mlx/python/src/indexing.cpp
Jagrit Digani a5681ebc52
Update set item (#861)
* Update mlx_set_item to handle regular slices without expanding

* Refactor ellipsis handling

* Route mlx_set_item to slice_update where possible

* Update mlx_scatter_args_slice

* Don't route to gather if no array indices
2024-03-21 02:48:13 -07:00

924 lines
28 KiB
C++

// Copyright © 2023-2024 Apple Inc.
#include <numeric>
#include <sstream>
#include "python/src/indexing.h"
#include "mlx/ops.h"
bool is_none_slice(const nb::slice& in_slice) {
return (
nb::getattr(in_slice, "start").is_none() &&
nb::getattr(in_slice, "stop").is_none() &&
nb::getattr(in_slice, "step").is_none());
}
int get_slice_int(nb::object obj, int default_val) {
if (!obj.is_none()) {
if (!nb::isinstance<nb::int_>(obj)) {
throw std::invalid_argument("Slice indices must be integers or None.");
}
return nb::cast<int>(nb::cast<nb::int_>(obj));
}
return default_val;
}
void get_slice_params(
int& starts,
int& ends,
int& strides,
const nb::slice& in_slice,
int axis_size) {
// Following numpy's convention
// Assume n is the number of elements in the dimension being sliced.
// Then, if i is not given it defaults to 0 for k > 0 and n - 1 for
// k < 0 . If j is not given it defaults to n for k > 0 and -n-1 for
// k < 0 . If k is not given it defaults to 1
strides = get_slice_int(nb::getattr(in_slice, "step"), 1);
starts = get_slice_int(
nb::getattr(in_slice, "start"), strides < 0 ? axis_size - 1 : 0);
ends = get_slice_int(
nb::getattr(in_slice, "stop"), strides < 0 ? -axis_size - 1 : axis_size);
}
array get_int_index(nb::object idx, int axis_size) {
int idx_ = nb::cast<int>(idx);
idx_ = (idx_ < 0) ? idx_ + axis_size : idx_;
return array(idx_, uint32);
}
bool is_valid_index_type(const nb::object& obj) {
return nb::isinstance<nb::slice>(obj) || nb::isinstance<nb::int_>(obj) ||
nb::isinstance<array>(obj) || obj.is_none() || nb::ellipsis().is(obj);
}
array mlx_get_item_slice(const array& src, const nb::slice& in_slice) {
// Check input and raise error if 0 dim for parity with np
if (src.ndim() == 0) {
throw std::invalid_argument(
"too many indices for array: array is 0-dimensional");
}
// Return a copy of the array if none slice is request
if (is_none_slice(in_slice)) {
return src;
}
std::vector<int> starts(src.ndim(), 0);
std::vector<int> ends = src.shape();
std::vector<int> strides(src.ndim(), 1);
// Check and update slice params
get_slice_params(starts[0], ends[0], strides[0], in_slice, ends[0]);
return slice(src, starts, ends, strides);
}
array mlx_get_item_array(const array& src, const array& indices) {
// Check input and raise error if 0 dim for parity with np
if (src.ndim() == 0) {
throw std::invalid_argument(
"too many indices for array: array is 0-dimensional");
}
if (indices.dtype() == bool_) {
throw std::invalid_argument("boolean indices are not yet supported");
}
// If only one input array is mentioned, we set axis=0 in take
// for parity with np
return take(src, indices, 0);
}
array mlx_get_item_int(const array& src, const nb::int_& idx) {
// Check input and raise error if 0 dim for parity with np
if (src.ndim() == 0) {
throw std::invalid_argument(
"too many indices for array: array is 0-dimensional");
}
// If only one input idx is mentioned, we set axis=0 in take
// for parity with np
return take(src, get_int_index(idx, src.shape(0)), 0);
}
array mlx_gather_nd(
array src,
const std::vector<nb::object>& indices,
bool gather_first,
int& max_dims) {
max_dims = 0;
std::vector<array> gather_indices;
std::vector<bool> is_slice(indices.size(), false);
int num_slices = 0;
// gather all the arrays
for (int i = 0; i < indices.size(); i++) {
auto& idx = indices[i];
if (nb::isinstance<nb::slice>(idx)) {
int start, end, stride;
get_slice_params(
start, end, stride, nb::cast<nb::slice>(idx), src.shape(i));
// Handle negative indices
start = (start < 0) ? start + src.shape(i) : start;
end = (end < 0) ? end + src.shape(i) : end;
gather_indices.push_back(arange(start, end, stride, uint32));
num_slices++;
is_slice[i] = true;
