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 TestLog1p(TestCase):
def cpu_op_exec(self, input1):
output = torch.log1p(input1)
output = output.numpy()
return output
def npu_op_exec(self, input1):
output = torch.log1p(input1)
output = output.to("cpu")
output = output.numpy()
return output
def cpu_op_exec_(self, input1):
input1.log1p_()
input1 = input1.numpy()
return input1
def npu_op_exec_(self, input1):
input1.log1p_()
input1 = input1.to("cpu")
input1 = input1.numpy()
return input1
def cpu_op_exec_fp16(self, input1):
input1 = input1.to(torch.float32)
output = torch.log1p(input1)
output = output.numpy()
output = output.astype(np.float16)
return output
def test_log1p_common_shape_format(self):
shape_format = [
[[np.float32, 0, 1]],
[[np.float32, 0, (64, 10)]],
[[np.float32, 4, (32, 1, 3, 3)]],
[[np.float32, 29, (10, 128)]]
]
for item in shape_format:
cpu_input, npu_input = create_common_tensor(item[0], -1, 1)
cpu_output = self.cpu_op_exec(cpu_input)
npu_output = self.npu_op_exec(npu_input)
cpu_output1 = self.cpu_op_exec_(cpu_input)
npu_output1 = self.npu_op_exec_(npu_input)
self.assertRtolEqual(cpu_output, npu_output)
self.assertRtolEqual(cpu_output1, npu_output1)
def test_log1p_float16_shape_format(self):
shape_format = [
[[np.float16, -1, 1]],
[[np.float16, -1, (64, 10)]],
[[np.float16, -1, (31, 1, 3)]]
]
for item in shape_format:
cpu_input, npu_input = create_common_tensor(item[0], -1, 1)
cpu_output = self.cpu_op_exec_fp16(cpu_input)
npu_output = self.npu_op_exec(npu_input)
self.assertRtolEqual(cpu_output, npu_output)
if __name__ == "__main__":
np.random.seed(100)
run_tests()