baichuan build.py  killed

A100
64G mem
Tue Oct 31 08:04:34 2023
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.86.10              Driver Version: 535.86.10    CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA A100-PCIE-40GB          Off | 00000000:CA:00.0 Off |                    0 |
| N/A   31C    P0              33W / 250W |      4MiB / 40960MiB |      0%      Default |
|                                         |                      |             Disabled |
python build.py --model_version v2_13b                 --model_dir ./../../../models_llm/LLM_Model/baichuan2-13b-chat                 --dtype float16                 --use_gemm_plugin float16                 --use_gpt_attention_plugin float16                 --output_dir ./tmp/baichuan_v1_13b/trt_engines/fp16/1-gpu/
[10/31/2023-07:59:41] [TRT-LLM] [I] Serially build TensorRT engines.
[10/31/2023-07:59:41] [TRT] [I] [MemUsageChange] Init CUDA: CPU +2, GPU +0, now: CPU 117, GPU 427 (MiB)
[10/31/2023-07:59:43] [TRT] [I] [MemUsageChange] Init builder kernel library: CPU +1974, GPU +350, now: CPU 2226, GPU 777 (MiB)
[10/31/2023-07:59:43] [TRT-LLM] [W] Invalid timing cache, using freshly created one
[10/31/2023-07:59:51] [TRT-LLM] [I] Loading HF Baichuan v2_13b ... from ./../../../models_llm/LLM_Model/baichuan2-13b-chat
[10/31/2023-07:59:59] Xformers is not installed correctly. If you want to use memory_efficient_attention to accelerate training use the following command to install Xformers
pip install xformers.
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [02:58<00:00, 59.43s/it]
[10/31/2023-08:02:57] [TRT-LLM] [I] HF Baichuan v2_13b loaded. Total time: 00:03:06
[10/31/2023-08:02:57] [TRT-LLM] [I] Loading weights from HF Baichuan v2_13b...
[10/31/2023-08:03:05] [TRT-LLM] [I] Normalizing lm_head.weight for v2_13b
[10/31/2023-08:03:07] [TRT-LLM] [I] Weights loaded. Total time: 00:00:10
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/vocab_embedding/GATHER_0_output_0 and BaichuanForCausalLM/layers/0/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/0/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/0/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/0/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/0/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/0/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/0/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/0/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/1/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/1/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/1/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/1/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/1/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/1/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/1/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/1/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/2/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/2/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/2/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/2/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/2/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/2/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/2/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/2/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/3/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/3/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/3/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/3/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/3/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/3/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/3/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/3/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/4/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/4/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/4/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/4/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/4/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/4/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/4/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/4/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/5/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/5/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/5/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/5/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/5/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/5/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/5/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/5/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/6/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/6/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/6/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/6/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/6/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/6/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/6/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/6/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/7/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/7/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/7/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/7/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/7/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/7/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/7/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/7/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/8/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/8/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/8/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/8/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/8/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/8/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/8/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/8/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/9/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/9/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/9/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/9/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/9/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/9/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/9/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/9/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/10/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/10/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/10/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/10/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/10/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/10/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/10/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/10/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/11/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/11/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/11/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/11/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/11/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/11/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/11/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/11/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/12/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/12/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/12/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/12/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/12/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/12/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/12/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/12/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/13/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/13/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/13/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/13/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/13/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/13/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/13/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/13/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/14/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/14/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/14/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/14/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/14/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/14/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/14/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/14/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/15/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/15/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/15/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/15/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/15/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/15/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/15/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/15/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/16/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/16/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/16/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/16/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/16/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/16/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/16/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/16/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/17/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/17/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/17/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/17/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/17/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/17/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/17/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/17/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/18/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/18/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/18/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/18/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/18/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/18/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/18/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/18/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/19/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/19/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/19/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/19/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/19/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/19/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/19/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/19/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/20/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/20/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/20/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/20/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/20/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/20/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/20/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/20/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/21/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/21/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/21/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/21/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/21/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/21/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/21/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/21/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/22/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/22/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/22/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/22/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/22/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/22/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/22/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/22/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/23/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/23/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/23/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/23/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/23/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/23/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/23/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/23/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/24/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/24/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/24/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/24/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/24/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/24/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/24/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/24/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/25/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/25/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/25/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/25/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/25/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/25/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/25/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/25/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/26/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/26/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/26/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/26/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/26/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/26/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/26/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/26/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/27/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/27/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/27/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/27/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/27/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/27/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/27/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/27/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/28/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/28/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/28/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/28/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/28/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/28/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/28/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/28/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/29/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:07] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:07] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/29/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/29/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/29/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/29/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/29/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/29/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/29/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/30/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/30/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/30/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/30/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/30/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/30/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/30/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/30/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/31/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/31/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/31/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/31/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/31/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/31/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/31/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/31/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/32/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/32/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/32/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/32/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/32/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/32/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/32/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/32/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/33/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/33/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/33/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/33/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/33/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/33/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/33/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/33/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/34/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/34/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/34/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/34/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/34/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/34/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/34/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/34/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/35/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/35/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/35/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/35/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/35/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/35/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/35/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/35/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/36/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/36/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/36/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/36/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/36/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/36/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/36/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/36/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/37/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/37/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/37/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/37/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/37/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/37/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/37/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/37/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/38/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/38/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/38/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/38/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/38/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/38/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/38/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/38/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/layers/39/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/39/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/39/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/39/ELEMENTWISE_SUM_0_output_0 and BaichuanForCausalLM/layers/39/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/39/post_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/39/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/39/ELEMENTWISE_SUM_1_output_0 and BaichuanForCausalLM/ln_f/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/ln_f/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/ln_f/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[10/31/2023-08:03:08] [TRT-LLM] [I] Build TensorRT engine baichuan_float16_tp1_rank0.engine
[10/31/2023-08:03:08] [TRT] [W] Unused Input: position_ids
[10/31/2023-08:03:08] [TRT] [W] Detected layernorm nodes in FP16.
[10/31/2023-08:03:08] [TRT] [W] Running layernorm after self-attention in FP16 may cause overflow. Exporting the model to the latest available ONNX opset (later than opset 17) to use the INormalizationLayer, or forcing layernorm layers to run in FP32 precision can help with preserving accuracy.
[10/31/2023-08:03:08] [TRT] [W] [RemoveDeadLayers] Input Tensor position_ids is unused or used only at compile-time, but is not being removed.
[10/31/2023-08:03:08] [TRT] [I] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 55301, GPU 3327 (MiB)
[10/31/2023-08:03:08] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 55303, GPU 3337 (MiB)
[10/31/2023-08:03:08] [TRT] [W] TensorRT was linked against cuDNN 8.9.4 but loaded cuDNN 8.8.1
[10/31/2023-08:03:08] [TRT] [I] Global timing cache in use. Profiling results in this builder pass will be stored.
[10/31/2023-08:03:26] [TRT] [I] [GraphReduction] The approximate region cut reduction algorithm is called.
[10/31/2023-08:03:26] [TRT] [I] Detected 48 inputs and 41 output network tensors.
[10/31/2023-08:03:37] [TRT] [I] Total Host Persistent Memory: 74448
[10/31/2023-08:03:37] [TRT] [I] Total Device Persistent Memory: 0
[10/31/2023-08:03:37] [TRT] [I] Total Scratch Memory: 329257088
[10/31/2023-08:03:37] [TRT] [I] [BlockAssignment] Started assigning block shifts. This will take 688 steps to complete.
[10/31/2023-08:03:37] [TRT] [I] [BlockAssignment] Algorithm ShiftNTopDown took 26.5533ms to assign 10 blocks to 688 nodes requiring 427301888 bytes.
[10/31/2023-08:03:37] [TRT] [I] Total Activation Memory: 427301888
[10/31/2023-08:03:38] [TRT] [I] Total Weights Memory:<PHONE_NUMBER>2
[10/31/2023-08:03:38] [TRT] [I] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 56598, GPU 29855 (MiB)
[10/31/2023-08:03:38] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 56599, GPU 29865 (MiB)
[10/31/2023-08:03:38] [TRT] [W] TensorRT was linked against cuDNN 8.9.4 but loaded cuDNN 8.8.1
[10/31/2023-08:03:38] [TRT] [I] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 2455 MiB, GPU 26506 MiB
[10/31/2023-08:03:38] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in building engine: CPU +0, GPU +26506, now: CPU 0, GPU 26506 (MiB)
Killed

