooler_output\" if self.is_clip else \"last_hidden_state\"\n",
        "\n",
        "        if self.is_clip:\n",
        "            self.tokenizer: CLIPTokenizer = CLIPTokenizer.from_pretrained(version, max_length=max_length)\n",
        "            self.hf_module: CLIPTextModel = CLIPTextModel.from_pretrained(version, **hf_kwargs)\n",
        "        else:\n",
        "            self.tokenizer: T5Tokenizer = T5Tokenizer.from_pretrained(version, max_length=max_length)\n",
        "            self.hf_module: T5EncoderModel = T5EncoderModel.from_pretrained(version, **hf_kwargs)\n",
        "\n",
        "        self.hf_module = self.hf_module.eval().requires_grad_(False)\n",
        "\n",
        "    def forward(self, text: list[str]) -> Tensor:\n",
        "        batch_encoding = self.tokenizer(\n",
        "            text,\n",
        "            truncation=True,\n",
        "            max_length=self.max_length,\n",
        "            return_length=False,\n",
        "            return_overflowing_tokens=False,\n",
        "            padding=\"max_length\",\n",
        "            return_tensors=\"pt\",\n",
        "        )\n",
        "\n",
        "        outputs = self.hf_module(\n",
        "            input_ids=batch_encoding[\"input_ids\"].to(self.hf_module.device),\n",
        "            attention_mask=None,\n",
        "            output_hidden_states=False,\n",
        "        )\n",
        "        return outputs[self.output_key]"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Image embedders\n",
        "\n",
        "- DepthImageEncoder: depth-anything\n",
        "- CannyImageEncoder: OpenCV canny edge detection\n",
        "- ReduxImageEncoder: SigLIP (CLIP with sigmoids), from Google, used to refine images\n",
        "\n",
        "I don't think we need any of these for the base diffusion pipeline, so I'm going to omit this code for now.\n",
        "\n",
        "It's just more image models, anyway. Turtles all the way down."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Sampling\n",
        "\n",
        "Let's take the code that implements sampling now.\n",
        "\n",
        "We start from noise, then we apply one or more ODE+Diffusion steps, based on the\n",
        "particular sampler used. These also operate at a given timestep that is altered based\n",
        "on the model application."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "import math\n",
        "from typing import Callable\n",
        "\n",
        "import numpy as np\n",
        "import torch\n",
        "from einops import rearrange, repeat\n",
        "from PIL import Image\n",
        "from torch import Tensor\n",
        "\n",
        "\n",
        "def get_noise(\n",
        "    num_samples: int,\n",
        "    height: int,\n",
        "    width: int,\n",
        "    device: torch.device,\n",
        "    dtype: torch.dtype,\n",
        "    seed: int,\n",
        "):\n",
        "    return torch.randn(\n",
        "        num_samples,\n",
        "        16,\n",
        "        # allow for packing\n",
        "        2 * math.ceil(height / 16),\n",
        "        2 * math.ceil(width / 16),\n",
        "        device=device,\n",
        "        dtype=dtype,\n",
        "        generator=torch.Generator(device=device).manual_seed(seed),\n",
        "    )\n",
        "\n",
        "\n",
        "def prepare(t5: HFEmbedder, clip: HFEmbedder, img: Tensor, prompt: str | list[str]) -> dict[str, Tensor]:\n",
        "    bs, c, h, w = img.shape\n",
        "    if bs == 1 and not isinstance(prompt, str):\n",
        "        bs = len(prompt)\n",
        "\n",
        "    img = rearrange(img, \"b c (h ph) (w pw) -> b (h w) (c ph pw)\", ph=2, pw=2)\n",
        "    if img.shape[0] == 1 and bs > 1:\n",
        "        img = repeat(img, \"1 ... -> bs ...\", bs=bs)\n",
        "\n",
        "    img_ids = torch.zeros(h // 2, w // 2, 3)\n",
        "    img_ids[..., 1] = img_ids[..., 1] + torch.arange(h // 2)[:, None]\n",
        "    img_ids[..., 2] = img_ids[..., 2] + torch.arange(w // 2)[None, :]\n",
        "    img_ids = repeat(img_ids, \"h w c -> b (h w) c\", b=bs)\n",
        "\n",
        "    if isinstance(prompt, str):\n",
        "        prompt = [prompt]\n",
        "    txt = t5(prompt)\n",
        "    if txt.shape[0] == 1 and bs > 1:\n",
        "        txt = repeat(txt, \"1 ... -> bs ...\", bs=bs)\n",
        "    txt_ids = torch.zeros(bs, txt.shape[1], 3)\n",
        "\n",
        "    vec = clip(prompt)\n",
        "    if vec.shape[0] == 1 and bs > 1:\n",
        "        vec = repeat(vec, \"1 ... -> bs ...\", bs=bs)\n",
        "\n",
        "    return {\n",
        "        \"img\": img,\n",
        "        \"img_ids\": img_ids.to(img.device),\n",
        "        \"txt\": txt.to(img.device),\n",
        "        \"txt_ids\": txt_ids.to(img.device),\n",
        "        \"vec\": vec.to(img.device),\n",
        "    }"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "def load_t5(device: str | torch.device = \"cuda\", max_length: int = 512) -> HFEmbedder:\n",
        "    # max length 64, 128, 256 and 512 should work (if your sequence is short enough)\n",
        "    return HFEmbedder(\"google/t5-v1_1-xxl\", max_length=max_length, torch_dtype=torch.bfloat16).to(device)\n",
        "\n",
        "\n",
        "def load_clip(device: str | torch.device = \"cuda\") -> HFEmbedder:\n",
        "    return HFEmbedder(\"openai/clip-vit-large-patch14\", max_length=77, torch_dtype=torch.bfloat16).to(device)\n",
        "\n",
        "\n",
        "t5 = load_t5(\"cuda\", max_length=256)  # schnell is 256\n",
