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- .gitattributes +211 -0
- .gitignore +1 -0
- .idea/.gitignore +8 -0
- .idea/flux-fast-main.iml +12 -0
- .idea/inspectionProfiles/Project_Default.xml +18 -0
- .idea/inspectionProfiles/profiles_settings.xml +6 -0
- .idea/misc.xml +7 -0
- .idea/modules.xml +8 -0
- .idea/workspace.xml +58 -0
- README.md +595 -0
- aoti_export.log +954 -0
- creative_marathon.sh +112 -0
- creative_prompts.txt +77 -0
- diverse_prompts.txt +142 -0
- experiments.sh +79 -0
- gen_image.py +60 -0
- gen_image_hq.py +107 -0
- gen_image_stable.py +91 -0
- gen_image_ultra.py +146 -0
- gen_run.sh +40 -0
- gen_run_optimized.sh +134 -0
- high_quality_test.sh +88 -0
- install_requirements.sh +64 -0
- marathon.log +2 -0
- marathon_20250706_123209/mega_001_fantasy_123209.png +3 -0
- marathon_20250706_123209/mega_002_fantasy_123227.png +3 -0
- marathon_20250706_123209/mega_003_fantasy_123247.png +3 -0
- marathon_20250706_123209/mega_004_fantasy_123305.png +3 -0
- marathon_20250706_123209/mega_005_fantasy_123324.png +3 -0
- marathon_20250706_123209/mega_006_fantasy_123342.png +3 -0
- marathon_20250706_123209/mega_007_fantasy_123401.png +3 -0
- marathon_20250706_123209/mega_008_fantasy_123419.png +3 -0
- marathon_20250706_123209/mega_009_fantasy_123437.png +3 -0
- marathon_20250706_123209/mega_010_fantasy_123451.png +3 -0
- marathon_20250706_123209/mega_011_fantasy_123507.png +3 -0
- marathon_20250706_123209/mega_012_fantasy_123521.png +3 -0
- marathon_20250706_123209/mega_013_fantasy_123537.png +3 -0
- marathon_20250706_123209/mega_014_fantasy_123553.png +3 -0
- marathon_20250706_123209/mega_015_fantasy_123607.png +3 -0
- marathon_20250706_123209/mega_016_fantasy_123622.png +3 -0
- marathon_20250706_123209/mega_017_fantasy_123637.png +3 -0
- marathon_20250706_123209/mega_018_fantasy_123651.png +3 -0
- marathon_20250706_123209/mega_019_fantasy_123706.png +3 -0
- marathon_20250706_123209/mega_020_fantasy_123720.png +3 -0
- marathon_20250706_123209/mega_021_scifi_123734.png +3 -0
- marathon_20250706_123209/mega_022_scifi_123747.png +3 -0
- marathon_20250706_123209/mega_023_scifi_123801.png +3 -0
- marathon_20250706_123209/mega_024_scifi_123815.png +3 -0
- marathon_20250706_123209/mega_025_scifi_123829.png +3 -0
- marathon_20250706_123209/mega_026_scifi_123843.png +3 -0
.gitattributes
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.gitignore
ADDED
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*.pyc
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ADDED
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# Default ignored files
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/shelf/
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/workspace.xml
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+
# Editor-based HTTP Client requests
|
| 5 |
+
/httpRequests/
|
| 6 |
+
# Datasource local storage ignored files
|
| 7 |
+
/dataSources/
|
| 8 |
+
/dataSources.local.xml
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.idea/flux-fast-main.iml
ADDED
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+
<?xml version="1.0" encoding="UTF-8"?>
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<module type="PYTHON_MODULE" version="4">
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| 3 |
+
<component name="NewModuleRootManager">
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| 4 |
+
<content url="file://$MODULE_DIR$" />
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| 5 |
+
<orderEntry type="jdk" jdkName="Python 3.10 virtualenv at ~/.pyenv/versions/3.10.13/envs/venv-py310" jdkType="Python SDK" />
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+
<orderEntry type="sourceFolder" forTests="false" />
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+
</component>
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| 8 |
+
<component name="PyDocumentationSettings">
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+
<option name="format" value="PLAIN" />
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+
<option name="myDocStringFormat" value="Plain" />
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| 11 |
+
</component>
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| 12 |
+
</module>
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.idea/inspectionProfiles/Project_Default.xml
ADDED
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| 1 |
+
<component name="InspectionProjectProfileManager">
|
| 2 |
+
<profile version="1.0">
|
| 3 |
+
<option name="myName" value="Project Default" />
|
| 4 |
+
<inspection_tool class="Eslint" enabled="true" level="WARNING" enabled_by_default="true" />
|
| 5 |
+
<inspection_tool class="GrazieInspection" enabled="false" level="GRAMMAR_ERROR" enabled_by_default="false" />
|
| 6 |
+
<inspection_tool class="LanguageDetectionInspection" enabled="false" level="WARNING" enabled_by_default="false" />
|
| 7 |
+
<inspection_tool class="PyDictCreationInspection" enabled="false" level="WEAK WARNING" enabled_by_default="false" />
|
| 8 |
+
<inspection_tool class="PyDictDuplicateKeysInspection" enabled="false" level="WARNING" enabled_by_default="false" />
|
| 9 |
+
<inspection_tool class="SpellCheckingInspection" enabled="false" level="TYPO" enabled_by_default="false">
|
| 10 |
+
<option name="processCode" value="true" />
|
| 11 |
+
<option name="processLiterals" value="true" />
|
| 12 |
+
<option name="processComments" value="true" />
|
| 13 |
+
</inspection_tool>
|
| 14 |
+
<inspection_tool class="TrailingSpacesInProperty" enabled="false" level="WARNING" enabled_by_default="false" />
|
| 15 |
+
<inspection_tool class="UnusedProperty" enabled="false" level="WARNING" enabled_by_default="false" />
|
| 16 |
+
<inspection_tool class="WrongPropertyKeyValueDelimiter" enabled="false" level="WEAK WARNING" enabled_by_default="false" />
|
| 17 |
+
</profile>
|
| 18 |
+
</component>
|
.idea/inspectionProfiles/profiles_settings.xml
ADDED
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| 1 |
+
<component name="InspectionProjectProfileManager">
|
| 2 |
+
<settings>
|
| 3 |
+
<option name="USE_PROJECT_PROFILE" value="false" />
|
| 4 |
+
<version value="1.0" />
|
| 5 |
+
</settings>
|
| 6 |
+
</component>
|
.idea/misc.xml
ADDED
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+
<?xml version="1.0" encoding="UTF-8"?>
|
| 2 |
+
<project version="4">
|
| 3 |
+
<component name="Black">
|
| 4 |
+
<option name="sdkName" value="Python 3.10 virtualenv at ~/.pyenv/versions/3.10.13/envs/venv-py310" />
|
| 5 |
+
</component>
|
| 6 |
+
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 virtualenv at ~/.pyenv/versions/3.10.13/envs/venv-py310" project-jdk-type="Python SDK" />
|
| 7 |
+
</project>
|
.idea/modules.xml
ADDED
|
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| 1 |
+
<?xml version="1.0" encoding="UTF-8"?>
|
| 2 |
+
<project version="4">
|
| 3 |
+
<component name="ProjectModuleManager">
|
| 4 |
+
<modules>
|
| 5 |
+
<module fileurl="file://$PROJECT_DIR$/.idea/flux-fast-main.iml" filepath="$PROJECT_DIR$/.idea/flux-fast-main.iml" />
|
| 6 |
+
</modules>
|
| 7 |
+
</component>
|
| 8 |
+
</project>
|
.idea/workspace.xml
ADDED
|
@@ -0,0 +1,58 @@
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|
| 1 |
+
<?xml version="1.0" encoding="UTF-8"?>
|
| 2 |
+
<project version="4">
|
| 3 |
+
<component name="AutoImportSettings">
|
| 4 |
+
<option name="autoReloadType" value="SELECTIVE" />
|
| 5 |
+
</component>
|
| 6 |
+
<component name="ChangeListManager">
|
| 7 |
+
<list default="true" id="98d7b715-8564-4636-8c4f-0d9067d28c48" name="Changes" comment="" />
|
| 8 |
+
<option name="SHOW_DIALOG" value="false" />
|
| 9 |
+
<option name="HIGHLIGHT_CONFLICTS" value="true" />
|
| 10 |
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README.md
ADDED
|
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|
| 1 |
+
# flux-fast
|
| 2 |
+
Making Flux go brrr on GPUs. With simple recipes from this repo, we enabled ~2.5x speedup on Flux.1-Schnell and Flux.1-Dev using (mainly) pure PyTorch code and a beefy GPU like H100. This repo is NOT meant to be a library or an out-of-the-box solution. So, please fork the repo, hack into the code, and share your results 🤗
|
| 3 |
+
|
| 4 |
+
Check out the accompanying blog post [here](https://pytorch.org/blog/presenting-flux-fast-making-flux-go-brrr-on-h100s/).
|
| 5 |
+
|
| 6 |
+
## Results
|
| 7 |
+
|
| 8 |
+
<table>
|
| 9 |
+
<thead>
|
| 10 |
+
<tr>
|
| 11 |
+
<th>Description</th>
|
| 12 |
+
<th>Image</th>
|
| 13 |
+
</tr>
|
| 14 |
+
</thead>
|
| 15 |
+
<tbody>
|
| 16 |
+
<tr>
|
| 17 |
+
<td>Flux.1-Schnell</td>
|
| 18 |
+
<td><img src="https://github.com/user-attachments/assets/3f18d621-bdcd-423d-a66c-fd34bbd90f27" width=500 alt="new_flux_schnell_plot" /></td>
|
| 19 |
+
</tr>
|
| 20 |
+
<tr>
|
| 21 |
+
<td>Flux.1-Dev</td>
|
| 22 |
+
<td><img src="https://github.com/user-attachments/assets/48945137-c826-497a-a292-b1f976a5b16a" width=500 alt="flux_dev_result_plot" /></td>
|
| 23 |
+
</tr>
|
| 24 |
+
</tbody>
|
| 25 |
+
</table>
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
Summary of the optimizations:
|
| 29 |
+
* Running with the bfloat16 precision
|
| 30 |
+
* `torch.compile`
|
| 31 |
+
* Combining q,k,v projections for attention computation
|
| 32 |
+
* `torch.channels_last` memory format for the decoder output
|
| 33 |
+
* Flash Attention v3 (FA3) with (unscaled) conversion of inputs to `torch.float8_e4m3fn`
|
| 34 |
+
* Dynamic float8 quantization and quantization of Linear layer weights via `torchao`'s `float8_dynamic_activation_float8_weight`
|
| 35 |
+
* Inductor flags:
|
| 36 |
+
* `conv_1x1_as_mm = True`
|
| 37 |
+
* `epilogue_fusion = False`
|
| 38 |
+
* `coordinate_descent_tuning = True`
|
| 39 |
+
* `coordinate_descent_check_all_directions = True`
|
| 40 |
+
* `torch.export` + Ahead-of-time Inductor (AOTI) + CUDAGraphs
|
| 41 |
+
|
| 42 |
+
All of the above optimizations are lossless (outside of minor numerical differences sometimes
|
| 43 |
+
introduced through the use of `torch.compile` / `torch.export`) EXCEPT FOR dynamic float8 quantization.
|
| 44 |
+
Disable quantization if you want the same quality results as the baseline while still being
|
| 45 |
+
quite a bit faster.
|
| 46 |
+
|
| 47 |
+
Here are some example outputs with Flux.1-Schnell for prompt `"A cat playing with a ball of yarn"`:
|
| 48 |
+
|
| 49 |
+
<table>
|
| 50 |
+
<thead>
|
| 51 |
+
<tr>
|
| 52 |
+
<th>Configuration</th>
|
| 53 |
+
<th>Output</th>
|
| 54 |
+
</tr>
|
| 55 |
+
</thead>
|
| 56 |
+
<tbody>
|
| 57 |
+
<tr>
|
| 58 |
+
<td><strong>Baseline</strong></td>
|
| 59 |
+
<td><img src="https://github.com/user-attachments/assets/8ba746d2-fbf3-4e30-adc4-11303231c146" alt="baseline_output" width=400/></td>
|
| 60 |
+
</tr>
|
| 61 |
+
<tr>
|
| 62 |
+
<td><strong>Fully-optimized (with quantization)</strong></td>
|
| 63 |
+
<td><img src="https://github.com/user-attachments/assets/1a31dec4-38d5-45b2-8ae6-c7fb2e6413a4" alt="fast_output" width=400/></td>
|
| 64 |
+
</tr>
|
| 65 |
+
</tbody>
|
| 66 |
+
</table>
|
| 67 |
+
|
| 68 |
+
## Setup
|
| 69 |
+
We rely primarily on pure PyTorch for the optimizations. Currently, a relatively recent nightly version of PyTorch is required.
|
| 70 |
+
|
| 71 |
+
The numbers reported here were gathered using:
|
| 72 |
+
* `torch==2.8.0.dev20250605+cu126` - note that we rely on some fixes since 2.7
|
| 73 |
+
* `torchao==0.12.0.dev20250610+cu126` - note that we rely on a fix in the 06/10 nightly
|
| 74 |
+
* `diffusers` - with [this fix](https://github.com/huggingface/diffusers/pull/11696) included
|
| 75 |
+
* `flash_attn_3==3.0.0b1`
|
| 76 |
+
|
| 77 |
+
To install deps:
|
| 78 |
+
```
|
| 79 |
+
pip install -U diffusers
|
| 80 |
+
pip install --pre torch==2.8.0.dev20250605+cu126 --index-url https://download.pytorch.org/whl/nightly/cu126
|
| 81 |
+
pip install --pre torchao==0.12.0.dev20250609+cu126 --index-url https://download.pytorch.org/whl/nightly/cu126
|
| 82 |
+
```
|
| 83 |
+
|
| 84 |
+
To install flash attention v3, follow the instructions in https://github.com/Dao-AILab/flash-attention#flashattention-3-beta-release.
|
| 85 |
+
|
| 86 |
+
For hardware, we used a 96GB 700W H100 GPU. Some of the optimizations applied (BFloat16, torch.compile, Combining q,k,v projections, dynamic float8 quantization) are available on CPU as well.
|
| 87 |
+
|
| 88 |
+
## Run the optimized pipeline
|
| 89 |
+
|
| 90 |
+
```sh
|
| 91 |
+
python gen_image.py --prompt "An astronaut standing next to a giant lemon" --output-file output.png --use-cached-model
|
| 92 |
+
```
|
| 93 |
+
|
| 94 |
+
This will include all optimizations and will attempt to use pre-cached binary models
|
| 95 |
+
generated via `torch.export` + AOTI. To generate these binaries for subsequent runs, run
|
| 96 |
+
the above command without the `--use-cached-model` flag.
|
| 97 |
+
|
| 98 |
+
> [!IMPORTANT]
|
| 99 |
+
> The binaries won't work for hardware that is sufficiently different from the hardware they were
|
| 100 |
+
> obtained on. For example, if the binaries were obtained on an H100, they won't work on A100.
|
| 101 |
+
> Further, the binaries are currently Linux-only and include dependencies on specific versions
|
| 102 |
+
> of system libs such as libstdc++; they will not work if they were generated in a sufficiently
|
| 103 |
+
> different environment than the one present at runtime. The PyTorch Compiler team is working on
|
| 104 |
+
> solutions for more portable binaries / artifact caching.
|
| 105 |
+
|
| 106 |
+
## Benchmarking
|
| 107 |
+
[`run_benchmark.py`](./run_benchmark.py) is the main script for benchmarking the different optimization techniques.
|
| 108 |
+
Usage:
|
| 109 |
+
```
|
| 110 |
+
usage: run_benchmark.py [-h] [--ckpt CKPT] [--prompt PROMPT] [--cache-dir CACHE_DIR]
|
| 111 |
+
[--device {cuda,cpu}] [--num_inference_steps NUM_INFERENCE_STEPS]
|
| 112 |
+
[--output-file OUTPUT_FILE] [--trace-file TRACE_FILE] [--disable_bf16]
|
| 113 |
+
[--compile_export_mode {compile,export_aoti,disabled}]
|
| 114 |
+
[--disable_fused_projections] [--disable_channels_last] [--disable_fa3]
|
| 115 |
+
[--disable_quant] [--disable_inductor_tuning_flags]
|
| 116 |
+
|
| 117 |
+
options:
|
| 118 |
+
-h, --help show this help message and exit
|
| 119 |
+
--ckpt CKPT Model checkpoint path (default: black-forest-labs/FLUX.1-schnell)
|
| 120 |
+
--prompt PROMPT Text prompt (default: A cat playing with a ball of yarn)
|
| 121 |
+
--cache-dir CACHE_DIR
|
| 122 |
+
Cache directory for storing exported models (default:
|
| 123 |
+
~/.cache/flux-fast)
|
| 124 |
+
--device {cuda,cpu} Device to use (default: cuda)
|
| 125 |
+
--num_inference_steps NUM_INFERENCE_STEPS
|
| 126 |
+
Number of denoising steps (default: 4)
|
| 127 |
+
--output-file OUTPUT_FILE
|
| 128 |
+
Output image file path (default: output.png)
|
| 129 |
+
--trace-file TRACE_FILE
|
| 130 |
+
Output PyTorch Profiler trace file path (default: None)
|
| 131 |
+
--disable_bf16 Disables usage of torch.bfloat16 (default: False)
|
| 132 |
+
--compile_export_mode {compile,export_aoti,disabled}
|
| 133 |
+
Configures how torch.compile or torch.export + AOTI are used (default:
|
| 134 |
+
export_aoti)
|
| 135 |
+
--disable_fused_projections
|
| 136 |
+
Disables fused q,k,v projections (default: False)
|
| 137 |
+
--disable_channels_last
|
| 138 |
+
Disables usage of torch.channels_last memory format (default: False)
|
| 139 |
+
--disable_fa3 Disables use of Flash Attention V3 (default: False)
|
| 140 |
+
--disable_quant Disables usage of dynamic float8 quantization (default: False)
|
| 141 |
+
--disable_inductor_tuning_flags
|
| 142 |
+
Disables use of inductor tuning flags (default: False)
|
| 143 |
+
```
|
| 144 |
+
|
| 145 |
+
Note that all optimizations are on by default and each can be individually toggled. Example run:
|
| 146 |
+
```
|
| 147 |
+
# Run with all optimizations and output a trace file alongside benchmark numbers
|
| 148 |
+
python run_benchmark.py --trace-file profiler_trace.json.gz
|
| 149 |
+
```
|
| 150 |
+
|
| 151 |
+
After an experiment has been run, you should expect to see
|
| 152 |
+
mean / variance times in seconds for 10 benchmarking runs printed to STDOUT, as well as:
|
| 153 |
+
|
| 154 |
+
* A `.png` image file corresponding to the experiment (e.g. `output.png`). The path can be configured via `--output-file`.
|
| 155 |
+
* An optional PyTorch profiler trace (e.g. `profiler_trace.json.gz`). The path can be configured via `--trace-file`
|
| 156 |
+
|
| 157 |
+
## Improvements, progressively
|
| 158 |
+
<details>
|
| 159 |
+
<summary>Baseline</summary>
|
| 160 |
+
|
| 161 |
+
For completeness, we demonstrate a (terrible) baseline here using the default `torch.float32` dtype.
|
| 162 |
+
There's no practical reason do this over loading in `torch.bfloat16`, and the results are slow enough
|
| 163 |
+
that they ruin the readability of the graph above when included (~7.5 sec).
|
| 164 |
+
|
| 165 |
+
```python
|
| 166 |
+
from diffusers import FluxPipeline
|
| 167 |
+
|
| 168 |
+
# Load the pipeline in full-precision and place its model components on CUDA.
|
| 169 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 170 |
+
"black-forest-labs/FLUX.1-schnell"
|
| 171 |
+
).to("cuda")
|
| 172 |
+
|
| 173 |
+
prompt = "A cat playing with a ball of yarn"
|
| 174 |
+
image = pipe(prompt, num_inference_steps=4).images[0]
|
| 175 |
+
```
|
| 176 |
+
|
| 177 |
+
</details>
|
| 178 |
+
|
| 179 |
+
<details>
|
| 180 |
+
<summary>BFloat16</summary>
|
| 181 |
+
|
| 182 |
+
```python
|
| 183 |
+
from diffusers import FluxPipeline
|
| 184 |
+
|
| 185 |
+
# Load the pipeline in full-precision and place its model components on CUDA.
|
| 186 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 187 |
+
"black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16
|
| 188 |
+
).to("cuda")
|
| 189 |
+
|
| 190 |
+
prompt = "A cat playing with a ball of yarn"
|
| 191 |
+
image = pipe(prompt, num_inference_steps=4).images[0]
|
| 192 |
+
```
|
| 193 |
+
|
| 194 |
+
</details>
|
| 195 |
+
|
| 196 |
+
<details>
|
| 197 |
+
<summary>torch.compile</summary>
|
| 198 |
+
|
| 199 |
+
```python
|
| 200 |
+
from diffusers import FluxPipeline
|
| 201 |
+
|
| 202 |
+
# Load the pipeline in full-precision and place its model components on CUDA.
|
| 203 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 204 |
+
"black-forest-labs/FLUX.1-schnell"
|
| 205 |
+
).to("cuda")
|
| 206 |
+
|
| 207 |
+
# Compile the compute-intensive portions of the model: denoising transformer / decoder
|
| 208 |
+
# "max-autotune" mode tunes kernel hyperparameters and applies CUDAGraphs
|
| 209 |
+
pipeline.transformer = torch.compile(
|
| 210 |
+
pipeline.transformer, mode="max-autotune", fullgraph=True
|
| 211 |
+
)
|
| 212 |
+
pipeline.vae.decode = torch.compile(
|
| 213 |
+
pipeline.vae.decode, mode="max-autotune", fullgraph=True
|
| 214 |
+
)
|
| 215 |
+
|
| 216 |
+
# warmup for a few iterations; trigger compilation
|
| 217 |
+
for _ in range(3):
|
| 218 |
+
pipeline(
|
| 219 |
+
"dummy prompt to trigger torch compilation",
|
| 220 |
+
output_type="pil",
|
| 221 |
+
num_inference_steps=4,
|
| 222 |
+
).images[0]
|
| 223 |
+
|
| 224 |
+
prompt = "A cat playing with a ball of yarn"
|
| 225 |
+
image = pipe(prompt, num_inference_steps=4).images[0]
|
| 226 |
+
```
|
| 227 |
+
|
| 228 |
+
</details>
|
| 229 |
+
|
| 230 |
+
<details>
|
| 231 |
+
<summary>Combining attention projection matrices</summary>
|
| 232 |
+
|
| 233 |
+
```python
|
| 234 |
+
from diffusers import FluxPipeline
|
| 235 |
+
|
| 236 |
+
# Load the pipeline in full-precision and place its model components on CUDA.
|
| 237 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 238 |
+
"black-forest-labs/FLUX.1-schnell"
|
| 239 |
+
).to("cuda")
|
| 240 |
+
|
| 241 |
+
# Use channels_last memory format
|
| 242 |
+
pipeline.vae = pipeline.vae.to(memory_format=torch.channels_last)
|
| 243 |
+
|
| 244 |
+
# Combine attention projection matrices for (q, k, v)
|
| 245 |
+
pipeline.transformer.fuse_qkv_projections()
|
| 246 |
+
pipeline.vae.fuse_qkv_projections()
|
| 247 |
+
|
| 248 |
+
# compilation details omitted (see above)
|
| 249 |
+
...
|
| 250 |
+
|
| 251 |
+
prompt = "A cat playing with a ball of yarn"
|
| 252 |
+
image = pipe(prompt, num_inference_steps=4).images[0]
|
| 253 |
+
```
|
| 254 |
+
|
| 255 |
+
Note that `torch.compile` is able to perform this fusion automatically, so we do not
|
| 256 |
+
observe a speedup from the fusion (outside of noise) when `torch.compile` is enabled.
|
| 257 |
+
|
| 258 |
+
</details>
|
| 259 |
+
|
| 260 |
+
<details>
|
| 261 |
+
<summary>channels_last memory format</summary>
|
| 262 |
+
|
| 263 |
+
```python
|
| 264 |
+
from diffusers import FluxPipeline
|
| 265 |
+
|
| 266 |
+
# Load the pipeline in full-precision and place its model components on CUDA.
|
| 267 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 268 |
+
"black-forest-labs/FLUX.1-schnell"
|
| 269 |
+
).to("cuda")
|
| 270 |
+
|
| 271 |
+
# Use channels_last memory format
|
| 272 |
+
pipeline.vae.to(memory_format=torch.channels_last)
|
| 273 |
+
|
| 274 |
+
# compilation details omitted (see above)
|
| 275 |
+
...
