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https://github.com/ml-explore/mlx.git
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dc937b8ed3
* build and load shared object for cpu compile * nits * cpu compile tests pass * cpu compile tests pass * fix preamble for g++ * donation * fix gpu buffer donation * reuse prebuilt libraries * faster contiguity conditoins * fix test * rid compiler warning * fast erf * Fix float16 for compile and add more types to cpu compile * Remove a forgotten comment * use cached libs * nits --------- Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
89 lines
2.8 KiB
C++
89 lines
2.8 KiB
C++
// Copyright © 2023 Apple Inc.
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#pragma once
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#include <variant>
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#include "array.h"
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#include "device.h"
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#include "dtype.h"
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#include "stream.h"
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namespace mlx::core {
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using StreamOrDevice = std::variant<std::monostate, Stream, Device>;
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Stream to_stream(StreamOrDevice s);
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struct StreamContext {
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public:
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StreamContext(StreamOrDevice s) : _stream(default_stream(default_device())) {
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if (std::holds_alternative<std::monostate>(s)) {
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throw std::runtime_error(
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"[StreamContext] Invalid argument, please specify a stream or device.");
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}
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auto _s = to_stream(s);
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set_default_device(_s.device);
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set_default_stream(_s);
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}
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~StreamContext() {
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set_default_device(_stream.device);
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set_default_stream(_stream);
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}
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private:
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Stream _stream;
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};
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struct PrintFormatter {
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inline void print(std::ostream& os, bool val);
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inline void print(std::ostream& os, int16_t val);
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inline void print(std::ostream& os, uint16_t val);
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inline void print(std::ostream& os, int32_t val);
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inline void print(std::ostream& os, uint32_t val);
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inline void print(std::ostream& os, int64_t val);
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inline void print(std::ostream& os, uint64_t val);
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inline void print(std::ostream& os, float16_t val);
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inline void print(std::ostream& os, bfloat16_t val);
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inline void print(std::ostream& os, float val);
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inline void print(std::ostream& os, complex64_t val);
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bool capitalize_bool{false};
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};
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extern PrintFormatter global_formatter;
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/** The type from promoting the arrays' types with one another. */
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Dtype result_type(const std::vector<array>& arrays);
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std::vector<int> broadcast_shapes(
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const std::vector<int>& s1,
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const std::vector<int>& s2);
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bool is_same_shape(const std::vector<array>& arrays);
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/**
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* Returns the axis normalized to be in the range [0, ndim).
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* Based on numpy's normalize_axis_index. See
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* https://numpy.org/devdocs/reference/generated/numpy.lib.array_utils.normalize_axis_index.html
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*/
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int normalize_axis(int axis, int ndim);
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std::ostream& operator<<(std::ostream& os, const Device& d);
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std::ostream& operator<<(std::ostream& os, const Stream& s);
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std::ostream& operator<<(std::ostream& os, const Dtype& d);
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std::ostream& operator<<(std::ostream& os, const Dtype::Kind& k);
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std::ostream& operator<<(std::ostream& os, array a);
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std::ostream& operator<<(std::ostream& os, const std::vector<int>& v);
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std::ostream& operator<<(std::ostream& os, const std::vector<size_t>& v);
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inline std::ostream& operator<<(std::ostream& os, const complex64_t& v) {
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return os << v.real() << (v.imag() >= 0 ? "+" : "") << v.imag() << "j";
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}
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inline std::ostream& operator<<(std::ostream& os, const float16_t& v) {
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return os << static_cast<float>(v);
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}
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inline std::ostream& operator<<(std::ostream& os, const bfloat16_t& v) {
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return os << static_cast<float>(v);
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}
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} // namespace mlx::core
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