[Tue Oct 31 08:20:43 2023] [295656]  1000 295656    43760     2363    98304        0           985 orted
[Tue Oct 31 08:20:43 2023] Memory cgroup out of memory: Killed process 295493 (python) total-vm:226952940kB, anon-rss:66589928kB, file-rss:464460kB, shmem-rss:14364kB, UID:1000
[Tue Oct 31 08:20:43 2023] oom_reaper: reaped process 295493 (python), now anon-rss:0kB, file-rss:87324kB, shmem-rss:14364kB

@Midcc  so there is 64GB host memory in your environment? Is it convenient for you to try with larger host memory and see what happens?
June

by the way, does this error matters?
[10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision
[10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/39/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/39/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.

by the way, does this error matters? [10/31/2023-08:03:08] [TRT] [W] A shape layer can only run in INT32 precision [10/31/2023-08:03:08] [TRT] [W] IElementWiseLayer with inputs BaichuanForCausalLM/layers/39/input_layernorm/REDUCE_AVG_0_output_0 and BaichuanForCausalLM/layers/39/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.

No, they are only warning ([W]).

Close this bug because the issue is inactivated. Feel free to ask here if you still have question/issue, we will reopen the issue.


Render audio graph without emitting to the speakers

This is the third PR for #216
There are some leftover To-dos and your review comments that I will address soon. Thanks for having a look!

Hi @b-ma I would love your opinion on my latest API-compliance decision:
commit 3e33da3636f7712474a798ac1ab5a00dcea8a886

    Drop double `Option` from AudioContextOptions.sink_id

    Before: `Option<Option<String>>`
    /// - use `None` for the default device
    /// - use `Some(None)` to process the audio graph without playing through an audio output device.
    /// - use `Some(Some(sinkId))` to use the specified audio sink id, obtained with `enumerate_devices`

    After: `Option<String>`
    /// - use `None` to process the audio graph without playing through an audio output device.
    /// - use `Some("")` for the default audio output device
    /// - use `Some(sinkId)` to use the specified audio sink id, obtained with `enumerate_devices`

    We now require the user to specify `Some("")` for the default audio
    device. In the docs we suggest to use the `::default()` implementation
    so you are not required to think about it for most usecases.

Hey! yup I try to check that today or tomorrow

Hey, after reading the spec (which I agree is quite hard to understand) and read again (a bit fast) https://github.com/WebAudio/web-audio-api/issues/2400, I would personally go for the very simple:
`String`
    /// - use `""` for the default audio output device
    /// - use `"none"` to process the audio graph without playing through an audio output device.
    /// - use `sinkId` to use the specified audio sink id, obtained with `enumerate_devices`

This is not very elegant, but much more simple in my opinion... and as the sinkIds are generated by the enumerate_devices code, we can guarantee there won't be any conflicts (but I must also admit I don't really get why these AudioSyncInfo and AudioSyncOptions types are defined in the spec)
Maybe we should mark the whole thing as unstable until this is implemented in Chrome or Firefox so that we can compare with what they did, to see if we didn't miss something?

Thanks for the suggestion. Way simpler indeed.
I will leave it this way for the 0.x versions


Cardcast data

I don't know if the public xyzzy instances had any caching of cardcast data, but if yes, is there any chance you could publish a public dump of the cached data somewhere?

I've also thought of that but the cache is stored with a SoftReference which is deleted by the garbage collector as soon as it doesn't have any more references to it. After the games using it have been removed it is likely to disappear.
Trying to take a memory dump will do no harm tough.

There's almost certainly nothing left in them after a week. The servers are constantly GCing. This is JVM memory usage for the past day; each time it goes down, the GC has run.


update alpine image to v3.14.2

How to categorize this PR?

