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final_ut_parallel_rule.py
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# -*- coding: utf-8 -*-
# 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.
import os
import json
import sys
def classify_cases_by_mem(rootPath):
"""classify cases by mem"""
case_filename = '%s/build/classify_case_by_cardNum.txt' % rootPath
case_exec_100 = [
'test_conv_eltwiseadd_bn_fuse_pass', 'test_trt_convert_pool2d',
'test_fc_fuse_pass', 'test_trt_convert_depthwise_conv2d',
'test_quant2_int8_resnet50_mkldnn',
'test_conv_elementwise_add_act_fuse_pass', 'test_trt_convert_conv2d',
'test_paddle_save_load', 'test_logical_op', 'test_nearest_interp_op',
'test_pool2d_op', 'test_conv3d_transpose_op', 'test_lstmp_op',
'test_cross_entropy2_op', 'test_sgd_op', 'test_imperative_ptq',
'test_model', 'test_custom_relu_op_setup', 'test_dropout_op',
'test_concat_op'
] #木桶原理 70s-100s之间的case
case_exec_200 = [
'test_post_training_quantization_mnist',
'test_imperative_auto_mixed_precision',
'test_trt_dynamic_shape_ernie_fp16_ser_deser',
'test_trt_dynamic_shape_ernie', 'test_layer_norm_op',
'trt_quant_int8_yolov3_r50_test', 'test_gru_op',
'test_post_training_quantization_while', 'test_mkldnn_log_softmax_op',
'test_mkldnn_matmulv2_op', 'test_mkldnn_shape_op',
'interceptor_pipeline_short_path_test',
'interceptor_pipeline_long_path_test', 'test_cpuonly_spawn'
] #木桶原理 110s-200s之间的case 以及容易timeout
case_always_timeout = [
'test_quant2_int8_resnet50_channelwise_mkldnn',
'test_parallel_dygraph_unused_variables_gloo',
'test_seq2seq',
'test_pool3d_op',
'test_trilinear_interp_op',
'test_trilinear_interp_v2_op',
'test_dropout_op',
'test_parallel_dygraph_sync_batch_norm',
'test_conv3d_op',
'test_quant2_int8_resnet50_range_mkldnn',
] # always timeout
f = open(case_filename)
lines = f.readlines()
all_tests_by_card = {}
for line in lines:
if line.startswith('single_card_tests:'):
all_tests_by_card['single_card_tests'] = []
line = line.split('single_card_tests: ^job$|')[1].split('|')
for case in line:
case = case.replace('^', '').replace('$', '').strip()
all_tests_by_card['single_card_tests'].append(case)
elif line.startswith('multiple_card_tests:'):
all_tests_by_card['multiple_card_tests'] = []
line = line.split('multiple_card_tests: ^job$|')[1].split('|')
for case in line:
case = case.replace('^', '').replace('$', '').strip()
all_tests_by_card['multiple_card_tests'].append(case)
elif line.startswith('exclusive_card_tests:'):
all_tests_by_card['exclusive_card_tests'] = []
line = line.split('exclusive_card_tests: ^job$')[1].split('|')
for case in line:
case = case.replace('^', '').replace('$', '').strip()
all_tests_by_card['exclusive_card_tests'].append(case)
if not os.path.exists("/pre_test"):
os.mkdir("/pre_test")
with open("/pre_test/classify_case_by_cardNum.json", "w") as f:
json.dump(all_tests_by_card, f)
with open("/pre_test/ut_mem_map.json", 'r') as load_f:
new_lastest_mem = json.load(load_f)
no_parallel_case = '^job$'
for cardType in all_tests_by_card:
case_mem_0 = '^job$'
case_mem_1 = {}
for case in all_tests_by_card[cardType]:
if case in case_exec_100 or case in case_exec_200:
continue
if case in case_always_timeout:
no_parallel_case = no_parallel_case + '|^' + case + '$'
continue
if case not in new_lastest_mem:
continue
#mem = 0
if new_lastest_mem[case]["mem_nvidia"] == 0:
case_mem_0 = case_mem_0 + '|^' + case + '$'
#mem != 0
else:
case_mem_1[case] = new_lastest_mem[case]["mem_nvidia"]
with open('/pre_test/%s_mem0' % cardType, 'w') as f:
f.write(case_mem_0)
f.close()
case_mem_1_sort = sorted(case_mem_1.items(), key=lambda x: x[1])
case_mem_1_line = '^job$'
mem_1_sum = 0
with open('/pre_test/%s' % cardType, 'w') as f_not_0:
for index in case_mem_1_sort:
if mem_1_sum < 14 * 1024 * 2:
mem_1_sum += index[1]
case_mem_1_line = case_mem_1_line + '|^' + index[0] + '$'
else:
f_not_0.write(case_mem_1_line + '\n')
'''
if len(always_timeout_list
) != 0 and cardType == 'single_card_tests' and count > 25:
f.write(case_mem_1_line + '|^%s$\n' %
always_timeout_list[0])
always_timeout_list.pop(0)
else:
f.write(case_mem_1_line + '\n')
count += 1
'''
case_mem_1_line = '^job$|^' + index[0] + '$'
mem_1_sum = index[1]
f_not_0.write(case_mem_1_line + '\n')
if cardType == 'single_card_tests':
for cases in [case_exec_100, case_exec_200]:
case_mem_1_line = '^job$'
for case in cases:
case_mem_1_line = case_mem_1_line + '|^' + case + '$'
f_not_0.write(case_mem_1_line + '\n')
f_not_0.close()
os.system('cp %s/build/nightly_case /pre_test/' % rootPath)
if __name__ == '__main__':
rootPath = sys.argv[1]
classify_cases_by_mem(rootPath)