mirror of
https://github.com/NVIDIA/nvbench.git
synced 2026-05-12 09:15:47 +00:00
ea592b6444
1. For JSON files that contains repeated measurements of run-time axis values, make sure that scripts compares corresponding reference entries. If cmp had two states with the same name and ref had two, we would compare measurements for each state in cmp against the first state in ref. Change here introduces counters tracking how many times each particular axis value, and retrieve corresponding entry in ref. Previously, I had ``` | BlockSize | NumBlocks | Ref Time | Ref Noise | Cmp Time | Cmp Noise | Diff | %Diff | Status | |-------------|-------------|------------|-------------|------------|-------------|-----------|---------|----------| | 2^8 | 64 | 1.776 ms | 0.46% | 1.777 ms | 0.40% | 1.024 us | 0.06% | SAME | | 2^8 | 64 | 1.776 ms | 0.46% | 1.774 ms | 0.52% | -2.048 us | -0.12% | SAME | | 2^8 | 64 | 1.776 ms | 0.46% | 1.773 ms | 0.52% | -3.072 us | -0.17% | SAME | | 2^8 | 64 | 1.776 ms | 0.46% | 1.774 ms | 0.58% | -2.048 us | -0.12% | SAME | | 2^8 | 64 | 1.776 ms | 0.46% | 1.773 ms | 0.58% | -3.072 us | -0.17% | SAME | ``` and now it becomes ``` | BlockSize | NumBlocks | Ref Time | Ref Noise | Cmp Time | Cmp Noise | Diff | %Diff | Status | |-------------|-------------|------------|-------------|------------|-------------|-----------|---------|----------| | 2^8 | 64 | 1.776 ms | 0.46% | 1.777 ms | 0.40% | 1.024 us | 0.06% | SAME | | 2^8 | 64 | 1.773 ms | 0.64% | 1.774 ms | 0.52% | 1.024 us | 0.06% | SAME | | 2^8 | 64 | 1.774 ms | 0.46% | 1.773 ms | 0.52% | -1.024 us | -0.06% | SAME | | 2^8 | 64 | 1.773 ms | 0.46% | 1.774 ms | 0.58% | 1.024 us | 0.06% | SAME | | 2^8 | 64 | 1.774 ms | 0.52% | 1.773 ms | 0.58% | -1.024 us | -0.06% | SAME | ``` With the following raw data expected ``` (py313) opavlyk@NV-22T4X34:~/repos/nvbench$ jq '. | .benchmarks[] | .states[] | .summaries[] | select(.tag == "nv/cold/time/gpu/median") | .data[] | .value' base.json "0.0017756160497665405" "0.0017725440263748169" "0.001773568034172058" "0.0017725440263748169" "0.001773568034172058" (py313) opavlyk@NV-22T4X34:~/repos/nvbench$ jq '. | .benchmarks[] | .states[] | .summaries[] | select(.tag == "nv/cold/time/gpu/median") | .data[] | .value' test.json "0.0017766400575637818" "0.001773568034172058" "0.0017725440263748169" "0.001773568034172058" "0.0017725440263748169" ``` 2. nvbench_compare changes from using min_noise = min(ref_noise, cmp_noise) to using max_noise = max(ref_noise, cmp_noise) Using larger of ref and cmp noise level as a reference against which to gauge timing difference ratio makes more sense.
714 lines
23 KiB
Python
714 lines
23 KiB
Python
#!/usr/bin/env python
|
|
|
|
import argparse
|
|
import math
|
|
import os
|
|
import sys
|
|
from enum import StrEnum
|
|
from itertools import islice
|
|
|
|
import jsondiff
|
|
import tabulate
|
|
from colorama import Fore
|
|
|
|
try:
|
|
from nvbench_json import reader
|
|
except ImportError:
|
|
from scripts.nvbench_json import reader
|
|
|
|
|
|
# Parse version string into tuple, "x.y.z" -> (x, y, z)
|
|
def version_tuple(v):
|
|
return tuple(map(int, (v.split("."))))
