+++ /dev/null
-#!/usr/bin/env python3
-
-import argparse
-import os
-import subprocess
-import sys
-
-import yaml
-
-CLI_ARGS_MAIN_PERPLEXITY = [
- "batch-size", "cfg-negative-prompt", "cfg-scale", "chunks", "color", "ctx-size", "escape",
- "export", "file", "frequency-penalty", "grammar", "grammar-file", "hellaswag",
- "hellaswag-tasks", "ignore-eos", "in-prefix", "in-prefix-bos", "in-suffix", "instruct",
- "interactive", "interactive-first", "keep", "logdir", "logit-bias", "lora", "lora-base",
- "low-vram", "main-gpu", "memory-f32", "mirostat", "mirostat-ent", "mirostat-lr", "mlock",
- "model", "multiline-input", "n-gpu-layers", "n-predict", "no-mmap", "no-mul-mat-q",
- "np-penalize-nl", "numa", "ppl-output-type", "ppl-stride", "presence-penalty", "prompt",
- "prompt-cache", "prompt-cache-all", "prompt-cache-ro", "random-prompt", "repeat-last-n",
- "repeat-penalty", "reverse-prompt", "rope-freq-base", "rope-freq-scale", "rope-scale", "seed",
- "simple-io", "tensor-split", "threads", "temp", "tfs", "top-k", "top-p", "typical",
- "verbose-prompt"
-]
-
-CLI_ARGS_LLAMA_BENCH = [
- "batch-size", "memory-f32", "low-vram", "model", "mul-mat-q", "n-gen", "n-gpu-layers",
- "n-prompt", "output", "repetitions", "tensor-split", "threads", "verbose"
-]
-
-CLI_ARGS_SERVER = [
- "alias", "batch-size", "ctx-size", "embedding", "host", "memory-f32", "lora", "lora-base",
- "low-vram", "main-gpu", "mlock", "model", "n-gpu-layers", "n-probs", "no-mmap", "no-mul-mat-q",
- "numa", "path", "port", "rope-freq-base", "timeout", "rope-freq-scale", "tensor-split",
- "threads", "verbose"
-]
-
-description = """Run llama.cpp binaries with presets from YAML file(s).
-To specify which binary should be run, specify the "binary" property (main, perplexity, llama-bench, and server are supported).
-To get a preset file template, run a llama.cpp binary with the "--logdir" CLI argument.
-
-Formatting considerations:
-- The YAML property names are the same as the CLI argument names of the corresponding binary.
-- Properties must use the long name of their corresponding llama.cpp CLI arguments.
-- Like the llama.cpp binaries the property names do not differentiate between hyphens and underscores.
-- Flags must be defined as "<PROPERTY_NAME>: true" to be effective.
-- To define the logit_bias property, the expected format is "<TOKEN_ID>: <BIAS>" in the "logit_bias" namespace.
-- To define multiple "reverse_prompt" properties simultaneously the expected format is a list of strings.
-- To define a tensor split, pass a list of floats.
-"""
-usage = "run_with_preset.py [-h] [yaml_files ...] [--<ARG_NAME> <ARG_VALUE> ...]"
-epilog = (" --<ARG_NAME> specify additional CLI ars to be passed to the binary (override all preset files). "
- "Unknown args will be ignored.")
-
-parser = argparse.ArgumentParser(
- description=description, usage=usage, epilog=epilog, formatter_class=argparse.RawTextHelpFormatter)
-parser.add_argument("-bin", "--binary", help="The binary to run.")
-parser.add_argument("yaml_files", nargs="*",
- help="Arbitrary number of YAML files from which to read preset values. "
- "If two files specify the same values the later one will be used.")
