represent, as a whole, an original work of authorship. For the purposes
      of this License, Derivative Works shall not include works that remain
      separable from, or merely link (or bind by name) to the interfaces of,
      the Work and Derivative Works thereof.

      "Contribution" shall mean any work of authorship, including
      the original version of the Work and any modifications or additions

  * If you work for a company that wants to allow you to contribute your work, then you'll need to sign a [corporate CLA](https://code.google.com/legal/corporate-cla-v1.0.html).

    TF_SetStatus(status, TF_OK, "");
    return n;
  };
  std::vector<char> out;
  std::unique_ptr<NowSecondsEnv> env(new NowSecondsEnv);
  // Create a cache with max staleness of 2 seconds, and verify that it works as
  // expected.
  tf_gcs_filesystem::RamFileBlockCache cache1(
      8, 16, 2 /* max staleness */, fetcher,
      [&env]() { return env->NowSeconds(); });
  // Execute the first read to load the block.

    forward_op_->outputs.push_back(retvals[i]);
  }
  // TODO(b/166669239): This is needed to support AttrBuilder::Get for string
  // attributes. Number type attrs and DataType attrs work fine without this.
  // Consider getting rid of this and making the behavior between number types
  // and string consistent.
  forward_op_->attrs.BuildNodeDef();
  std::unique_ptr<GradientFunction> gradient_fn;

      immediate_execution_ctx_.get(), {x.get()}, UseFunction()));
}

TEST_P(CppGradients, TestMatMulGrad) {
  // TODO(vnvo2409): Figure out why `gradient_checker` does not work very
  // well with `MatMul` and remove `TestMatMul*` in
  // `mnist_gradients_test` when done.
  GTEST_SKIP();

  float A_vals[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f};
  int64_t A_dims[] = {3, 3};

  EXPECT_EQ(TF_GetCode(status.get()), TF_INVALID_ARGUMENT);
  EXPECT_THAT(TF_Message(status.get()), HasSubstr("assertion failed"));

  // Note that future collectives with the same context do not work at the
  // moment; once canceled, the collective executor requires the program to be
  // restarted / context to be reset.
}

TEST(PARALLEL_DEVICE_LIB, TestDifferentShapes) {

    gcloud components install docker-credential-gcr kubectl gsutil;

# Install cygwin and packages
# Running a seperate ps1 file since when running inside a Dockerfile, it does
# not work.
COPY install/install_cygwin.ps1 c:/
RUN c:/install_cygwin.ps1; \
    $old_path = [Environment]::GetEnvironmentVariable(\"PATH\", \"Machine\"); \

                             serialized_update.size(), status);
  EXPECT_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Even after the prevoiusly failed cluster update, another update and op
  // execution should work fine as long as the provided server_def is valid.
  TFE_ContextUpdateServerDef(ctx, 0, serialized.data(), serialized.size(),
                             status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

      aid = output_tensor.ZerosLike();
    } else {
      // TODO(allenl): Figure out why using zeros_like everywhere causes issues
      // for some gradient functions and if there's another way to work around
      // it (e.g. conds instead of ifs). The value shouldn't really matter.
      TF_RETURN_IF_ERROR(vspace_.BuildOnesLike(output_tensor, &aid));
    }
    if (TF_PREDICT_FALSE(aid == nullptr)) {

  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_DeleteTensorHandle(retval);

  // Custom device: inputs in same custom device works.
  matmul.reset(MatMulOp(context.get(), hcustom0.get(), hcustom0.get()));
  num_retvals = 1;
  executed = false;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());