|
|
|
|
|
|
tabulate_version = version_tuple(tabulate.__version__)
|
|
|
|
all_ref_devices = []
|
|
all_cmp_devices = []
|
|
config_count = 0
|
|
unknown_count = 0
|
|
failure_count = 0
|
|
pass_count = 0
|
|
|
|
|
|
class Emoji(StrEnum):
|
|
YELLOW = "\U0001f7e1"
|
|
BLUE = "\U0001f535"
|
|
GREEN = "\U0001f7e2"
|
|
RED = "\U0001f534"
|
|
NONE = ""
|
|
|
|
|
|
def colorize(msg: str, fore: Fore, emoji: Emoji, no_color: bool) -> str:
|
|
if no_color:
|
|
prefix = ""
|
|
if emoji_s := str(emoji):
|
|
prefix = f"{emoji_s} "
|
|
return f"{prefix}{msg}"
|
|
else:
|
|
return f"{fore}{msg}{Fore.RESET}"
|
|
|
|
|
|
def find_matching_bench(needle, haystack):
|
|
for hay in haystack:
|
|
if hay["name"] == needle["name"]:
|
|
return hay
|
|
return None
|
|
|
|
|
|
def find_device_by_id(device_id, all_devices):
|
|
for device in all_devices:
|
|
if device["id"] == device_id:
|
|
return device
|
|
return None
|
|
|
|
|
|
def format_int64_axis_value(axis_name, axis_value, axes):
|
|
axis = next(filter(lambda ax: ax["name"] == axis_name, axes))
|
|
axis_flags = axis["flags"]
|
|
value = int(axis_value["value"])
|
|
if axis_flags == "pow2":
|
|
value = math.log2(value)
|
|
return "2^%d" % value
|
|
return "%d" % value
|
|
|
|
|
|
def format_float64_axis_value(axis_name, axis_value, axes):
|
|
return "%.5g" % float(axis_value["value"])
|
|
|
|
|
|
def format_type_axis_value(axis_name, axis_value, axes):
|
|
return "%s" % axis_value["value"]
|
|
|
|
|
|
def format_string_axis_value(axis_name, axis_value, axes):
|
|
return "%s" % axis_value["value"]
|
|
|
|
|
|
def format_axis_value(axis_name, axis_value, axes):
|
|
axis = next(filter(lambda ax: ax["name"] == axis_name, axes))
|
|
axis_type = axis["type"]
|
|
if axis_type == "int64":
|
|
return format_int64_axis_value(axis_name, axis_value, axes)
|
|
elif axis_type == "float64":
|
|
return format_float64_axis_value(axis_name, axis_value, axes)
|
|
elif axis_type == "type":
|
|
return format_type_axis_value(axis_name, axis_value, axes)
|
|
elif axis_type == "string":
|
|
return format_string_axis_value(axis_name, axis_value, axes)
|
|
|
|
|
|
def make_display(name: str, display_values: [list[str]]) -> str:
|
|
open_bracket, close_bracket = ("[", "]") if len(display_values) > 1 else ("", "")
|
|
display_values = ",".join(display_values)
|
|
return f"{name}={open_bracket}{display_values}{close_bracket}"
|
|
|
|
|
|
def parse_axis_filters(axis_args):
|
|
filters = []
|
|
for axis_arg in axis_args:
|
|
if "=" not in axis_arg:
|
|
raise ValueError(f"Axis filter must be NAME=VALUE: {axis_arg}")
|
|
name, value = axis_arg.split("=", 1)
|
|
name = name.strip()
|
|
value = value.strip()
|
|
if not name or not value:
|
|
raise ValueError(f"Axis filter must be NAME=VALUE: {axis_arg}")
|
|
|
|
values = []
|
|
if value.startswith("[") and value.endswith("]"):
|
|
inner = value[1:-1].strip()
|
|
values = [
|
|
stripped for item in inner.split(",") if (stripped := item.strip())
|
|
]
|
|
else:
|
|
values = [value]
|
|
display_values = list(values)
|
|
|
|
if name.endswith("[pow2]"):
|
|
name = name[: -len("[pow2]")].strip()
|
|
if not name:
|
|
raise ValueError(f"Axis filter missing name before [pow2]: {axis_arg}")
|
|
try:
|
|
exponents = [int(v) for v in values]
|
|
except ValueError as exc:
|
|
raise ValueError(
|
|
f"Axis filter [pow2] value must be integer: {axis_arg}"
|
|
) from exc
|
|
values = [str(2**exponent) for exponent in exponents]
|
|
display_values = [f"2^{exponent}" for exponent in exponents]