-
-known_args, unknown_args = parser.parse_known_args()
-
-if not known_args.yaml_files and not unknown_args:
- parser.print_help()
- sys.exit(0)
-
-props = dict()
-
-for yaml_file in known_args.yaml_files:
- with open(yaml_file, "r") as f:
- props.update(yaml.load(f, yaml.SafeLoader))
-
-props = {prop.replace("_", "-"): val for prop, val in props.items()}
-
-binary = props.pop("binary", "main")
-if known_args.binary:
- binary = known_args.binary
-
-if os.path.exists(f"./{binary}"):
- binary = f"./{binary}"
-
-if binary.lower().endswith("main") or binary.lower().endswith("perplexity"):
- cli_args = CLI_ARGS_MAIN_PERPLEXITY
-elif binary.lower().endswith("llama-bench"):
- cli_args = CLI_ARGS_LLAMA_BENCH
-elif binary.lower().endswith("server"):
- cli_args = CLI_ARGS_SERVER
-else:
- print(f"Unknown binary: {binary}")
- sys.exit(1)
-
-command_list = [binary]
-
-for cli_arg in cli_args:
- value = props.pop(cli_arg, None)
-
- if not value or value == -1:
- continue
-
- if cli_arg == "logit-bias":
- for token, bias in value.items():
- command_list.append("--logit-bias")
- command_list.append(f"{token}{bias:+}")
- continue
-
- if cli_arg == "reverse-prompt" and not isinstance(value, str):
- for rp in value:
- command_list.append("--reverse-prompt")
- command_list.append(str(rp))
- continue
-
- command_list.append(f"--{cli_arg}")
-
- if cli_arg == "tensor-split":
- command_list.append(",".join([str(v) for v in value]))
- continue
-
- value = str(value)
-
- if value != "True":
- command_list.append(str(value))
-
-num_unused = len(props)
-if num_unused > 10:
- print(f"The preset file contained a total of {num_unused} unused properties.")
-elif num_unused > 0:
- print("The preset file contained the following unused properties:")
- for prop, value in props.items():
- print(f" {prop}: {value}")
-
-command_list += unknown_args
-
-sp = subprocess.Popen(command_list)
-
-while sp.returncode is None:
- try:
- sp.wait()
- except KeyboardInterrupt:
- pass
-
-sys.exit(sp.returncode)
--- /dev/null
+#!/usr/bin/env python3
+
+import argparse
+import os
+import subprocess
+import sys
+
+import yaml
+
+CLI_ARGS_MAIN_PERPLEXITY = [
+ "batch-size", "cfg-negative-prompt", "cfg-scale", "chunks", "color", "ctx-size", "escape",
+ "export", "file", "frequency-penalty", "grammar", "grammar-file", "hellaswag",
+ "hellaswag-tasks", "ignore-eos", "in-prefix", "in-prefix-bos", "in-suffix", "instruct",
+ "interactive", "interactive-first", "keep", "logdir", "logit-bias", "lora", "lora-base",
+ "low-vram", "main-gpu", "memory-f32", "mirostat", "mirostat-ent", "mirostat-lr", "mlock",
+ "model", "multiline-input", "n-gpu-layers", "n-predict", "no-mmap", "no-mul-mat-q",
+ "np-penalize-nl", "numa", "ppl-output-type", "ppl-stride", "presence-penalty", "prompt",
+ "prompt-cache", "prompt-cache-all", "prompt-cache-ro", "random-prompt", "repeat-last-n",
+ "repeat-penalty", "reverse-prompt", "rope-freq-base", "rope-freq-scale", "rope-scale", "seed",
+ "simple-io", "tensor-split", "threads", "temp", "tfs", "top-k", "top-p", "typical",
+ "verbose-prompt"
+]
+
+CLI_ARGS_LLAMA_BENCH = [
+ "batch-size", "memory-f32", "low-vram", "model", "mul-mat-q", "n-gen", "n-gpu-layers",
+ "n-prompt", "output", "repetitions", "tensor-split", "threads", "verbose"
+]
+
+CLI_ARGS_SERVER = [
+ "alias", "batch-size", "ctx-size", "embedding", "host", "memory-f32", "lora", "lora-base",
+ "low-vram", "main-gpu", "mlock", "model", "n-gpu-layers", "n-probs", "no-mmap", "no-mul-mat-q",
+ "numa", "path", "port", "rope-freq-base", "timeout", "rope-freq-scale", "tensor-split",
+ "threads", "verbose"
+]
+
+description = """Run llama.cpp binaries with presets from YAML file(s).
