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Remove f16 decompression lib from SD compile.py (#8121)

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* Remove f16-to-f32-gpu lib, use tinygrad exported decompression

* No need to create new instance
This commit is contained in:
Ahmed Harmouche
2024-12-09 14:09:00 +01:00
committed by GitHub
parent 22d99f1421
commit c6277fce09
2 changed files with 11 additions and 9 deletions
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8
examples/webgpu/stable_diffusion/compile.py
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@@ -1,9 +1,10 @@
import os
from extra.export_model import compile_net, jit_model, dtype_to_js_type
from extra.f16_decompress import u32_to_f16
from examples.stable_diffusion import StableDiffusion
from tinygrad.nn.state import get_state_dict, safe_save, safe_load_metadata, torch_load, load_state_dict
from tinygrad.tensor import Tensor
from tinygrad import Device
from tinygrad import Device, dtypes
from tinygrad.helpers import fetch
from typing import NamedTuple, Any, List
import requests
@@ -95,7 +96,8 @@ if __name__ == "__main__":
sub_steps = [
Step(name = "textModel", input = [Tensor.randn(1, 77)], forward = model.cond_stage_model.transformer.text_model),
Step(name = "diffusor", input = [Tensor.randn(1, 77, 768), Tensor.randn(1, 77, 768), Tensor.randn(1,4,64,64), Tensor.rand(1), Tensor.randn(1), Tensor.randn(1), Tensor.randn(1)], forward = model),
Step(name = "decoder", input = [Tensor.randn(1,4,64,64)], forward = model.decode)
Step(name = "decoder", input = [Tensor.randn(1,4,64,64)], forward = model.decode),
Step(name = "f16tof32", input = [Tensor.randn(2097120, dtype=dtypes.uint32)], forward = u32_to_f16)
]
prg = ""
@@ -130,7 +132,7 @@ if __name__ == "__main__":
return {{
"setup": async (device, safetensor) => {{
const metadata = getTensorMetadata(safetensor[0]);
const metadata = safetensor ? getTensorMetadata(safetensor[0]) : null;
{exported_bufs}

12
examples/webgpu/stable_diffusion/index.html
View File

@@ -165,10 +165,6 @@
import ClipTokenizer from './clip_tokenizer.js';
window.clipTokenizer = new ClipTokenizer();
</script>
<script type="module">
import { f16tof32GPU } from 'https://unpkg.com/f16-to-f32-gpu@0.1.0/src/index.js';
window.f16tof32GPU = f16tof32GPU;
</script>
<script src="./net.js"></script>
</head>
<body>
@@ -214,6 +210,8 @@
<canvas id="canvas" width="512" height="512"></canvas>
<script>
let f16decomp = null;
function initDb() {
return new Promise((resolve, reject) => {
let db;
@@ -416,7 +414,7 @@
const metadata = JSON.parse(new TextDecoder("utf8").decode(combinedBuffer.subarray(8, 8 + metadataLength)));
const allToDecomp = combinedBuffer.byteLength - (8 + metadataLength);
const decodeChunkSize = 67107840;
const decodeChunkSize = 8388480;
const numChunks = Math.ceil(allToDecomp/decodeChunkSize);
console.log(allToDecomp + " bytes to decompress");
@@ -440,7 +438,8 @@
let chunkStartF16 = 8 + metadataLength + (decodeChunkSize * i);
let chunkEndF16 = chunkStartF16 + decodeChunkSize;
let chunk = combinedBuffer.subarray(chunkStartF16, chunkEndF16);
let result = await f16tof32GPU(chunk);
let uint32Chunk = new Uint32Array(chunk.buffer, chunk.byteOffset, chunk.byteLength / 4);
let result = await f16decomp(uint32Chunk);
let resultUint8 = new Uint8Array(result.buffer);
let chunkStartF32 = 8 + metadataLength + (decodeChunkSize * i * 2);
let chunkEndF32 = chunkStartF32 + resultUint8.byteLength;
@@ -483,6 +482,7 @@
}
const device = await getDevice();
f16decomp = await f16tof32().setup(device, safetensorParts),
safetensorParts = await getAndDecompressF16Safetensors(device, progress);
modelDlTitle.innerHTML = "Compiling model"