# Note: this is excluded on the full code base, since any submitted code must
# have passed Google's internal style guidelines.
@test "Check pylint for Python files" {
    echo "Python formatting is recommended. Here are the pylint errors:"
    echo "============================="
    grep -e "\.py$" $BATS_FILE_TMPDIR/changed_files > $BATS_TEST_TMPDIR/files || true
    if [[ ! -s $BATS_TEST_TMPDIR/files ]]; then return 0; fi

  EXPECT_EQ(out.size(), 1);
  // Now read the first block; this should yield an INTERNAL error because we
  // had already cached a partial block at a later position.
  Status status = ReadCache(&cache, "", 0, block_size, &out);
  EXPECT_EQ(status.code(), error::INTERNAL);
}

TEST(RamFileBlockCacheTest, LRU) {
  const size_t block_size = 16;
  std::list<size_t> calls;

build --copt="-mtune=generic" --copt="-march=armv8-a" --copt="-O3"

# Test-related settings below this point.
test --build_tests_only --keep_going --test_output=errors --verbose_failures=true
test --test_timeout=500,900,-1,-1
# Give only the list of failed tests at the end of the log
test --test_summary=short

# "nonpip" tests are regular py_test tests.

#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/test.h"

using tensorflow::Status;
using tensorflow::string;
using tensorflow::TF_StatusPtr;

namespace tensorflow {

//  --test_arg=--scheme= --test_arg=--scheme=file
//
// Note that to test the local filesystem we use an empty value.

namespace tensorflow {
namespace {

using ::tensorflow::error::Code;

// As we need to test multiple URI schemes we need a parameterized test.
// Furthermore, since each test creates and deletes files, we will use the same

    // TODO(b/168850692): Fix this.
    return errors::Unimplemented(
        "BroadcastMul is not supported in tracing mode yet.");
  }
  auto imm_ctx = dyn_cast<ImmediateExecutionContext>(ctx);
  AbstractTensorPtr minus_1(imm_ctx->CreateInt32Scalar(-1));
  ImmediateTensorHandlePtr dim(imm_ctx->CreateLocalHandle(minus_1.get()));
  AbstractTensorHandle* expand_dims_outputs;
  TF_RETURN_IF_ERROR(

      "' (available: ");
  // Ensure deterministic (sorted) order in the error message
  std::set<string> factories_sorted;
  for (const auto& factory : GetFactories())
    factories_sorted.insert(factory.first);
  const char* comma = "";
  for (const string& factory : factories_sorted) {
    msg += comma + factory;
    comma = ", ";
  }
  msg += ")";

  return errors::InvalidArgument(msg.c_str());
}

  }
  registry_.insert({op_name, gradient_function_factory});
  return absl::OkStatus();
}
Status GradientRegistry::Lookup(
    const ForwardOperation& op,
    std::unique_ptr<GradientFunction>* gradient_function) const {
  auto iter = registry_.find(op.op_name);
  if (iter == registry_.end()) {
    const string error_msg = "No gradient defined for op: " + op.op_name + ".";
    return errors::NotFound(error_msg);

        if [[ ! -f $target ]] && [[ ! -d $target ]]; then
            echo "$i" >> errors.txt
        fi
        if [[ -e errors.txt ]]; then
            echo "Broken links found:"
            cat errors.txt
            rm errors.txt
            false
        fi
    done
}

@test "No duplicate files on Windows" {
    cat <<EOF

using tensorflow::string;
using tensorflow::Tensor;
using tensorflow::TensorId;
using tensorflow::TensorShapeProto;
using tensorflow::VersionDef;
using tensorflow::errors::FailedPrecondition;
using tensorflow::errors::InvalidArgument;
using tensorflow::errors::OutOfRange;
using tensorflow::gtl::ArraySlice;
using tensorflow::strings::StrCat;

extern "C" {