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import pytest

import triton
import triton.language as tl
import triton.language.extra.ascend.libdevice as libdevice
import test_common

import torch
import torch_npu

@triton.jit
def triton_acos(in_ptr0, out_ptr0, XBLOCK : tl.constexpr, XBLOCK_SUB : tl.constexpr):
    offset = tl.program_id(0) * XBLOCK
    base1 = tl.arange(0, XBLOCK_SUB)
    loops1: tl.constexpr = XBLOCK // XBLOCK_SUB
    for loop1 in range(loops1):
        x0 = offset + (loop1 * XBLOCK_SUB) + base1
        tmp0 = tl.load(in_ptr0 + (x0), None)
        tmp1 = libdevice.acos(tmp0)
        tl.store(out_ptr0 + (x0), tmp1, None)


@pytest.mark.parametrize('param_list',
                            [
                                'float32',
                                'float16',
                                'bfloat16'
                            ])
def test_asinh_special(param_list):
    dtype = param_list
    x0 = torch.linspace(-1.0 + 1e-6, 1.0 - 1e-6, 256, dtype=eval("torch."+dtype)).npu()
    
    y_ref = torch.acos(x0)
    y_cal = torch.zeros_like(y_ref)
    triton_acos[1, 1, 1](x0, y_cal, x0.shape[0], x0.shape[0])
    bf16_tolerance = 1.0 / 128
    if dtype == 'bfloat16':
        torch.testing.assert_close(y_ref, y_cal, rtol=bf16_tolerance, atol=bf16_tolerance)
    else:
        torch.testing.assert_close(y_ref, y_cal, rtol=1e-3, atol=1e-3)