# Copyright (c) Huawei Technologies Co., Ltd. 2025. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.


import pytest

import triton
import triton.language as tl
import time
import torch
import torch_npu
import test_common
def torch_clamp_float(x0):
    res = torch.clamp(x0, 0.0, 100.0)
    return res

@triton.jit
def triton_clamp_float(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 = tl.clamp(tmp0, 0.0, 100.0)
        tl.store(out_ptr0 + (x0), tmp1, None)

@pytest.mark.parametrize('param_list',
                         [
                             # int原生不支持
                             ['float16', (4, 4), 4, 4, 4],
                             ['float32', (4, 4), 4, 4, 4],
                         ])
def test_clamp(param_list):
    dtype, shape, ncore, xblock, xblock_sub = param_list
    x0 = test_common.generate_tensor(shape, dtype)
    y_ref = torch_clamp_float(x0)
    tyname = test_common.get_triton_sig_typename(dtype)
    
    y_cal = torch.zeros(shape, dtype = eval('torch.' + dtype)).npu()
    x0 = x0.npu()
    triton_clamp_float[ncore, 1, 1](x0, y_cal, xblock, xblock_sub,  debug=True)
    test_common.validate_cmp(dtype, y_cal, y_ref)