ifstream in(argv[1]);
  ofstream out(argv[2]);
  bool preserve_sparsity = argc >= 4 ? atoi(argv[3]) : false;
  int precision = argc >= 5 ? atoi(argv[4]) : 8;

  vector<tuple<int, string, int, string>> infos;
  vector<Histogram> hists;


            

Reported by FlawFinder.

                ifstream in(argv[1]);
  ofstream out(argv[2]);
  bool preserve_sparsity = argc >= 4 ? atoi(argv[3]) : false;
  int precision = argc >= 5 ? atoi(argv[4]) : 8;

  vector<tuple<int, string, int, string>> infos;
  vector<Histogram> hists;

  string line;

            

Reported by FlawFinder.

              import argparse
import torch

if __name__ == '__main__':
    parser = argparse.ArgumentParser()

    # Required args. Raises error if they aren't passed.
    parser.add_argument('--foo', help='foo', required=True)
    parser.add_argument('--bar', help='bar', required=True)

            

Reported by Pylint.

              import argparse
import torch

if __name__ == '__main__':
    parser = argparse.ArgumentParser()

    # Required args. Raises error if they aren't passed.
    parser.add_argument('--foo', help='foo', required=True)
    parser.add_argument('--bar', help='bar', required=True)

            

Reported by Pylint.

              
#ifdef TORCH_ENABLE_LLVM

TEST(Conv, DepthwiseConv2D) {
  te::KernelScope kernel_scope;
  constexpr int N = 1, C = 72, H = 56, W = 56;
  constexpr int K = 72, R = 3, S = 3;
  constexpr int kPad = 1, kStride = 2, kGroups = C;
  constexpr int CperG = C / kGroups;

            

Reported by Cppcheck.

              
#endif

TEST(Conv, Conv2D) {
  te::KernelScope kernel_scope;

  // Input dimensions.
  constexpr int N = 1;
  constexpr int C = 3;

            

Reported by Cppcheck.

              build script to create a tailored build which only contains these used ops.
"""

import torch
import torchvision
import yaml

# Download and trace the model.
model = torchvision.models.mobilenet_v2(pretrained=True)

            

Reported by Pylint.

              """

import torch
import torchvision
import yaml

# Download and trace the model.
model = torchvision.models.mobilenet_v2(pretrained=True)
model.eval()

            

Reported by Pylint.

              
} // extern "C"

REGISTER_NNC_KERNEL("slow_mul", slow_mul_kernel)
REGISTER_NNC_KERNEL("dummy", dummy_kernel)

InputSpec create_test_input_spec(const std::vector<int64_t>& sizes) {
  InputSpec input_spec;
  input_spec.sizes_ = sizes;

            

Reported by Cppcheck.

                auto outputs = f.run(c10::impl::toList(input));
  auto output = ((const c10::IValue&) outputs[0]).toTensor();
  auto expected_output = at::ones({size}, at::kFloat).mul(a * n);
  EXPECT_TRUE(output.equal(expected_output));
}

TEST(Function, Serialization) {
  Function f;
  f.set_name("test_function");

            

Reported by FlawFinder.

              
  ifstream in(argv[1]);
  ofstream out(argv[2]);
  bool preserve_sparsity = argc >= 4 ? atoi(argv[3]) : false;
  int precision = argc >= 5 ? atoi(argv[4]) : 8;

  vector<tuple<int, string, int, string>> infos;
  vector<Histogram> hists;


            

Reported by FlawFinder.

                ifstream in(argv[1]);
  ofstream out(argv[2]);
  bool preserve_sparsity = argc >= 4 ? atoi(argv[3]) : false;
  int precision = argc >= 5 ? atoi(argv[4]) : 8;

  vector<tuple<int, string, int, string>> infos;
  vector<Histogram> hists;

  string line;

            

Reported by FlawFinder.

                ASSERT_EQ(result, expected_result);
}

TEST(RunTimeTest, Delegate) {
  std::string filePath(__FILE__);
  auto testModelFile = filePath.substr(0, filePath.find_last_of("/\\") + 1);
  // "delegate_test.ptl" is generated from test/cpp/jit/test_backend.cpp,
  // BackendTest.TestCompiler. This test is on target runtime. It has
  // model running capability, but no compilation and serialization.

            

Reported by Cppcheck.

                inputs.emplace_back(1.0 * at::ones({}));

  auto mres = mlm.forward(inputs);
  AT_ASSERT(mres.toTensor().equal(3 * at::ones({})));
}

TEST(RunTimeTest, DelegateException) {
  std::string filePath(__FILE__);
  auto testModelFile = filePath.substr(0, filePath.find_last_of("/\\") + 1);

            

Reported by FlawFinder.

                      &Y->original_tensor, filter.sizes(), at::dtype<int8_t>().device(CPU));
    auto* buffer = Y->original_tensor.template mutable_data<int8_t>();
    CAFFE_ENFORCE_EQ(Y->original_tensor.numel(), W_quantized.size());
    memcpy(buffer, W_quantized.data(), W_quantized.size() * sizeof(int8_t));
  }
  if (this->InputIsType<int8::Int8TensorCPU>(0) && quantize_channelwise_) {
    static int log_occurences = 0;
    if (log_occurences < 32) {
      ++log_occurences;

            

Reported by FlawFinder.

                      &Y->original_tensor, filter.sizes(), at::dtype<int8_t>().device(CPU));
    auto* buffer = Y->original_tensor.template mutable_data<int8_t>();
    CAFFE_ENFORCE_EQ(Y->original_tensor.numel(), W_quantized.size());
    memcpy(buffer, W_quantized.data(), W_quantized.size() * sizeof(int8_t));
  }

  if (this->InputIsType<int8::Int8TensorCPU>(FILTER) && quantize_groupwise_) {
    static int log_occurences = 0;
    if (log_occurences < 32) {

            

Reported by FlawFinder.

              #!/usr/bin/env python3

# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.

import argparse

            

Reported by Pylint.

              
    rank = int(os.environ["RANK"])

    if args.raises:
        raise RuntimeError(f"raised from {rank}")
    else:
        print(f"{args.msg} from {rank}")

            

Reported by Pylint.

              import torch

x = torch.ones((3, 3), requires_grad=True)
(3 * x).sum().backward()

            

Reported by Pylint.

              import torch

x = torch.ones((3, 3), requires_grad=True)
(3 * x).sum().backward()

            

Reported by Pylint.