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Benchmarks for flipping and random flipping #15348

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Dec 14, 2017
Merged

Benchmarks for flipping and random flipping #15348

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94436a3
Random flip benchmark
Dec 13, 2017
b6f11d5
More benchmarks
Dec 13, 2017
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83 changes: 83 additions & 0 deletions tensorflow/python/ops/image_ops_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -374,6 +374,89 @@ def testInvalidShapes(self):
self._adjustHueTf(x_np, delta_h)


class FlipImageBenchmark(test.Benchmark):

def _benchmarkFlipLeftRight(self, device, cpu_count):
image_shape = [299, 299, 3]
warmup_rounds = 100
benchmark_rounds = 1000
config = config_pb2.ConfigProto()
if cpu_count is not None:
config.inter_op_parallelism_threads = 1
config.intra_op_parallelism_threads = cpu_count
with session.Session("", graph=ops.Graph(), config=config) as sess:
with ops.device(device):
inputs = variables.Variable(
random_ops.random_uniform(
image_shape, dtype=dtypes.float32) * 255,
trainable=False,
dtype=dtypes.float32)
run_op = image_ops.flip_left_right(inputs)
sess.run(variables.global_variables_initializer())
for i in xrange(warmup_rounds + benchmark_rounds):
if i == warmup_rounds:
start = time.time()
sess.run(run_op)
end = time.time()
step_time = (end - start) / benchmark_rounds
tag = device + "_%s" % (cpu_count if cpu_count is not None else "_all")
print("benchmarkFlipLeftRight_299_299_3_%s step_time: %.2f us" %
(tag, step_time * 1e6))
self.report_benchmark(
name="benchmarkFlipLeftRight_299_299_3_%s" % (tag),
iters=benchmark_rounds,
wall_time=step_time)

def _benchmarkRandomFlipLeftRight(self, device, cpu_count):
image_shape = [299, 299, 3]
warmup_rounds = 100
benchmark_rounds = 1000
config = config_pb2.ConfigProto()
if cpu_count is not None:
config.inter_op_parallelism_threads = 1
config.intra_op_parallelism_threads = cpu_count
with session.Session("", graph=ops.Graph(), config=config) as sess:
with ops.device(device):
inputs = variables.Variable(
random_ops.random_uniform(
image_shape, dtype=dtypes.float32) * 255,
trainable=False,
dtype=dtypes.float32)
run_op = image_ops.random_flip_left_right(inputs)
sess.run(variables.global_variables_initializer())
for i in xrange(warmup_rounds + benchmark_rounds):
if i == warmup_rounds:
start = time.time()
sess.run(run_op)
end = time.time()
step_time = (end - start) / benchmark_rounds
tag = device + "_%s" % (cpu_count if cpu_count is not None else "_all")
print("benchmarkRandomFlipLeftRight_299_299_3_%s step_time: %.2f us" %
(tag, step_time * 1e6))
self.report_benchmark(
name="benchmarkRandomFlipLeftRight_299_299_3_%s" % (tag),
iters=benchmark_rounds,
wall_time=step_time)

def benchmarkFlipLeftRightCpu1(self):
self._benchmarkFlipLeftRight("/cpu:0", 1)

def benchmarkFlipLeftRightCpuAll(self):
self._benchmarkFlipLeftRight("/cpu:0", None)

def benchmarkFlipLeftRightGpu(self):
self._benchmarkFlipLeftRight(test.gpu_device_name(), None)

def benchmarkRandomFlipLeftRightCpu1(self):
self._benchmarkRandomFlipLeftRight("/cpu:0", 1)

def benchmarkRandomFlipLeftRightCpuAll(self):
self._benchmarkRandomFlipLeftRight("/cpu:0", None)

def benchmarkRandomFlipLeftRightGpu(self):
self._benchmarkRandomFlipLeftRight(test.gpu_device_name(), None)


class AdjustHueBenchmark(test.Benchmark):

def _benchmarkAdjustHue(self, device, cpu_count):
Expand Down