mirror of
https://github.com/ml-explore/mlx.git
synced 2025-12-16 01:49:05 +08:00
redesign for faster cpu/gpu synch (#1869)
* redesign for faster cpu/gpu synch * load + more async CPU * use command encoder API and move more ops to use it * make fence back-end generic + CPU only fence * faster build * fix async eval * fixes + handle temporaries * fix / improve cpu conv * remove unused status, fix siblings * fix extensions * fix * fix no cpu build * format * comments * fix perf regression, remove unecessary abort * fix events, task limit cpu * fix waiting * fix donation / temporaries in normalization
This commit is contained in:
@@ -38,8 +38,7 @@ inline void set_binary_op_output_data(
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const array& a,
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const array& b,
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array& out,
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BinaryOpType bopt,
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bool donate_with_move = false) {
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BinaryOpType bopt) {
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bool b_donatable = is_donatable(b, out);
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bool a_donatable = is_donatable(a, out);
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switch (bopt) {
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@@ -49,11 +48,7 @@ inline void set_binary_op_output_data(
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break;
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case BinaryOpType::ScalarVector:
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if (b_donatable) {
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if (donate_with_move) {
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out.move_shared_buffer(b);
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} else {
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out.copy_shared_buffer(b);
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}
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out.copy_shared_buffer(b);
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} else {
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out.set_data(
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allocator::malloc_or_wait(b.data_size() * out.itemsize()),
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@@ -64,11 +59,7 @@ inline void set_binary_op_output_data(
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break;
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case BinaryOpType::VectorScalar:
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if (a_donatable) {
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if (donate_with_move) {
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out.move_shared_buffer(a);
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} else {
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out.copy_shared_buffer(a);
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}
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out.copy_shared_buffer(a);
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} else {
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out.set_data(
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allocator::malloc_or_wait(a.data_size() * out.itemsize()),
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@@ -79,17 +70,9 @@ inline void set_binary_op_output_data(
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break;
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case BinaryOpType::VectorVector:
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if (a_donatable) {
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if (donate_with_move) {
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out.move_shared_buffer(a);
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} else {
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out.copy_shared_buffer(a);
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}
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out.copy_shared_buffer(a);
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} else if (b_donatable) {
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if (donate_with_move) {
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out.move_shared_buffer(b);
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} else {
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out.copy_shared_buffer(b);
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}
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out.copy_shared_buffer(b);
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} else {
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out.set_data(
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allocator::malloc_or_wait(a.data_size() * out.itemsize()),
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@@ -100,18 +83,10 @@ inline void set_binary_op_output_data(
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break;
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case BinaryOpType::General:
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if (a_donatable && a.flags().row_contiguous && a.size() == out.size()) {
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if (donate_with_move) {
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out.move_shared_buffer(a);
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} else {
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out.copy_shared_buffer(a);
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}
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out.copy_shared_buffer(a);
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} else if (
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b_donatable && b.flags().row_contiguous && b.size() == out.size()) {
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if (donate_with_move) {
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out.move_shared_buffer(b);
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} else {
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out.copy_shared_buffer(b);
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}
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out.copy_shared_buffer(b);
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} else {
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out.set_data(allocator::malloc_or_wait(out.nbytes()));
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}
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@@ -39,7 +39,7 @@ void AsStrided::eval(const std::vector<array>& inputs, array& out) {
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// rely on data_size anyway.