+To specify which binary should be run, specify the "binary" property (main, perplexity, llama-bench, and server are supported).
+To get a preset file template, run a llama.cpp binary with the "--logdir" CLI argument.
+
+Formatting considerations:
+- The YAML property names are the same as the CLI argument names of the corresponding binary.
+- Properties must use the long name of their corresponding llama.cpp CLI arguments.
+- Like the llama.cpp binaries the property names do not differentiate between hyphens and underscores.
+- Flags must be defined as "<PROPERTY_NAME>: true" to be effective.
+- To define the logit_bias property, the expected format is "<TOKEN_ID>: <BIAS>" in the "logit_bias" namespace.
+- To define multiple "reverse_prompt" properties simultaneously the expected format is a list of strings.
+- To define a tensor split, pass a list of floats.
+"""
+usage = "run-with-preset.py [-h] [yaml_files ...] [--<ARG_NAME> <ARG_VALUE> ...]"
+epilog = (" --<ARG_NAME> specify additional CLI ars to be passed to the binary (override all preset files). "
+ "Unknown args will be ignored.")
+
+parser = argparse.ArgumentParser(
+ description=description, usage=usage, epilog=epilog, formatter_class=argparse.RawTextHelpFormatter)
+parser.add_argument("-bin", "--binary", help="The binary to run.")
+parser.add_argument("yaml_files", nargs="*",
+ help="Arbitrary number of YAML files from which to read preset values. "
+ "If two files specify the same values the later one will be used.")
+
+known_args, unknown_args = parser.parse_known_args()
+
+if not known_args.yaml_files and not unknown_args:
+ parser.print_help()
+ sys.exit(0)
+
+props = dict()
+
+for yaml_file in known_args.yaml_files:
+ with open(yaml_file, "r") as f:
+ props.update(yaml.load(f, yaml.SafeLoader))
+
+props = {prop.replace("_", "-"): val for prop, val in props.items()}
+
+binary = props.pop("binary", "main")
+if known_args.binary:
+ binary = known_args.binary
+
+if os.path.exists(f"./{binary}"):
+ binary = f"./{binary}"
+
+if binary.lower().endswith("main") or binary.lower().endswith("perplexity"):
+ cli_args = CLI_ARGS_MAIN_PERPLEXITY
+elif binary.lower().endswith("llama-bench"):
+ cli_args = CLI_ARGS_LLAMA_BENCH
+elif binary.lower().endswith("server"):
+ cli_args = CLI_ARGS_SERVER
+else:
+ print(f"Unknown binary: {binary}")
+ sys.exit(1)
+
+command_list = [binary]
+
+for cli_arg in cli_args:
+ value = props.pop(cli_arg, None)
+
+ if not value or value == -1:
+ continue
+
+ if cli_arg == "logit-bias":
+ for token, bias in value.items():
+ command_list.append("--logit-bias")
+ command_list.append(f"{token}{bias:+}")
+ continue
+
+ if cli_arg == "reverse-prompt" and not isinstance(value, str):
+ for rp in value:
+ command_list.append("--reverse-prompt")
+ command_list.append(str(rp))
+ continue
+
+ command_list.append(f"--{cli_arg}")
+
+ if cli_arg == "tensor-split":
+ command_list.append(",".join([str(v) for v in value]))
+ continue
+
+ value = str(value)
+
+ if value != "True":
+ command_list.append(str(value))
+
+num_unused = len(props)
+if num_unused > 10:
+ print(f"The preset file contained a total of {num_unused} unused properties.")
+elif num_unused > 0:
+ print("The preset file contained the following unused properties:")
+ for prop, value in props.items():
+ print(f" {prop}: {value}")
+
+command_list += unknown_args
+
+sp = subprocess.Popen(command_list)
+
+while sp.returncode is None:
+ try:
+ sp.wait()
+ except KeyboardInterrupt:
+ pass
+
+sys.exit(sp.returncode)