RuntimeError: TRT Engine build failed...

Hi,
I ran the example with 4xA100 system and encountered the following issue. Please advise how can I resolve this issue? Thanks
python examples/text-generation/llama.py --hub-token ${HF_TOKEN} meta-llama/Llama-2-7b-chat-hf ./output
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[12/31/2023-12:31:34] Quantization descriptor was None, assuming no quantization will be applied. If you want to change this behaviour, please use TRTEngineBuilder.with_quantization_schema()
[12/31/2023-12:31:34] [TRT] [I] [MemUsageChange] Init CUDA: CPU +13, GPU +0, now: CPU 152, GPU 70212 (MiB)
[12/31/2023-12:31:39] [TRT] [I] [MemUsageChange] Init builder kernel library: CPU +1973, GPU +350, now: CPU 2261, GPU 70562 (MiB)
[12/31/2023-12:32:13] [TRT-LLM] [I] Context FMHA Enabled
[12/31/2023-12:32:13] [TRT-LLM] [I] Remove Padding Enabled
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/vocab_embedding/GATHER_0_output_0 and LLaMAForCausalLM/layers/0/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/0/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/0/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/0/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/0/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/0/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/0/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/0/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/1/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/1/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/1/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/1/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/1/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/1/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/1/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/1/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/2/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/2/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/2/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/2/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/2/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:13] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:13] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/2/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/2/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/2/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/3/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/3/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/3/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/3/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/3/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/3/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/3/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/3/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/4/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/4/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/4/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/4/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/4/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/4/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/4/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/4/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/5/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/5/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/5/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/5/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/5/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/5/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/5/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/5/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/6/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/6/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/6/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/6/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/6/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:14] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:14] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/6/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/6/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/6/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/7/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/7/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/7/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/7/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/7/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/7/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/7/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/7/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/8/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/8/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/8/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/8/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/8/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/8/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/8/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/8/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/9/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/9/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/9/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/9/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/9/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:15] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:15] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/9/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/9/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/9/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/10/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/10/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/10/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/10/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/10/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/10/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/10/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/10/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/11/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/11/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/11/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/11/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/11/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/11/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/11/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/11/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/12/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/12/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/12/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/12/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/12/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/12/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/12/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/12/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/13/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/13/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/13/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/13/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/13/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:16] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:16] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/13/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/13/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/13/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/14/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/14/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/14/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/14/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/14/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/14/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/14/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/14/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/15/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/15/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/15/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/15/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/15/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/15/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/15/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/15/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/16/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/16/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/16/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/16/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/16/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:17] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:17] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/16/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/16/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/16/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/17/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/17/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/17/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/17/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/17/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/17/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/17/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/17/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/18/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/18/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/18/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/18/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/18/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/18/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/18/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/18/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/19/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/19/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/19/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/19/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/19/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/19/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/19/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/19/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/20/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/20/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/20/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/20/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/20/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:18] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:18] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/20/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/20/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/20/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/21/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/21/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/21/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/21/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/21/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/21/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/21/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/21/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/22/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/22/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/22/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/22/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/22/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/22/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/22/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/22/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/23/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/23/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/23/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/23/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/23/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:19] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:19] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/23/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/23/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/23/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/24/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/24/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/24/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/24/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/24/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/24/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/24/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/24/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/25/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/25/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/25/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/25/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/25/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/25/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/25/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/25/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/26/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/26/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/26/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/26/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/26/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:20] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:20] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/26/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/26/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/26/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/27/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/27/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/27/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/27/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/27/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/27/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/27/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/27/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/28/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/28/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/28/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/28/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/28/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/28/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/28/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/28/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/29/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/29/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/29/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/29/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/29/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/29/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/29/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/29/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/30/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/30/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/30/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/30/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/30/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:21] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:21] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/30/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/30/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:22] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:22] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/30/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/layers/31/input_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:22] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:22] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/31/input_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/31/input_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:22] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:22] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/31/ELEMENTWISE_SUM_0_output_0 and LLaMAForCausalLM/layers/31/post_layernorm/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:22] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:22] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/31/post_layernorm/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/layers/31/post_layernorm/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:22] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:22] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/layers/31/ELEMENTWISE_SUM_1_output_0 and LLaMAForCausalLM/ln_f/SHUFFLE_0_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:22] [TRT] [W] A shape layer can only run in INT32 precision
[12/31/2023-12:32:22] [TRT] [W] IElementWiseLayer with inputs LLaMAForCausalLM/ln_f/REDUCE_AVG_0_output_0 and LLaMAForCausalLM/ln_f/SHUFFLE_1_output_0: first input has type Half but second input has type Float.
[12/31/2023-12:32:27] [TRT-LLM] [I] Build TensorRT engine llama_float16_tp1_rank0.engine
[12/31/2023-12:32:27] [TRT] [W] Unused Input: position_ids
[12/31/2023-12:32:27] [TRT] [W] Detected layernorm nodes in FP16.
[12/31/2023-12:32:27] [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.
[12/31/2023-12:32:27] [TRT] [W] [RemoveDeadLayers] Input Tensor position_ids is unused or used only at compile-time, but is not being removed.
[12/31/2023-12:32:27] [TRT] [I] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 15250, GPU 71162 (MiB)
[12/31/2023-12:32:27] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 15252, GPU 71172 (MiB)
[12/31/2023-12:32:27] [TRT] [W] TensorRT was linked against cuDNN 8.9.6 but loaded cuDNN 8.9.4
[12/31/2023-12:32:27] [TRT] [I] Global timing cache in use. Profiling results in this builder pass will be stored.
[12/31/2023-12:32:37] [TRT] [I] [GraphReduction] The approximate region cut reduction algorithm is called.
[12/31/2023-12:32:37] [TRT] [I] Detected 73 inputs and 33 output network tensors.
[12/31/2023-12:32:41] [TRT] [E] 2: [virtualMemoryBuffer.cpp::resizePhysical::140] Error Code 2: OutOfMemory (no further information)
[12/31/2023-12:32:41] [TRT] [E] 2: [virtualMemoryBuffer.cpp::resizePhysical::140] Error Code 2: OutOfMemory (no further information)
[12/31/2023-12:32:41] [TRT] [W] Requested amount of GPU memory<PHONE_NUMBER>0 bytes) could not be allocated. There may not be enough free memory for allocation to succeed.
[12/31/2023-12:32:42] [TRT] [E] 2:
[12/31/2023-12:32:42] [TRT] [E] 2: [globWriter.cpp::makeResizableGpuMemory::423] Error Code 2: OutOfMemory (no further information)
[12/31/2023-12:32:42] [TRT-LLM] [E] Engine building failed, please check the error log.
[12/31/2023-12:32:42] [TRT] [I] Serialized 59 bytes of code generator cache.
[12/31/2023-12:32:42] [TRT] [I] Serialized 156869 bytes of compilation cache.
[12/31/2023-12:32:42] [TRT] [I] Serialized 136 timing cache entries
[12/31/2023-12:32:42] [TRT-LLM] [I] Timing cache serialized to output/timings.cache
[12/31/2023-12:32:42] [TRT-LLM] [I] Config saved to output/build.json.
Traceback (most recent call last):
File "/opt/optimum-nvidia/examples/text-generation/llama.py", line 101, in
builder.build(args.output, args.optimization_level)
File "/opt/optimum-nvidia/src/optimum/nvidia/builder.py", line 405, in build
build_func(shards_info, files, output_path, optimization_level)
File "/opt/optimum-nvidia/src/optimum/nvidia/builder.py", line 418, in _build_serial
self._build_engine_for_rank(shard, weights, output_path, opt_level, is_parallel=False)
File "/opt/optimum-nvidia/src/optimum/nvidia/builder.py", line 579, in _build_engine_for_rank
raise RuntimeError("TRT Engine build failed... Please check the logs and open up an issue.")
RuntimeError: TRT Engine build failed... Please check the logs and open up an issue.

