Abstract class that provides helpers for TensorFlow benchmarks.
tf.test.Benchmark()
Methods
evaluate
View source
evaluate(
tensors
)
Evaluates tensors and returns numpy values.
| Args |
|---|
tensors
|
A Tensor or a nested list/tuple of Tensors.
|
| Returns |
|---|
|
tensors numpy values.
|
is_abstract
View source
@classmethod
is_abstract()
report_benchmark
View source
report_benchmark(
iters=None, cpu_time=None, wall_time=None, throughput=None, extras=None,
name=None, metrics=None
)
Report a benchmark.
| Args |
|---|
iters
|
(optional) How many iterations were run
|
cpu_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 with name.
Otherwise it is inferred from the top-level method name.
|
metrics
|
(optional) A list of dict, where each dict has the keys below
name (required), string, metric name
value (required), double, metric value
min_value (optional), double, minimum acceptable metric value
max_value (optional), double, maximum acceptable metric value
|
run_op_benchmark
View source
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 or Tensor to benchmark.
|
feed_dict
|
A dict of values to feed for each op iteration (see the
feed_dict parameter of Session.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 with name.
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.
|
TensorFlow 2 version
View source on GitHub