message: Remove ResizeInputTensorStrict test.
diff: @@ -59,20 +59,19 @@ class DynamicInputTest : public tflite_shims::testing::Test {
  kDilatedConvolutionModelWithMetaData));
  engine_->InitInterpreter();
  - SUPPORT_ASSERT_OK_AND_ASSIGN(preprocessor_,
  + SUPPORT_ASSERT_OK_AND_ASSIGN(auto preprocessor,
  ImagePreprocessor::Create(engine_.get(), {0}));
  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
  frame_buffer_ = CreateFromRgbRawBuffer(
  image.pixel_data, FrameBuffer::Dimension{image.width, image.height});
  - preprocessor_->Preprocess(*frame_buffer_);
  + preprocessor->Preprocess(*frame_buffer_);
  }
  protected:
  std::unique_ptr<TfLiteEngine> engine_ = nullptr;
  std::unique_ptr<FrameBuffer> frame_buffer_ = nullptr;
  - std::unique_ptr<ImagePreprocessor> preprocessor_ = nullptr;
  };
  // See if output tensor has been re-dimmed as per the input
  @@ -106,20 +105,6 @@ TEST_F(DynamicInputTest, GoldenImageComparison) {
  std::numeric_limits<float>::epsilon());
  }
  -// Modifying batch/depth to invalid size after Init()
  -// call should throw error.
  -TEST_F(DynamicInputTest, InvalidBatchOrDepthResize) {
  - // Resized input tensor to invalid batch and depth size.
  - engine_->interpreter()->ResizeInputTensorStrict(
  - 0, {50, frame_buffer_->dimension().height,
  - frame_buffer_->dimension().width, 3});
  - auto process_status = preprocessor_->Preprocess(*frame_buffer_);
  - EXPECT_EQ(process_status.code(), absl::StatusCode::kInvalidArgument);
  - EXPECT_THAT(process_status.message(),
  - HasSubstr("The input tensor should have dimensions 1 x height x "
  - "width x 3. Got"));
  -}
  -
  } // namespace
  } // namespace processor
  } // namespace task
  