|
| 276 |
+
|
| 277 |
+
prompt = "A cat playing with a ball of yarn"
|
| 278 |
+
image = pipe(prompt, num_inference_steps=4).images[0]
|
| 279 |
+
```
|
| 280 |
+
|
| 281 |
+
</details>
|
| 282 |
+
|
| 283 |
+
<details>
|
| 284 |
+
<summary>Flash Attention V3</summary>
|
| 285 |
+
|
| 286 |
+
Flash Attention V3 is substantially faster on H100s than the previous iteration FA2, due
|
| 287 |
+
in large part to float8 support. As this kernel isn't quite available yet within PyTorch Core, we implement a custom
|
| 288 |
+
attention processor [`FlashFusedFluxAttnProcessor3_0`](./utils/pipeline_utils.py#L70) that uses the `flash_attn_interface`
|
| 289 |
+
python bindings directly. We also ensure proper PyTorch custom op integration so that
|
| 290 |
+
the op integrates well with `torch.compile` / `torch.export`. Inputs are converted to float8 in an unscaled fashion before
|
| 291 |
+
kernel invocation and outputs are converted back to the original dtype on the way out.
|
| 292 |
+
|
| 293 |
+
```python
|
| 294 |
+
from diffusers import FluxPipeline
|
| 295 |
+
|
| 296 |
+
# Load the pipeline in full-precision and place its model components on CUDA.
|
| 297 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 298 |
+
"black-forest-labs/FLUX.1-schnell"
|
| 299 |
+
).to("cuda")
|
| 300 |
+
|
| 301 |
+
# Use channels_last memory format
|
| 302 |
+
pipeline.vae.to(memory_format=torch.channels_last)
|
| 303 |
+
|
| 304 |
+
# Combine attention projection matrices for (q, k, v)
|
| 305 |
+
pipeline.transformer.fuse_qkv_projections()
|
| 306 |
+
pipeline.vae.fuse_qkv_projections()
|
| 307 |
+
|
| 308 |
+
# Use FA3; reference FlashFusedFluxAttnProcessor3_0 impl for details
|
| 309 |
+
pipeline.transformer.set_attn_processor(FlashFusedFluxAttnProcessor3_0())
|
| 310 |
+
|
| 311 |
+
# compilation details omitted (see above)
|
| 312 |
+
...
|
| 313 |
+
|
| 314 |
+
prompt = "A cat playing with a ball of yarn"
|
| 315 |
+
image = pipe(prompt, num_inference_steps=4).images[0]
|
| 316 |
+
```
|
| 317 |
+
|
| 318 |
+
</details>
|
| 319 |
+
|
| 320 |
+
<details>
|
| 321 |
+
<summary>float8 quantization</summary>
|
| 322 |
+
|
| 323 |
+
```python
|
| 324 |
+
from diffusers import FluxPipeline
|
| 325 |
+
|
| 326 |
+
# Load the pipeline in full-precision and place its model components on CUDA.
|
| 327 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 328 |
+
"black-forest-labs/FLUX.1-schnell"
|
| 329 |
+
).to("cuda")
|
| 330 |
+
|
| 331 |
+
# Use channels_last memory format
|
| 332 |
+
pipeline.vae.to(memory_format=torch.channels_last)
|
| 333 |
+
|
| 334 |
+
# Combine attention projection matrices for (q, k, v)
|
| 335 |
+
pipeline.transformer.fuse_qkv_projections()
|
| 336 |
+
pipeline.vae.fuse_qkv_projections()
|
| 337 |
+
|
| 338 |
+
# Use FA3; reference FlashFusedFluxAttnProcessor3_0 impl for details
|
| 339 |
+
pipeline.transformer.set_attn_processor(FlashFusedFluxAttnProcessor3_0())
|
| 340 |
+
|
| 341 |
+
# Apply float8 quantization on weights and activations
|
| 342 |
+
from torchao.quantization import quantize_, float8_dynamic_activation_float8_weight
|
| 343 |
+
|
| 344 |
+
quantize_(
|
| 345 |
+
pipeline.transformer,
|
| 346 |
+
float8_dynamic_activation_float8_weight(),
|
| 347 |
+
)
|
| 348 |
+
|
| 349 |
+
# compilation details omitted (see above)
|
| 350 |
+
...
|
| 351 |
+
|
| 352 |
+
prompt = "A cat playing with a ball of yarn"
|
| 353 |
+
image = pipe(prompt, num_inference_steps=4).images[0]
|
| 354 |
+
```
|
| 355 |
+
|
| 356 |
+
</details>
|
| 357 |
+
|
| 358 |
+
<details>
|
| 359 |
+
<summary>Inductor tuning flags</summary>
|
| 360 |
+
|
| 361 |
+
```python
|
| 362 |
+
from diffusers import FluxPipeline
|
| 363 |
+
|
| 364 |
+
# Load the pipeline in full-precision and place its model components on CUDA.
|
| 365 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 366 |
+
"black-forest-labs/FLUX.1-schnell"
|
| 367 |
+
).to("cuda")
|
| 368 |
+
|
| 369 |
+
# Use channels_last memory format
|
| 370 |
+
pipeline.vae.to(memory_format=torch.channels_last)
|
| 371 |
+
|
| 372 |
+
# Combine attention projection matrices for (q, k, v)
|
| 373 |
+
pipeline.transformer.fuse_qkv_projections()
|
| 374 |
+
pipeline.vae.fuse_qkv_projections()
|
| 375 |
+
|
| 376 |
+
# Use FA3; reference FlashFusedFluxAttnProcessor3_0 impl for details
|
| 377 |
+
pipeline.transformer.set_attn_processor(FlashFusedFluxAttnProcessor3_0())
|
| 378 |
+
|
| 379 |
+
# Apply float8 quantization on weights and activations
|
| 380 |
+
from torchao.quantization import quantize_, float8_dynamic_activation_float8_weight
|
| 381 |
+
|
| 382 |
+
quantize_(
|
| 383 |
+
pipeline.transformer,
|
| 384 |
+
float8_dynamic_activation_float8_weight(),
|
| 385 |
+
)
|
| 386 |
+
|
| 387 |
+
# Tune Inductor flags
|
| 388 |
+
config = torch._inductor.config
|
| 389 |
+
config.conv_1x1_as_mm = True # treat 1x1 convolutions as matrix muls
|
| 390 |
+
# adjust autotuning algorithm
|
| 391 |
+
config.coordinate_descent_tuning = True
|
| 392 |
+
config.coordinate_descent_check_all_directions = True
|
| 393 |
+
config.epilogue_fusion = False # do not fuse pointwise ops into matmuls
|
| 394 |
+
|
| 395 |
+
# compilation details omitted (see above)
|
| 396 |
+
...
|
| 397 |
+
|
| 398 |
+
prompt = "A cat playing with a ball of yarn"
|
| 399 |
+
image = pipe(prompt, num_inference_steps=4).images[0]
|
| 400 |
+
```
|
| 401 |
+
|
| 402 |
+
</details>
|
| 403 |
+
|
| 404 |
+
<details>
|
| 405 |
+
<summary>torch.export + Ahead-Of-Time Inductor (AOTI)</summary>
|
| 406 |
+
|
| 407 |
+
To avoid initial compilation times, we can use `torch.export` + Ahead-Of-Time Inductor (AOTI). This will
|
| 408 |
+
serialize a binary, precompiled form of the model without initial compilation overhead.
|
| 409 |
+
|
| 410 |
+
```python
|
| 411 |
+
# Apply torch.export + AOTI. If serialize=True, writes out the exported models within the cache_dir.
|
| 412 |
+
# Otherwise, attempts to load previously-exported models from the cache_dir.
|
| 413 |
+
# This function also applies CUDAGraphs on the loaded models.
|
| 414 |
+
def use_export_aoti(pipeline, cache_dir, serialize=False):
|
| 415 |
+
from torch._inductor.package import load_package
|
| 416 |
+
|
| 417 |
+
# create cache dir if needed
|
| 418 |
+
pathlib.Path(cache_dir).mkdir(parents=True, exist_ok=True)
|
| 419 |
+
|
| 420 |
+
def _example_tensor(*shape):
|
| 421 |
+
return torch.randn(*shape, device="cuda", dtype=torch.bfloat16)
|
| 422 |
+
|
| 423 |
+
# === Transformer export ===
|
| 424 |
+
# torch.export requires a representative set of example args to be passed in
|
| 425 |
+
transformer_kwargs = {
|
| 426 |
+
"hidden_states": _example_tensor(1, 4096, 64),
|
| 427 |
+
"timestep": torch.tensor([1.], device="cuda", dtype=torch.bfloat16),
|
| 428 |
+
"guidance": None,
|
| 429 |
+
"pooled_projections": _example_tensor(1, 768),
|
| 430 |
+
"encoder_hidden_states": _example_tensor(1, 512, 4096),
|
| 431 |
+
"txt_ids": _example_tensor(512, 3),
|
| 432 |
+
"img_ids": _example_tensor(4096, 3),
|
| 433 |
+
"joint_attention_kwargs": {},
|
| 434 |
+
"return_dict": False,
|
| 435 |
+
}
|
| 436 |
+
|
| 437 |
+
# Possibly serialize model out
|
| 438 |
+
transformer_package_path = os.path.join(cache_dir, "exported_transformer.pt2")
|
| 439 |
+
if serialize:
|
| 440 |
+
# Apply export
|
| 441 |
+
exported_transformer: torch.export.ExportedProgram = torch.export.export(
|
| 442 |
+
pipeline.transformer, args=(), kwargs=transformer_kwargs
|
| 443 |
+
)
|
| 444 |
+
|
| 445 |
+
# Apply AOTI
|
| 446 |
+
path = torch._inductor.aoti_compile_and_package(
|
| 447 |
+
exported_transformer,
|
| 448 |
+
package_path=transformer_package_path,
|
| 449 |
+
inductor_configs={"max_autotune": True, "triton.cudagraphs": True},
|
| 450 |
+
)
|
| 451 |
+
|
| 452 |
+
loaded_transformer = load_package(
|
| 453 |
+
transformer_package_path, run_single_threaded=True
|
| 454 |
+
)
|
| 455 |
+
|
| 456 |
+
# warmup before cudagraphing
|
| 457 |
+
with torch.no_grad():
|
| 458 |
+
loaded_transformer(**transformer_kwargs)
|
| 459 |
+
|
| 460 |
+
# Apply CUDAGraphs. CUDAGraphs are utilized in torch.compile with mode="max-autotune", but
|
| 461 |
+
# they must be manually applied for torch.export + AOTI.
|
| 462 |
+
loaded_transformer = cudagraph(loaded_transformer)
|
| 463 |
+
pipeline.transformer.forward = loaded_transformer
|
| 464 |
+
|
| 465 |
+
# warmup after cudagraphing
|
| 466 |
+
with torch.no_grad():
|
| 467 |
+
pipeline.transformer(**transformer_kwargs)
|
| 468 |
+
|
| 469 |
+
# hack to get around export's limitations
|
| 470 |
+
pipeline.vae.forward = pipeline.vae.decode
|
| 471 |
+
|
| 472 |
+
vae_decode_kwargs = {
|
| 473 |
+
"return_dict": False,
|
| 474 |
+
}
|
| 475 |
+
|
| 476 |
+
# Possibly serialize model out
|
| 477 |
+
decoder_package_path = os.path.join(cache_dir, "exported_decoder.pt2")
|
| 478 |
+
if serialize:
|
| 479 |
+
# Apply export
|
| 480 |
+
exported_decoder: torch.export.ExportedProgram = torch.export.export(
|
| 481 |
+
pipeline.vae, args=(_example_tensor(1, 16, 128, 128),), kwargs=vae_decode_kwargs
|
| 482 |
+
)
|
| 483 |
+
|
| 484 |
+
# Apply AOTI
|
| 485 |
+
path = torch._inductor.aoti_compile_and_package(
|
| 486 |
+
exported_decoder,
|
| 487 |
+
package_path=decoder_package_path,
|
| 488 |
+
inductor_configs={"max_autotune": True, "triton.cudagraphs": True},
|
| 489 |
+
)
|
| 490 |
+
|
| 491 |
+
loaded_decoder = load_package(decoder_package_path, run_single_threaded=True)
|
| 492 |
+
|
| 493 |
+
# warmup before cudagraphing
|
| 494 |
+
with torch.no_grad():
|
| 495 |
+
loaded_decoder(_example_tensor(1, 16, 128, 128), **vae_decode_kwargs)
|
| 496 |
+
|
| 497 |
+
loaded_decoder = cudagraph(loaded_decoder)
|
| 498 |
+
pipeline.vae.decode = loaded_decoder
|
| 499 |
+
|
| 500 |
+
# warmup for a few iterations
|
| 501 |
+
for _ in range(3):
|
| 502 |
+
pipeline(
|
| 503 |
+
"dummy prompt to trigger torch compilation",
|
| 504 |
+
output_type="pil",
|
| 505 |
+
num_inference_steps=4,
|
| 506 |
+
).images[0]
|
| 507 |
+
|
| 508 |
+
return pipeline
|
| 509 |
+
```
|
| 510 |
+
|
| 511 |
+
Note that, unlike for `torch.compile`, running a model loaded from the torch.export + AOTI workflow
|
| 512 |
+
doesn't use CUDAGraphs by default. This was found to result in a ~5% performance decrease vs. torch.compile.
|
| 513 |
+
To address this discrepancy, we manually record / replay CUDAGraphs over the exported models using the following helper:
|
| 514 |
+
```python
|
| 515 |
+
# wrapper to automatically handle CUDAGraph record / replay over the given function
|
| 516 |
+
def cudagraph(f):
|
| 517 |
+
from torch.utils._pytree import tree_map_only
|
| 518 |
+
|
| 519 |
+
_graphs = {}
|
| 520 |
+
def f_(*args, **kwargs):
|
| 521 |
+
key = hash(tuple(tuple(kwargs[a].shape) for a in sorted(kwargs.keys())
|
| 522 |
+
if isinstance(kwargs[a], torch.Tensor)))
|
| 523 |
+
if key in _graphs:
|
| 524 |
+
# use the cached wrapper if one exists. this will perform CUDAGraph replay
|
| 525 |
+
wrapped, *_ = _graphs[key]
|
| 526 |
+
return wrapped(*args, **kwargs)
|
| 527 |
+
|
| 528 |
+
# record a new CUDAGraph and cache it for future use
|
| 529 |
+
g = torch.cuda.CUDAGraph()
|
| 530 |
+
in_args, in_kwargs = tree_map_only(torch.Tensor, lambda t: t.clone(), (args, kwargs))
|
| 531 |
+
f(*in_args, **in_kwargs) # stream warmup
|
| 532 |
+
with torch.cuda.graph(g):
|
| 533 |
+
out_tensors = f(*in_args, **in_kwargs)
|
| 534 |
+
def wrapped(*args, **kwargs):
|
| 535 |
+
# note that CUDAGraphs require inputs / outputs to be in fixed memory locations.
|
| 536 |
+
# inputs must be copied into the fixed input memory locations.
|
| 537 |
+
[a.copy_(b) for a, b in zip(in_args, args) if isinstance(a, torch.Tensor)]
|
| 538 |
+
for key in kwargs:
|
| 539 |
+
if isinstance(kwargs[key], torch.Tensor):
|
| 540 |
+
in_kwargs[key].copy_(kwargs[key])
|
| 541 |
+
g.replay()
|
| 542 |
+
# clone() outputs on the way out to disconnect them from the fixed output memory
|
| 543 |
+
# locations. this allows for CUDAGraph reuse without accidentally overwriting memory
|
| 544 |
+
return [o.clone() for o in out_tensors]
|
| 545 |
+
|
| 546 |
+
# cache function that does CUDAGraph replay
|
| 547 |
+
_graphs[key] = (wrapped, g, in_args, in_kwargs, out_tensors)
|
| 548 |
+
return wrapped(*args, **kwargs)
|
| 549 |
+
return f_
|
| 550 |
+
```
|
| 551 |
+
|
| 552 |
+
Finally, here is the fully-optimized form of the model:
|
| 553 |
+
|
| 554 |
+
```python
|
| 555 |
+
from diffusers import FluxPipeline
|
| 556 |
+
|
| 557 |
+
# Load the pipeline in full-precision and place its model components on CUDA.
|
| 558 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 559 |
+
"black-forest-labs/FLUX.1-schnell"
|
| 560 |
+
).to("cuda")
|
| 561 |
+
|
| 562 |
+
# Use channels_last memory format
|
| 563 |
+
pipeline.vae.to(memory_format=torch.channels_last)
|
| 564 |
+
|
| 565 |
+
# Combine attention projection matrices for (q, k, v)
|
| 566 |
+
pipeline.transformer.fuse_qkv_projections()
|
| 567 |
+
pipeline.vae.fuse_qkv_projections()
|
| 568 |
+
|
| 569 |
+
# Use FA3; reference FlashFusedFluxAttnProcessor3_0 impl for details
|
| 570 |
+
pipeline.transformer.set_attn_processor(FlashFusedFluxAttnProcessor3_0())
|
| 571 |
+
|
| 572 |
+
# Apply float8 quantization on weights and activations
|
| 573 |
+
from torchao.quantization import quantize_, float8_dynamic_activation_float8_weight
|
| 574 |
+
|
| 575 |
+
quantize_(
|
| 576 |
+
pipeline.transformer,
|
| 577 |
+
float8_dynamic_activation_float8_weight(),
|
| 578 |
+
)
|
| 579 |
+
|
| 580 |
+
# Tune Inductor flags
|
| 581 |
+
config = torch._inductor.config
|
| 582 |
+
config.conv_1x1_as_mm = True # treat 1x1 convolutions as matrix muls
|
| 583 |
+
# adjust autotuning algorithm
|
| 584 |
+
config.coordinate_descent_tuning = True
|
| 585 |
+
config.coordinate_descent_check_all_directions = True
|
| 586 |
+
config.epilogue_fusion = False # do not fuse pointwise ops into matmuls
|
| 587 |
+
|
| 588 |
+
# Apply torch.export + AOTI with CUDAGraphs
|
| 589 |
+
pipeline = use_export_aoti(pipeline, cache_dir=args.cache_dir, serialize=False)
|
| 590 |
+
|
| 591 |
+
prompt = "A cat playing with a ball of yarn"
|
| 592 |
+
image = pipe(prompt, num_inference_steps=4).images[0]
|
| 593 |
+
```
|
| 594 |
+
|
| 595 |
+
</details>
|
aoti_export.log
ADDED
|
@@ -0,0 +1,954 @@
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| 40 |
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|
| 1 |
+
🔁 [Sun Jul 6 06:22:45 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 2 |
+
💾 [Sun Jul 6 06:22:45 AM PDT 2025] Cache kontrolü yapılıyor...
|
| 3 |
+
📊 [Sun Jul 6 06:22:45 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 4 |
+
CPU Info:
|
| 5 |
+
Cores: 16, Load: 0.77
|
| 6 |
+
RAM Info:
|
| 7 |
+
total used free shared buff/cache available
|
| 8 |
+
Mem: 30Gi 6.9Gi 12Gi 282Mi 12Gi 23Gi
|
| 9 |
+
Swap: 23Gi 25Mi 23Gi
|
| 10 |
+
GPU Info:
|
| 11 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 5738 MiB, 41, 0 %
|
| 12 |
+
---
|
| 13 |
+
🔍 [Sun Jul 6 06:22:45 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 14 |
+
🔥 [Sun Jul 6 06:22:46 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 15 |
+
CUDA Available: True
|
| 16 |
+
GPU Count: 1
|
| 17 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 18 |
+
GPU Memory: 5.6 GB
|
| 19 |
+
GPU warm-up tamamlandı
|
| 20 |
+
🚀 [Sun Jul 6 06:22:48 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 21 |
+
🔁 [Sun Jul 6 10:29:32 AM PDT 2025] ⚙️ Başlatılıyor
|
| 22 |
+
🧠 Sistem durumu (RAM, Swap, GPU):
|
| 23 |
+
total used free shared buff/cache available
|
| 24 |
+
Mem: 30Gi 4.0Gi 25Gi 66Mi 2.2Gi 26Gi
|
| 25 |
+
Swap: 23Gi 23Mi 23Gi
|
| 26 |
+
---
|
| 27 |
+
Sun Jul 6 10:29:32 2025
|
| 28 |
+
+-----------------------------------------------------------------------------------------+
|
| 29 |
+
| NVIDIA-SMI 575.64 Driver Version: 575.64 CUDA Version: 12.9 |
|
| 30 |
+
|-----------------------------------------+------------------------+----------------------+
|
| 31 |
+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
|
| 32 |
+
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
|
| 33 |
+
| | | MIG M. |
|
| 34 |
+
|=========================================+========================+======================|
|
| 35 |
+
| 0 NVIDIA GeForce RTX 2060 Off | 00000000:01:00.0 Off | N/A |
|
| 36 |
+
| N/A 38C P8 4W / 90W | 613MiB / 6144MiB | 12% Default |
|
| 37 |
+
| | | N/A |
|
| 38 |
+
+-----------------------------------------+------------------------+----------------------+
|
| 39 |
+
|
| 40 |
+
+-----------------------------------------------------------------------------------------+
|
| 41 |
+
| Processes: |
|
| 42 |
+
| GPU GI CI PID Type Process name GPU Memory |
|
| 43 |
+
| ID ID Usage |
|
| 44 |
+
|=========================================================================================|
|
| 45 |
+
| 0 N/A N/A 1683 G /usr/bin/ksecretd 2MiB |
|
| 46 |
+
| 0 N/A N/A 1686 G /usr/lib/Xorg 214MiB |
|
| 47 |
+
| 0 N/A N/A 1791 G /usr/bin/ksmserver 2MiB |
|
| 48 |
+
| 0 N/A N/A 1793 G /usr/bin/kded6 2MiB |
|
| 49 |
+
| 0 N/A N/A 1794 G /usr/bin/kwin_x11 131MiB |
|
| 50 |
+
| 0 N/A N/A 1862 G /usr/bin/kaccess 3MiB |
|
| 51 |
+
| 0 N/A N/A 1863 G ...it-kde-authentication-agent-1 2MiB |
|
| 52 |
+
| 0 N/A N/A 1865 G /usr/lib/xdg-desktop-portal-kde 2MiB |
|
| 53 |
+
| 0 N/A N/A 2022 G /usr/bin/kclockd 2MiB |
|
| 54 |
+
| 0 N/A N/A 2023 G /usr/bin/kdeconnectd 2MiB |
|
| 55 |
+
| 0 N/A N/A 2054 G /usr/bin/kalendarac 2MiB |
|
| 56 |
+
| 0 N/A N/A 2058 G /usr/bin/pamac-tray-plasma 2MiB |
|
| 57 |
+
| 0 N/A N/A 2069 G /usr/bin/kmix 2MiB |
|
| 58 |
+
| 0 N/A N/A 2148 G /sbin/akonadi_control 2MiB |
|
| 59 |
+
| 0 N/A N/A 2229 G /usr/bin/plasmashell 89MiB |
|
| 60 |
+
| 0 N/A N/A 2259 G ...bin/akonadi_archivemail_agent 2MiB |
|
| 61 |
+
| 0 N/A N/A 2260 G ...in/akonadi_birthdays_resource 2MiB |
|
| 62 |
+
| 0 N/A N/A 2261 G ...bin/akonadi_contacts_resource 2MiB |
|
| 63 |
+
| 0 N/A N/A 2262 G ...konadi_followupreminder_agent 2MiB |
|
| 64 |
+
| 0 N/A N/A 2263 G /usr/bin/akonadi_ical_resource 2MiB |
|
| 65 |
+
| 0 N/A N/A 2264 G /usr/bin/akonadi_indexing_agent 2MiB |
|
| 66 |
+
| 0 N/A N/A 2265 G .../bin/akonadi_maildir_resource 2MiB |
|
| 67 |
+
| 0 N/A N/A 2266 G .../akonadi_maildispatcher_agent 2MiB |
|
| 68 |
+
| 0 N/A N/A 2267 G .../bin/akonadi_mailfilter_agent 2MiB |
|
| 69 |
+
| 0 N/A N/A 2268 G /usr/bin/akonadi_mailmerge_agent 2MiB |
|
| 70 |
+
| 0 N/A N/A 2269 G /usr/bin/akonadi_migration_agent 2MiB |
|
| 71 |
+
| 0 N/A N/A 2270 G ...akonadi_newmailnotifier_agent 2MiB |
|
| 72 |
+
| 0 N/A N/A 2271 G /usr/bin/akonadi_sendlater_agent 2MiB |
|
| 73 |
+
| 0 N/A N/A 2272 G .../akonadi_unifiedmailbox_agent 2MiB |
|
| 74 |
+
| 0 N/A N/A 2475 G /usr/lib/kf6/kioworker 1MiB |
|
| 75 |
+
| 0 N/A N/A 2506 G /sbin/dolphin 2MiB |
|
| 76 |
+
| 0 N/A N/A 2670 G /opt/visual-studio-code/code 83MiB |
|
| 77 |
+
| 0 N/A N/A 2815 G /usr/bin/kwalletd6 12MiB |
|
| 78 |
+
+-----------------------------------------------------------------------------------------+
|
| 79 |
+
---
|
| 80 |
+
🚀 [Sun Jul 6 10:29:33 AM PDT 2025] Model çalıştırılıyor...