/area security
/kind enhancement
What this PR does / why we need it:
Update alpine image to v3.14.2 to have the latest security fixes in.
Special notes for your reviewer:
Release note:

none

/cc: @timuthy

From @vpnachev , I know:

Please, avoid upgrading OCI images to use alpine 3.14 as there are breaking syscal changes that requires runc >=v1.0.0-rc93 , but we still have a lot of nodes that are on older versions.

From @vpnachev , I know:

Please, avoid upgrading OCI images to use alpine 3.14 as there are breaking syscal changes that requires runc >=v1.0.0-rc93 , but we still have a lot of nodes that are on older versions.

If you rely on v3.13.5, I will upload the image as well and update the PR.

If you rely on v3.13.5, I will upload the image as well and update the PR.

Yes, let's prefer 3.13.5.

Updated the PR.


Node not indentified as underutilized

What version of descheduler are you using?
descheduler version: 0.18.0
Does this issue reproduce with the latest release?
Yes
Which descheduler CLI options are you using?
        - "--policy-config-file"
        - "/policy-dir/policy.yaml"
        - "--v"
        - "3"
        - "--node-selector"
        - "node-role.kubernetes.io/production=true"

Please provide a copy of your descheduler policy config file
apiVersion: "descheduler/v1alpha1"
kind: "DeschedulerPolicy"
strategies:
  "RemoveDuplicates":
     enabled: true
  "RemovePodsViolatingInterPodAntiAffinity":
     enabled: true
  "LowNodeUtilization":
     enabled: true
     params:
       nodeResourceUtilizationThresholds:
         thresholds:
           "cpu" : 30
           "memory": 30
           "pods": 30
         targetThresholds:
           "cpu" : 50
           "memory": 50
           "pods": 70

What k8s version are you using (kubectl version)?
kubectl version Output
$ kubectl version
Client Version: version.Info{Major:"1", Minor:"18", GitVersion:"v1.18.8", GitCommit:"9f2892aab98fe339f3bd70e3c470144299398ace", GitTreeState:"clean", BuildDate:"2020-08-14T11:09:22Z", GoVersion:"go1.14.7", Compiler:"gc", Platform:"darwin/amd64"}
Server Version: version.Info{Major:"1", Minor:"16", GitVersion:"v1.16.7", GitCommit:"be3d344ed06bff7a4fc60656200a93c74f31f9a4", GitTreeState:"clean", BuildDate:"2020-02-11T19:24:46Z", GoVersion:"go1.13.6", Compiler:"gc", Platform:"linux/amd64"}

What did you do?
Run the job once
What did you expect to see?
Atleast one node (k8s-node-vm-01.int.vgnett.no) is registred as underutilized.
What did you see instead?
I0820 10:43:23.889948       1 lownodeutilization.go:157] Node "k8s-node-vm-01.int.vgnett.no" is appropriately utilized with usage: api.ResourceThresholds{"cpu":6.962025316455696, "memory":7.106983524831375, "pods":6.363636363636363}
I0820 10:43:23.890119       1 lownodeutilization.go:157] Node "oa68-k8s-node-01.int.vgnett.no" is appropriately utilized with usage: api.ResourceThresholds{"cpu":35.678391959798994, "memory":15.592868177245256, "pods":48.18181818181818}
I0820 10:43:23.890284       1 lownodeutilization.go:157] Node "oa68-k8s-node-02.int.vgnett.no" is appropriately utilized with usage: api.ResourceThresholds{"cpu":22.609603340292274, "memory":20.008464895317026, "pods":66.36363636363636}
I0820 10:43:23.890397       1 lownodeutilization.go:157] Node "oa68-k8s-node-03.int.vgnett.no" is appropriately utilized with usage: api.ResourceThresholds{"cpu":17.432150313152402, "memory":18.385332871544318, "pods":53.63636363636363}
I0820 10:43:23.890526       1 lownodeutilization.go:157] Node "u89-k8s-node-02.int.vgnett.no" is appropriately utilized with usage: api.ResourceThresholds{"cpu":19.62421711899791, "memory":20.405043432173535, "pods":67.27272727272727}
I0820 10:43:23.890638       1 lownodeutilization.go:157] Node "u89-k8s-node-03.int.vgnett.no" is appropriately utilized with usage: api.ResourceThresholds{"cpu":13.883089770354905, "memory":16.56802734599502, "pods":60}
I0820 10:43:23.890658       1 lownodeutilization.go:66] Criteria for a node under utilization: CPU: 30, Mem: 30, Pods: 30
I0820 10:43:23.890680       1 lownodeutilization.go:70] No node is underutilized, nothing to do here, you might tune your thresholds further

@auduny i'm not super familiar with using the LowNodeUtilization strategy, but why do you believe the node k8s-node-vm-01.int.vgnett.no is underutilized? Can you provide the output of kubectl describe node k8s-node-vm-01.int.vgnett.no?

Because the logs says ```Node "k8s-node-vm-01.int.vgnett.no" is appropriately utilized with usage: api.ResourceThresholds{"cpu":6.962025316455696, "memory":7.106983524831375, "pods":6.363636363636363}
And i set the limits to be 30 for cpu, memory and pods. All of them are under 30 and should then be marked as underutilized? Or am I missing something here? The other nodes has over 30 pods so they are correct.

The docs says. "If a node's usage is below threshold for all (cpu, memory, and number of pods), the node is considered underutilized. "

and

"Any node between the thresholds, thresholds and targetThresholds is considered appropriately utilized and is not considered for eviction."

@auduny  Is your node Unschedulable? I think that's the only reason descheduler regard an underutilized node appropriately utilized.

/kind cleaup
/remove-kind bug
I agree we should log this, so it is less confusing. @auduny and @lixiang233 thanks for helping to track this down!

