[ET-VK][Ops] choose_qparams.tensor test setup

Creating choose_qparams.tensor operator testing framework along with a reference implementation for testing

Differential Revision: [D76436894](https://our.internmc.facebook.com/intern/diff/D76436894/)

[ghstack-poisoned]

Author: morelos

backends/vulkan/test/op_tests/choose_qparams_test.cpp

@@ -232,3 +232,277 @@ vkcompute::vkapi::ScalarType from_at_scalartype(c10::ScalarType at_scalartype) {
           ")");
   }
 }
+
+//
+// Reference Implementation
+//
+
+/*
+ * Reference implementation of choose_qparams_tensor
+ */
+std::tuple<at::Tensor, at::Tensor> choose_qparams_tensor_reference_impl(
+    const at::Tensor& input,
+    int64_t quant_min,
+    int64_t quant_max) {
+  // Create output tensors
+  at::Tensor scale_out = at::empty({}, at::device(at::kCPU).dtype(at::kDouble));
+  at::Tensor zero_point_out =
+      at::empty({}, at::device(at::kCPU).dtype(at::kLong));
+
+  // Find min and max values in the input tensor
+  float min_val = input.min().item<float>();
+  float max_val = input.max().item<float>();
+
+  // Extend the [min, max] interval to ensure it contains 0
+  min_val = std::min(min_val, 0.f);
+  max_val = std::max(max_val, 0.f);
+
+  // Calculate scale
+  double scale =
+      (static_cast<double>(max_val) - min_val) / (quant_max - quant_min);
+
+  // Handle small scale
+  constexpr float SMALL_SCALE_THRESHOLD = 6.1e-5f;
+  if (float(scale) == 0.0f || std::isinf(1.0f / float(scale))) {
+    scale = 0.1;
+  }
+
+  if (scale < SMALL_SCALE_THRESHOLD) {
+    float org_scale = scale;
+    scale = SMALL_SCALE_THRESHOLD;
+    // Adjust min and max based on new scale
+    if (min_val == 0.0f) {
+      max_val = SMALL_SCALE_THRESHOLD * (quant_max - quant_min);
+    } else if (max_val == 0.0f) {
+      min_val = -SMALL_SCALE_THRESHOLD * (quant_max - quant_min);
+    } else {
+      float amplifier = SMALL_SCALE_THRESHOLD / org_scale;
+      min_val *= amplifier;
+      max_val *= amplifier;
+    }
+  }
+
+  // Calculate zero point
+  double zero_point_from_min = quant_min - min_val / static_cast<double>(scale);
+  double zero_point_from_max = quant_max - max_val / static_cast<double>(scale);
+  double zero_point_from_min_error =
+      std::abs(quant_min) - std::abs(min_val / static_cast<double>(scale));
+  double zero_point_from_max_error =
+      std::abs(quant_max) - std::abs(max_val / static_cast<double>(scale));
+  double initial_zero_point =
+      zero_point_from_min_error < zero_point_from_max_error
+      ? zero_point_from_min
+      : zero_point_from_max;
+
+  // Nudge zero point to be an integer
+  int64_t nudged_zero_point = 0;
+  if (initial_zero_point < quant_min) {
+    nudged_zero_point = quant_min;
+  } else if (initial_zero_point > quant_max) {
+    nudged_zero_point = quant_max;
+  } else {
+    nudged_zero_point = std::nearbyint(static_cast<float>(initial_zero_point));
+  }
+
+  // Set output values - use item_mutable() for scalar tensors
+  scale_out.fill_(scale);
+  zero_point_out.fill_(nudged_zero_point);
+
+  return std::make_tuple(scale_out, zero_point_out);
+}
+
+// Forward declaration of implementation functions
+void test_vulkan_choose_qparams_tensor_impl(
+    const std::vector<int>& input_sizes,
+    int64_t quant_min,
+    int64_t quant_max,
+    at::ScalarType dtype,
+    const vkcompute::utils::StorageType in_storage,
+    const vkcompute::utils::StorageType out_storage);
+
+// Wrapper function to test both buffer and texture storage types
+void test_vulkan_choose_qparams_tensor(
+    const std::vector<int>& input_sizes,
+    int64_t quant_min,
+    int64_t quant_max,
+    at::ScalarType dtype) {
+  // Test with buffer storage
+  test_vulkan_choose_qparams_tensor_impl(
+      input_sizes,
+      quant_min,
+      quant_max,
+      dtype,
+      vkcompute::utils::kBuffer,
+      vkcompute::utils::kBuffer);
+
+  // Test with texture storage
+  test_vulkan_choose_qparams_tensor_impl(
+      input_sizes,
+      quant_min,
+      quant_max,
+      dtype,
+      vkcompute::utils::kTexture3D,
+      vkcompute::utils::kTexture3D);
+}
+
+void test_reference_choose_qparams_tensor(
+    const std::vector<int>& input_sizes,
+    int64_t quant_min,
+    int64_t quant_max,
+    at::ScalarType dtype) {
+  std::vector<int64_t> input_sizes_int64(
+      input_sizes.begin(), input_sizes.end());
+  at::Tensor input =
+      at::rand(input_sizes_int64, at::device(at::kCPU).dtype(at::kFloat));
+
+  // Get reference output
+  auto [reference_scale, reference_zero_point] =
+      choose_qparams_tensor_reference_impl(input, quant_min, quant_max);
+
+  // Get implementation output
+  auto [impl_scale, impl_zero_point] =
+      torch::executor::native::choose_qparams_tensor_aten(
+          input, quant_min, quant_max, dtype);
+
+  // Compare outputs
+  const bool scale_correct = at::allclose(reference_scale, impl_scale);
+  const bool zero_point_correct =
+      at::equal(reference_zero_point, impl_zero_point);
+