|
|
|
|
if not values:
|
|
raise ValueError(f"Axis filter must specify at least one value: {axis_arg}")
|
|
|
|
display = make_display(name, display_values)
|
|
filters.append(
|
|
{
|
|
"name": name,
|
|
"values": values,
|
|
"display": display,
|
|
}
|
|
)
|
|
return filters
|
|
|
|
|
|
def matches_axis_filters(state, axis_filters):
|
|
if not axis_filters:
|
|
return True
|
|
|
|
axis_values = state.get("axis_values") or []
|
|
for axis_filter in axis_filters:
|
|
filter_name = axis_filter["name"]
|
|
filter_values = axis_filter["values"]
|
|
matched = False
|
|
for axis_value in axis_values:
|
|
if axis_value.get("name") != filter_name:
|
|
continue
|
|
value = axis_value.get("value")
|
|
if value is None:
|
|
continue
|
|
if str(value) in filter_values:
|
|
matched = True
|
|
break
|
|
if not matched:
|
|
return False
|
|
return True
|
|
|
|
|
|
def format_duration(seconds):
|
|
if seconds >= 1:
|
|
multiplier = 1.0
|
|
units = "s"
|
|
elif seconds >= 1e-3:
|
|
multiplier = 1e3
|
|
units = "ms"
|
|
elif seconds >= 1e-6:
|
|
multiplier = 1e6
|
|
units = "us"
|
|
else:
|
|
multiplier = 1e6
|
|
units = "us"
|
|
return "%0.3f %s" % (seconds * multiplier, units)
|
|
|
|
|
|
def format_percentage(percentage):
|
|
# When there aren't enough samples for a meaningful noise measurement,
|
|
# the noise is recorded as infinity. Unfortunately, JSON spec doesn't
|
|
# allow for inf, so these get turned into null.
|
|
if percentage is None:
|
|
return "inf"
|
|
return "%0.2f%%" % (percentage * 100.0)
|
|
|
|
|
|
def format_axis_values(axis_values, axes, axis_filters=None):
|
|
if not axis_values:
|
|
return ""
|
|
filtered_names = set()
|
|
if axis_filters:
|
|
filtered_names = {
|
|
axis_filter["name"]
|
|
for axis_filter in axis_filters
|
|
if len(axis_filter["values"]) == 1
|
|
}
|
|
parts = []
|
|
for axis_value in axis_values:
|
|
axis_name = axis_value["name"]
|
|
if axis_name in filtered_names:
|
|
continue
|
|
formatted = format_axis_value(axis_name, axis_value, axes)
|
|
parts.append(f"{axis_name}={formatted}")
|
|
return " ".join(parts)
|
|
|
|
|
|
def plot_comparison_entries(entries, title=None, dark=False):
|
|
if not entries:
|
|
print("No comparison data to plot.")
|
|
return 1
|
|
|
|
if not os.environ.get("DISPLAY"):
|
|
import matplotlib
|
|
|
|
matplotlib.use("Agg")
|
|
|
|
import matplotlib.pyplot as plt
|
|
from matplotlib.ticker import PercentFormatter
|
|
|
|
labels, values, statuses, bench_names = map(list, zip(*entries))
|
|
|
|
status_colors = {
|
|
"SLOW": "red",
|
|
"FAST": "green",
|
|
"SAME": "blue",
|
|
}
|
|
colors = [status_colors.get(status, "gray") for status in statuses]
|
|
|
|
fig_height = max(4.0, 0.3 * len(entries) + 1.5)
|
|
fig, ax = plt.subplots(figsize=(10, fig_height))
|
|
if dark:
|
|
fig.patch.set_facecolor("black")
|
|
ax.set_facecolor("black")
|
|
ax.tick_params(colors="white")
|
|
ax.xaxis.label.set_color("white")
|
|
ax.yaxis.label.set_color("white")
|
|
ax.title.set_color("white")
|
|
for spine in ax.spines.values():
|
|
spine.set_color("white")
|
|
|
|
y_pos = range(len(labels))
|
|
ax.barh(y_pos, values, color=colors)
|
|
ax.set_yticks(y_pos)
|
|
ax.set_yticklabels(labels)
|
|
ax.invert_yaxis()
|
|
ax.set_ylim(len(labels) - 0.5, -0.5)
|
|
|
|
separator_color = "white" if dark else "gray"
|
|
ax.axvline(0, color=separator_color, linewidth=1, alpha=0.6)
|
|
for index in range(1, len(bench_names)):
|
|
if bench_names[index] != bench_names[index - 1]:
|
|
ax.axhline(index - 0.5, color=separator_color, linewidth=0.6, alpha=0.4)
|
|
ax.xaxis.set_major_formatter(PercentFormatter(1.0))
|
|
|
|
if title:
|
|
ax.set_title(title)
|
|
|
|
min_val = min(values)
|
|
max_val = max(values)
|
|
if min_val == max_val:
|
|
pad = 0.05 if min_val == 0 else abs(min_val) * 0.1
|
|
ax.set_xlim(min_val - pad, max_val + pad)
|
|
else:
|
|
pad = (max_val - min_val) * 0.1
|
|
ax.set_xlim(min_val - pad, max_val + pad)
|
|
|
|
fig.tight_layout()
|
|
|
|
if not os.environ.get("DISPLAY"):
|
|
output = "nvbench_compare.png"
|
|
fig.savefig(output, dpi=150)
|
|
print(f"Saved comparison plot to {output}")
|
|
else:
|
|
plt.show()
|
|
return 0
|
|
|
|
|
|
def compare_benches(
|
|
ref_benches,
|
|
cmp_benches,
|
|
threshold,
|
|
plot_along,
|
|
plot,
|
|
dark,
|
|
axis_filters,
|
|
benchmark_filters,
|
|
no_color,
|
|
):
|
|
if plot_along:
|
|
import matplotlib.pyplot as plt
|
|
import seaborn as sns
|
|
|
|
sns.set_theme()
|
|
|
|
comparison_entries = []
|
|
comparison_device_names = set()
|
|
for cmp_bench in cmp_benches:
|
|
ref_bench = find_matching_bench(cmp_bench, ref_benches)
|
|
if not ref_bench:
|
|
continue
|
|
if benchmark_filters and cmp_bench["name"] not in benchmark_filters:
|
|
continue
|
|
|
|
print(f"""# {cmp_bench["name"]}\n""")
|
|
|
|
cmp_device_ids = cmp_bench["devices"]
|
|
axes = cmp_bench["axes"]
|
|
ref_states = ref_bench["states"]
|
|
cmp_states = cmp_bench["states"]
|
|
|
|
axes = axes if axes else []
|
|
|
|
headers = [x["name"] for x in axes]
|
|
colalign = ["center"] * len(headers)
|
|
|
|
headers.append("Ref Time")
|
|
colalign.append("right")
|
|
headers.append("Ref Noise")
|
|
colalign.append("right")
|
|
headers.append("Cmp Time")
|
|
colalign.append("right")
|
|
headers.append("Cmp Noise")
|
|
colalign.append("right")
|
|
headers.append("Diff")
|
|
colalign.append("right")
|
|
headers.append("%Diff")
|
|
colalign.append("right")
|
|
headers.append("Status")
|
|
colalign.append("center")
|
|
|
|
for cmp_device_id in cmp_device_ids:
|
|
rows = []
|
|
plot_data = {"cmp": {}, "ref": {}, "cmp_noise": {}, "ref_noise": {}}
|
|
counters = {}
|
|
|
|
for cmp_state in cmp_states:
|
|
cmp_state_name = cmp_state["name"]
|
|
counters[cmp_state_name] = counters.get(cmp_state_name, 0) + 1
|
|
ref_state = next(
|
|
islice(
|
|
filter(lambda st: st["name"] == cmp_state_name, ref_states),
|
|
counters[cmp_state_name] - 1,
|
|
None,
|
|
),
|
|
None,
|
|
)
|
|
if not ref_state:
|
|
continue
|
|
if not matches_axis_filters(cmp_state, axis_filters):
|
|
continue
|
|
|
|
axis_values = cmp_state["axis_values"]
|
|
if not axis_values:
|
|
axis_values = []
|
|
|
|
row = []
|
|
for axis_value in axis_values:
|
|
axis_value_name = axis_value["name"]
|
|
row.append(format_axis_value(axis_value_name, axis_value, axes))
|
|
|
|
cmp_summaries = cmp_state["summaries"]
|
|
ref_summaries = ref_state["summaries"]
|
|
|
|
if not ref_summaries or not cmp_summaries:
|
|
continue
|
|
|
|
def lookup_summary(summaries, tag):
|
|
return next(filter(lambda s: s["tag"] == tag, summaries), None)
|
|
|
|
cmp_time_summary = lookup_summary(
|
|
cmp_summaries, "nv/cold/time/gpu/mean"
|
|
)
|
|
ref_time_summary = lookup_summary(
|
|
ref_summaries, "nv/cold/time/gpu/mean"
|
|
)
|
|
cmp_noise_summary = lookup_summary(
|
|
cmp_summaries, "nv/cold/time/gpu/stdev/relative"
|
|
)
|
|
ref_noise_summary = lookup_summary(
|
|
ref_summaries, "nv/cold/time/gpu/stdev/relative"
|
|
)
