mirror of
https://github.com/ml-explore/mlx.git
synced 2025-11-02 09:18:11 +08:00
@@ -65,8 +65,8 @@ void Gather::eval_gpu(const std::vector<array>& inputs, array& out) {
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Dtype idx_dtype = nidx > 0 ? inputs[1].dtype() : int32;
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int32_t idx_ndim = nidx > 0 ? inputs[1].ndim() : 0;
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bool large = (nidx > 0 && inputs[1].size() > UINT32_MAX) ||
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(src.size() > UINT32_MAX) || (out.size() > UINT32_MAX);
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bool large = (nidx > 0 && inputs[1].size() > INT32_MAX) ||
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(src.size() > INT32_MAX) || (out.size() > INT32_MAX);
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uint32_t slice_size = std::accumulate(
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slice_sizes_.begin(), slice_sizes_.end(), 1, std::multiplies<uint32_t>());
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@@ -88,7 +88,7 @@ void Gather::eval_gpu(const std::vector<array>& inputs, array& out) {
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dtype_to_cuda_type(idx_dtype),
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nidx,
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ndim,
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large ? "int64_t" : "uint32_t"));
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large ? "int64_t" : "int32_t"));
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}
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}
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return std::make_pair(jit_source_gather, std::move(kernel_names));
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@@ -99,7 +99,7 @@ void Gather::eval_gpu(const std::vector<array>& inputs, array& out) {
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if (large) {
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mod.append_arg<int64_t>(out.size());
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} else {
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mod.append_arg<uint32_t>(out.size());
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mod.append_arg<int32_t>(out.size());
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}
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mod.append_ndim_arg(src.shape());
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mod.append_ndim_arg(src.strides());
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@@ -115,7 +115,7 @@ void Gather::eval_gpu(const std::vector<array>& inputs, array& out) {
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dtype_to_cuda_type(idx_dtype),
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nidx,
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idx_ndim,
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large ? "int64_t" : "uint32_t");
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large ? "int64_t" : "int32_t");
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auto& encoder = cu::get_command_encoder(s);
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for (const auto& in : inputs) {
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@@ -152,14 +152,14 @@ void Scatter::eval_gpu(const std::vector<array>& inputs, array& out) {
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Dtype idx_dtype = nidx > 0 ? inputs[1].dtype() : int32;
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int32_t idx_ndim = nidx > 0 ? inputs[1].ndim() : 0;
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bool large = (nidx > 0 && inputs[1].size() > UINT32_MAX) ||
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(upd.size() > UINT32_MAX) || (out.size() > UINT32_MAX);
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bool large = (nidx > 0 && inputs[1].size() > INT32_MAX) ||
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(upd.size() > INT32_MAX) || (out.size() > INT32_MAX);
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uint32_t upd_post_idx_size = std::accumulate(
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int32_t upd_post_idx_size = std::accumulate(
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upd.shape().begin() + idx_ndim,
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upd.shape().end(),
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1,
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std::multiplies<uint32_t>());
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std::multiplies<int32_t>());
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const char* op = g_scatter_ops[reduce_type_];
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std::string module_name = fmt::format(
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@@ -181,7 +181,7 @@ void Scatter::eval_gpu(const std::vector<array>& inputs, array& out) {
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op,
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nidx,
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ndim,
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large ? "int64_t" : "uint32_t"));
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large ? "int64_t" : "int32_t"));
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}
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}
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return std::make_pair(jit_source_scatter, std::move(kernel_names));
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@@ -192,7 +192,7 @@ void Scatter::eval_gpu(const std::vector<array>& inputs, array& out) {
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if (large) {
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mod.append_arg<int64_t>(upd.size());
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} else {
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mod.append_arg<uint32_t>(upd.size());
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mod.append_arg<int32_t>(upd.size());
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}
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mod.append_ndim_arg(upd.shape());
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mod.append_ndim_arg(upd.strides());
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@@ -200,7 +200,7 @@ void Scatter::eval_gpu(const std::vector<array>& inputs, array& out) {
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if (large) {
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mod.append_arg<int64_t>(upd_post_idx_size);
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} else {
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mod.append_arg<uint32_t>(upd_post_idx_size);
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mod.append_arg<int32_t>(upd_post_idx_size);
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}
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mod.append_ndim_arg(out.shape());
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mod.append_ndim_arg(out.strides());
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@@ -215,7 +215,7 @@ void Scatter::eval_gpu(const std::vector<array>& inputs, array& out) {