/kind cleanup

This is fixed in master with the recent refactor to this strategy in https://github.com/kubernetes-sigs/descheduler/pull/384 https://github.com/kubernetes-sigs/descheduler/blob/c9cfeb35c2724b3a49e0f95adea76ce125f15576/pkg/descheduler/strategies/lownodeutilization.go#L105-L107
(specifically, commit https://github.com/kubernetes-sigs/descheduler/pull/384/commits/9b4f781c5c902017b1b521129b3b356623d43146)
If there's any desire to backport this to 1.19 or 1.18, feel free. Otherwise we can probably consider this fixed

/close


[WFY] Update copy on WFY MarketingHeader

Per Zeplin spec: https://app.zeplin.io/project/5aabc5d2e01881c81138e58e/screen/5b744b54d9c164411cea20e5
Corresponding web PR:
https://github.com/artsy/reaction/pull/1349

LGTM!


Non-ASCII characters in OME XML metadata causes rename_tiff_channels to fail

Since the update to tifffile in the mti-utils docker image in https://github.com/goeckslab/tools-mti/pull/82, rename_tiff_channels.xml has been failing with the following error:
Traceback (most recent call last):
  File "/usr/local/lib/python3.11/site-packages/tifffile/tifffile.py", line 11543, in overwrite
    value = value.encode('ascii')
            ^^^^^^^^^^^^^^^^^^^^^
UnicodeEncodeError: 'ascii' codec can't encode character '\xb5' in position 522: ordinal not in range(128)

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/mnt/efs/fs1/cancer-usegalaxy-shared/database/jobs/075/75759/configs/tmpdv0gnsig", line 46, in <module>
    tiffcomment(os.path.join(cwd, 'renamed_image.ome.tiff'), updated_ome_xml)
  File "/usr/local/lib/python3.11/site-packages/tifffile/tifffile.py", line 24458, in tiffcomment
    tag.overwrite(comment)
  File "/usr/local/lib/python3.11/site-packages/tifffile/tifffile.py", line 11545, in overwrite
    raise ValueError(
ValueError: TIFF strings must be 7-bit ASCII

I didn't catch this in testing because the small test data didn't happen to have units specified for the physical distance, which typically contains a non-ASCII character:
PhysicalSizeXUnit="µm"
Luckily there's a seemingly simple fix found here: https://github.com/cgohlke/tifffile/issues/233
Will push a fix soon

Fixed in https://github.com/goeckslab/tools-mti/pull/84


Review and prioritise WSSS publications

I recently received the latest WSSS report which has a list of publications that I would like to review and ensure we have in our tracking sheet.
Acceptance criteria:

[ ] list of publications for H12020 report reviewed, any missing publications added to tracker
[ ] any appropriate datasets prioritised and assigned to wranglers for wrangling

these are all added to the tracker now

these are all added to the tracker now


Fix serializer failing to find source when defining source with dot syntax

Fixes this issue https://github.com/localmed/pyserializer/issues/13
@petebrowne @thatgibbyguy @reneric

👍


Don't run evaluation twice on the last epoch

This fixes the bug which resulted in 'The reported value is ignored because this step X is already reported' warning

Let me merge this PR, since we have one approval by @nzw0301. Sorry for the late.


VM runs in an infinite loop

The VM currently runs in the same page as the UI and it seems to enter infinite loops. This program locks up the entire page.

This happens as soon as the servo role is started.

oh yeah, i was just thinking about that case...

what if you remove the wait?

fixed


[material-ui] TypeError: theme.typography.pxToRem is not a function

Steps to reproduce
No response
Current behavior
Here's the screenshot:

Expected behavior
No response
Context
I've built NextJs app using Typescript (SSG only)
Your environment
System:
OS: macOS 14.3
Binaries:
Node: 18.19.1 - ~/.nvm/versions/node/v18.19.1/bin/node
npm: 10.2.4 - ~/.nvm/versions/node/v18.19.1/bin/npm
pnpm: Not Found
Browsers:
Chrome: 123.0.6312.107
Edge: Not Found
Safari: 17.3
npmPackages:
@emotion/react: ^11.11.4 => 11.11.4
@emotion/styled: ^11.11.0 => 11.11.0
@mui/base:  5.0.0-beta.39
@mui/core-downloads-tracker:  5.15.13
@mui/icons-material: ^5.15.13 => 5.15.13
@mui/material: ^5.15.13 => 5.15.13
@mui/private-theming:  5.15.13
@mui/styled-engine:  5.15.11
@mui/system:  5.15.13
@mui/types:  7.2.13
@mui/utils:  5.15.13
@types/react: ^18 => 18.2.64
react: ^18 => 18.2.0
react-dom: ^18 => 18.2.0
typescript: ^5 => 5.4.2
Search keywords: theme.typography.pxToRem is not a function

Hey, thanks for opening the issue! Could you provide a minimal reproduction? It helps us troubleshoot. A live example would be perfect. This StackBlitz sandbox template may be a good starting point.


Allow use of findUnique with MongoDB composite types

Update 05 Sep 2022:
I accidentally merged this, so I reverted it, then made a new PR. The new PR is here: https://github.com/prisma/docs/pull/3722
This docs work is done, but we need to wait until the feature actually foes out. We will need to update the version numbers in the text to [whatever version this goes into]
SME: Cristian, Daniel
Cristian and Dan have reviewed it; however, we can't merge this, because there are issues with it. Also note that we still mention 4.3, and this didn't go out with that version, so we'll need to update it.
This is NOT a preview feature

Eng ticket: https://github.com/prisma/prisma/issues/12409

Notion discussion: https://www.notion.so/prismaio/Proposal-Composite-Field-Indices-03baf2ea1865417684fdab7fda2ee007

See this section on Docs notes: https://www.notion.so/prismaio/Proposal-Composite-Field-Indices-03baf2ea1865417684fdab7fda2ee007 (the naming there is pretty convuluted)

This change relates to MongoDB only

It allows findUniques inside MongoDB embedded types

Notes:
Our docs here currently giv an example of composite findUniques as they work now:
prisma
  .user
  .findUnique({
    where: {
      firstName_lastName: {
      fullName: {
        firstName: "Paul",
        lastName: "Panther"
    }
  })

Incidentally, we should ensure we link to these examples from our main findUnique entry (if we don't already), because we don't go into this amount of detail there.
MongoDB has embedded documents. We currently don't support findUniques with them. With this new feature, composite findUniques work with MongoDB embedded types.
With this feature, you can findUnique on embedded documents, as follows:
In the schema:
@@unique([name, location.address])
@@unique([cost, location.address])

So if we want to find records with a unique attribute that is a combination of name, location.address and cost (a bit of a wacky example - we might be able to come up with a better one for the doc), our app code might be as follows:
findUniqueA(where: {
  name_location_address: {
    name: "",
    location: {
      address: ""
    }
  },
  cost_location_address: {
   cost: 1,
   location: {
     address: ""
    }
  }
})

Is this PR going to go in? Considering Prima client for a project.


