// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

package multixds

// multixds knows how to target either central Istiod or all the Istiod pods on a cluster.

import (
	"context"
	"encoding/json"
	"errors"
	"fmt"
	"io"

  %0 = "tfl.dequantize"(%arg0) : (tensor<1000x1000x!quant.uniform<i8:f32, 7.812500e-03>>) -> tensor<1000x1000xf32>
  %1 = "tfl.gather"(%0, %arg1) {axis = 0 : i32, batch_dims = 0 : i32}: (tensor<1000x1000xf32>, tensor<1x1xi32>) -> tensor<1x1x1000xf32>
  func.return %1 : tensor<1x1x1000xf32>

// CHECK-NEXT: tfl.gather
// CHECK-NEXT: tfl.dequantize
}

// CHECK-LABEL: dequantize_pushdown_gather_with_reduction

	metrics, err := legacyregistry.DefaultGatherer.Gather()
	if err != nil {
		t.Fatalf("Failed to gather metrics: %s", err)
	}

	counterSum := 0
	for _, mf := range metrics {
		if mf.GetName() != name {
			continue // Ignore other metrics.
		}
		for _, metric := range mf.GetMetric() {
			if !testutil.LabelsMatch(metric, labelFilter) {
				continue

    // it from a Gather op.
    // i = 0: index = 2
    // i = 1: index = [1, 0]
    auto index = op.input(i);
    if (index.type() != DT_INT32) {
      index = Cast(scope, index, DT_INT32);
    }
    // Gather the index specified locations in the gradient and
    // propagate it as the gradient for the i'th data item.
    // i = 0: gather(grad, 2) = [g_5, g_6]

  }
}

TEST(TFCompileTest, Gather) {
  GatherComp gather;
  EXPECT_EQ(gather.arg0_data(), gather.arg_data(0));
  EXPECT_EQ(gather.arg1_data(), gather.arg_data(1));

  // Successful gather.
  {
    const float params[4] = {1, 2, 3, 4};
    std::copy(params + 0, params + 4, gather.arg0_data());
    const int32 indices[2] = {1, 3};
    std::copy(indices + 0, indices + 2, gather.arg1_data());

// CHECK-NEXT: [[res:%.*]] = tfrt_fallback_async.executeop key(1) cost({{.*}}) device("/job:localhost/replica:0/task:0/device:CPU:0") "tf.GatherV2"([[value]], {{.*}}, [[const]])
// CHECK-NEXT: tfrt.return [[out_chain]], [[res]] : !tfrt.chain, !tfrt_fallback.tf_tensor
func.func @gather(%indices: tensor<?xi32>,
             %resource: tensor<*x!tf_type.resource>) -> tensor<*xi32> {

// CHECK: %[[GATHER:.*]] = "tf.XlaGather"(%[[DEQUANTIZED]], %arg0, %cst) <{dimension_numbers = "\0A\02\00\01\12\01\00\1A\02\00\01 \01", indices_are_sorted = true}> : (tensor<200x100x300xf32>, tensor<10x2xi32>, tensor<3xi64>) -> tensor<1x300x10xf32>
// CHECK: return %[[GATHER]] : tensor<1x300x10xf32>

// -----

module {

  %15 = "mhlo.gather"(%arg0, %14) <{dimension_numbers = #mhlo.gather<offset_dims = [0, 1, 3], collapsed_slice_dims = [2], start_index_map = [2], index_vector_dim = 1>, slice_sizes = dense<[4, 8, 1, 32]> : tensor<4xi64>}> : (tensor<4x8x32x32xf32>, tensor<64x1xi32>) -> tensor<4x8x64x32xf32>

    TF::TensorArrayGatherV3Op gather,
    const llvm::SmallDenseMap<Value, TensorArrayStats>& stats) {
  auto local_var = gather.getHandle();
  if (stats.count(local_var) == 0) {
    return gather.emitOpError("unknown tensor array");
  }
  OpBuilder builder(gather);
  auto buffer = cutil::ReadLocalVariable(local_var, builder, gather.getLoc());
  auto result = cutil::GatherElements(gather.getIndices(), buffer, builder,

		t.Fatalf("incorrect sum: %v", s)
	}
}

func gatherHistogram(t *testing.T, name string) (count uint64, sum float64) {
	metrics, err := legacyregistry.DefaultGatherer.Gather()
	if err != nil {
		t.Fatalf("Failed to gather metrics: %s", err)
	}
	for _, mf := range metrics {
		if mf.GetName() == name {
			for _, m := range mf.GetMetric() {
				h := m.GetHistogram()
				count += h.GetSampleCount()