op_->node_builder.Attr(attr_name, v);
    }
    return absl::OkStatus();
  }
  Status SetAttrFloatList(const char* attr_name, const float* values,
                          int num_values) override {
    op_->node_builder.Attr(attr_name,
                           ArraySlice<const float>(values, num_values));
    return absl::OkStatus();
  }
  Status SetAttrIntList(const char* attr_name, const int64_t* values,

        "//tensorflow/c/experimental/ops:nn_ops",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
        "//tensorflow/core/platform:tensor_float_32_utils",
    ] + if_libtpu(
        if_false = ["//tensorflow/compiler/mlir/tensorflow/c:mlir_c_api_registration"],
        if_true = [],
    ),
)

tf_cuda_cc_test(
    name = "math_grad_test",

                     float value) {
  desc->node_builder.Attr(attr_name, value);
}

void TF_SetAttrFloatList(TF_OperationDescription* desc, const char* attr_name,
                         const float* values, int num_values) {
  desc->node_builder.Attr(attr_name,
                          ArraySlice<const float>(values, num_values));
}

      "        name: 'sum'"
      "        type: DT_FLOAT"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read0'"
      "      op: 'ReadVariableOp'"
      "      input: 'var'"
      "      device: '/job:localhost/replica:0/task:0/device:CPU:0'"
      "      attr {"
      "        key: 'dtype'"
      "        value {"
      "          type: DT_FLOAT"
      "        }"
      "      }"
      "    }"

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

  AbstractTensorHandlePtr t;
  {
    AbstractTensorHandle* x_raw = nullptr;
    Status s = TestScalarTensorHandle<float, TF_FLOAT>(ctx.get(), 1.0f, &x_raw);
    ASSERT_EQ(errors::OK, s.code()) << s.message();
    t.reset(x_raw);
  }

  AbstractOperationPtr check_numerics_op(ctx->CreateOperation());
  ForwardOperation forward_op;

          i_vector.push_back(default_value.list().i(i));
        }
        TFE_OpSetAttrIntList(op, attr_name, i_vector.data(), i_size);
      }
      // Float
      if (const int f_size = default_value.list().f_size()) {
        absl::InlinedVector<float, 4> f_vector;
        f_vector.reserve(f_size);
        for (int i = 0; i < f_size; ++i) {
          f_vector.push_back(default_value.list().f(i));
        }

        "//tensorflow/c:tf_tensor_internal",
        "//tensorflow/c/experimental/ops",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
        "//tensorflow/core/platform:tensor_float_32_utils",
        "@com_google_absl//absl/types:span",
    ],
)

cc_library(
    name = "abstract_tensor_handle",
    srcs = ["abstract_tensor_handle.cc"],
    hdrs = ["abstract_tensor_handle.h"],

* `tf.config.experimental.enable_tensor_float_32_execution`

          tf_additional_profiler_deps()) + if_xla_available([
        "//tensorflow/compiler/aot:tfcompile_lib",
    ]) + if_static(extra_deps = [
        "//tensorflow/core/platform:tensor_float_32_utils",
        "//tensorflow/core/platform:enable_tf2_utils",
    ]) + if_oss([
        "//tensorflow/core/distributed_runtime/rpc:grpc_server_lib",
        "//tensorflow/core/distributed_runtime/rpc:grpc_session",

limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/c_api_unified_experimental.h"

#include <vector>

#include "absl/container/flat_hash_map.h"
#include "absl/strings/str_cat.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"