# 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.level1 @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.level1 @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.level1 @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=(',', ': '))