Skip to content

Instantly share code, notes, and snippets.

Show Gist options
  • Save josephrocca/02036280e19a3cbb1555fb7569f0257e to your computer and use it in GitHub Desktop.
Save josephrocca/02036280e19a3cbb1555fb7569f0257e to your computer and use it in GitHub Desktop.
Minimal dalle-mini inference and tflite/onnx/tfjs conversion
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/josephrocca/02036280e19a3cbb1555fb7569f0257e/minimal-dalle-mini-inference-and-tflite-onnx-tfjs-conversion.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"source": [
"# This notebook is based on work done by @kuprel: https://github.com/kuprel/min-dalle"
],
"metadata": {
"id": "snN3kT1PWRp3"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"!pip install jax[cpu]==0.3.14 # since, as of writing, Colab currently uses JAX v0.3.8 and that has a bug in jax2tf"
],
"metadata": {
"id": "th9znbh3dBKN"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "ix_xt4X1_6F4",
"cellView": "code"
},
"outputs": [],
"source": [
"!git clone --depth 1 --branch 0.1.1 https://github.com/kuprel/min-dalle\n",
"!mkdir -p /content/min-dalle/pretrained/vqgan/\n",
"!curl https://huggingface.co/dalle-mini/vqgan_imagenet_f16_16384/resolve/main/flax_model.msgpack -L --output /content/min-dalle/pretrained/vqgan/flax_model.msgpack\n",
"!pip install torch flax==0.4.2 wandb\n",
"!wandb login --anonymously\n",
"!wandb artifact get --root=/content/min-dalle/pretrained/dalle_bart_mini dalle-mini/dalle-mini/mini-1:v0\n"
]
},
{
"cell_type": "code",
"source": [
"%cd /content/min-dalle/min_dalle"
],
"metadata": {
"id": "EuEPj3zBIkkm"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from flax import traverse_util, serialization\n",
"from typing import Dict, Tuple, List\n",
"import jax\n",
"from jax import numpy as jnp\n",
"import numpy\n",
"import os\n",
"import json\n",
"from PIL import Image\n",
"import torch"
],
"metadata": {
"id": "ry9H5pKSQUy9"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"def load_dalle_bart_flax_params(path: str) -> Dict[str, numpy.ndarray]:\n",
" with open(os.path.join(path, \"flax_model.msgpack\"), \"rb\") as f:\n",
" params = serialization.msgpack_restore(f.read())\n",
"\n",
" for codec in ['encoder', 'decoder']:\n",
" k = 'FlaxBart{}Layers'.format(codec.title())\n",
" P: dict = params['model'][codec]['layers'][k]\n",
" P['pre_self_attn_layer_norm'] = P.pop('LayerNorm_0')\n",
" P['self_attn_layer_norm'] = P.pop('LayerNorm_1')\n",
" P['self_attn'] = P.pop('FlaxBartAttention_0')\n",
" if codec == 'decoder':\n",
" P['pre_encoder_attn_layer_norm'] = P.pop('LayerNorm_2')\n",
" P['encoder_attn_layer_norm'] = P.pop('LayerNorm_3')\n",
" P['encoder_attn'] = P.pop('FlaxBartAttention_1')\n",
" P['glu']: dict = P.pop('GLU_0')\n",
" P['glu']['ln0'] = P['glu'].pop('LayerNorm_0')\n",
" P['glu']['ln1'] = P['glu'].pop('LayerNorm_1')\n",
" P['glu']['fc0'] = P['glu'].pop('Dense_0')\n",
" P['glu']['fc1'] = P['glu'].pop('Dense_1')\n",
" P['glu']['fc2'] = P['glu'].pop('Dense_2')\n",
"\n",
" for codec in ['encoder', 'decoder']:\n",
" layers_params = params['model'][codec].pop('layers')\n",
" params['model'][codec] = {\n",
" **params['model'][codec], \n",
" **layers_params\n",
" }\n",
" \n",
" model_params = params.pop('model')\n",
" params = {**params, **model_params}\n",
"\n",
" params['decoder']['lm_head'] = params.pop('lm_head')\n",
"\n",
" return params"
],
"metadata": {
"id": "0rFl-rxiNpvn"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from typing import Tuple, List\n",
"def load_dalle_bart_metadata(path: str) -> Tuple[dict, dict, List[str]]:\n",
" print(\"parsing metadata from {}\".format(path))\n",
" for f in ['config.json', 'flax_model.msgpack', 'vocab.json', 'merges.txt']:\n",
" assert(os.path.exists(os.path.join(path, f)))\n",
" with open(path + '/config.json', 'r') as f: \n",
" config = json.load(f)\n",
" with open(path + '/vocab.json') as f:\n",
" vocab = json.load(f)\n",
" with open(path + '/merges.txt') as f:\n",