        "clip = load_clip(\"cuda\")"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "2f6a239fe62a4eedb790172bac775bc5",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "tokenizer_config.json:   0%|          | 0.00/1.86k [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "131cb03b906345b0ae00268581a073c3",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "spiece.model:   0%|          | 0.00/792k [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "c760c431b9024156ac1e469ddf016a8a",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "special_tokens_map.json:   0%|          | 0.00/1.79k [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f6e6d725610249ef8a61c04e3b98c9d8",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "config.json:   0%|          | 0.00/593 [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "e8578a4d66d147bb99707b54c4aa6113",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "pytorch_model.bin:   0%|          | 0.00/44.5G [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "fbdbc8fe8a8c4572ab8bedc950c8c1a6",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "model.safetensors:   0%|          | 0.00/44.5G [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "fcc4dce525b246bc8ddb84d233a0f686",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "tokenizer_config.json:   0%|          | 0.00/905 [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "5a4e3f9eaf2347d9a6cef8e191d26db2",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "vocab.json:   0%|          | 0.00/961k [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f9c3cabe9ad148fab6491c662e323f89",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "merges.txt:   0%|          | 0.00/525k [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "dfbb0a7545e34b31bc1ff8539afbb28a",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "special_tokens_map.json:   0%|          | 0.00/389 [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "99f4d36a57c7480e92c8289384223afc",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "tokenizer.json:   0%|          | 0.00/2.22M [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3bf44d70b02e4c3b9233356c99d57009",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "config.json:   0%|          | 0.00/4.52k [00:00<?, ?B/s]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f54a00139a174185bdab68ff1e4188e5",
              "version_minor": 0.0,
              "version_major": 2.0
            },
            "text/plain": "model.safetensors:   0%|          | 0.00/1.71G [00:00<?, ?B/s]"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Lol great, did not realize T5 would be another 44.5 GB of weights data. Fine.\n",
        "\n",
        "Is this going to fit on my H100 GPU? Hm\u2026 some GPU memory metrics would be real nice right now.\n",
        "\n",
        "_Ok it seems fine!_ Just took like 4 minutes lol. Only 48s after first download though."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "!nvidia-smi"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sun Jun 22 16:33:48 2025       \r\n",
            "+-----------------------------------------------------------------------------------------+\r\n",
            "| NVIDIA-SMI 570.86.15              Driver Version: 570.86.15      CUDA Version: 12.8     |\r\n",
            "|-----------------------------------------+------------------------+----------------------+\r\n",
            "| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |\r\n",
            "| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |\r\n",
            "|                                         |                        |               MIG M. |\r\n",
            "|=========================================+========================+======================|\r\n",
            "|   0  NVIDIA H100 80GB HBM3          On  |   00000000:4C:00.0 Off |                  Off |\r\n",
            "| N/A   29C    P0            116W /  700W |   32992MiB /  81559MiB |      1%      Default |\r\n",
            "|                                         |                        |             Disabled |\r\n",
            "+-----------------------------------------+------------------------+----------------------+\r\n",
            "                                                                                         \r\n",
            "+-----------------------------------------------------------------------------------------+\r\n",
            "| Processes:                                                                              |\r\n",
            "|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |\r\n",
            "|        ID   ID                                                               Usage      |\r\n",
            "|=========================================================================================|\r\n",
            "+-----------------------------------------------------------------------------------------+\r\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "seed = 42\n",
        "\n",
        "x = get_noise(\n",
        "    1,\n",
        "    256,\n",
        "    256,\n",
        "    device=\"cuda\",\n",
        "    dtype=torch.bfloat16,\n",
        "    seed=seed,\n",
        ")"
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "inp = prepare(t5, clip, x, prompt=\"an apple being eaten by a brown bear at the north pole\")"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "{k: (v.dtype, v.shape) for k, v in inp.items()}"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 42,
          "data": {
            "text/plain": "{'img': (torch.bfloat16, torch.Size([1, 256, 64])),\n 'img_ids': (torch.float32, torch.Size([1, 256, 3])),\n 'txt': (torch.bfloat16, torch.Size([1, 256, 4096])),\n 'txt_ids': (torch.float32, torch.Size([1, 256, 3])),\n 'vec': (torch.bfloat16, torch.Size([1, 768]))}"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "def get_schedule(\n",
