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utils.py
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def add_common_args(parser):
parser.add_argument('--max_new_tokens', type=int, default=128)
parser.add_argument('--batch_size', type=int, default=1)
parser.add_argument('--log_level', type=str, default='info')
parser.add_argument('--visual_engine_dir',
type=str,
default=None,
help='Directory containing visual TRT engines')
parser.add_argument('--visual_engine_name',
type=str,
default='model.engine',
help='Name of visual TRT engine')
parser.add_argument('--llm_engine_dir',
type=str,
default=None,
help='Directory containing TRT-LLM engines')
parser.add_argument('--hf_model_dir',
type=str,
default=None,
help="Directory containing tokenizer")
parser.add_argument('--input_text',
type=str,
nargs='+',
default=None,
help='Text prompt to LLM')
parser.add_argument('--num_beams',
type=int,
help="Use beam search if num_beams >1",
default=1)
parser.add_argument('--top_k', type=int, default=1)
parser.add_argument('--top_p', type=float, default=0.0)
parser.add_argument('--temperature', type=float, default=1.0)
parser.add_argument('--repetition_penalty', type=float, default=1.0)
parser.add_argument('--run_profiling',
action='store_true',
help='Profile runtime over several iterations')
parser.add_argument('--profiling_iterations',
type=int,
help="Number of iterations to run profiling",
default=20)
parser.add_argument('--check_accuracy',
action='store_true',
help='Check correctness of text output')
parser.add_argument(
'--video_path',
type=str,
default=None,
help=
'Path to your local video file, using \'llava-onevision-accuracy\' to check the Llava-OneVision model accuracy'
)
parser.add_argument(
'--video_num_frames',
type=int,
help=
"The number of frames sampled from the video in the Llava-OneVision model.",
default=None)
parser.add_argument("--image_path",
type=str,
nargs='+',
default=None,
help='List of input image paths, separated by symbol')
parser.add_argument("--path_sep",
type=str,
default=",",
help='Path separator symbol')
parser.add_argument('--enable_context_fmha_fp32_acc',
action='store_true',
default=None,
help="Enable FMHA runner FP32 accumulation.")
parser.add_argument(
'--enable_chunked_context',
action='store_true',
help='Enables chunked context (only available with cpp session).',
)
parser.add_argument(
'--use_py_session',
default=False,
action='store_true',
help=
"Whether or not to use Python runtime session. By default C++ runtime session is used for the LLM."
)
parser.add_argument(
'--kv_cache_free_gpu_memory_fraction',
default=0.9,
type=float,
help='Specify the free gpu memory fraction.',
)
parser.add_argument(
'--cross_kv_cache_fraction',
default=0.5,
type=float,
help=
'Specify the kv cache fraction reserved for cross attention. Only applicable for encoder-decoder models. By default 0.5 for self and 0.5 for cross.',
)
parser.add_argument(
'--multi_block_mode',
type=lambda s: s.lower() in
("yes", "true", "t", "1"
), # custom boolean function to convert input string to boolean
default=True,
help=
"Distribute the work across multiple CUDA thread-blocks on the GPU for masked MHA kernel."
)
return parser