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 TestErfc(TestCase):
def get_shapeFormat(self):
shape_format = [
[np.float32, 0, (4, 3, 10, 9)],
[np.float32, -1, (2, 4, 3)],
[np.float32, 3, (20, 13)],
[np.float32, 4, (20, 13)],
[np.float32, 2, (100, 50)],
[np.float32, 30, (20, 13, 10, 15, 20)]
]
return shape_format
def cpu_op_exec(self, input1):
output = torch.erfc(input1)
output = output.numpy()
return output
def npu_op_exec(self, input1):
output = torch.erfc(input1)
output = output.to("cpu")
output = output.numpy()
return output
def cpu_op_exec_(self, input1):
torch.erfc_(input1)
output = input1.numpy()
return output
def npu_op_exec_(self, input1):
torch.erfc_(input1)
output = input1.to("cpu")
output = output.numpy()
return output
def cpu_op_exec_out(self, input1, cpu_out):
torch.erfc(input1, out=cpu_out)
output = cpu_out.numpy()
return output
def npu_op_exec_out(self, input1, npu_out):
torch.erfc(input1, out=npu_out)
output = npu_out.to("cpu")
output = output.numpy()
return output
def test_erfc_float32_common_shape_format(self):
shape_format = self.get_shapeFormat()
for item in shape_format:
cpu_input1, npu_input1 = create_common_tensor(item, 1, 100)
cpu_output = self.cpu_op_exec(cpu_input1)
npu_output = self.npu_op_exec(npu_input1)
self.assertRtolEqual(cpu_output, npu_output)
def test_erfc_float16_common_shape_format(self):
shape_format = self.get_shapeFormat()
for item in shape_format:
cpu_input1, npu_input1 = create_common_tensor(item, 1, 100)
cpu_input1 = cpu_input1.to(torch.float32)
cpu_output = self.cpu_op_exec(cpu_input1)
npu_output = self.npu_op_exec(npu_input1)
cpu_output = cpu_output.astype(npu_output.dtype)
self.assertRtolEqual(cpu_output, npu_output)
def test_erfc_float321_common_shape_format(self):
shape_format = self.get_shapeFormat()
for item in shape_format:
cpu_input1, npu_input1 = create_common_tensor(item, 1, 100)
cpu_output = self.cpu_op_exec_(cpu_input1)
npu_output = self.npu_op_exec_(npu_input1)
self.assertRtolEqual(cpu_output, npu_output)
def test_erfc_float161_common_shape_format(self):
shape_format = self.get_shapeFormat()
for item in shape_format:
cpu_input1, npu_input1 = create_common_tensor(item, 1, 100)
cpu_input1 = cpu_input1.to(torch.float32)
cpu_output = self.cpu_op_exec_(cpu_input1)
npu_output = self.npu_op_exec_(npu_input1)
cpu_output = cpu_output.astype(npu_output.dtype)
self.assertRtolEqual(cpu_output, npu_output)
def test_erfc_out_float32_common_shape_format(self):
shape_format = self.get_shapeFormat()
for item in shape_format:
cpu_input1, npu_input1 = create_common_tensor(item, 1, 100)
cpu_out, npu_out = create_common_tensor(item, 1, 100)
cpu_output = self.cpu_op_exec_out(cpu_input1, cpu_out)
npu_output = self.npu_op_exec_out(npu_input1, npu_out)
self.assertRtolEqual(cpu_output, npu_output)
def test_erfc_out_float16_common_shape_format(self):
shape_format = self.get_shapeFormat()
for item in shape_format:
cpu_input1, npu_input1 = create_common_tensor(item, 1, 100)
cpu_input1 = cpu_input1.to(torch.float32)
cpu_out, npu_out = create_common_tensor(item, 1, 100)
cpu_out = cpu_out.to(torch.float32)
cpu_output = self.cpu_op_exec_out(cpu_input1, cpu_out)
npu_output = self.npu_op_exec_out(npu_input1, npu_out)
cpu_output = cpu_output.astype(npu_output.dtype)
self.assertRtolEqual(cpu_output, npu_output)
if __name__ == "__main__":
run_tests()