|
|
|
|
# TODO: Use other timings, too. Maybe multiple rows, with a
|
|
# "Timing" column + values "CPU/GPU/Batch"?
|
|
if not all(
|
|
[
|
|
cmp_time_summary,
|
|
ref_time_summary,
|
|
cmp_noise_summary,
|
|
ref_noise_summary,
|
|
]
|
|
):
|
|
continue
|
|
|
|
def extract_value(summary):
|
|
summary_data = summary["data"]
|
|
value_data = next(
|
|
filter(lambda v: v["name"] == "value", summary_data)
|
|
)
|
|
assert value_data["type"] == "float64"
|
|
return value_data["value"]
|
|
|
|
cmp_time = extract_value(cmp_time_summary)
|
|
ref_time = extract_value(ref_time_summary)
|
|
cmp_noise = extract_value(cmp_noise_summary)
|
|
ref_noise = extract_value(ref_noise_summary)
|
|
|
|
# Convert string encoding to expected numerics:
|
|
cmp_time = float(cmp_time)
|
|
ref_time = float(ref_time)
|
|
|
|
diff = cmp_time - ref_time
|
|
frac_diff = diff / ref_time
|
|
|
|
if ref_noise and cmp_noise:
|
|
ref_noise = float(ref_noise)
|
|
cmp_noise = float(cmp_noise)
|
|
max_noise = max(ref_noise, cmp_noise)
|
|
elif ref_noise:
|
|
ref_noise = float(ref_noise)
|
|
max_noise = ref_noise
|
|
elif cmp_noise:
|
|
cmp_noise = float(cmp_noise)
|
|
max_noise = cmp_noise
|
|
else:
|
|
max_noise = None # Noise is inf
|
|
|
|
if plot_along:
|
|
axis_name = []
|
|
axis_value = "--"
|
|
for av in axis_values:
|
|
if av["name"] != plot_along:
|
|
axis_name.append(f"""{av["name"]} = {av["value"]}""")
|
|
else:
|
|
axis_value = float(av["value"])
|
|
axis_name = ", ".join(axis_name)
|
|
|
|
if axis_name not in plot_data["cmp"]:
|
|
plot_data["cmp"][axis_name] = {}
|
|
plot_data["ref"][axis_name] = {}
|
|
plot_data["cmp_noise"][axis_name] = {}
|
|
plot_data["ref_noise"][axis_name] = {}
|
|
|
|
plot_data["cmp"][axis_name][axis_value] = cmp_time
|
|
plot_data["ref"][axis_name][axis_value] = ref_time
|
|
plot_data["cmp_noise"][axis_name][axis_value] = cmp_noise
|
|
plot_data["ref_noise"][axis_name][axis_value] = ref_noise
|
|
|
|
global config_count
|
|
global unknown_count
|
|
global pass_count
|
|
global failure_count
|
|
|
|
config_count += 1
|
|
if max_noise is None:
|
|
unknown_count += 1
|
|
status_label = "????"
