DLTensor* dltensor_in = &dlm_in.dl_tensor;
  dltensor_in->data = data.data();
  dltensor_in->device = {kDLCPU, 0};
  dltensor_in->ndim = static_cast<int32_t>(shape.size());
  dltensor_in->dtype = {kDLFloat, 32, 1};
  dltensor_in->shape = shape.data();
  dltensor_in->strides = strides.data();
  TFE_TensorHandle* handle = TFE_HandleFromDLPack(&dlm_in, status, ctx);
  ASSERT_NE(handle, nullptr)

      immediate_execution_ctx_.reset(ctx_raw);
    }

    // Computing numerical gradients with TensorFloat-32 is numerically
    // unstable. Some forward pass tests also fail with TensorFloat-32 due to
    // low tolerances
    enable_tensor_float_32_execution(false);
  }

  AbstractContextPtr immediate_execution_ctx_;
  GradientRegistry registry_;
  Status status_;

 public:

  char* dst = buffer;
  int64_t read = 0;

  while (n > 0) {
    // Some platforms, notably macs, throw `EINVAL` if `pread` is asked to read
    // more than fits in a 32-bit integer.
    size_t requested_read_length;
    if (n > INT32_MAX)
      requested_read_length = INT32_MAX;
    else
      requested_read_length = n;

      immediate_execution_ctx_.reset(ctx_raw);
    }

    // Computing numerical gradients with TensorFloat-32 is numerically
    // unstable. Some forward pass tests also fail with TensorFloat-32 due to
    // low tolerances
    enable_tensor_float_32_execution(false);
  }

  AbstractContextPtr immediate_execution_ctx_;
  GradientRegistry registry_;
  Status status_;

 public:

  };
  tf_gcs_filesystem::RamFileBlockCache cache1(0, 0, 0, fetcher);
  tf_gcs_filesystem::RamFileBlockCache cache2(16, 0, 0, fetcher);
  tf_gcs_filesystem::RamFileBlockCache cache3(0, 32, 0, fetcher);
  tf_gcs_filesystem::RamFileBlockCache cache4(16, 32, 0, fetcher);

  EXPECT_FALSE(cache1.IsCacheEnabled());
  EXPECT_FALSE(cache2.IsCacheEnabled());
  EXPECT_FALSE(cache3.IsCacheEnabled());
  EXPECT_TRUE(cache4.IsCacheEnabled());
}

      immediate_execution_ctx_.reset(ctx_raw);
    }

    // Computing numerical gradients with TensorFloat-32 is numerically
    // unstable. Some forward pass tests also fail with TensorFloat-32 due to
    // low tolerances
    enable_tensor_float_32_execution(false);
  }

  AbstractContextPtr immediate_execution_ctx_;
  GradientRegistry registry_;
  Status status_;

 public:

        case 8:
          *tf_dtype = TF_DataType::TF_UINT8;
          return absl::OkStatus();
        case 16:
          *tf_dtype = TF_DataType::TF_UINT16;
          return absl::OkStatus();
        case 32:
          *tf_dtype = TF_DataType::TF_UINT32;
          return absl::OkStatus();
        case 64:
          *tf_dtype = TF_DataType::TF_UINT64;
          return absl::OkStatus();
        default:

      ASSERT_EQ(errors::OK, s.code()) << s.message();
      ctx_.reset(ctx_raw);
    }

    // Computing numerical gradients with TensorFloat-32 is numerically
    // unstable. Some forward pass tests also fail with TensorFloat-32 due to
    // low tolerances
    enable_tensor_float_32_execution(false);
  }

  AbstractContextPtr ctx_;

 public:
  bool UseMlir() const { return strcmp(std::get<0>(GetParam()), "mlir") == 0; }