def experiment_definitions():
rm4 = combos(
bind_nested("task", utils.tldr_task),
bind("mpi", 1),
bind_nested("reward_model_spec", utils.rm4()),
bind(
"input_path",
"https://openaipublic.blob.core.windows.net/summarize-from-feedback/samples/sup4_ppo_rm4"
),
)
test = combos(
bind_nested("task", utils.test_task),
bind_nested("reward_model_spec", utils.random_teeny_model_spec()),
bind("mpi", 1),
bind(
"input_path",
"https://openaipublic.blob.core.windows.net/summarize-from-feedback/samples/test"
),
)
test_cpu = combos(
test,
bind_nested("reward_model_spec", utils.stub_model_spec()),
)
tldrtest = combos(
bind_nested("task", utils.test_tldr_task),
bind_nested("reward_model_spec",
utils.random_teeny_model_spec(n_shards=2)),
bind("mpi", 2),
)
return locals()
def random_teeny_model_spec(**run_params):
return combos(
bind(
"load_path",
"https://openaipublic.blob.core.windows.net/summarize-from-feedback/models/random-teeny"
),
*[bind(f"run_params.{k}", v) for (k, v) in run_params.items()],
)
def fn(name, trials, **extra_args):
# Bind remaining extra arguments from the defaults and from the command line
trials = combos(
*[bind(k, v) for k, v in default_bindings.items()],
trials,
*[bind(k, v) for k, v in extra_args.items()],
)
exp_jobs = get_experiment_jobs(name, main_fn, trials)
return jobs.multilaunch(exp_jobs)
def experiment_definitions():
sup_xl = combos(
bind_nested("model_spec", utils.sup4()),
bind_nested("task", utils.tldr_task),
bind("query_dataset_split", "valid"),
bind("mpi", 1),
bind("num_queries", 128),
bind("sample.temperature", 0.01),
)
ppo_xl = combos(
bind_nested("model_spec", utils.sup4_ppo_rm4()),
bind_nested("task", utils.tldr_task),
bind("query_dataset_split", "valid"),
bind("mpi", 1),
bind("num_queries", 128),
bind("sample.temperature", 0.01),
)
test = combos(
bind_nested("task", utils.test_task),
bind_nested("model_spec", utils.random_teeny_model_spec(n_shards=2)),
bind_nested("orig_model_spec", utils.random_teeny_model_spec(n_shards=2)),
bind("query_dataset_split", "train"),
bind("mpi", 2),
bind("num_queries", 8),
bind("responses_per_query", 2),
bind("responses_per_query_per_batch", 1),
)
test_cpu = combos(
test,
bind("model_spec.device", "cpu"),
bind("orig_model_spec.device", "cpu"),
bind("fp16_activations", False),
)
return locals()
def load_model_spec(load_path, short_name=None, **run_params):
return combos(
bind("load_path", load_path),
bind("short_name", short_name),
*[bind(f"run_params.{k}", v) for (k, v) in run_params.items()],
)
from functools import partial
from summarize_from_feedback import encoder
from summarize_from_feedback.utils.combos import combos, bind, options_shortdesc
def seeds(n):
return options_shortdesc("seed", "s", range(1, 1 + n))
cnndm_task = combos(
bind("query.format_str", "Article:\n{article}\n\nTL;DR:\n"),
bind("query.dataset", "cnndm"),
bind("query.length", 2047 - 128),
bind("response.length", 128),
bind("query.truncate_text", "\n"),
bind("query.truncate_field", "article"),
bind("query.pad_side", "left"),
bind("response.truncate_token", 50256), # endoftext
bind("response.ref_format_str", "{reference}"),
)
cnndm_task_filtered = combos(
cnndm_task,
bind("query.dataset", "cnndm_filtered"),
bind("query.length", 2047 - 64),
bind("response.length", 64),
)
cnndm_task_filtered_short = combos(
cnndm_task,