Same problem with the TRT Engine.
File "/opt/optimum-nvidia/src/optimum/nvidia/models/base.py", line 60, in _from_pretrained
return model_class.from_pretrained(
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py", line 118, in _inner_fn
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/hub_mixin.py", line 157, in from_pretrained
return cls._from_pretrained(
File "/opt/optimum-nvidia/src/optimum/nvidia/runtime.py", line 154, in _from_pretrained
builder.build(engine_folder, optimization_level)
File "/opt/optimum-nvidia/src/optimum/nvidia/builder.py", line 405, in build
build_func(shards_info, files, output_path, optimization_level)
File "/opt/optimum-nvidia/src/optimum/nvidia/builder.py", line 418, in _build_serial
self._build_engine_for_rank(shard, weights, output_path, opt_level, is_parallel=False)
File "/opt/optimum-nvidia/src/optimum/nvidia/builder.py", line 579, in _build_engine_for_rank
raise RuntimeError("TRT Engine build failed... Please check the logs and open up an issue.")
RuntimeError: TRT Engine build failed... Please check the logs and open up an issue.


[Fix #3590] Adding $input support

Fix https://github.com/apache/incubator-kie-kogito-runtimes/issues/3590

PR job #2 was: UNSTABLE
Possible explanation: This should be test failures

Reproducer
build-chain build full_downstream  -f 'https://raw.githubusercontent.com/${AUTHOR:apache}/incubator-kie-kogito-pipelines/${BRANCH:main}/.ci/buildchain-config-pr-cdb.yaml' -o 'bc' -p apache/incubator-kie-kogito-runtimes -u https://github.com/apache/incubator-kie-kogito-runtimes/pull/3591 --skipParallelCheckout
NOTE: To install the build-chain tool, please refer to https://github.com/kiegroup/github-action-build-chain#local-execution

Please look here: https://ci-builds.apache.org/job/KIE/job/kogito/job/main/job/pullrequest_jobs/job/kogito-runtimes-pr/job/PR-3591/2/display/redirect
Test results:

PASSED: 3273
FAILED: 9

Those are the test failures:

org.kie.kogito.codegen.tests.ServerlessWorkflowIT.testSubFlowWorkflow
Expected size: 1 but was: 2 in:{"workflowdata"={"parentData":"parentTestData","childData":"childTestData"}, "workflowdatainput"=null}

org.kie.kogito.codegen.tests.ServerlessWorkflowIT.testBasicServiceWorkflow(String)[1]
Expected size: 1 but was: 2 in:{"workflowdata"={"name":"john","result":"Hello john"}, "workflowdatainput"=null}

org.kie.kogito.codegen.tests.ServerlessWorkflowIT.testBasicServiceWorkflow(String)[2]
Expected size: 1 but was: 2 in:{"workflowdata"={"name":"john","result":"Hello john"}, "workflowdatainput"=null}

org.kie.kogito.codegen.tests.ServerlessWorkflowIT.testSingleInjectWorkflow(String)[1]
Expected size: 1 but was: 2 in:{"workflowdata"={"name":"john"}, "workflowdatainput"=null}

org.kie.kogito.codegen.tests.ServerlessWorkflowIT.testSingleInjectWorkflow(String)[2]
Expected size: 1 but was: 2 in:{"workflowdata"={"name":"john"}, "workflowdatainput"=null}

org.kie.kogito.codegen.tests.ServerlessWorkflowIT.testApproveSwitchStateWorkflow(String)[1]
Expected size: 1 but was: 2 in:{"workflowdata"={"people":[{"name":"john","age":25}],"decision":"Approved"}, "workflowdatainput"=null}

org.kie.kogito.codegen.tests.ServerlessWorkflowIT.testApproveSwitchStateWorkflow(String)[2]
Expected size: 1 but was: 2 in:{"workflowdata"={"people":[{"name":"john","age":25}],"decision":"Approved"}, "workflowdatainput"=null}

org.kie.kogito.codegen.tests.ServerlessWorkflowIT.testDenySwitchStateWorkflow(String)[1]
Expected size: 1 but was: 2 in:{"workflowdata"={"people":[{"name":"john","age":15}],"decision":"Denied"}, "workflowdatainput"=null}

org.kie.kogito.codegen.tests.ServerlessWorkflowIT.testDenySwitchStateWorkflow(String)[2]
Expected size: 1 but was: 2 in:{"workflowdata"={"people":[{"name":"john","age":15}],"decision":"Denied"}, "workflowdatainput"=null}


[Bug]: Select and download the zwavejs_current.log results in empty zip

Checklist

[X]  I am not using Home Assistant. Or: a developer has told me to come here.
[X] I have checked the troubleshooting section and my problem is not described there.
[X] I have read the changelog and my problem is not mentioned there.

Deploy method
Snap
Zwavejs2Mqtt version
<IP_ADDRESS>c2434f
ZwaveJS version
9.6.2
Describe the bug
Selecting the zwavejs_current.log and then choose to download it would result in an empty zip. I guess its because this file is a symlink.
To Reproduce

Expected behavior
That the zip contained the linked file.
Additional context
No response

Ok just found the reason this is not working. It's actually not a file but a symbolic link to a file, for security reasons I'm not allowing that. You should just download the correct file it is pointing to (the last one created)

Fixed by #2611


⚠ Bofrost.lu has degraded performance

In a83486f, Bofrost.lu (https://www.bofrost.lu) experienced degraded performance:

HTTP code: 200
Response time: 2205 ms

Resolved: Bofrost.lu performance has improved in 56cf618 after 19 minutes.