[Tools] Support Azure OpenAI GPT-4 Turbo with Vision auto list deployment_name

Description
When user use Azure OpenAI GPT-4 Turbo with Vision tool in portal, after user select connection, the deployment is able to auto list available gpt4v deployment under current connection.
Validation in workspace promptflow-canary-dev:

All Promptflow Contribution checklist:

[ ] The pull request does not introduce [breaking changes].
[ ] CHANGELOG is updated for new features, bug fixes or other significant changes.
[ ] I have read the contribution guidelines.
[ ] Create an issue and link to the pull request to get dedicated review from promptflow team. Learn more: suggested workflow.

General Guidelines and Best Practices

[ ] Title of the pull request is clear and informative.
[ ] There are a small number of commits, each of which have an informative message. This means that previously merged commits do not appear in the history of the PR. For more information on cleaning up the commits in your PR, see this page.

Testing Guidelines

[ ] Pull request includes test coverage for the included changes.

please attach extension screenshot in the description


[Python3.9] Add github actions for py3.9

What changes were proposed in this pull request?

Github actions added for python3.9

How was this patch tested?

Manually
In this PR itself we can see Python 3.9 CI (checks)

Maybe let's try reusing the existing py3 CI and adding 3.9 in the matrix? I think that way we wont need a new explicit CI check and it can be expanded for more py version in the future.

Maybe let's try reusing the existing py3 CI and adding 3.9 in the matrix? I think that way we wont need a new explicit CI check and it can be expanded for more py version in the future.

Yup, good idea.


Create Card component

Instead of rendering it using CSS, create component for it

https://github.com/hellowin/kanca/pull/69


torchState Inverted after using toggleTorch

After Upgrading from 4.0.1 to 5.0.1 torchState is Inverted after using toggleTorch.
I am calling:
await controller.toggleTorch();
final state =  controller.value.torchState
torchState is on when my device flash is off and off when my device is on.
tested on android 13, POCO X5 PRO
flutter doctor -v
[√] Flutter (Channel stable, 3.19.6, on Microsoft Windows [versÆo 10.0.22631.3447], locale pt-BR)
• Flutter version 3.19.6 on channel stable at C:\Flutter\flutter
• Upstream repository https://github.com/flutter/flutter.git
• Framework revision 54e66469a9 (7 days ago), 2024-04-17 13:08:03 -0700
• Engine revision c4cd48e186
• Dart version 3.3.4
• DevTools version 2.31.1
[√] Windows Version (Installed version of Windows is version 10 or higher)
[√] Android toolchain - develop for Android devices (Android SDK version 34.0.0)
• Android SDK at C:\Users....\AppData\Local\Android\sdk
• Platform android-34, build-tools 34.0.0
• Java binary at: C:\Program Files\Android\Android Studio\jbr\bin\java
• Java version OpenJDK Runtime Environment (build 17.0.9+0--11185874)
• All Android licenses accepted.
[√] Chrome - develop for the web
• Chrome at C:\Program Files\Google\Chrome\Application\chrome.exe
[√] Visual Studio - develop Windows apps (Visual Studio Community 2022 17.9.6)
• Visual Studio at C:\Program Files\Microsoft Visual Studio\2022\Community
• Visual Studio Community 2022 version 17.9.34728.123
• Windows 10 SDK version 10.0.22621.0
[√] Android Studio (version 2023.2)
• Android Studio at C:\Program Files\Android\Android Studio
• Flutter plugin can be installed from:
https://plugins.jetbrains.com/plugin/9212-flutter
• Dart plugin can be installed from:
https://plugins.jetbrains.com/plugin/6351-dart
• Java version OpenJDK Runtime Environment (build 17.0.9+0--11185874)
[√] VS Code (version 1.88.1)
• VS Code at C:\Users....\AppData\Local\Programs\Microsoft VS Code
• Flutter extension version 3.86.0
[√] Connected device (4 available)
• 22101320I (mobile) • e6f01007 • android-arm64  • Android 14 (API 34)
• Windows (desktop)  • windows  • windows-x64    • Microsoft Windows [versÆo 10.0.22631.3447]
• Chrome (web)       • chrome   • web-javascript • Google Chrome 124.0.6367.61
• Edge (web)         • edge     • web-javascript • Microsoft Edge 123.0.2420.97
[√] Network resources
• All expected network resources are available.
• No issues found!

The new fix in version 5.0.2 defers to the native side for determining the new state of the torch, with updates coming through the torch state stream. @AndreLuizNogueira Can you verify if this fix resolves your issue?

The new fix in version 5.0.2 defers to the native side for determining the new state of the torch, with updates coming through the torch state stream. @AndreLuizNogueira Can you verify if this fix resolves your issue?

It changed, but not Immediately after calling await controller.value.torchState, and I had to add a setstate

The controller's value does not need an await, since the controller is a ValueNotifier.
Is using the controller in a ValueListenableBuilder sufficient? If not, we can look into updating the state right after calling toggleTorch(). Should be easy to do anyway, now that we also have the immediate state update when the controller is started, I think we can reduce the dependency on the torchStateStream.

Sorry. I meant await controller.toggleTorch(). It doesn't update immediately after this.

The controller's value does not need an await, since the controller is a ValueNotifier.
Is using the controller in a ValueListenableBuilder sufficient? If not, we can look into updating the state right after calling toggleTorch(). Should be easy to do anyway, now that we also have the immediate state update when the controller is started, I think we can reduce the dependency on the torchStateStream.

Sorry. I meant await controller.toggleTorch(). It doesn't update immediately after this.

