Add benchmark for channel_shuffle operator (#43509)

taivu · facebook-github-bot · commit 8722952dbdc7 · 2020-09-02T08:15:19.000-07:00
Summary: Pull Request resolved: #43509 Test Plan: Imported from OSS Reviewed By: kimishpatel Differential Revision: D23299972 Pulled By: kimishpatel fbshipit-source-id: 6189d209859da5a41067eb9e8317e3bf7a0fc754
diff --git a/benchmarks/operator_benchmark/benchmark_all_other_test.py b/benchmarks/operator_benchmark/benchmark_all_other_test.py
@@ -6,8 +6,8 @@
 import operator_benchmark as op_bench
 from pt import ( # noqa
     add_test, as_strided_test, batchnorm_test, binary_test, cat_test,  # noqa
-    chunk_test, conv_test, diag_test, embeddingbag_test, fill_test,  # noqa
-    gather_test, linear_test, matmul_test, pool_test,  # noqa
+    channel_shuffle_test, chunk_test, conv_test, diag_test, embeddingbag_test,  # noqa
+    fill_test, gather_test, linear_test, matmul_test, pool_test,  # noqa
     softmax_test, hardsigmoid_test, hardswish_test, layernorm_test,  # noqa
     groupnorm_test, instancenorm_test # noqa
 )
diff --git a/benchmarks/operator_benchmark/pt/channel_shuffle_test.py b/benchmarks/operator_benchmark/pt/channel_shuffle_test.py
@@ -0,0 +1,61 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+from __future__ import unicode_literals
+
+import operator_benchmark as op_bench
+import torch
+
+
+"""Microbenchmarks for channel_shuffle operator."""
+
+
+# Configs for PT channel_shuffle operator
+channel_shuffle_long_configs = op_bench.cross_product_configs(
+    batch_size=[4, 8],
+    channels_per_group=[32, 64],
+    height=[32, 64],
+    width=[32, 64],
+    groups=[4, 8],
+    channel_last=[True, False],
+    tags=["long"]
+)
+
+
+channel_shuffle_short_configs = op_bench.config_list(
+    attr_names=["batch_size", "channels_per_group", "height", "width", "groups"],
+    attrs=[
+        [2, 16, 16, 16, 2],
+        [2, 32, 32, 32, 2],
+        [4, 32, 32, 32, 4],
+        [4, 64, 64, 64, 4],
+        [8, 64, 64, 64, 8],
+        [16, 64, 64, 64, 16],
+    ],
+    cross_product_configs={
+        "channel_last": [True, False],
+    },
+    tags=["short"]
+)
+
+
+class ChannelSHuffleBenchmark(op_bench.TorchBenchmarkBase):
+    def init(self, batch_size, channels_per_group, height, width, groups, channel_last):
+        self.groups = groups
+        channels = channels_per_group * groups
+        data_shape = (batch_size, channels, height, width)
+        self.input_data = torch.rand(data_shape)
+        if channel_last:
+            self.input_data = self.input_data.contiguous(memory_format=torch.channels_last)
+        self.set_module_name('channel_shuffle')
+
+    def forward(self):
+        return torch.channel_shuffle(self.input_data, self.groups)
+
+
+op_bench.generate_pt_test(channel_shuffle_short_configs + channel_shuffle_long_configs,
+                          ChannelSHuffleBenchmark)
+
+
+if __name__ == "__main__":
+    op_bench.benchmark_runner.main()