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size_t data_size = out.size();
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return move_or_copy(in, out, strides_, flags, data_size, offset_);
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return out.copy_shared_buffer(in, strides_, flags, data_size, offset_);
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}
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void broadcast(const array& in, array& out) {
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@@ -56,7 +56,7 @@ void broadcast(const array& in, array& out) {
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if (out.size() > in.size()) {
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flags.row_contiguous = flags.col_contiguous = false;
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}
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move_or_copy(in, out, strides, flags, in.data_size());
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out.copy_shared_buffer(in, strides, flags, in.data_size());
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}
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void Broadcast::eval(const std::vector<array>& inputs, array& out) {
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@@ -69,7 +69,7 @@ void BroadcastAxes::eval(const std::vector<array>& inputs, array& out) {
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void Copy::eval(const std::vector<array>& inputs, array& out) {
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assert(inputs.size() == 1);
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move_or_copy(inputs[0], out);
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out.copy_shared_buffer(inputs[0]);
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}
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void CustomTransforms::eval(
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@@ -78,7 +78,7 @@ void CustomTransforms::eval(
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assert(inputs.size() > outputs.size());
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for (int i = 0, j = inputs.size() - outputs.size(); i < outputs.size();
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i++, j++) {
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move_or_copy(inputs[j], outputs[i]);
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outputs[i].copy_shared_buffer(inputs[j]);
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}
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}
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@@ -87,7 +87,7 @@ void Depends::eval(
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std::vector<array>& outputs) {
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assert(inputs.size() > outputs.size());
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for (int i = 0; i < outputs.size(); i++) {
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move_or_copy(inputs[i], outputs[i]);
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outputs[i].copy_shared_buffer(inputs[i]);
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}
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}
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@@ -98,7 +98,7 @@ void ExpandDims::eval(const std::vector<array>& inputs, array& out) {
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for (auto ax : axes_) {
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strides.insert(strides.begin() + ax, 1);
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}
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move_or_copy(in, out, strides, in.flags(), in.data_size());
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out.copy_shared_buffer(in, strides, in.flags(), in.data_size());
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}
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void NumberOfElements::eval(const std::vector<array>& inputs, array& out) {
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@@ -210,7 +210,7 @@ void shared_buffer_reshape(
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auto max_dim = std::max_element(out.shape().begin(), out.shape().end());
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flags.col_contiguous = out.size() <= 1 || out.size() == *max_dim;
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}
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move_or_copy(in, out, out_strides, flags, in.data_size());
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out.copy_shared_buffer(in, out_strides, flags, in.data_size());
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}
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void Split::eval(
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@@ -276,12 +276,12 @@ void Squeeze::eval(const std::vector<array>& inputs, array& out) {
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strides.push_back(in.strides(i));
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}
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}
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move_or_copy(in, out, strides, in.flags(), in.data_size());
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out.copy_shared_buffer(in, strides, in.flags(), in.data_size());
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}
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void StopGradient::eval(const std::vector<array>& inputs, array& out) {
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assert(inputs.size() == 1);
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move_or_copy(inputs[0], out);
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out.copy_shared_buffer(inputs[0]);
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}
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void Transpose::eval(const std::vector<array>& inputs, array& out) {
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@@ -315,7 +315,7 @@ void Transpose::eval(const std::vector<array>& inputs, array& out) {
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b_stride *= out.shape(ri);
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}
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}
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move_or_copy(in, out, out_strides, flags, in.data_size());
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out.copy_shared_buffer(in, out_strides, flags, in.data_size());
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}
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} // namespace mlx::core
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@@ -161,8 +161,7 @@ void compiled_allocate_outputs(
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std::vector<array>& outputs,
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const std::vector<array>& inputs_,
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const std::unordered_set<uintptr_t>& constant_ids_,
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bool contiguous,
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bool move_buffers /* = false */) {
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bool contiguous) {
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if (contiguous) {
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int o = 0;
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Strides strides;
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@@ -178,11 +177,7 @@ void compiled_allocate_outputs(
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if (in.itemsize() == outputs[o].itemsize() && !is_scalar(in) &&
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in.is_donatable() &&
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constant_ids_.find(inputs_[i].id()) == constant_ids_.end()) {
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if (move_buffers) {
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outputs[o++].move_shared_buffer(in);
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} else {
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outputs[o++].copy_shared_buffer(in);
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}
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outputs[o++].copy_shared_buffer(in);
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}
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// Get representative input flags to properly set non-donated outputs
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if (strides.empty() && in.size() == outputs[0].size()) {
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@@ -210,13 +205,8 @@ void compiled_allocate_outputs(
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if (in.flags().row_contiguous && in.size() == outputs[o].size() &&
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in.itemsize() == outputs[o].itemsize() && in.is_donatable() &&
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constant_ids_.find(inputs_[i].id()) == constant_ids_.end()) {
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if (move_buffers) {
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outputs[o].move_shared_buffer(
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in, outputs[o].strides(), in.flags(), in.data_size());
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} else {
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outputs[o].copy_shared_buffer(
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in, outputs[o].strides(), in.flags(), in.data_size());
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}
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outputs[o].copy_shared_buffer(
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in, outputs[o].strides(), in.flags(), in.data_size());
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o++;
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}
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}
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@@ -62,7 +62,6 @@ void compiled_allocate_outputs(
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std::vector<array>& outputs,
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const std::vector<array>& inputs_,
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const std::unordered_set<uintptr_t>& constant_ids_,
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bool contiguous,
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bool move_buffers = false);
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bool contiguous);
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} // namespace mlx::core
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@@ -22,4 +22,25 @@ enum class CopyType {
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GeneralGeneral
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};
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inline bool set_copy_output_data(const array& in, array& out, CopyType ctype) {
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if (ctype == CopyType::Vector) {
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// If the input is donateable, we are doing a vector copy and the types
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// have the same size, then the input buffer can hold the output.
