mlx/mlx/backend/common/compiled.cpp
2025-06-24 10:18:52 -07:00

242 lines
6.5 KiB
C++

// Copyright © 2023-2024 Apple Inc.
#include "mlx/backend/common/compiled.h"
#include "mlx/backend/common/utils.h"
#include "mlx/utils.h"
namespace mlx::core {
void print_constant(std::ostream& os, const array& x) {
switch (x.dtype()) {
case float32:
return print_float_constant<float>(os, x);
case float16:
return print_float_constant<float16_t>(os, x);
case bfloat16:
return print_float_constant<bfloat16_t>(os, x);
case float64:
return print_float_constant<double>(os, x);
case complex64:
return print_complex_constant<complex64_t>(os, x);
case int8:
os << static_cast<int32_t>(x.item<int8_t>());
return;
case int16:
return print_int_constant<int16_t>(os, x);
case int32:
return print_int_constant<int32_t>(os, x);
case int64:
return print_int_constant<int64_t>(os, x);
case uint8:
os << static_cast<uint32_t>(x.item<uint8_t>());
return;
case uint16:
return print_int_constant<uint16_t>(os, x);
case uint32:
return print_int_constant<uint32_t>(os, x);
case uint64:
return print_int_constant<uint64_t>(os, x);
case bool_:
os << std::boolalpha << x.item<bool>();
return;
default:
throw std::runtime_error("Unsupported constant type");
}
}
std::string get_type_string(Dtype d) {
switch (d) {
case float32:
return "float";
case float16:
return "float16_t";
case bfloat16:
return "bfloat16_t";
case float64:
return "double";
case complex64:
return "complex64_t";
case bool_:
return "bool";
case int8:
return "int8_t";
case int16:
return "int16_t";
case int32:
return "int32_t";
case int64:
return "int64_t";
case uint8:
return "uint8_t";
case uint16:
return "uint16_t";
case uint32:
return "uint32_t";
case uint64:
return "uint64_t";
default: {
std::ostringstream msg;
msg << "Unsupported compilation type " << d;
throw std::runtime_error(msg.str());
}
}
}
bool compiled_check_contiguity(
const std::vector<array>& inputs,
const Shape& shape) {
bool contiguous = true;
bool all_contig = true;
bool all_row_contig = true;
bool all_col_contig = true;
int non_scalar_inputs = 0;
for (const auto& x : inputs) {
if (is_scalar(x)) {
continue;
}
non_scalar_inputs++;
bool shape_eq = x.shape() == shape;
all_contig &= (x.flags().contiguous && shape_eq);
all_row_contig &= (x.flags().row_contiguous && shape_eq);
all_col_contig &= (x.flags().col_contiguous && shape_eq);
}
if (non_scalar_inputs > 1 && !all_row_contig && !all_col_contig) {
contiguous = false;
} else if (non_scalar_inputs == 1 && !all_contig) {
contiguous = false;
} else if (non_scalar_inputs == 0 && !shape.empty()) {
contiguous = false;
}
return contiguous;
}
void compiled_allocate_outputs(
const std::vector<array>& inputs,
std::vector<array>& outputs,
const std::function<bool(size_t)>& is_constant,
bool contiguous) {
if (contiguous) {
int o = 0;
Strides strides;
size_t data_size;
array::Flags flags;
for (int i = 0; i < inputs.size() && o < outputs.size(); ++i) {
auto& in = inputs[i];
// Conditions for donation
// - Correct size
// - Not a scalar
// - Donatable
// - Not a constant
if (in.itemsize() == outputs[o].itemsize() && !is_scalar(in) &&
in.is_donatable() && is_constant(i)) {
outputs[o++].copy_shared_buffer(in);
}
// Get representative input flags to properly set non-donated outputs
if (strides.empty() && in.size() == outputs[0].size()) {
strides = in.strides();
flags = in.flags();
data_size = in.data_size();
}
}
for (; o < outputs.size(); ++o) {
outputs[o].set_data(
allocator::malloc(data_size * outputs[o].itemsize()),
data_size,
strides,
flags);
}
} else {
int o = 0;
for (int i = 0; i < inputs.size() && o < outputs.size(); ++i) {
auto& in = inputs[i];
// Conditions for donation
// - Row contiguous
// - Donatable
// - Correct size
// - Not a constant
if (in.flags().row_contiguous && in.size() == outputs[o].size() &&
in.itemsize() == outputs[o].itemsize() && in.is_donatable() &&
is_constant(i)) {
outputs[o].copy_shared_buffer(
in, outputs[o].strides(), in.flags(), in.data_size());
o++;
}
}
for (; o < outputs.size(); ++o) {
outputs[o].set_data(allocator::malloc(outputs[o].nbytes()));
}
}
}
std::tuple<bool, Shape, std::vector<Strides>> compiled_collapse_contiguous_dims(
const std::vector<array>& inputs,
const array& out,
const std::function<bool(size_t)>& is_constant) {
const Shape& shape = out.shape();
bool contiguous = compiled_check_contiguity(inputs, shape);
if (contiguous) {
return {true, shape, {}};
}
std::vector<Strides> strides_vec{out.strides()};
for (size_t i = 0; i < inputs.size(); ++i) {
// Skip constants.
if (is_constant(i)) {
continue;
}
// Skip scalar inputs.
const auto& x = inputs[i];
if (is_scalar(x)) {
continue;
}
// Broadcast the inputs to the output shape.
Strides xstrides;
size_t j = 0;
for (; j < shape.size() - x.ndim(); ++j) {
if (shape[j] == 1) {
xstrides.push_back(out.strides()[j]);
} else {
xstrides.push_back(0);
}
}
for (size_t i = 0; i < x.ndim(); ++i, ++j) {
if (x.shape(i) == 1) {
if (shape[j] == 1) {
xstrides.push_back(out.strides()[j]);
} else {
xstrides.push_back(0);
}
} else {
xstrides.push_back(x.strides()[i]);
}
}
strides_vec.push_back(std::move(xstrides));
}
auto tup = collapse_contiguous_dims(shape, strides_vec, INT32_MAX);
return {false, std::move(std::get<0>(tup)), std::move(std::get<1>(tup))};
}
bool compiled_use_large_index(
const std::vector<array>& inputs,
const std::vector<array>& outputs,
bool contiguous) {
if (contiguous) {
size_t max_size = 0;
for (const auto& in : inputs) {
max_size = std::max(max_size, in.data_size());
}
return max_size > UINT32_MAX;
} else {
size_t max_size = 0;
for (const auto& o : outputs) {
max_size = std::max(max_size, o.size());
}
return max_size > UINT32_MAX;
}
}
} // namespace mlx::core