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Add tidy fixes #5268

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20 changes: 8 additions & 12 deletions fbgemm_gpu/include/fbgemm_gpu/split_embeddings_cache/raw_embedding_streamer.h
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Original file line number Diff line number Diff line change
Expand Up @@ -22,18 +22,14 @@ struct StreamQueueItem {
std::optional<at::Tensor> identities;
std::optional<at::Tensor> runtime_meta;
at::Tensor count;
StreamQueueItem(
at::Tensor src_indices,
at::Tensor src_weights,
std::optional<at::Tensor> src_identities,
std::optional<at::Tensor> src_runtime_meta,
at::Tensor src_count) {
indices = std::move(src_indices);
weights = std::move(src_weights);
identities = std::move(src_identities);
runtime_meta = std::move(src_runtime_meta);
count = std::move(src_count);
}
StreamQueueItem(at::Tensor src_indices, at::Tensor src_weights,
std::optional<at::Tensor> src_identities,
std::optional<at::Tensor> src_runtime_meta,
at::Tensor src_count)
: indices(std::move(src_indices)), count(std::move(src_count)),
identities(std::move(src_identities)),
runtime_meta(std::move(src_runtime_meta)),
weights(std::move(src_weights)) {}
};

class RawEmbeddingStreamer : public torch::jit::CustomClassHolder {
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2 changes: 1 addition & 1 deletion fbgemm_gpu/include/fbgemm_gpu/utils/tensor_accessor.h
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Expand Up @@ -327,7 +327,7 @@ class PackedTensorAccessor
}

protected:
size_t numel_;
size_t numel_{};
char name_[NAME_MAX_LEN];
char context_[CONTEXT_MAX_LEN];

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2 changes: 1 addition & 1 deletion fbgemm_gpu/src/config/feature_gates.cpp
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Expand Up @@ -31,7 +31,7 @@ std::string to_string(const FeatureGateName& value) {
return "UNKNOWN";
}

bool ev_check_key(const std::string& key) {
static bool ev_check_key(const std::string& key) {
const auto env_var = "FBGEMM_" + key;

const auto value = std::getenv(env_var.c_str());
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12 changes: 5 additions & 7 deletions fbgemm_gpu/src/embedding_inplace_ops/embedding_inplace_update_cpu.cpp
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Expand Up @@ -23,7 +23,7 @@ using Tensor = at::Tensor;
namespace fbgemm_gpu {

template <typename index_t>
void embedding_inplace_update_cpu_kernel(
static void embedding_inplace_update_cpu_kernel(
at::TensorAccessor<uint8_t, 1> dev_weights,
at::TensorAccessor<uint8_t, 1> uvm_weights,
const at::TensorAccessor<int32_t, 1>& weights_placements,
Expand Down Expand Up @@ -151,9 +151,9 @@ void dram_kv_embedding_inplace_update_cpu(

const uint8_t* weights_tys_ptr = weights_tys.data_ptr<uint8_t>();
const int32_t* D_offsets_ptr = D_offsets.data_ptr<int32_t>();
const uint8_t* update_weights_ptr = update_weights.data_ptr<uint8_t>();
uint8_t* update_weights_ptr = update_weights.mutable_data_ptr<uint8_t>();
const int32_t* update_table_idx_ptr = update_table_idx.data_ptr<int32_t>();
const int64_t* update_row_idx_ptr = update_row_idx.data_ptr<int64_t>();
int64_t* update_row_idx_ptr = update_row_idx.mutable_data_ptr<int64_t>();
const int64_t* update_offsets_ptr = update_offsets.data_ptr<int64_t>();

int64_t window_start = 0;
Expand All @@ -172,15 +172,13 @@ void dram_kv_embedding_inplace_update_cpu(
int32_t D_bytes =
nbit::padded_row_size_in_bytes(D, weight_ty, row_alignment);

uint8_t* batched_weights_ptr = const_cast<uint8_t*>(
update_weights_ptr + update_offsets_ptr[window_start]);
uint8_t* batched_weights_ptr = update_weights_ptr + update_offsets_ptr[window_start];
auto weights_tensor = at::from_blob(
batched_weights_ptr,
{window_size, D_bytes},
at::TensorOptions().dtype(at::kByte));

int64_t* row_ids_ptr =
const_cast<int64_t*>(update_row_idx_ptr + window_start);
int64_t* row_ids_ptr = update_row_idx_ptr + window_start;
auto row_id_tensor = at::from_blob(
row_ids_ptr, {window_size}, at::TensorOptions().dtype(at::kLong));

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2 changes: 1 addition & 1 deletion fbgemm_gpu/src/faster_hash_ops/faster_hash.cpp
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Expand Up @@ -263,7 +263,7 @@ std::tuple<Tensor, Tensor> create_zch_buffer_cpu(
return {identity, metadata};
}

void zero_collision_hash_cpu_out(
static void zero_collision_hash_cpu_out(
Tensor& output,
const Tensor& input,
const Tensor& identities,
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14 changes: 7 additions & 7 deletions fbgemm_gpu/src/input_combine_ops/input_combine_cpu.cpp
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Expand Up @@ -27,7 +27,7 @@ using Tensor = at::Tensor;

namespace fbgemm_gpu {

void _cat_int_tensors_out(
static void _cat_int_tensors_out(
Tensor& combined_tensors,
const std::vector<Tensor>& tensor_list,
int64_t total_num,
Expand Down Expand Up @@ -82,7 +82,7 @@ void _cat_int_tensors_out(
}
}