|
|
status = colorize(status_label, Fore.YELLOW, Emoji.YELLOW, no_color)
|
|
elif abs(frac_diff) <= max_noise:
|
|
pass_count += 1
|
|
status_label = "SAME"
|
|
status = colorize(status_label, Fore.BLUE, Emoji.BLUE, no_color)
|
|
elif diff < 0:
|
|
failure_count += 1
|
|
status_label = "FAST"
|
|
status = colorize(status_label, Fore.GREEN, Emoji.GREEN, no_color)
|
|
else:
|
|
failure_count += 1
|
|
status_label = "SLOW"
|
|
status = colorize(status_label, Fore.RED, Emoji.RED, no_color)
|
|
|
|
if abs(frac_diff) >= threshold:
|
|
row.append(format_duration(ref_time))
|
|
row.append(format_percentage(ref_noise))
|
|
row.append(format_duration(cmp_time))
|
|
row.append(format_percentage(cmp_noise))
|
|
row.append(format_duration(diff))
|
|
row.append(format_percentage(frac_diff))
|
|
row.append(status)
|
|
|
|
rows.append(row)
|
|
if plot:
|
|
axis_label = format_axis_values(axis_values, axes, axis_filters)
|
|
if axis_label:
|
|
label = f"""{cmp_bench["name"]} | {axis_label}"""
|
|
else:
|
|
label = cmp_bench["name"]
|
|
cmp_device = find_device_by_id(
|
|
cmp_state["device"], all_cmp_devices
|
|
)
|
|
if cmp_device:
|
|
comparison_device_names.add(cmp_device["name"])
|
|
comparison_entries.append(
|
|
(label, frac_diff, status_label, cmp_bench["name"])
|
|
)
|
|
|
|
if len(rows) == 0:
|
|
continue
|
|
|
|
cmp_device = find_device_by_id(cmp_device_id, all_cmp_devices)
|
|
ref_device = find_device_by_id(ref_state["device"], all_ref_devices)
|
|
|
|
if cmp_device == ref_device:
|
|
print("## [%d] %s\n" % (cmp_device["id"], cmp_device["name"]))
|
|
else:
|
|
print(
|
|
"## [%d] %s vs. [%d] %s\n"
|
|
% (
|
|
ref_device["id"],
|
|
ref_device["name"],
|
|
cmp_device["id"],
|
|
cmp_device["name"],
|
|
)
|
|
)
|
|
# colalign and github format require tabulate 0.8.3
|
|
if tabulate_version >= (0, 8, 3):
|
|
print(
|
|
tabulate.tabulate(
|
|
rows, headers=headers, colalign=colalign, tablefmt="github"
|
|
)
|
|
)
|
|
else:
|
|
print(tabulate.tabulate(rows, headers=headers, tablefmt="markdown"))
|
|
|
|
print("")
|
|
|
|
if plot_along:
|
|
plt.xscale("log")
|
|
plt.yscale("log")
|
|
plt.xlabel(plot_along)
|
|
plt.ylabel("time [s]")
|
|
plt.title(cmp_device["name"])
|
|
|
|
def plot_line(key, shape, label):
|
|
x = [float(x) for x in plot_data[key][axis].keys()]
|
|
y = list(plot_data[key][axis].values())
|
|
|
|
noise = list(plot_data[key + "_noise"][axis].values())
|
|
|
|
top = [y[i] + y[i] * noise[i] for i in range(len(x))]
|
|
bottom = [y[i] - y[i] * noise[i] for i in range(len(x))]
|
|
|
|
p = plt.plot(x, y, shape, marker="o", label=label)
|
|
plt.fill_between(x, bottom, top, color=p[0].get_color(), alpha=0.1)
|
|
|
|
for axis in plot_data["cmp"].keys():
|
|
plot_line("cmp", "-", axis)
|
|
plot_line("ref", "--", axis + " ref")
|
|
|
|
plt.legend()
|
|
plt.show()
|
|
|
|
if plot:
|
|
title = "%SOL Bandwidth change"
|
|
if len(comparison_device_names) == 1:
|
|
title = f"{title} - {next(iter(comparison_device_names))}"
|
|
if axis_filters:
|
|
axis_label = ", ".join(
|
|
axis_filter["display"]
|
|
for axis_filter in axis_filters
|
|
if len(axis_filter["values"]) == 1
|
|
)
|
|
if axis_label:
|
|
title = f"{title} ({axis_label})"
|
|
plot_comparison_entries(comparison_entries, title=title, dark=dark)
|
|
|
|
|
|
def main():
|
|
help_text = "%(prog)s [reference.json compare.json | reference_dir/ compare_dir/]"
|
|
parser = argparse.ArgumentParser(prog="nvbench_compare", usage=help_text)
