# Copyright 2021-2022 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 shutil import numpy as np import mindspore.offline_debug.dbg_services as d from dump_test_utils import build_dump_structure, write_watchpoint_to_json from tests.security_utils import security_off_wrap class TestOfflineWatchpoints: """Test watchpoint for offline debugger.""" GENERATE_GOLDEN = False test_name = "watchpoints" watchpoint_hits_json = [] temp_dir = '' @classmethod def setup_class(cls): """Init setup for offline watchpoints test""" 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) name3 = "CudnnUniformReal.CudnnUniformReal-op391.0.0.3" tensor4 = np.array([-32.0, -4096.0], np.float32) info4 = d.TensorInfo(node_name="Default/CudnnUniformReal-op391", slot=0, iteration=2, rank_id=0, root_graph_id=0, is_output=False) name4 = "Cast.Cast-op4.0.0.1" tensor_all_zero = np.array([[[0, 0, 0], [0, 0, 0], [0, 0, 0]]], np.float32) info5 = d.TensorInfo(node_name="Default/network-WithLossCell/_backbone-AlexNet/Cast-op4", slot=0, iteration=0, rank_id=0, root_graph_id=0, is_output=True) name5 = "Cast.Cast-op40.0.0.1" tensor_all_one = np.array([[[1, 1, 1], [1, 1, 1], [1, 1, 1]]], np.float32) info6 = d.TensorInfo(node_name="Default/network-WithLossCell/_backbone-AlexNet/Cast-op40", slot=0, iteration=0, rank_id=0, root_graph_id=0, is_output=True) tensor_info = [info1, info2, info3, info4, info5, info6] tensor_name = [name1, name2, name2, name3, name4, name5] tensor_list = [tensor1, tensor2, tensor3, tensor4, tensor_all_zero, tensor_all_one] cls.temp_dir = build_dump_structure(tensor_name, tensor_list, "Test", tensor_info) @classmethod def teardown_class(cls): shutil.rmtree(cls.temp_dir) @security_off_wrap def test_sync_add_remove_watchpoints_hit(self): # NOTES: watch_condition=6 is MIN_LT # watchpoint set and hit (watch_condition=6), then remove it debugger_backend = d.DbgServices(dump_file_path=self.temp_dir) _ = debugger_backend.initialize(net_name="Test", is_sync_mode=True) param = 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=[param]) # add second watchpoint to check the watchpoint hit in correct order param1 = d.Parameter(name="param", disabled=False, value=10.0) _ = debugger_backend.add_watchpoint(watchpoint_id=2, watch_condition=6, check_node_list={"Default/CudnnUniformReal-op391": {"rank_id": [0], "root_graph_id": [0], "is_output": False }}, parameter_list=[param1]) watchpoint_hits_test = debugger_backend.check_watchpoints(iteration=2) assert len(watchpoint_hits_test) == 2 if self.GENERATE_GOLDEN: self.print_watchpoint_hits(watchpoint_hits_test, 0, False) else: self.compare_expect_actual_result(watchpoint_hits_test, 0) _ = debugger_backend.remove_watchpoint(watchpoint_id=1) watchpoint_hits_test_1 = debugger_backend.check_watchpoints(iteration=2) assert len(watchpoint_hits_test_1) == 1 @security_off_wrap def test_sync_add_remove_watchpoints_not_hit(self): # watchpoint set and not hit(watch_condition=6), then remove debugger_backend = d.DbgServices(dump_file_path=self.temp_dir) _ = debugger_backend.initialize(net_name="Test", is_sync_mode=True) param = 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=[param]) watchpoint_hits_test = debugger_backend.check_watchpoints(iteration=2) assert not watchpoint_hits_test _ = debugger_backend.remove_watchpoint(watchpoint_id=2) @security_off_wrap def test_sync_weight_change_watchpoints_hit(self): # NOTES: watch_condition=18 is CHANGE_TOO_LARGE # weight change watchpoint set and hit(watch_condition=18) debugger_backend = d.DbgServices(dump_file_path=self.temp_dir) _ = debugger_backend.initialize(net_name="Test", is_sync_mode=True) 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 = debugger_backend.check_watchpoints(iteration=3) assert len(watchpoint_hits_test) == 1 if self.GENERATE_GOLDEN: self.print_watchpoint_hits(watchpoint_hits_test, 2, True) else: self.compare_expect_actual_result(watchpoint_hits_test, 2) @security_off_wrap def test_async_add_remove_watchpoint_hit(self): # watchpoint set and hit(watch_condition=6) in async mode, then remove debugger_backend = d.DbgServices(dump_file_path=self.temp_dir) _ = debugger_backend.initialize(net_name="Test", is_sync_mode=False) param = 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=[param]) watchpoint_hits_test = debugger_backend.check_watchpoints(iteration=2) assert len(watchpoint_hits_test) == 1 if not self.GENERATE_GOLDEN: self.compare_expect_actual_result(watchpoint_hits_test, 0) _ = debugger_backend.remove_watchpoint(watchpoint_id=1) watchpoint_hits_test_1 = debugger_backend.check_watchpoints(iteration=2) assert not watchpoint_hits_test_1 @security_off_wrap def test_async_add_remove_watchpoints_not_hit(self): # watchpoint set and not hit(watch_condition=6) in async mode, then remove debugger_backend = d.DbgServices(dump_file_path=self.temp_dir) _ = debugger_backend.initialize(net_name="Test", is_sync_mode=False) param = 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=[param]) watchpoint_hits_test = debugger_backend.check_watchpoints(iteration=2) assert not watchpoint_hits_test _ = debugger_backend.remove_watchpoint(watchpoint_id=2) @security_off_wrap def test_async_watchpoints_no_duplicate_wp_hit(self): """ Feature: Offline Debugger CheckWatchpoint. Description: Test check watchpoint hit with similar op name (one is the prefix of the other) Expectation: Get exactly one watchpoint hit result and no duplicate watchpoints in the hit results. """ # watchpoint set and hit only one (watch_condition=3) in async mode debugger_backend = d.DbgServices(dump_file_path=self.temp_dir) _ = debugger_backend.initialize(net_name="Test", is_sync_mode=False) max_gt = d.Parameter(name="max_gt", disabled=False, value=0.0) debugger_backend.add_watchpoint(watchpoint_id=3, watch_condition=3, check_node_list={"Default/network-WithLossCell/_backbone-AlexNet/Cast-op4": {"rank_id": [0], "root_graph_id": [0], "is_output": True }, "Default/network-WithLossCell/_backbone-AlexNet/Cast-op40": {"rank_id": [0], "root_graph_id": [0], "is_output": True }}, parameter_list=[max_gt]) watchpoint_hits_test = debugger_backend.check_watchpoints(iteration=0) assert len(watchpoint_hits_test) == 1 def compare_expect_actual_result(self, watchpoint_hits_list, test_index): """Compare actual result with golden file.""" golden_file = os.path.realpath(os.path.join("../data/dump/gpu_dumps/golden/", self.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(self, watchpoint_hits_list, test_index, is_print): """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) self.watchpoint_hits_json.append({watchpoint_hit: wp}) if is_print: with open(self.test_name + "_expected.json", "w") as dump_f: json.dump(self.watchpoint_hits_json, dump_f, indent=4, separators=(',', ': '))