From 8b2c96c41066ccf7dba2e040c40649afef968dea Mon Sep 17 00:00:00 2001
From: Yifan Zhao <yifanz16@illinois.edu>
Date: Tue, 6 Apr 2021 23:43:27 -0500
Subject: [PATCH] Changing metadata protocol
---
predtuner/pipedbin.py | 26 ++++++++++----------------
1 file changed, 10 insertions(+), 16 deletions(-)
diff --git a/predtuner/pipedbin.py b/predtuner/pipedbin.py
index bfa277c..81581b6 100644
--- a/predtuner/pipedbin.py
+++ b/predtuner/pipedbin.py
@@ -165,37 +165,31 @@ class PipedBinaryApp(ModeledApp):
metadata = json.load(f)
op_costs = metadata["op_cost"]
op_knobs = metadata["op_knobs"]
- knob_speedup = metadata["knob_speedup"]
- knob_devices = metadata["knob_devices"]
- baseline_knob = metadata["baseline_knob"]
+ knobs = metadata["knobs"]
# Check sanity
if set(op_costs.keys()) != set(op_knobs.keys()):
raise ValueError(
"Operators listed in layer_cost and knobs_of_layer mismatch"
)
- if set(knob_speedup.keys()) != set(knob_devices.keys()):
- raise ValueError(
- "Knobs listed in knob_speedup and knob_devices mismatch"
- )
knobs_used = set().union(*[set(knobs) for knobs in op_knobs.values()])
- knobs_defined = set(knob_speedup.keys())
+ knobs_defined = set(knobs.keys())
undefined = knobs_used - knobs_defined
if undefined:
raise ValueError(
f"These knobs used in knobs_of_layer are undefined: {undefined}"
)
- if baseline_knob not in knobs_defined:
- raise ValueError(f"baseline_knob {baseline_knob} is undefined")
# Create actual knob object from knob names
- name2knob = {
- s: ApproxKnob(s, knob_devices[s], (0 if s == baseline_knob else None))
- for s in knobs_used
- }
- op_knobs = {op: [name2knob[k] for k in knobs] for op, knobs in op_knobs.items()}
+ knob_objs = {}
+ knob_speedup = {}
+ for knob_name, knob_args in knobs.items():
+ knob_speedup[knob_name] = knob_args.pop("speedup")
+ knob_objs[knob_name] = ApproxKnob(knob_name, **knob_args)
+ op_knobs = {op: [knob_objs[k] for k in knobs] for op, knobs in op_knobs.items()}
+ # Process other fields in metadata
tune_labels_file = Path(metadata["tune_labels_path"])
tune_labels = torch.from_numpy(np.fromfile(tune_labels_file, dtype=np.int32))
conf_file = Path(metadata["conf_path"])
- # Our "w" file is the binary's "r" file, vice versa
+ # -- Our "w" file is the binary's "r" file, vice versa
fifo_r_file = Path(metadata["fifo_path_w"])
fifo_w_file = Path(metadata["fifo_path_r"])
return (
--
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