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Replace --mul_mat_q with --no_mul_mat_q

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oobabooga 2023-10-22 12:22:06 -07:00
parent d0c3b407b3
commit df90d03e0b
9 changed files with 12 additions and 11 deletions
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2
Colab-TextGen-GPU.ipynb
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@ -89,7 +89,7 @@
"# Parameters\n",
"model_url = \"https://huggingface.co/turboderp/Mistral-7B-instruct-exl2\" #@param {type:\"string\"}\n",
"branch = \"4.0bpw\" #@param {type:\"string\"}\n",
"command_line_flags = \"--n-gpu-layers 128 --mul_mat_q --load-in-4bit --use_double_quant\" #@param {type:\"string\"}\n",
"command_line_flags = \"--n-gpu-layers 128 --load-in-4bit --use_double_quant\" #@param {type:\"string\"}\n",
"api = False #@param {type:\"boolean\"}\n",
"\n",
"if api:\n",

2
README.md
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@ -319,7 +319,7 @@ Optionally, you can use the following command-line flags:
| `--n_ctx N_CTX` | Size of the prompt context. |
| `--threads` | Number of threads to use. |
| `--threads-batch THREADS_BATCH` | Number of threads to use for batches/prompt processing. |
| `--mul_mat_q` | Activate new mulmat kernels. |
| `--no_mul_mat_q` | Disable the mulmat kernels. |
| `--n_batch` | Maximum number of prompt tokens to batch together when calling llama_eval. |
| `--no-mmap` | Prevent mmap from being used. |
| `--mlock` | Force the system to keep the model in RAM. |

2
docs/04 ‐ Model Tab.md
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@ -90,7 +90,7 @@ Example: https://huggingface.co/TheBloke/Llama-2-7b-Chat-GGUF
* **threads**: Number of threads. Recommended value: your number of physical cores.
* **threads_batch**: Number of threads for batch processing. Recommended value: your total number of cores (physical + virtual).
* **n_batch**: Batch size for prompt processing. Higher values are supposed to make generation faster, but I have never obtained any benefit from changing this value.
* **mul_mat_q**: Use the mul_mat_q kernel. This usually improves generation speed significantly.
* **mul_mat_q**: Disable the mul_mat_q kernel. This kernel usually improves generation speed significantly. This option to disable it is included in case it doesn't work on some system.
* **no-mmap**: Loads the model into memory at once, possibly preventing I/O operations later on at the cost of a longer load time.
* **mlock**: Force the system to keep the model in RAM rather than swapping or compressing (no idea what this means, never used it).
* **numa**: May improve performance on certain multi-cpu systems.

2
modules/llamacpp_hf.py
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@ -198,7 +198,7 @@ class LlamacppHF(PreTrainedModel):
'n_batch': shared.args.n_batch,
'use_mmap': not shared.args.no_mmap,
'use_mlock': shared.args.mlock,
'mul_mat_q': shared.args.mul_mat_q,
'mul_mat_q': not shared.args.no_mul_mat_q,
'numa': shared.args.numa,
'n_gpu_layers': shared.args.n_gpu_layers,
'rope_freq_base': RoPE.get_rope_freq_base(shared.args.alpha_value, shared.args.rope_freq_base),

2
modules/llamacpp_model.py
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@ -80,7 +80,7 @@ class LlamaCppModel:
'n_batch': shared.args.n_batch,
'use_mmap': not shared.args.no_mmap,
'use_mlock': shared.args.mlock,
'mul_mat_q': shared.args.mul_mat_q,
'mul_mat_q': not shared.args.no_mul_mat_q,
'numa': shared.args.numa,
'n_gpu_layers': shared.args.n_gpu_layers,
'rope_freq_base': RoPE.get_rope_freq_base(shared.args.alpha_value, shared.args.rope_freq_base),