Tensor _cat_int_tensors(
static Tensor _cat_int_tensors(
const std::vector<Tensor>& tensor_list,
int64_t total_num,
bool use_pin_memory,
Expand All @@ -107,7 +107,7 @@ Tensor _cat_int_tensors(
return combined_tensors;
}

Tensor _cat_int_tensors_with_padding(
static Tensor _cat_int_tensors_with_padding(
const std::vector<Tensor>& tensor_list,
int64_t total_num,
bool use_pin_memory,
Expand Down Expand Up @@ -140,7 +140,7 @@ Tensor _cat_int_tensors_with_padding(
return combined_tensors;
}

void _cat_per_sample_weights_list_out(
static void _cat_per_sample_weights_list_out(
Tensor& out,
const std::vector<Tensor>& per_sample_weights,
const std::vector<Tensor>& indices_list,
Expand Down Expand Up @@ -178,7 +178,7 @@ void _cat_per_sample_weights_list_out(
}
}

Tensor _cat_per_sample_weights_list(
static Tensor _cat_per_sample_weights_list(
const std::vector<Tensor>& per_sample_weights,
const std::vector<Tensor>& indices_list,
int64_t total_num,
Expand Down Expand Up @@ -375,7 +375,7 @@ void tbe_input_combine_with_length_cpu_out(
combined_per_sample_weights.resize_({0});
}

std::tuple<Tensor, Tensor, Tensor> tbe_input_combine_with_length_cpu(
static std::tuple<Tensor, Tensor, Tensor> tbe_input_combine_with_length_cpu(
const std::vector<Tensor>& indices_list,
const std::vector<Tensor>& lengths_list,
const std::vector<Tensor>& per_sample_weights) {
Expand Down Expand Up @@ -518,7 +518,7 @@ std::tuple<Tensor, Tensor, Tensor> padding_fused_tbe_input_combine_cpu(
/// @param lengths_list list of lengths.
/// @param per_sample_weights list of per_sample_weights
/// @return tuple of combined indices, lengths, and per_sample_weights
std::tuple<Tensor, Tensor, Tensor>
static std::tuple<Tensor, Tensor, Tensor>
padding_fused_tbe_input_combine_with_length_cpu(
const std::vector<Tensor>& indices_list,
const std::vector<Tensor>& lengths_list,
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6 changes: 3 additions & 3 deletions fbgemm_gpu/src/input_combine_ops/input_combine_gpu.cpp
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Expand Up @@ -31,12 +31,12 @@ enum args_pos {
};

template <typename T>
uint64_t compute_num_uint64s(const uint64_t num_elements) {
static uint64_t compute_num_uint64s(const uint64_t num_elements) {
const uint64_t ratio = sizeof(uint64_t) / sizeof(T);
return (num_elements + ratio - 1) / ratio;
}

void offset_tbe_input_combine_with_length_args(
static void offset_tbe_input_combine_with_length_args(
uint64_t** indices_addrs,
uint64_t** lengths_addrs,
uint64_t** indices_offsets,
Expand All @@ -59,7 +59,7 @@ void offset_tbe_input_combine_with_length_args(
reinterpret_cast<uint32_t*>(base_addr + ptr_offsets[P_lengths_is_long]);
}

std::tuple<Tensor, Tensor, Tensor> tbe_input_combine_with_length_gpu(
static std::tuple<Tensor, Tensor, Tensor> tbe_input_combine_with_length_gpu(
const std::vector<Tensor>& indices_list,
const std::vector<Tensor>& lengths_list,
const std::vector<Tensor>& per_sample_weights) {
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4 changes: 2 additions & 2 deletions fbgemm_gpu/src/jagged_tensor_ops/jagged_tensor_ops_autograd.cpp
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Expand Up @@ -788,7 +788,7 @@ class JaggedSliceOp : public torch::autograd::Function<JaggedSliceOp> {
} // namespace

///@ingroup jagged-tensor-ops-cpu
Tensor jagged_to_padded_dense_forward_autograd(
static Tensor jagged_to_padded_dense_forward_autograd(
const Tensor& values,
const std::vector<Tensor>& offsets,
const c10::SymIntArrayRef max_lengths,
Expand Down Expand Up @@ -883,7 +883,7 @@ std::tuple<Tensor, std::vector<Tensor>> dense_to_jagged(
auto output = op.call(dense, offsets, total_L);
return {output, offsets};
}
Tensor dense_to_jagged_forward_autograd(
static Tensor dense_to_jagged_forward_autograd(
const Tensor& dense,
const std::vector<Tensor>& offsets,
std::optional<at::SymInt> total_L) {
Expand Down
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