Staging next

Motivation for this change
Things done

[ ] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS)
Built on platform(s)

[ ] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nix-review --run "nix-review wip"
[ ] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Assured whether relevant documentation is up to date
[ ] Fits CONTRIBUTING.md.

@peti GHC 8.6.5 fails on staging-next. Could you have a look?
https://hydra.nixos.org/build/92947674

cc @basvandijk for GHC

8.6.5 fails on staging-next.

I re-started https://hydra.nixos.org/build/92947674 and now it succeeds. It appears the problem is some transient phenomenon related to parallel building, i.e. a race condition in GHC's build system.

llvm 7 failure on aarch
https://hydra.nixos.org/build/92951911

@fridh we're seeing two issues with the new macOS stuff:

https://hydra.nixos.org/build/92964363
https://hydra.nixos.org/build/92930990

I'll have some time this weekend to work on it

There's also a problem with llvm 7.1 on darwin, blocking rustc. Since the queue is completely empty I would propose to merge both #60849 and #60912 first.

@LnL7 go for it

Afterwards I do want to merge this with master so we can go to the next batch of updates (staging).

Merged #60912 into staging-next but not #60849; to do a full linux rebuild as well seems a bit extreme.


Hiding applications (cmd+h) not supported

This used to work in previous versions because of polling.
As we are now relying on notifications to update our state, and there are only didHideApplication and didUnhideApplication notifications available, I've decided not to bother with implementing support for this.
The solution would be to drop all cached information for every single space of all connected displays, or figure out which spaces these windows were located on and mark all of them for update upon next space activation.
I suspect there to be more complex cases which I have yet to think about as well.
Minimizing windows should work fine, for the most part, assuming that the OSX notifications that we rely on is actually delievered by the system.

Are those notifications insufficient? I'd like to see this feature, and I wouldn't mind trying to implement it, given a little more information about why those notifications won't work.

I don't have any reason to believe that they are insufficient, however, they cause a lot of otherwise unnecessary overhead and complexity that I personally feel is not worth dealing with.
The approach you'd have to take, is pretty much what I described above. The following would have to happen every time either of those notifications were received.

The solution would be to drop all cached information for every single space of all connected displays, or figure out which spaces these windows were located on and mark all of them for update upon next space activation.

There would also be the need to check upon space-transition end, if that space has been flagged for an update, and respond accordingly.

My main issue with this bug is I accidentally hide things when KWM does not respond sometimes (cmd + alt - h).
Recovering from this issue is a huge pain in the ass, pretty much requires either quitting the apps I hid - or - quitting KWM.
I don't hide things often (ever) but sometimes kwm doesn't catch a command and OS X picks it up and hides things. Huge headache

Recovering from this issue is a huge pain in the ass, pretty much requires either quitting the apps I hid - or - quitting KWM.

I realize this is not a fix or anything, but simply unhiding an application and toggling the window in question float and then unfloat will force a retile.

Hi @koekeishiya,
I often have windows fall out of control of KWM, sometimes after its been hidden and other times when an app is closed and reopened.
How can I float an individual window to force a retile?
I have the keybind for floating all windows:
// Set Space Tiling Mode To Floating
kwmc bindsym cmd+ctrl-d space -t float

But this doesn't seem to change anything, and seems to stop me moving from window to window.
Any help appreciated, thanks

The issue in question is a couple of months old, feel free to create new issues if / when you have a problem that isn't necessarily already answered in previous issues.

I often have windows fall out of control of KWM

Not sure how this is to be interpreted. Can you elaborate on what this means exactly?

How can I float an individual window to force a retile?

You can float individual windows using the command kwmc window -t focused. Performing the command twice will do a float -> unfloatwhich should trigger tiling.
Available commands can be found here

Not sure how this is to be interpreted. Can you elaborate on what this means exactly?

As an example Spotify will be tiled with other windows, I'll hide it for a bit and when I unhide it KWM doesn't see it as a new window and carries on with tiling the existing windows that were there before, with Spotify just floating over the top. I'm looking for the best way to 'refresh' KWM as it were.

As an example Spotify will be tiled with other windows, I'll hide it for a bit and when I unhide it KWM doesn't see it as a new window and carries on with tiling the existing windows that were there before, with Spotify just floating over the top. I'm looking for the best way to 'refresh' KWM as it were.

Hm, I'm unable to reproduce this. Are you on the latest version (v3.1.3) ?
If so, feel free to create a new issue to track this


[REQUEST] New UI Themes

Is your feature request related to a problem? Please describe.
It would be be awesome if Hydra was themable. Color changes, palette swaps, fonts, etc.
Describe the solution you'd like
Flexible theming options to change the Hydra Launcher UI
Describe alternatives you've considered
No response
Additional context
No response

Themes are WIP
Pull request is https://github.com/hydralauncher/hydra/pull/422


Have static method on React Components for pre-fetching?

Hello @goatslacker,
Instead of making a request for fetching data before server-side render into the app.use like in your example:
getNameFromServer(function (name) {
  res.locals.data = {
    HelloStore: { name: name }
  }
  next()
})

(That means double-work, one method in component / stores for fetching data when app is running client-side, and one on the server-side. Or am I wrong and I didn't understand something?)
Would it possible to have static method on components that would be resolved before rendering, like https://github.com/ericclemmons/react-resolver/ is doing?
Anyway, thank's for Alt & iso :)

iso doesn't have an opinion on how you load your data. It's just a helper function that lets you transfer JSON data from server to client.
I don't know in much detail but I believe react-resolver returns promises, if that's the case then yes you can use react-resolver to declare your data fetching needs at the component level.

Okey thank's for the precision!


Swift 3 issue

I have downloaded all dependencies with cocoapods and converted the code to Swift 3 syntax. Now the project is full of errors. Please help to resolve the issue or someone share a link with final project without cocoapods.

Were you able to convert this into Swift 3?

Yes Jain...i converted it. But now project is with full of errors.
Sent from my iPhone

On 09-Mar-2017, at 9:59 PM, Anuraag D Jain<EMAIL_ADDRESS>wrote:
Were you able to convert this into Swift 3?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or mute the thread.

@harikeerthipati Do you resolved the swift3 issues?


