From bf2b128fd71c607ddd7111614b98c60182eca43d Mon Sep 17 00:00:00 2001 From: nawnie <106923464+nawnie@users.noreply.github.com> Date: Sat, 18 Feb 2023 23:54:27 -0600 Subject: [PATCH] Created using Colaboratory --- Train_Colab.ipynb | 23 ++++++++++++++--------- 1 file changed, 14 insertions(+), 9 deletions(-) diff --git a/Train_Colab.ipynb b/Train_Colab.ipynb index c5f4a30..f3d0203 100644 --- a/Train_Colab.ipynb +++ b/Train_Colab.ipynb @@ -68,7 +68,7 @@ "outputs": [], "source": [ "#@title Optional connect Gdrive\n", - "#@markdown # but strongly recommended\n", + "#@markdown # But strongly recommended\n", "#@markdown This will let you put all your training data and checkpoints directly on your drive. Much faster/easier to continue later, less setup time.\n", "\n", "#@markdown Creates /content/drive/MyDrive/everydreamlogs/ckpt\n", @@ -82,8 +82,8 @@ "cell_type": "code", "execution_count": null, "metadata": { - "cellView": "form", - "id": "hAuBbtSvGpau" + "id": "hAuBbtSvGpau", + "cellView": "form" }, "outputs": [], "source": [ @@ -94,7 +94,7 @@ "s = getoutput('nvidia-smi')\n", "!pip install -q torch==1.13.1+cu117 torchvision==0.14.1+cu117 --extra-index-url \"https://download.pytorch.org/whl/cu117\"\n", "!pip install -q transformers==4.25.1\n", - "!pip install -q diffusers[torch]==0.10.2\n", + "!pip install -q diffusers[torch]==0.13.0\n", "!pip install -q pynvml==11.4.1\n", "!pip install -q bitsandbytes==0.35.0\n", "!pip install -q ftfy==6.1.1\n", @@ -290,7 +290,7 @@ "\n", "#@markdown * Batch size impacts VRAM use. 8 should work on SD1.x models and 5 for SD2.x models at 512 resolution. Lower this if you get CUDA out of memory errors. You can check resources on your instance and watch the GPU RAM.\n", "\n", - "Batch_Size = 6 #@param{type: 'number'}\n", + "Batch_Size = 8 #@param{type: 'number'}\n", "\n", "#@markdown * Gradient accumulation is sort of like a virtual batch size increase use this to increase batch size with out increasing vram usage\n", "#@markdown Increasing from 1 to 2 will have a minor impact on vram use, but more beyond that will not.\n", @@ -306,7 +306,7 @@ "\n", "#@markdown * Max Epochs to train for, this defines how many total times all your training data is used. Default of 100 is a good start if you are training ~30-40 images of one subject. If you have 100 images, you can reduce this to 40-50 and so forth.\n", "\n", - "Max_Epochs = 100 #@param {type:\"slider\", min:0, max:200, step:5}\n", + "Max_Epochs = 200 #@param {type:\"slider\", min:0, max:200, step:5}\n", "\n", "#@markdown * How often to save checkpoints.\n", "Save_every_N_epoch = 20 #@param{type:\"integer\"}\n", @@ -329,7 +329,12 @@ "#@markdown * Using the same seed each time you train allows for more accurate a/b comparison of models, leave at -1 for random\n", "#@markdown * The seed also effects your training samples, if you want the same seed each sample you will need to change it from -1\n", "Training_Seed = -1 #@param{type:\"integer\"}\n", - "\n", + "#@markdown * use this option to configure a sample_prompts.json\n", + "#@markdown * check out /content/EveryDream2trainer/doc/logging.md. for more details\n", + "Advance_Samples = False #@param{type:\"boolean\"}\n", + "Sample_File = \"sample_prompts.txt\"\n", + "if Advance_Samples:\n", + " Sample_File = \"sample_prompts.json\"\n", "#@markdown * Checkpointing Saves Vram to allow larger batch sizes minor slow down on a single batch size but will can allow room for a higher traning resolution (suggested on Colab Free tier, turn off for A100)\n", "Gradient_checkpointing = True #@param{type:\"boolean\"}\n", "Disable_Xformers = False #@param{type:\"boolean\"}\n", @@ -405,7 +410,7 @@ " --max_epochs $Max_Epochs \\\n", " --project_name \"$Project_Name\" \\\n", " --resolution $Resolution \\\n", - " --sample_prompts \"sample_prompts.txt\" \\\n", + " --sample_prompts \"$Sample_File\" \\\n", " --sample_steps $Steps_between_samples \\\n", " --save_every_n_epoch $Save_every_N_epoch \\\n", " --seed $Training_Seed \\\n", @@ -501,4 +506,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} +} \ No newline at end of file