        "    num_steps: int,\n",
        "    image_seq_len: int,\n",
        "    base_shift: float = 0.5,\n",
        "    max_shift: float = 1.15,\n",
        "    shift: bool = True,\n",
        ") -> list[float]:\n",
        "    # extra step for zero\n",
        "    timesteps = torch.linspace(1, 0, num_steps + 1)\n",
        "\n",
        "    # shifting the schedule to favor high timesteps for higher signal images\n",
        "    if shift:\n",
        "        # estimate mu based on linear estimation between two points\n",
        "        mu = get_lin_function(y1=base_shift, y2=max_shift)(image_seq_len)\n",
        "        timesteps = time_shift(mu, 1.0, timesteps)\n",
        "\n",
        "    return timesteps.tolist()\n",
        "\n",
        "\n",
        "name = \"flux-schnell\"\n",
        "num_steps = 4\n",
        "timesteps = get_schedule(num_steps, inp[\"img\"].shape[1], shift=(name != \"flux-schnell\"))"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "timesteps"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 44,
          "data": {
            "text/plain": "[1.0, 0.75, 0.5, 0.25, 0.0]"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "!nvidia-smi"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sun Jun 22 16:34:05 2025       \r\n",
            "+-----------------------------------------------------------------------------------------+\r\n",
            "| NVIDIA-SMI 570.86.15              Driver Version: 570.86.15      CUDA Version: 12.8     |\r\n",
            "|-----------------------------------------+------------------------+----------------------+\r\n",
            "| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |\r\n",
            "| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |\r\n",
            "|                                         |                        |               MIG M. |\r\n",
            "|=========================================+========================+======================|\r\n",
            "|   0  NVIDIA H100 80GB HBM3          On  |   00000000:4C:00.0 Off |                  Off |\r\n",
            "| N/A   29C    P0            117W /  700W |   33166MiB /  81559MiB |      0%      Default |\r\n",
            "|                                         |                        |             Disabled |\r\n",
            "+-----------------------------------------+------------------------+----------------------+\r\n",
            "                                                                                         \r\n",
            "+-----------------------------------------------------------------------------------------+\r\n",
            "| Processes:                                                                              |\r\n",
            "|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |\r\n",
            "|        ID   ID                                                               Usage      |\r\n",
            "|=========================================================================================|\r\n",
            "+-----------------------------------------------------------------------------------------+\r\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "def denoise(\n",
        "    model: Flux,\n",
        "    # model input\n",
        "    img: Tensor,\n",
        "    img_ids: Tensor,\n",
        "    txt: Tensor,\n",
        "    txt_ids: Tensor,\n",
        "    vec: Tensor,\n",
        "    # sampling parameters\n",
        "    timesteps: list[float],\n",
        "    guidance: float = 4.0,\n",
        "    # extra img tokens\n",
        "    img_cond: Tensor | None = None,\n",
        "):\n",
        "    # this is ignored for schnell\n",
        "    guidance_vec = torch.full((img.shape[0],), guidance, device=img.device, dtype=img.dtype)\n",
        "    for t_curr, t_prev in zip(timesteps[:-1], timesteps[1:]):\n",
        "        t_vec = torch.full((img.shape[0],), t_curr, dtype=img.dtype, device=img.device)\n",
        "        pred = model(\n",
        "            img=torch.cat((img, img_cond), dim=-1) if img_cond is not None else img,\n",
        "            img_ids=img_ids,\n",
        "            txt=txt,\n",
        "            txt_ids=txt_ids,\n",
        "            y=vec,\n",
        "            timesteps=t_vec,\n",
        "            guidance=guidance_vec,\n",
        "        )\n",
        "\n",
        "        img = img + (t_prev - t_curr) * pred\n",
        "\n",
        "    return img\n",
        "\n",
        "with torch.no_grad():\n",
        "    x = denoise(model, **inp, timesteps=timesteps)"
      ],
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "x.shape"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 47,
          "data": {
            "text/plain": "torch.Size([1, 256, 64])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "def unpack(x: Tensor, height: int, width: int) -> Tensor:\n",
        "    return rearrange(\n",
        "        x,\n",
        "        \"b (h w) (c ph pw) -> b c (h ph) (w pw)\",\n",
        "        h=math.ceil(height / 16),\n",
        "        w=math.ceil(width / 16),\n",
        "        ph=2,\n",
        "        pw=2,\n",
        "    )\n",
        "\n",
        "with torch.no_grad():\n",
        "    x = unpack(x, 256, 256)\n",
        "x.shape"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 48,
          "data": {
            "text/plain": "torch.Size([1, 16, 32, 32])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": false
      },
      "source": [
        "# plot output latents\n",
        "plot_latents(x)"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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