" merges = f.read().split(\"\\n\")[1:-1]\n",
" return config, vocab, merges\n",
"\n",
"model_name = 'mini' # or 'mega'\n",
"model_path = '../pretrained/dalle_bart_{}'.format(model_name)\n",
"config, vocab, merges = load_dalle_bart_metadata(model_path)\n",
"params_dalle_bart = load_dalle_bart_flax_params(model_path)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "qSR7lFawNk-o",
"outputId": "7bf77b37-8535-4586-a210-ac87e7b2ec63"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"parsing metadata from ../pretrained/dalle_bart_mini\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!pip install tokenizers"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Asn9rrNtg8IG",
"outputId": "86305582-11a5-4271-f7c1-d67894727784"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
"Requirement already satisfied: tokenizers in /usr/local/lib/python3.7/dist-packages (0.12.1)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"from models.dalle_bart_encoder_flax import DalleBartEncoderFlax\n",
"from models.dalle_bart_decoder_flax import DalleBartDecoderFlax\n",
"\n",
"dalle_bart_encoder_flax_model = DalleBartEncoderFlax(\n",
" attention_head_count = config['encoder_attention_heads'],\n",
" embed_count = config['d_model'],\n",
" glu_embed_count = config['encoder_ffn_dim'],\n",
" text_token_count = config['max_text_length'],\n",
" text_vocab_count = config['encoder_vocab_size'],\n",
" layer_count = config['encoder_layers']\n",
").bind({'params': params_dalle_bart.pop('encoder')})\n",
"\n",
"dalle_bart_decoder_flax_model = DalleBartDecoderFlax(\n",
" image_token_count = config['image_length'],\n",
" text_token_count = config['max_text_length'],\n",
" image_vocab_count = config['image_vocab_size'],\n",
" attention_head_count = config['decoder_attention_heads'],\n",
" embed_count = config['d_model'],\n",
" glu_embed_count = config['decoder_ffn_dim'],\n",
" layer_count = config['decoder_layers'],\n",
" start_token = config['decoder_start_token_id']\n",
")"
],
"metadata": {
"id": "V0LCW-ViDiSg"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"def load_vqgan_torch_params(path: str) -> Dict[str, torch.Tensor]:\n",
" with open(os.path.join(path, 'flax_model.msgpack'), \"rb\") as f:\n",
" params: Dict[str, numpy.ndarray] = serialization.msgpack_restore(f.read())\n",
"\n",
" P: Dict[str, numpy.ndarray] = traverse_util.flatten_dict(params, sep='.')\n",
"\n",
" for i in list(P.keys()):\n",
" j = i\n",
" if 'up' in i or 'down' in i:\n",
" j = i.replace('_', '.')\n",
" j = j.replace('proj.out', 'proj_out')\n",
" j = j.replace('nin.short', 'nin_short')\n",
" if 'bias' in i:\n",
" P[j] = P.pop(i)\n",
" elif 'scale' in i:\n",
" j = j.replace('scale', 'weight')\n",
" P[j] = P.pop(i)\n",
" elif 'kernel' in i:\n",
" j = j.replace('kernel', 'weight')\n",
" P[j] = P.pop(i).transpose(3, 2, 0, 1)\n",
"\n",
" for i in P:\n",
" P[i] = torch.tensor(P[i])\n",
"\n",
" P['embedding.weight'] = P.pop('quantize.embedding.embedding')\n",
"\n",
" for i in list(P):\n",
" if i.split('.')[0] in ['encoder', 'quant_conv']:\n",
" P.pop(i)\n",
" \n",
" return P"
],
"metadata": {
"id": "vMpgNCGOK-N4"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from torch import LongTensor, FloatTensor\n",
"from models.vqgan_detokenizer import VQGanDetokenizer\n",
"\n",
"def detokenize_torch(image_tokens: LongTensor, is_torch: bool) -> numpy.ndarray:\n",
" print(\"detokenizing image\")\n",
" model_path = '../pretrained/vqgan'\n",
" params = load_vqgan_torch_params(model_path)\n",
" detokenizer = VQGanDetokenizer()\n",
" detokenizer.load_state_dict(params)\n",
" if torch.cuda.is_available() and is_torch: detokenizer = detokenizer.cuda()\n",
" image = detokenizer.forward(image_tokens).to(torch.uint8)\n",
" del detokenizer, params\n",
" return image.to('cpu').detach().numpy()"
],
"metadata": {
"id": "pHrSOkC8KqwU"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from math import inf\n",
"from typing import List, Tuple\n",
