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eval_cmd_generator.py
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# Copyright 2023 Amirkeivan Mohtashami, Martin Jaggi
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import dataclasses
@dataclasses.dataclass
class Setting(object):
exp_dir: str
eval_len: int
topk: int
mem_size: int
mid_length: int
use_cache: bool = True
selection_method: str = "per_token_and_head"
mem_cache_freq: int = 50
eval_sample_size: int = 4000000
lm_cache: str = "mem"
exp_dirs = {
"arxiv_landmark": "./exps/arxiv_landmark",
"arxiv_baseline": "./exps/arxiv_baseline",
"pg19_landmark": "./exps/pg19_landmark",
"pg19_baseline": "./exps/pg19_baseline",
"pg19_xl": "./exps/pg19_xl",
}
settings = [
dict(exp_dir=exp_dirs["pg19_baseline"], eval_len=360, mid_length=360,
lm_cache="none", mem_cache_freq=None, mem_size=None, topk=None, use_cache=False,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_baseline"], eval_len=512, mid_length=512,
lm_cache="none", mem_cache_freq=None, mem_size=None, topk=None, use_cache=False,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_xl"], eval_len=2048, mid_length=256,
lm_cache="kv", mem_cache_freq=None, mem_size=256, topk=None,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_xl"], eval_len=4096, mid_length=256,
lm_cache="kv", mem_cache_freq=None, mem_size=256, topk=None,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=512, mid_length=250, mem_size=10, topk=2,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=2,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=350, mem_size=40, topk=2,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=300, mem_size=40, topk=3,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=250, mem_size=20, topk=4,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=4,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=4096, mid_length=250, mem_size=40, topk=4,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=4096, mid_length=250, mem_size=80, topk=2,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=4096, mid_length=250, mem_size=80, topk=4,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=2,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=4,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=4096, mid_length=250, mem_size=40, topk=4,eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=2,
selection_method="max_over_heads",eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=4,
selection_method="max_over_heads",eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=4096, mid_length=250, mem_size=80, topk=4,
selection_method="max_over_heads",eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=2,
selection_method="max_over_tokens",eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=4,
selection_method="max_over_tokens",eval_sample_size=None),
dict(exp_dir=exp_dirs["pg19_landmark"], eval_len=4096, mid_length=250, mem_size=80, topk=4,
selection_method="max_over_tokens",eval_sample_size=None),
dict(exp_dir=exp_dirs["arxiv_baseline"], eval_len=360, mid_length=360,
lm_cache=None, mem_cache_freq=None, mem_size=None, topk=None, use_cache=False),
dict(exp_dir=exp_dirs["arxiv_baseline"], eval_len=512, mid_length=512,
lm_cache=None, mem_cache_freq=None, mem_size=None, topk=None, use_cache=False),
dict(exp_dir=exp_dirs["arxiv_landmark"], eval_len=512, mid_length=250, mem_size=10, topk=2),
dict(exp_dir=exp_dirs["arxiv_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=2),
dict(exp_dir=exp_dirs["arxiv_landmark"], eval_len=2048, mid_length=350, mem_size=40, topk=2),
dict(exp_dir=exp_dirs["arxiv_landmark"], eval_len=2048, mid_length=300, mem_size=40, topk=3),
dict(exp_dir=exp_dirs["arxiv_landmark"], eval_len=2048, mid_length=250, mem_size=20, topk=4),
dict(exp_dir=exp_dirs["arxiv_landmark"], eval_len=2048, mid_length=250, mem_size=40, topk=4),
dict(exp_dir=exp_dirs["arxiv_landmark"], eval_len=4096, mid_length=250, mem_size=40, topk=4),
dict(exp_dir=exp_dirs["arxiv_landmark"], eval_len=4096, mid_length=250, mem_size=80, topk=2),
dict(exp_dir=exp_dirs["arxiv_landmark"], eval_len=4096, mid_length=250, mem_size=80, topk=4),
]
import itertools
def product_dict(**kwargs):
keys = kwargs.keys()
for instance in itertools.product(*kwargs.values()):
yield dict(zip(keys, instance))
flat_settings = []
for setting in settings:
flat_settings.extend(product_dict(**{x: y if isinstance(y, list) else [y] for x, y in setting.items()}))
settings = [Setting(**d) for d in flat_settings]
last_exp_dir = None
print ("#!/bin/bash")
for setting in settings:
s_lines = []
if last_exp_dir != setting.exp_dir:
s_lines.append("""EXP_DIR="{exp_dir}";""".format(**dataclasses.asdict(setting)))
last_exp_dir = setting.exp_dir
use_cache_str = "--use_cache" if setting.use_cache else ""
mem_size_flag = ""
s_lines += ["""
filename="$EXP_DIR/eval-{eval_len}-{selection_method}-{topk}-memsize{mem_size}-midlength{mid_length}-memcachefreq{mem_cache_freq}";
grep val_acc $filename /dev/null;
if [[ $? -ne 0 ]]; then
script -c \\
"python eval.py \\
--checkpoint $EXP_DIR \\
--distributed_backend None \\
--lm_cache {lm_cache} \\""","""
--mem_cache_size {mem_size} \\""" if setting.mem_size is not None else "","""
--mem_cache_freq {mem_cache_freq} \\""" if setting.mem_cache_freq is not None else "", """
--mem_freq None \\
--eval_seq_length {eval_len} \\
--cache_selection_method {selection_method} \\""","""
--cache_topk {topk} \\""" if setting.topk is not None else "", """
--no_compile \\
--batch_size 16 \\
--mid_length {mid_length} \\
--positional_encoder rotary \\
--pos_jump_on_mem 0 \\
{use_cache_str} \\""", """
--eval_sample_size {eval_sample_size}""" if setting.eval_sample_size is not None else "", """
" $filename;
fi;"""]
print ("".join(s_lines).format(**dataclasses.asdict(setting), use_cache_str=use_cache_str))