awni's commit files

examples/extensions/axpby/axpby.h

@@ -0,0 +1,84 @@
+#pragma once
+
+#include "mlx/ops.h"
+#include "mlx/primitives.h"
+
+namespace mlx::core {
+
+///////////////////////////////////////////////////////////////////////////////
+// Operation
+///////////////////////////////////////////////////////////////////////////////
+
+/**
+ *  Scale and sum two vectors elementwise
+ *  z = alpha * x + beta * y
+ *
+ *  Follow numpy style broadcasting between x and y
+ *  Inputs are upcasted to floats if needed
+ **/
+array axpby(
+    const array& x, // Input array x
+    const array& y, // Input array y
+    const float alpha, // Scaling factor for x
+    const float beta, // Scaling factor for y
+    StreamOrDevice s = {} // Stream on which to schedule the operation
+);
+
+///////////////////////////////////////////////////////////////////////////////
+// Primitive
+///////////////////////////////////////////////////////////////////////////////
+
+class Axpby : public Primitive {
+ public:
+  explicit Axpby(Stream stream, float alpha, float beta)
+      : Primitive(stream), alpha_(alpha), beta_(beta){};
+
+  /**
+   * A primitive must know how to evaluate itself on the CPU/GPU
+   * for the given inputs and populate the output array.
+   *
+   * To avoid unecessary allocations, the evaluation function
+   * is responsible for allocating space for the array.
+   */
+  void eval_cpu(const std::vector<array>& inputs, array& out) override;
+  void eval_gpu(const std::vector<array>& inputs, array& out) override;
+
+  /** The Jacobian-vector product. */
+  array jvp(
+      const std::vector<array>& primals,
+      const std::vector<array>& tangents,
+      const std::vector<int>& argnums) override;
+
+  /** The vector-Jacobian product. */
+  std::vector<array> vjp(
+      const std::vector<array>& primals,
+      const array& cotan,
+      const std::vector<int>& argnums) override;
+
+  /**
+   * The primitive must know how to vectorize itself accross
+   * the given axes. The output is a pair containing the array
+   * representing the vectorized computation and the axis which
+   * corresponds to the output vectorized dimension.
+   */
+  std::pair<array, int> vmap(
+      const std::vector<array>& inputs,
+      const std::vector<int>& axes) override;
+
+  /** Print the primitive. */
+  void print(std::ostream& os) override {
+    os << "Axpby";
+  }
+
+  /** Equivalence check **/
+  bool is_equivalent(const Primitive& other) const override;
+
+ private:
+  float alpha_;
+  float beta_;
+
+  /** Fall back implementation for evaluation on CPU */
+  void eval(const std::vector<array>& inputs, array& out);
+};
+
+} // namespace mlx::core