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op,
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nidx,
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idx_ndim,
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large ? "int64_t" : "uint32_t");
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large ? "int64_t" : "int32_t");
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auto& encoder = cu::get_command_encoder(s);
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for (const auto& in : inputs) {
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@@ -238,7 +238,7 @@ void GatherAxis::eval_gpu(const std::vector<array>& inputs, array& out) {
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return;
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}
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bool large = idx.size() > UINT32_MAX || src.size() > UINT32_MAX;
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bool large = idx.size() > INT32_MAX || src.size() > INT32_MAX;
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std::string module_name = fmt::format(
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"gather_axis_{}_{}",
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@@ -258,7 +258,7 @@ void GatherAxis::eval_gpu(const std::vector<array>& inputs, array& out) {
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ndim,
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contiguous & 1 ? true : false,
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contiguous & 2 ? true : false,
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large ? "int64_t" : "uint32_t"));
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large ? "int64_t" : "int32_t"));
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}
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}
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}
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@@ -283,9 +283,9 @@ void GatherAxis::eval_gpu(const std::vector<array>& inputs, array& out) {
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mod.append_arg<int64_t>(idx_size_axis);
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mod.append_arg<int64_t>(idx_size_post);
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} else {
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mod.append_arg<uint32_t>(idx_size_pre);
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mod.append_arg<uint32_t>(idx_size_axis);
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mod.append_arg<uint32_t>(idx_size_post);
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mod.append_arg<int32_t>(idx_size_pre);
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mod.append_arg<int32_t>(idx_size_axis);
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mod.append_arg<int32_t>(idx_size_post);
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}
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mod.append_arg(remove_index(idx.shape(), axis_));
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mod.append_arg(remove_index(src.strides(), axis_));
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@@ -302,7 +302,7 @@ void GatherAxis::eval_gpu(const std::vector<array>& inputs, array& out) {
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src.ndim() - 1,
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src.flags().row_contiguous,
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idx.flags().row_contiguous,
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large ? "int64_t" : "uint32_t");
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large ? "int64_t" : "int32_t");
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auto& encoder = cu::get_command_encoder(s);
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for (const auto& in : inputs) {
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@@ -337,7 +337,7 @@ void ScatterAxis::eval_gpu(const std::vector<array>& inputs, array& out) {
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return;
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}
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bool large = idx.size() > UINT32_MAX || src.size() > UINT32_MAX;
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bool large = idx.size() > INT32_MAX || src.size() > INT32_MAX;
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const char* op = reduce_type_ == ScatterAxis::Sum ? "Sum" : "Assign";
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std::string module_name = fmt::format(
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@@ -360,7 +360,7 @@ void ScatterAxis::eval_gpu(const std::vector<array>& inputs, array& out) {
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ndim,
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contiguous & 1 ? true : false,
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contiguous & 2 ? true : false,
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large ? "int64_t" : "uint32_t"));
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large ? "int64_t" : "int32_t"));
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}
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}
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}
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@@ -385,9 +385,9 @@ void ScatterAxis::eval_gpu(const std::vector<array>& inputs, array& out) {
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mod.append_arg<int64_t>(idx_size_axis);
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mod.append_arg<int64_t>(idx_size_post);
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} else {
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mod.append_arg<uint32_t>(idx_size_pre);
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mod.append_arg<uint32_t>(idx_size_axis);
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mod.append_arg<uint32_t>(idx_size_post);
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mod.append_arg<int32_t>(idx_size_pre);
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mod.append_arg<int32_t>(idx_size_axis);
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mod.append_arg<int32_t>(idx_size_post);
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}
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mod.append_arg(remove_index(idx.shape(), axis_));
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mod.append_arg(remove_index(upd.strides(), axis_));
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@@ -405,7 +405,7 @@ void ScatterAxis::eval_gpu(const std::vector<array>& inputs, array& out) {
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idx.ndim() - 1,
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upd.flags().row_contiguous,
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idx.flags().row_contiguous,
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large ? "int64_t" : "uint32_t");
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large ? "int64_t" : "int32_t");
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auto& encoder = cu::get_command_encoder(s);
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for (const auto& in : inputs) {
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