|
|
parser.add_argument(
|
|
"--ignore-devices",
|
|
dest="ignore_devices",
|
|
default=False,
|
|
help="Ignore differences in the device sections and compare anyway",
|
|
action="store_true",
|
|
)
|
|
parser.add_argument(
|
|
"--threshold-diff",
|
|
type=float,
|
|
dest="threshold",
|
|
default=0.0,
|
|
help="only show benchmarks where percentage diff is >= THRESHOLD",
|
|
)
|
|
parser.add_argument(
|
|
"--plot-along", type=str, dest="plot_along", default=None, help="plot results"
|
|
)
|
|
parser.add_argument(
|
|
"--plot",
|
|
dest="plot",
|
|
default=False,
|
|
help="plot comparison summary",
|
|
action="store_true",
|
|
)
|
|
parser.add_argument(
|
|
"--dark",
|
|
action="store_true",
|
|
help="Use dark theme (black background, white text)",
|
|
)
|
|
parser.add_argument(
|
|
"--no-color",
|
|
dest="no_color",
|
|
action="store_true",
|
|
help="Use emoji instead of ANSI color codes (useful for GitHub issues/PRs)",
|
|
)
|
|
parser.add_argument(
|
|
"-a",
|
|
"--axis",
|
|
action="append",
|
|
default=[],
|
|
help="Filter on axis value, e.g. -a Elements{io}=2^20 (can repeat)",
|
|
)
|
|
parser.add_argument(
|
|
"-b",
|
|
"--benchmark",
|
|
action="append",
|
|
default=[],
|
|
help="Filter by benchmark name (can repeat)",
|
|
)
|
|
|
|
args, files_or_dirs = parser.parse_known_args()
|
|
print(files_or_dirs)
|
|
try:
|
|
axis_filters = parse_axis_filters(args.axis)
|
|
except ValueError as exc:
|
|
print(str(exc))
|
|
sys.exit(1)
|
|
|
|
if len(files_or_dirs) != 2:
|
|
parser.print_help()
|
|
sys.exit(1)
|
|
|
|
# if provided two directories, find all the exactly named files
|
|
# in both and treat them as the reference and compare
|
|
to_compare = []
|
|
if os.path.isdir(files_or_dirs[0]) and os.path.isdir(files_or_dirs[1]):
|
|
for f in os.listdir(files_or_dirs[1]):
|
|
if os.path.splitext(f)[1] != ".json":
|
|
continue
|
|
r = os.path.join(files_or_dirs[0], f)
|
|
c = os.path.join(files_or_dirs[1], f)
|
|
if (
|
|
os.path.isfile(r)
|
|
and os.path.isfile(c)
|
|
and os.path.getsize(r) > 0
|
|
and os.path.getsize(c) > 0
|
|
):
|
|
to_compare.append((r, c))
|
|
else:
|
|
to_compare = [(files_or_dirs[0], files_or_dirs[1])]
|
|
|
|
for ref, comp in to_compare:
|
|
ref_root = reader.read_file(ref)
|
|
cmp_root = reader.read_file(comp)
|
|
|
|
global all_ref_devices
|
|
global all_cmp_devices
|
|
all_ref_devices = ref_root["devices"]
|
|
all_cmp_devices = cmp_root["devices"]
|
|
|
|
if ref_root["devices"] != cmp_root["devices"]:
|
|
warn_fore = Fore.YELLOW if args.ignore_devices else Fore.RED
|
|
msg_text = "Device sections do not match"
|
|
print(colorize(msg_text, warn_fore, Emoji.NONE, args.no_color), end="")
|
|
print(": ", end="")
|
|
|
|
print(
|
|
jsondiff.diff(
|
|
ref_root["devices"], cmp_root["devices"], syntax="symmetric"
|
|
)
|
|
)
|
|
if not args.ignore_devices:
|
|
sys.exit(1)
|
|
|
|
compare_benches(
|
|
ref_root["benchmarks"],
|
|
cmp_root["benchmarks"],
|
|
args.threshold,
|
|
args.plot_along,
|
|
args.plot,
|
|
args.dark,
|
|
axis_filters,
|
|
args.benchmark,
|
|
args.no_color,
|
|
)
|
|
|
|
print("# Summary\n")
|
|
print("- Total Matches: %d" % config_count)
|
|
print(" - Pass (diff <= max_noise): %d" % pass_count)
|
|
print(" - Unknown (infinite noise): %d" % unknown_count)
|
|
print(" - Failure (diff > max_noise): %d" % failure_count)
|
|
return failure_count
|
|
|
|
|
|
if __name__ == "__main__":
|
|
sys.exit(main())
|