"\n",
"\n",
"class TextTokenizer:\n",
" def __init__(self, vocab: dict, merges: List[str]):\n",
" self.token_from_subword = vocab\n",
" pairs = [tuple(pair.split()) for pair in merges]\n",
" self.rank_from_pair = dict(zip(pairs, range(len(pairs))))\n",
"\n",
" def __call__(self, text: str) -> List[int]:\n",
" sep_token = self.token_from_subword['</s>']\n",
" cls_token = self.token_from_subword['<s>']\n",
" unk_token = self.token_from_subword['<unk>']\n",
" text = text.lower().encode(\"ascii\", errors=\"ignore\").decode()\n",
" tokens = [\n",
" self.token_from_subword.get(subword, unk_token)\n",
" for word in text.split(\" \") if len(word) > 0\n",
" for subword in self.get_byte_pair_encoding(word)\n",
" ]\n",
" return [cls_token] + tokens + [sep_token]\n",
"\n",
" def get_byte_pair_encoding(self, word: str) -> List[str]:\n",
" def get_pair_rank(pair: Tuple[str, str]) -> int:\n",
" return self.rank_from_pair.get(pair, inf)\n",
"\n",
" subwords = [chr(ord(\" \") + 256)] + list(word)\n",
" while len(subwords) > 1:\n",
" pairs = list(zip(subwords[:-1], subwords[1:]))\n",
" pair_to_merge = min(pairs, key=get_pair_rank)\n",
" if pair_to_merge not in self.rank_from_pair: break\n",
" i = pairs.index(pair_to_merge)\n",
" subwords = (\n",
" (subwords[:i] if i > 0 else []) + \n",
" [subwords[i] + subwords[i + 1]] + \n",
" (subwords[i + 2:] if i + 2 < len(subwords) else [])\n",
" )\n",
"\n",
" # print(subwords)\n",
" return subwords"
],
"metadata": {
"id": "KAUjwzWYuKru"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"def tokenize_text(\n",
" text: str, \n",
" config: dict,\n",
" vocab: dict,\n",
" merges: List[str]\n",
") -> numpy.ndarray:\n",
" tokens = TextTokenizer(vocab, merges)(text)\n",
" text_tokens = numpy.ones((2, config['max_text_length']), dtype=numpy.int32)\n",
" text_tokens[0, :len(tokens)] = tokens\n",
" text_tokens[1, :2] = [tokens[0], tokens[-1]]\n",
" return text_tokens"
],
"metadata": {
"id": "28vowjQ1B0aw"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"def generate_image(text_tokens, seed):\n",
" encoder_state = dalle_bart_encoder_flax_model(text_tokens)\n",
" image_tokens = dalle_bart_decoder_flax_model.sample_image_tokens(\n",
" text_tokens,\n",
" encoder_state,\n",
" jax.random.PRNGKey(seed[0]),\n",
" params_dalle_bart['decoder'],\n",
" )\n",
" return image_tokens"
],
"metadata": {
"id": "xFGb3Gs1Th1N"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"generate_image_jitted = jax.jit(generate_image)"
],
"metadata": {
"id": "hxLZepOUT-qi"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# text: \"game concept art with a lush green village surrounded by a dry orange canyon with a hill in the background and a blue sky, digital art\"\n",
"# text tokens: [[0,880,3319,241,208,58,21843,899,2595,30419,185,58,3441,2566,7308,208,58,2349,91,99,1396,128,58,789,1955,11,1189,241,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1],[0,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]]\n",
"# Image output for seed=2: https://i.imgur.com/9fBoJg8.png\n",
"\n",
"text = \"game concept art with a lush green village surrounded by a dry orange canyon with a hill in the background and a blue sky, digital art\"\n",
"seed = jnp.array([2])\n",
"\n",
"text_tokens = tokenize_text(text, config, vocab, merges)\n",
"print(\"text tokens shape:\", text_tokens.shape)\n",
"\n",
"image_tokens = generate_image_jitted(text_tokens, seed)\n",
"\n",
"image_tokens_numpy = numpy.array(image_tokens)\n",
"# print(\"image tokens\", list(image_tokens))\n",
"\n",
"image = detokenize_torch(torch.tensor(image_tokens_numpy), is_torch=False)\n",
"display(Image.fromarray(image))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 327
},
"id": "CEUUtqNNF7L5",
"outputId": "b1f3500a-9b01-4145-c41c-60fc76f777ab"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"text tokens shape: (2, 64)\n",
"detokenizing image\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<PIL.Image.Image image mode=RGB size=256x256 at 0x7F6CC8F9F5D0>"
