import copy
import torch
import numpy as np
import torch_npu
from torch_npu.testing.testcase import TestCase, run_tests
from torch_npu.testing.common_utils import create_common_tensor
class Test__Or__(TestCase):
def cpu_op_exec(self, input1, input2):
output = input1.__or__(input2)
if output.dtype != torch.int32:
output = output.to(torch.int32)
return output.numpy()
def npu_op_exec(self, input1, input2):
output = input1.__or__(input2)
output = output.to("cpu")
if output.dtype != torch.int32:
output = output.to(torch.int32)
return output.numpy()
def test___Or___shape_format(self, device="npu"):
shape_format = [
[[np.int32, 0, [256, 1000]], [1]],
[[np.int32, 0, [256, 1000]], [np.int32, 0, [256, 1000]]],
[[np.int16, 0, [256, 1000]], [2]],
[[np.int16, 0, [256, 1000]], [np.int16, 0, [256, 1000]]],
[[np.int8, 0, [256, 1000]], [3]],
[[np.int8, 0, [256, 1000]], [np.int8, 0, [256, 1000]]],
]
for item in shape_format:
if len(item[1]) > 1:
cpu_input1, npu_input1 = create_common_tensor(item[0], 0, 100)
cpu_input2, npu_input2 = create_common_tensor(item[1], 0, 100)
cpu_output = self.cpu_op_exec(cpu_input1, cpu_input2)
npu_output = self.npu_op_exec(npu_input1, npu_input2)
self.assertRtolEqual(cpu_output, npu_output)
else:
cpu_input1, npu_input1 = create_common_tensor(item[0], 0, 100)
cpu_output = self.cpu_op_exec(cpu_input1, item[1][0])
npu_output = self.npu_op_exec(npu_input1, item[1][0])
self.assertRtolEqual(cpu_output, npu_output)
cpu_input1 = torch.tensor([True, False, True, False, True], dtype=torch.bool)
npu_input1 = torch.tensor(
[True, False, True, False, True], dtype=torch.bool, device="npu"
)
cpu_input2 = torch.tensor([True, False, True, False, False], dtype=torch.bool)
npu_input2 = torch.tensor(
[True, False, True, False, False], dtype=torch.bool, device="npu"
)
cpu_output = self.cpu_op_exec(cpu_input1, cpu_input2)
npu_output = self.npu_op_exec(npu_input1, npu_input2)
self.assertRtolEqual(cpu_output, npu_output)
if __name__ == "__main__":
run_tests()