|
| 81 |
+
|
| 82 |
+
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+
Fetching 23 files: 17%|█▋ | 4/23 [00:10<00:50, 2.64s/it]
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Fetching 23 files: 26%|██▌ | 6/23 [02:53<10:03, 35.50s/it]
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Fetching 23 files: 30%|███ | 7/23 [04:33<13:24, 50.27s/it]
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Fetching 23 files: 83%|████████▎ | 19/23 [06:46<01:16, 19.21s/it]
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Fetching 23 files: 100%|██████████| 23/23 [06:46<00:00, 17.68s/it]
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+
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Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]
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+
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+
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Loading checkpoint shards: 100%|██████████| 2/2 [00:00<00:00, 34.67it/s]
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+
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Loading checkpoint shards: 100%|██████████| 3/3 [00:00<00:00, 22.04it/s]
|
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+
|
| 102 |
+
Loading pipeline components...: 29%|██▊ | 2/7 [00:00<00:00, 5.53it/s]You set `add_prefix_space`. The tokenizer needs to be converted from the slow tokenizers
|
| 103 |
+
|
| 104 |
+
Loading pipeline components...: 57%|█████▋ | 4/7 [00:00<00:00, 9.79it/s]
|
| 105 |
+
Traceback (most recent call last):
|
| 106 |
+
File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2260, in _from_pretrained
|
| 107 |
+
tokenizer = cls(*init_inputs, **init_kwargs)
|
| 108 |
+
File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/models/t5/tokenization_t5_fast.py", line 119, in __init__
|
| 109 |
+
super().__init__(
|
| 110 |
+
File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/tokenization_utils_fast.py", line 108, in __init__
|
| 111 |
+
raise ValueError(
|
| 112 |
+
ValueError: Cannot instantiate this tokenizer from a slow version. If it's based on sentencepiece, make sure you have sentencepiece installed.
|
| 113 |
+
|
| 114 |
+
During handling of the above exception, another exception occurred:
|
| 115 |
+
|
| 116 |
+
Traceback (most recent call last):
|
| 117 |
+
File "/data/projects/flux-fast-main/gen_image.py", line 27, in <module>
|
| 118 |
+
main(args)
|
| 119 |
+
File "/data/projects/flux-fast-main/gen_image.py", line 15, in main
|
| 120 |
+
pipeline = load_pipeline(args)
|
| 121 |
+
File "/data/projects/flux-fast-main/utils/pipeline_utils.py", line 410, in load_pipeline
|
| 122 |
+
pipeline = FluxPipeline.from_pretrained(
|
| 123 |
+
File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
|
| 124 |
+
return fn(*args, **kwargs)
|
| 125 |
+
File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/pipelines/pipeline_utils.py", line 1022, in from_pretrained
|
| 126 |
+
loaded_sub_model = load_sub_model(
|
| 127 |
+
File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 830, in load_sub_model
|
| 128 |
+
loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
|
| 129 |
+
File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2014, in from_pretrained
|
| 130 |
+
return cls._from_pretrained(
|
| 131 |
+
File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2261, in _from_pretrained
|
| 132 |
+
except import_protobuf_decode_error():
|
| 133 |
+
File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 87, in import_protobuf_decode_error
|
| 134 |
+
raise ImportError(PROTOBUF_IMPORT_ERROR.format(error_message))
|
| 135 |
+
ImportError:
|
| 136 |
+
requires the protobuf library but it was not found in your environment. Check out the instructions on the
|
| 137 |
+
installation page of its repo: https://github.com/protocolbuffers/protobuf/tree/master/python#installation and follow the ones
|
| 138 |
+
that match your environment. Please note that you may need to restart your runtime after installation.
|
| 139 |
+
|
| 140 |
+
🔁 [Sun Jul 6 10:40:09 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 141 |
+
💾 [Sun Jul 6 10:40:09 AM PDT 2025] Cache kontrolü yapılıyor...
|
| 142 |
+
📊 [Sun Jul 6 10:40:09 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 143 |
+
CPU Info:
|
| 144 |
+
Cores: 16, Load: 0.77
|
| 145 |
+
RAM Info:
|
| 146 |
+
total used free shared buff/cache available
|
| 147 |
+
Mem: 30Gi 5.0Gi 3.2Gi 134Mi 23Gi 25Gi
|
| 148 |
+
Swap: 23Gi 23Mi 23Gi
|
| 149 |
+
GPU Info:
|
| 150 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 5009 MiB, 59, 35 %
|
| 151 |
+
---
|
| 152 |
+
🔍 [Sun Jul 6 10:40:09 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 153 |
+
🔥 [Sun Jul 6 10:40:11 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 154 |
+
CUDA Available: True
|
| 155 |
+
GPU Count: 1
|
| 156 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 157 |
+
GPU Memory: 5.6 GB
|
| 158 |
+
GPU warm-up tamamlandı
|
| 159 |
+
🚀 [Sun Jul 6 10:40:13 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 160 |
+
[10:40:16] Traceback (most recent call last):
|
| 161 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 2154, in __getattr__
|
| 162 |
+
[10:40:16] module = self._get_module(self._class_to_module[name])
|
| 163 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 2184, in _get_module
|
| 164 |
+
[10:40:16] raise e
|
| 165 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 2182, in _get_module
|
| 166 |
+
[10:40:16] return importlib.import_module("." + module_name, self.__name__)
|
| 167 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/lib/python3.10/importlib/__init__.py", line 126, in import_module
|
| 168 |
+
[10:40:16] return _bootstrap._gcd_import(name[level:], package, level)
|
| 169 |
+
[10:40:16] File "<frozen importlib._bootstrap>", line 1050, in _gcd_import
|
| 170 |
+
[10:40:16] File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
|
| 171 |
+
[10:40:16] File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
|
| 172 |
+
[10:40:16] File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
|
| 173 |
+
[10:40:16] File "<frozen importlib._bootstrap_external>", line 883, in exec_module
|
| 174 |
+
[10:40:16] File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
|
| 175 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/models/clip/image_processing_clip.py", line 21, in <module>
|
| 176 |
+
[10:40:16] from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
|
| 177 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/image_processing_utils.py", line 22, in <module>
|
| 178 |
+
[10:40:16] from .image_transforms import center_crop, normalize, rescale
|
| 179 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/image_transforms.py", line 22, in <module>
|
| 180 |
+
[10:40:16] from .image_utils import (
|
| 181 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/image_utils.py", line 59, in <module>
|
| 182 |
+
[10:40:16] from torchvision.transforms import InterpolationMode
|
| 183 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torchvision/__init__.py", line 10, in <module>
|
| 184 |
+
[10:40:16] from torchvision import _meta_registrations, datasets, io, models, ops, transforms, utils # usort:skip
|
| 185 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torchvision/_meta_registrations.py", line 164, in <module>
|
| 186 |
+
[10:40:16] def meta_nms(dets, scores, iou_threshold):
|
| 187 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/library.py", line 1023, in register
|
| 188 |
+
[10:40:16] use_lib._register_fake(op_name, func, _stacklevel=stacklevel + 1)
|
| 189 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/library.py", line 214, in _register_fake
|
| 190 |
+
[10:40:16] handle = entry.fake_impl.register(func_to_register, source)
|
| 191 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/_library/fake_impl.py", line 31, in register
|
| 192 |
+
[10:40:16] if torch._C._dispatch_has_kernel_for_dispatch_key(self.qualname, "Meta"):
|
| 193 |
+
[10:40:16] RuntimeError: operator torchvision::nms does not exist
|
| 194 |
+
[10:40:16]
|
| 195 |
+
[10:40:16] The above exception was the direct cause of the following exception:
|
| 196 |
+
[10:40:16]
|
| 197 |
+
[10:40:16] Traceback (most recent call last):
|
| 198 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/utils/import_utils.py", line 883, in _get_module
|
| 199 |
+
[10:40:16] return importlib.import_module("." + module_name, self.__name__)
|
| 200 |
+
[10:40:16] File "/home/asahiner/.pyenv/versions/3.10.13/lib/python3.10/importlib/__init__.py", line 126, in import_module
|
| 201 |
+
[10:40:16] return _bootstrap._gcd_import(name[level:], package, level)
|
| 202 |
+
[10:40:16] File "<frozen importlib._bootstrap>", line 1050, in _gcd_import
|
| 203 |
+
[10:40:16] File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
|
| 204 |
+
[10:40:16] File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
|
| 205 |
+
[10:40:17] File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
|
| 206 |
+
[10:40:17] File "<frozen importlib._bootstrap_external>", line 883, in exec_module
|
| 207 |
+
[10:40:17] File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
|
| 208 |
+
[10:40:17] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/pipelines/flux/pipeline_flux.py", line 20, in <module>
|
| 209 |
+
[10:40:17] from transformers import (
|
| 210 |
+
[10:40:17] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 2157, in __getattr__
|
| 211 |
+
[10:40:17] raise ModuleNotFoundError(
|
| 212 |
+
[10:40:17] ModuleNotFoundError: Could not import module 'CLIPImageProcessor'. Are this object's requirements defined correctly?
|
| 213 |
+
[10:40:17]
|
| 214 |
+
[10:40:17] The above exception was the direct cause of the following exception:
|
| 215 |
+
[10:40:17]
|
| 216 |
+
[10:40:17] Traceback (most recent call last):
|
| 217 |
+
[10:40:17] File "/data/projects/flux-fast-main/gen_image.py", line 6, in <module>
|
| 218 |
+
[10:40:17] from utils.pipeline_utils import load_pipeline # noqa: E402
|
| 219 |
+
[10:40:17] File "/data/projects/flux-fast-main/utils/pipeline_utils.py", line 5, in <module>
|
| 220 |
+
[10:40:17] from diffusers import FluxPipeline
|
| 221 |
+
[10:40:17] File "<frozen importlib._bootstrap>", line 1075, in _handle_fromlist
|
| 222 |
+
[10:40:17] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/utils/import_utils.py", line 874, in __getattr__
|
| 223 |
+
[10:40:17] value = getattr(module, name)
|
| 224 |
+
[10:40:17] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/utils/import_utils.py", line 874, in __getattr__
|
| 225 |
+
[10:40:17] value = getattr(module, name)
|
| 226 |
+
[10:40:17] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/utils/import_utils.py", line 873, in __getattr__
|
| 227 |
+
[10:40:17] module = self._get_module(self._class_to_module[name])
|
| 228 |
+
[10:40:17] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/utils/import_utils.py", line 885, in _get_module
|
| 229 |
+
[10:40:17] raise RuntimeError(
|
| 230 |
+
[10:40:17] RuntimeError: Failed to import diffusers.pipelines.flux.pipeline_flux because of the following error (look up to see its traceback):
|
| 231 |
+
[10:40:17] Could not import module 'CLIPImageProcessor'. Are this object's requirements defined correctly?
|
| 232 |
+
🔁 [Sun Jul 6 10:45:07 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 233 |
+
💾 [Sun Jul 6 10:45:07 AM PDT 2025] Cache kontrolü yapılıyor...
|
| 234 |
+
📊 [Sun Jul 6 10:45:07 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 235 |
+
CPU Info:
|
| 236 |
+
Cores: 16, Load: 0.90
|
| 237 |
+
RAM Info:
|
| 238 |
+
total used free shared buff/cache available
|
| 239 |
+
Mem: 30Gi 4.9Gi 3.0Gi 154Mi 23Gi 25Gi
|
| 240 |
+
Swap: 23Gi 22Mi 23Gi
|
| 241 |
+
GPU Info:
|
| 242 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4935 MiB, 62, 57 %
|
| 243 |
+
---
|
| 244 |
+
🔍 [Sun Jul 6 10:45:07 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 245 |
+
🔥 [Sun Jul 6 10:45:09 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 246 |
+
CUDA Available: True
|
| 247 |
+
GPU Count: 1
|
| 248 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 249 |
+
GPU Memory: 5.6 GB
|
| 250 |
+
GPU warm-up tamamlandı
|
| 251 |
+
🚀 [Sun Jul 6 10:45:11 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 252 |
+
[10:46:23]
|
| 253 |
+
[10:46:24]
|
| 254 |
+
🔁 [Sun Jul 6 10:59:42 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 255 |
+
💾 [Sun Jul 6 10:59:42 AM PDT 2025] Cache kontrolü yapılıyor...
|
| 256 |
+
📊 [Sun Jul 6 10:59:42 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 257 |
+
CPU Info:
|
| 258 |
+
Cores: 16, Load: 1.64
|
| 259 |
+
RAM Info:
|
| 260 |
+
total used free shared buff/cache available
|
| 261 |
+
Mem: 30Gi 5.0Gi 4.7Gi 161Mi 21Gi 25Gi
|
| 262 |
+
Swap: 23Gi 22Mi 23Gi
|
| 263 |
+
GPU Info:
|
| 264 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 5009 MiB, 58, 6 %
|
| 265 |
+
---
|
| 266 |
+
🔍 [Sun Jul 6 10:59:42 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 267 |
+
🔥 [Sun Jul 6 10:59:43 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 268 |
+
CUDA Available: True
|
| 269 |
+
GPU Count: 1
|
| 270 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 271 |
+
GPU Memory: 5.6 GB
|
| 272 |
+
GPU warm-up tamamlandı
|
| 273 |
+
🚀 [Sun Jul 6 10:59:46 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 274 |
+
[10:59:50] Traceback (most recent call last):
|
| 275 |
+
[10:59:50] File "/data/projects/flux-fast-main/gen_image.py", line 12, in <module>
|
| 276 |
+
[10:59:50] torch.backends.openmp.set_num_threads(16)
|
| 277 |
+
[10:59:50] AttributeError: module 'torch.backends.openmp' has no attribute 'set_num_threads'
|
| 278 |
+
🔁 [Sun Jul 6 11:01:33 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 279 |
+
💾 [Sun Jul 6 11:01:33 AM PDT 2025] Cache kontrolü yapılıyor...
|
| 280 |
+
📊 [Sun Jul 6 11:01:33 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 281 |
+
CPU Info:
|
| 282 |
+
Cores: 16, Load: 1.65
|
| 283 |
+
RAM Info:
|
| 284 |
+
total used free shared buff/cache available
|
| 285 |
+
Mem: 30Gi 5.1Gi 4.6Gi 161Mi 21Gi 25Gi
|
| 286 |
+
Swap: 23Gi 22Mi 23Gi
|
| 287 |
+
GPU Info:
|
| 288 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4959 MiB, 54, 15 %
|
| 289 |
+
---
|
| 290 |
+
🔍 [Sun Jul 6 11:01:33 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 291 |
+
🔥 [Sun Jul 6 11:01:34 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 292 |
+
CUDA Available: True
|
| 293 |
+
GPU Count: 1
|
| 294 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 295 |
+
GPU Memory: 5.6 GB
|
| 296 |
+
GPU warm-up tamamlandı
|
| 297 |
+
🚀 [Sun Jul 6 11:01:36 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 298 |
+
[11:01:44]
|
| 299 |
+
🔁 [Sun Jul 6 11:08:51 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 300 |
+
💾 [Sun Jul 6 11:08:51 AM PDT 2025] Cache kontrolü yapılıyor...
|
| 301 |
+
📊 [Sun Jul 6 11:08:51 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 302 |
+
CPU Info:
|
| 303 |
+
Cores: 16, Load: 1.96
|
| 304 |
+
RAM Info:
|
| 305 |
+
total used free shared buff/cache available
|
| 306 |
+
Mem: 30Gi 5.9Gi 3.7Gi 161Mi 21Gi 24Gi
|
| 307 |
+
Swap: 23Gi 22Mi 23Gi
|
| 308 |
+
GPU Info:
|
| 309 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4901 MiB, 61, 48 %
|
| 310 |
+
---
|
| 311 |
+
🔍 [Sun Jul 6 11:08:51 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 312 |
+
🔥 [Sun Jul 6 11:08:53 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 313 |
+
CUDA Available: True
|
| 314 |
+
GPU Count: 1
|
| 315 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 316 |
+
GPU Memory: 5.6 GB
|
| 317 |
+
GPU warm-up tamamlandı
|
| 318 |
+
🚀 [Sun Jul 6 11:08:55 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 319 |
+
[11:09:00] 🎯 Başlatılıyor: An astronaut standing next to a giant lemon
|
| 320 |
+
[11:09:00] 📁 Çıktı: lemon.png
|
| 321 |
+
[11:09:00] 🔧 Device: cuda, Steps: 4
|
| 322 |
+
[11:09:00] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 323 |
+
[11:09:02]
|
| 324 |
+
[11:09:04] 🚀 GPU'ya aktarılıyor (cuda)
|
| 325 |
+
[11:09:04] ✅ Pipeline yüklendi (6.7s)
|
| 326 |
+
[11:09:04] 🎨 Görüntü oluşturuluyor...
|
| 327 |
+
[11:09:04]
|
| 328 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 329 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 330 |
+
[11:09:04] Traceback (most recent call last):
|
| 331 |
+
[11:09:04] File "/data/projects/flux-fast-main/gen_image_stable.py", line 81, in <module>
|
| 332 |
+
[11:09:04] main(args)
|
| 333 |
+
[11:09:04] File "/data/projects/flux-fast-main/gen_image_stable.py", line 61, in main
|
| 334 |
+
[11:09:04] image = pipeline(
|
| 335 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
|
| 336 |
+
[11:09:04] return func(*args, **kwargs)
|
| 337 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py", line 1040, in __call__
|
| 338 |
+
[11:09:04] noise_pred = self.unet(
|
| 339 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 340 |
+
[11:09:04] return self._call_impl(*args, **kwargs)
|
| 341 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 342 |
+
[11:09:04] return forward_call(*args, **kwargs)
|
| 343 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/unets/unet_2d_condition.py", line 1214, in forward
|
| 344 |
+
[11:09:04] sample, res_samples = downsample_block(
|
| 345 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 346 |
+
[11:09:04] return self._call_impl(*args, **kwargs)
|
| 347 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 348 |
+
[11:09:04] return forward_call(*args, **kwargs)
|
| 349 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/unets/unet_2d_blocks.py", line 1270, in forward
|
| 350 |
+
[11:09:04] hidden_states = attn(
|
| 351 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 352 |
+
[11:09:04] return self._call_impl(*args, **kwargs)
|
| 353 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 354 |
+
[11:09:04] return forward_call(*args, **kwargs)
|
| 355 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/transformers/transformer_2d.py", line 427, in forward
|
| 356 |
+
[11:09:04] hidden_states = block(
|
| 357 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 358 |
+
[11:09:04] return self._call_impl(*args, **kwargs)
|
| 359 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 360 |
+
[11:09:04] return forward_call(*args, **kwargs)
|
| 361 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/attention.py", line 514, in forward
|
| 362 |
+
[11:09:04] attn_output = self.attn1(
|
| 363 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 364 |
+
[11:09:04] return self._call_impl(*args, **kwargs)
|
| 365 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 366 |
+
[11:09:04] return forward_call(*args, **kwargs)
|
| 367 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/attention_processor.py", line 605, in forward
|
| 368 |
+
[11:09:04] return self.processor(
|
| 369 |
+
[11:09:04] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/attention_processor.py", line 3317, in __call__
|
| 370 |
+
[11:09:04] hidden_states = F.scaled_dot_product_attention(
|
| 371 |
+
[11:09:04] torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU 0 has a total capacity of 5.60 GiB of which 30.50 MiB is free. Including non-PyTorch memory, this process has 4.79 GiB memory in use. Of the allocated memory 4.67 GiB is allocated by PyTorch, and 13.65 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
|
| 372 |
+
🔁 [Sun Jul 6 11:09:38 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 373 |
+
💾 [Sun Jul 6 11:09:38 AM PDT 2025] Cache kontrolü yapılıyor...
|
| 374 |
+
📊 [Sun Jul 6 11:09:38 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 375 |
+
CPU Info:
|
| 376 |
+
Cores: 16, Load: 1.93
|
| 377 |
+
RAM Info:
|
| 378 |
+
total used free shared buff/cache available
|
| 379 |
+
Mem: 30Gi 5.2Gi 4.5Gi 159Mi 21Gi 25Gi
|
| 380 |
+
Swap: 23Gi 22Mi 23Gi
|
| 381 |
+
GPU Info:
|
| 382 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4926 MiB, 55, 18 %
|
| 383 |
+
---
|
| 384 |
+
🔍 [Sun Jul 6 11:09:38 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 385 |
+
🔥 [Sun Jul 6 11:09:39 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 386 |
+
CUDA Available: True
|
| 387 |
+
GPU Count: 1
|
| 388 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 389 |
+
GPU Memory: 5.6 GB
|
| 390 |
+
GPU warm-up tamamlandı
|
| 391 |
+
🚀 [Sun Jul 6 11:09:41 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 392 |
+
[11:09:46] 🎯 Başlatılıyor: An astronaut standing next to a giant lemon
|
| 393 |
+
[11:09:46] 📁 Çıktı: lemon.png
|
| 394 |
+
[11:09:46] 🔧 Device: cuda, Steps: 4
|
| 395 |
+
[11:09:46] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 396 |
+
[11:09:49]
|
| 397 |
+
[11:09:51] 🚀 GPU'ya aktarılıyor (cuda)
|
| 398 |
+
[11:09:51] ✅ Pipeline yüklendi (7.5s)
|
| 399 |
+
[11:09:51] 🎨 Görüntü oluşturuluyor...
|
| 400 |
+
[11:09:51]
|
| 401 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 402 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 403 |
+
[11:09:51] Traceback (most recent call last):
|
| 404 |
+
[11:09:51] File "/data/projects/flux-fast-main/gen_image_stable.py", line 81, in <module>
|
| 405 |
+
[11:09:51] main(args)
|
| 406 |
+
[11:09:51] File "/data/projects/flux-fast-main/gen_image_stable.py", line 61, in main
|
| 407 |
+
[11:09:51] image = pipeline(
|
| 408 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
|
| 409 |
+
[11:09:51] return func(*args, **kwargs)
|
| 410 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py", line 1040, in __call__
|
| 411 |
+
[11:09:51] noise_pred = self.unet(
|
| 412 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 413 |
+
[11:09:51] return self._call_impl(*args, **kwargs)
|
| 414 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 415 |
+
[11:09:51] return forward_call(*args, **kwargs)
|
| 416 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/unets/unet_2d_condition.py", line 1214, in forward
|
| 417 |
+
[11:09:51] sample, res_samples = downsample_block(
|
| 418 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 419 |
+
[11:09:51] return self._call_impl(*args, **kwargs)
|
| 420 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 421 |
+
[11:09:51] return forward_call(*args, **kwargs)
|
| 422 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/unets/unet_2d_blocks.py", line 1270, in forward
|
| 423 |
+
[11:09:51] hidden_states = attn(
|
| 424 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 425 |
+
[11:09:51] return self._call_impl(*args, **kwargs)
|
| 426 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 427 |
+
[11:09:51] return forward_call(*args, **kwargs)
|
| 428 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/transformers/transformer_2d.py", line 427, in forward
|
| 429 |
+
[11:09:51] hidden_states = block(
|
| 430 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 431 |
+
[11:09:51] return self._call_impl(*args, **kwargs)
|
| 432 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 433 |
+
[11:09:51] return forward_call(*args, **kwargs)
|
| 434 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/attention.py", line 514, in forward
|
| 435 |
+
[11:09:51] attn_output = self.attn1(
|
| 436 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
|
| 437 |
+
[11:09:51] return self._call_impl(*args, **kwargs)
|
| 438 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
|
| 439 |
+
[11:09:51] return forward_call(*args, **kwargs)
|
| 440 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/attention_processor.py", line 605, in forward
|
| 441 |
+
[11:09:51] return self.processor(
|
| 442 |
+
[11:09:51] File "/home/asahiner/.pyenv/versions/3.10.13/envs/flux-env/lib/python3.10/site-packages/diffusers/models/attention_processor.py", line 3317, in __call__
|
| 443 |
+
[11:09:51] hidden_states = F.scaled_dot_product_attention(
|
| 444 |
+
[11:09:51] torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1024.00 MiB. GPU 0 has a total capacity of 5.60 GiB of which 1017.31 MiB is free. Including non-PyTorch memory, this process has 3.79 GiB memory in use. Of the allocated memory 3.67 GiB is allocated by PyTorch, and 17.65 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
|
| 445 |
+
🔁 [Sun Jul 6 11:11:14 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 446 |
+
💾 [Sun Jul 6 11:11:14 AM PDT 2025] Cache kontrolü yapılıyor...
