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- #include "cpu_adagrad.h"
- #include <cuda_runtime_api.h>
- #include <math.h>
- #include <omp.h>
- #include <torch/extension.h>
- #include <iostream>
- #include <memory>
- #include <type_traits>
- #include <unordered_map>
- #include "cublas_v2.h"
- #include "cuda.h"
- #include "curand.h"
- #include "custom_cuda_layers.h"
- static std::unordered_map<int, std::shared_ptr<void>> s_optimizers;
- // C++ interface
- void Adagrad_Optimizer::Step_1(float* _params,
- float* grads,
- float* _exp_avg_sq,
- size_t _param_size,
- __half* dev_params,
- bool half_precision)
- {
- size_t rounded_size = 0;
- #if defined(__AVX512__) or defined(__AVX256__)
- Step_AVX<1>(
- &rounded_size, _params, grads, _exp_avg_sq, _param_size, dev_params, half_precision);
- #endif
- if (_param_size > rounded_size) {
- float step_size = -1 * _alpha;
- __half* grads_cast_h;
- __half* params_cast_h;
- if (half_precision) {
- grads_cast_h = reinterpret_cast<__half*>(grads);
- params_cast_h = reinterpret_cast<__half*>(_params);
- }
- for (size_t t = rounded_size; t < _param_size; t += TILE) {
- size_t copy_size = TILE;
- if ((t + TILE) > _param_size) copy_size = _param_size - t;
- size_t offset = copy_size + t;
- if ((t / TILE) >= 2) { cudaStreamSynchronize(_streams[_buf_index]); }
- #pragma omp parallel for
- for (size_t k = t; k < offset; k++) {
- float grad = half_precision ? (float)grads_cast_h[k] : grads[k];
- float param = half_precision ? (float)params_cast_h[k] : _params[k];
- float momentum = grads[k];
- float variance = _exp_avg_sq[k];
- if (_weight_decay > 0) { grad = param * _weight_decay + grad; }
- variance += grad * grad;
- grad = sqrt(variance);
- grad += _eps;
- grad = momentum / grad;
- param = grad * step_size + param;
- if (dev_params) _doubled_buffer[_buf_index][k - t] = param;
- if (half_precision)
- params_cast_h[k] = (__half)param;
- else
- _params[k] = param;
- // STORE UPDATE TERM TO GRAD'S MEMORY
- grads[k] = grad * step_size;
- _exp_avg_sq[k] = variance;
- }
- if (dev_params) {
- launch_param_update(
- _doubled_buffer[_buf_index], dev_params + t, (copy_size), _streams[_buf_index]);
- _buf_index = !_buf_index;
- }
- }
- }
- }
- void Adagrad_Optimizer::Step_4(float* _params,
- float* grads,
- float* _exp_avg_sq,
- size_t _param_size,
- __half* dev_params,
- bool half_precision)
- {
- size_t rounded_size = 0;
- #if defined(__AVX512__) or defined(__AVX256__)
- Step_AVX<4>(
- &rounded_size, _params, grads, _exp_avg_sq, _param_size, dev_params, half_precision);
- #endif
- if (_param_size > rounded_size)
- Step_1((_params + rounded_size),
- (grads + rounded_size),
- (_exp_avg_sq + rounded_size),
- (_param_size - rounded_size),
- (dev_params != nullptr ? (dev_params + rounded_size) : dev_params),
- half_precision);
- }
- int create_adagrad_optimizer(int optimizer_id,
- float alpha = 1e-2,
- float eps = 1e-8,
- float weight_decay = 0,
- bool should_log = false)
- {
- auto opt = std::make_shared<Adagrad_Optimizer>(alpha, eps, weight_decay);
- s_optimizers[optimizer_id] = opt;
- if (should_log) {
- std::string avx_type = "";
- #if defined(__AVX512__)
- avx_type = "AVX512";
- #else
- #if defined(__AVX256__)
- avx_type = "AVX2";
- #else
