def _load_pytorch_transformer_model(device, dynamic_axes=False, legacy_api=False):
# Loads external Pytorch TransformerModel into utils
pytorch_transformer_path = os.path.join('samples', 'python', 'pytorch_transformer')
pt_model_path = os.path.join(pytorch_transformer_path, 'pt_model.py')
pt_model = _utils.import_module_from_file(pt_model_path)
ort_utils_path = os.path.join(pytorch_transformer_path, 'ort_utils.py')
ort_utils = _utils.import_module_from_file(ort_utils_path)
utils_path = os.path.join(pytorch_transformer_path, 'utils.py')
utils = _utils.import_module_from_file(utils_path)
# Modeling
model = pt_model.TransformerModel(28785, 200, 2, 200, 2, 0.2).to(device)
my_loss = ort_utils.my_loss
if legacy_api:
if dynamic_axes:
model_desc = ort_utils.legacy_transformer_model_description_dynamic_axes()
else:
model_desc = ort_utils.legacy_transformer_model_description()
else:
if dynamic_axes:
model_desc = ort_utils.transformer_model_description_dynamic_axes()
else:
model_desc = ort_utils.transformer_model_description()
# Preparing data
train_data, val_data, test_data = utils.prepare_data(device, 20, 20)
return model, model_desc, my_loss, utils.get_batch, train_data, val_data, test_data
def _load_pytorch_transformer_model(device,
dynamic_axes=False,
legacy_api=False,
data_dir=None):
# Loads external Pytorch TransformerModel into utils
root = "samples"
if not os.path.exists(root):
root = os.path.normpath(
os.path.join(os.path.dirname(os.path.abspath(__file__)), "..",
"..", "..", "..", "samples"))
if not os.path.exists(root):
raise FileNotFoundError("Unable to find folder 'samples', tried %r." %
root)
pytorch_transformer_path = os.path.join(root, "python", "training",
"orttrainer",
"pytorch_transformer")
pt_model_path = os.path.join(pytorch_transformer_path, "pt_model.py")
pt_model = _utils.import_module_from_file(pt_model_path)
ort_utils_path = os.path.join(pytorch_transformer_path, "ort_utils.py")
ort_utils = _utils.import_module_from_file(ort_utils_path)
utils_path = os.path.join(pytorch_transformer_path, "utils.py")
utils = _utils.import_module_from_file(utils_path)
# Modeling
model = pt_model.TransformerModel(28785, 200, 2, 200, 2, 0.2).to(device)
my_loss = ort_utils.my_loss
if legacy_api:
if dynamic_axes:
model_desc = ort_utils.legacy_transformer_model_description_dynamic_axes(
)
else:
model_desc = ort_utils.legacy_transformer_model_description()
else:
if dynamic_axes:
model_desc = ort_utils.transformer_model_description_dynamic_axes()
else:
model_desc = ort_utils.transformer_model_description()
# Preparing data
train_data, val_data, test_data = utils.prepare_data(
device, 20, 20, data_dir)
return model, model_desc, my_loss, utils.get_batch, train_data, val_data, test_data