Using watcher causes changes to generate new instance of elements on DOM rather than replacing old ones

fuse.ts looks like this:
import { fusebox } from 'fuse-box'; const fuse = fusebox({   entry: 'src/index.ts',   target: 'browser',   devServer: { enabled: true, open: true },   webIndex: true,   watcher: true,   cache: true, }); fuse.runDev();
If I add an element to the DOM at runtime while the dev server and watcher are running, I just get another instance of the DOM element on screen. I would expect the DOM to refresh with whatever changes I made. For example, having in this in my index.ts:
const el:HTMLElement = document.createElement('button'); document.body.appendChild(el);
causes a new button to appear on screen every time I save the file.
Is this a cacheing issue of some sort? Is my fuse config setup incorrectly?
Currently using latest Chrome on a Mac for testing.

There is nothing wrong, the entry point is being triggered this is expected. YOu need to handle it this soft reload at your application level. For example
if(window.initialized) {
  clearAndStart()
} else {
  window.initialized = true;
  justStart()
}

Ah, okay. I suppose other bundlers that handle this out of the box probably have some kind of logic automatically added to the container HTML page? In my case the project is very simple and a full page refresh between saves is sufficient. So I guess I really just need live reloading, not hot reloading. Is there really no option for automatic live reloading right out of the box?

It's not that a bundler "handles" them. It's framework specific.  As I said, the following code will re-init your app and no refresh needed.
if(window.initialized) {
 document.body.innerHTML = ""
}
window.initialized = true;
const el:HTMLElement = document.createElement('button'); document.body.appendChild(el);

So once an entry point is triggered the second time you flush your state and start over. It's very handy.
Some more information for you:
https://fuse-box.org/docs/development/hmr
You could also take a look at the custom HMR plugin in this example:
https://github.com/fuse-box/sandbox/tree/master/hmr-plugin-example
https://github.com/fuse-box/sandbox/blob/master/hmr-plugin-example/src/hmr.ts
You can choose to reload the page too or apply some custom magic to it, good luck ;-)

Thanks, I edited my comment, you probably didn't see it in time. I did see this doc page:
https://fuse-box.org/docs/development/hmr
and the Typescript compiler seems to choke on 'hardReloadScripts' prop in the 'watch' or 'watcher' object (using v4.0.0 of fuse-box). I'm not clear if the documentation is for a previous version?
Either way, for simple live reloading using the basic technique of checking the initialized prop and clearing the page in my dev builds should suffice for now.

👍


Write downloader for tlgu

The TLGU class, which wraps the tlgu command line utility, needs a method to automatically download the utility. There is already an initial method to compile the executable from the downloaded C file. I have hosted the files on GitHub here (https://github.com/smargh/tlgu), but we will likely eventually move this under the CLTK organization.
The downloader definitely needs the tlgu.c and tlgu.h files, but do we want all the rest as well? And where do we download them to? To a temp directory that we then delete? Or make it permanent somewhere in the cltk directory tree?

TLGU can be downloaded, installed, and used.
The code which downloads it is at: https://github.com/kylepjohnson/cltk/blob/master/cltk/corpus/utils/importer.py
And installation code: https://github.com/kylepjohnson/cltk/blob/master/cltk/corpus/greek/tlgu.py
It can be downloaded with instructions at: http://docs.cltk.org/en/latest/importing_corpora.html#listing-corpora
And used with instructions: http://docs.cltk.org/en/latest/greek.html#converting-tlg-and-phi-texts-with-tlgu
In fact, only the latter is completely necessary for end users.

Looks good.


RippleMask blocks input after ScreenConfig.Back is called

After calling Back() on a ScreenConfig, the ripple mask object of that screen stays in place after the animation has finished playing and, while it is invisible so doesn't visually obscure the new screen, still blocks clicks and touches.
This seems to also have something to do with timing of the animation since as the animation plays, the ripple mask shrinks and sometimes becomes so small that it isn't noticeable.

Hi! Thanks for bringing this issue to my attention :)
I'm now working on MaterialUI in a private repo, adding features and the likes for an official release on the Asset Store - this means that I won't be adding/fixing anything more in this repo (sorry). Feel free to fork this one if you'd like to tackle to issue yourself, and/or send me an email at<EMAIL_ADDRESS>if you want me to let you know when it's available.
Cheers,
Declan.


🚀 [Feature]: otelfiber - Propergate tracing headers in outbound response

Feature Description
When using the otelfiber middleware it would be nice to propergate the tracing headers to the outbound response in order to unify tracing across the call-chain. It would be needed to inject the coresponding headers from the TextMapPropagator, similar to the code snippet below.
This is already done in the limiter middleware for propergating the X-Ratelimit* headers (also see https://github.com/gofiber/fiber/blob/master/middleware/limiter/limiter_fixed.go#L100-L102).
Additional Context (optional)
No response
Code Snippet (optional)
func AddTracingHeadersToContext(ctx *fiber.Ctx) {
	var tracingHeader = make(propagation.HeaderCarrier)
	otel.GetTextMapPropagator().Inject(ctx.UserContext(), tracingHeader)

	for _, headerKey := range tracingHeader.Keys() {
		ctx.Set(headerKey, tracingHeader.Get(headerKey))
	}
}

Checklist:

[X] I agree to follow Fiber's Code of Conduct.
[X] I have checked for existing issues that describe my suggestion prior to opening this one.
[X] I understand that improperly formatted feature requests may be closed without explanation.

I would be able to implement this in general, but some feedback on this would be appreciated 😀

unfortunately i have no experience with this middleware, so i need an opinion from you
@KaptinLin @emanuelef @efumagal @mstrYoda @danielalvarenga @eko @onematchfox @ijsong @lucasoares @WLun001

Is it to be able to add the spans in the same trace across different services ?
I remember I was able to do that in case and described in an article: https://medium.com/stackademic/start-using-opentelemetry-with-go-fiber-1005697d841f.
But maybe I'm misunderstanding.

@ledex

Sorry for not replying earlier, I'm currently on vacation, but will get back to this issue/pull request on monday.
@emanuelef I'll have a look at the article you posted and build an example of my use case for this.


Update log4j-api, log4j-core, ... to 2.18.0

Updates

org.apache.logging.log4j:log4j-api
org.apache.logging.log4j:log4j-core
org.apache.logging.log4j:log4j-slf4j-impl

from 2.17.2 to 2.18.0.
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

Adjust future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "org.apache.logging.log4j" } ]

Or, add this to slow down future updates of this dependency:
dependencyOverrides = [{
  pullRequests = { frequency = "@monthly" },
  dependency = { groupId = "org.apache.logging.log4j" }
}]

labels: library-update, early-semver-minor, semver-spec-minor, commit-count:1

already upgraded to 2.18.0


Lines with changed indentation are not highlighted

VSCode Version: 1.19.0 (1.19.0)
OS Version: macOS High Sierra 10.13.2

Steps to Reproduce:

Change indentation
Save file

Reproduces without extensions: Yes

Line №7 was changed, but is not highlighted. While in the file explorer the files with changed indentation only are highlighted as changed.