- avx_type = "scalar";
- #endif
- #endif
- printf("Adagrad Optimizer #%d is created with %s arithmetic capability.\n",
- optimizer_id,
- avx_type.c_str());
- printf("Config: alpha=%f, weight_decay=%f\n", alpha, weight_decay);
- }
- return 0;
- }
- void Adagrad_Optimizer::Step_8(float* _params,
- float* grads,
- float* _exp_avg_sq,
- size_t _param_size,
- __half* dev_params,
- bool half_precision)
- {
- size_t rounded_size = 0;
- #if defined(__AVX512__) or defined(__AVX256__)
- Step_AVX<8>(
- &rounded_size, _params, grads, _exp_avg_sq, _param_size, dev_params, half_precision);
- #endif
- if (_param_size > rounded_size)
- Step_4((_params + rounded_size),
- (grads + rounded_size),
- (_exp_avg_sq + rounded_size),
- (_param_size - rounded_size),
- (dev_params != nullptr ? (dev_params + rounded_size) : dev_params),
- half_precision);
- }
- int ds_adagrad_step(int optimizer_id,
- size_t step,
- float lr,
- float epsilon,
- float weight_decay,
- torch::Tensor& params,
- torch::Tensor& grads,
- torch::Tensor& exp_avg_sq)
- {
- auto params_c = params.contiguous();
- auto grads_c = grads.contiguous();
- auto exp_avg_sq_c = exp_avg_sq.contiguous();
- float* params_ptr = (float*)params_c.data_ptr();
- float* grads_ptr = (float*)grads_c.data_ptr();
- float* exp_avg_sq_ptr = (float*)exp_avg_sq_c.data_ptr();
- std::shared_ptr<Adagrad_Optimizer> opt =
- std::static_pointer_cast<Adagrad_Optimizer>(s_optimizers[optimizer_id]);
- opt->IncrementStep(step);
- opt->update_state(lr, epsilon, weight_decay);
- opt->Step_8(params_ptr, grads_ptr, exp_avg_sq_ptr, params_c.size(0));
- opt->SynchronizeStreams();
- return 0;
- }
- int ds_adagrad_step_plus_copy(int optimizer_id,
- size_t step,
- float lr,
- float epsilon,
- float weight_decay,
- torch::Tensor& params,
- torch::Tensor& grads,
- torch::Tensor& exp_avg_sq,
- torch::Tensor& gpu_params)
- {
- auto params_c = params.contiguous();
- auto gpu_params_c = gpu_params.contiguous();
- auto exp_avg_sq_c = exp_avg_sq.contiguous();
- auto grads_c = grads.contiguous();
- float* params_ptr = (float*)params_c.data_ptr();
- float* grads_ptr = (float*)grads_c.data_ptr();
- __half* gpu_params_ptr = (__half*)gpu_params_c.data_ptr();
- float* exp_avg_sq_ptr = (float*)exp_avg_sq_c.data_ptr();
- std::shared_ptr<Adagrad_Optimizer> opt =
- std::static_pointer_cast<Adagrad_Optimizer>(s_optimizers[optimizer_id]);
- opt->IncrementStep(step);
- opt->update_state(lr, epsilon, weight_decay);
- opt->Step_8(params_ptr,
- grads_ptr,
- exp_avg_sq_ptr,
- params_c.size(0),
- gpu_params_ptr,
- (params.options().dtype() == at::kHalf));
- opt->SynchronizeStreams();
- return 0;
- }
- int destroy_adagrad_optimizer(int optimizer_id)
- {
- s_optimizers.erase(optimizer_id);
- return 0;
- }
- PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)
- {
- m.def("adagrad_update", &ds_adagrad_step, "DeepSpeed CPU Adagrad update (C++)");
- m.def("adagrad_update_copy",
- &ds_adagrad_step_plus_copy,
- "DeepSpeed CPU Adagrad update and param copy (C++)");
- m.def("create_adagrad", &create_adagrad_optimizer, "DeepSpeed CPU Adagrad (C++)");
- m.def("destroy_adagrad", &destroy_adagrad_optimizer, "DeepSpeed CPU Adagrad destroy (C++)");
- }
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