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https://github.com/ml-explore/mlx.git
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9adcd1a650
* Update API to allow mask='causal' in fast::sdpa * Add fallback * Update steel::AttnParams * Fix typo * WIP, basic causal * Update tests * Update benchmarking * Update masking loop limits * Add bool masking and update tests * Update additive mask * Update benchmarks * Update benchmarks * Update tests * Update for bfloat error * Update early exit * Add random seed to tests
93 lines
2.2 KiB
C++
93 lines
2.2 KiB
C++
// Copyright © 2023-2024 Apple Inc.
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#pragma once
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#include <optional>
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#include <variant>
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#include "mlx/utils.h"
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namespace mlx::core::fast {
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array rms_norm(
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const array& x,
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const std::optional<array>& weight,
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float eps,
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StreamOrDevice s = {});
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array layer_norm(
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const array& x,
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const std::optional<array>& weight,
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const std::optional<array>& bias,
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float eps,
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StreamOrDevice s = {});
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array rope(
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const array& x,
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int dims,
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bool traditional,
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std::optional<float> base,
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float scale,
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int offset,
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const std::optional<array>& freqs = std::nullopt,
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StreamOrDevice s = {});
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array rope(
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const array& x,
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int dims,
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bool traditional,
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std::optional<float> base,
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float scale,
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const array& offset,
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const std::optional<array>& freqs = std::nullopt,
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StreamOrDevice s = {});
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/** Computes: O = softmax(Q @ K.T) @ V **/
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array scaled_dot_product_attention(
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const array& queries,
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const array& keys,
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const array& values,
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const float scale,
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const std::variant<std::monostate, std::string, array>& mask = {},
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const std::optional<int> memory_efficient_threshold = std::nullopt,
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StreamOrDevice s = {});
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std::tuple<array, array, array> affine_quantize(
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const array& w,
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int group_size = 64,
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int bits = 4,
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StreamOrDevice s = {});
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array affine_dequantize(
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const array& w,
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const array& scales,
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const array& biases,
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int group_size = 64,
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int bits = 4,
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StreamOrDevice s = {});
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typedef std::variant<int, bool, Dtype> TemplateArg;
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typedef std::function<std::vector<array>(
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const std::vector<array>&,
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const std::vector<Shape>&,
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const std::vector<Dtype>&,
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std::tuple<int, int, int>,
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std::tuple<int, int, int>,
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std::vector<std::pair<std::string, TemplateArg>>,
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std::optional<float>,
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bool,
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StreamOrDevice)>
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MetalKernelFunction;
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MetalKernelFunction metal_kernel(
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const std::string& name,
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const std::vector<std::string>& input_names,
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const std::vector<std::string>& output_names,
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const std::string& source,
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const std::string& header = "",
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bool ensure_row_contiguous = true,
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bool atomic_outputs = false);
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} // namespace mlx::core::fast
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