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if (in.is_donatable() && in.itemsize() == out.itemsize()) {
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out.copy_shared_buffer(in);
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return true;
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} else {
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out.set_data(
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allocator::malloc_or_wait(in.data_size() * out.itemsize()),
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in.data_size(),
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in.strides(),
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in.flags());
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return false;
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}
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} else {
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out.set_data(allocator::malloc_or_wait(out.nbytes()));
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return false;
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}
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}
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} // namespace mlx::core
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@@ -3,7 +3,8 @@
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#include <algorithm>
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#include <utility>
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#include "mlx/backend/common/load.h"
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#include "mlx/primitives.h"
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#include "mlx/scheduler.h"
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namespace {
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@@ -26,26 +27,31 @@ void swap_endianness(uint8_t* data_bytes, size_t N) {
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namespace mlx::core {
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void load(
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array& out,
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size_t offset,
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const std::shared_ptr<io::Reader>& reader,
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bool swap_endianness_) {
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reader->read(out.data<char>(), out.nbytes(), offset);
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if (swap_endianness_) {
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switch (out.itemsize()) {
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case 2:
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swap_endianness<2>(out.data<uint8_t>(), out.data_size());
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break;
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case 4:
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swap_endianness<4>(out.data<uint8_t>(), out.data_size());
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break;
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case 8:
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swap_endianness<8>(out.data<uint8_t>(), out.data_size());
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break;
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void Load::eval_cpu(const std::vector<array>& inputs, array& out) {
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out.set_data(allocator::malloc_or_wait(out.nbytes()));
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auto read_task = [out_ptr = out.data<char>(),
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size = out.size(),
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itemsize = out.itemsize(),
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offset = offset_,
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reader = reader_,
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swap_endianness_ = swap_endianness_]() mutable {
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reader->read(out_ptr, size * itemsize, offset);
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if (swap_endianness_) {
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switch (itemsize) {
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case 2:
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swap_endianness<2>(reinterpret_cast<uint8_t*>(out_ptr), size);
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break;
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case 4:
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swap_endianness<4>(reinterpret_cast<uint8_t*>(out_ptr), size);
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break;
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case 8:
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swap_endianness<8>(reinterpret_cast<uint8_t*>(out_ptr), size);
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break;
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}
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}
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}
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};
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auto fut = io::thread_pool().enqueue(std::move(read_task)).share();
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scheduler::enqueue(stream(), [fut = std::move(fut)]() { fut.wait(); });
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}
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} // namespace mlx::core
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@@ -1,14 +0,0 @@
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// Copyright © 2024 Apple Inc.
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#include "mlx/array.h"
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#include "mlx/io/load.h"
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namespace mlx::core {
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void load(
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array& out,
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size_t offset,
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const std::shared_ptr<io::Reader>& reader,
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bool swap_endianess);
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} // namespace mlx::core
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@@ -36,7 +36,7 @@ void shared_buffer_slice(
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flags.col_contiguous = is_col_contiguous;
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flags.contiguous = (no_bsx_size == data_size);
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move_or_copy(in, out, out_strides, flags, data_size, data_offset);
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out.copy_shared_buffer(in, out_strides, flags, data_size, data_offset);
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}
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void slice(
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@@ -36,15 +36,10 @@ inline void set_ternary_op_output_data(
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const array& b,
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const array& c,
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array& out,
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TernaryOpType topt,
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bool donate_with_move = false) {
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auto maybe_donate = [&out, donate_with_move](const array& x) {
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TernaryOpType topt) {
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auto maybe_donate = [&out](const array& x) {
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if (is_donatable(x, out)) {
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if (donate_with_move) {
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out.move_shared_buffer(x);
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} else {
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out.copy_shared_buffer(x);
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}
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out.copy_shared_buffer(x);
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return true;
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}
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return false;
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@@ -4,28 +4,6 @@
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namespace mlx::core {
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void move_or_copy(const array& in, array& out) {
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if (in.is_donatable()) {
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out.move_shared_buffer(in);
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} else {
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out.copy_shared_buffer(in);
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}
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}
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void move_or_copy(
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const array& in,
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array& out,
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const Strides& strides,
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array::Flags flags,
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size_t data_size,
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size_t offset /* = 0 */) {
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if (in.is_donatable()) {
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out.move_shared_buffer(in, strides, flags, data_size, offset);
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} else {
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out.copy_shared_buffer(in, strides, flags, data_size, offset);
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}
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}
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std::tuple<Shape, std::vector<Strides>> collapse_contiguous_dims(
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const Shape& shape,
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const std::vector<Strides>& strides,
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@@ -159,15 +159,6 @@ inline bool is_donatable(const array& in, const array& out) {
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in.buffer_size() <= out.nbytes() + donation_extra;
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}
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void move_or_copy(const array& in, array& out);
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void move_or_copy(
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const array& in,
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array& out,
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const Strides& strides,
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array::Flags flags,
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size_t data_size,
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size_t offset = 0);
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std::pair<bool, Strides> prepare_reshape(const array& in, const array& out);
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void shared_buffer_reshape(
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Block a user