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add get ops scripts (PaddlePaddle#47049)
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
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import paddle | ||
import argparse | ||
import numpy as np | ||
import os | ||
import re | ||
from paddle.inference import _get_phi_kernel_name | ||
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paddle.enable_static() | ||
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def parse_args(): | ||
parser = argparse.ArgumentParser() | ||
parser.add_argument('--model_dir', | ||
type=str, | ||
default="", | ||
help='Directory of the inference models.') | ||
return parser.parse_args() | ||
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def get_model_ops(model_file): | ||
model_bytes = paddle.static.load_from_file(model_file) | ||
pg = paddle.static.deserialize_program(model_bytes) | ||
ops_set = set() | ||
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for i in range(0, pg.desc.num_blocks()): | ||
block = pg.desc.block(i) | ||
size = block.op_size() | ||
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for j in range(0, size): | ||
ops_set.add(block.op(j).type()) | ||
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return ops_set | ||
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def get_model_phi_kernels(ops_set): | ||
phi_set = set() | ||
for op in ops_set: | ||
phi_set.add(_get_phi_kernel_name(op)) | ||
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return phi_set | ||
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if __name__ == '__main__': | ||
args = parse_args() | ||
for root, dirs, files in os.walk(args.model_dir, topdown=True): | ||
for name in files: | ||
if (re.match(r'.*pdmodel', name)): | ||
ops_set = get_model_ops(os.path.join(root, name)) | ||
phi_set = get_model_phi_kernels(ops_set) | ||
ops = ";".join(ops_set) | ||
kernels = ";".join(phi_set) | ||
print("op_list: ", ops) | ||
print("kernel_list: ", kernels) | ||
ops = np.array([ops]) | ||
kernels = np.array([kernels]) | ||
np.savetxt("op_list.txt", ops, fmt='%s') | ||
np.savetxt("kernel_list.txt", kernels, fmt='%s') |