forked from huawei/mindspore2022
286 lines
8.0 KiB
Python
286 lines
8.0 KiB
Python
# 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.
|
|
# ============================================================================
|
|
""" test graph fallback """
|
|
import pytest
|
|
import numpy as np
|
|
|
|
import mindspore.nn as nn
|
|
import mindspore.common.dtype as mstype
|
|
from mindspore import Tensor, ms_function, context
|
|
from mindspore.ops import Primitive
|
|
|
|
context.set_context(mode=context.GRAPH_MODE)
|
|
|
|
|
|
class ControlNet(nn.Cell):
|
|
def inner_function_1(self, a, b):
|
|
return a + b
|
|
|
|
def inner_function_2(self, a, b):
|
|
return a - b
|
|
|
|
def construct(self, x):
|
|
a = Tensor(np.array(4), mstype.int32)
|
|
b = Tensor(np.array(5), mstype.int32)
|
|
if a + b > x:
|
|
return self.inner_function_1(a, b)
|
|
return self.inner_function_2(a, b)
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_fallback_control_sink_tensor():
|
|
"""
|
|
Feature: Fallback feature: support define Tensor in Class construct.
|
|
Description: Fallback feature: support define Tensor in Class construct.
|
|
Expectation: Fallback feature: support define Tensor in Class construct.
|
|
"""
|
|
x = Tensor(np.array(1), mstype.int32)
|
|
net = ControlNet()
|
|
output = net(x)
|
|
output_expect = Tensor(9, mstype.int32)
|
|
assert output == output_expect
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_np_tensor_list():
|
|
"""
|
|
Feature: Fallback feature
|
|
Description: support Basic method of Tensor list.
|
|
Expectation: No exception.
|
|
"""
|
|
@ms_function
|
|
def np_tensor_list():
|
|
a = Tensor(np.array(4), mstype.int32)
|
|
b = Tensor(np.array(5), mstype.int32)
|
|
c = Tensor(np.array(6), mstype.int32)
|
|
tensor_list = [a, b]
|
|
for tensor in tensor_list:
|
|
print(tensor)
|
|
tensor_list.append(tensor_list[-1] + c)
|
|
return tensor_list
|
|
|
|
tensor_list = np_tensor_list()
|
|
print("tensor_list:", tensor_list)
|
|
assert len(tensor_list) == 3
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_list_count():
|
|
"""
|
|
Feature: Fallback feature
|
|
Description: support attr/method of builtin type.
|
|
Expectation: No exception.
|
|
"""
|
|
@ms_function
|
|
def list_count():
|
|
x = list([1, 2, 3])
|
|
res = x.count(1)
|
|
return res
|
|
assert list_count() == 1
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_list_append():
|
|
"""
|
|
Feature: Fallback feature
|
|
Description: support attr/method of builtin type.
|
|
Expectation: No exception.
|
|
"""
|
|
@ms_function
|
|
def list_append():
|
|
x = list([1, 2, 3])
|
|
x.append(4)
|
|
return Tensor(x)
|
|
assert np.all(list_append().asnumpy() == np.array([1, 2, 3, 4]))
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_list_insert_1():
|
|
"""
|
|
Feature: Fallback feature
|
|
Description: support attr/method of builtin type.
|
|
Expectation: No exception.
|
|
"""
|
|
@ms_function
|
|
def list_insert():
|
|
x = list([1, 3, 4])
|
|
x.insert(0, 2)
|
|
return Tensor(x)
|
|
assert np.all(list_insert().asnumpy() == np.array([2, 1, 3, 4]))
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_list_insert_2():
|
|
"""
|
|
Feature: Fallback feature
|
|
Description: support attr/method of builtin type.
|
|
Expectation: No exception.
|
|
"""
|
|
@ms_function
|
|
def list_insert():
|
|
x = list([1, 3, 4])
|
|
x.insert(5, 2)
|
|
return Tensor(x)
|
|
assert np.all(list_insert().asnumpy() == np.array([1, 3, 4, 2]))
|
|
|
|
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_list_insert_3():
|
|
"""
|
|
Feature: Fallback feature
|
|
Description: support attr/method of builtin type.
|
|
Expectation: No exception.
|
|
"""
|
|
@ms_function
|
|
def list_insert():
|
|
x = list([1, 3, 4])
|
|
x.insert(-1, 2)
|
|
return Tensor(x)
|
|
assert np.all(list_insert().asnumpy() == np.array([1, 3, 2, 4]))
|
|
|
|
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_list_insert_4():
|
|
"""
|
|
Feature: Fallback feature
|
|
Description: support attr/method of builtin type.
|
|
Expectation: No exception.
|
|
"""
|
|
@ms_function
|
|
def list_insert():
|
|
x = list([1, 3, 4])
|
|
x.insert(-5, 2)
|
|
return Tensor(x)
|
|
assert np.all(list_insert().asnumpy() == np.array([2, 1, 3, 4]))
|
|
|
|
|
|
@ms_function
|
|
def np_fallback_func_tensor_index(x):
|
|
array_x = tuple([2, 3, 4, 5])
|
|
np_x = np.array(array_x).astype(np.float32)
|
|
me_x = Tensor(np_x)
|
|
me_x = me_x + me_x
|
|
return me_x[x]
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_np_fallback_func_tensor_index():
|
|
"""
|
|
Feature: Fallback feature: support Tensor index.
|
|
Description: Fallback feature: support Tensor index.
|
|
Expectation: Fallback feature: support Tensor index.
|
|
"""
|
|
x = Tensor(1, mstype.int32)
|
|
output = np_fallback_func_tensor_index(x)
|
|
output_expect = Tensor(6, mstype.float32)
|
|
assert output == output_expect
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_np_calculate():
|
|
"""
|
|
Feature: Fallback feature.
|
|
Description: Support numpy calculation.
|
|
Expectation: No exception.
|
|
"""
|
|
@ms_function
|
|
def np_calculate():
|
|
x = np.array([3, 1, 2, 4, 5])
|
|
y = x % 2
|
|
z = Tensor(y)
|
|
return z
|
|
assert np.all(np_calculate().asnumpy() == np.array([1, 1, 0, 0, 1]))
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_fallback_tensor_array_astype():
|
|
"""
|
|
Feature: JIT Fallback
|
|
Description: Test Tensor(array) with astype() in graph mode.
|
|
Expectation: No exception.
|
|
"""
|
|
@ms_function
|
|
def foo():
|
|
me_x = Tensor([1.1, -2.1]).astype("float32")
|
|
return me_x
|
|
print(foo())
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
def test_fallback_tuple_with_mindspore_function():
|
|
"""
|
|
Feature: JIT Fallback
|
|
Description: Test fallback when local input has tuple with mindspore function type, such as Cell, Primitive.
|
|
Expectation: No exception.
|
|
"""
|
|
def test_isinstance(a, base_type):
|
|
mro = type(a).mro()
|
|
for i in base_type:
|
|
if i in mro:
|
|
return True
|
|
return False
|
|
|
|
@ms_function
|
|
def foo():
|
|
return test_isinstance(np.array(1), (np.ndarray, nn.Cell, Primitive))
|
|
|
|
assert foo()
|