You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
Paddle/python/paddle/fluid/contrib/tests/test_calibration_mobilenetv...

60 lines
2.5 KiB

# copyright (c) 2018 paddlepaddle authors. all rights reserved.
#
# licensed under the apache license, version 2.0 (the "license");
# you may not use this file except in compliance with the license.
# you may obtain a copy of the license at
#
# http://www.apache.org/licenses/license-2.0
#
# unless required by applicable law or agreed to in writing, software
# distributed under the license is distributed on an "as is" basis,
# without warranties or conditions of any kind, either express or implied.
# see the license for the specific language governing permissions and
# limitations under the license.
import unittest
import sys
from test_calibration_resnet50 import TestCalibration
class TestCalibrationForMobilenetv1(TestCalibration):
def download_model(self):
# mobilenetv1 fp32 data
data_urls = [
'http://paddle-inference-dist.bj.bcebos.com/int8/mobilenetv1_int8_model.tar.gz'
]
data_md5s = ['13892b0716d26443a8cdea15b3c6438b']
self.model_cache_folder = self.download_data(data_urls, data_md5s,
"mobilenetv1_fp32")
self.model = "MobileNet-V1"
self.algo = "KL"
def test_calibration(self):
self.download_model()
print("Start FP32 inference for {0} on {1} images ...").format(
self.model, self.infer_iterations * self.batch_size)
(fp32_throughput, fp32_latency,
fp32_acc1) = self.run_program(self.model_cache_folder + "/model")
print("Start INT8 calibration for {0} on {1} images ...").format(
self.model, self.sample_iterations * self.batch_size)
self.run_program(
self.model_cache_folder + "/model", True, algo=self.algo)
print("Start INT8 inference for {0} on {1} images ...").format(
self.model, self.infer_iterations * self.batch_size)
(int8_throughput, int8_latency,
int8_acc1) = self.run_program(self.int8_model)
delta_value = fp32_acc1 - int8_acc1
self.assertLess(delta_value, 0.01)
print(
"FP32 {0}: batch_size {1}, throughput {2} images/second, latency {3} second, accuracy {4}".
format(self.model, self.batch_size, fp32_throughput, fp32_latency,
fp32_acc1))
print(
"INT8 {0}: batch_size {1}, throughput {2} images/second, latency {3} second, accuracy {4}".
format(self.model, self.batch_size, int8_throughput, int8_latency,
int8_acc1))
sys.stdout.flush()
if __name__ == '__main__':
unittest.main()