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 TestSign(TestCase):
def cpu_op_exec(self, input1):
cpu_output = torch.sign(input1)
cpu_output = cpu_output.numpy()
return cpu_output
def npu_op_exec(self, input1):
output = torch.sign(input1)
output = output.to("cpu")
output = output.numpy()
return output
def npu_op_exec_out(self, input1, input2):
torch.sign(input1, out=input2)
output = input2.to("cpu")
output = output.numpy()
return output
def cpu_inp_op_exec(self, input1):
input1.sign_()
output = input1.numpy()
return output
def npu_inp_op_exec(self, input1):
input1.sign_()
output = input1.to("cpu")
output = output.numpy()
return output
def sign_result(self, shape_format):
for item in shape_format:
cpu_input1, npu_input1 = create_common_tensor(item, -100, 100)
cpu_input2, npu_input2 = create_common_tensor(item, -100, 100)
if cpu_input1.dtype == torch.float16:
cpu_input1 = cpu_input1.to(torch.float32)
cpu_output = self.cpu_op_exec(cpu_input1)
npu_output = self.npu_op_exec(npu_input1)
npu_output_out = self.npu_op_exec_out(npu_input1, npu_input2)
cpu_output_inp = self.cpu_inp_op_exec(cpu_input1)
npu_output_inp = self.npu_inp_op_exec(npu_input1)
cpu_output = cpu_output.astype(npu_output.dtype)
cpu_output_inp = cpu_output_inp.astype(npu_output_inp.dtype)
self.assertRtolEqual(cpu_output, npu_output)
self.assertRtolEqual(cpu_output, npu_output_out)
self.assertRtolEqual(cpu_output_inp, npu_output_inp)
def test_sign_shape_format_fp16_1d(self):
format_list = [0, 3]
shape_format = [[np.float16, i, [18]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_fp16_2d(self):
format_list = [0, 3, 29]
shape_format = [[np.float16, i, [5, 256]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_fp16_3d(self):
format_list = [0, 3, 29]
shape_format = [[np.float16, i, [32, 3, 3]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_fp16_4d(self):
format_list = [0, 3, 29]
shape_format = [[np.float16, i, [64, 112, 7, 7]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_fp32_1d(self):
format_list = [0, 3]
shape_format = [[np.float32, i, [18]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_fp32_2d(self):
format_list = [0, 3, 29]
shape_format = [[np.float32, i, [5, 256]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_fp32_3d(self):
format_list = [0, 3, 29]
shape_format = [[np.float32, i, [32, 3, 3]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_fp32_4d(self):
format_list = [0, 3, 29]
shape_format = [[np.float32, i, [64, 112, 7, 7]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_int32_1d(self):
format_list = [0]
shape_format = [[np.int32, i, [18]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_int32_2d(self):
format_list = [0]
shape_format = [[np.int32, i, [5, 256]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_int32_3d(self):
format_list = [0]
shape_format = [[np.int32, i, [32, 3, 3]] for i in format_list]
self.sign_result(shape_format)
def test_sign_shape_format_int32_4d(self):
format_list = [0]
shape_format = [[np.int32, i, [64, 112, 7, 7]] for i in format_list]
self.sign_result(shape_format)
if __name__ == "__main__":
run_tests()