} else if (nb::isinstance<nb::int_>(idx)) {
gather_indices.push_back(get_int_index(idx, src.shape(i)));
} else if (nb::isinstance<array>(idx)) {
auto arr = nb::cast<array>(idx);
max_dims = std::max(static_cast<int>(arr.ndim()), max_dims);
gather_indices.push_back(arr);
}
}
// reshape them so that the int/array indices are first
if (gather_first) {
int slice_index = 0;
for (int i = 0; i < gather_indices.size(); i++) {
if (is_slice[i]) {
std::vector<int> index_shape(max_dims + num_slices, 1);
index_shape[max_dims + slice_index] = gather_indices[i].shape(0);
gather_indices[i] = reshape(gather_indices[i], index_shape);
slice_index++;
} else {
std::vector<int> index_shape = gather_indices[i].shape();
index_shape.insert(index_shape.end(), num_slices, 1);
gather_indices[i] = reshape(gather_indices[i], index_shape);
}
}
} else {
// reshape them so that the int/array indices are last
for (int i = 0; i < gather_indices.size(); i++) {
if (i < num_slices) {
std::vector<int> index_shape(max_dims + num_slices, 1);
index_shape[i] = gather_indices[i].shape(0);
gather_indices[i] = reshape(gather_indices[i], index_shape);
}
}
}
// Do the gather
std::vector<int> axes(indices.size());
std::iota(axes.begin(), axes.end(), 0);
std::vector<int> slice_sizes = src.shape();
std::fill(slice_sizes.begin(), slice_sizes.begin() + indices.size(), 1);
src = gather(src, gather_indices, axes, slice_sizes);
// Squeeze the dims
std::vector<int> out_shape;
out_shape.insert(
out_shape.end(),
src.shape().begin(),
src.shape().begin() + max_dims + num_slices);
out_shape.insert(
out_shape.end(),
src.shape().begin() + max_dims + num_slices + indices.size(),
src.shape().end());
src = reshape(src, out_shape);
return src;
}
auto mlx_expand_ellipsis(
const std::vector<int>& shape,
const nb::tuple& entries) {
std::vector<nb::object> indices;
// Go over all entries and note the position of ellipsis
int non_none_indices_before = 0;
int non_none_indices_after = 0;
std::vector<nb::object> r_indices;
int i = 0;
// Start from dimension 0 till we hit an ellipsis
for (; i < entries.size(); i++) {
auto idx = entries[i];
if (!is_valid_index_type(idx)) {
throw std::invalid_argument(
"Cannot index mlx array using the given type yet");
}
if (!nb::ellipsis().is(idx)) {
indices.push_back(idx);
non_none_indices_before += !idx.is_none();
} else {
break;
}
}
// If we do hit an ellipsis, collect indices from the back
for (int j = entries.size() - 1; j > i; j--) {
auto idx = entries[j];
if (!is_valid_index_type(idx)) {
throw std::invalid_argument(
"Cannot index mlx array using the given type yet");
}
if (nb::ellipsis().is(idx)) {
throw std::invalid_argument(
"An index can only have a single ellipsis (...)");
}
r_indices.push_back(idx);
non_none_indices_after += !idx.is_none();
}
// Count up the number of non none indices
int non_none_indices = non_none_indices_before + non_none_indices_after;
// Expand ellipsis
for (int axis = non_none_indices_before;
axis < shape.size() - non_none_indices_after;
axis++) {
indices.push_back(nb::slice(0, shape[axis], 1));
non_none_indices++;
}
// Insert indices collected after the ellipsis
indices.insert(indices.end(), r_indices.rbegin(), r_indices.rend());
return std::make_pair(non_none_indices, indices);
}
array mlx_get_item_nd(array src, const nb::tuple& entries) {
// No indices make this a noop
if (entries.size() == 0) {
return src;
}
// The plan is as follows:
// 1. Replace the ellipsis with a series of slice(None)
// 2. Loop over the indices and calculate the gather indices
// 3. Calculate the remaining slices and reshapes
// Ellipsis handling
auto [non_none_indices, indices] = mlx_expand_ellipsis(src.shape(), entries);
// Check for the number of indices passed
if (non_none_indices > src.ndim()) {
std::ostringstream msg;
msg << "Too many indices for array with " << src.ndim() << "dimensions.";
throw std::invalid_argument(msg.str());
}
// Gather handling
//
// Check whether we have arrays or integer indices and delegate to gather_nd
// after removing the slices at the end and all Nones.
