Hui Zhang
2 years ago
parent
9c4763ecce
commit
a9a3cb4860
@ -1,111 +0,0 @@
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#!/usr/bin/env python3 -W ignore::DeprecationWarning
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# 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
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import argparse
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# paddle inference shape
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def process_old_ops_desc(program):
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"""set matmul op head_number attr to 1 is not exist.
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Args:
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program (_type_): _description_
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"""
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for i in range(len(program.blocks[0].ops)):
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if program.blocks[0].ops[i].type == "matmul":
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if not program.blocks[0].ops[i].has_attr("head_number"):
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program.blocks[0].ops[i]._set_attr("head_number", 1)
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def infer_shape(program, input_shape_dict):
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# 2002002
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model_version = program.desc._version()
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# 2.2.2
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paddle_version = paddle.__version__
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major_ver = model_version // 1000000
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minor_ver = (model_version - major_ver * 1000000) // 1000
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patch_ver = model_version - major_ver * 1000000 - minor_ver * 1000
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model_version = "{}.{}.{}".format(major_ver, minor_ver, patch_ver)
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if model_version != paddle_version:
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print(
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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"
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)
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OP_WITHOUT_KERNEL_SET = {
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'feed', 'fetch', 'recurrent', 'go', 'rnn_memory_helper_grad',
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'conditional_block', 'while', 'send', 'recv', 'listen_and_serv',
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'fl_listen_and_serv', 'ncclInit', 'select', 'checkpoint_notify',
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'gen_bkcl_id', 'c_gen_bkcl_id', 'gen_nccl_id', 'c_gen_nccl_id',
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'c_comm_init', 'c_sync_calc_stream', 'c_sync_comm_stream',
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'queue_generator', 'dequeue', 'enqueue', 'heter_listen_and_serv',
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'c_wait_comm', 'c_wait_compute', 'c_gen_hccl_id', 'c_comm_init_hccl',
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'copy_cross_scope'
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}
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for k, v in input_shape_dict.items():
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program.blocks[0].var(k).desc.set_shape(v)
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for i in range(len(program.blocks)):
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for j in range(len(program.blocks[0].ops)):
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# for ops
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if program.blocks[i].ops[j].type in OP_WITHOUT_KERNEL_SET:
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print(f"not infer: {program.blocks[i].ops[j].type} op")
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continue
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print(f"infer: {program.blocks[i].ops[j].type} op")
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program.blocks[i].ops[j].desc.infer_shape(program.blocks[i].desc)
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def parse_arguments():
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# python pd_infer_shape.py --model_dir data/exp/deepspeech2_online/checkpoints \
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# --model_filename avg_1.jit.pdmodel\
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# --params_filename avg_1.jit.pdiparams \
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# --save_dir . \
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# --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]}"
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parser = argparse.ArgumentParser()
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parser.add_argument(
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'--model_dir',
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required=True,
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help='Path of directory saved the input model.')
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parser.add_argument(
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'--model_filename', required=True, help='model.pdmodel.')
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parser.add_argument(
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'--params_filename', required=True, help='model.pdiparams.')
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parser.add_argument(
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'--save_dir',
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required=True,
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help='directory to save the exported model.')
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parser.add_argument(
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'--input_shape_dict', required=True, help="The new shape information.")
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return parser.parse_args()
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if __name__ == '__main__':
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args = parse_arguments()
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import paddle
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paddle.enable_static()
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import paddle.fluid as fluid
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input_shape_dict_str = args.input_shape_dict
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input_shape_dict = eval(input_shape_dict_str)
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print("Start to load paddle model...")
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exe = fluid.Executor(fluid.CPUPlace())
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prog, ipts, outs = fluid.io.load_inference_model(
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args.model_dir,
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exe,
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model_filename=args.model_filename,
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params_filename=args.params_filename)
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process_old_ops_desc(prog)
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infer_shape(prog, input_shape_dict)
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fluid.io.save_inference_model(
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args.save_dir,
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ipts,
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outs,
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exe,
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prog,
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model_filename=args.model_filename,
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params_filename=args.params_filename)
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@ -1,158 +0,0 @@
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#!/usr/bin/env python3 -W ignore::DeprecationWarning
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# https://github.com/jiangjiajun/PaddleUtils/blob/main/paddle/README.md#1-%E8%A3%81%E5%89%AApaddle%E6%A8%A1%E5%9E%8B
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import argparse
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import sys
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from typing import List
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# paddle prune model.
