240 lines
11 KiB
Python
240 lines
11 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
|
|
#
|
|
# 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.
|
|
# ==============================================================================
|
|
"""
|
|
Watchpoints test script for offline debugger APIs.
|
|
"""
|
|
|
|
import os
|
|
import json
|
|
import time
|
|
import tempfile
|
|
import numpy as np
|
|
import pytest
|
|
import mindspore.offline_debug.dbg_services as d
|
|
from tests.security_utils import security_off_wrap
|
|
from dump_test_utils import build_dump_structure, write_watchpoint_to_json
|
|
|
|
GENERATE_GOLDEN = False
|
|
watchpoint_hits_json = []
|
|
|
|
|
|
def run_watchpoints(is_sync):
|
|
if is_sync:
|
|
test_name = "sync_watchpoints"
|
|
else:
|
|
test_name = "async_watchpoints"
|
|
|
|
name1 = "Conv2D.Conv2D-op369.0.0.1"
|
|
tensor1 = np.array([[[-1.2808e-03, 7.7629e-03, 1.9241e-02],
|
|
[-1.3931e-02, 8.9359e-04, -1.1520e-02],
|
|
[-6.3248e-03, 1.8749e-03, 1.0132e-02]],
|
|
[[-2.5520e-03, -6.0005e-03, -5.1918e-03],
|
|
[-2.7866e-03, 2.5487e-04, 8.4782e-04],
|
|
[-4.6310e-03, -8.9111e-03, -8.1778e-05]],
|
|
[[1.3914e-03, 6.0844e-04, 1.0643e-03],
|
|
[-2.0966e-02, -1.2865e-03, -1.8692e-03],
|
|
[-1.6647e-02, 1.0233e-03, -4.1313e-03]]], np.float32)
|
|
info1 = d.TensorInfo(node_name="Default/network-WithLossCell/_backbone-AlexNet/conv1-Conv2d/Conv2D-op369",
|
|
slot=1, iteration=2, rank_id=0, root_graph_id=0, is_output=False)
|
|
|
|
name2 = "Parameter.fc2.bias.0.0.2"
|
|
tensor2 = np.array([-5.0167350e-06, 1.2509107e-05, -4.3148934e-06, 8.1415592e-06,
|
|
2.1177532e-07, 2.9952851e-06], np.float32)
|
|
info2 = d.TensorInfo(node_name="Default/network-WithLossCell/_backbone-AlexNet/fc3-Dense/"
|
|
"Parameter[6]_11/fc2.bias",
|
|
slot=0, iteration=2, rank_id=0, root_graph_id=0, is_output=True)
|
|
|
|
tensor3 = np.array([2.9060817e-07, -5.1009415e-06, -2.8662325e-06, 2.6036503e-06,
|
|
-5.1546101e-07, 6.0798648e-06], np.float32)
|
|
info3 = d.TensorInfo(node_name="Default/network-WithLossCell/_backbone-AlexNet/fc3-Dense/"
|
|
"Parameter[6]_11/fc2.bias",
|
|
slot=0, iteration=3, rank_id=0, root_graph_id=0, is_output=True)
|
|
|
|
tensor_info = [info1, info2, info3]
|
|
tensor_name = [name1, name2, name2]
|
|
tensor_list = [tensor1, tensor2, tensor3]
|
|
|
|
pwd = os.getcwd()
|
|
with tempfile.TemporaryDirectory(dir=pwd) as tmp_dir:
|
|
temp_dir = build_dump_structure(tmp_dir, tensor_name, tensor_list, "Test", tensor_info)
|
|
|
|
debugger_backend = d.DbgServices(dump_file_path=temp_dir)
|
|
debugger_backend.initialize(net_name="Test", is_sync_mode=is_sync)
|
|
|
|
# NOTES:
|
|
# -> watch_condition=6 is MIN_LT
|
|
# -> watch_condition=18 is CHANGE_TOO_LARGE
|
|
|
|
# test 1: watchpoint set and hit (watch_condition=6)
|
|
param1 = d.Parameter(name="param", disabled=False, value=0.0)
|
|
debugger_backend.add_watchpoint(watchpoint_id=1, watch_condition=6,