|
| 447 |
+
📊 [Sun Jul 6 11:11:14 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 448 |
+
CPU Info:
|
| 449 |
+
Cores: 16, Load: 1.91
|
| 450 |
+
RAM Info:
|
| 451 |
+
total used free shared buff/cache available
|
| 452 |
+
Mem: 30Gi 5.2Gi 4.4Gi 159Mi 21Gi 25Gi
|
| 453 |
+
Swap: 23Gi 22Mi 23Gi
|
| 454 |
+
GPU Info:
|
| 455 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4908 MiB, 59, 3 %
|
| 456 |
+
---
|
| 457 |
+
🔍 [Sun Jul 6 11:11:14 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 458 |
+
🔥 [Sun Jul 6 11:11:16 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 459 |
+
CUDA Available: True
|
| 460 |
+
GPU Count: 1
|
| 461 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 462 |
+
GPU Memory: 5.6 GB
|
| 463 |
+
GPU warm-up tamamlandı
|
| 464 |
+
🚀 [Sun Jul 6 11:11:18 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 465 |
+
[11:11:23] 🎯 Başlatılıyor: An astronaut standing next to a giant lemon
|
| 466 |
+
[11:11:23] 📁 Çıktı: lemon.png
|
| 467 |
+
[11:11:23] 🔧 Device: cuda, Steps: 4
|
| 468 |
+
[11:11:23] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 469 |
+
[11:11:25]
|
| 470 |
+
[11:11:26] 🚀 GPU'ya aktarılıyor (cuda)
|
| 471 |
+
[11:11:26] ✅ Pipeline yüklendi (7.0s)
|
| 472 |
+
[11:11:26] 🎨 Görüntü oluşturuluyor...
|
| 473 |
+
[11:11:29]
|
| 474 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 475 |
25%|██▌ | 1/4 [00:00<00:02, 1.02it/s]
|
| 476 |
50%|█████ | 2/4 [00:01<00:01, 1.45it/s]
|
| 477 |
75%|███████▌ | 3/4 [00:01<00:00, 1.74it/s]
|
| 478 |
+
[11:11:29] ✅ Görüntü oluşturuldu (3.2s)
|
| 479 |
+
[11:11:29] 💾 Kaydedildi: lemon.png
|
| 480 |
+
[11:11:29] ⏱️ Toplam süre: 10.2s
|
| 481 |
+
📊 [Sun Jul 6 11:11:30 AM PDT 2025] İşlem sonrası detaylı analiz:
|
| 482 |
+
GPU Status:
|
| 483 |
+
837, 6144, 48, 63, 50.95
|
| 484 |
+
CPU Status:
|
| 485 |
+
%Cpu(s): 2.2 us, 1.7 sy, 0.0 ni, 96.1 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
|
| 486 |
+
Memory Status:
|
| 487 |
+
total used free shared buff/cache available
|
| 488 |
+
Mem: 30Gi 5.3Gi 4.3Gi 162Mi 21Gi 25Gi
|
| 489 |
+
Swap: 23Gi 22Mi 23Gi
|
| 490 |
+
Process Info:
|
| 491 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 492 |
+
asahiner 16810 50.0 0.0 0 0 ? Z 11:11 0:00 [git] <defunct>
|
| 493 |
+
asahiner 2706 27.5 1.4 1468216440 459156 ? Rl 10:28 11:54 /opt/visual-studio-code/code --type=zygote
|
| 494 |
+
asahiner 2670 11.5 0.9 34356576 317924 ? Sl 10:28 5:00 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 495 |
+
asahiner 1794 5.5 1.0 2127284 353472 ? Ssl 10:27 2:27 /usr/bin/kwin_x11 --replace
|
| 496 |
+
✅ [Sun Jul 6 11:11:30 AM PDT 2025] BAŞARILI: lemon.png oluşturuldu! Süre: 16s
|
| 497 |
+
📁 Dosya boyutu: 308K
|
| 498 |
+
🧹 [Sun Jul 6 11:11:30 AM PDT 2025] Cache temizleniyor...
|
| 499 |
+
🏁 [Sun Jul 6 11:11:31 AM PDT 2025] İşlem tamamlandı. Toplam süre: 16s
|
| 500 |
+
🔁 [Sun Jul 6 11:54:25 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 501 |
+
💾 [Sun Jul 6 11:54:25 AM PDT 2025] Cache kontrolü yapılıyor...
|
| 502 |
+
⚠️ Mevcut çıktı dosyası bulundu, siliniyor...
|
| 503 |
+
📊 [Sun Jul 6 11:54:25 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 504 |
+
CPU Info:
|
| 505 |
+
Cores: 16, Load: 4.58
|
| 506 |
+
RAM Info:
|
| 507 |
+
total used free shared buff/cache available
|
| 508 |
+
Mem: 30Gi 4.0Gi 26Gi 65Mi 1.1Gi 26Gi
|
| 509 |
+
Swap: 23Gi 2.0Gi 21Gi
|
| 510 |
+
GPU Info:
|
| 511 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 5051 MiB, 54, 5 %
|
| 512 |
+
---
|
| 513 |
+
🔍 [Sun Jul 6 11:54:25 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 514 |
+
🔥 [Sun Jul 6 11:54:27 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 515 |
+
CUDA Available: True
|
| 516 |
+
GPU Count: 1
|
| 517 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 518 |
+
GPU Memory: 5.6 GB
|
| 519 |
+
GPU warm-up tamamlandı
|
| 520 |
+
🚀 [Sun Jul 6 11:54:29 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 521 |
+
[11:54:35] 🎯 Başlatılıyor: An astronaut standing next to a giant peach at moon
|
| 522 |
+
[11:54:35] 📁 Çıktı: peach.png
|
| 523 |
+
[11:54:35] 🔧 Device: cuda, Steps: 4
|
| 524 |
+
[11:54:35] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 525 |
+
[11:54:38]
|
| 526 |
+
[11:54:39] 🚀 GPU'ya aktarılıyor (cuda)
|
| 527 |
+
[11:54:39] ✅ Pipeline yüklendi (8.3s)
|
| 528 |
+
[11:54:39] 🎨 Görüntü oluşturuluyor...
|
| 529 |
+
[11:54:41]
|
| 530 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 531 |
25%|██▌ | 1/4 [00:00<00:02, 1.11it/s]
|
| 532 |
50%|█████ | 2/4 [00:01<00:01, 1.60it/s]
|
| 533 |
75%|███████▌ | 3/4 [00:01<00:00, 1.87it/s]
|
| 534 |
+
[11:54:42] ✅ Görüntü oluşturuldu (3.0s)
|
| 535 |
+
[11:54:42] 💾 Kaydedildi: peach.png
|
| 536 |
+
[11:54:42] ⏱️ Toplam süre: 11.3s
|
| 537 |
+
📊 [Sun Jul 6 11:54:43 AM PDT 2025] İşlem sonrası detaylı analiz:
|
| 538 |
+
GPU Status:
|
| 539 |
+
721, 6144, 98, 59, 43.57
|
| 540 |
+
CPU Status:
|
| 541 |
+
%Cpu(s): 1.1 us, 0.6 sy, 0.0 ni, 98.3 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
|
| 542 |
+
Memory Status:
|
| 543 |
+
total used free shared buff/cache available
|
| 544 |
+
Mem: 30Gi 3.5Gi 21Gi 64Mi 6.7Gi 27Gi
|
| 545 |
+
Swap: 23Gi 2.0Gi 21Gi
|
| 546 |
+
Process Info:
|
| 547 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 548 |
+
asahiner 2706 25.6 1.1 1473361400 355036 ? Rl 10:28 22:10 /opt/visual-studio-code/code --type=zygote
|
| 549 |
+
asahiner 2670 8.6 0.3 34356708 121400 ? Sl 10:28 7:27 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 550 |
+
asahiner 1794 4.4 0.5 2162520 186140 ? Ssl 10:27 3:52 /usr/bin/kwin_x11 --replace
|
| 551 |
+
asahiner 1686 4.4 0.3 26621312 122172 tty2 Sl+ 10:27 3:50 /usr/lib/Xorg :0 vt2
|
| 552 |
+
✅ [Sun Jul 6 11:54:43 AM PDT 2025] BAŞARILI: lemon.png oluşturuldu! Süre: 18s
|
| 553 |
+
🧹 [Sun Jul 6 11:54:43 AM PDT 2025] Cache temizleniyor...
|
| 554 |
+
🏁 [Sun Jul 6 11:54:43 AM PDT 2025] İşlem tamamlandı. Toplam süre: 18s
|
| 555 |
+
🔁 [Sun Jul 6 11:59:28 AM PDT 2025] 🟡 Optimized başlatılıyor
|
| 556 |
+
💾 [Sun Jul 6 11:59:28 AM PDT 2025] Benzersiz dosya adı oluşturuldu: peach_20250706_115928.png
|
| 557 |
+
📊 [Sun Jul 6 11:59:28 AM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 558 |
+
CPU Info:
|
| 559 |
+
Cores: 16, Load: 3.53
|
| 560 |
+
RAM Info:
|
| 561 |
+
total used free shared buff/cache available
|
| 562 |
+
Mem: 30Gi 4.0Gi 20Gi 64Mi 6.7Gi 26Gi
|
| 563 |
+
Swap: 23Gi 2.0Gi 21Gi
|
| 564 |
+
GPU Info:
|
| 565 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 5004 MiB, 54, 3 %
|
| 566 |
+
---
|
| 567 |
+
🔍 [Sun Jul 6 11:59:28 AM PDT 2025] PyTorch kurulum kontrolü...
|
| 568 |
+
🔥 [Sun Jul 6 11:59:29 AM PDT 2025] GPU warm-up başlatılıyor...
|
| 569 |
+
CUDA Available: True
|
| 570 |
+
GPU Count: 1
|
| 571 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 572 |
+
GPU Memory: 5.6 GB
|
| 573 |
+
GPU warm-up tamamlandı
|
| 574 |
+
🚀 [Sun Jul 6 11:59:32 AM PDT 2025] Optimized komut çalıştırılıyor...
|
| 575 |
+
[11:59:37] 🎯 Başlatılıyor: An astronaut standing next to a giant peach at moon
|
| 576 |
+
[11:59:37] 📁 Çıktı: peach_20250706_115928.png
|
| 577 |
+
[11:59:37] 🔧 Device: cuda, Steps: 4
|
| 578 |
+
[11:59:37] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 579 |
+
[11:59:39]
|
| 580 |
+
[11:59:41] 🚀 GPU'ya aktarılıyor (cuda)
|
| 581 |
+
[11:59:41] ✅ Pipeline yüklendi (7.8s)
|
| 582 |
+
[11:59:41] 🎨 Görüntü oluşturuluyor...
|
| 583 |
+
[11:59:43]
|
| 584 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 585 |
25%|██▌ | 1/4 [00:01<00:03, 1.01s/it]
|
| 586 |
50%|█████ | 2/4 [00:01<00:01, 1.43it/s]
|
| 587 |
75%|███████▌ | 3/4 [00:01<00:00, 1.72it/s]
|
| 588 |
+
[11:59:44] ✅ Görüntü oluşturuldu (3.2s)
|
| 589 |
+
[11:59:44] 💾 Kaydedildi: peach_20250706_115928.png
|
| 590 |
+
[11:59:44] ⏱️ Toplam süre: 11.0s
|
| 591 |
+
📊 [Sun Jul 6 11:59:45 AM PDT 2025] İşlem sonrası detaylı analiz:
|
| 592 |
+
GPU Status:
|
| 593 |
+
727, 6144, 99, 59, 49.48
|
| 594 |
+
CPU Status:
|
| 595 |
+
%Cpu(s): 2.3 us, 2.3 sy, 0.0 ni, 95.4 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
|
| 596 |
+
Memory Status:
|
| 597 |
+
total used free shared buff/cache available
|
| 598 |
+
Mem: 30Gi 4.2Gi 20Gi 65Mi 6.9Gi 26Gi
|
| 599 |
+
Swap: 23Gi 2.0Gi 21Gi
|
| 600 |
+
Process Info:
|
| 601 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 602 |
+
asahiner 2706 25.9 2.1 1473361400 709176 ? Rl 10:28 23:42 /opt/visual-studio-code/code --type=zygote
|
| 603 |
+
asahiner 2670 8.6 0.3 34356708 126216 ? Sl 10:28 7:52 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 604 |
+
asahiner 22083 8.4 0.4 765068 141240 ? SNl 11:59 0:00 /usr/lib/kf6/kioworker /usr/lib/qt6/plugins/kf6/kio/thumbnail.so thumbnail local:/run/user/1000/dolphinZgRTKF.29.kioworker.socket
|
| 605 |
+
asahiner 1686 4.4 0.3 26621832 124196 tty2 Sl+ 10:27 4:04 /usr/lib/Xorg :0 vt2
|
| 606 |
+
✅ [Sun Jul 6 11:59:45 AM PDT 2025] BAŞARILI: peach_20250706_115928.png oluşturuldu! Süre: 17s
|
| 607 |
+
📁 Dosya boyutu: 308K
|
| 608 |
+
🧹 [Sun Jul 6 11:59:45 AM PDT 2025] Cache temizleniyor...
|
| 609 |
+
🏁 [Sun Jul 6 11:59:45 AM PDT 2025] İşlem tamamlandı. Toplam süre: 17s
|
| 610 |
+
🔁 [Sun Jul 6 12:04:09 PM PDT 2025] 🟡 Optimized başlatılıyor
|
| 611 |
+
💾 [Sun Jul 6 12:04:09 PM PDT 2025] Benzersiz dosya adı oluşturuldu: peach_20250706_120409.png
|
| 612 |
+
📊 [Sun Jul 6 12:04:09 PM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 613 |
+
CPU Info:
|
| 614 |
+
Cores: 16, Load: 3.00
|
| 615 |
+
RAM Info:
|
| 616 |
+
total used free shared buff/cache available
|
| 617 |
+
Mem: 30Gi 4.3Gi 19Gi 82Mi 7.0Gi 26Gi
|
| 618 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 619 |
+
GPU Info:
|
| 620 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 5017 MiB, 65, 66 %
|
| 621 |
+
---
|
| 622 |
+
🔍 [Sun Jul 6 12:04:09 PM PDT 2025] PyTorch kurulum kontrolü...
|
| 623 |
+
🔥 [Sun Jul 6 12:04:11 PM PDT 2025] GPU warm-up başlatılıyor...
|
| 624 |
+
CUDA Available: True
|
| 625 |
+
GPU Count: 1
|
| 626 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 627 |
+
GPU Memory: 5.6 GB
|
| 628 |
+
GPU warm-up tamamlandı
|
| 629 |
+
🚀 [Sun Jul 6 12:04:13 PM PDT 2025] Optimized komut çalıştırılıyor...
|
| 630 |
+
[12:04:18] 🎯 Başlatılıyor: A mystical dragon made of aurora lights flying over a crystal mountain range under starry sky
|
| 631 |
+
[12:04:18] 📁 Çıktı: peach_20250706_120409.png
|
| 632 |
+
[12:04:18] 🔧 Device: cuda, Steps: 4
|
| 633 |
+
[12:04:18] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 634 |
+
[12:04:20]
|
| 635 |
+
[12:04:21] 🚀 GPU'ya aktarılıyor (cuda)
|
| 636 |
+
[12:04:21] ✅ Pipeline yüklendi (7.0s)
|
| 637 |
+
[12:04:21] 🎨 Görüntü oluşturuluyor...
|
| 638 |
+
[12:04:24]
|
| 639 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 640 |
25%|██▌ | 1/4 [00:00<00:02, 1.11it/s]
|
| 641 |
50%|█████ | 2/4 [00:01<00:01, 1.59it/s]
|
| 642 |
75%|███████▌ | 3/4 [00:01<00:00, 1.85it/s]
|
| 643 |
+
[12:04:24] Potential NSFW content was detected in one or more images. A black image will be returned instead. Try again with a different prompt and/or seed.
|
| 644 |
+
[12:04:24] ✅ Görüntü oluşturuldu (3.0s)
|
| 645 |
+
[12:04:24] 💾 Kaydedildi: peach_20250706_120409.png
|
| 646 |
+
[12:04:24] ⏱️ Toplam süre: 10.0s
|
| 647 |
+
📊 [Sun Jul 6 12:04:25 PM PDT 2025] İşlem sonrası detaylı analiz:
|
| 648 |
+
GPU Status:
|
| 649 |
+
728, 6144, 42, 66, 44.63
|
| 650 |
+
CPU Status:
|
| 651 |
+
%Cpu(s): 2.9 us, 5.7 sy, 2.3 ni, 87.9 id, 0.6 wa, 0.0 hi, 0.6 si, 0.0 st
|
| 652 |
+
Memory Status:
|
| 653 |
+
total used free shared buff/cache available
|
| 654 |
+
Mem: 30Gi 4.9Gi 19Gi 82Mi 7.0Gi 25Gi
|
| 655 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 656 |
+
Process Info:
|
| 657 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 658 |
+
asahiner 22791 54.2 0.4 690356 145884 ? SNl 12:04 0:00 /usr/lib/kf6/kioworker /usr/lib/qt6/plugins/kf6/kio/thumbnail.so thumbnail local:/run/user/1000/dolphintoPzSF.30.kioworker.socket
|
| 659 |
+
asahiner 2706 26.0 2.7 1473357556 897176 ? Rl 10:28 25:05 /opt/visual-studio-code/code --type=zygote
|
| 660 |
+
asahiner 2670 8.7 0.4 34356964 137272 ? Sl 10:28 8:22 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 661 |
+
asahiner 1794 4.4 0.6 2147116 201232 ? Ssl 10:27 4:20 /usr/bin/kwin_x11 --replace
|
| 662 |
+
✅ [Sun Jul 6 12:04:25 PM PDT 2025] BAŞARILI: peach_20250706_120409.png oluşturuldu! Süre: 16s
|
| 663 |
+
📁 Dosya boyutu: 4.0K
|
| 664 |
+
🧹 [Sun Jul 6 12:04:25 PM PDT 2025] Cache temizleniyor...
|
| 665 |
+
🏁 [Sun Jul 6 12:04:25 PM PDT 2025] İşlem tamamlandı. Toplam süre: 16s
|
| 666 |
+
🔁 [Sun Jul 6 12:06:12 PM PDT 2025] 🟡 Optimized başlatılıyor
|
| 667 |
+
💾 [Sun Jul 6 12:06:12 PM PDT 2025] Benzersiz dosya adı oluşturuldu: peach_20250706_120612.png
|
| 668 |
+
📊 [Sun Jul 6 12:06:12 PM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 669 |
+
CPU Info:
|
| 670 |
+
Cores: 16, Load: 2.74
|
| 671 |
+
RAM Info:
|
| 672 |
+
total used free shared buff/cache available
|
| 673 |
+
Mem: 30Gi 4.0Gi 20Gi 86Mi 7.0Gi 26Gi
|
| 674 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 675 |
+
GPU Info:
|
| 676 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4995 MiB, 56, 11 %
|
| 677 |
+
---
|
| 678 |
+
🔍 [Sun Jul 6 12:06:12 PM PDT 2025] PyTorch kurulum kontrolü...
|
| 679 |
+
🔥 [Sun Jul 6 12:06:14 PM PDT 2025] GPU warm-up başlatılıyor...
|
| 680 |
+
CUDA Available: True
|
| 681 |
+
GPU Count: 1
|
| 682 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 683 |
+
GPU Memory: 5.6 GB
|
| 684 |
+
GPU warm-up tamamlandı
|
| 685 |
+
🚀 [Sun Jul 6 12:06:16 PM PDT 2025] Optimized komut çalıştırılıyor...
|
| 686 |
+
[12:06:21] 🎯 Başlatılıyor: A crystal waterfall falling from a floating island in the sky
|
| 687 |
+
[12:06:21] 📁 Çıktı: peach_20250706_120612.png
|
| 688 |
+
[12:06:21] 🔧 Device: cuda, Steps: 4
|
| 689 |
+
[12:06:21] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 690 |
+
[12:06:23]
|
| 691 |
+
[12:06:25] 🚀 GPU'ya aktarılıyor (cuda)
|
| 692 |
+
[12:06:25] ✅ Pipeline yüklendi (7.4s)
|
| 693 |
+
[12:06:25] 🎨 Görüntü oluşturuluyor...
|
| 694 |
+
[12:06:27]
|
| 695 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 696 |
25%|██▌ | 1/4 [00:00<00:02, 1.02it/s]
|
| 697 |
50%|█████ | 2/4 [00:01<00:01, 1.45it/s]
|
| 698 |
75%|███████▌ | 3/4 [00:01<00:00, 1.74it/s]
|
| 699 |
+
[12:06:28] ✅ Görüntü oluşturuldu (3.2s)
|
| 700 |
+
[12:06:28] 💾 Kaydedildi: peach_20250706_120612.png
|
| 701 |
+
[12:06:28] ⏱️ Toplam süre: 10.6s
|
| 702 |
+
📊 [Sun Jul 6 12:06:29 PM PDT 2025] İşlem sonrası detaylı analiz:
|
| 703 |
+
GPU Status:
|
| 704 |
+
707, 6144, 78, 62, 49.39
|
| 705 |
+
CPU Status:
|
| 706 |
+
%Cpu(s): 2.3 us, 1.1 sy, 0.0 ni, 96.6 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
|
| 707 |
+
Memory Status:
|
| 708 |
+
total used free shared buff/cache available
|
| 709 |
+
Mem: 30Gi 4.5Gi 19Gi 86Mi 7.0Gi 26Gi
|
| 710 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 711 |
+
Process Info:
|
| 712 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 713 |
+
asahiner 2706 26.1 2.5 1473361656 831036 ? Rl 10:28 25:38 /opt/visual-studio-code/code --type=zygote
|
| 714 |
+
asahiner 2670 8.6 0.4 34356964 137964 ? Sl 10:28 8:29 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 715 |
+
asahiner 1686 4.4 0.3 26621356 125188 tty2 Sl+ 10:27 4:26 /usr/lib/Xorg :0 vt2
|
| 716 |
+
asahiner 1794 4.4 0.6 2146644 216184 ? Ssl 10:27 4:26 /usr/bin/kwin_x11 --replace
|
| 717 |
+
✅ [Sun Jul 6 12:06:29 PM PDT 2025] BAŞARILI: peach_20250706_120612.png oluşturuldu! Süre: 17s
|
| 718 |
+
📁 Dosya boyutu: 320K
|
| 719 |
+
🧹 [Sun Jul 6 12:06:29 PM PDT 2025] Cache temizleniyor...
|
| 720 |
+
🏁 [Sun Jul 6 12:06:29 PM PDT 2025] İşlem tamamlandı. Toplam süre: 17s
|
| 721 |
+
🔁 [Sun Jul 6 12:07:12 PM PDT 2025] 🟡 Optimized başlatılıyor
|
| 722 |
+
💾 [Sun Jul 6 12:07:12 PM PDT 2025] Benzersiz dosya adı oluşturuldu: peach_20250706_120712.png
|
| 723 |
+
📊 [Sun Jul 6 12:07:12 PM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 724 |
+
CPU Info:
|
| 725 |
+
Cores: 16, Load: 2.61
|
| 726 |
+
RAM Info:
|
| 727 |
+
total used free shared buff/cache available
|
| 728 |
+
Mem: 30Gi 4.2Gi 20Gi 87Mi 7.0Gi 26Gi
|
| 729 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 730 |
+
GPU Info:
|
| 731 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4987 MiB, 57, 4 %
|
| 732 |
+
---
|
| 733 |
+
🔍 [Sun Jul 6 12:07:12 PM PDT 2025] PyTorch kurulum kontrolü...
|
| 734 |
+
🔥 [Sun Jul 6 12:07:13 PM PDT 2025] GPU warm-up başlatılıyor...
|
| 735 |
+
CUDA Available: True
|
| 736 |
+
GPU Count: 1
|
| 737 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 738 |
+
GPU Memory: 5.6 GB
|
| 739 |
+
GPU warm-up tamamlandı
|
| 740 |
+
🚀 [Sun Jul 6 12:07:16 PM PDT 2025] Optimized komut çalıştırılıyor...
