&shape_info));
  auto iter = shape_info.find("sink");
  EXPECT_NE(iter, shape_info.end());
  EXPECT_EQ(iter->second.size(), 1);
  EXPECT_EQ(iter->second.at(0).handle_type, DT_FLOAT);
  TensorShape resource_shape;
  EXPECT_TRUE(iter->second.at(0).handle_shape.AsTensorShape(&resource_shape));
  EXPECT_EQ(resource_shape, TensorShape({2, 3}));
}

}  // namespace

		claimStates []string
		expected    bool
		skipPodUID  bool
	}{
		{
			name:        "all missing",
			claimStates: []string{missing, missing},
			expected:    false,
		},
		{
			name:        "no claims",
			claimStates: []string{},
			expected:    false,
		},
		{
			name:        "exists",
			claimStates: []string{missing, exists},
			expected:    false,
		},
		{

  EXPECT_TRUE(result.ok());
  EXPECT_EQ(compilation_status.Delta(kMlirCombinedMlirSuccess), 1);
  EXPECT_EQ(compilation_status.Delta(kMlirCombinedMlirFailure), 0);
  EXPECT_EQ(compilation_status.Delta(kMlirCombinedOldSuccess), 1);
  EXPECT_EQ(compilation_status.Delta(kMlirCombinedOldFailure), 0);
  // Old bridge should never be called at all.
  EXPECT_EQ(compilation_status.Delta(kOldBridgeMlirFilteredFailure), 0);

        if (kUseUpdatedHybridSchemeDefault) {
          EXPECT_EQ(quant_tensor->quantization()->scale()->size(), shape[0]);
        } else {
          EXPECT_EQ(quant_tensor->quantization()->scale()->size(), 1);
        }
      } else {
        EXPECT_EQ(quant_tensor->type(), TensorType_FLOAT32);
      }
    }
    EXPECT_EQ(used_tensors.size(), quantized_graph->tensors()->size());
  }
}

  std::optional<CalibrationStatistics> statistics = collector.GetStatistics();

  EXPECT_TRUE(statistics.has_value());
  EXPECT_EQ(statistics.value().average_min_max_statistics().min_sum(), -4.0f);
  EXPECT_EQ(statistics.value().average_min_max_statistics().max_sum(), 15.0f);
  EXPECT_EQ(statistics.value().average_min_max_statistics().num_samples(), 2);
}

TEST(CalibrationStatisticsCollectorTest, ClearDataAndGetResultsMinMax) {

  // verify transpose
  EXPECT_EQ(
      fused_lstm_func_->getAttrOfType<StringAttr>(kTFImplements).getValue(),
      convert.GetCompositeOpName());
  EXPECT_EQ(fused_lstm_func_.getNumArguments(), 5);
  EXPECT_EQ(fused_lstm_func_.getFunctionType().getNumResults(), 1);

  auto transpose_op = fused_lstm_func_.getBody().front().begin();
  transpose_op++;

  EXPECT_EQ(0, TF_ShapeDims(shape_a));

  const TF_SignatureDefParam* param_b = TF_SignatureDefParamListGet(args, 1);
  const TF_TensorSpec* tensor_spec_b = TF_SignatureDefParamTensorSpec(param_b);
  const TF_Shape* shape_b = TF_TensorSpecShape(tensor_spec_b);

  // Input "b" is a scalar, float32 tensor
  EXPECT_EQ("b", std::string(TF_SignatureDefParamName(param_b)));

			manifestsDir:  "/etc/bar/",
			expected:      "/etc/bar/foo.yaml",
		},
	}
	for _, rt := range tests {
		t.Run(rt.componentName, func(t *testing.T) {
			actual := GetStaticPodFilepath(rt.componentName, rt.manifestsDir)
			expected := filepath.FromSlash(rt.expected)
			if actual != expected {
				t.Errorf(
					"failed GetStaticPodFilepath:\n\texpected: %s\n\t  actual: %s",
					rt.expected,
					actual,
				)
			}
		})

		}
		if !reflect.DeepEqual(actual.CPUQuota, testCase.expected.CPUQuota) {
			t.Errorf("unexpected result, test: %v, cpu quota not as expected. Expected: %v, Actual:%v", testName, *testCase.expected.CPUQuota, *actual.CPUQuota)
		}
		if !reflect.DeepEqual(actual.CPUShares, testCase.expected.CPUShares) {

			input:    int64(5),
			period:   uint64(10000),
			expected: minQuotaPeriod,
		},
		{
			msg:      "5 input 5k period and default quota expected",
			input:    int64(5),
			period:   uint64(5000),
			expected: minQuotaPeriod,
		},
		{
			msg:      "9 input 10k period and default quota expected",
			input:    int64(9),
			period:   uint64(10000),
			expected: minQuotaPeriod,