Function EXPECT_DEATH

tensorflow/lite/kernels/fully_connected_test.cc:899–936

Note that it is not required that the first dimension be the number of batches. But it is required that the last dimension is the 'input_dim'. For this particular test, it is required for the output to be reformattable into a shape of form {4, 1, 5, ?} but since the output size (the product of output dimensions: units times batches) is 6, this is not possible.

  // into a shape of form {4, 1, 5, ?} but since the output size (the product of
  // output dimensions: units times batches) is 6, this is not possible.
  EXPECT_DEATH(FloatFullyConnectedOpModel m(
                   GetRegistration(), /*units=*/3, /*batches=*/2,
                   /*input=*/{TensorType_FLOAT32, {4, 1, 5, 1}},
                   /*output=*/{TensorType_FLOAT32},
                   /*keep_num_dims=*/true),
               "Cannot allocate tensors");
}
#endif

TEST_P(QuantizedFullyConnectedOpTest, SimpleTest4dInputQuantizedUint8) {
  QuantizedFullyConnectedOpModel m(
      GetRegistration(), /*units=*/3, /*batches=*/2,
      /*input=*/{TensorType_UINT8, {4, 1, 5, 1}, -63.5, 64},
      /*output=*/{TensorType_UINT8, {}, -127, 128});

  // input_product_scale < output_scale was not true.
  m.SetWeights<uint8_t>({
      1, 2, 3, 4, 5, 6, 7, 8, 9, 10,  // u = 0
      1, 2, 3, 4, 5, 6, 7, 8, 9, 10,  // u = 1
      1, 2, 3, 4, 5, 6, 7, 8, 9, 10,  // u = 2
  });
  m.SetBias({1, 2, 3});

  m.SetInput<uint8_t>({
      1, 2, 3, 4, 5, 6, 7, 8,  -9, -10,  // b = 0
      1, 2, 3, 4, 5, 6, 7, -8, 9,  -10,  // b = 1
  });

  m.Invoke();

  EXPECT_THAT(m.GetDequantizedOutput<uint8_t>(),
              ElementsAreArray(ArrayFloatNear({
                  24, 25, 26,  //
                  58, 59, 60,  //
              })));
  EXPECT_THAT(m.GetOutput<uint8_t>(),
              ElementsAre(151, 152, 153, 185, 186, 187));
}

TEST_P(QuantizedFullyConnectedOpTest,
       SimpleTest4dInputQuantizedOutputMultiplierGreaterThan1Uint8) {