Yes, currently torch updates are received only through the torch state stream. PR #1048 added the initial torch state to the start call as well, but we need to do the same for toggle torch (getting the new torch state as a result of toggle torch)


Define Voodoo_serialize, drop ppx_deriving_yojson dependency

drop the ppx_deriving_yojson dependency (that adds a lower bound on ocaml)
have the of_yojson/to_yojson in one place
have the lib as a package so it can be used in ocamlorg_package
have some unit tests

Cool, this reduces the dependencies voodoo has, and it will make voodoo-do run again for older ocaml versions.
Note: needs a patch on https://github.com/ocurrent/ocaml-docs-ci to make ocaml-docs-ci watch the src/serialize folder.
Alternatively, don't add new folders.
Currently, ocaml-docs-ci watches only

src/voodoo
src/voodoo-prep
src/voodoo-do
src/voodoo-gen

@gpetiot the base v0.15.1 requirement is stopping CI building on OCaml 5.1~beta1. It seems un-used? If so could it be removed in this PR?

It is used in the cram tests only, but I removed it in #113


Compile files in subdirectories

Update form-data module to pass the subdirectory information to the API
Recursively traverse source directories
Include the base name for all source files to be compiled

I think it looks great! We should rebase it on master and release :)
:shipit:


[ter-indent] add new options for arrays and objects

Since the last time I updated the rule there have been new changes, see:
https://github.com/eslint/eslint/compare/0643bfeff68979044ca57a2b392d855d18be7d08...dec3ec6a1d1ded6f931a0b9e31c324e3fea50550
I'll try to get these in with a couple of other rules for next minor release.

@jmlopez-rod Is this related to the issues I'm seeing in ter-indent when using it like:
.update(
  {},
  {
    returnChanges: 'always'
  }
)

@blakeembrey What's the configuration and errors you are using with the code? It could be, I'm gonna say the rule is complaining on { returnChanges: 'always' } parameter?

I'm gonna say the rule is complaining on { returnChanges: 'always' } parameter?

Yes, sorry - it is. The rule is https://github.com/blakeembrey/tslint-config-standard/blob/6d0d2f5a968e36f7b763188d32f1b019cee85c52/tslint.js#L63-L69.

This was the enhancement request I was about to file. I could use the Array and Object indent rule options that eslint has. I wanted to use this rule in tslint.yml:
    ter-indent:
        severity: error
        options:
            - 4
            -
                SwitchCase: 1
                FunctionDeclaration:
                    parameters: first
                    body: 1
                FunctionExpression:
                    parameters: first
                    body: 1
                MemberExpression: off
                CallExpression:
                    arguments: first
                ArrayExpression: first
                ObjectExpression: first
                ImportDeclaration: first

so that this passes:
    return {
               name,
               text: `You have to do ${name}`
           };

Any updates?


chore: release 2.0.1

:robot: I have created a release *beep* *boop*
2.0.1 (2022-01-17)
Bug Fixes

component schmea not find in operation (6084457)

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/keq-request/keq-cli/releases/tag/v2.0.1 :sunflower:


add stack y axis switch right not show in right

What type of PR is this?

[ ] Refactor
[ ] Feature
[x] Bug Fix
[ ] New Query Runner (Data Source)
[ ] New Alert Destination
[ ] Other

Description

How is this tested?

[ ] Unit tests (pytest, jest)
[ ] E2E Tests (Cypress)
[ ] Manually
[ ] N/A

Related Tickets & Documents

Mobile & Desktop Screenshots/Recordings (if there are UI changes)

Cool. :smile:


Tacotron multispeaker training orders speakers unreliably

No idea what could be causing it, but it seems to rely on speaker count: an 8-speaker model of mine had the inference IDs match the training ones, whereas a 20-speaker one is jumbled up. dhama the llama on Discord has been able to (eventually) find all the training voices in their 61-speaker model, so it's likely that the IDs are only being shuffled and not discarded.

bump

Will take a look.

New information that might conclude that IDs are being treated as strings inside the trainer:
Here is a list LeifEricson put together inside discord:

This is obviously incorrect sorting. This sorting is also consistent when sorting strings:

e.g "10" is where "2" should be, etc.

good catch.  just merged a fix that i think should work.


libarchive: 3.7.4 -> 3.7.6

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://github.com/libarchive/libarchive/releases.
meta.description for libarchive is: Multi-format archive and compression library
meta.homepage for libarchive is: http://libarchive.org
meta.changelog for libarchive is: https://github.com/libarchive/libarchive/releases/tag/v3.7.5
Updates performed

Version update

To inspect upstream changes

Release on GitHub

Compare changes on GitHub

Impact
Checks done

built on NixOS

[!CAUTION]
A test defined in passthru.tests did not pass.

found 3.7.5 with grep in /nix/store/npz599iipwpj25mbp8zw2b2752xxv0rb-libarchive-3.7.5
found 3.7.5 in filename of file in /nix/store/npz599iipwpj25mbp8zw2b2752xxv0rb-libarchive-3.7.5

Rebuild report (if merged into master) (click to expand)

55403 total rebuild path(s)

55402 package rebuild(s)

First fifty rebuilds by attrpath

ArchiSteamFarm
CuboCore.coreaction
CuboCore.corearchiver
CuboCore.corefm
CuboCore.coregarage
CuboCore.corehunt
CuboCore.coreimage
CuboCore.coreinfo
CuboCore.corekeyboard
CuboCore.corepad
CuboCore.corepaint
CuboCore.corepdf
CuboCore.corepins
CuboCore.corerenamer
CuboCore.coreshot
CuboCore.corestats
CuboCore.corestuff
CuboCore.coreterminal
CuboCore.coretime
CuboCore.coretoppings
CuboCore.coreuniverse
CuboCore.libcprime
CuboCore.libcsys
DisnixWebService
Fabric
LAStools
LPCNet
MMA
OSCAR
OVMF
OVMF-cloud-hypervisor
OVMFFull
QuadProgpp
R
SDL
SDL1
SDL2
SDL2_Pango
SDL2_gfx
SDL2_image
SDL2_image_2_0
SDL2_image_2_6
SDL2_mixer
SDL2_mixer_2_0
SDL2_net
SDL2_sound
SDL2_ttf
SDL_Pango
SDL_audiolib