],
"image/png": "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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"# Below is JAX-to-tflite/onnx/tfjs conversion process"
],
"metadata": {
"id": "h5GG1Qw1SqDT"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from jax.experimental import jax2tf\n",
"import tensorflow as tf"
],
"metadata": {
"id": "kVF1_1Gqnwwi"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"my_model = tf.Module()\n",
"generate_image_jitted_tf = jax2tf.convert(generate_image_jitted, enable_xla=False)\n",
"my_model.f = tf.function(generate_image_jitted_tf, autograph=False, input_signature=[\n",
" tf.TensorSpec(shape=[2, 64], dtype=tf.int32, name=\"text_tokens\"),\n",
" tf.TensorSpec(shape=[1], dtype=tf.int32, name=\"seed\"),\n",
"])\n",
"tf.saved_model.save(my_model, '/content/dalle-mini-tfsavedmodel', options=tf.saved_model.SaveOptions(experimental_custom_gradients=False))\n",
"# restored_model = tf.saved_model.load('/content/dalle-mini-tfsavedmodel')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "-74vChXbStPY",
"outputId": "08494556-9bb3-4d57-a7c4-9e68d4de3936"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"WARNING:tensorflow:@custom_gradient grad_fn has 'variables' in signature, but no ResourceVariables were used on the forward pass.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!pip install git+https://github.com/onnx/tensorflow-onnx"
],
"metadata": {
"id": "8D8xeUAZpabs"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# Unsupported ops: BitwiseXor, BitwiseOr, Bitcast, BitwiseAnd - https://github.com/onnx/tensorflow-onnx/issues/1985\n",
"# Also, if you see ^C at the end of the logs, then that's because it's running out of RAM and being terminated.\n",
"\n",
"!python -m tf2onnx.convert --saved-model \"/content/dalle-mini-tfsavedmodel\" --output \"/content/dalle-mini.onnx\" --opset 16"
],
"metadata": {
"id": "UsZndOC0pZI9"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# This doesn't work due to a bug - resulting model is zero bytes: https://github.com/tensorflow/tensorflow/issues/56629\n",
"\n",
"# converter = tf.lite.TFLiteConverter.from_saved_model(\"/content/dalle-mini-tfsavedmodel\")\n",
"# converter.target_spec.supported_ops = [\n",
"# tf.lite.OpsSet.TFLITE_BUILTINS, # enable TensorFlow Lite ops.\n",
"# tf.lite.OpsSet.SELECT_TF_OPS # enable TensorFlow ops.\n",
"# ]\n",
"# tflite_model = converter.convert()\n",
"# with open('/content/dalle-mini.tflite', 'wb') as f:\n",
"# f.write(tflite_model)"
],
"metadata": {
"id": "cD4UtFEXe_4h"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# This doesn't work due to: \"ValueError: Unsupported Ops in the model before optimization: LeftShift, Bitcast, BitwiseOr, BitwiseXor, RightShift, BitwiseAnd\" - https://github.com/tensorflow/tfjs/issues/6599\n",
"\n",
"# !pip install tensorflowjs \n",
"# !tensorflowjs_converter --input_format=tf_saved_model --output_format=tfjs_graph_model /content/dalle-mini-tfsavedmodel /content/dalle-mini-tfjs"
],
"metadata": {
"id": "kRxPaG6zmBfX"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# This approach doesn't work due to a weird bug \"Jax transforms and Flax models cannot be mixed\": https://github.com/tensorflow/tensorflow/issues/56660\n",
"\n",
"# converter = tf.lite.TFLiteConverter.experimental_from_jax([generate_image_jitted], [[\n",
"# ('text_tokens', jnp.zeros((2, 64))),\n",
"# ('seed', jnp.zeros((1,))),\n",
"# ]])\n",
"# tflite_model = converter.convert()\n",
"# with open('/content/dalle-mini.tflite', 'wb') as f:\n",
"# f.write(tflite_model)"
],
"metadata": {
"id": "yfH6UYUTtcQh"
},
"execution_count": null,
"outputs": []
}
],
"metadata": {
"colab": {
"collapsed_sections": [],
"name": "Minimal dalle-mini inference and tflite/onnx/tfjs conversion",
"provenance": [],
"machine_shape": "hm",
"include_colab_link": true
},
"gpuClass": "standard",
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment