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update import in convert_generation.py (#19385)

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Fix for https://github.com/microsoft/onnxruntime/issues/19376
- Use absolute import instead of relative import for now. 
- Fix some typo
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Tianlei Wu 2024-02-02 10:16:37 -08:00 committed by GitHub
parent ccbe264a39
commit 18c3acb198
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1 changed files with 9 additions and 9 deletions
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18
onnxruntime/python/tools/transformers/convert_generation.py
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@ -55,10 +55,6 @@ import onnx
import torch
from benchmark_helper import Precision, setup_logger
from fusion_utils import NumpyHelper
from models.gpt2.convert_to_onnx import main as convert_gpt2_to_onnx
from models.gpt2.gpt2_helper import PRETRAINED_GPT2_MODELS
from models.t5.convert_to_onnx import export_onnx_models as export_t5_onnx_models
from models.t5.t5_helper import PRETRAINED_MT5_MODELS, PRETRAINED_T5_MODELS
from onnx import GraphProto, ModelProto, TensorProto
from onnx_model import OnnxModel
from transformers import (
@ -73,6 +69,10 @@ from transformers import (
)
from onnxruntime import GraphOptimizationLevel, InferenceSession, SessionOptions, get_available_providers
from onnxruntime.transformers.models.gpt2.convert_to_onnx import main as convert_gpt2_to_onnx
from onnxruntime.transformers.models.gpt2.gpt2_helper import PRETRAINED_GPT2_MODELS
from onnxruntime.transformers.models.t5.convert_to_onnx import export_onnx_models as export_t5_onnx_models
from onnxruntime.transformers.models.t5.t5_helper import PRETRAINED_MT5_MODELS, PRETRAINED_T5_MODELS
logger = logging.getLogger("")
@ -372,7 +372,7 @@ def parse_arguments(argv: Optional[List[str]] = None) -> argparse.Namespace:
type=int,
required=False,
default=1,
help="Minimumber of tokens we keep per batch example in the output.",
help="Minimum number of tokens we keep per batch example in the output.",
)
beam_parameters_group.add_argument(
@ -466,7 +466,7 @@ def parse_arguments(argv: Optional[List[str]] = None) -> argparse.Namespace:
"--save_test_data",
required=False,
action="store_true",
help="save test data for onnxruntimer_perf_test tool",
help="save test data for onnxruntime_perf_test tool",
)
test_group.set_defaults(save_test_data=False)
@ -1225,7 +1225,7 @@ def find_past_seq_len_usage(subg: GraphProto):
tensor_names_to_rename = set()
nodes_to_remove = []
graph_intput_names = {inp.name: index for index, inp in enumerate(subg.input)}
graph_input_names = {inp.name: index for index, inp in enumerate(subg.input)}
input_name_to_nodes = {}
output_name_to_node = {}
@ -1259,7 +1259,7 @@ def find_past_seq_len_usage(subg: GraphProto):
if (
shape_node.op_type == "Shape"
and shape_node.input[0]
and shape_node.input[0] in graph_intput_names
and shape_node.input[0] in graph_input_names
and (
shape_node.input[0].startswith("past_key_self_")
or shape_node.input[0].startswith("past_value_self_")
@ -1423,7 +1423,7 @@ def update_decoder_subgraph_share_buffer_and_use_decoder_masked_mha(subg: ModelP
if node.op_type == "MultiHeadAttention":
old_nodes.extend([node])
# If not all the MultiheadAttention nodes are fused, this optimization is not applicable
# If not all the MultiHeadAttention nodes are fused, this optimization is not applicable
if len(old_nodes) < num_layers:
return False