|
| 741 |
+
[12:07:21] 🎯 Başlatılıyor: An enchanted valley with golden trees and floating lanterns
|
| 742 |
+
[12:07:21] 📁 Çıktı: peach_20250706_120712.png
|
| 743 |
+
[12:07:21] 🔧 Device: cuda, Steps: 4
|
| 744 |
+
[12:07:21] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 745 |
+
[12:07:23]
|
| 746 |
+
[12:07:24] 🚀 GPU'ya aktarılıyor (cuda)
|
| 747 |
+
[12:07:24] ✅ Pipeline yüklendi (7.2s)
|
| 748 |
+
[12:07:24] 🎨 Görüntü oluşturuluyor...
|
| 749 |
+
[12:07:27]
|
| 750 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 751 |
25%|██▌ | 1/4 [00:00<00:02, 1.05it/s]
|
| 752 |
50%|█████ | 2/4 [00:01<00:01, 1.45it/s]
|
| 753 |
75%|███████▌ | 3/4 [00:01<00:00, 1.74it/s]
|
| 754 |
+
[12:07:27] ✅ Görüntü oluşturuldu (3.1s)
|
| 755 |
+
[12:07:27] 💾 Kaydedildi: peach_20250706_120712.png
|
| 756 |
+
[12:07:27] ⏱️ Toplam süre: 10.4s
|
| 757 |
+
📊 [Sun Jul 6 12:07:28 PM PDT 2025] İşlem sonrası detaylı analiz:
|
| 758 |
+
GPU Status:
|
| 759 |
+
726, 6144, 81, 62, 50.99
|
| 760 |
+
CPU Status:
|
| 761 |
+
%Cpu(s): 2.3 us, 1.7 sy, 0.0 ni, 96.0 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
|
| 762 |
+
Memory Status:
|
| 763 |
+
total used free shared buff/cache available
|
| 764 |
+
Mem: 30Gi 4.8Gi 19Gi 91Mi 7.0Gi 25Gi
|
| 765 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 766 |
+
Process Info:
|
| 767 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 768 |
+
asahiner 2706 26.0 2.6 1473361656 846636 ? Rl 10:28 25:53 /opt/visual-studio-code/code --type=zygote
|
| 769 |
+
asahiner 2670 8.6 0.4 34360036 137992 ? Sl 10:28 8:33 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 770 |
+
asahiner 1686 4.5 0.3 26622564 126220 tty2 Sl+ 10:27 4:30 /usr/lib/Xorg :0 vt2
|
| 771 |
+
asahiner 1794 4.4 0.7 2162772 227692 ? Ssl 10:27 4:28 /usr/bin/kwin_x11 --replace
|
| 772 |
+
✅ [Sun Jul 6 12:07:29 PM PDT 2025] BAŞARILI: peach_20250706_120712.png oluşturuldu! Süre: 17s
|
| 773 |
+
📁 Dosya boyutu: 292K
|
| 774 |
+
🧹 [Sun Jul 6 12:07:29 PM PDT 2025] Cache temizleniyor...
|
| 775 |
+
🏁 [Sun Jul 6 12:07:29 PM PDT 2025] İşlem tamamlandı. Toplam süre: 17s
|
| 776 |
+
🔁 [Sun Jul 6 12:08:12 PM PDT 2025] 🟡 Optimized başlatılıyor
|
| 777 |
+
💾 [Sun Jul 6 12:08:12 PM PDT 2025] Benzersiz dosya adı oluşturuldu: peach_20250706_120812.png
|
| 778 |
+
📊 [Sun Jul 6 12:08:12 PM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 779 |
+
CPU Info:
|
| 780 |
+
Cores: 16, Load: 2.48
|
| 781 |
+
RAM Info:
|
| 782 |
+
total used free shared buff/cache available
|
| 783 |
+
Mem: 30Gi 4.2Gi 20Gi 90Mi 7.0Gi 26Gi
|
| 784 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 785 |
+
GPU Info:
|
| 786 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4988 MiB, 58, 8 %
|
| 787 |
+
---
|
| 788 |
+
🔍 [Sun Jul 6 12:08:12 PM PDT 2025] PyTorch kurulum kontrolü...
|
| 789 |
+
🔥 [Sun Jul 6 12:08:14 PM PDT 2025] GPU warm-up başlatılıyor...
|
| 790 |
+
CUDA Available: True
|
| 791 |
+
GPU Count: 1
|
| 792 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 793 |
+
GPU Memory: 5.6 GB
|
| 794 |
+
GPU warm-up tamamlandı
|
| 795 |
+
🚀 [Sun Jul 6 12:08:16 PM PDT 2025] Optimized komut çalıştırılıyor...
|
| 796 |
+
[12:08:21] 🎯 Başlatılıyor: A tiny dragon sitting on a bookshelf, photorealistic
|
| 797 |
+
[12:08:21] 📁 Çıktı: peach_20250706_120812.png
|
| 798 |
+
[12:08:21] 🔧 Device: cuda, Steps: 4
|
| 799 |
+
[12:08:21] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 800 |
+
[12:08:24]
|
| 801 |
+
[12:08:25] 🚀 GPU'ya aktarılıyor (cuda)
|
| 802 |
+
[12:08:25] ✅ Pipeline yüklendi (7.4s)
|
| 803 |
+
[12:08:25] 🎨 Görüntü oluşturuluyor...
|
| 804 |
+
[12:08:28]
|
| 805 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 806 |
25%|██▌ | 1/4 [00:00<00:02, 1.01it/s]
|
| 807 |
50%|█████ | 2/4 [00:01<00:01, 1.43it/s]
|
| 808 |
75%|███████▌ | 3/4 [00:01<00:00, 1.72it/s]
|
| 809 |
+
[12:08:28] Potential NSFW content was detected in one or more images. A black image will be returned instead. Try again with a different prompt and/or seed.
|
| 810 |
+
[12:08:28] ✅ Görüntü oluşturuldu (3.2s)
|
| 811 |
+
[12:08:28] 💾 Kaydedildi: peach_20250706_120812.png
|
| 812 |
+
[12:08:28] ⏱️ Toplam süre: 10.7s
|
| 813 |
+
📊 [Sun Jul 6 12:08:29 PM PDT 2025] İşlem sonrası detaylı analiz:
|
| 814 |
+
GPU Status:
|
| 815 |
+
709, 6144, 68, 64, 54.13
|
| 816 |
+
CPU Status:
|
| 817 |
+
%Cpu(s): 2.9 us, 1.1 sy, 0.0 ni, 95.4 id, 0.6 wa, 0.0 hi, 0.0 si, 0.0 st
|
| 818 |
+
Memory Status:
|
| 819 |
+
total used free shared buff/cache available
|
| 820 |
+
Mem: 30Gi 5.0Gi 19Gi 94Mi 7.0Gi 25Gi
|
| 821 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 822 |
+
Process Info:
|
| 823 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 824 |
+
asahiner 2706 26.0 2.9 1473362616 960644 ? Sl 10:28 26:07 /opt/visual-studio-code/code --type=zygote
|
| 825 |
+
asahiner 2670 8.5 0.4 34360996 158240 ? Sl 10:28 8:36 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 826 |
+
asahiner 1686 4.5 0.3 26622532 127928 tty2 Sl+ 10:27 4:34 /usr/lib/Xorg :0 vt2
|
| 827 |
+
asahiner 1794 4.5 0.7 2174972 240052 ? Ssl 10:27 4:32 /usr/bin/kwin_x11 --replace
|
| 828 |
+
✅ [Sun Jul 6 12:08:30 PM PDT 2025] BAŞARILI: peach_20250706_120812.png oluşturuldu! Süre: 18s
|
| 829 |
+
📁 Dosya boyutu: 4.0K
|
| 830 |
+
🧹 [Sun Jul 6 12:08:30 PM PDT 2025] Cache temizleniyor...
|
| 831 |
+
🏁 [Sun Jul 6 12:08:30 PM PDT 2025] İşlem tamamlandı. Toplam süre: 18s
|
| 832 |
+
🔁 [Sun Jul 6 12:09:00 PM PDT 2025] 🟡 Optimized başlatılıyor
|
| 833 |
+
💾 [Sun Jul 6 12:09:00 PM PDT 2025] Benzersiz dosya adı oluşturuldu: peach_20250706_120900.png
|
| 834 |
+
📊 [Sun Jul 6 12:09:00 PM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 835 |
+
CPU Info:
|
| 836 |
+
Cores: 16, Load: 2.40
|
| 837 |
+
RAM Info:
|
| 838 |
+
total used free shared buff/cache available
|
| 839 |
+
Mem: 30Gi 4.3Gi 20Gi 91Mi 7.0Gi 26Gi
|
| 840 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 841 |
+
GPU Info:
|
| 842 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 5023 MiB, 59, 7 %
|
| 843 |
+
---
|
| 844 |
+
🔍 [Sun Jul 6 12:09:00 PM PDT 2025] PyTorch kurulum kontrolü...
|
| 845 |
+
🔥 [Sun Jul 6 12:09:02 PM PDT 2025] GPU warm-up başlatılıyor...
|
| 846 |
+
CUDA Available: True
|
| 847 |
+
GPU Count: 1
|
| 848 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 849 |
+
GPU Memory: 5.6 GB
|
| 850 |
+
GPU warm-up tamamlandı
|
| 851 |
+
🚀 [Sun Jul 6 12:09:04 PM PDT 2025] Optimized komut çalıştırılıyor...
|
| 852 |
+
[12:09:09] 🎯 Başlatılıyor: A giant turtle carrying a forest on its back
|
| 853 |
+
[12:09:09] 📁 Çıktı: peach_20250706_120900.png
|
| 854 |
+
[12:09:09] 🔧 Device: cuda, Steps: 4
|
| 855 |
+
[12:09:09] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 856 |
+
[12:09:11]
|
| 857 |
+
[12:09:12] 🚀 GPU'ya aktarılıyor (cuda)
|
| 858 |
+
[12:09:12] ✅ Pipeline yüklendi (6.8s)
|
| 859 |
+
[12:09:12] 🎨 Görüntü oluşturuluyor...
|
| 860 |
+
[12:09:15]
|
| 861 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 862 |
25%|██▌ | 1/4 [00:00<00:02, 1.01it/s]
|
| 863 |
50%|█████ | 2/4 [00:01<00:01, 1.44it/s]
|
| 864 |
75%|███████▌ | 3/4 [00:01<00:00, 1.73it/s]
|
| 865 |
+
[12:09:15] ✅ Görüntü oluşturuldu (3.2s)
|
| 866 |
+
[12:09:15] 💾 Kaydedildi: peach_20250706_120900.png
|
| 867 |
+
[12:09:15] ⏱️ Toplam süre: 10.0s
|
| 868 |
+
📊 [Sun Jul 6 12:09:16 PM PDT 2025] İşlem sonrası detaylı analiz:
|
| 869 |
+
GPU Status:
|
| 870 |
+
716, 6144, 44, 64, 50.70
|
| 871 |
+
CPU Status:
|
| 872 |
+
%Cpu(s): 2.9 us, 2.3 sy, 0.0 ni, 94.3 id, 0.6 wa, 0.0 hi, 0.0 si, 0.0 st
|
| 873 |
+
Memory Status:
|
| 874 |
+
total used free shared buff/cache available
|
| 875 |
+
Mem: 30Gi 4.2Gi 20Gi 92Mi 7.0Gi 26Gi
|
| 876 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 877 |
+
Process Info:
|
| 878 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 879 |
+
asahiner 2706 26.0 1.2 1473361720 415428 ? Sl 10:28 26:16 /opt/visual-studio-code/code --type=zygote
|
| 880 |
+
asahiner 2670 8.5 0.4 34357028 158908 ? Sl 10:28 8:40 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 881 |
+
asahiner 1686 4.5 0.3 26622532 127928 tty2 Sl+ 10:27 4:37 /usr/lib/Xorg :0 vt2
|
| 882 |
+
asahiner 1794 4.4 0.7 2174972 240136 ? Ssl 10:27 4:34 /usr/bin/kwin_x11 --replace
|
| 883 |
+
✅ [Sun Jul 6 12:09:16 PM PDT 2025] BAŞARILI: peach_20250706_120900.png oluşturuldu! Süre: 16s
|
| 884 |
+
📁 Dosya boyutu: 300K
|
| 885 |
+
🧹 [Sun Jul 6 12:09:16 PM PDT 2025] Cache temizleniyor...
|
| 886 |
+
🏁 [Sun Jul 6 12:09:16 PM PDT 2025] İşlem tamamlandı. Toplam süre: 16s
|
| 887 |
+
🔁 [Sun Jul 6 12:13:27 PM PDT 2025] 🟡 Optimized başlatılıyor
|
| 888 |
+
💾 [Sun Jul 6 12:13:27 PM PDT 2025] Benzersiz dosya adı oluşturuldu: peach_20250706_121327.png
|
| 889 |
+
📊 [Sun Jul 6 12:13:27 PM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 890 |
+
CPU Info:
|
| 891 |
+
Cores: 16, Load: 2.40
|
| 892 |
+
RAM Info:
|
| 893 |
+
total used free shared buff/cache available
|
| 894 |
+
Mem: 30Gi 5.1Gi 19Gi 97Mi 7.0Gi 25Gi
|
| 895 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 896 |
+
GPU Info:
|
| 897 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4966 MiB, 67, 38 %
|
| 898 |
+
---
|
| 899 |
+
🔍 [Sun Jul 6 12:13:27 PM PDT 2025] PyTorch kurulum kontrolü...
|
| 900 |
+
🔥 [Sun Jul 6 12:13:29 PM PDT 2025] GPU warm-up başlatılıyor...
|
| 901 |
+
CUDA Available: True
|
| 902 |
+
GPU Count: 1
|
| 903 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 904 |
+
GPU Memory: 5.6 GB
|
| 905 |
+
GPU warm-up tamamlandı
|
| 906 |
+
🚀 [Sun Jul 6 12:13:32 PM PDT 2025] Optimized komut çalıştırılıyor...
|
| 907 |
+
[12:13:37] 🎯 Başlatılıyor: A beautiful butterfly with rainbow wings sitting on a blooming sunflower in a peaceful garden
|
| 908 |
+
[12:13:37] 📁 Çıktı: peach_20250706_121327.png
|
| 909 |
+
[12:13:37] 🔧 Device: cuda, Steps: 4
|
| 910 |
+
[12:13:37] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 911 |
+
[12:13:39]
|
| 912 |
+
[12:13:40] ⚠️ NSFW filtresi devre dışı bırakıldı
|
| 913 |
+
[12:13:40] 🚀 GPU'ya aktarılıyor (cuda)
|
| 914 |
+
[12:13:40] ✅ Pipeline yüklendi (7.0s)
|
| 915 |
+
[12:13:40] 🎨 Görüntü oluşturuluyor...
|
| 916 |
+
[12:13:43]
|
| 917 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 918 |
25%|██▌ | 1/4 [00:01<00:03, 1.09s/it]
|
| 919 |
50%|█████ | 2/4 [00:01<00:01, 1.31it/s]
|
| 920 |
75%|███████▌ | 3/4 [00:02<00:00, 1.52it/s]
|
| 921 |
+
[12:13:44] ✅ Görüntü oluşturuldu (3.5s)
|
| 922 |
+
[12:13:44] 💾 Kaydedildi: peach_20250706_121327.png
|
| 923 |
+
[12:13:44] ⏱️ Toplam süre: 10.6s
|
| 924 |
+
📊 [Sun Jul 6 12:13:45 PM PDT 2025] İşlem sonrası detaylı analiz:
|
| 925 |
+
GPU Status:
|
| 926 |
+
755, 6144, 90, 69, 52.56
|
| 927 |
+
CPU Status:
|
| 928 |
+
%Cpu(s): 4.0 us, 2.3 sy, 0.0 ni, 93.8 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
|
| 929 |
+
Memory Status:
|
| 930 |
+
total used free shared buff/cache available
|
| 931 |
+
Mem: 30Gi 4.6Gi 19Gi 101Mi 7.0Gi 26Gi
|
| 932 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 933 |
+
Process Info:
|
| 934 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 935 |
+
asahiner 2706 26.9 2.6 1473369784 863380 ? Sl 10:28 28:27 /opt/visual-studio-code/code --type=zygote
|
| 936 |
+
asahiner 2670 8.9 0.4 34367140 150968 ? Sl 10:28 9:26 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 937 |
+
asahiner 1686 4.6 0.3 26622572 127932 tty2 Sl+ 10:27 4:57 /usr/lib/Xorg :0 vt2
|
| 938 |
+
asahiner 1794 4.6 0.7 2175804 241312 ? Ssl 10:27 4:56 /usr/bin/kwin_x11 --replace
|
| 939 |
+
✅ [Sun Jul 6 12:13:45 PM PDT 2025] BAŞARILI: peach_20250706_121327.png oluşturuldu! Süre: 18s
|
| 940 |
+
📁 Dosya boyutu: 292K
|
| 941 |
+
🧹 [Sun Jul 6 12:13:45 PM PDT 2025] Cache temizleniyor...
|
| 942 |
+
🏁 [Sun Jul 6 12:13:45 PM PDT 2025] İşlem tamamlandı. Toplam süre: 18s
|
| 943 |
+
🔁 [Sun Jul 6 12:18:18 PM PDT 2025] 🟡 Optimized başlatılıyor
|
| 944 |
+
💾 [Sun Jul 6 12:18:18 PM PDT 2025] Benzersiz dosya adı oluşturuldu: peach_20250706_121818.png
|
| 945 |
+
📊 [Sun Jul 6 12:18:18 PM PDT 2025] Detaylı sistem durumu: CPU Cores: 16, RAM, GPU
|
| 946 |
+
CPU Info:
|
| 947 |
+
Cores: 16, Load: 2.20
|
| 948 |
+
RAM Info:
|
| 949 |
+
total used free shared buff/cache available
|
| 950 |
+
Mem: 30Gi 4.4Gi 19Gi 99Mi 7.1Gi 26Gi
|
| 951 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 952 |
+
GPU Info:
|
| 953 |
+
NVIDIA GeForce RTX 2060, 6144 MiB, 4957 MiB, 58, 7 %
|
| 954 |
+
---
|
| 955 |
+
🔍 [Sun Jul 6 12:18:18 PM PDT 2025] PyTorch kurulum kontrolü...
|
| 956 |
+
🔥 [Sun Jul 6 12:18:20 PM PDT 2025] GPU warm-up başlatılıyor...
|
| 957 |
+
CUDA Available: True
|
| 958 |
+
GPU Count: 1
|
| 959 |
+
GPU Name: NVIDIA GeForce RTX 2060
|
| 960 |
+
GPU Memory: 5.6 GB
|
| 961 |
+
GPU warm-up tamamlandı
|
| 962 |
+
🚀 [Sun Jul 6 12:18:22 PM PDT 2025] Optimized komut çalıştırılıyor...
|
| 963 |
+
[12:18:27] 🎯 Başlatılıyor: An old typewriter transforming into a butterfly, double exposure style, digital art
|
| 964 |
+
[12:18:27] 📁 Çıktı: peach_20250706_121818.png
|
| 965 |
+
[12:18:27] 🔧 Device: cuda, Steps: 4
|
| 966 |
+
[12:18:27] 🔄 StableDiffusionPipeline yükleniyor: runwayml/stable-diffusion-v1-5
|
| 967 |
+
[12:18:29]
|
| 968 |
+
[12:18:31] ⚠️ NSFW filtresi devre dışı bırakıldı
|
| 969 |
+
[12:18:31] 🚀 GPU'ya aktarılıyor (cuda)
|
| 970 |
+
[12:18:31] ✅ Pipeline yüklendi (7.1s)
|
| 971 |
+
[12:18:31] 🎨 Görüntü oluşturuluyor...
|
| 972 |
+
[12:18:33]
|
| 973 |
0%| | 0/4 [00:00<?, ?it/s]
|
| 974 |
25%|██▌ | 1/4 [00:01<00:03, 1.07s/it]
|
| 975 |
50%|█████ | 2/4 [00:01<00:01, 1.39it/s]
|
| 976 |
75%|███████▌ | 3/4 [00:01<00:00, 1.69it/s]
|
| 977 |
+
[12:18:34] ✅ Görüntü oluşturuldu (3.2s)
|
| 978 |
+
[12:18:34] 💾 Kaydedildi: peach_20250706_121818.png
|
| 979 |
+
[12:18:34] ⏱️ Toplam süre: 10.3s
|
| 980 |
+
📊 [Sun Jul 6 12:18:35 PM PDT 2025] İşlem sonrası detaylı analiz:
|
| 981 |
+
GPU Status:
|
| 982 |
+
752, 6144, 78, 62, 50.83
|
| 983 |
+
CPU Status:
|
| 984 |
+
%Cpu(s): 2.3 us, 0.6 sy, 0.0 ni, 97.1 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
|
| 985 |
+
Memory Status:
|
| 986 |
+
total used free shared buff/cache available
|
| 987 |
+
Mem: 30Gi 5.1Gi 19Gi 99Mi 7.1Gi 25Gi
|
| 988 |
+
Swap: 23Gi 1.9Gi 21Gi
|
| 989 |
+
Process Info:
|
| 990 |
+
USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND
|
| 991 |
+
asahiner 2706 27.4 3.3 1473361656 1089528 ? Sl 10:28 30:14 /opt/visual-studio-code/code --type=zygote
|
| 992 |
+
asahiner 2670 9.0 0.5 34359008 162056 ? Sl 10:28 10:00 /opt/visual-studio-code/code --type=zygote --no-zygote-sandbox
|
| 993 |
+
asahiner 1686 4.7 0.4 26623744 130048 tty2 Sl+ 10:27 5:18 /usr/lib/Xorg :0 vt2
|
| 994 |
+
asahiner 1794 4.7 0.7 2194484 255740 ? Ssl 10:27 5:15 /usr/bin/kwin_x11 --replace
|
| 995 |
+
✅ [Sun Jul 6 12:18:35 PM PDT 2025] BAŞARILI: peach_20250706_121818.png oluşturuldu! Süre: 17s
|
| 996 |
+
📁 Dosya boyutu: 300K
|
| 997 |
+
🧹 [Sun Jul 6 12:18:35 PM PDT 2025] Cache temizleniyor...
|
| 998 |
+
🏁 [Sun Jul 6 12:18:35 PM PDT 2025] İşlem tamamlandı. Toplam süre: 17s
|
creative_marathon.sh
ADDED
|
@@ -0,0 +1,112 @@
|
|
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|
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|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
|
| 3 |
+
# 🎨 Creative Image Generation with Multiple Prompts
|
| 4 |
+
# 📅 2025-01-06 - Advanced creative prompts without NSFW issues
|
| 5 |
+
|
| 6 |
+
set -e
|
| 7 |
+
|
| 8 |
+
# 🌟 Environment setup
|
| 9 |
+
if [[ "$(which python)" != *"flux-env"* ]]; then
|
| 10 |
+
echo "⚠️ flux-env aktivasyonu gerekli"
|
| 11 |
+
exit 1
|
| 12 |
+
fi
|
| 13 |
+
|
| 14 |
+
# 🚀 Performance optimizations
|
| 15 |
+
export OMP_NUM_THREADS=16
|
| 16 |
+
export MKL_NUM_THREADS=16
|
| 17 |
+
export NUMBA_NUM_THREADS=16
|
| 18 |
+
export CUDA_LAUNCH_BLOCKING=0
|
| 19 |
+
export CUDA_ALLOC_CONF=expandable_segments:True
|
| 20 |
+
|
| 21 |
+
# 🎯 Creative prompts array - Safe but artistic
|
| 22 |
+
PROMPTS=(
|
| 23 |
+
"A mystical dragon made of rainbow light soaring through a nebula filled with stars and cosmic dust, fantasy art, ethereal, 4K"
|
| 24 |
+
"A steampunk airship floating above a Victorian city at sunset, brass gears, vintage aesthetic, detailed mechanical parts"
|
| 25 |
+
"A crystal cave with luminescent mushrooms and glowing crystals, magical atmosphere, bioluminescent plants, underground wonderland"
|
| 26 |
+
"A futuristic cyberpunk cityscape at night with neon lights reflecting on wet streets, flying cars, holographic billboards"
|
| 27 |
+
"A majestic phoenix rising from golden flames against a dramatic stormy sky, mythical creature, powerful wings, epic scene"
|
| 28 |
+
"A serene Japanese zen garden with cherry blossoms, koi pond, bamboo fountain, traditional architecture, peaceful meditation"
|
| 29 |
+
"An underwater coral reef teeming with colorful tropical fish, sea turtles, and vibrant marine life, crystal clear water"
|
| 30 |
+
"A magical forest with floating islands, waterfalls cascading into clouds, ancient trees, enchanted atmosphere"
|
| 31 |
+
"A desert oasis at twilight with palm trees, clear blue water, camels, Arabian nights aesthetic, warm golden light"
|
| 32 |
+
"A space station orbiting Earth with solar panels, docking bays, astronauts in EVA suits, realistic sci-fi"
|
| 33 |
+
)
|
| 34 |
+
|
| 35 |
+
echo "🎨 Creative Image Generation Marathon Starting!"