4
modules/loaders.py
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@ -94,7 +94,7 @@ loaders_and_params = OrderedDict({
'threads_batch',
'no_mmap',
'mlock',
'mul_mat_q',
'no_mul_mat_q',
'llama_cpp_seed',
'alpha_value',
'rope_freq_base',
@ -111,7 +111,7 @@ loaders_and_params = OrderedDict({
'threads_batch',
'no_mmap',
'mlock',
'mul_mat_q',
'no_mul_mat_q',
'alpha_value',
'rope_freq_base',
'compress_pos_emb',

5
modules/shared.py
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@ -103,7 +103,7 @@ parser.add_argument('--quant_type', type=str, default='nf4', help='quant_type fo
parser.add_argument('--n_ctx', type=int, default=2048, help='Size of the prompt context.')
parser.add_argument('--threads', type=int, default=0, help='Number of threads to use.')
parser.add_argument('--threads-batch', type=int, default=0, help='Number of threads to use for batches/prompt processing.')
parser.add_argument('--mul_mat_q', action='store_true', help='Activate new mulmat kernels.')
parser.add_argument('--no_mul_mat_q', action='store_true', help='Disable the mulmat kernels.')
parser.add_argument('--n_batch', type=int, default=512, help='Maximum number of prompt tokens to batch together when calling llama_eval.')
parser.add_argument('--no-mmap', action='store_true', help='Prevent mmap from being used.')
parser.add_argument('--mlock', action='store_true', help='Force the system to keep the model in RAM.')
@ -173,6 +173,7 @@ parser.add_argument('--multimodal-pipeline', type=str, default=None, help='The m
parser.add_argument('--notebook', action='store_true', help='DEPRECATED')
parser.add_argument('--chat', action='store_true', help='DEPRECATED')
parser.add_argument('--no-stream', action='store_true', help='DEPRECATED')
parser.add_argument('--mul_mat_q', action='store_true', help='DEPRECATED')
args = parser.parse_args()
args_defaults = parser.parse_args([])
@ -183,7 +184,7 @@ for arg in sys.argv[1:]:
provided_arguments.append(arg)
# Deprecation warnings
for k in ['chat', 'notebook', 'no_stream']:
for k in ['chat', 'notebook', 'no_stream', 'mul_mat_q']:
if getattr(args, k):
logger.warning(f'The --{k} flag has been deprecated and will be removed soon. Please remove that flag.')

2
modules/ui.py
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@ -73,7 +73,7 @@ def list_model_elements():
'n_batch',
'no_mmap',
'mlock',
'mul_mat_q',
'no_mul_mat_q',
'n_gpu_layers',
'tensor_split',
'n_ctx',

2
modules/ui_model_menu.py
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@ -103,7 +103,7 @@ def create_ui():
shared.gradio['no_inject_fused_mlp'] = gr.Checkbox(label="no_inject_fused_mlp", value=shared.args.no_inject_fused_mlp, info='Affects Triton only. Disable fused MLP. Fused MLP improves performance but uses more VRAM. Disable if running low on VRAM.')
shared.gradio['no_use_cuda_fp16'] = gr.Checkbox(label="no_use_cuda_fp16", value=shared.args.no_use_cuda_fp16, info='This can make models faster on some systems.')
shared.gradio['desc_act'] = gr.Checkbox(label="desc_act", value=shared.args.desc_act, info='\'desc_act\', \'wbits\', and \'groupsize\' are used for old models without a quantize_config.json.')
shared.gradio['mul_mat_q'] = gr.Checkbox(label="mul_mat_q", value=shared.args.mul_mat_q, info='Recommended in most cases. Improves generation speed by 10-20%.')
shared.gradio['no_mul_mat_q'] = gr.Checkbox(label="no_mul_mat_q", value=shared.args.no_mul_mat_q, info='Disable the mulmat kernels.')
shared.gradio['cfg_cache'] = gr.Checkbox(label="cfg-cache", value=shared.args.cfg_cache, info='Create an additional cache for CFG negative prompts.')
shared.gradio['no_mmap'] = gr.Checkbox(label="no-mmap", value=shared.args.no_mmap)
shared.gradio['mlock'] = gr.Checkbox(label="mlock", value=shared.args.mlock)