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 TestSin(TestCase):
def cpu_op_exec(self, input1):
output = torch.sin(input1)
output = output.numpy()
return output
def npu_op_exec(self, input1):
output = torch.sin(input1)
output = output.to("cpu")
output = output.numpy()
return output
def npu_op_exec_out(self, input1, input2):
torch.sin(input1, out=input2)
output = input2.to("cpu")
output = output.numpy()
return output
def test_sin_common_shape_format(self):
shape_format = [
[[np.float32, 0, (5, 3)]],
]
for item in shape_format:
cpu_input1, npu_input1 = create_common_tensor(item[0], -10, 10)
cpu_output = self.cpu_op_exec(cpu_input1)
npu_output = self.npu_op_exec(npu_input1)
self.assertRtolEqual(cpu_output, npu_output)
def test_sin_out_common_shape_format(self):
shape_format = [
[[np.float16, -1, (4, 3, 128, 128)], [np.float16, -1, (4, 3, 128, 128)]],
[[np.float16, 0, (4, 3, 128, 128)], [np.float16, 0, (10, 3, 64, 128)]],
[[np.float16, 0, (4, 3, 128, 128)], [np.float16, 0, (2, 3, 256, 128)]],
[[np.float32, 0, (4, 3, 128, 128)], [np.float32, 0, (4, 3, 128, 128)]],
[[np.float32, 0, (4, 3, 128, 128)], [np.float32, 0, (8, 3, 64, 128)]],
[[np.float32, -1, (4, 3, 128, 128)], [np.float32, -1, (4, 3, 256, 64)]],
]
for item in shape_format:
cpu_input1, npu_input1 = create_common_tensor(item[0], -10, 10)
cpu_input2, npu_input2 = create_common_tensor(item[0], -10, 10)
cpu_input3, npu_input3 = create_common_tensor(item[1], -10, 10)
if cpu_input1.dtype == torch.float16:
cpu_input1 = cpu_input1.to(torch.float32)
cpu_output = self.cpu_op_exec(cpu_input1)
npu_output_out1 = self.npu_op_exec_out(npu_input1, npu_input2)
npu_output_out2 = self.npu_op_exec_out(npu_input1, npu_input3)
cpu_output = cpu_output.astype(npu_output_out1.dtype)
self.assertRtolEqual(cpu_output, npu_output_out1)
self.assertRtolEqual(cpu_output, npu_output_out2)
if __name__ == "__main__":
run_tests()