forked from phoenix-oss/llama-stack-mirror
91 lines
2.9 KiB
Python
91 lines
2.9 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import argparse
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import os
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import textwrap
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from pathlib import Path
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import pkg_resources
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from llama_toolchain.cli.subcommand import Subcommand
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from llama_toolchain.utils import DEFAULT_DUMP_DIR
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CONFIGS_BASE_DIR = os.path.join(DEFAULT_DUMP_DIR, "configs")
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class InferenceConfigure(Subcommand):
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"""Llama cli for configuring llama toolchain configs"""
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def __init__(self, subparsers: argparse._SubParsersAction):
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super().__init__()
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self.parser = subparsers.add_parser(
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"configure",
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prog="llama inference configure",
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description="Configure llama toolchain inference configs",
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epilog=textwrap.dedent(
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"""
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Example:
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llama inference configure
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"""
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),
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formatter_class=argparse.RawTextHelpFormatter,
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)
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self._add_arguments()
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self.parser.set_defaults(func=self._run_inference_configure_cmd)
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def _add_arguments(self):
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pass
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def read_user_inputs(self):
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checkpoint_dir = input(
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"Enter the checkpoint directory for the model (e.g., ~/.llama/checkpoints/Meta-Llama-3-8B/): "
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)
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model_parallel_size = input(
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"Enter model parallel size (e.g., 1 for 8B / 8 for 70B and 405B): "
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)
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assert model_parallel_size.isdigit() and int(model_parallel_size) in {
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1,
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8,
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}, "model parallel size must be 1 or 8"
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return checkpoint_dir, model_parallel_size
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def write_output_yaml(self, checkpoint_dir, model_parallel_size, yaml_output_path):
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default_conf_path = pkg_resources.resource_filename(
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"llama_toolchain", "data/default_inference_config.yaml"
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)
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with open(default_conf_path, "r") as f:
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yaml_content = f.read()
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yaml_content = yaml_content.format(
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checkpoint_dir=checkpoint_dir,
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model_parallel_size=model_parallel_size,
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)
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with open(yaml_output_path, "w") as yaml_file:
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yaml_file.write(yaml_content.strip())
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print(f"YAML configuration has been written to {yaml_output_path}")
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def _run_inference_configure_cmd(self, args: argparse.Namespace) -> None:
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checkpoint_dir, model_parallel_size = self.read_user_inputs()
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checkpoint_dir = os.path.expanduser(checkpoint_dir)
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assert (
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Path(checkpoint_dir).exists() and Path(checkpoint_dir).is_dir()
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), f"{checkpoint_dir} does not exist or it not a directory"
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os.makedirs(CONFIGS_BASE_DIR, exist_ok=True)
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yaml_output_path = Path(CONFIGS_BASE_DIR) / "inference.yaml"
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self.write_output_yaml(
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checkpoint_dir,
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model_parallel_size,
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yaml_output_path,
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)
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