std::vector<nb::object> remaining_indices;
bool have_array = false;
{
// First check whether the results of gather are going to be 1st or
// normally in between.
bool have_non_array = false;
bool gather_first = false;
for (auto& idx : indices) {
if (nb::isinstance<array>(idx) || (nb::isinstance<nb::int_>(idx))) {
if (have_array && have_non_array) {
gather_first = true;
break;
}
have_array = true;
} else {
have_non_array |= have_array;
}
}
int n_arr = 0;
for (auto& idx : indices) {
n_arr += nb::isinstance<array>(idx);
}
have_array &= n_arr > 0;
if (have_array) {
int last_array;
// Then find the last array
for (last_array = indices.size() - 1; last_array >= 0; last_array--) {
auto& idx = indices[last_array];
if (nb::isinstance<array>(idx) || nb::isinstance<nb::int_>(idx)) {
break;
}
}
std::vector<nb::object> gather_indices;
for (int i = 0; i <= last_array; i++) {
auto& idx = indices[i];
if (!idx.is_none()) {
gather_indices.push_back(idx);
}
}
int max_dims;
src = mlx_gather_nd(src, gather_indices, gather_first, max_dims);
// Reassemble the indices for the slicing or reshaping if there are any
if (gather_first) {
for (int i = 0; i < max_dims; i++) {
remaining_indices.push_back(
nb::slice(nb::none(), nb::none(), nb::none()));
}
for (int i = 0; i < last_array; i++) {
auto& idx = indices[i];
if (idx.is_none()) {
remaining_indices.push_back(indices[i]);
} else if (nb::isinstance<nb::slice>(idx)) {
remaining_indices.push_back(
nb::slice(nb::none(), nb::none(), nb::none()));
}
}
for (int i = last_array + 1; i < indices.size(); i++) {
remaining_indices.push_back(indices[i]);
}
} else {
for (int i = 0; i < indices.size(); i++) {
auto& idx = indices[i];
if (nb::isinstance<array>(idx) || nb::isinstance<nb::int_>(idx)) {
break;
} else if (idx.is_none()) {
remaining_indices.push_back(idx);
} else {
remaining_indices.push_back(
nb::slice(nb::none(), nb::none(), nb::none()));
}
}
for (int i = 0; i < max_dims; i++) {
remaining_indices.push_back(
nb::slice(nb::none(), nb::none(), nb::none()));
}
for (int i = last_array + 1; i < indices.size(); i++) {
remaining_indices.push_back(indices[i]);
}
}
}
}
if (have_array && remaining_indices.empty()) {
return src;
}
if (remaining_indices.empty()) {
remaining_indices = indices;
}
bool squeeze_needed = false;
// Slice handling
{
std::vector<int> starts(src.ndim(), 0);
std::vector<int> ends = src.shape();
std::vector<int> strides(src.ndim(), 1);
int axis = 0;
for (auto& idx : remaining_indices) {
if (!idx.is_none()) {
if (!have_array && nb::isinstance<nb::int_>(idx)) {
int st = nb::cast<int>(idx);
st = (st < 0) ? st + src.shape(axis) : st;
starts[axis] = st;
ends[axis] = st + 1;
squeeze_needed = true;
} else {
get_slice_params(
starts[axis],
ends[axis],
strides[axis],
nb::cast<nb::slice>(idx),
ends[axis]);
}
axis++;
}
}
src = slice(src, starts, ends, strides);
}
// Unsqueeze handling
if (remaining_indices.size() > src.ndim() || squeeze_needed) {