The call to computeDirtyDiff could use the setting diffEditor.ignoreTrimWhitespace instead of hard-coding it to true here. @joaomoreno any objections?

That's a good idea. I can take this.


fix azure piplines windows env activate call

[ ] Closes issue #xxxx
[ ] I am familiar with the contributing guidelines.
[ ] Fully tested. Added and/or modified tests to ensure correct behavior for all reasonable inputs. Tests (usually) must pass on the TravisCI and Appveyor testing services.
[ ] Updates entries to docs/sphinx/source/api.rst for API changes.
[ ] Adds description and name entries in the appropriate docs/sphinx/source/whatsnew file for all changes.
[ ] Code quality and style is sufficient. Passes LGTM and SticklerCI checks.
[ ] New code is fully documented. Includes sphinx/numpydoc compliant docstrings and comments in the code where necessary.
[ ] Pull request is nearly complete and ready for detailed review.

I did not set up the Azure Pipeline builds for windows correctly, so the tests that require optional dependencies (scipy, tables, pvfactors, numba) did not run. This PR fixes that.
It appears that pvfactors multiprocessing might not work on windows. @anomam?
I'm going to go ahead and merge since this CI fix will support active PRs.

Thanks @wholmgren
Sent from my iPhone
On May 14, 2019, at 4:43 PM, Will Holmgren <notifications<EMAIL_ADDRESS>wrote:
Merged #723https://github.com/pvlib/pvlib-python/pull/723 into master.
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHubhttps://github.com/pvlib/pvlib-python/pull/723?email_source=notifications&email_token=ABJE2LY22ISPJJQZYTA7DTDPVM57PA5CNFSM4HM6BRB2YY3PNVWWK3TUL52HS4DFWZEXG43VMVCXMZLOORHG65DJMZUWGYLUNFXW5KTDN5WW2ZLOORPWSZGOROJKPGQ#event-2341644186, or mute the threadhttps://github.com/notifications/unsubscribe-auth/ABJE2LY6TZ62GXBGWVRVOB3PVM57PANCNFSM4HM6BRBQ.

Thanks @wholmgren , I think this is fixed with pvfactors v1.0.1


Louis

XJoe price feed using joe:xjoe ratio

I think you actually removed package.json from the directory. What i meant is that don't any package.json changes to this PR, i.e. revert any package.json changes you've made.


remove .rakeTasks

This change is

Coverage remained the same at ?% when pulling c8dbab158df906e85341f9d35c60da3687d5aab2 on remove-rake-tasks-file into 8dbd5b9a38103ddd9e6023dd666c69ec01a69788 on master.


Styling appointments in the 'show more' popover

Thank you for the awesome calendar!
I have different styling for appointments based on whether an appointment was confirmed or not, however, when there are multiple appointments for a single day in month view and I bring up the 'show more' popover, I only get one style for appointments (confirmed). How can I propagate the different (unconfirmed) style class to the appointments in the popover as well? They work great in day and week views, just not in the popover
Thanks!

+1

I think this has been fixed?

Hmm I did indeed find a workaround that I am having a hard time remembering the details of right now. If anyone runs across this in the future and needs help I can look :)


On stack reload support in Dart standalone

Forked from https://github.com/dart-lang/sdk/issues/26127

[] Make the library tag handler return when the whole load is completed.
[] Stop invoking Dart code during load.

@turnidge @johnmccutchan


Allow wizard_step updates after DepositorSetupInfo and AnalysisPlan are "complete"

Currently both DepositorSetupInfo and AnalysisPlan disallow further updates once the data is marked as complete

Update the PATCH endpoints to allow wizard_step to be updated even after steps are complete to allow UI flexibility

Note: wizard_step isn't tied to internal status logic other than on initiation

Notes

DepositorSetupInfo

If DepositorSetupInfo is_complete and a PATCH comes through, remove all data from the request except wizard_step
For the is_complete attribute, add it to PATCH but don't change it to True unless internal data requirements are also met.

(See #760 re: data requirements, etc)

AnalysisPlan

Similar to above: If AnalysisPlan is_complete and a PATCH comes through, remove all data from the request except wizard_step
Set is_complete=True once a ReleaseInfo is generated. (What should be the state if it ends on error? Or the plan expires?)

Frontend Changes

For the AnalysisPlan workflow:

epsilon, delta, and confidence_level values should come from the AnalysisPlan object.  (Previously they were sourced from the DepositorSetupInfo)

Of the values epsilon, delta, and confidence_level -- only confidence_level is editable by the analyst.
Attempted patches to the depositor setup info will result in 400s--except for updating wizard step

e.g. See the file analysis.js and method patchDepositorSetup


Sanatize entrypoint names to support what bootgen allows

Fixes: https://github.com/nod-ai/iree-amd-aie/issues/513

I can see the error the CI is producing locally for a simple case, looks like $ means something special to IREE so I will have to investigate this further.


Backstage ADR013 - Use fetch from node-fetch package

Description
Issue number: 37
Type of change

[ ] New feature (non-breaking change which adds functionality)
[x] Fix (non-breaking change which fixes an issue)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist

[ ] I have performed a self-review of this change
[ x] Changes have been tested
[ ] Changes are documented
[ ] Changes generate no new warnings
[ ] PR title follows conventional commit semantics

If this is a breaking change 👇

[ ] I have documented the migration process
[ ] I have implemented necessary warnings (if it can live side by side)

Acknowledgement
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.
Disclaimer: We value your time and bandwidth. As such, any pull requests created on non-triaged issues might not be successful.

This is failing due to type check validations as response.json() returns type unknown. I'm working on fixing these and will contribute with the necessary changes to make it work.

@pcgqueiroz this is now passing all tests and validations. Can you check if this works from behind the proxy?

@pcgqueiroz let me know once you have time to test this and if it works or not. Thanks!

