# 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. # ============================================================================== from absl import flags import tensorflow as tf import benchmark_cnn benchmark_cnn.define_flags() flags.adopt_module_key_flags(benchmark_cnn) FLAGS = tf.app.flags.FLAGS def main(_): FLAGS.eval = True params = benchmark_cnn.make_params_from_flags() params, config = benchmark_cnn.setup(params) bench = benchmark_cnn.BenchmarkCNN(params) bench.evaluate() if __name__ == '__main__': tf.app.run()
from __future__ import print_function
import tensorflow as tf
import benchmark_cnn
import cnn_util
from cnn_util import log_fn
from setenvs import setenvs
from setenvs import arglist
import sys
args = arglist()
benchmark_cnn.define_flags()
def main(extra_flags):
# extra_flags is a list of command line arguments, excluding those defined
# in tf.flags.FLAGS. extra_flags[0] is always the program name. It is an error
# to supply flags not defined with tf.flags.FLAGS, so we raise an ValueError
# in that case.
assert len(extra_flags) >= 1
# if len(extra_flags) > 1:
# raise ValueError('Received unknown flags: %s' % extra_flags[1:])
global args
args = setenvs(sys.argv)
print('Running on CPU :', args.cpu)