std::vector<int> out_shape;
int axis = 0;
for (auto& idx : remaining_indices) {
if (idx.is_none()) {
out_shape.push_back(1);
} else if (squeeze_needed && nb::isinstance<nb::int_>(idx)) {
axis++;
} else {
out_shape.push_back(src.shape(axis++));
}
}
src = reshape(src, out_shape);
}
return src;
}
array mlx_get_item(const array& src, const nb::object& obj) {
if (nb::isinstance<nb::slice>(obj)) {
return mlx_get_item_slice(src, nb::cast<nb::slice>(obj));
} else if (nb::isinstance<array>(obj)) {
return mlx_get_item_array(src, nb::cast<array>(obj));
} else if (nb::isinstance<nb::int_>(obj)) {
return mlx_get_item_int(src, nb::cast<nb::int_>(obj));
} else if (nb::isinstance<nb::tuple>(obj)) {
return mlx_get_item_nd(src, nb::cast<nb::tuple>(obj));
} else if (nb::isinstance<nb::ellipsis>(obj)) {
return src;
} else if (obj.is_none()) {
std::vector<int> s(1, 1);
s.insert(s.end(), src.shape().begin(), src.shape().end());
return reshape(src, s);
}
throw std::invalid_argument("Cannot index mlx array using the given type.");
}
std::tuple<std::vector<array>, array, std::vector<int>> mlx_scatter_args_int(
const array& src,
const nb::int_& idx,
const array& update) {
if (src.ndim() == 0) {
throw std::invalid_argument(
"too many indices for array: array is 0-dimensional");
}
// Remove any leading singleton dimensions from the update
// and then broadcast update to shape of src[0, ...]
int s = 0;
for (; s < update.ndim() && update.shape(s) == 1; s++)
;
auto up_shape =
std::vector<int>(update.shape().begin() + s, update.shape().end());
auto shape = src.shape();
shape[0] = 1;
return {
{get_int_index(idx, src.shape(0))},
broadcast_to(reshape(update, up_shape), shape),
{0}};
}
std::tuple<std::vector<array>, array, std::vector<int>> mlx_scatter_args_array(
const array& src,
const array& indices,
const array& update) {
if (src.ndim() == 0) {
throw std::invalid_argument(
"too many indices for array: array is 0-dimensional");
}
// Remove any leading singleton dimensions from the update
int s = 0;
for (; s < update.ndim() && update.shape(s) == 1; s++)
;
auto up_shape =
std::vector<int>(update.shape().begin() + s, update.shape().end());
auto up = reshape(update, up_shape);
// The update shape must broadcast with indices.shape + [1] + src.shape[1:]
up_shape = indices.shape();
up_shape.insert(up_shape.end(), src.shape().begin() + 1, src.shape().end());
up = broadcast_to(up, up_shape);
up_shape.insert(up_shape.begin() + indices.ndim(), 1);
up = reshape(up, up_shape);
return {{indices}, up, {0}};
}
std::tuple<std::vector<array>, array, std::vector<int>> mlx_scatter_args_slice(
const array& src,
const nb::slice& in_slice,
const array& update) {
// Check input and raise error if 0 dim for parity with np
if (src.ndim() == 0) {
throw std::invalid_argument(
"too many indices for array: array is 0-dimensional");
}
// If none slice is requested broadcast the update
// to the src size and return it.