@t1agob , I have tested with the package version 0.4.6-next.0 and it did not work. I have the following error:
/backstage/node_modules/@pagerduty/backstage-plugin-backend/dist/index.cjs.js:8
var fetch$1 = require('node-fetch');
              ^

Error [ERR_REQUIRE_ESM]: require() of ES Module<EMAIL_ADDRESS>from<EMAIL_ADDRESS>not supported.
Instead change the require of index.js in<EMAIL_ADDRESS>to a dynamic import() which is available in all CommonJS modules.
    at Object.<anonymous> (/backstage/node_modules/@pagerduty/backstage-plugin-backend/dist/index.cjs.js:8:15)
    at @pagerduty/backstage-plugin-backend (/backstage/packages/backend/dist/main.js:577:18)
    at __webpack_require__ (/backstage/packages/backend/dist/main.js:1090:33)
    at fn (/backstage/packages/backend/dist/main.js:1301:21)
    at eval (webpack-internal:///./src/plugins/pagerduty.ts:5:93)
    at ./src/plugins/pagerduty.ts (/backstage/packages/backend/dist/src_plugins_pagerduty_ts.chunk.js:20:1)
    at __webpack_require__ (/backstage/packages/backend/dist/main.js:1090:33)
    at Function.fn (/backstage/packages/backend/dist/main.js:1301:21) {
  code: 'ERR_REQUIRE_ESM'
}

I suspect the error above is related to the node-fetch version 3.3.0. So I have used the source code of the branch and tested with the previous node-fetch version 2.6.7 and everything worked as expected :-)

@pcgqueiroz Oh...got it! This is due to the lack of support for ESM for backend modules in Backstage. node-fetch starting on version 3.x is ESM only so we need to downgrade to version 2.x like you suggested.
Can you try it with version 0.4.6-next.2? Thanks!

Hey @t1agob ! Version 0.4.6-next.2 worked out of the box! Thanks for that, I think it's fine to be merged.


Error when building for real device (ios) using 'SDWebImage.Maui.iOS' nuget package

Hello,
I am referencing version 1.0.3 of the nuget SDWebImage.Maui.iOS.
When building for relal device, I have this issue :
clang++ exited with code 1:
Undefined symbols for architecture arm64:
  "_OBJC_CLASS_$_SDImageCache", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDImageCacheConfig", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImageCoderHelper", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImageCodersManager", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImageDownloadToken", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImageDownloader", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImageDownloaderOperation", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImageFrame", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImageGIFCoder", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImageImageIOCoder", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImageManager", referenced from:
      objc-class-ref in registrar.o
  "_OBJC_CLASS_$_SDWebImagePrefetcher", referenced from:
      objc-class-ref in registrar.o	TVST.iOS.UI (net8.0-ios)	C:\Program Files\dotnet\packs\Microsoft.iOS.Sdk.net8.0_17.5\17.5.8020\targets\Xamarin.Shared.Sdk.targets	1641

My runtime identifier is defined like this :
<RuntimeIdentifiers>ios-arm64</RuntimeIdentifiers>

Do you have any sugestion to help me ?
Thanks a lot for this repository and package.

Please use version 1.1.7


Is TFS Supported?

I noticed that the "Download" button no longer appears on the Marketplace.  Does that mean TFS is no longer supported?  Other documentation seems to imply that it is, although the readme and repository titles both say vsts with no mention of tfs.
Sorry if I'm not supposed to open an Issue just to ask a question - let me know if I'm doing this wrong.

pebcac


Implement --no-window option for macOS and Linux

Godot version:
Godot Engine v3.2.3.stable.mono.official
OS/device including version:
macOS Sierra Version 10.12.6
Issue description:
When i try to run a script via OS.execute() with option --no-window the window pops up.
Under Windows 10 it works as expected but under MacOs the window is not hidden
Steps to reproduce:
class_name GdUnitRunnerClient
extends SceneTree

func _initialize():
  pass
...

execution from a EditorPlugin context
var arguments := Array()
arguments.append("--no-window")
arguments.append("-d")
arguments.append("-s")
arguments.append("res://addons/gdUnit/src/core/GdUnitRunnerClient.gd")

var output = []
_current_runner_process_id = OS.execute(OS.get_executable_path(), arguments, false, output, true);

Minimal reproduction project:

On Linux and macOS --no-window is not implemented, here's PR for it #42276.

$ godot --help | grep no-window
  --no-window                      Disable window creation (Windows only). Useful together with --script.

ok thanks for this feedback

Let's repurpose this as a feature request to implement --no-window for macOS and Linux I guess, which #42276 can close.

Now that the resolving PR has been merged, can this issue be closed?


Public view is broken

Public view shows an empty page due to insufficient permissions on anonymous roles in emo.py. However this calls for a bit of restructuring on the theme wrapper (minor)

way too burnt out to fix this

Fixing this cus a friend need requested it


zlib:x64-windows failed with: BUILD_FAILED

Installation of zlib fails for me with following error:
CMake Error at scripts/cmake/vcpkg_test_cmake.cmake:56 (message):
CMake integration test failed; unable to find_package(ZLIB MODULE REQUIRED)

https://github.com/Microsoft/vcpkg/pull/5635

It is a known issue with our vcpkg_test_cmake() function, my suggestion is to remove the call.


Review SmartAPI registration update and merged PR and then redeploy ICEES+ API instances

Max and I updated a bunch of SmartAPI registrations over the holiday break, including this one:  https://github.com/ExposuresProvider/icees-api/pull/251#pullrequestreview-1225041490. This issue is to request that you review the change and, if no additional changes are required, redeploy the ICEES+ API instances.

@karafecho I think this ticket can be closed now that the redeployed ICEES+ API instances have been verified.

Agreed. I didn't test the production instances of the ICEES+ APIS, but I did test the four development instances (asthma, pcd, dili, covid) by creating a cohort and running a feature association functionality. All looks fine, so closing ticket.