|
|
check_node_list={"Default/network-WithLossCell/_backbone-AlexNet/"
|
|
"conv1-Conv2d/Conv2D-op369":
|
|
{"rank_id": [0], "root_graph_id": [0], "is_output": False
|
|
}}, parameter_list=[param1])
|
|
|
|
watchpoint_hits_test_1 = debugger_backend.check_watchpoints(iteration=2)
|
|
assert len(watchpoint_hits_test_1) == 1
|
|
if GENERATE_GOLDEN:
|
|
print_watchpoint_hits(watchpoint_hits_test_1, 0, False, test_name)
|
|
else:
|
|
compare_expect_actual_result(watchpoint_hits_test_1, 0, test_name)
|
|
|
|
# test 2: watchpoint remove and ensure it's not hit
|
|
debugger_backend.remove_watchpoint(watchpoint_id=1)
|
|
watchpoint_hits_test_2 = debugger_backend.check_watchpoints(iteration=2)
|
|
assert not watchpoint_hits_test_2
|
|
|
|
# test 3: watchpoint set and not hit, then remove
|
|
param2 = d.Parameter(name="param", disabled=False, value=-1000.0)
|
|
debugger_backend.add_watchpoint(watchpoint_id=2, watch_condition=6,
|
|
check_node_list={"Default/network-WithLossCell/_backbone-AlexNet/"
|
|
"conv1-Conv2d/Conv2D-op369":
|
|
{"rank_id": [0], "root_graph_id": [0], "is_output": False
|
|
}}, parameter_list=[param2])
|
|
|
|
watchpoint_hits_test_3 = debugger_backend.check_watchpoints(iteration=2)
|
|
assert not watchpoint_hits_test_3
|
|
_ = debugger_backend.remove_watchpoint(watchpoint_id=2)
|
|
|
|
# test 4: weight change watchpoint set and hit
|
|
param_abs_mean_update_ratio_gt = d.Parameter(
|
|
name="abs_mean_update_ratio_gt", disabled=False, value=0.0)
|
|
param_epsilon = d.Parameter(name="epsilon", disabled=True, value=0.0)
|
|
debugger_backend.add_watchpoint(watchpoint_id=3, watch_condition=18,
|
|
check_node_list={"Default/network-WithLossCell/_backbone-AlexNet/fc3-Dense/"
|
|
"Parameter[6]_11/fc2.bias":
|
|
{"rank_id": [0], "root_graph_id": [0], "is_output": True
|
|
}}, parameter_list=[param_abs_mean_update_ratio_gt,
|
|
param_epsilon])
|
|
|
|
watchpoint_hits_test_4 = debugger_backend.check_watchpoints(iteration=3)
|
|
assert len(watchpoint_hits_test_4) == 1
|
|
|
|
if GENERATE_GOLDEN:
|
|
print_watchpoint_hits(watchpoint_hits_test_4, 1, True, test_name)
|
|
else:
|
|
compare_expect_actual_result(watchpoint_hits_test_4, 1, test_name)
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
@security_off_wrap
|
|
def test_sync_watchpoints():
|
|
run_watchpoints(True)
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
@security_off_wrap
|
|
def test_async_watchpoints():
|
|
run_watchpoints(False)
|
|
|
|
|
|
def run_overflow_watchpoint(is_overflow):
|
|
test_name = "overflow_watchpoint"
|
|
tensor = np.array([65504, 65504], np.float16)
|
|
task_id = 2
|
|
stream_id = 7
|
|
pwd = os.getcwd()
|
|
with tempfile.TemporaryDirectory(dir=pwd) as tmp_dir:
|
|
path = os.path.join(tmp_dir, "rank_0", "Add", "0", "0")
|
|
os.makedirs(path, exist_ok=True)
|
|
add_file = os.path.join(path, "Add.Default_Add-op0." + str(task_id) + "." + str(stream_id) + "."