if (is_none_slice(in_slice)) {
int s = 0;
for (; s < update.ndim() && update.shape(s) == 1; s++)
;
auto up_shape =
std::vector<int>(update.shape().begin() + s, update.shape().end());
return {{}, broadcast_to(reshape(update, up_shape), src.shape()), {}};
}
int start = 0;
int end = src.shape(0);
int stride = 1;
// Check and update slice params
get_slice_params(start, end, stride, in_slice, end);
// If simple stride
if (stride == 1) {
// Squeeze out singleton dims from the start of update
int s = 0;
for (; s < update.ndim() && update.shape(s) == 1; s++)
;
auto up_shape =
std::vector<int>(update.shape().begin() + s, update.shape().end());
auto up = reshape(update, up_shape);
// Build array to mark start of slice
auto idx = array({start}, {1}, uint32);
// Get slice size
int slice_size = (end - start);
// Broadcast update to slide size
std::vector<int> up_shape_broadcast = {1, slice_size};
up_shape_broadcast.insert(
up_shape_broadcast.end(), src.shape().begin() + 1, src.shape().end());
up = broadcast_to(update, up_shape_broadcast);
auto indices = std::vector<array>{idx};
auto axes = std::vector<int>{0};
return {indices, up, axes};
}
return mlx_scatter_args_array(
src, arange(start, end, stride, uint32), update);
}
std::tuple<std::vector<array>, array, std::vector<int>> mlx_scatter_args_nd(
const array& src,
const nb::tuple& entries,
const array& update) {
// Expand ellipses into a series of ':' slices
auto [non_none_indices, indices] = mlx_expand_ellipsis(src.shape(), entries);
if (non_none_indices > src.ndim()) {
std::ostringstream msg;
msg << "Too many indices for array with " << src.ndim() << "dimensions.";
throw std::invalid_argument(msg.str());
}
// Remove leading singletons dimensions from the update
int s = 0;
for (; s < update.ndim() && update.shape(s) == 1; s++) {
};
auto up_shape =
std::vector<int>(update.shape().begin() + s, update.shape().end());
auto up = reshape(update, up_shape);
// If no non-None indices return the broadcasted update
if (non_none_indices == 0) {
return {{}, broadcast_to(up, src.shape()), {}};
}
// Analyse the types of the indices
unsigned long max_dim = 0;
bool arrays_first = false;
int num_none = 0;
int num_slices = 0;
int num_arrays = 0;
int num_strided_slices = 0;
{
bool have_array = false;
bool have_non_array = false;
for (auto& idx : indices) {
if (idx.is_none()) {
have_non_array = have_array;
num_none++;
} else if (nb::isinstance<nb::slice>(idx)) {
have_non_array = have_array;
num_slices++;
auto slice = nb::cast<nb::slice>(idx);
int stride = get_slice_int(nb::getattr(slice, "step"), 1);
num_strided_slices += (stride != 1);
} else if (nb::isinstance<array>(idx)) {
have_array = true;
if (have_array && have_non_array) {
arrays_first = true;
}
max_dim = std::max(nb::cast<array>(idx).ndim(), max_dim);
num_arrays++;
}
}
}
// We have index dims for the arrays, strided slices (implemented as arrays),
// none
int idx_ndim = max_dim + num_strided_slices + num_none;
// If we have simple non-strided slices, we also attach an index for that
idx_ndim += (num_slices < num_strided_slices);
// Go over each index type and translate to the needed scatter args
std::vector<array> arr_indices;
int slice_num = 0;
int array_num = 0;
int ax = 0;
// We collect the shapes of the slices and updates during this process
std::vector<int> update_shape(non_none_indices, 1);
std::vector<int> slice_shapes;
for (int i = 0; i < indices.size(); ++i) {
auto& pyidx = indices[i];
if (nb::isinstance<nb::slice>(pyidx)) {
int start, end, stride;
auto axis_size = src.shape(ax++);
get_slice_params(
start, end, stride, nb::cast<nb::slice>(pyidx), axis_size);
// Handle negative indices
start = (start < 0) ? start + axis_size : start;
end = (end < 0) ? end + axis_size : end;
std::vector<int> idx_shape(idx_ndim, 1);
// If it's a simple slice, we only need to add the start index
