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PaddleSpeech/speechx/examples/ds2_ol/onnx/local/pd_infer_shape.py

111 lines
4.2 KiB

#!/usr/bin/env python3 -W ignore::DeprecationWarning
# https://github.com/jiangjiajun/PaddleUtils/blob/main/paddle/README.md#2-%E4%BF%AE%E6%94%B9paddle%E6%A8%A1%E5%9E%8B%E8%BE%93%E5%85%A5shape
import argparse
# paddle inference shape
def process_old_ops_desc(program):
"""set matmul op head_number attr to 1 is not exist.
Args:
program (_type_): _description_
"""
for i in range(len(program.blocks[0].ops)):
if program.blocks[0].ops[i].type == "matmul":
if not program.blocks[0].ops[i].has_attr("head_number"):
program.blocks[0].ops[i]._set_attr("head_number", 1)
def infer_shape(program, input_shape_dict):
# 2002002
model_version = program.desc._version()
# 2.2.2
paddle_version = paddle.__version__
major_ver = model_version // 1000000
minor_ver = (model_version - major_ver * 1000000) // 1000
patch_ver = model_version - major_ver * 1000000 - minor_ver * 1000
model_version = "{}.{}.{}".format(major_ver, minor_ver, patch_ver)
if model_version != paddle_version:
print(
f"[WARNING] The model is saved by paddlepaddle v{model_version}, but now your paddlepaddle is version of {paddle_version}, this difference may cause error, it is recommend you reinstall a same version of paddlepaddle for this model"
)
OP_WITHOUT_KERNEL_SET = {
'feed', 'fetch', 'recurrent', 'go', 'rnn_memory_helper_grad',
'conditional_block', 'while', 'send', 'recv', 'listen_and_serv',
'fl_listen_and_serv', 'ncclInit', 'select', 'checkpoint_notify',
'gen_bkcl_id', 'c_gen_bkcl_id', 'gen_nccl_id', 'c_gen_nccl_id',
'c_comm_init', 'c_sync_calc_stream', 'c_sync_comm_stream',
'queue_generator', 'dequeue', 'enqueue', 'heter_listen_and_serv',
'c_wait_comm', 'c_wait_compute', 'c_gen_hccl_id', 'c_comm_init_hccl',
'copy_cross_scope'
}
for k, v in input_shape_dict.items():
program.blocks[0].var(k).desc.set_shape(v)
for i in range(len(program.blocks)):
for j in range(len(program.blocks[0].ops)):
# for ops
if program.blocks[i].ops[j].type in OP_WITHOUT_KERNEL_SET:
print(f"not infer: {program.blocks[i].ops[j].type} op")
continue
print(f"infer: {program.blocks[i].ops[j].type} op")
program.blocks[i].ops[j].desc.infer_shape(program.blocks[i].desc)
def parse_arguments():
# python pd_infer_shape.py --model_dir data/exp/deepspeech2_online/checkpoints \
# --model_filename avg_1.jit.pdmodel\
# --params_filename avg_1.jit.pdiparams \
# --save_dir . \
# --input_shape_dict="{'audio_chunk':[1,-1,161], 'audio_chunk_lens':[1], 'chunk_state_c_box':[5, 1, 1024], 'chunk_state_h_box':[5,1,1024]}"
parser = argparse.ArgumentParser()
parser.add_argument(
'--model_dir',
required=True,
help='Path of directory saved the input model.')
parser.add_argument(
'--model_filename', required=True, help='model.pdmodel.')
parser.add_argument(
'--params_filename', required=True, help='model.pdiparams.')
parser.add_argument(
'--save_dir',
required=True,
help='directory to save the exported model.')
parser.add_argument(
'--input_shape_dict', required=True, help="The new shape information.")
return parser.parse_args()
if __name__ == '__main__':
args = parse_arguments()
import paddle
paddle.enable_static()
import paddle.fluid as fluid
input_shape_dict_str = args.input_shape_dict
input_shape_dict = eval(input_shape_dict_str)
print("Start to load paddle model...")
exe = fluid.Executor(fluid.CPUPlace())
prog, ipts, outs = fluid.io.load_inference_model(
args.model_dir,
exe,
model_filename=args.model_filename,
params_filename=args.params_filename)
process_old_ops_desc(prog)
infer_shape(prog, input_shape_dict)
fluid.io.save_inference_model(
args.save_dir,
ipts,
outs,
exe,
prog,
model_filename=args.model_filename,
params_filename=args.params_filename)