diff --git a/debug/accuracy_tools/api_accuracy_checker/test/resources/forward.json b/debug/accuracy_tools/api_accuracy_checker/test/resources/forward.json index fe5212ebe3313673508a9b5a2a0739cec3dbc88d..5f54e077bfd0425be200f89e14a8ba131d3a3a8b 100644 --- a/debug/accuracy_tools/api_accuracy_checker/test/resources/forward.json +++ b/debug/accuracy_tools/api_accuracy_checker/test/resources/forward.json @@ -1,3 +1,3 @@ { - "Functional*silu*0": {"args": [{"type": "torch.Tensor", "dtype": "torch.float16", "shape": [2, 2560, 24, 24], "Max": 5.7421875, "Min": -5.125, "requires_grad": true}], "kwargs" :{"inplace": {"type": "bool", "value": false}}} + "Functional*silu*0": {"args": [{"type": "torch.Tensor", "dtype": "torch.float32", "shape": [2, 2560, 24, 24], "Max": 5.7421875, "Min": -5.125, "requires_grad": true}], "kwargs" :{"inplace": {"type": "bool", "value": false}}} } \ No newline at end of file diff --git a/debug/accuracy_tools/api_accuracy_checker/test/ut/run_ut/test_data_generate.py b/debug/accuracy_tools/api_accuracy_checker/test/ut/run_ut/test_data_generate.py index 7cb9a8504d53520af3ccc21cdddae3f2927ee967..fff5d6e4bd7c978448576f4b328ab57e3ebc0b81 100644 --- a/debug/accuracy_tools/api_accuracy_checker/test/ut/run_ut/test_data_generate.py +++ b/debug/accuracy_tools/api_accuracy_checker/test/ut/run_ut/test_data_generate.py @@ -23,7 +23,7 @@ class TestDataGenerateMethods(unittest.TestCase): max_diff = abs(args_params[0].max() - max_value) min_diff = abs(args_params[0].min() - min_value) self.assertEqual(len(args_params), 1) - self.assertEqual(args_params[0].dtype, torch.float16) + self.assertEqual(args_params[0].dtype, torch.float32) self.assertLessEqual(max_diff, 0.001) self.assertLessEqual(min_diff, 0.001) self.assertEqual(args_params[0].shape, torch.Size([2, 2560, 24, 24])) @@ -34,7 +34,7 @@ class TestDataGenerateMethods(unittest.TestCase): max_diff = abs(args_result[0].max() - max_value) min_diff = abs(args_result[0].min() - min_value) self.assertEqual(len(args_result), 1) - self.assertEqual(args_result[0].dtype, torch.float16) + self.assertEqual(args_result[0].dtype, torch.float32) self.assertLessEqual(max_diff, 0.001) self.assertLessEqual(min_diff, 0.001) self.assertEqual(args_result[0].shape, torch.Size([2, 2560, 24, 24])) @@ -43,7 +43,7 @@ class TestDataGenerateMethods(unittest.TestCase): data = gen_data(api_info_dict.get('args')[0], True, None) max_diff = abs(data.max() - max_value) min_diff = abs(data.min() - min_value) - self.assertEqual(data.dtype, torch.float16) + self.assertEqual(data.dtype, torch.float32) self.assertEqual(data.requires_grad, True) self.assertLessEqual(max_diff, 0.001) self.assertLessEqual(min_diff, 0.001) @@ -55,15 +55,15 @@ class TestDataGenerateMethods(unittest.TestCase): self.assertEqual(kwargs_params, {'inplace': False}) def test_gen_kwargs_device(self): - k_dict = {"kwargs": {"device": {"type": "torch.device", "value": "npu:0"}}} + k_dict = {"kwargs": {"device": {"type": "torch.device", "value": "cpu"}}} kwargs_params = gen_kwargs(k_dict, None) - self.assertEqual(str(kwargs_params), "{'device': device(type='npu', index=0)}") + self.assertEqual(str(kwargs_params), "{'device': device(type='cpu')}") def test_gen_kwargs_1(self): - k_dict = {"device": {"type": "torch.device", "value": "npu:0"}} + k_dict = {"device": {"type": "torch.device", "value": "cpu"}} for key, value in k_dict.items(): gen_torch_kwargs(k_dict, key, value) - self.assertEqual(str(k_dict), "{'device': device(type='npu', index=0)}") + self.assertEqual(str(k_dict), "{'device': device(type='cpu')}") def