// Prepare some tensors for shape.
  TF_Tensor* tensor_1X6 = Int32Tensor({1, 6});
  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);
  TF_Tensor* tensor_1X1X6 = Int32Tensor({1, 1, 6});
  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);

  TFE_Op* reshape_op = TFE_NewOp(tfe_context_, "Reshape", status_);
  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);
  TFE_OpSetAttrType(reshape_op, "T", TF_FLOAT);

*   Fixes a `CHECK` fail in `AudioSummaryV2` ([CVE-2022-35995](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-35995))
*   Fixes a `CHECK` fail in `CollectiveGather` ([CVE-2022-35994](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-35994))
*   Fixes a `CHECK` fail in `SetSize` ([CVE-2022-35993](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-35993))

  # list all .whl files by their modification time (ls -t) and delete anything
  # other than the most recently-modified one (the new one).
  ls -t *.whl | tail -n +2 | xargs rm
fi

# Check if size is too big. TFCI_WHL_SIZE_LIMIT is in find's format, which can be
# 'k' for kilobytes, 'M' for megabytes, or 'G' for gigabytes, and the + to indicate
# "anything greater than" is added by the script.

#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

using ::tensorflow::string;

string MatMulFunction(const string& matmul_device) {
  tensorflow::FunctionDef def;
  CHECK(tensorflow::protobuf::TextFormat::ParseFromString(
      absl::StrCat("    signature {"
                   "      name: 'MatMulFunction'"
                   "      input_arg {"
                   "        name: 'a'"

# Writes the list of tests that would be run from BAZEL_TEST_COMMAND to OUTPUT.
# Hides all extra output and always exits with success for now.

OUTPUT=$1
shift

    ],
)

tf_cuda_cc_test(
    name = "gradients_test",
    size = "small",
    srcs = [
        "gradients_test.cc",
    ],
    args = ["--heap_check="],
    tags = tf_cuda_tests_tags() + ["nomac"],
    deps = [
        ":abstract_context",
        ":abstract_tensor_handle",
        ":c_api_experimental",
        ":c_api_test_util",

            type=registry,ref=gcr.io/tensorflow-sigs/build:${{ github.event.number }}-${{ matrix.python-version }}
          cache-to: type=inline
      -
        name: Add a comment with the pushed containers
        uses: mshick/add-pr-comment@a65df5f64fc741e91c59b8359a4bc56e57aaf5b1 # v2
        if: contains(github.event.pull_request.labels.*.name, 'build and push to gcr.io for staging')
        with:
          repo-token: ${{ secrets.GITHUB_TOKEN }}

                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    // TODO(b/161805092): Support broadcasting.

    DCHECK(grad_outputs[0]);
    grad_inputs[0] = grad_outputs[0];
    grad_inputs[1] = grad_outputs[0];

    grad_inputs[0]->Ref();
    grad_inputs[1]->Ref();
    return absl::OkStatus();
  }

  }

  tensorflow::Status Shape(
      tensorflow::PartialTensorShape* shape) const override {
    DCHECK(shape != nullptr);
    TF_Status status;
    int num_dims = TF_GraphGetTensorNumDims(graph_, output_, &status);
    DCHECK_GE(num_dims, -1);
    TF_RETURN_IF_ERROR(StatusFromTF_Status(&status));
    if (num_dims == kUnknownRank) {
      return absl::OkStatus();
    }

#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace {

// Specification for expected input/output and its type.
// DataType value of DT_INVALID signifies that we don't want to
// check the data type.
typedef std::pair<string, DataType> IOSpec;

const char* kFeedStackToString = "File \"feed.cc\", line 10, in alpha";
const char* kNegStackToString = "File \"neg.cc\", line 15, in beta";