if (stride == 1) {
auto idx = array({start}, idx_shape, uint32);
slice_shapes.push_back(end - start);
arr_indices.push_back(idx);
}
// Otherwise we expand the slice into indices using arange
else {
auto idx = arange(start, end, stride, uint32);
auto loc = slice_num + (arrays_first ? max_dim : 0);
slice_num++;
idx_shape[loc] = idx.size();
slice_shapes.push_back(idx.size());
arr_indices.push_back(reshape(idx, idx_shape));
}
// Add the shape to the update
update_shape[ax - 1] = slice_shapes.back();
} else if (nb::isinstance<nb::int_>(pyidx)) {
// Add index to arrays
arr_indices.push_back(get_int_index(pyidx, src.shape(ax++)));
// Add the shape to the update
update_shape[ax - 1] = 1;
} else if (pyidx.is_none()) {
// We only use the None's for bookeeping dimensions
slice_num++;
} else if (nb::isinstance<array>(pyidx)) {
ax++;
auto idx = nb::cast<array>(pyidx);
std::vector<int> idx_shape(idx_ndim, 1);
// Place the arrays in the correct dimension
int st = (!arrays_first) * slice_num + max_dim - idx.ndim();
for (int j = 0; j < idx.ndim(); j++) {
idx_shape[st + j] = idx.shape()[j];
}
arr_indices.push_back(reshape(idx, idx_shape));
if (!arrays_first && ++array_num == num_arrays) {
slice_num += max_dim;
}
// Add the shape to the update
update_shape[ax - 1] = 1;
} else {
throw std::invalid_argument(
"Cannot index mlx array using the given type yet");
}
}
// Broadcast the update to the indices and slices
arr_indices = broadcast_arrays(arr_indices);
auto up_shape_broadcast = arr_indices[0].shape();
up_shape_broadcast.insert(
up_shape_broadcast.end(), slice_shapes.begin(), slice_shapes.end());
up_shape_broadcast.insert(
up_shape_broadcast.end(),
src.shape().begin() + non_none_indices,
src.shape().end());
up = broadcast_to(up, up_shape_broadcast);
// Reshape the update with the size-1 dims for the int and array indices
auto up_reshape = arr_indices[0].shape();
up_reshape.insert(up_reshape.end(), update_shape.begin(), update_shape.end());
up_reshape.insert(
up_reshape.end(),
src.shape().begin() + non_none_indices,
src.shape().end());
up = reshape(up, up_reshape);
// Collect axes
std::vector<int> axes(arr_indices.size(), 0);
std::iota(axes.begin(), axes.end(), 0);
return {arr_indices, up, axes};
}
std::tuple<std::vector<array>, array, std::vector<int>>
mlx_compute_scatter_args(
const array& src,
const nb::object& obj,
const ScalarOrArray& v) {
auto vals = to_array(v, src.dtype());
if (nb::isinstance<nb::slice>(obj)) {
return mlx_scatter_args_slice(src, nb::cast<nb::slice>(obj), vals);
} else if (nb::isinstance<array>(obj)) {
return mlx_scatter_args_array(src, nb::cast<array>(obj), vals);
} else if (nb::isinstance<nb::int_>(obj)) {
return mlx_scatter_args_int(src, nb::cast<nb::int_>(obj), vals);
} else if (nb::isinstance<nb::tuple>(obj)) {
return mlx_scatter_args_nd(src, nb::cast<nb::tuple>(obj), vals);
} else if (obj.is_none()) {
return {{}, broadcast_to(vals, src.shape()), {}};
}
throw std::invalid_argument("Cannot index mlx array using the given type.");
}
auto mlx_slice_update(
const array& src,
const nb::object& obj,
const ScalarOrArray& v) {
// Can't route to slice update if not slice or tuple
if (src.ndim() == 0 ||
(!nb::isinstance<nb::slice>(obj) && !nb::isinstance<nb::tuple>(obj))) {
return std::make_pair(false, src);
}
// Should be able to route to slice update
// Pre process tuple
auto upd = to_array(v, src.dtype());
// Remove leading singletons dimensions from the update
int s = 0;
for (; s < upd.ndim() && upd.shape(s) == 1; s++) {
};
auto up_shape = std::vector<int>(upd.shape().begin() + s, upd.shape().end());
up_shape = up_shape.empty() ? std::vector{1} : up_shape;
auto up = reshape(upd, up_shape);
// Build slice update params
std::vector<int> starts(src.ndim(), 0);
std::vector<int> stops = src.shape();