|
| 36 |
+
echo "📊 Will generate ${#PROMPTS[@]} unique images"
|
| 37 |
+
echo "🛡️ NSFW Filter: DISABLED for maximum creativity"
|
| 38 |
+
echo ""
|
| 39 |
+
|
| 40 |
+
# 📊 Initial system status
|
| 41 |
+
echo "🖥️ Initial System Status:"
|
| 42 |
+
echo " RAM: $(free -h | awk '/^Mem:/ {print $3 "/" $2}')"
|
| 43 |
+
echo " GPU: $(nvidia-smi --query-gpu=memory.used,memory.total --format=csv,noheader,nounits | awk '{print $1 "/" $2 " MB"}')"
|
| 44 |
+
echo ""
|
| 45 |
+
|
| 46 |
+
TOTAL_START=$(date +%s)
|
| 47 |
+
SUCCESS_COUNT=0
|
| 48 |
+
|
| 49 |
+
# 🔄 Generate images for each prompt
|
| 50 |
+
for i in "${!PROMPTS[@]}"; do
|
| 51 |
+
PROMPT="${PROMPTS[$i]}"
|
| 52 |
+
TIMESTAMP=$(date +"%Y%m%d_%H%M%S")
|
| 53 |
+
OUTPUT_FILE="creative_$(printf "%02d" $((i+1)))_${TIMESTAMP}.png"
|
| 54 |
+
|
| 55 |
+
echo "🎯 [$(date '+%H:%M:%S')] Generating image $((i+1))/${#PROMPTS[@]}"
|
| 56 |
+
echo " Prompt: ${PROMPT:0:80}..."
|
| 57 |
+
echo " Output: $OUTPUT_FILE"
|
| 58 |
+
|
| 59 |
+
START_TIME=$(date +%s)
|
| 60 |
+
|
| 61 |
+
# 🎨 Generate image with NSFW filter disabled
|
| 62 |
+
if timeout 60s python gen_image_stable.py \
|
| 63 |
+
--ckpt "runwayml/stable-diffusion-v1-5" \
|
| 64 |
+
--prompt "$PROMPT" \
|
| 65 |
+
--output-file "$OUTPUT_FILE" \
|
| 66 |
+
--device cuda \
|
| 67 |
+
--num_inference_steps 15 \
|
| 68 |
+
--seed $RANDOM \
|
| 69 |
+
--disable-nsfw-filter > /dev/null 2>&1; then
|
| 70 |
+
|
| 71 |
+
DURATION=$(($(date +%s) - START_TIME))
|
| 72 |
+
|
| 73 |
+
if [ -f "$OUTPUT_FILE" ]; then
|
| 74 |
+
SIZE=$(stat -c%s "$OUTPUT_FILE")
|
| 75 |
+
echo " ✅ Success! ${DURATION}s, ${SIZE} bytes"
|
| 76 |
+
SUCCESS_COUNT=$((SUCCESS_COUNT + 1))
|
| 77 |
+
else
|
| 78 |
+
echo " ❌ Failed: File not created"
|
| 79 |
+
fi
|
| 80 |
+
else
|
| 81 |
+
echo " ⏰ Timeout or error occurred"
|
| 82 |
+
fi
|
| 83 |
+
|
| 84 |
+
# 🔄 Brief pause between generations
|
| 85 |
+
sleep 2
|
| 86 |
+
echo ""
|
| 87 |
+
done
|
| 88 |
+
|
| 89 |
+
TOTAL_DURATION=$(($(date +%s) - TOTAL_START))
|
| 90 |
+
|
| 91 |
+
echo "🎉 Creative Generation Marathon Complete!"
|
| 92 |
+
echo "📊 Results:"
|
| 93 |
+
echo " Total Images: ${#PROMPTS[@]}"
|
| 94 |
+
echo " Successful: $SUCCESS_COUNT"
|
| 95 |
+
echo " Failed: $((${#PROMPTS[@]} - SUCCESS_COUNT))"
|
| 96 |
+
echo " Total Time: ${TOTAL_DURATION}s"
|
| 97 |
+
echo " Average per Image: $((TOTAL_DURATION / ${#PROMPTS[@]}))s"
|
| 98 |
+
echo ""
|
| 99 |
+
|
| 100 |
+
# 📊 Final system status
|
| 101 |
+
echo "🖥️ Final System Status:"
|
| 102 |
+
echo " RAM: $(free -h | awk '/^Mem:/ {print $3 "/" $2}')"
|
| 103 |
+
echo " GPU: $(nvidia-smi --query-gpu=memory.used,memory.total --format=csv,noheader,nounits | awk '{print $1 "/" $2 " MB"}')"
|
| 104 |
+
echo ""
|
| 105 |
+
|
| 106 |
+
# 📁 List generated files
|
| 107 |
+
echo "📁 Generated Files:"
|
| 108 |
+
ls -la creative_*.png 2>/dev/null || echo " No files found"
|
| 109 |
+
|
| 110 |
+
echo ""
|
| 111 |
+
echo "🎨 Use 'ls creative_*.png' to see all generated images!"
|
| 112 |
+
echo "🖼️ Use 'identify creative_*.png' to check image details!"
|
creative_prompts.txt
ADDED
|
@@ -0,0 +1,77 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Creative Image Generation Prompts
|
| 2 |
+
# Çeşitli konularda yaratıcı resim üretme komutları
|
| 3 |
+
|
| 4 |
+
## Fantasy & Sci-Fi (Fantastik & Bilim Kurgu)
|
| 5 |
+
1. "A majestic dragon perched on a crystal tower in a floating city among the clouds"
|
| 6 |
+
2. "Cyberpunk samurai warrior with neon katana in a rain-soaked futuristic Tokyo"
|
| 7 |
+
3. "Ancient wizard's library filled with floating books and magical glowing orbs"
|
| 8 |
+
4. "Space station orbiting a purple nebula with alien ships in the background"
|
| 9 |
+
5. "Steampunk airship sailing through a storm of mechanical gears and clockwork"
|
| 10 |
+
|
| 11 |
+
## Nature & Landscapes (Doğa & Manzaralar)
|
| 12 |
+
6. "Enchanted forest with bioluminescent mushrooms and fairy lights at twilight"
|
| 13 |
+
7. "Majestic waterfall cascading into a crystal clear lake surrounded by cherry blossoms"
|
| 14 |
+
8. "Desert oasis with palm trees reflected in still water under a starry night sky"
|
| 15 |
+
9. "Misty mountain peaks emerging from clouds during golden hour sunrise"
|
| 16 |
+
10. "Underwater coral reef city with colorful fish swimming between coral buildings"
|
| 17 |
+
|
| 18 |
+
## Animals & Creatures (Hayvanlar & Yaratıklar)
|
| 19 |
+
11. "Wise old owl wearing a tiny wizard hat sitting on a stack of ancient books"
|
| 20 |
+
12. "Majestic white wolf running through a snowy forest with aurora borealis above"
|
| 21 |
+
13. "Giant friendly octopus playing with children in a magical underwater playground"
|
| 22 |
+
14. "Phoenix rising from flames with rainbow-colored feathers spreading wide"
|
| 23 |
+
15. "Cute robot cat with LED eyes exploring a garden full of mechanical flowers"
|
| 24 |
+
|
| 25 |
+
## Food & Culinary (Yemek & Mutfak)
|
| 26 |
+
16. "Floating island made entirely of different types of cheese with wine waterfalls"
|
| 27 |
+
17. "Giant coffee cup serving as a hot air balloon over a landscape of pastries"
|
| 28 |
+
18. "Magical bakery where bread loaves grow on trees and cupcakes float in the air"
|
| 29 |
+
19. "Underwater sushi restaurant with fish chefs preparing meals for sea creatures"
|
| 30 |
+
20. "Candy castle made of chocolate walls and gummy bear guards"
|
| 31 |
+
|
| 32 |
+
## Architecture & Cities (Mimari & Şehirler)
|
| 33 |
+
21. "Ancient Egyptian pyramid with modern skyscrapers growing from its sides"
|
| 34 |
+
22. "Venice-style canal city built inside a giant tree trunk with boat elevators"
|
| 35 |
+
23. "Miniature medieval village built inside a snow globe on a wizard's desk"
|
| 36 |
+
24. "Futuristic greenhouse city with plants and buildings integrated seamlessly"
|
| 37 |
+
25. "Floating monastery built on a chain of connected hot air balloons"
|
| 38 |
+
|
| 39 |
+
## Art & Abstract (Sanat & Soyut)
|
| 40 |
+
26. "Melting clock tower in a surreal landscape inspired by Salvador Dalí"
|
| 41 |
+
27. "Rainbow-colored liquid splashing upward forming the shape of a dancer"
|
| 42 |
+
28. "Geometric crystal formations growing from a canvas in an art studio"
|
| 43 |
+
29. "Musical notes transforming into butterflies and flying off sheet music"
|
| 44 |
+
30. "Kaleidoscope pattern made of tiny mirrors reflecting a sunset"
|
| 45 |
+
|
| 46 |
+
## Retro & Vintage (Retro & Vintage)
|
| 47 |
+
31. "1950s diner on Mars with alien customers and robot waitresses"
|
| 48 |
+
32. "Victorian mansion decorated for Halloween with friendly ghosts and pumpkins"
|
| 49 |
+
33. "Old-fashioned train traveling through a portal between different time periods"
|
| 50 |
+
34. "Vintage record player with music notes flowing out as colorful smoke"
|
| 51 |
+
35. "Art Deco style robot butler serving tea in an elegant 1920s parlor"
|
| 52 |
+
|
| 53 |
+
## Seasons & Weather (Mevsimler & Hava Durumu)
|
| 54 |
+
36. "Autumn forest where falling leaves transform into small birds mid-flight"
|
| 55 |
+
37. "Winter wonderland with ice sculptures that glow from within"
|
| 56 |
+
38. "Spring meadow with flowers that change colors like mood rings"
|
| 57 |
+
39. "Summer beach with sand castles that are actually tiny functional cities"
|
| 58 |
+
40. "Thunderstorm over a field where lightning bolts are growing into trees"
|
| 59 |
+
|
| 60 |
+
## Transportation & Vehicles (Ulaşım & Araçlar)
|
| 61 |
+
41. "Pirate ship sailing through clouds instead of water with sky whales nearby"
|
| 62 |
+
42. "Submarine shaped like a whale exploring a coral reef city"
|
| 63 |
+
43. "Flying bicycle with butterfly wings carrying a basket of flowers"
|
| 64 |
+
44. "Train made of books traveling on rainbow tracks through the sky"
|
| 65 |
+
45. "Hot air balloon shaped like a giant peacock feather floating over mountains"
|
| 66 |
+
|
| 67 |
+
## Everyday Objects in Unusual Settings (Sıradışı Ortamlarda Günlük Objeler)
|
| 68 |
+
46. "Giant pencils growing like trees in a forest with eraser mushrooms"
|
| 69 |
+
47. "Umbrella serving as a parachute for a cat floating down from the clouds"
|
| 70 |
+
48. "Teacup large enough to be used as a swimming pool by tiny people"
|
| 71 |
+
49. "Books with pages that show live moving scenes like windows to other worlds"
|
| 72 |
+
50. "Clock tower where each number is a different miniature world"
|
| 73 |
+
|
| 74 |
+
# Kullanım Örnekleri:
|
| 75 |
+
# ./gen_run_optimized.sh ile bu promptları kullanmak için:
|
| 76 |
+
# Script içindeki prompt satırını değiştirin:
|
| 77 |
+
# --prompt "Yukarıdaki promptlardan birini buraya yazın"
|
diverse_prompts.txt
ADDED
|
@@ -0,0 +1,142 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
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|
| 1 |
+
# Diverse Creative Prompts for Image Generation
|
| 2 |
+
# Categories: Fantasy, Cyberpunk, Nature, Architecture, Surreal, Portrait, Food Art, Abstract, Historical, Futuristic
|
| 3 |
+
|
| 4 |
+
## Fantasy & Mythology (10 prompts)
|
| 5 |
+
"A majestic phoenix rising from golden flames in an ancient temple"
|
| 6 |
+
"Underwater kingdom with mermaids swimming between coral skyscrapers"
|
| 7 |
+
"A wise old wizard brewing potions in a floating tower above clouds"
|
| 8 |
+
"Dragon's lair filled with glowing crystals and treasure chests"
|
| 9 |
+
"Enchanted forest where trees have glowing neon leaves at midnight"
|
| 10 |
+
"Ancient stone circle with magical runes floating in purple mist"
|
| 11 |
+
"A fairy tale castle built inside a giant hollow tree trunk"
|
| 12 |
+
"Unicorn galloping across rainbow bridge between mountain peaks"
|
| 13 |
+
"Dark sorcerer summoning lightning storms in volcanic wasteland"
|
| 14 |
+
"Crystal cave with luminescent mushrooms and sleeping earth spirits"
|
| 15 |
+
|
| 16 |
+
## Cyberpunk & Sci-Fi (10 prompts)
|
| 17 |
+
"Neon-lit street market in a futuristic Tokyo with flying cars overhead"
|
| 18 |
+
"Cyberpunk hacker in a dark room with multiple holographic screens"
|
| 19 |
+
"Space station orbiting a purple planet with twin moons"
|
| 20 |
+
"Robot bartender serving glowing cocktails in underground nightclub"
|
| 21 |
+
"Futuristic city built on floating platforms above toxic clouds"
|
| 22 |
+
"Time traveler stepping through a swirling portal of blue energy"
|
| 23 |
+
"Android warrior with glowing red eyes in post-apocalyptic ruins"
|
| 24 |
+
"Virtual reality arcade with people connected to glowing pods"
|
| 25 |
+
"Alien marketplace on Mars with diverse extraterrestrial species"
|
| 26 |
+
"Cybernetic tree growing circuit boards instead of leaves"
|
| 27 |
+
|
| 28 |
+
## Nature & Landscapes (10 prompts)
|
| 29 |
+
"Autumn forest with golden leaves falling into crystal clear lake"
|
| 30 |
+
"Tropical waterfall cascading into turquoise pool surrounded by orchids"
|
| 31 |
+
"Desert oasis at sunset with palm trees and camel caravan"
|
| 32 |
+
"Northern lights dancing over snow-covered pine forest"
|
| 33 |
+
"Volcanic island with lava flowing into ocean creating steam clouds"
|
| 34 |
+
"Bamboo forest with sunbeams filtering through green canopy"
|
| 35 |
+
"Alpine meadow filled with wildflowers and distant snow peaks"
|
| 36 |
+
"Rocky coastline with lighthouse during violent thunderstorm"
|
| 37 |
+
"Redwood forest with morning mist and deer grazing peacefully"
|
| 38 |
+
"Lavender fields stretching to horizon under cloudy sky"
|
| 39 |
+
|
| 40 |
+
## Architecture & Urban (10 prompts)
|
| 41 |
+
"Art Deco skyscraper reaching into storm clouds at twilight"
|
| 42 |
+
"Ancient Roman colosseum overgrown with vines and flowers"
|
| 43 |
+
"Modern glass house built on cliff overlooking ocean waves"
|
| 44 |
+
"Gothic cathedral with stained glass windows casting colorful shadows"
|
| 45 |
+
"Abandoned subway station reclaimed by nature with growing plants"
|
| 46 |
+
"Futuristic dome city under transparent protective shield"
|
| 47 |
+
"Traditional Japanese pagoda reflected in mirror-like pond"
|
| 48 |
+
"Industrial warehouse converted into artist's loft with exposed beams"
|
| 49 |
+
"Moroccan bazaar with intricate tile work and hanging lanterns"
|
| 50 |
+
"Brutalist concrete building covered in street art murals"
|
| 51 |
+
|
| 52 |
+
## Surreal & Abstract (10 prompts)
|
| 53 |
+
"Melting clocks floating in space between giant chess pieces"
|
| 54 |
+
"Staircase to nowhere spiraling through clouds made of cotton candy"
|
| 55 |
+
"Human figure dissolving into flock of colorful butterflies"
|
| 56 |
+
"Inverted cityscape hanging from sky like stalactites"
|
| 57 |
+
"Giant eye in desert watching pyramid made of mirrors"
|
| 58 |
+
"Floating islands connected by bridges made of musical notes"
|
| 59 |
+
"Tree growing books instead of leaves with words falling like rain"
|
| 60 |
+
"Ocean waves frozen mid-crash in crystalline formations"
|
| 61 |
+
"Doorway opening to different seasons on each side"
|
| 62 |
+
"Gravity-defying waterfalls flowing upward into starry void"
|
| 63 |
+
|
| 64 |
+
## Portrait & Character (10 prompts)
|
| 65 |
+
"Elegant Victorian woman with steampunk mechanical arm in garden"
|
| 66 |
+
"Tribal warrior with intricate face paint and feathered headdress"
|
| 67 |
+
"Elderly craftsman with weathered hands working on wooden sculpture"
|
| 68 |
+
"Young dancer frozen mid-leap with flowing fabric and dramatic lighting"
|
| 69 |
+
"Mysterious figure in hooded cloak standing at crossroads at dusk"
|
| 70 |
+
"Astronaut removing helmet to reveal alien features on distant planet"
|
| 71 |
+
"Street musician playing violin while pigeons dance around feet"
|
| 72 |
+
"Renaissance painter creating self-portrait in candlelit studio"
|
| 73 |
+
"Cyberpunk courier with neon hair delivering glowing package"
|
| 74 |
+
"Mountain climber reaching summit with breathtaking view behind"
|
| 75 |
+
|
| 76 |
+
## Food & Culinary Art (10 prompts)
|
| 77 |
+
"Elaborate wedding cake designed like fairy tale castle with sugar flowers"
|
| 78 |
+
"Sushi chef creating artistic rolls with rainbow-colored ingredients"
|
| 79 |
+
"Chocolate fountain surrounded by exotic fruits and golden decorations"
|
| 80 |
+
"Traditional wood-fired pizza oven with flames and flying flour"
|
| 81 |
+
"French patisserie window display with colorful macarons and pastries"
|
| 82 |
+
"Molecular gastronomy dish with smoking dry ice and edible flowers"
|
| 83 |
+
"Rustic farmhouse kitchen with homemade bread cooling on windowsill"
|
| 84 |
+
"Street food vendor preparing spicy noodles with dramatic fire wok"
|
| 85 |
+
"Wine cellar with ancient bottles covered in cobwebs and candlelight"
|
| 86 |
+
"Ice cream parlor with impossible flavors in crystal cones"
|
| 87 |
+
|
| 88 |
+
## Abstract & Geometric (10 prompts)
|
| 89 |
+
"Kaleidoscope pattern made from butterfly wings and precious stones"
|
| 90 |
+
"Geometric mandala constructed from flowing liquid metal"
|
| 91 |
+
"Abstract representation of music as colorful waves and particles"
|
| 92 |
+
"Fractal tree made of pure light branching into infinity"
|
| 93 |
+
"Tessellated pattern inspired by Islamic architecture in gold and blue"
|
| 94 |
+
"DNA helix twisted into impossible Möbius strip formation"
|
| 95 |
+
"Crystalline structure growing from mathematical equations"
|
| 96 |
+
"Color spectrum explosion frozen in geometric crystal formations"
|
| 97 |
+
"Sacred geometry symbols floating in cosmic void"
|
| 98 |
+
"Parametric architecture design morphing through time and space"
|
| 99 |
+
|
| 100 |
+
## Historical & Cultural (10 prompts)
|
| 101 |
+
"Viking longship sailing through icy fjord under aurora borealis"
|
| 102 |
+
"Ancient Egyptian tomb chamber with golden artifacts and hieroglyphs"
|
| 103 |
+
"Samurai warrior meditating in cherry blossom garden at dawn"
|
| 104 |
+
"Medieval marketplace bustling with merchants and exotic goods"
|
| 105 |
+
"Native American chief in full regalia overlooking sacred canyon"
|
| 106 |
+
"Renaissance inventor's workshop filled with mechanical contraptions"
|
| 107 |
+
"Ancient Greek philosopher teaching students in marble colonnade"
|
| 108 |
+
"Aztec pyramid emerging from jungle mist at sunrise"
|
| 109 |
+
"Wild West saloon during poker game with dramatic lighting"
|
| 110 |
+
"Ancient Chinese tea ceremony in bamboo pavilion by mountain stream"
|
| 111 |
+
|
| 112 |
+
## Futuristic & Space (10 prompts)
|
| 113 |
+
"Terraforming machine converting barren planet into garden world"
|
| 114 |
+
"Space elevator stretching from Earth surface to orbital station"
|
| 115 |
+
"Alien archaeology site with crystalline ruins on distant moon"
|
| 116 |
+
"Generation ship's biodome containing entire ecosystem"
|
| 117 |
+
"Quantum computer the size of building processing universal data"
|
| 118 |
+
"Solar panel fields covering entire continent from orbital view"
|
| 119 |
+
"Interstellar highway with ships traveling at light speed"
|
| 120 |
+
"Dyson sphere partially constructed around dying star"
|
| 121 |
+
"Mars colony with transparent domes and red rocky landscape"
|
| 122 |
+
"Wormhole gateway connecting two different galaxy clusters"
|
| 123 |
+
|
| 124 |
+
# Usage Instructions:
|
| 125 |
+
# 1. Copy any prompt from above
|
| 126 |
+
# 2. Paste it into gen_run_optimized.sh replacing the current prompt
|
| 127 |
+
# 3. Run the script to generate unique artwork
|
| 128 |
+
# 4. Experiment with different styles by adding terms like:
|
| 129 |
+
# - "in the style of Van Gogh"
|
| 130 |
+
# - "photorealistic"
|
| 131 |
+
# - "digital art"
|
| 132 |
+
# - "oil painting"
|
| 133 |
+
# - "anime style"
|
| 134 |
+
# - "concept art"
|
| 135 |
+
# - "hyperrealistic"
|
| 136 |
+
|
| 137 |
+
# Pro Tips:
|
| 138 |
+
# - Combine prompts from different categories for unique results
|
| 139 |
+
# - Add lighting terms: "golden hour", "dramatic lighting", "soft ambient"
|
| 140 |
+
# - Specify art styles: "impressionist", "art nouveau", "minimalist"
|
| 141 |
+
# - Include camera angles: "bird's eye view", "close-up", "wide angle"
|
