Add TODOs for multipier and method chaining.
@@ -91,27 +91,25 @@ def get_raw_data(i):
'tflite-0.1.7' : 'tflite-0.1.7',
}
- # Platforms
+ # TODO: Move the platform mappings to meta.
+ # Linaro HiKey960
hikey_model = 'HiKey960\x00'
hikey_name = 'Linaro HiKey960'
hikey_id = 'hikey-960'
hikey_gpu = 'Mali-G71 MP8'
hikey_gpu_mhz = '807 MHz'
-
# Firefly RK3399
firefly_model = 'Rockchip RK3399 Firefly Board (Linux Opensource)\x00'
firefly_name = 'Firefly RK3399'
firefly_id = 'firefly'
firefly_gpu = 'Mali-T860 MP4'
firefly_gpu_mhz = '800 MHz'
-
# Huawei Mate 10 Pro
mate_model = 'BLA-L09'
mate_name = 'Huawei BLA-L09'
mate_id = 'mate'
mate_gpu = 'Mali-G72 MP12'
mate_gpu_mhz = '767 MHz'
-
# Platform mappings
model_to_id = {
firefly_model : firefly_id,
@@ -164,16 +162,17 @@ def get_raw_data(i):
if _platform and _platform!=platform: continue
batch_size = np.int64(point_data_raw['choices']['env'].get('CK_BATCH_SIZE',-1))
batch_count = np.int64(point_data_raw['choices']['env'].get('CK_BATCH_COUNT',-1))
- # FIXME: ReQuEST data uses CK_CONVOLUTION_METHOD_HINT.
+ # ReQuEST data uses _METHOD_HINT; new data uses _METHOD. Try both.
+ # TODO: Introduce chaining? (See also multiplier below.)
convolution_method = convolution_method_to_name[np.int64(point_data_raw['choices']['env'].get('CK_CONVOLUTION_METHOD',1))]
- # TODO: Use CK_DATA_LAYOUT for filtering.
data_layout = point_data_raw['choices']['env'].get('CK_DATA_LAYOUT','NHWC')
if library.startswith('tensorflow-') or library.startswith('tflite-'):
multiplier = np.float64(point_data_raw['choices']['env'].get('CK_ENV_TENSORFLOW_MODEL_MOBILENET_MULTIPLIER',-1))
resolution = np.int64(point_data_raw['choices']['env'].get('CK_ENV_TENSORFLOW_MODEL_MOBILENET_RESOLUTION',-1))
version = np.int64(point_data_raw['choices']['env'].get('CK_ENV_TENSORFLOW_MODEL_MOBILENET_VERSION',1))
else:
- # ReQuEST data uses WIDTH_MULTIPLIER; new data uses MULTIPLIER.
+ # ReQuEST data uses _WIDTH_MULTIPLIER; new data uses _MULTIPLIER. Try both.
+ # TODO: Introduce chaining? (See also convolution_method above.)
multiplier = np.float64(point_data_raw['choices']['env'].get('CK_ENV_MOBILENET_WIDTH_MULTIPLIER',-1))
if multiplier==-1: multiplier = np.float64(point_data_raw['choices']['env'].get('CK_ENV_MOBILENET_MULTIPLIER',-1))
resolution = np.int64(point_data_raw['choices']['env'].get('CK_ENV_MOBILENET_RESOLUTION',-1))
