[ET-VK][Ops] quantize ops skeleton test framework

Differential Revision: D75959066

Pull Request resolved: #11366

Author: ahmtox

backends/vulkan/test/op_tests/quantize_test.cpp

@@ -0,0 +1,158 @@
+/*
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ * All rights reserved.
+ *
+ * This source code is licensed under the BSD-style license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+#include <gtest/gtest.h>
+
+#include <ATen/ATen.h>
+
+#include <executorch/backends/vulkan/runtime/api/api.h>
+#include <executorch/backends/vulkan/runtime/graph/ComputeGraph.h>
+#include <executorch/backends/vulkan/runtime/graph/ops/OperatorRegistry.h>
+
+#include <executorch/extension/aten_util/make_aten_functor_from_et_functor.h>
+#include <executorch/extension/kernel_util/make_boxed_from_unboxed_functor.h>
+
+#include "test_utils.h"
+
+#include <cassert>
+#include <iostream>
+
+namespace torch {
+namespace executor {
+namespace native {
+
+// Forward declarations of the functions we're testing
+Tensor& quantize_per_tensor_out(
+    const Tensor& input,
+    double scale,
+    int64_t zero_point,
+    int64_t quant_min,
+    int64_t quant_max,
+    ScalarType dtype,
+    Tensor& out);
+
+Tensor& quantize_per_token_out(
+    const Tensor& input,
+    const Tensor& scale,
+    const Tensor& zero_point,
+    int64_t quant_min,
+    int64_t quant_max,
+    ScalarType dtype,
+    Tensor& out);
+
+// Wrapper function for quantize_per_tensor_out without context
+Tensor& quantize_per_tensor_out_no_context(
+    const Tensor& input,
+    double scale,
+    int64_t zero_point,
+    int64_t quant_min,
+    int64_t quant_max,
+    ScalarType dtype,
+    Tensor& out) {
+  return torch::executor::native::quantize_per_tensor_out(
+      input, scale, zero_point, quant_min, quant_max, dtype, out);
+}
+
+// Wrapper function for quantize_per_token_out without context
+Tensor& quantize_per_token_out_no_context(
+    const Tensor& input,
+    const Tensor& scale,
+    const Tensor& zero_point,
+    int64_t quant_min,
+    int64_t quant_max,
+    ScalarType dtype,
+    Tensor& out) {
+  return torch::executor::native::quantize_per_token_out(
+      input, scale, zero_point, quant_min, quant_max, dtype, out);
+}
+
+// ATen wrapper for quantize_per_tensor
+at::Tensor quantize_per_tensor_aten(
+    const at::Tensor& input,
+    double scale,
+    int64_t zero_point,
+    int64_t quant_min,
+    int64_t quant_max,
+    at::ScalarType dtype) {
+  auto out = at::empty_like(input, dtype);
+  ScalarType et_dtype = at_scalartype_to_et_scalartype(dtype);
+
+  WRAP_TO_ATEN(quantize_per_tensor_out_no_context, 6)
+  (input, scale, zero_point, quant_min, quant_max, et_dtype, out);
+  return out;
+}
+
+// ATen wrapper for quantize_per_token
+at::Tensor quantize_per_token_aten(
+    const at::Tensor& input,
+    const at::Tensor& scale,
+    const at::Tensor& zero_point,
+    int64_t quant_min,
+    int64_t quant_max,
+    at::ScalarType dtype) {
+  auto out = at::empty_like(input, dtype);
+  ScalarType et_dtype = at_scalartype_to_et_scalartype(dtype);
+
+  WRAP_TO_ATEN(quantize_per_token_out_no_context, 6)
+  (input, scale, zero_point, quant_min, quant_max, et_dtype, out);
+  return out;
+}
+
+} // namespace native
+} // namespace executor
+} // namespace torch
+
+void check_quantize_args(
+    int64_t quant_min,
+    int64_t quant_max,
+    c10::ScalarType out_dtype) {
+  using namespace vkcompute;
+  int32_t quant_min_lower_bound = 0, quant_max_upper_bound = 0;
+  switch (out_dtype) {
+    case c10::kByte:
+      quant_min_lower_bound =
+          static_cast<int32_t>(std::numeric_limits<uint8_t>::min());
+      quant_max_upper_bound =
+          static_cast<int32_t>(std::numeric_limits<uint8_t>::max());
+      break;
+    case c10::kChar:
+      quant_min_lower_bound =
+          static_cast<int32_t>(std::numeric_limits<int8_t>::min());
+      quant_max_upper_bound =
+          static_cast<int32_t>(std::numeric_limits<int8_t>::max());
+      break;
+    case c10::kBits16:
+    case c10::kUInt16:
+      quant_min_lower_bound = std::numeric_limits<uint16_t>::min();
+      quant_max_upper_bound = std::numeric_limits<uint16_t>::max();
+      break;
+    case c10::kShort:
+      quant_min_lower_bound = std::numeric_limits<int16_t>::min();
+      quant_max_upper_bound = std::numeric_limits<int16_t>::max();
+      break;
+    case c10::kInt:
+      quant_min_lower_bound = std::numeric_limits<int32_t>::min();
+      quant_max_upper_bound = std::numeric_limits<int32_t>::max();
+      break;
+    default:
+      VK_CHECK_COND(false, "Unsupported dtype: ", scalar_type_name(out_dtype));
+  }
+  VK_CHECK_COND(
+      quant_min >= quant_min_lower_bound,
+      "quant_min out of bound for dtype, expected quant_min_lower_bound: ",
+      quant_min_lower_bound,
+      " actual quant_min: ",
+      quant_min);
+
+  VK_CHECK_COND(
+      quant_max <= quant_max_upper_bound,
+      "quant_max out of bound for dtype, expected quant_max_upper_bound: ",
+      quant_max_upper_bound,
+      " actual quant_max: ",
+      quant_max);
+}

backends/vulkan/test/op_tests/targets.bzl

@@ -177,6 +177,15 @@ def define_common_targets(is_fbcode = False):
             "//executorch/extension/tensor:tensor",
         ]
     )
+    define_test_targets(
+        "quantize_test",
+        extra_deps = [
+            ":test_utils",
+            "//executorch/kernels/quantized/cpu:op_quantize",
+            "//executorch/extension/tensor:tensor",
+            "//executorch/extension/aten_util:aten_bridge",
+        ]
+    )
     define_test_targets(
         "linear_weight_int4_test",
         extra_deps = [