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def prepend_feed_ops(program,
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feed_target_names: List[str],
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feed_holder_name='feed'):
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import paddle.fluid.core as core
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if len(feed_target_names) == 0:
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return
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global_block = program.global_block()
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feed_var = global_block.create_var(
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name=feed_holder_name,
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type=core.VarDesc.VarType.FEED_MINIBATCH,
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persistable=True, )
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for i, name in enumerate(feed_target_names, 0):
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if not global_block.has_var(name):
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print(
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f"The input[{i}]: '{name}' doesn't exist in pruned inference program, which will be ignored in new saved model."
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)
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continue
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out = global_block.var(name)
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global_block._prepend_op(
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type='feed',
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inputs={'X': [feed_var]},
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outputs={'Out': [out]},
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attrs={'col': i}, )
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def append_fetch_ops(program,
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fetch_target_names: List[str],
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fetch_holder_name='fetch'):
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"""in the place, we will add the fetch op
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Args:
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program (_type_): inference program
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fetch_target_names (List[str]): target names
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fetch_holder_name (str, optional): fetch op name. Defaults to 'fetch'.
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"""
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import paddle.fluid.core as core
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global_block = program.global_block()
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fetch_var = global_block.create_var(
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name=fetch_holder_name,
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type=core.VarDesc.VarType.FETCH_LIST,
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persistable=True, )
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print(f"the len of fetch_target_names: {len(fetch_target_names)}")
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for i, name in enumerate(fetch_target_names):
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global_block.append_op(
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type='fetch',
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inputs={'X': [name]},
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outputs={'Out': [fetch_var]},
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attrs={'col': i}, )
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def insert_fetch(program,
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fetch_target_names: List[str],
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fetch_holder_name='fetch'):
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"""in the place, we will add the fetch op
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Args:
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program (_type_): inference program
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fetch_target_names (List[str]): target names
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fetch_holder_name (str, optional): fetch op name. Defaults to 'fetch'.
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"""
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global_block = program.global_block()
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# remove fetch
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need_to_remove_op_index = []
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for i, op in enumerate(global_block.ops):
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if op.type == 'fetch':
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need_to_remove_op_index.append(i)
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for index in reversed(need_to_remove_op_index):
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global_block._remove_op(index)
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program.desc.flush()
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# append new fetch
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append_fetch_ops(program, fetch_target_names, fetch_holder_name)
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def parse_arguments():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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'--model_dir',
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required=True,
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help='Path of directory saved the input model.')
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parser.add_argument(
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'--model_filename', required=True, help='model.pdmodel.')
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parser.add_argument(
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'--params_filename', required=True, help='model.pdiparams.')
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parser.add_argument(
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'--output_names',
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required=True,
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help='The outputs of model. sep by comma')
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parser.add_argument(
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'--save_dir',
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required=True,
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help='directory to save the exported model.')
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parser.add_argument('--debug', default=False, help='output debug info.')
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return parser.parse_args()
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if __name__ == '__main__':
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args = parse_arguments()
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args.output_names = args.output_names.split(",")
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if len(set(args.output_names)) < len(args.output_names):
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print(
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f"[ERROR] There's dumplicate name in --output_names {args.output_names}, which is not allowed."
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)
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sys.exit(-1)
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import paddle
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paddle.enable_static()
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# hack prepend_feed_ops
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paddle.fluid.io.prepend_feed_ops = prepend_feed_ops
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import paddle.fluid as fluid
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print("start to load paddle model")
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exe = fluid.Executor(fluid.CPUPlace())
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prog, ipts, outs = fluid.io.load_inference_model(
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args.model_dir,
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exe,
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model_filename=args.model_filename,
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params_filename=args.params_filename)
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print("start to load insert fetch op")
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new_outputs = []
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insert_fetch(prog, args.output_names)
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for out_name in args.output_names:
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new_outputs.append(prog.global_block().var(out_name))
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# not equal to paddle.static.save_inference_model
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fluid.io.save_inference_model(
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args.save_dir,
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ipts,
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new_outputs,
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exe,
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prog,
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model_filename=args.model_filename,
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params_filename=args.params_filename)
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if args.debug:
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for op in prog.global_block().ops:
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print(op)
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@ -1,23 +0,0 @@
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#!/bin/bash
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set -e
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if [ $# != 5 ]; then
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# local/prune.sh data/exp/deepspeech2_online/checkpoints avg_1.jit.pdmodel avg_1.jit.pdiparams softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 $PWD
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echo "usage: $0 model_dir model_filename param_filename outputs_names save_dir"
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exit 1
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fi
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dir=$1
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model=$2
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param=$3
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outputs=$4
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save_dir=$5
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python local/pd_prune_model.py \
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--model_dir $dir \
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--model_filename $model \
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--params_filename $param \
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--output_names $outputs \
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--save_dir $save_dir
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