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 TestExp(TestCase):
def cpu_op_exec(self, input1):
output = torch.exp(input1)
output = output.numpy()
return output
def npu_op_exec(self, input1):
output = torch.exp(input1)
output = output.to("cpu")
output = output.numpy()
return output
def test_exp_shape_format_fp16(self):
format_list = [0, 3]
shape_list = [[5], [2, 4], [2, 2, 4], [2, 3, 3, 4]]
shape_format = [
[np.float16, i, j] for i in format_list for j in shape_list
]
for item in shape_format:
cpu_input, npu_input = create_common_tensor(item, -1, 1)
cpu_input = cpu_input.to(torch.float32)
cpu_output = self.cpu_op_exec(cpu_input)
npu_output = self.npu_op_exec(npu_input)
cpu_output = cpu_output.astype(npu_output.dtype)
self.assertRtolEqual(cpu_output, npu_output)
def test_exp_shape_format_fp32(self):
format_list = [0, 3]
shape_list = [[5], [2, 4], [2, 2, 4], [2, 3, 3, 4]]
shape_format = [
[np.float32, i, j] for i in format_list for j in shape_list
]
for item in shape_format:
cpu_input, npu_input = create_common_tensor(item, -1, 1)
cpu_output = self.cpu_op_exec(cpu_input)
npu_output = self.npu_op_exec(npu_input)
self.assertRtolEqual(cpu_output, npu_output)
if __name__ == "__main__":
run_tests()