test_gen_kwargs_2(self): k_dict = {"inplace": {"type": "bool", "value": "False"}} @@ -75,7 +75,7 @@ class TestDataGenerateMethods(unittest.TestCase): data = gen_random_tensor(api_info_dict.get('args')[0], None) max_diff = abs(data.max() - max_value) min_diff = abs(data.min() - min_value) - self.assertEqual(data.dtype, torch.float16) + self.assertEqual(data.dtype, torch.float32) self.assertEqual(data.requires_grad, False) self.assertLessEqual(max_diff, 0.001) self.assertLessEqual(min_diff, 0.001) @@ -89,7 +89,7 @@ class TestDataGenerateMethods(unittest.TestCase): data = gen_common_tensor(low, high, shape, data_dtype, None) max_diff = abs(data.max() - max_value) min_diff = abs(data.min() - min_value) - self.assertEqual(data.dtype, torch.float16) + self.assertEqual(data.dtype, torch.float32) self.assertEqual(data.requires_grad, False) self.assertLessEqual(max_diff, 0.001) self.assertLessEqual(min_diff, 0.001) diff --git a/debug/accuracy_tools/api_accuracy_checker/test/ut/run_ut/test_run_ut.py b/debug/accuracy_tools/api_accuracy_checker/test/ut/run_ut/test_run_ut.py index 6ed7acbedea07acae0be151fcd5271274a585757..e966e1810418fdd9a273b8d79f296866f83a00d4 100644 --- a/debug/accuracy_tools/api_accuracy_checker/test/ut/run_ut/test_run_ut.py +++ b/debug/accuracy_tools/api_accuracy_checker/test/ut/run_ut/test_run_ut.py @@ -1,12 +1,11 @@ # coding=utf-8 import os import copy -import numpy as np import unittest -from unittest.mock import patch +import torch +from unittest.mock import patch, DEFAULT from api_accuracy_checker.run_ut.run_ut import * from api_accuracy_checker.common.utils import get_json_contents -from api_accuracy_checker.run_ut.run_ut import generate_cpu_params, get_api_info, UtDataInfo base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) forward_file = os.path.join(base_dir, "../resources/forward.json") @@ -22,13 +21,12 @@ class TestRunUtMethods(unittest.TestCase): args, kwargs, need_grad = get_api_info(api_info, api_name) cpu_args, cpu_kwargs = generate_cpu_params(args, kwargs, True) out = exec_api(api_type, api_name, cpu_args, cpu_kwargs) - self.assertEqual(out.dtype, torch.float32) + self.assertEqual(out.dtype, torch.float64) self.assertEqual(out.requires_grad, True) self.assertEqual(out.shape, torch.Size([2, 2560, 24, 24])) def test_generate_device_params(self): - MockTensor = namedtuple('MockTensor', ['requires_grad', 'dtype', 'shape']) - mock_tensor = MockTensor(True, torch.float16, torch.Size([2, 2560, 24, 24])) + mock_tensor = torch.rand([2, 2560, 24, 24], dtype=torch.float32, requires_grad=True) with patch.multiple('torch.Tensor', to=DEFAULT, @@ -46,7 +44,7 @@ class TestRunUtMethods(unittest.TestCase): device_args, device_kwargs = generate_device_params([mock_tensor], {'inplace': False}, True) self.assertEqual(len(device_args), 1) - self.assertEqual(device_args[0].dtype, torch.float16) + self.assertEqual(device_args[0].dtype, torch.float32) self.assertEqual(device_args[0].requires_grad, True) self.assertEqual(device_args[0].shape, torch.Size([2, 2560, 24, 24])) self.assertEqual(device_kwargs, {'inplace': False}) @@ -57,7 +55,7 @@ class TestRunUtMethods(unittest.TestCase): args, kwargs, need_grad = get_api_info(api_info, api_name) cpu_args, cpu_kwargs = generate_cpu_params(args, kwargs, True) self.assertEqual(len(cpu_args), 1) - self.assertEqual(cpu_args[0].dtype, torch.float32) + self.assertEqual(cpu_args[0].dtype, torch.float64) self.assertEqual(cpu_args[0].requires_grad, True) self.assertEqual(cpu_args[0].shape, torch.Size([2, 2560, 24, 24])) self.assertEqual(cpu_kwargs, {'inplace': False})