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/npz599iipwpj25mbp8zw2b2752xxv0rb-libarchive-3.7.5 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A libarchive https://github.com/r-ryantm/nixpkgs/archive/f4907d801096ba71737466cd3f80fa48e9db6a1f.tar.gz

Or:
nix build github:r-ryantm/nixpkgs/f4907d801096ba71737466cd3f80fa48e9db6a1f#libarchive

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/npz599iipwpj25mbp8zw2b2752xxv0rb-libarchive-3.7.5
ls -la /nix/store/npz599iipwpj25mbp8zw2b2752xxv0rb-libarchive-3.7.5/bin

Pre-merge build results
NixPkgs review skipped

Maintainer pings
cc @jcumming @AndersonTorres for testing.

[!TIP]
As a maintainer, if your package is located under pkgs/by-name/*, you can comment @NixOS/nixpkgs-merge-bot merge to automatically merge this update using the nixpkgs-merge-bot.

Add a :+1: reaction to pull requests you find important.

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://github.com/libarchive/libarchive/releases.
meta.description for libarchive is: Multi-format archive and compression library
meta.homepage for libarchive is: http://libarchive.org
meta.changelog for libarchive is: https://github.com/libarchive/libarchive/releases/tag/v3.7.6
Updates performed

Version update

To inspect upstream changes

Release on GitHub

Compare changes on GitHub

Impact
Checks done

built on NixOS

[!CAUTION]
A test defined in passthru.tests did not pass.

found 3.7.6 with grep in /nix/store/qzhc612j67vqpcjbx3b33scb3ybfrz7n-libarchive-3.7.6
found 3.7.6 in filename of file in /nix/store/qzhc612j67vqpcjbx3b33scb3ybfrz7n-libarchive-3.7.6

Rebuild report (if merged into master) (click to expand)

55335 total rebuild path(s)

55334 package rebuild(s)

First fifty rebuilds by attrpath

ArchiSteamFarm
CuboCore.coreaction
CuboCore.corearchiver
CuboCore.corefm
CuboCore.coregarage
CuboCore.corehunt
CuboCore.coreimage
CuboCore.coreinfo
CuboCore.corekeyboard
CuboCore.corepad
CuboCore.corepaint
CuboCore.corepdf
CuboCore.corepins
CuboCore.corerenamer
CuboCore.coreshot
CuboCore.corestats
CuboCore.corestuff
CuboCore.coreterminal
CuboCore.coretime
CuboCore.coretoppings
CuboCore.coreuniverse
CuboCore.libcprime
CuboCore.libcsys
DisnixWebService
Fabric
LAStools
LPCNet
MMA
OSCAR
OVMF
OVMF-cloud-hypervisor
OVMFFull
QuadProgpp
R
SDL
SDL1
SDL2
SDL2_Pango
SDL2_gfx
SDL2_image
SDL2_image_2_0
SDL2_image_2_6
SDL2_mixer
SDL2_mixer_2_0
SDL2_net
SDL2_sound
SDL2_ttf
SDL_Pango
SDL_audiolib

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/qzhc612j67vqpcjbx3b33scb3ybfrz7n-libarchive-3.7.6 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A libarchive https://github.com/r-ryantm/nixpkgs/archive/3cd51572e3de79080e6ab7da2f6bafd66681f5e5.tar.gz

Or:
nix build github:r-ryantm/nixpkgs/3cd51572e3de79080e6ab7da2f6bafd66681f5e5#libarchive

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/qzhc612j67vqpcjbx3b33scb3ybfrz7n-libarchive-3.7.6
ls -la /nix/store/qzhc612j67vqpcjbx3b33scb3ybfrz7n-libarchive-3.7.6/bin

Pre-merge build results
NixPkgs review skipped

Maintainer pings
cc @jcumming @AndersonTorres for testing.

[!TIP]
As a maintainer, if your package is located under pkgs/by-name/*, you can comment @NixOS/nixpkgs-merge-bot merge to automatically merge this update using the nixpkgs-merge-bot.

Add a :+1: reaction to pull requests you find important.

Security related, it fixes CVE-2024-20696 and  CVE-2024-26256 in 3.7.5.
https://github.com/libarchive/libarchive/releases/tag/v3.7.5

Can someone from Darwin look at this?

On unsandboxed aarch64-darwin I'm getting this
Totals:
  Tests run:              622
  Tests failed:             1
  Assertions checked:29963628
  Assertions failed:        6
  Skips reported:          54

Failing tests:
  3: test_acl_platform_nfs4 (6 failures)

(when picking this update atop the current nixpkgs master)

Wait... it did pass on second or third attempt 🤦🏽   Anyway, we surely do want the RCE fix in the upcoming staging-next.


Can I catch a puback from client?

Hello, I want to see pubacks from client. Is it possible?

Hi,
this is not possible. Why do you need that?
Best regards
Christian

I want to check that the message is received by client.

Do you want to check this in the server or client? I can add a new event handler for such a situation.

I want to check this in the server.

Do you want to check this in the server or client? I can add a new event handler for such a situation.

Hello!  Have you finished this event handler?  I need to check that the message is received int the server too...

This event handler will be added in version 4.1. The myget preview feed already contains this feature.


