import copy
import torch
import numpy as np
import torch_npu
from torch_npu.testing.testcase import TestCase, run_tests
class TestTan(TestCase):
def generate_single_data(self, min_d, max_d, shape, dtype):
input1 = np.random.uniform(min_d, max_d, shape).astype(dtype)
npu_input1 = torch.from_numpy(input1)
return npu_input1
def cpu_op_exec(self, input1):
output = torch.atan(input1)
output = output.numpy()
return output
def cpu_op_exec_out(self, input1, input2):
torch.atan(input1, out=input2)
output = input2.numpy()
return output
def cpu_op_exec_self(self, input1):
torch.atan_(input1)
output = input1.numpy()
return output
def npu_op_exec(self, input1):
input1 = input1.to("npu")
output = torch.atan(input1)
output = output.to("cpu")
output = output.numpy()
return output
def npu_op_exec_out(self, input1, input2):
input1 = input1.to("npu")
output = input2.to("npu")
torch.atan(input1, out=output)
output = output.to("cpu")
output = output.numpy()
return output
def npu_op_exec_self(self, input1):
input1 = input1.to("npu")
torch.atan_(input1)
output = input1.to("cpu")
output = output.numpy()
return output
def test_atan_float32(self):
input1 = self.generate_single_data(-1, 1, (1, 3), np.float32)
cpu_output = self.cpu_op_exec(input1)
npu_output = self.npu_op_exec(input1)
self.assertRtolEqual(cpu_output, npu_output)
def test_atan_out_float32(self):
input1 = self.generate_single_data(-1, 1, (1, 3), np.float32)
input2 = self.generate_single_data(-1, 1, (1, 3), np.float32)
cpu_output = self.cpu_op_exec_out(input1, input2)
npu_output = self.npu_op_exec_out(input1, input2)
self.assertRtolEqual(cpu_output, npu_output)
def test_atan_self_float32(self):
input1 = self.generate_single_data(-1, 1, (1, 3), np.float32)
input2 = copy.deepcopy(input1)
cpu_output = self.cpu_op_exec_self(input1)
npu_output = self.npu_op_exec_self(input2)
self.assertRtolEqual(cpu_output, npu_output)
if __name__ == "__main__":
run_tests()