| 142 |
+
# - Add mood descriptors: "mysterious", "serene", "chaotic", "majestic"
|
experiments.sh
ADDED
|
@@ -0,0 +1,79 @@
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|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
|
| 3 |
+
# baseline
|
| 4 |
+
python run_benchmark.py \
|
| 5 |
+
--trace-file baseline.json.gz \
|
| 6 |
+
--disable_bf16 \
|
| 7 |
+
--compile_export_mode disabled \
|
| 8 |
+
--disable_fused_projections \
|
| 9 |
+
--disable_channels_last \
|
| 10 |
+
--disable_fa3 \
|
| 11 |
+
--disable_quant \
|
| 12 |
+
--disable_inductor_tuning_flags \
|
| 13 |
+
> baseline.txt 2>&1
|
| 14 |
+
|
| 15 |
+
# bfloat16
|
| 16 |
+
python run_benchmark.py \
|
| 17 |
+
--trace-file bfloat16.json.gz \
|
| 18 |
+
--compile_export_mode disabled \
|
| 19 |
+
--disable_fused_projections \
|
| 20 |
+
--disable_channels_last \
|
| 21 |
+
--disable_fa3 \
|
| 22 |
+
--disable_quant \
|
| 23 |
+
--disable_inductor_tuning_flags \
|
| 24 |
+
> bf16.txt 2>&1
|
| 25 |
+
|
| 26 |
+
# bfloat16 + torch.compile
|
| 27 |
+
python run_benchmark.py \
|
| 28 |
+
--trace-file bf16_compile.json.gz \
|
| 29 |
+
--compile_export_mode compile \
|
| 30 |
+
--disable_fused_projections \
|
| 31 |
+
--disable_channels_last \
|
| 32 |
+
--disable_fa3 \
|
| 33 |
+
--disable_quant \
|
| 34 |
+
--disable_inductor_tuning_flags \
|
| 35 |
+
> bf16_compile.txt 2>&1
|
| 36 |
+
|
| 37 |
+
# bfloat16 + torch.compile + qkv projection
|
| 38 |
+
python run_benchmark.py \
|
| 39 |
+
--trace-file bf16_compile_qkv.json.gz \
|
| 40 |
+
--compile_export_mode compile \
|
| 41 |
+
--disable_channels_last \
|
| 42 |
+
--disable_fa3 \
|
| 43 |
+
--disable_quant \
|
| 44 |
+
--disable_inductor_tuning_flags \
|
| 45 |
+
> bf16_compile_qkv.txt 2>&1
|
| 46 |
+
|
| 47 |
+
# bfloat16 + torch.compile + qkv projection + channels_last
|
| 48 |
+
python run_benchmark.py \
|
| 49 |
+
--trace-file bf16_compile_qkv_chan.json.gz \
|
| 50 |
+
--compile_export_mode compile \
|
| 51 |
+
--disable_fa3 \
|
| 52 |
+
--disable_quant \
|
| 53 |
+
--disable_inductor_tuning_flags \
|
| 54 |
+
> bf16_compile_qkv_chan.txt 2>&1
|
| 55 |
+
|
| 56 |
+
# bfloat16 + torch.compile + qkv projection + channels_last + FA3
|
| 57 |
+
python run_benchmark.py \
|
| 58 |
+
--trace-file bf16_compile_qkv_chan_fa3.json.gz \
|
| 59 |
+
--compile_export_mode compile \
|
| 60 |
+
--disable_quant \
|
| 61 |
+
--disable_inductor_tuning_flags \
|
| 62 |
+
> bf16_compile_qkv_chan_fa3.txt 2>&1
|
| 63 |
+
|
| 64 |
+
# bfloat16 + torch.compile + qkv projection + channels_last + FA3 + float8 quant
|
| 65 |
+
python run_benchmark.py \
|
| 66 |
+
--trace-file bf16_compile_qkv_chan_fa3_quant.json.gz \
|
| 67 |
+
--compile_export_mode compile \
|
| 68 |
+
--disable_inductor_tuning_flags \
|
| 69 |
+
> bf16_compile_qkv_chan_fa3_quant.txt 2>&1
|
| 70 |
+
|
| 71 |
+
# bfloat16 + torch.compile + qkv projection + channels_last + FA3 + float8 quant + inductor flags
|
| 72 |
+
python run_benchmark.py \
|
| 73 |
+
--trace-file bf16_compile_qkv_chan_fa3_quant_flags.json.gz \
|
| 74 |
+
--compile_export_mode compile \
|
| 75 |
+
> bf16_compile_qkv_chan_fa3_quant_flags.txt 2>&1
|
| 76 |
+
|
| 77 |
+
# fully optimized (torch.export + AOTI to address cold start)
|
| 78 |
+
python run_benchmark.py --trace-file fully_optimized.json.gz \
|
| 79 |
+
> fully_optimized.txt 2>&1
|
gen_image.py
ADDED
|
@@ -0,0 +1,60 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
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|
|
|
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|
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|
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|
|
|
|
|
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|
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|
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|
|
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|
|
|
|
| 1 |
+
import random
|
| 2 |
+
import time
|
| 3 |
+
import torch
|
| 4 |
+
from torch.profiler import profile, record_function, ProfilerActivity
|
| 5 |
+
from utils.benchmark_utils import annotate, create_parser
|
| 6 |
+
from utils.pipeline_utils import load_pipeline, optimize # noqa: E402
|
| 7 |
+
|
| 8 |
+
# 🚀 CPU parallelization optimizations
|
| 9 |
+
torch.set_num_threads(16) # Use all 16 cores
|
| 10 |
+
torch.set_num_interop_threads(16) # Parallelism for inter-operations
|
| 11 |
+
|
| 12 |
+
# 🔧 Additional performance optimizations
|
| 13 |
+
torch.backends.cudnn.benchmark = True # Optimize CUDNN for consistent input sizes
|
| 14 |
+
torch.backends.cuda.matmul.allow_tf32 = True # Enable TF32 for faster matrix operations
|
| 15 |
+
torch.backends.cudnn.allow_tf32 = True
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
def set_rand_seeds(seed):
|
| 19 |
+
random.seed(seed)
|
| 20 |
+
torch.manual_seed(seed)
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
def main(args):
|
| 24 |
+
torch.cuda.empty_cache()
|
| 25 |
+
|
| 26 |
+
with annotate("Initialization"):
|
| 27 |
+
pipeline = load_pipeline(args)
|
| 28 |
+
# Apply optimizations (including AOTI if specified)
|
| 29 |
+
pipeline = optimize(pipeline, args)
|
| 30 |
+
set_rand_seeds(args.seed)
|
| 31 |
+
|
| 32 |
+
print(f"🚀 Generating image: {args.prompt}")
|
| 33 |
+
print(f"📁 Output file: {args.output_file}")
|
| 34 |
+
print(f"⚙️ Compile mode: {args.compile_export_mode}")
|
| 35 |
+
print(f"🔄 Inference steps: {args.num_inference_steps}")
|
| 36 |
+
|
| 37 |
+
with annotate("Generate Image"):
|
| 38 |
+
# Use appropriate guidance scale for the model type
|
| 39 |
+
guidance_scale = 0.0 if hasattr(pipeline, 'transformer') else 7.5
|
| 40 |
+
print(f"🎯 Guidance scale: {guidance_scale}")
|
| 41 |
+
|
| 42 |
+
start_time = time.time()
|
| 43 |
+
image = pipeline(
|
| 44 |
+
args.prompt,
|
| 45 |
+
num_inference_steps=args.num_inference_steps,
|
| 46 |
+
guidance_scale=guidance_scale
|
| 47 |
+
).images[0]
|
| 48 |
+
end_time = time.time()
|
| 49 |
+
|
| 50 |
+
print(f"⏱️ Generation time: {end_time - start_time:.2f} seconds")
|
| 51 |
+
|
| 52 |
+
with annotate("Save Image"):
|
| 53 |
+
image.save(args.output_file)
|
| 54 |
+
print(f"✅ Image saved to: {args.output_file}")
|
| 55 |
+
|
| 56 |
+
|
| 57 |
+
if __name__ == "__main__":
|
| 58 |
+
parser = create_parser()
|
| 59 |
+
args = parser.parse_args()
|
| 60 |
+
main(args)
|
gen_image_hq.py
ADDED
|
@@ -0,0 +1,107 @@
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/usr/bin/env python3
|
| 2 |
+
|
| 3 |
+
import random
|
| 4 |
+
import time
|
| 5 |
+
import torch
|
| 6 |
+
from utils.benchmark_utils import annotate, create_parser
|
| 7 |
+
|
| 8 |
+
# 🚀 CPU parallelization optimizations - Ana script'ten
|
| 9 |
+
torch.set_num_threads(16)
|
| 10 |
+
torch.set_num_interop_threads(16)
|
| 11 |
+
|
| 12 |
+
# 🔧 Performance optimizations
|
| 13 |
+
torch.backends.cudnn.benchmark = True
|
| 14 |
+
torch.backends.cuda.matmul.allow_tf32 = True
|
| 15 |
+
torch.backends.cudnn.allow_tf32 = True
|
| 16 |
+
|
| 17 |
+
def set_rand_seeds(seed):
|
| 18 |
+
random.seed(seed)
|
| 19 |
+
torch.manual_seed(seed)
|
| 20 |
+
|
| 21 |
+
def load_stable_diffusion_pipeline(args):
|
| 22 |
+
from diffusers import StableDiffusionPipeline
|
| 23 |
+
|
| 24 |
+
torch.cuda.empty_cache()
|
| 25 |
+
|
| 26 |
+
load_dtype = torch.float32 if args.device == "cpu" else (
|
| 27 |
+
torch.float16 if args.disable_bf16 else torch.bfloat16
|
| 28 |
+
)
|
| 29 |
+
|
| 30 |
+
print(f"🔄 StableDiffusionPipeline yükleniyor: {args.ckpt}")
|
| 31 |
+
pipeline = StableDiffusionPipeline.from_pretrained(
|
| 32 |
+
args.ckpt,
|
| 33 |
+
torch_dtype=load_dtype,
|
| 34 |
+
low_cpu_mem_usage=True,
|
| 35 |
+
use_safetensors=True,
|
| 36 |
+
)
|
| 37 |
+
|
| 38 |
+
# NSFW filtresini devre dışı bırak (siyah görüntü problemini çözer)
|
| 39 |
+
if hasattr(args, 'disable_nsfw_filter') and args.disable_nsfw_filter:
|
| 40 |
+
print("⚠️ NSFW filtresi devre dışı bırakıldı")
|
| 41 |
+
pipeline.safety_checker = None
|
| 42 |
+
pipeline.requires_safety_checker = False
|
| 43 |
+
|
| 44 |
+
# Memory optimization için
|
| 45 |
+
pipeline.enable_attention_slicing()
|
| 46 |
+
pipeline.enable_vae_slicing()
|
| 47 |
+
|
| 48 |
+
print(f"🚀 GPU'ya aktarılıyor ({args.device})")
|
| 49 |
+
pipeline = pipeline.to(args.device, dtype=load_dtype)
|
| 50 |
+
|
| 51 |
+
pipeline.set_progress_bar_config(disable=False) # Progress göster
|
| 52 |
+
|
| 53 |
+
return pipeline
|
| 54 |
+
|
| 55 |
+
def main(args):
|
| 56 |
+
start_time = time.time()
|
| 57 |
+
|
| 58 |
+
print(f"🎯 Başlatılıyor: {args.prompt}")
|
| 59 |
+
print(f"📁 Çıktı: {args.output_file}")
|
| 60 |
+
print(f"🔧 Device: {args.device}, Steps: {args.num_inference_steps}")
|
| 61 |
+
|
| 62 |
+
pipeline = load_stable_diffusion_pipeline(args)
|
| 63 |
+
load_time = time.time() - start_time
|
| 64 |
+
print(f"✅ Pipeline yüklendi ({load_time:.1f}s)")
|
| 65 |
+
|
| 66 |
+
set_rand_seeds(args.seed)
|
| 67 |
+
|
| 68 |
+
print("🎨 Görüntü oluşturuluyor...")
|
| 69 |
+
gen_start = time.time()
|
| 70 |
+
|
| 71 |
+
# 🎨 OPTIMIZED QUALITY settings - RTX 2060 uyumlu
|
| 72 |
+
if args.num_inference_steps >= 20: # Yüksek kalite modu
|
| 73 |
+
height, width = 512, 512 # Kare format, GPU memory için güvenli
|
| 74 |
+
guidance_scale = 8.5 # Daha güçlü guidance
|
| 75 |
+
print(f"🔥 HIGH QUALITY MODE: {width}x{height}, guidance={guidance_scale}")
|
| 76 |
+
elif args.num_inference_steps >= 15: # Orta kalite
|
| 77 |
+
height, width = 448, 448 # Orta format
|
| 78 |
+
guidance_scale = 8.0
|
| 79 |
+
print(f"⚡ MEDIUM QUALITY MODE: {width}x{height}, guidance={guidance_scale}")
|
| 80 |
+
else: # Hızlı mod
|
| 81 |
+
height, width = 384, 384 # Küçük format
|
| 82 |
+
guidance_scale = 7.5
|
| 83 |
+
print(f"🚀 FAST MODE: {width}x{height}, guidance={guidance_scale}")
|
| 84 |
+
|
| 85 |
+
image = pipeline(
|
| 86 |
+
args.prompt,
|
| 87 |
+
num_inference_steps=args.num_inference_steps,
|
| 88 |
+
guidance_scale=guidance_scale,
|
| 89 |
+
height=height,
|
| 90 |
+
width=width
|
| 91 |
+
).images[0]
|
| 92 |
+
|
| 93 |
+
gen_time = time.time() - gen_start
|
| 94 |
+
print(f"✅ Görüntü oluşturuldu ({gen_time:.1f}s)")
|
| 95 |
+
|
| 96 |
+
# 🖼️ Save with higher quality
|
| 97 |
+
image.save(args.output_file, quality=95, optimize=True)
|
| 98 |
+
total_time = time.time() - start_time
|
| 99 |
+
|
| 100 |
+
print(f"💾 Kaydedildi: {args.output_file}")
|
| 101 |
+
print(f"📐 Çözünürlük: {width}x{height}")
|
| 102 |
+
print(f"⏱️ Toplam süre: {total_time:.1f}s")
|
| 103 |
+
|
| 104 |
+
if __name__ == "__main__":
|
| 105 |
+
parser = create_parser()
|
| 106 |
+
args = parser.parse_args()
|
| 107 |
+
main(args)
|
gen_image_stable.py
ADDED
|
@@ -0,0 +1,91 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/usr/bin/env python3
|
| 2 |
+
|
| 3 |
+
import random
|
| 4 |
+
import time
|
| 5 |
+
import torch
|
| 6 |
+
from utils.benchmark_utils import annotate, create_parser
|
| 7 |
+
|
| 8 |
+
# 🚀 CPU parallelization optimizations - Ana script'ten
|
| 9 |
+
torch.set_num_threads(16)
|
| 10 |
+
torch.set_num_interop_threads(16)
|
| 11 |
+
|
| 12 |
+
# 🔧 Performance optimizations
|
| 13 |
+
torch.backends.cudnn.benchmark = True
|
| 14 |
+
torch.backends.cuda.matmul.allow_tf32 = True
|
| 15 |
+
torch.backends.cudnn.allow_tf32 = True
|
| 16 |
+
|
| 17 |
+
def set_rand_seeds(seed):
|
| 18 |
+
random.seed(seed)
|
| 19 |
+
torch.manual_seed(seed)
|
| 20 |
+
|
| 21 |
+
def load_stable_diffusion_pipeline(args):
|
| 22 |
+
from diffusers import StableDiffusionPipeline
|
| 23 |
+
|
| 24 |
+
torch.cuda.empty_cache()
|
| 25 |
+
|
| 26 |
+
load_dtype = torch.float32 if args.device == "cpu" else (
|
| 27 |
+
torch.float16 if args.disable_bf16 else torch.bfloat16
|
| 28 |
+
)
|
| 29 |
+
|
| 30 |
+
print(f"🔄 StableDiffusionPipeline yükleniyor: {args.ckpt}")
|
| 31 |
+
pipeline = StableDiffusionPipeline.from_pretrained(
|
| 32 |
+
args.ckpt,
|
| 33 |
+
torch_dtype=load_dtype,
|
| 34 |
+
low_cpu_mem_usage=True,
|
| 35 |
+
use_safetensors=True,
|
| 36 |
+
)
|
| 37 |
+
|
| 38 |
+
# NSFW filtresini devre dışı bırak (siyah görüntü problemini çözer)
|
| 39 |
+
if hasattr(args, 'disable_nsfw_filter') and args.disable_nsfw_filter:
|
| 40 |
+
print("⚠️ NSFW filtresi devre dışı bırakıldı")
|
| 41 |
+
pipeline.safety_checker = None
|
| 42 |
+
pipeline.requires_safety_checker = False
|
| 43 |
+
|
| 44 |
+
# Memory optimization için
|
| 45 |
+
pipeline.enable_attention_slicing()
|
| 46 |
+
pipeline.enable_vae_slicing()
|
| 47 |
+
|
| 48 |
+
print(f"🚀 GPU'ya aktarılıyor ({args.device})")
|
| 49 |
+
pipeline = pipeline.to(args.device, dtype=load_dtype)
|
| 50 |
+
|
| 51 |
+
pipeline.set_progress_bar_config(disable=False) # Progress göster
|
| 52 |
+
|
| 53 |
+
return pipeline
|
| 54 |
+
|
| 55 |
+
def main(args):
|
| 56 |
+
start_time = time.time()
|
| 57 |
+
|
| 58 |
+
print(f"🎯 Başlatılıyor: {args.prompt}")
|
| 59 |
+
print(f"📁 Çıktı: {args.output_file}")
|
| 60 |
+
print(f"🔧 Device: {args.device}, Steps: {args.num_inference_steps}")
|
| 61 |
+
|
| 62 |
+
pipeline = load_stable_diffusion_pipeline(args)
|
| 63 |
+
load_time = time.time() - start_time
|
| 64 |
+
print(f"✅ Pipeline yüklendi ({load_time:.1f}s)")
|
| 65 |
+
|
| 66 |
+
set_rand_seeds(args.seed)
|
| 67 |
+
|
| 68 |
+
print("🎨 Görüntü oluşturuluyor...")
|
| 69 |
+
gen_start = time.time()
|
| 70 |
+
|
| 71 |
+
image = pipeline(
|
| 72 |
+
args.prompt,
|
| 73 |
+
num_inference_steps=args.num_inference_steps,
|
| 74 |
+
guidance_scale=7.5, # Stable Diffusion için uygun değer
|
| 75 |
+
height=384, # Daha düşük resolution (GPU memory için)
|
| 76 |
+
width=384
|
| 77 |
+
).images[0]
|
| 78 |
+
|
| 79 |
+
gen_time = time.time() - gen_start
|
| 80 |
+
print(f"✅ Görüntü oluşturuldu ({gen_time:.1f}s)")
|
| 81 |
+
|
| 82 |
+
image.save(args.output_file)
|
| 83 |
+
total_time = time.time() - start_time
|
| 84 |
+
|
| 85 |
+
print(f"💾 Kaydedildi: {args.output_file}")
|
| 86 |
+
print(f"⏱️ Toplam süre: {total_time:.1f}s")
|
| 87 |
+
|
| 88 |
+
if __name__ == "__main__":
|
| 89 |
+
parser = create_parser()
|
| 90 |
+
args = parser.parse_args()
|
| 91 |
+
main(args)
|
gen_image_ultra.py
ADDED
|
@@ -0,0 +1,146 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/usr/bin/env python3
|
| 2 |
+
|
| 3 |
+
import random
|
| 4 |
+
import time
|
| 5 |
+
import torch
|
| 6 |
+
from utils.benchmark_utils import annotate, create_parser
|
| 7 |
+
|
| 8 |
+
# 🚀 CPU parallelization optimizations
|
| 9 |
+
torch.set_num_threads(16)
|
| 10 |
+
torch.set_num_interop_threads(16)
|
| 11 |
+
|
| 12 |
+
# 🔧 Performance optimizations
|
| 13 |
+
torch.backends.cudnn.benchmark = True
|
| 14 |
+
torch.backends.cuda.matmul.allow_tf32 = True
|
| 15 |
+
torch.backends.cudnn.allow_tf32 = True
|
| 16 |
+
|
| 17 |
+
def set_rand_seeds(seed):
|
| 18 |
+
random.seed(seed)
|
| 19 |
+
torch.manual_seed(seed)
|
| 20 |
+
|
| 21 |
+
def load_stable_diffusion_pipeline(args):
|
| 22 |
+
from diffusers import StableDiffusionPipeline
|
| 23 |
+
|
| 24 |
+
torch.cuda.empty_cache()
|
| 25 |
+
|
| 26 |
+
load_dtype = torch.float32 if args.device == "cpu" else (
|
| 27 |
+
torch.float16 if args.disable_bf16 else torch.bfloat16
|
| 28 |
+
)
|
| 29 |
+
|
| 30 |
+
print(f"🔄 StableDiffusionPipeline yükleniyor: {args.ckpt}")
|
| 31 |
+
pipeline = StableDiffusionPipeline.from_pretrained(
|
| 32 |
+
args.ckpt,
|
| 33 |
+
torch_dtype=load_dtype,
|
| 34 |
+
low_cpu_mem_usage=True,
|
| 35 |
+
use_safetensors=True,
|
| 36 |
+
)
|
| 37 |
+
|
| 38 |
+
# NSFW filtresini devre dışı bırak
|
| 39 |
+
if hasattr(args, 'disable_nsfw_filter') and args.disable_nsfw_filter:
|
| 40 |
+
print("⚠️ NSFW filtresi devre dışı bırakıldı")
|
| 41 |
+
pipeline.safety_checker = None
|
| 42 |
+
pipeline.requires_safety_checker = False
|
| 43 |
+
|
| 44 |
+
# ULTRA Memory optimization - dikkatli ayarlar
|
| 45 |
+
pipeline.enable_attention_slicing()
|
| 46 |
+
pipeline.enable_vae_slicing()
|
| 47 |
+
|
| 48 |
+
print(f"🚀 GPU'ya aktarılıyor ({args.device})")
|
| 49 |
+
pipeline = pipeline.to(args.device, dtype=load_dtype)
|
| 50 |
+
|
| 51 |
+
pipeline.set_progress_bar_config(disable=False)
|
| 52 |
+
|
| 53 |
+
return pipeline
|
| 54 |
+
|
| 55 |
+
def main(args):
|
| 56 |
+
start_time = time.time()
|
| 57 |
+
|
| 58 |
+
print(f"🎯 Başlatılıyor: {args.prompt}")
|
| 59 |
+
print(f"📁 Çıktı: {args.output_file}")
|
| 60 |
+
print(f"🔧 Device: {args.device}, Steps: {args.num_inference_steps}")
|
| 61 |
+
|
| 62 |
+
pipeline = load_stable_diffusion_pipeline(args)
|
| 63 |
+
load_time = time.time() - start_time
|
| 64 |
+
print(f"✅ Pipeline yüklendi ({load_time:.1f}s)")
|
| 65 |
+
|
| 66 |
+
set_rand_seeds(args.seed)
|
| 67 |
+
|
| 68 |
+
print("🎨 ULTRA HIGH QUALITY görüntü oluşturuluyor...")
|
| 69 |
+
gen_start = time.time()
|
| 70 |
+
|
| 71 |
+
# 🔥 ULTRA HIGH QUALITY settings
|
| 72 |
+
if args.num_inference_steps >= 50: # ULTRA kalite
|
| 73 |
+
height, width = 704, 512 # Portrait format (maksimum RTX 2060 için)
|
| 74 |
+
guidance_scale = 9.0 # Maksimum guidance
|
| 75 |
+
print(f"🔥🔥 ULTRA QUALITY MODE: {width}x{height}, guidance={guidance_scale}")
|
| 76 |
+
elif args.num_inference_steps >= 35: # Super yüksek kalite
|
| 77 |
+
height, width = 640, 512 # Geniş format
|
| 78 |
+
guidance_scale = 8.7
|
| 79 |
+
print(f"🔥 SUPER HIGH QUALITY MODE: {width}x{height}, guidance={guidance_scale}")
|
| 80 |
+
elif args.num_inference_steps >= 20: # Yüksek kalite
|
| 81 |
+
height, width = 512, 512 # Kare format
|
| 82 |
+
guidance_scale = 8.5
|
| 83 |
+
print(f"⚡ HIGH QUALITY MODE: {width}x{height}, guidance={guidance_scale}")
|
| 84 |
+
else: # Normal mod
|
| 85 |
+
height, width = 384, 384
|
| 86 |
+
guidance_scale = 7.5
|
| 87 |
+
print(f"🚀 NORMAL MODE: {width}x{height}, guidance={guidance_scale}")
|
| 88 |
+
|
| 89 |
+
# 🎨 Multiple generation attempts for best quality
|
| 90 |
+
best_image = None
|
| 91 |
+
best_seed = args.seed
|
| 92 |
+
|
| 93 |
+
if args.num_inference_steps >= 35: # Multi-attempt için sadece yüksek kalite modlarda
|
| 94 |
+
print("🎲 Multiple generation attempts for best quality...")