definitions and extra parentage for spermatogenesis terms

Some suggested definitions for the spermatogenesis part
of the tree:
Nebenkern formation ; GO:0007287
Fusion of mitochondria during insect spermatid
differentiation to form two masses, which wrap around
each other to form a densely packed sphere called the
Nebenkern.
ISBN:0879694238
comment: See also the cellular component term Nebenkern
; GO:0016006, and the fly_anatomy.ontology term
Nebenkern ; FBbt:00004943.
#
sperm individualization ; GO:0007291
The resolution of the male germline syncytium or cyst
into individual gametes by packaging each spermatid
into its own plasma membrane.
PMID: 9550716.
#
spermatid nuclear differentiation ; GO:0007289
The specialization of the spermatid nucleus during the
development of a spermatid into a mature male gamete
competent for fertilization.
FB:bf
comment: See also the cell.ontology terms 'spermatid ;
CL:0000018'.
#
spermatid nuclear elongation ; GO:0007290
The change in shape of the spermatid nucleus from a
spherical structure to an elongated organelle, during
the latter part of spermatid differentiation.
ISBN:0879694238
FB:bf
#
spermatogonial cell division ; GO:0007284
The mitotic divisions of the primary spermatogonial
cell (a primordial male germ cell) to form a cyst of
secondary spermatogonia (primary spermatocytes).
ISBN:0879694238
See also the cell.ontology terms 'spermatogonium ;
CL:0000020' and 'primary spermatocyte ; CL:0000656'.
#
Also, I would like to add the synonym 'spermatid
differentiation' to spermatid development ; GO:0007286
; synonym:spermiogenesis.
#
And i would like to add the following extra parentage:
spermatid nuclear differentiation ; GO:0007289
--<spermatid nuclear elongation ; GO:0007290
male germ-line cyst formation ; GO:0048136
--<spermatogonial cell division ; GO:0007284 [new
relationship]
--<spermatocyte cell division ; GO:0048137
#
and some other suggested definitions while i am here:
pole cell formation ; GO:0007279
Formation of a small group of cells (pole cells) at the
posterior pole of the insect blastula. They are the
first cells to cellularize after the arrival of nuclei
at the end of the synctial blastula stage and are the
precursors to the insect germ cells.
PMID: 9988212
comment: See also the cell.ontology term 'pole cell ;
GO:0000301'.
#
pole cell migration ; GO:0007280
The directed movement of pole cells (germline
progenitors in insects) from their site of production
at the posterior pole of the embryo through to the site
where the gonads will form.
PMID: 9988212
comment: See also the cell.ontology term 'pole cell ;
GO:0000301'.
#
pattern recognition receptor activity ; GO:0008329
Combining with pathogen-associated molecular patterns
to initiate a change in cell activity.
Pathogen-associated molecular patterns are conserved
molecular structures found in large groups of pathogens.
PMID: 14557290
#
ecdysone receptor holocomplex ; GO:0008230
A heterodimeric complex containing the products of the
insect genes Ecdysone receptor (EcR) and ultraspiracle
(usp). Binding of ecdysone promotes association between
the two subunits, and the receptor complex then
initiates molting and metamorphosis by binding DNA and
regulating the transcription of target genes.
PMID: 14592980
FB:bf
#
Will add these definitions and extra relationships in
this week if there's no objections.
Thanks,
Becky
Reported by: beckyfoulger
Original Ticket: "geneontology/ontology-requests/1688":https://sourceforge.net/p/geneontology/ontology-requests/1688

thanks www.movied.org


Updated Validation Regex for Validators to allow - and _

I have modified the troposphere use case to allow for the following:
GIVEN an AWS resource described by Troposphere script (specifically, SNS)
WHEN Troposphere is run
AND AWS resource includes alphanumerics and hyphens and underscores in display names
THEN Troposphere successfully generates CloudFormation which can run in AWS

I had a need to create SNS topics using Troposphere, and although AWS allows for alphanumerics + hyphens and underscores, the Troposphere validation was blocking successful creation of SNS topic names, such as "THIS_SNS_TOPIC-1"
Please let me know if there is a less global way to inject this regex change so that it only affects SNS topic creation, and I will gladly contribute.

Actually, after further inspection, this is an AWS issue.  CloudFormation validation API is disparate as juxtaposed to the SNS, et al validation APIs.  i.e., When CloudFormation validates your template, it is currently different than if SNS API directly validates your template.  The correct syntax for this instead is the following in Troposphere:
       template.add_resource(
            Topic(
                "MyTopic",
                TopicName="THIS_SNS_TOPIC-1",
                DisplayName="THIS_SNS_TOPIC-1"
            )
        )

Closing PR for now; this should be re-evaluated if and when AWS


new

@MuhammadAdrin Pull request merged. Please start requesting the licenses in about an hour, to let the changes to propagate through our system. Thank you.


increase the delay value

hi
is there any way to increase or decrease the value of delay prop for each Transition?

Unfortunately not. Sorry.


feat: upgrade to Node v20

Fix #244
Tested this by tweeting via the free API, still works.

Wow, fastest merge in the West, thanks!
BTW the tests failing seem to be API creds to your X profile being misconfigured.

BTW the tests failing seem to be API creds to your X profile being misconfigured.

I think it's because your PR was from a fork

Ah OK.


Make logo bigger and font on menu bold and a bit bigger on size.

Currently the logos are very small, both main menu and footer. We should try to make those a bit bigger so the wording Prizren 2023 is readable.
Also the font on menu is very light and small, which makes it not very readable.
@jbelien let me know if you would like me to do this, or you want to change it yourself.

@jbelien let me know if you would like me to do this, or you want to change it yourself.

You're more than welcome to do it yourself! 👍
If we start working together, I suggest we go through Pull Requests to add new feature or change things (if it works for you, of course).

ok this works for me as well :)


This is no Open-Xml-PowerTools.psm1 file, that I can import module to PS

Correct. You need to build it first.
Follow the instructions from https://www.youtube.com/watch?v=60w-yPDSQD0.

Closing all issues as this repo is being archived and will no longer be maintained by Microsoft. The project is licensed for continued use and development by forking to your own repo.


Unclear documentation

Describe the feature you'd like to have
Clearly/well arranged documentation, actualy it is written in xy pages in xy directories, that is very hard for orientation and it's complicated to understand it in short time period
What is the value to the end user? (why is it a priority?)
It really can save time, increases better readability, one unified documentation
How would the end user gain value from having this feature?
Clear instruction how to use this plugin
How will we know we have a good solution? (acceptance criteria)

Feedback, if the documentation is useful, if is clearly written and ask some question from end users if it is unified and so on.

Could you be a little more explicit in what you expect of the documentation? Proposals for restructuring are definitely welcome, ideally send them as pull-requests :tada:
There is https://github.com/ceph/ceph-csi/blob/devel/docs/deploy-cephfs.md#deployment-with-kubernetes which explains how to deploy the CephFS driver on Kubernetes, a same document is available for RBD.
The usage of CSI operations to manage volumes depend on the container platform. Ceph-CSI mostly focuses on Kubernetes with dynamic provisioning of PersistentVolumeClaims, other platforms use different terminology for the volumes. Explaining how to create volumes on different container platforms is out-of-scope for the documentation of the driver.

