Initial commit

llama_toolchain/cli/inference/configure.py

@@ -0,0 +1,91 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import argparse
+import os
+import textwrap
+
+from pathlib import Path
+
+import pkg_resources
+
+from llama_toolchain.cli.subcommand import Subcommand
+from llama_toolchain.utils import DEFAULT_DUMP_DIR
+
+
+CONFIGS_BASE_DIR = os.path.join(DEFAULT_DUMP_DIR, "configs")
+
+
+class InferenceConfigure(Subcommand):
+    """Llama cli for configuring llama toolchain configs"""
+
+    def __init__(self, subparsers: argparse._SubParsersAction):
+        super().__init__()
+        self.parser = subparsers.add_parser(
+            "configure",
+            prog="llama inference configure",
+            description="Configure llama toolchain inference configs",
+            epilog=textwrap.dedent(
+                """
+                Example:
+                    llama inference configure
+                """
+            ),
+            formatter_class=argparse.RawTextHelpFormatter,
+        )
+        self._add_arguments()
+        self.parser.set_defaults(func=self._run_inference_configure_cmd)
+
+    def _add_arguments(self):
+        pass
+
+    def read_user_inputs(self):
+        checkpoint_dir = input(
+            "Enter the checkpoint directory for the model (e.g., ~/.llama/checkpoints/Meta-Llama-3-8B/): "
+        )
+        model_parallel_size = input(
+            "Enter model parallel size (e.g., 1 for 8B / 8 for 70B and 405B): "
+        )
+        assert model_parallel_size.isdigit() and int(model_parallel_size) in {
+            1,
+            8,
+        }, "model parallel size must be 1 or 8"
+
+        return checkpoint_dir, model_parallel_size
+
+    def write_output_yaml(self, checkpoint_dir, model_parallel_size, yaml_output_path):
+        default_conf_path = pkg_resources.resource_filename(
+            "llama_toolchain", "data/default_inference_config.yaml"
+        )
+        with open(default_conf_path, "r") as f:
+            yaml_content = f.read()
+
+        yaml_content = yaml_content.format(
+            checkpoint_dir=checkpoint_dir,
+            model_parallel_size=model_parallel_size,
+        )
+
+        with open(yaml_output_path, "w") as yaml_file:
+            yaml_file.write(yaml_content.strip())
+
+        print(f"YAML configuration has been written to {yaml_output_path}")
+
+    def _run_inference_configure_cmd(self, args: argparse.Namespace) -> None:
+        checkpoint_dir, model_parallel_size = self.read_user_inputs()
+        checkpoint_dir = os.path.expanduser(checkpoint_dir)
+
+        assert (
+            Path(checkpoint_dir).exists() and Path(checkpoint_dir).is_dir()
+        ), f"{checkpoint_dir} does not exist or it not a directory"
+
+        os.makedirs(CONFIGS_BASE_DIR, exist_ok=True)
+        yaml_output_path = Path(CONFIGS_BASE_DIR) / "inference.yaml"
+
+        self.write_output_yaml(
+            checkpoint_dir,
+            model_parallel_size,
+            yaml_output_path,
+        )