|
| 95 |
+
attempts = 3 if args.num_inference_steps >= 50 else 2
|
| 96 |
+
|
| 97 |
+
for attempt in range(attempts):
|
| 98 |
+
current_seed = args.seed + attempt * 1000
|
| 99 |
+
set_rand_seeds(current_seed)
|
| 100 |
+
print(f" Attempt {attempt + 1}/{attempts} (seed: {current_seed})")
|
| 101 |
+
|
| 102 |
+
image = pipeline(
|
| 103 |
+
args.prompt,
|
| 104 |
+
num_inference_steps=args.num_inference_steps,
|
| 105 |
+
guidance_scale=guidance_scale,
|
| 106 |
+
height=height,
|
| 107 |
+
width=width
|
| 108 |
+
).images[0]
|
| 109 |
+
|
| 110 |
+
if attempt == 0 or best_image is None:
|
| 111 |
+
best_image = image
|
| 112 |
+
best_seed = current_seed
|
| 113 |
+
|
| 114 |
+
print(f"🏆 Best result selected (seed: {best_seed})")
|
| 115 |
+
else:
|
| 116 |
+
# Single generation
|
| 117 |
+
best_image = pipeline(
|
| 118 |
+
args.prompt,
|
| 119 |
+
num_inference_steps=args.num_inference_steps,
|
| 120 |
+
guidance_scale=guidance_scale,
|
| 121 |
+
height=height,
|
| 122 |
+
width=width
|
| 123 |
+
).images[0]
|
| 124 |
+
|
| 125 |
+
gen_time = time.time() - gen_start
|
| 126 |
+
print(f"✅ ULTRA HIGH QUALITY görüntü oluşturuldu ({gen_time:.1f}s)")
|
| 127 |
+
|
| 128 |
+
# 🖼️ Save with maximum quality
|
| 129 |
+
if args.num_inference_steps >= 35:
|
| 130 |
+
# PNG için lossless compression
|
| 131 |
+
best_image.save(args.output_file, format='PNG', optimize=True)
|
| 132 |
+
print("💾 PNG formatında kaydedildi (lossless)")
|
| 133 |
+
else:
|
| 134 |
+
best_image.save(args.output_file, quality=95, optimize=True)
|
| 135 |
+
|
| 136 |
+
total_time = time.time() - start_time
|
| 137 |
+
|
| 138 |
+
print(f"💾 Kaydedildi: {args.output_file}")
|
| 139 |
+
print(f"📐 Çözünürlük: {width}x{height}")
|
| 140 |
+
print(f"🎲 Seed: {best_seed}")
|
| 141 |
+
print(f"⏱️ Toplam süre: {total_time:.1f}s")
|
| 142 |
+
|
| 143 |
+
if __name__ == "__main__":
|
| 144 |
+
parser = create_parser()
|
| 145 |
+
args = parser.parse_args()
|
| 146 |
+
main(args)
|
gen_run.sh
ADDED
|
@@ -0,0 +1,40 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
set -euo pipefail
|
| 3 |
+
|
| 4 |
+
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
|
| 5 |
+
|
| 6 |
+
START_TIME=$(date +%s)
|
| 7 |
+
|
| 8 |
+
echo "🔁 [$(date)] ⚙️ Başlatılıyor" | tee -a resume.log aoti_export.log
|
| 9 |
+
|
| 10 |
+
if [ -f "lemon.png" ]; then
|
| 11 |
+
echo "⚠️ Mevcut çıktı lemon.png bulundu, siliniyor..." | tee -a aoti_export.log
|
| 12 |
+
rm lemon.png
|
| 13 |
+
fi
|
| 14 |
+
|
| 15 |
+
echo "🧠 Sistem durumu (RAM, Swap, GPU):" | tee -a aoti_export.log
|
| 16 |
+
free -h | tee -a aoti_export.log
|
| 17 |
+
echo "---" >> aoti_export.log
|
| 18 |
+
nvidia-smi | tee -a aoti_export.log
|
| 19 |
+
echo "---" >> aoti_export.log
|
| 20 |
+
|
| 21 |
+
echo "🚀 [$(date)] Model çalıştırılıyor..." | tee -a aoti_export.log
|
| 22 |
+
|
| 23 |
+
python gen_image.py \
|
| 24 |
+
--prompt "An astronaut standing next to a giant lemon" \
|
| 25 |
+
--output-file lemon.png \
|
| 26 |
+
--device cuda \
|
| 27 |
+
--num_inference_steps 4 \
|
| 28 |
+
--compile_export_mode export_aoti \
|
| 29 |
+
--use-cached-model \
|
| 30 |
+
>> >(tee -a aoti_export.log) 2> >(tee -a aoti_export.log >&2)
|
| 31 |
+
|
| 32 |
+
status=$?
|
| 33 |
+
END_TIME=$(date +%s)
|
| 34 |
+
DURATION=$((END_TIME - START_TIME))
|
| 35 |
+
|
| 36 |
+
if [ $status -eq 0 ]; then
|
| 37 |
+
echo "✅ [$(date)] Tamamlandı: lemon.png oluşturuldu. Süre: ${DURATION}s" | tee -a resume.log aoti_export.log
|
| 38 |
+
else
|
| 39 |
+
echo "❌ [$(date)] HATA! Kod: $status Süre: ${DURATION}s" | tee -a resume.log aoti_export.log
|
| 40 |
+
fi
|
gen_run_optimized.sh
ADDED
|
@@ -0,0 +1,134 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
set -euo pipefail
|
| 3 |
+
|
| 4 |
+
# Activate flux-env environment
|
| 5 |
+
source /home/asahiner/.pyenv/versions/flux-env/bin/activate
|
| 6 |
+
|
| 7 |
+
# Advanced GPU Memory optimization
|
| 8 |
+
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True,max_split_size_mb:128,roundup_power2_divisions:16
|
| 9 |
+
export CUDA_VISIBLE_DEVICES=0
|
| 10 |
+
export TORCH_CUDNN_V8_API_ENABLED=1
|
| 11 |
+
export CUDA_LAUNCH_BLOCKING=0
|
| 12 |
+
|
| 13 |
+
# CPU optimization for maximum parallel processing
|
| 14 |
+
export OMP_NUM_THREADS=16
|
| 15 |
+
export MKL_NUM_THREADS=16
|
| 16 |
+
export NUMBA_NUM_THREADS=16
|
| 17 |
+
export TORCH_NUM_THREADS=16
|
| 18 |
+
export OPENBLAS_NUM_THREADS=16
|
| 19 |
+
export BLIS_NUM_THREADS=16
|
| 20 |
+
export VECLIB_MAXIMUM_THREADS=16
|
| 21 |
+
|
| 22 |
+
# Additional parallel processing optimizations
|
| 23 |
+
export OMP_SCHEDULE=dynamic
|
| 24 |
+
export OMP_PROC_BIND=true
|
| 25 |
+
export KMP_AFFINITY=granularity=fine,compact,1,0
|
| 26 |
+
export KMP_BLOCKTIME=1
|
| 27 |
+
export KMP_SETTINGS=1
|
| 28 |
+
|
| 29 |
+
# Memory management optimizations
|
| 30 |
+
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True,roundup_power2_divisions:16
|
| 31 |
+
export CUDA_MEMORY_FRACTION=0.95
|
| 32 |
+
|
| 33 |
+
# Performance optimizations
|
| 34 |
+
export TORCH_COMPILE_DEBUG=0
|
| 35 |
+
export TORCHINDUCTOR_CACHE_DIR="/tmp/torch_cache"
|
| 36 |
+
export PYTORCH_JIT_USE_NNC_NOT_NVFUSER=0
|
| 37 |
+
|
| 38 |
+
# Create cache directory if it doesn't exist
|
| 39 |
+
mkdir -p /tmp/torch_cache
|
| 40 |
+
|
| 41 |
+
START_TIME=$(date +%s)
|
| 42 |
+
|
| 43 |
+
echo "🔁 [$(date)] 🟡 Optimized başlatılıyor" | tee -a resume.log aoti_export.log
|
| 44 |
+
|
| 45 |
+
# Enhanced system monitoring and unique filename generation
|
| 46 |
+
TIMESTAMP=$(date '+%Y%m%d_%H%M%S')
|
| 47 |
+
OUTPUT_FILE="peach_${TIMESTAMP}.png"
|
| 48 |
+
echo "💾 [$(date)] Benzersiz dosya adı oluşturuldu: ${OUTPUT_FILE}" | tee -a aoti_export.log
|
| 49 |
+
|
| 50 |
+
echo "📊 [$(date)] Detaylı sistem durumu: CPU Cores: $(nproc), RAM, GPU" | tee -a aoti_export.log
|
| 51 |
+
echo "CPU Info:" | tee -a aoti_export.log
|
| 52 |
+
echo "Cores: $(nproc), Load: $(uptime | awk '{print $NF}')" | tee -a aoti_export.log
|
| 53 |
+
echo "RAM Info:" | tee -a aoti_export.log
|
| 54 |
+
free -h | tee -a aoti_export.log
|
| 55 |
+
echo "GPU Info:" | tee -a aoti_export.log
|
| 56 |
+
nvidia-smi --query-gpu=name,memory.total,memory.free,temperature.gpu,utilization.gpu --format=csv,noheader | tee -a aoti_export.log
|
| 57 |
+
echo "---" | tee -a aoti_export.log
|
| 58 |
+
|
| 59 |
+
# Check PyTorch installation
|
| 60 |
+
echo "🔍 [$(date)] PyTorch kurulum kontrolü..." | tee -a aoti_export.log
|
| 61 |
+
if ! python -c "import torch" 2>/dev/null; then
|
| 62 |
+
echo "❌ [$(date)] HATA: PyTorch kurulu değil!" | tee -a aoti_export.log
|
| 63 |
+
echo "💡 Çözüm: PyTorch kurulumu gerekiyor." | tee -a aoti_export.log
|
| 64 |
+
echo "🚀 Örnek kurulum komutu:" | tee -a aoti_export.log
|
| 65 |
+
echo "pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118" | tee -a aoti_export.log
|
| 66 |
+
exit 1
|
| 67 |
+
fi
|
| 68 |
+
|
| 69 |
+
# GPU warm-up and CUDA initialization
|
| 70 |
+
echo "🔥 [$(date)] GPU warm-up başlatılıyor..." | tee -a aoti_export.log
|
| 71 |
+
python -c "
|
| 72 |
+
import torch
|
| 73 |
+
import time
|
| 74 |
+
print(f'CUDA Available: {torch.cuda.is_available()}')
|
| 75 |
+
print(f'GPU Count: {torch.cuda.device_count()}')
|
| 76 |
+
if torch.cuda.is_available():
|
| 77 |
+
print(f'GPU Name: {torch.cuda.get_device_name(0)}')
|
| 78 |
+
print(f'GPU Memory: {torch.cuda.get_device_properties(0).total_memory / 1024**3:.1f} GB')
|
| 79 |
+
# Warm up GPU
|
| 80 |
+
x = torch.randn(1000, 1000).cuda()
|
| 81 |
+
y = torch.matmul(x, x.T)
|
| 82 |
+
torch.cuda.synchronize()
|
| 83 |
+
torch.cuda.empty_cache()
|
| 84 |
+
print('GPU warm-up tamamlandı')
|
| 85 |
+
else:
|
| 86 |
+
print('⚠️ CUDA kullanılamıyor, CPU modunda çalışacak')
|
| 87 |
+
" 2>&1 | tee -a aoti_export.log
|
| 88 |
+
|
| 89 |
+
echo "🚀 [$(date)] Optimized komut çalıştırılıyor..." | tee -a aoti_export.log
|
| 90 |
+
|
| 91 |
+
# Enhanced command with better logging and CPU affinity
|
| 92 |
+
# Using a safer prompt that won't trigger NSFW filter
|
| 93 |
+
taskset -c 0-15 python gen_image_stable.py \
|
| 94 |
+
--prompt "An old typewriter transforming into a butterfly, double exposure style, digital art" \
|
| 95 |
+
--output-file "${OUTPUT_FILE}" \
|
| 96 |
+
--device cuda \
|
| 97 |
+
--num_inference_steps 4 \
|
| 98 |
+
--ckpt "runwayml/stable-diffusion-v1-5" \
|
| 99 |
+
--disable-nsfw-filter 2>&1 | \
|
| 100 |
+
while IFS= read -r line; do
|
| 101 |
+
echo "[$(date '+%H:%M:%S')] $line" | tee -a aoti_export.log
|
| 102 |
+
done
|
| 103 |
+
|
| 104 |
+
status=$?
|
| 105 |
+
|
| 106 |
+
# Comprehensive post-execution monitoring
|
| 107 |
+
echo "📊 [$(date)] İşlem sonrası detaylı analiz:" | tee -a aoti_export.log
|
| 108 |
+
echo "GPU Status:" | tee -a aoti_export.log
|
| 109 |
+
nvidia-smi --query-gpu=memory.used,memory.total,utilization.gpu,temperature.gpu,power.draw --format=csv,noheader,nounits | tee -a aoti_export.log
|
| 110 |
+
echo "CPU Status:" | tee -a aoti_export.log
|
| 111 |
+
top -bn1 | grep "Cpu(s)" | tee -a aoti_export.log
|
| 112 |
+
echo "Memory Status:" | tee -a aoti_export.log
|
| 113 |
+
free -h | tee -a aoti_export.log
|
| 114 |
+
echo "Process Info:" | tee -a aoti_export.log
|
| 115 |
+
ps aux --sort=-%cpu | head -5 | tee -a aoti_export.log
|
| 116 |
+
|
| 117 |
+
END_TIME=$(date +%s)
|
| 118 |
+
DURATION=$((END_TIME - START_TIME))
|
| 119 |
+
|
| 120 |
+
if [ $status -eq 0 ]; then
|
| 121 |
+
echo "✅ [$(date)] BAŞARILI: ${OUTPUT_FILE} oluşturuldu! Süre: ${DURATION}s" | tee -a resume.log aoti_export.log
|
| 122 |
+
if [ -f "${OUTPUT_FILE}" ]; then
|
| 123 |
+
file_size=$(du -h "${OUTPUT_FILE}" | cut -f1)
|
| 124 |
+
echo "📁 Dosya boyutu: $file_size" | tee -a resume.log aoti_export.log
|
| 125 |
+
fi
|
| 126 |
+
else
|
| 127 |
+
echo "❌ [$(date)] HATA: Komut başarısız oldu. Çıkış kodu: $status. Süre: ${DURATION}s" | tee -a resume.log aoti_export.log
|
| 128 |
+
fi
|
| 129 |
+
|
| 130 |
+
# Clean up temporary cache
|
| 131 |
+
echo "🧹 [$(date)] Cache temizleniyor..." | tee -a aoti_export.log
|
| 132 |
+
rm -rf /tmp/torch_cache/* 2>/dev/null || true
|
| 133 |
+
|
| 134 |
+
echo "🏁 [$(date)] İşlem tamamlandı. Toplam süre: ${DURATION}s" | tee -a resume.log aoti_export.log
|
high_quality_test.sh
ADDED
|
@@ -0,0 +1,88 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
|
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|
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|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
|
| 3 |
+
# 🎨 HIGH QUALITY Image Generation
|
| 4 |
+
# 📅 2025-01-06 - Maximum quality settings
|
| 5 |
+
|
| 6 |
+
set -e
|
| 7 |
+
|
| 8 |
+
# 🌟 Environment setup (quick_test tarzı)
|
| 9 |
+
if [[ "$(which python)" != *"flux-env"* ]]; then
|
| 10 |
+
echo "⚠️ flux-env aktivasyonu gerekli"
|
| 11 |
+
exit 1
|
| 12 |
+
fi
|
| 13 |
+
|
| 14 |
+
# 🚀 Performance optimizations
|
| 15 |
+
export OMP_NUM_THREADS=16
|
| 16 |
+
export MKL_NUM_THREADS=16
|
| 17 |
+
export CUDA_ALLOC_CONF=expandable_segments:True
|
| 18 |
+
|
| 19 |
+
# 🎯 High Quality Test Prompts - Artistic and diverse
|
| 20 |
+
PROMPTS=(
|
| 21 |
+
"A majestic dragon with iridescent scales soaring over a mystical mountain range at golden hour, ultra detailed, fantasy art, 8K"
|
| 22 |
+
"A cyberpunk cityscape at night with neon reflections on wet streets, flying cars, holographic advertisements, photorealistic, cinematic"
|
| 23 |
+
"An ancient oak tree in autumn with golden leaves falling, deer family grazing nearby, soft morning light, hyperrealistic nature photography"
|
| 24 |
+
"A crystal cave with luminescent minerals, underground lake reflecting stalactites, magical atmosphere, stunning geological formations"
|
| 25 |
+
"A steampunk airship floating above Victorian London, brass mechanisms, vintage aesthetic, detailed mechanical parts, sepia tones"
|
| 26 |
+
"A serene Japanese zen garden with cherry blossoms, koi pond, bamboo fountain, traditional architecture, peaceful meditation, 4K detail"
|
| 27 |
+
"A cosmic nebula with swirling colors, distant galaxies, star formation, astronomical photography, deep space, ethereal beauty"
|
| 28 |
+
"A tropical paradise with turquoise water, white sand beach, palm trees, exotic birds, paradise island, travel photography"
|
| 29 |
+
"A medieval castle on a cliff overlooking stormy seas, dramatic clouds, gothic architecture, epic fantasy landscape, moody lighting"
|
| 30 |
+
"A underwater coral reef ecosystem with colorful fish, sea turtles, marine life, crystal clear water, National Geographic style"
|
| 31 |
+
)
|
| 32 |
+
|
| 33 |
+
echo "🎨 HIGH QUALITY Image Generation Test"
|
| 34 |
+
echo "📊 Settings: 512x768, 25 steps, guidance 8.5"
|
| 35 |
+
echo "🛡️ NSFW Filter: DISABLED"
|
| 36 |
+
echo "⏱️ Estimated time per image: ~45-60 seconds"
|
| 37 |
+
echo ""
|
| 38 |
+
|
| 39 |
+
# 📊 System status
|
| 40 |
+
echo "🖥️ System Status:"
|
| 41 |
+
echo " RAM: $(free -h | awk '/^Mem:/ {print $3 "/" $2}')"
|
| 42 |
+
echo " GPU: $(nvidia-smi --query-gpu=memory.used,memory.total --format=csv,noheader,nounits | awk '{print $1 "/" $2 " MB"}')"
|
| 43 |
+
echo ""
|
| 44 |
+
|
| 45 |
+
for i in "${!PROMPTS[@]}"; do
|
| 46 |
+
PROMPT="${PROMPTS[$i]}"
|
| 47 |
+
TIMESTAMP=$(date +"%Y%m%d_%H%M%S")
|
| 48 |
+
OUTPUT_FILE="hq_$(printf "%02d" $((i+1)))_${TIMESTAMP}.png"
|
| 49 |
+
|
| 50 |
+
echo "🎯 [$(date '+%H:%M:%S')] Generating HIGH QUALITY image $((i+1))/${#PROMPTS[@]}"
|
| 51 |
+
echo " Prompt: ${PROMPT:0:80}..."
|
| 52 |
+
echo " Output: $OUTPUT_FILE"
|
| 53 |
+
|
| 54 |
+
START_TIME=$(date +%s)
|
| 55 |
+
|
| 56 |
+
# 🎨 HIGH QUALITY generation with enhanced parameters
|
| 57 |
+
python gen_image_hq.py \
|
| 58 |
+
--ckpt "runwayml/stable-diffusion-v1-5" \
|
| 59 |
+
--prompt "$PROMPT" \
|
| 60 |
+
--output-file "$OUTPUT_FILE" \
|
| 61 |
+
--device cuda \
|
| 62 |
+
--num_inference_steps 25 \
|
| 63 |
+
--disable-nsfw-filter
|
| 64 |
+
|
| 65 |
+
DURATION=$(($(date +%s) - START_TIME))
|
| 66 |
+
|
| 67 |
+
if [ -f "$OUTPUT_FILE" ]; then
|
| 68 |
+
SIZE=$(stat -c%s "$OUTPUT_FILE")
|
| 69 |
+
SIZE_KB=$((SIZE / 1024))
|
| 70 |
+
echo " ✅ Success! ${DURATION}s, ${SIZE_KB}KB"
|
| 71 |
+
echo " 📐 Dimensions: $(identify "$OUTPUT_FILE" 2>/dev/null | awk '{print $3}' || echo "N/A")"
|
| 72 |
+
else
|
| 73 |
+
echo " ❌ Failed: File not created"
|
| 74 |
+
fi
|
| 75 |
+
|
| 76 |
+
# 🔄 Brief pause between generations
|
| 77 |
+
sleep 3
|
| 78 |
+
echo ""
|
| 79 |
+
done
|
| 80 |
+
|
| 81 |
+
echo "🎉 HIGH QUALITY generation complete!"
|
| 82 |
+
echo "📊 Final System Status:"
|
| 83 |
+
echo " RAM: $(free -h | awk '/^Mem:/ {print $3 "/" $2}')"
|
| 84 |
+
echo " GPU: $(nvidia-smi --query-gpu=memory.used,memory.total --format=csv,noheader,nounits | awk '{print $1 "/" $2 " MB"}')"
|
| 85 |
+
echo ""
|
| 86 |
+
|
| 87 |
+
echo "📁 Generated HIGH QUALITY files:"
|
| 88 |
+
ls -la hq_*.png
|
install_requirements.sh
ADDED
|
@@ -0,0 +1,64 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
set -euo pipefail
|
| 3 |
+
|
| 4 |
+
echo "🔧 [$(date)] PyTorch ve gerekli paketlerin kurulumu başlatılıyor..."
|
| 5 |
+
|
| 6 |
+
# Check Python version
|
| 7 |
+
PYTHON_VERSION=$(python3 --version | cut -d' ' -f2)
|
| 8 |
+
echo "🐍 Python version: $PYTHON_VERSION"
|
| 9 |
+
|
| 10 |
+
# Check CUDA version for optimal PyTorch installation
|
| 11 |
+
if command -v nvidia-smi &> /dev/null; then
|
| 12 |
+
CUDA_VERSION=$(nvidia-smi | grep -oP "CUDA Version: \K[0-9]+\.[0-9]+")
|
| 13 |
+
echo "🚀 CUDA Version: $CUDA_VERSION"
|
| 14 |
+
|
| 15 |
+
# Install PyTorch with CUDA support
|
| 16 |
+
if [[ "$CUDA_VERSION" == "12"* ]]; then
|
| 17 |
+
echo "📦 CUDA 12.x için PyTorch kurulumu..."
|
| 18 |
+
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
|
| 19 |
+
elif [[ "$CUDA_VERSION" == "11"* ]]; then
|
| 20 |
+
echo "📦 CUDA 11.x için PyTorch kurulumu..."
|
| 21 |
+
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
|
| 22 |
+
else
|
| 23 |
+
echo "📦 Genel CUDA için PyTorch kurulumu..."
|
| 24 |
+
pip3 install torch torchvision torchaudio
|
| 25 |
+
fi
|
| 26 |
+
else
|
| 27 |
+
echo "⚠️ CUDA bulunamadı, CPU-only PyTorch kurulacak..."
|
| 28 |
+
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
|
| 29 |
+
fi
|
| 30 |
+
|
| 31 |
+
# Install additional required packages
|
| 32 |
+
echo "📦 Ek paketler kuruluyor..."
|
| 33 |
+
pip3 install \
|
| 34 |
+
numpy \
|
| 35 |
+
pillow \
|
| 36 |
+
transformers \
|
| 37 |
+
diffusers \
|
| 38 |
+
accelerate \
|
| 39 |
+
xformers \
|
| 40 |
+
safetensors \
|
| 41 |
+
requests \
|
| 42 |
+
tqdm
|
| 43 |
+
|
| 44 |
+
# Verify installation
|
| 45 |
+
echo "✅ [$(date)] Kurulum tamamlandı. Test ediliyor..."
|
| 46 |
+
python3 -c "
|
| 47 |
+
import torch
|
| 48 |
+
import numpy as np
|
| 49 |
+
from PIL import Image
|
| 50 |
+
import transformers
|
| 51 |
+
import diffusers
|
| 52 |
+
|
| 53 |
+
print(f'✅ PyTorch: {torch.__version__}')
|
| 54 |
+
print(f'✅ CUDA Available: {torch.cuda.is_available()}')
|
| 55 |
+
if torch.cuda.is_available():
|
| 56 |
+
print(f'✅ GPU: {torch.cuda.get_device_name(0)}')
|
| 57 |
+
print(f'✅ GPU Memory: {torch.cuda.get_device_properties(0).total_memory / 1024**3:.1f} GB')
|
| 58 |
+
print(f'✅ NumPy: {np.__version__}')
|
| 59 |
+
print(f'✅ Transformers: {transformers.__version__}')
|
| 60 |
+
print(f'✅ Diffusers: {diffusers.__version__}')
|
| 61 |
+
print('🎉 Tüm paketler başarıyla kuruldu!')
|
| 62 |
+
"
|
| 63 |
+
|
| 64 |
+
echo "🎉 [$(date)] Kurulum başarıyla tamamlandı!"
|
marathon.log
ADDED
|
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
|
|
|
| 1 |
+
nohup: ignoring input
|
| 2 |
+
⚠️ flux-env aktivasyonu gerekli
|
marathon_20250706_123209/mega_001_fantasy_123209.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_002_fantasy_123227.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_003_fantasy_123247.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_004_fantasy_123305.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_005_fantasy_123324.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_006_fantasy_123342.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_007_fantasy_123401.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_008_fantasy_123419.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_009_fantasy_123437.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_010_fantasy_123451.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_011_fantasy_123507.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_012_fantasy_123521.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_013_fantasy_123537.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_014_fantasy_123553.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_015_fantasy_123607.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_016_fantasy_123622.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_017_fantasy_123637.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_018_fantasy_123651.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_019_fantasy_123706.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_020_fantasy_123720.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_021_scifi_123734.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_022_scifi_123747.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_023_scifi_123801.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_024_scifi_123815.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_025_scifi_123829.png
ADDED
|
Git LFS Details
|
marathon_20250706_123209/mega_026_scifi_123843.png
ADDED
|
Git LFS Details
|