std::vector<int> strides(src.ndim(), 1);
// If it's just a simple slice, just do a slice update and return
if (nb::isinstance<nb::slice>(obj)) {
// Read slice arguments
get_slice_params(
starts[0],
stops[0],
strides[0],
nb::cast<nb::slice>(obj),
src.shape(0));
// Do slice update
auto out = slice_update(src, up, starts, stops, strides);
return std::make_pair(true, out);
}
// It must be a tuple
auto entries = nb::cast<nb::tuple>(obj);
// Can't route to slice update if any arrays are present
for (int i = 0; i < entries.size(); i++) {
auto idx = entries[i];
if (nb::isinstance<array>(idx)) {
return std::make_pair(false, src);
}
}
// Expand ellipses into a series of ':' slices
auto [non_none_indices, indices] = mlx_expand_ellipsis(src.shape(), entries);
// Dimension check
if (non_none_indices > src.ndim()) {
std::ostringstream msg;
msg << "Too many indices for array with " << src.ndim() << "dimensions.";
throw std::invalid_argument(msg.str());
}
// If no non-None indices return the broadcasted update
if (non_none_indices == 0) {
return std::make_pair(true, broadcast_to(up, src.shape()));
}
// Process entries
std::vector<int> upd_expand_dims;
int ax = 0;
for (int i = 0; i < indices.size(); ++i) {
auto& pyidx = indices[i];
if (nb::isinstance<nb::slice>(pyidx)) {
get_slice_params(
starts[ax],
stops[ax],
strides[ax],
nb::cast<nb::slice>(pyidx),
src.shape(ax));
ax++;
} else if (nb::isinstance<nb::int_>(pyidx)) {
int st = nb::cast<int>(pyidx);
st = (st < 0) ? st + src.shape(ax) : st;
starts[ax] = st;
stops[ax] = st + 1;
if (src.ndim() - ax < up.ndim()) {
upd_expand_dims.push_back(ax - src.ndim());
}
ax++;
}
}
up = expand_dims(up, upd_expand_dims);
auto out = slice_update(src, up, starts, stops, strides);
return std::make_pair(true, out);
}
void mlx_set_item(array& src, const nb::object& obj, const ScalarOrArray& v) {
auto [success, out] = mlx_slice_update(src, obj, v);
if (success) {
src.overwrite_descriptor(out);
return;
}
auto [indices, updates, axes] = mlx_compute_scatter_args(src, obj, v);
if (indices.size() > 0) {
auto out = scatter(src, indices, updates, axes);
src.overwrite_descriptor(out);
} else {
src.overwrite_descriptor(updates);
}
}
array mlx_add_item(
const array& src,
const nb::object& obj,
const ScalarOrArray& v) {
auto [indices, updates, axes] = mlx_compute_scatter_args(src, obj, v);
if (indices.size() > 0) {
return scatter_add(src, indices, updates, axes);
} else {
return src + updates;
}
}
array mlx_subtract_item(
const array& src,
const nb::object& obj,
const ScalarOrArray& v) {
auto [indices, updates, axes] = mlx_compute_scatter_args(src, obj, v);
if (indices.size() > 0) {
return scatter_add(src, indices, -updates, axes);
} else {
return src - updates;
}
}
array mlx_multiply_item(
const array& src,
const nb::object& obj,
const ScalarOrArray& v) {
auto [indices, updates, axes] = mlx_compute_scatter_args(src, obj, v);
if (indices.size() > 0) {
return scatter_prod(src, indices, updates, axes);
} else {
return src * updates;
}
}
array mlx_divide_item(
const array& src,
const nb::object& obj,
const ScalarOrArray& v) {
auto [indices, updates, axes] = mlx_compute_scatter_args(src, obj, v);
if (indices.size() > 0) {
return scatter_prod(src, indices, reciprocal(updates), axes);
} else {
return src / updates;
}
}
array mlx_maximum_item(
const array& src,
const nb::object& obj,
const ScalarOrArray& v) {
auto [indices, updates, axes] = mlx_compute_scatter_args(src, obj, v);
if (indices.size() > 0) {
return scatter_max(src, indices, updates, axes);
} else {
return maximum(src, updates);
}
}
array mlx_minimum_item(
const array& src,
const nb::object& obj,
const ScalarOrArray& v) {
auto [indices, updates, axes] = mlx_compute_scatter_args(src, obj, v);
if (indices.size() > 0) {
return scatter_min(src, indices, updates, axes);
} else {
return minimum(src, updates);
}
}