Conv ops to check

Author: Devjiu

dl_bench/cli/launcher.py

@@ -6,6 +6,7 @@
 from dl_bench.mlp import MlpBenchmark
 from dl_bench.cnn import CnnBenchmark
 from dl_bench.llm import LlmBenchmark
+from dl_bench.ops import OpsBenchmark
 from dl_bench.mlp_basic import MlpBasicBenchmark
 from dl_bench.report.report import BenchmarkDb
 from dl_bench.utils import Backend
@@ -16,6 +17,7 @@
     "mlp": MlpBenchmark,
     "cnn": CnnBenchmark,
     "llm": LlmBenchmark,
+    "ops": OpsBenchmark,
 }
 
 

dl_bench/ops.py

@@ -0,0 +1,41 @@
+from dl_bench.utils import Benchmark, RandomInfDataset
+
+import torch
+
+class Conv2dNoPaddingModule(torch.nn.Module):
+
+    def __init__(self):
+        super().__init__()
+        torch.manual_seed(0)
+        self.conv = torch.nn.Conv2d(2, 10, 3, bias=False)
+        self.train(False)
+
+    def forward(self, x):
+        return self.conv(x)
+
+def get_op(name):
+
+    name2model = {
+        "conv210": Conv2dNoPaddingModule,
+    }
+    if name in name2model:
+        return name2model[name]()
+    else:
+        raise ValueError(f"Unknown name {name}")
+
+
+class OpsBenchmark(Benchmark):
+    def __init__(self, params) -> None:
+        batch_size = int(params.get("batch_size", 1024))
+
+        in_shape = (2, 10, 20)
+        min_batches = 10
+        DATASET_SIZE = max(10_240, batch_size * min_batches)
+        dataset = RandomInfDataset(DATASET_SIZE, in_shape)
+
+        name = params.get("name", "conv210")
+        net = get_op(name=name)
+
+        super().__init__(
+            net=net, in_shape=in_shape, dataset=dataset, batch_size=batch_size
+        )

ops.sh

@@ -0,0 +1,20 @@
+#!/bin/bash
+
+set -x
+
+export ONEDNN_VERBOSE=0
+
+if [[ -z "${DL_BENCH_ARGS}" ]]; then
+  echo "Please, provide DL_BENCH_ARGS environment variable"
+  exit 1
+fi
+
+CNNS=(conv210)
+for BS in 0001 0032 0128
+do
+    for name in "${CNNS[@]}"
+    do
+        echo "Benchmark $name"
+        benchmark-run -b ops -p "name='${name}',batch_size='$BS'" --benchmark_desc "${name}_bs$BS" ${DL_BENCH_ARGS} || echo Failed
+    done
+done