mlx/mlx/fast_primitives.h

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#include "mlx/primitives.h"
namespace mlx::core::fast {
// Custom primitive accepts a fallback function which it uses for
// transformations. Transformations are virtual so that derived classes may
// override the default behavior.
class Custom : public Primitive {
public:
explicit Custom(
Stream stream,
std::function<std::vector<array>(std::vector<array>)> fallback)
: Primitive(stream), fallback_(fallback){};
virtual std::pair<std::vector<array>, std::vector<int>> vmap(
const std::vector<array>& inputs,
const std::vector<int>& axes) override;
virtual std::vector<array> jvp(
const std::vector<array>& primals,
const std::vector<array>& tangents,
const std::vector<int>& argnums) override;
virtual std::vector<array> vjp(
const std::vector<array>& primals,
const std::vector<array>& cotangents,
const std::vector<int>& argnums,
const std::vector<array>& outputs) override;
private:
std::function<std::vector<array>(std::vector<array>)> fallback_;
};
class RoPE : public Custom {
public:
RoPE(
Stream stream,
std::function<std::vector<array>(std::vector<array>)> fallback,
int dims,
bool traditional,
float base,
float scale,
int offset)
: Custom(stream, fallback),
dims_(dims),
traditional_(traditional),
base_(base),
scale_(scale),
offset_(offset){};
void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
override;
void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
override;
DEFINE_PRINT(RoPE)
bool is_equivalent(const Primitive& other) const override;
private:
std::function<std::vector<array>(std::vector<array>)> fallback_;
int dims_;
bool traditional_;
float base_;
float scale_;
int offset_;
};
Fast Inference SDPA op (#735) * Fast Inference SDPA op Implements metal shaders for: o = mx.fast_inference_sdpa(queries, keys, values, scale, mask) Supports fp16, fp32 dtypes; assumes d_k = 128. Generic op support / prompt encoding supported via mlx primitives. Metal implementation is for the inference use case only. Majority of performance benefits appears to results from GQA & reduced bandwidth requirements; there is approximate performance parity for the MHA use case (from some measurements on M3 Max). * Flush shared memory to zero before unprotected reads for (scores @ values) * Move to fast:: namespace, address reviewer comments ... also attempt to revert formatter auto-change for files not relevant to this change * Shared memory flush to top of kernel * Resolve compiler warnings * Update python/src/fast.cpp Co-authored-by: Awni Hannun <awni.hannun@gmail.com> * Update python/src/fast.cpp Co-authored-by: Awni Hannun <awni.hannun@gmail.com> * Update python/src/fast.cpp Co-authored-by: Awni Hannun <awni.hannun@gmail.com> * Update python/src/fast.cpp Co-authored-by: Awni Hannun <awni.hannun@gmail.com> * Update docstring per PR feedback * Softmax in higher precision, ... * route to fallback for more use cases - batch size > 1, head_dim other than 128, etc. * Address linux build failure * Address other reviewer comments * Remove extraneous eval_cpu function per review --------- Co-authored-by: Atila Orhon <64497909+atiorh@users.noreply.github.com> Co-authored-by: Awni Hannun <awni.hannun@gmail.com> Co-authored-by: atila <atiorh@icloud.com>
2024-03-05 13:06:11 +08:00
class ScaledDotProductAttention : public Custom {
public:
explicit ScaledDotProductAttention(
Stream stream,
std::function<std::vector<array>(std::vector<array>)> fallback,
const float scale,
const bool needs_mask)
: Custom(stream, fallback), scale_(scale), needs_mask_(needs_mask){};
void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
override {
outputs[0] = fallback_(inputs)[0];
};
void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
override {
eval_gpu(inputs, outputs[0]);
};
void eval_gpu(const std::vector<array>& inputs, array& out);
bool is_equivalent(const Primitive& other) const override;
DEFINE_PRINT(ScaledDotProductAttention)
private:
std::function<std::vector<array>(std::vector<array>)> fallback_;
float scale_;
bool needs_mask_;
};
} // namespace mlx::core::fast