Improve formatting (blank lines between blocks).
@@ -164,20 +164,23 @@ def get_raw_data(i):
convolution_method_from_env = point_env.get('CK_CONVOLUTION_METHOD', point_env.get('CK_CONVOLUTION_METHOD_HINT',"-1"))
convolution_method = convolution_method_to_name[ str(convolution_method_from_env) ]
+ # Data layout.
data_layout = point_env.get('CK_DATA_LAYOUT','default')
+
# Model.
if library.startswith('tensorflow-') or library.startswith('tflite-'):
+ version_from_env = point_env.get('CK_ENV_TENSORFLOW_MODEL_MOBILENET_VERSION',1)
multiplier_from_env = point_env.get('CK_ENV_TENSORFLOW_MODEL_MOBILENET_MULTIPLIER',-1)
resolution_from_env = point_env.get('CK_ENV_TENSORFLOW_MODEL_MOBILENET_RESOLUTION',-1)
- version_from_env = point_env.get('CK_ENV_TENSORFLOW_MODEL_MOBILENET_VERSION',1)
else:
+ version_from_env = point_env.get('CK_ENV_MOBILENET_VERSION',1)
multiplier_from_env = point_env.get('CK_ENV_MOBILENET_MULTIPLIER', point_env.get('CK_ENV_MOBILENET_WIDTH_MULTIPLIER', -1))
resolution_from_env = point_env.get('CK_ENV_MOBILENET_RESOLUTION',-1)
- version_from_env = point_env.get('CK_ENV_MOBILENET_VERSION',1)
+ version = np.int64(version_from_env)
multiplier = np.float64(multiplier_from_env)
resolution = np.int64(resolution_from_env)
- version = np.int64(version_from_env)
model = 'v%d-%.2f-%d' % (version, multiplier, resolution)
+
# Dataset.
dataset_raw = point_env.get('CK_ENV_DATASET_IMAGENET_VAL', '')
dataset = ''
@@ -187,6 +190,7 @@ def get_raw_data(i):
dataset = 'val-min'
elif 'val' in dataset_raw:
dataset = 'val'
+
# Target names for CPU and OS.
target_os_name = point_data_raw['features']['platform']['os']['name']
cpu_names = [ map_cpu_code_to_cpu_name(cpu_dict['ck_cpu_name']) for cpu_dict in point_data_raw['features']['platform']['cpu_misc'].values() ]
@@ -194,10 +198,12 @@ def get_raw_data(i):
for cpu_name in cpu_names:
cpu_count_by_type[cpu_name] += 1
target_cpu_name = ' + '.join( [ '{} MP{}'.format(k,v) for (k,v) in cpu_count_by_type.items() ] )
+
# Frequencies for CPU and GPU.
cpu_freq = point_data_raw['choices']['cpu_freq']
gpu_freq = point_data_raw['choices']['gpu_freq']
+ # Construct an individual DataFrame.
data = []
for repetition_id, characteristics in enumerate(characteristics_list):
datum = {
@@ -308,7 +314,7 @@ def get_raw_data(i):
default_selected_repo = ''
default_selected_repo = 'mlperf-mobilenets'
- #default_selected_repo = 'mobilenet-v1-armcl-opencl-18.08-52ba29e9'
+ default_selected_repo = 'linaro-hikey960-18.08-52ba29e9-mobilenet-v1-0.25-128'
selected_repo = i.get('selected_repo', default_selected_repo)