[Addition]:

Hotspot b58 Addresses
115gJjguoipqVhF5oc2h7YswVGsZ7jHce4YFcYjdXe3mbCTwJtQ
112FXwQrxn7xUEK75vrCPAR2PaW36RswBbdB3RjQegfvahrzNJAy
112KReMFoBquBwKrwRrt4FJmsAFvG1WuCr9YfWjCTREoM3AyFgZT
112NNPe4Uvk4syRTdZ5eZ3L9ZKsBHTPaKweFvrsfbYYgEAvRqxwf
112ntRMrP1F6Ze3LLxz8LNFxZEEgwrKh6QuPWamSbkGLiz7wgzcZ
112AmmNuXSoZ4aASVX8Fgtvtyh15AZnWLSSzooeSY7Ybx6CUi66i
11RGqR9Jge2dxqTfKyNZ4Xep5NoQXz3mNjGJJJvcT9gW4LqCSPh
11Wqo44tdNQhxBb2DoWDBi9Sku4FMq8Hk5mjD4qCah78meo6xix
112oAuK1tXsZgkUnsQ98WBVVuHEfS4KVov7jGUVomoKreMyMT1iJ
1124YiwnUDYAyGWScuaCrLG6S2jy4vbS3fWeNbPfekkbMbXf6R6C
1121mCtbchxEVrLeC8NXhteGgZHEEbAg3ZPs2gkv523HjpAsduch
Discord Handle
malder
Reason(s)
This group of hotspots only witness each other, despite there being 248 other online hotspots within 25 KM

We have taken into account this addition request in the next iteration of the denylist. Some or all of the Hotspots listed may be added to the denylist. This is an automated comment due to the volume of addition and removal requests. A future tool is in the works to provide more insight into the analysis approach made by the Helium team and community members that maintain this list.


JOSS review

Hi @rg727 , I am a reviewer for your JOSS paper of statemodify and will use this issue to track things as they come up. I hope to finish this by the end of the week. Feel free to address these issues here as they come up, or create a new issue for them.
Comments:

[ ] Path error in test, I think due to my using a windows machine. Should be fixable by using os.path.join in COMP_FILE under TestModify. Though you may want to consider using pathlib throughout for a more convenient long term handling of file paths than os.

FAILED statemodify/tests/test_modify.py::TestModify::test_construct_outfile_name - AssertionError: '/my/output/directory/file_S0_test.txt' != '/my/output/directory\\file_S0_test.txt'

[ ] To avoid potential other issues like this, I think it would be sensible for your testing in automation to run on windows and macos. You would only need to add windows-latest and macos-latest into .github/workflows/build.yml.
[ ] Maybe I am impatient but I wonder if you could use a shorter selection of dates in your quickstart notebooks, perhaps just select an interesting decade (or even better a year!)? 20-30 mins doesn't feel like a particularly quick start

openjournals/joss-reviews#6325

Thanks @barneydobson , we will get on these ASAP.

@barneydobson thank you for your thorough review, we really appreciate getting this feedback! We will start to chip away at your suggestions ASAP!

Addressed in #66


Add support for soft bodies.

Soft bodies would be a useful addition to the physics engine?

More physics-related functionality is always nice, so I second this.
However, I don't think it'd be realistic to expect it for the upcoming release though (as it would be a bit of a project to implement in a way that supports everything).

problem with physics is that soft bodies are more useful when computed on
GPU. Move to vulkan on 3.0 should help make a more proper framework for this
On Sat, Oct 17, 2015 at 3:49 PM, Ace-Dragon<EMAIL_ADDRESS>wrote:

More physics-related functionality is always nice, so I second this.
However, I don't think it'd be realistic to expect it for the upcoming
release though (as it would be a bit of a project to implement in a way
that supports everything).
—
Reply to this email directly or view it on GitHub
https://github.com/okamstudio/godot/issues/2612#issuecomment-148942533.

moving to 3.1, but there is hope of moving physics engine to Bullet eventually before that

I really want soft body support!

@RubrumExPlaneta You could follow this https://github.com/godotengine/godot/pull/12678 , I think its soon be merged

https://github.com/godotengine/godot/pull/12678 is merged.


The API of anaconda.org is providing incorrect information about the latest version.

Solution to issue cannot be found in the documentation.

[X] I checked the documentation.

Issue
When I tried to create a badge using shields for the version of the package registered on conda-forge, an old version (v0.3.1) was reported instead of the latest version (v0.4.1). I inquired about this issue with shields.
https://github.com/badges/shields/issues/10177
Upon inquiry, it was found that the "latest_version" at https://api.anaconda.org/package/conda-forge/wslPath is "0.3.1", and the latest version, which is 0.4.1, is not reflected. Although version 0.4.1 is registered under "versions", why is "latest_version" showing as 0.3.1?
I would appreciate any guidance on how to address this issue.
Installed packages
None

Environment info
https://api.anaconda.org/package/conda-forge/wslPath

Move to: https://github.com/conda/infrastructure/issues/943


load_dataset fails on distributed recipes for datasets with remote code

Description
When you load a dataset from HF with remote code, the load_dataset function prompts the user for permission to run remote code. This prompt only happens the first time the user downloads the dataset, but will cause a crash if the first time the user uses a dataset is with a distributed recipe. The likely causes a crash because load_dataset is called on all distributed processes, but the user is only prompted for permission on rank 0. The user will give permission but all the other ranks will hang waiting for a response which causes torch.distributed to crash.
Reproduce
This can be reproduced with cnn_dailymail_articles_dataset which runs remote code.
First ensure that you don't have the dataset cached (this will remove all cached datasets but it's the only way to guarantee you remove the cached files.
rm -r ~/.cache/huggingface/datasets
rm -r ~/.cache/huggingface/modules/datasets_modules/datasets

Then run any distributed recipe with this dataset. For example
tune run --nproc-per-node=2 lora_finetune_distributed --config llama2/7B_lora dataset._component_=torchtune.datasets.cnn_dailymail_articles_dataset

This should reach dataset initialization and then ask for permission to run remote code. Whichever response you provide will cause the recipe to crash since the processes will be out of sync after.
Possible Solutions

We could explore making load_dataset only happen on one rank per node but this breaks assumptions around packed datasets and would only work in single node setttings.
We could hard code trust_remote_code=True for datasets we know and support like cnn_dailymail_articles_dataset but we risk making users vulnerable to changes in hf hub.
Capture this question ourself in cnn_dailymail_articles_dataset on rank 0, and then broadcast the answer via a torch tensor of size 1 to all the other ranks.

Thanks for pointing this out @pbontrager. I've also found this is an issue with grammar_dataset. HF datasets that run remote code may be more prevalent than we thought, so we should prioritize this in the near future. I can look into it.

It might be worth checking what setting num_processes in load_dataset would do. Documentation