Yes, but the documentation is quite misleading and not well structured, it is written on multiple different directories and there are not good references between multiple pages, which creates harder readability and harder orientation.
I've tried to install it but after so much time spent I could not with usage of kubectl and plain yamls, then I found out I dont know on which page, that I can use install with bash script, that only worked... Even it was last changed 2 years ago

I'm also having a hard time settings things up. In particular, the parts about installing the CephFS plugin with Helm (https://github.com/ceph/ceph-csi/blob/devel/charts/ceph-csi-cephfs/README.md) could be significantly improved I think.
For instance, it is not clear to me what the different config options and ConfigMaps do. These are in the chart's README (https://github.com/ceph/ceph-csi/tree/devel/charts/ceph-csi-cephfs):
configMapName: "Name of the configmap which contains cluster configuration"
cephConfConfigMapName: "Name of the configmap which contains ceph.conf configuration"
csiConfig: "Configuration for the CSI to connect to the cluster"
However values.yaml also contains cephconf, with the comment "This is a sample configmap that helps define a Ceph configuration as required by the CSI plugins", which is not in the README. Also, both configMapName and cephConfConfigMapName, which are documented in the README, are in a section commented as "Variables for 'internal' use please use with caution!"
Some things appear not to be up to date. For instance, the README mentions the configuration parameters nodeplugin.podSecurityPolicy.enabled and provisioner.podSecurityPolicy.enabled, but as far as I can tell, they are not used in any template:
gpothier@tadzim4:/tmp/ceph-csi $ grep -R charts/ceph-csi-cephfs -e podSecurityPolicy
charts/ceph-csi-cephfs/README.md:| `nodeplugin.podSecurityPolicy.enabled`         | If true, create & use [Pod Security Policy resources](https://kubernetes.io/docs/concepts/policy/pod-security-policy/).                              | `false`                                            |
charts/ceph-csi-cephfs/README.md:| `provisioner.podSecurityPolicy.enabled`        | Specifies whether podSecurityPolicy is enabled                                                                                | `false`                                            |
charts/ceph-csi-cephfs/README.md:helm install --set configMapName=ceph-csi-config --set provisioner.podSecurityPolicy.enabled=true

I've been following instructions from this external page, which helped me a lot: https://www.pivert.org/ceph-csi-on-kubernetes-1-24/, and I think some of these could be included in the README. I would suggest the following:
Explain that a CephFS volume and subvolume group are needed, and how to create them in the cluster, noting that the  subvolume group name is what should be put in csiConfig[x].cephFS.subvolumeGroup and that the volume name is what should be put in storageClass.fsName:
ceph fs volume create myvol
ceph fs subvolumegroup create myvol csi

Explain what to put in the ceph-config ConfigMap (if it is both correct & needed: as stated above, I'm not sure it is, as it appears to have the same information as csiConfig):
kubectl create namespace ceph-csi-cephfs  # If needed

ceph config generate-minimal-conf > /tmp/csi-ceph.conf
kubectl --namespace ceph-csi-cephfs \
	create configmap ceph-config \
	--from-file=ceph.conf=/tmp/csi-ceph.conf

Explain how to create the csi-cephfs-secret secret:
KEY=$(ceph auth get client.admin -f json | jq -r '.[0].key')

kubectl --namespace ceph-csi-cephfs \
	create secret generic csi-cephfs-secret \
	--from-literal=adminID=admin \
	--from-literal=adminKey="${KEY}"

Give an example minimal content for values.yaml:
---
csiConfig:
  - clusterID: <cluster id as returned by ceph config generate-minimal-conf>
    monitors:
      - <list of monitor IPs, as returned by ceph config generate-minimal-conf>
      - ...
      - ...
    cephFS:
      subvolumeGroup: "csi"
      netNamespaceFilePath: "{{ .kubeletDir }}/plugins/{{ .driverName }}/net"

storageClass:
  # Specifies whether the Storage class should be created
  create: true
  name: mysc

  # String representing a Ceph cluster to provision storage from.
  # Should be unique across all Ceph clusters in use for provisioning,
  # cannot be greater than 36 bytes in length, and should remain immutable for
  # the lifetime of the StorageClass in use.
  clusterID: <cluster id as returned by ceph config generate-minimal-conf>
  # (required) CephFS filesystem name into which the volume shall be created
  # eg: fsName: myfs
  fsName: myvol

And finally the Helm install command, which is more or less what is currently in the README:
helm install \
	--namespace ceph-csi-cephfs \
	ceph-csi-cephfs \
	ceph-csi/ceph-csi-cephfs \
	--values values.yaml

After following all these steps, I am finally able to provision PVs, with the subvolume actually created in Ceph and the PVC marked as Bound.
However, I am now stuck with a mount error on pods that try to consume them:
│   Type     Reason       Age                    From     Message                                                                                │
│   ----     ------       ----                   ----     -------                                                                                │
│   Warning  FailedMount  18m (x655 over 25h)    kubelet  Unable to attach or mount volumes: unmounted volumes=[mypvc], unattached volumes=[], failed  │
│ to process volumes=[]: timed out waiting for the condition                                                                                │
│   Warning  FailedMount  3m35s (x745 over 25h)  kubelet  MountVolume.MountDevice failed for volume "pvc-a3c70635-871e-485a-82b0-cc7d423bea41" : rpc e │
│ rror: code = Internal desc = failed to get stat for {{ .kubeletDir }}/plugins/{{ .driverName }}/net stat {{ .kubeletDir }}/plugins/{{ .driverName }} │
│ /net: no such file or directory stderr:

I don't know how to troubleshoot this. I see there are two requirements, but it is not clear how to ensure they are met, or at least check if they are met:

"Your Kubernetes cluster must allow privileged pods (i.e. --allow-privileged flag must be set to true for both the API server and the kubelet)". I understand it is my responsibility as the cluster administrator to ensure it is the case, but it would be nice to have a way to check that it is correctly configured.
Same with "Moreover, as stated in the mount propagation docs, the Docker daemon of the cluster nodes must allow shared mounts.". The linked docs do not explain how this can be configured.

About the section "Running CephCSI with pod networking" (https://github.com/ceph/ceph-csi/blob/devel/examples/README.md#running-cephcsi-with-pod-networking): I see this is a warning that thinks will not work with "pod networking", but it is not clear if it is something that some clusters have, and I don't know how to check if this is what I have. It would be nice to have instructions to check if I have "pod networking", and how to avoid it.

When I was deploying without scripts but with plain manifests, there in not also well documented how to implement KMS configuration in K8s cluster and so on, there is only reference to KMS folder without README.md, because I could not run the deployment because some kms secret, without any referencing it in documentation was missing in my cluster....

I finally was able to mount the provisioned volume in my app pod by removing this line from values.yaml:
netNamespaceFilePath: "{{ .kubeletDir }}/plugins/{{ .driverName }}/net"

The netNamespaceFilePath option is given in the example for csiConfig in the chart's values.yaml: https://github.com/ceph/ceph-csi/blob/5298762c4cbab1eec7b2e467908c98c5d1e38e11/charts/ceph-csi-cephfs/values.yaml#L30
This option enables the "pod networking" mode (https://github.com/ceph/ceph-csi/blob/devel/examples/README.md#running-cephcsi-with-pod-networking), which seems to be a somewhat unsupported mode of operation. I therefore suggest removing the netNamespaceFilePath option from the example in values.yaml, or at least clarify what it does.