/* Copyright 2023 Google LLC

Licensed under the Apache License, Version 2.0 (the "License");

you may not use this file except in compliance with the License.

You may obtain a copy of the License at

      http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software

distributed under the License is distributed on an "AS IS" BASIS,

WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

See the License for the specific language governing permissions and

limitations under the License.

*/

#include <stdint.h>

#include <stdio.h>

#include <stdlib.h>

#include <fuzzer/FuzzedDataProvider.h>

#include <xnnpack.h>

#include <algorithm>

#include <array>

#include <functional>

#include <iostream>

#include <limits>

extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {

  FuzzedDataProvider provider(data, size);

  xnn_status status = xnn_initialize(nullptr);

  if (status != xnn_status_success) {

    return 0;

  }

  /* Prepare a set of input arrays with fuzzer-generated data */

  alignas(16) static std::array<int8_t, 864 + XNN_EXTRA_BYTES / sizeof(int8_t)>

      w1;

  alignas(16) static std::array<int32_t, 32 + XNN_EXTRA_BYTES / sizeof(int8_t)>

      w2;

  std::generate(w1.begin(), w1.end(),

                [&]() mutable { return provider.ConsumeIntegral<uint8_t>(); });

  std::generate(w2.begin(), w2.end(),

                [&]() mutable { return provider.ConsumeIntegral<uint32_t>(); });

  xnn_operator_t op0 = nullptr;

  status = xnn_create_convolution2d_nhwc_qs8(

      0 /* top padding */, 1 /* right padding */, 1 /* bottom padding */,

      0 /* left padding */, 3 /* kernel height */, 3 /* kernel width */,

      2 /* subsampling height */, 2 /* subsampling width */,

      1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */,

      3 /* input channels per group */, 32 /* output_channels_per_group */,

      3 /* input pixel stride */, 32 /* output pixel stride */,

      -1 /* input zero point */,

      provider.ConsumeFloatingPoint<float>() /* input scale */,

      provider.ConsumeFloatingPoint<float>() /* kernel scale */, w1.data(),

      w2.data(), -1 /* output zero point */,

      provider.ConsumeFloatingPoint<float>() /* output scale */,

      -126 /* output min */, 126 /* output max */, 0 /* flags */, nullptr,

      nullptr, &op0);

  xnn_deinitialize();

  return 0;

}