Class Benchmark
Defined in tensorflow/python/platform/benchmark.py
.
Abstract class that provides helpers for TensorFlow benchmarks.
Methods
tf.test.Benchmark.evaluate
evaluate(tensors)
Evaluates tensors and returns numpy values.
Args:
tensors
: A Tensor or a nested list/tuple of Tensors.
Returns:
tensors numpy values.
tf.test.Benchmark.is_abstract
@classmethod
is_abstract(cls)
tf.test.Benchmark.report_benchmark
report_benchmark(
iters=None,
cpu_time=None,
wall_time=None,
throughput=None,
extras=None,
name=None
)
Report a benchmark.
Args:
iters
: (optional) How many iterations were runcpu_time
: (optional) median or mean cpu time in seconds.wall_time
: (optional) median or mean wall time in seconds.throughput
: (optional) Throughput (in MB/s)extras
: (optional) Dict mapping string keys to additional benchmark info. Values may be either floats or values that are convertible to strings.name
: (optional) Override the BenchmarkEntry name withname
. Otherwise it is inferred from the top-level method name.
tf.test.Benchmark.run_op_benchmark
run_op_benchmark(
sess,
op_or_tensor,
feed_dict=None,
burn_iters=2,
min_iters=10,
store_trace=False,
store_memory_usage=True,
name=None,
extras=None,
mbs=0
)
Run an op or tensor in the given session. Report the results.
Args:
sess
:Session
object to use for timing.op_or_tensor
:Operation
orTensor
to benchmark.feed_dict
: Adict
of values to feed for each op iteration (see thefeed_dict
parameter ofSession.run
).burn_iters
: Number of burn-in iterations to run.min_iters
: Minimum number of iterations to use for timing.store_trace
: Boolean, whether to run an extra untimed iteration and store the trace of iteration in returned extras. The trace will be stored as a string in Google Chrome trace format in the extras field "full_trace_chrome_format". Note that trace will not be stored in test_log_pb2.TestResults proto.store_memory_usage
: Boolean, whether to run an extra untimed iteration, calculate memory usage, and store that in extras fields.name
: (optional) Override the BenchmarkEntry name withname
. Otherwise it is inferred from the top-level method name.extras
: (optional) Dict mapping string keys to additional benchmark info. Values may be either floats or values that are convertible to strings.mbs
: (optional) The number of megabytes moved by this op, used to calculate the ops throughput.
Returns:
A dict
containing the key-value pairs that were passed to
report_benchmark
. If store_trace
option is used, then
full_chrome_trace_format
will be included in return dictionary even
though it is not passed to report_benchmark
with extras
.