|
|
+ str(int(round(time.time() * 1000000))))
|
|
with open(add_file, 'wb') as add_f:
|
|
add_f.write(b'1')
|
|
add_f.seek(8)
|
|
add_f.write(b'\n\x032.0\x10\x83\xf7\xef\x9f\x99\xc8\xf3\x02\x1a\x10\x08\x02\x10\x02\x1a\x03')
|
|
add_f.write(b'\n\x01\x020\x04:\x03\n\x01\x022\x0f')
|
|
add_f.write(b'Default/Add-op0')
|
|
add_f.write(tensor)
|
|
overflow_file = os.path.join(path, "Opdebug.Node_OpDebug." + str(task_id) + "." + str(stream_id) +
|
|
"." + str(int(round(time.time() * 1000000))))
|
|
with open(overflow_file, 'wb') as f:
|
|
f.seek(321, 0)
|
|
byte_list = []
|
|
for i in range(256):
|
|
if i == 16:
|
|
byte_list.append(stream_id)
|
|
elif i == 24:
|
|
if is_overflow:
|
|
byte_list.append(task_id)
|
|
else:
|
|
# wrong task_id, should not generate overflow watchpoint hit
|
|
byte_list.append(task_id + 1)
|
|
else:
|
|
byte_list.append(0)
|
|
new_byte_array = bytearray(byte_list)
|
|
f.write(bytes(new_byte_array))
|
|
debugger_backend = d.DbgServices(dump_file_path=tmp_dir)
|
|
debugger_backend.initialize(net_name="Add", is_sync_mode=False)
|
|
debugger_backend.add_watchpoint(watchpoint_id=1, watch_condition=2,
|
|
check_node_list={"Default/Add-op0":
|
|
{"rank_id": [0], "root_graph_id": [0], "is_output": True
|
|
}}, parameter_list=[])
|
|
|
|
watchpoint_hits_test = debugger_backend.check_watchpoints(iteration=0)
|
|
|
|
if is_overflow:
|
|
assert len(watchpoint_hits_test) == 1
|
|
if GENERATE_GOLDEN:
|
|
print_watchpoint_hits(watchpoint_hits_test, 0, True, test_name)
|
|
else:
|
|
compare_expect_actual_result(watchpoint_hits_test, 0, test_name)
|
|
else:
|
|
assert not watchpoint_hits_test
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
@security_off_wrap
|
|
def test_async_overflow_watchpoints_hit():
|
|
"""
|
|
Feature: Offline Debugger CheckWatchpoint
|
|
Description: Test check overflow watchpoint hit
|
|
Expectation: Overflow watchpoint is hit
|
|
"""
|
|
run_overflow_watchpoint(True)
|
|
|
|
|
|
def compare_expect_actual_result(watchpoint_hits_list, test_index, test_name):
|
|
"""Compare actual result with golden file."""
|
|
pwd = os.getcwd()
|
|
golden_file = os.path.realpath(os.path.join(pwd, "golden", test_name + "_expected.json"))
|
|
with open(golden_file) as f:
|
|
expected_list = json.load(f)
|
|
for x, watchpoint_hits in enumerate(watchpoint_hits_list):
|
|
test_id = "watchpoint_hit" + str(test_index + x + 1)
|
|
expect_wp = expected_list[x + test_index][test_id]
|
|
actual_wp = write_watchpoint_to_json(watchpoint_hits)
|
|
assert actual_wp == expect_wp
|
|
|
|
def print_watchpoint_hits(watchpoint_hits_list, test_index, is_print, test_name):
|
|
"""Print watchpoint hits."""
|
|
for x, watchpoint_hits in enumerate(watchpoint_hits_list):
|
|
watchpoint_hit = "watchpoint_hit" + str(test_index + x + 1)
|
|
wp = write_watchpoint_to_json(watchpoint_hits)
|
|
watchpoint_hits_json.append({watchpoint_hit: wp})
|
|
if is_print:
|
|
with open(test_name + "_expected.json", "w") as dump_f:
|
|
json.dump(watchpoint_hits_json, dump_f, indent=4, separators=(',', ': '))
|