"vllm/vscode:/vscode.git/clone" did not exist on "0cd5353644d3d045ab33c7e8e19c182bfd7db911"
Commit 4c676e3d authored by zhuwenwen's avatar zhuwenwen
Browse files

Merge tag 'v0.9.1' into v0.9.1-dev

parents b4c4464d b6553be1
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# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import argparse
import json
......@@ -7,9 +8,9 @@ import os
from typing import Any
def convert_to_pytorch_benchmark_format(args: argparse.Namespace,
metrics: dict[str, list],
extra_info: dict[str, Any]) -> list:
def convert_to_pytorch_benchmark_format(
args: argparse.Namespace, metrics: dict[str, list], extra_info: dict[str, Any]
) -> list:
"""
Save the benchmark results in the format used by PyTorch OSS benchmark with
on metric per record
......@@ -37,12 +38,12 @@ def convert_to_pytorch_benchmark_format(args: argparse.Namespace,
},
}
tp = record["benchmark"]["extra_info"]["args"].get(
"tensor_parallel_size")
tp = record["benchmark"]["extra_info"]["args"].get("tensor_parallel_size")
# Save tensor_parallel_size parameter if it's part of the metadata
if not tp and "tensor_parallel_size" in extra_info:
record["benchmark"]["extra_info"]["args"][
"tensor_parallel_size"] = extra_info["tensor_parallel_size"]
record["benchmark"]["extra_info"]["args"]["tensor_parallel_size"] = (
extra_info["tensor_parallel_size"]
)
records.append(record)
......@@ -50,7 +51,6 @@ def convert_to_pytorch_benchmark_format(args: argparse.Namespace,
class InfEncoder(json.JSONEncoder):
def clear_inf(self, o: Any):
if isinstance(o, dict):
return {k: self.clear_inf(v) for k, v in o.items()}
......@@ -66,4 +66,9 @@ class InfEncoder(json.JSONEncoder):
def write_to_json(filename: str, records: list) -> None:
with open(filename, "w") as f:
json.dump(records, f, cls=InfEncoder)
json.dump(
records,
f,
cls=InfEncoder,
default=lambda o: f"<{type(o).__name__} object is not JSON serializable>",
)
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# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
# Weight Shapes are in the format
# ([K, N], TP_SPLIT_DIM)
......
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