+  if (!scale_correct || !zero_point_correct) {
+    std::cout << "\n"
+              << "Failed with parameters: " << std::endl;
+    std::cout << "  quant_min: " << quant_min << std::endl;
+    std::cout << "  quant_max: " << quant_max << std::endl;
+
+    std::cout << "input:" << std::endl;
+    std::cout << input << std::endl;
+    std::cout << "reference scale:" << std::endl;
+    std::cout << reference_scale << std::endl;
+    std::cout << "implementation scale:" << std::endl;
+    std::cout << impl_scale << std::endl;
+    std::cout << "reference zero_point:" << std::endl;
+    std::cout << reference_zero_point << std::endl;
+    std::cout << "implementation zero_point:" << std::endl;
+    std::cout << impl_zero_point << std::endl;
+  }
+
+  ASSERT_TRUE(scale_correct && zero_point_correct);
+}
+
+void test_vulkan_choose_qparams_tensor_impl(
+    const std::vector<int>& input_sizes,
+    int64_t quant_min,
+    int64_t quant_max,
+    at::ScalarType dtype,
+    const vkcompute::utils::StorageType in_storage,
+    const vkcompute::utils::StorageType out_storage) {
+  std::vector<int64_t> input_sizes_int64(
+      input_sizes.begin(), input_sizes.end());
+  at::Tensor input =
+      at::rand(input_sizes_int64, at::device(at::kCPU).dtype(at::kFloat));
+
+  // Get reference output
+  auto [reference_scale, reference_zero_point] =
+      torch::executor::native::choose_qparams_tensor_aten(
+          input, quant_min, quant_max, dtype);
+
+  // Build Vulkan choose_qparams_tensor graph
+  using namespace vkcompute;
+
+  GraphConfig config;
+  config.set_storage_type_override(in_storage);
+  ComputeGraph graph(config);
+
+  IOValueRef r_input = graph.add_input_tensor(
+      input.sizes().vec(), from_at_scalartype(input.scalar_type()), in_storage);
+
+  const ValueRef r_quant_min = graph.add_scalar<int64_t>(quant_min);
+  const ValueRef r_quant_max = graph.add_scalar<int64_t>(quant_max);
+
+  // Output tensors
+  const ValueRef r_scale = graph.add_tensor({}, vkapi::kFloat, out_storage);
+  const ValueRef r_zero_point = graph.add_tensor({}, vkapi::kInt, out_storage);
+
+  VK_GET_OP_FN("choose_qparams.tensor")
+  (graph,
+   {
+       r_input.value,
+       r_quant_min,
+       r_quant_max,
+       r_scale,
+       r_zero_point,
+   });
+
+  ValueRef staging_scale = graph.set_output_tensor(r_scale);
+  ValueRef staging_zero_point = graph.set_output_tensor(r_zero_point);
+
+  graph.prepare();
+  graph.encode_prepack();
+  graph.prepack();
+  graph.encode_execute();
+
+  // Run Vulkan choose_qparams_tensor
+  graph.copy_into_staging(
+      r_input.staging, input.const_data_ptr(), input.numel());
+
+  graph.execute();
+
+  // Create output tensors to hold the results - use types that match GPU output
+  at::Tensor vk_scale =
+      at::empty({}, at::device(at::kCPU).dtype(at::kFloat)).contiguous();
+  at::Tensor vk_zero_point =
+      at::empty({}, at::device(at::kCPU).dtype(at::kInt)).contiguous();
+
+  // Copy results from GPU to CPU
+  graph.copy_from_staging(
+      staging_scale, vk_scale.mutable_data_ptr(), vk_scale.numel());
+  graph.copy_from_staging(
+      staging_zero_point,
+      vk_zero_point.mutable_data_ptr(),
+      vk_zero_point.numel());
+
+  // Convert reference values to match Vulkan output types for comparison
+  at::Tensor reference_scale_float = reference_scale.to(at::kFloat);
+  at::Tensor reference_zero_point_int = reference_zero_point.to(at::kInt);
+
+  // Compare outputs
+  const bool scale_correct = at::allclose(reference_scale_float, vk_scale);
+  const bool zero_point_correct =
+      at::equal(reference_zero_point_int, vk_zero_point);
+
+  if (!scale_correct || !zero_point_correct) {
+    std::cout << "\n"
+              << "Failed with parameters: " << std::endl;
+    std::cout << "  quant_min: " << quant_min << std::endl;
+    std::cout << "  quant_max: " << quant_max << std::endl;
+    std::cout << "  storage type: "
+              << (in_storage == vkcompute::utils::kBuffer ? "buffer"
+                                                          : "texture")
+              << std::endl;
+
+    // make sure that there arent a ton of elements in the input tensor
+    if (input.numel() < 100) {
+      std::cout << "input:" << std::endl;
+      std::cout << input << "\n" << std::endl;
+      std::cout << "reference scale:" << std::endl;
+      std::cout << reference_scale << std::endl;
+      std::cout << "vulkan scale:" << std::endl;
+      std::cout << vk_scale << "\n" << std::endl;
+      std::cout << "reference zero_point:" << std::endl;
+      std::cout << reference_zero_point << std::endl;
+      std::cout << "vulkan zero_point:" << std::endl;
+      std::cout << vk_zero_point << std::endl;
+    }
+  }
+
+  ASSERT_TRUE(scale_correct && zero_point_correct);
+}
+
+TEST(VulkanChooseQparamsTest, test_reference_choose_qparams_tensor_int8) {
+  test_reference_choose_qparams_tensor(
+      {2, 3, 4}, // input sizes
+      -128, // quant_min
+      127, // quant_max
+      at::kChar);
+}