code stringlengths 3 6.57k |
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parse_results_for_speed(output, iter_tolerance, speed_tolerance) |
output.split("\n") |
re.match(r"([\d.]+) |
matches.groups() |
float(iterations) |
float(speed) |
AssertionError("No results detected in this run") |
parse_results_for_accuracy(output, expected_accuracies, acc_tolerance) |
output.split("\n") |
re.match(r" + Accuracy=+([\d.]+) |
float(re.match(r" + Accuracy=+([\d.]+) |
groups() |
accuracies.append(accuracy) |
re.search(r"Validation accuracy", line) |
re.search(r"accuracy:\s(.*) |
group(1) |
float(accuracy_str[:accuracy_str.rfind("%") |
accuracies.append(accuracy) |
len(accuracies) |
AssertionError("No results detected in this run") |
len(accuracies) |
len(expected_accuracies) |
_verify_model_accuracies(accuracies, expected_accuracies, acc_tolerance) |
str(iter_tolerance[1]) |
str(speed_tolerance[0]) |
sys.stderr.write("\n".join([line, iter_error, speed_error]) |
AssertionError("Timings out of tolerance range") |
sys.stderr.write(line) |
AssertionError(iter_error + speed_error) |
_verify_model_accuracies(accuracies, expected_accuracy, acc_tolerance) |
accuracies (%) |
accuracies (%) |
range(len(accuracies) |
accuracy (%) |
ljust(22) |
Accuracy (%) |
ljust(22) |
format(acc_str, exp_acc_str) |
format(iter_num + 1, full_acc_str) |
format(iter_num + 1, full_acc_str) |
assert_result_equals_tensor_value(output, tensor) |
array([3., 8.], dtype=float32) |
output.split("\n") |
re.match(list_regex, first_line) |
array([3., 8.], dtype=float32) |
re.match(np_array_str_regex, contents) |
array([3., 8.], dtype=float32) |
np.array_repr(tensor) |
format(np.array_repr(contents) |
parse_results_for_ipus_used(output) |
On ([\d.]+) |
output.split("\n") |
re.match(shards_regex, line) |
matches.group(1) |
int(shards) |
assert_shards(output, expected_shards) |
parse_results_for_ipus_used(output) |
get_final_accuracy(output) |
parse_results_with_regex(output, result_regex) |
get_final_loss(output) |
parse_results_with_regex(output, result_regex) |
get_average_speeds(output) |
parse_results_with_regex(output, result_regex) |
mean(itr_sec_list) |
mean(tokens_sec_list) |
parse_results_with_regex(output, regex) |
output.split("\n") |
re.search(regex, line) |
range(0, number_of_results) |
float(matches.group(match_index + 1) |
append(result) |
AssertionError("Regex {} not found in result".format(regex) |
get_total_epochs(output) |
output.split("\n") |
re.search(r"Epoch #([\d.]+) |
int(epoch_match.group(1) |
assert_total_run_time(total_time, time_range) |
assert_final_accuracy(output, minimum, maximum) |
percentage (between 0.0% and 100%) |
percentage (between 0.0% and 100%) |
get_final_accuracy(output) |
run_python_script_helper(cwd, script, **kwargs) |
format(sys.version_info[0]) |
str(item) |
kwargs.items() |
cmd.extend(args) |
subprocess.check_output(cmd, cwd=cwd, universal_newlines=True) |
print(out) |
time.time() |
subprocess_function(**kwargs) |
time.time() |
assert_total_run_time(total_time, total_run_time_range) |
range_from_tolerances(value, tolerance) |
percentage (between 0.0 and 1.0) |
value (minimum) |
above (maximum) |
get_minimum_with_tolerance(value, tolerance) |
get_maximum_with_tolerance(value, tolerance) |
get_minimum_with_tolerance(value, tolerance) |
percentage (between 0.0 and 1.0) |
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