def create_models(models_dir, dtype, shape, no_batch=True):
model_version = 1
if FLAGS.graphdef:
create_tf_modelconfig(False, models_dir, model_version, 8, dtype, shape)
create_tf_modelfile(False, models_dir, model_version, 8, dtype, shape)
if no_batch:
create_tf_modelconfig(False, models_dir, model_version, 0, dtype, shape)
create_tf_modelfile(False, models_dir, model_version, 0, dtype, shape)
if FLAGS.savedmodel:
create_tf_modelconfig(True, models_dir, model_version, 8, dtype, shape)
create_tf_modelfile(True, models_dir, model_version, 8, dtype, shape)
if no_batch:
create_tf_modelconfig(True, models_dir, model_version, 0, dtype, shape)
create_tf_modelfile(True, models_dir, model_version, 0, dtype, shape)
if FLAGS.netdef:
create_netdef_modelconfig(models_dir, model_version, 8, dtype, shape)
create_netdef_modelfile(models_dir, model_version, 8, dtype, shape)
if no_batch:
create_netdef_modelconfig(models_dir, model_version, 0, dtype, shape)
create_netdef_modelfile(models_dir, model_version, 0, dtype, shape)
if FLAGS.tensorrt:
create_plan_modelconfig(models_dir, model_version, 8, dtype, shape + [1, 1])
create_plan_modelfile(models_dir, model_version, 8, dtype, shape + [1, 1])
if no_batch:
create_plan_modelconfig(models_dir, model_version, 0, dtype, shape + [1, 1])
create_plan_modelfile(models_dir, model_version, 0, dtype, shape + [1, 1])
if FLAGS.onnx:
create_onnx_modelconfig(models_dir, model_version, 8, dtype, shape)
create_onnx_modelfile(models_dir, model_version, 8, dtype, shape)
if no_batch:
create_onnx_modelconfig(models_dir, model_version, 0, dtype, shape)
create_onnx_modelfile(models_dir, model_version, 0, dtype, shape)
if FLAGS.ensemble:
for pair in emu.platform_types_and_validation():
if pair[0] == "plan":
shape = shape + [1, 1]
if not pair[1](dtype, dtype, dtype,
shape, shape, shape):
continue
emu.create_sequence_ensemble_modelconfig(
pair[0], models_dir, 8, model_version, shape, dtype)
emu.create_sequence_ensemble_modelfile(
pair[0], models_dir, 8, model_version, shape, dtype)
if no_batch:
emu.create_sequence_ensemble_modelconfig(
pair[0], models_dir, 0, model_version, shape, dtype)
emu.create_sequence_ensemble_modelfile(
pair[0], models_dir, 0, model_version, shape, dtype)
def create_models(models_dir, dtype, shape, no_batch=True):
model_version = 1
if FLAGS.graphdef:
create_tf_modelconfig(False, models_dir, model_version, 8, dtype,
shape)
create_tf_modelfile(False, models_dir, model_version, 8, dtype, shape)
if no_batch:
create_tf_modelconfig(False, models_dir, model_version, 0, dtype,
shape)
create_tf_modelfile(False, models_dir, model_version, 0, dtype,
shape)
if FLAGS.savedmodel:
create_tf_modelconfig(True, models_dir, model_version, 8, dtype, shape)
create_tf_modelfile(True, models_dir, model_version, 8, dtype, shape)
if no_batch:
create_tf_modelconfig(True, models_dir, model_version, 0, dtype,
shape)
create_tf_modelfile(True, models_dir, model_version, 0, dtype,
shape)
if FLAGS.tensorrt:
suffix = []
if dtype == np.int8:
suffix = [1, 1]
create_plan_modelconfig(models_dir, model_version, 8, dtype,
shape + suffix)
create_plan_modelfile(models_dir, model_version, 8, dtype,
shape + suffix)
if no_batch:
create_plan_modelconfig(models_dir, model_version, 0, dtype,
shape + suffix)
create_plan_modelfile(models_dir, model_version, 0, dtype,
shape + suffix)
if FLAGS.onnx:
create_onnx_modelconfig(models_dir, model_version, 8, dtype, shape)
create_onnx_modelfile(models_dir, model_version, 8, dtype, shape)
if no_batch:
create_onnx_modelconfig(models_dir, model_version, 0, dtype, shape)
create_onnx_modelfile(models_dir, model_version, 0, dtype, shape)
if FLAGS.libtorch:
create_libtorch_modelconfig(models_dir, model_version, 8, dtype, shape)
create_libtorch_modelfile(models_dir, model_version, 8, dtype, shape)
if no_batch:
create_libtorch_modelconfig(models_dir, model_version, 0, dtype,
shape)
create_libtorch_modelfile(models_dir, model_version, 0, dtype,
shape)
if FLAGS.ensemble:
for pair in emu.platform_types_and_validation():
config_shape = shape
if pair[0] == "plan" and dtype == np.int8:
config_shape = shape + [1, 1]
if not pair[1](dtype, dtype, dtype, config_shape, config_shape,
config_shape):
continue
emu.create_sequence_ensemble_modelconfig(pair[0], models_dir, 8,
model_version,
config_shape, dtype)
emu.create_sequence_ensemble_modelfile(pair[0], models_dir, 8,
model_version, config_shape,
dtype)
if no_batch:
emu.create_sequence_ensemble_modelconfig(
pair[0], models_dir, 0, model_version, config_shape, dtype)
emu.create_sequence_ensemble_modelfile(pair[0], models_dir, 0,
model_version,
config_shape, dtype)