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add adamw and sgdw implemented build changed arg name format reflect reviews format
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// Copyright (c) 2017 Sony Corporation. All Rights Reserved. | ||
// | ||
// Licensed under the Apache License, Version 2.0 (the "License"); | ||
// you may not use this file except in compliance with the License. | ||
// You may obtain a copy of the License at | ||
// | ||
// http://www.apache.org/licenses/LICENSE-2.0 | ||
// | ||
// Unless required by applicable law or agreed to in writing, software | ||
// distributed under the License is distributed on an "AS IS" BASIS, | ||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
// See the License for the specific language governing permissions and | ||
// limitations under the License. | ||
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#ifndef __NBLA_CUDA_SOLVER_ADAMW_HPP__ | ||
#define __NBLA_CUDA_SOLVER_ADAMW_HPP__ | ||
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#include <nbla/cuda/cuda.hpp> | ||
#include <nbla/solver/adamw.hpp> | ||
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namespace nbla { | ||
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template <typename T> class AdamWCuda : public AdamW<T> { | ||
public: | ||
explicit AdamWCuda(const Context &ctx, float alpha, float beta1, float beta2, | ||
float eps, float wd) | ||
: AdamW<T>(ctx, alpha, beta1, beta2, eps, wd) {} | ||
virtual ~AdamWCuda() {} | ||
virtual string name() { return "AdamWCuda"; } | ||
virtual vector<string> allowed_array_classes() { | ||
return SingletonManager::get<Cuda>()->array_classes(); | ||
} | ||
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protected: | ||
virtual void update_impl(const string &key, VariablePtr param); | ||
NBLA_DECL_WEIGHT_DECAY(); | ||
NBLA_DECL_CHECK_INF_GRAD(); | ||
NBLA_DECL_CHECK_NAN_GRAD(); | ||
NBLA_DECL_CHECK_INF_OR_NAN_GRAD(); | ||
NBLA_DECL_SCALE_GRAD(); | ||
}; | ||
} | ||
#endif |
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// Copyright (c) 2017 Sony Corporation. All Rights Reserved. | ||
// | ||
// Licensed under the Apache License, Version 2.0 (the "License"); | ||
// you may not use this file except in compliance with the License. | ||
// You may obtain a copy of the License at | ||
// | ||
// http://www.apache.org/licenses/LICENSE-2.0 | ||
// | ||
// Unless required by applicable law or agreed to in writing, software | ||
// distributed under the License is distributed on an "AS IS" BASIS, | ||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
// See the License for the specific language governing permissions and | ||
// limitations under the License. | ||
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#ifndef __NBLA_CUDA_SOLVER_SGDW_HPP__ | ||
#define __NBLA_CUDA_SOLVER_SGDW_HPP__ | ||
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#include <nbla/cuda/cuda.hpp> | ||
#include <nbla/solver/sgdw.hpp> | ||
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namespace nbla { | ||
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template <typename T> class SgdWCuda : public SgdW<T> { | ||
public: | ||
explicit SgdWCuda(const Context &ctx, float lr, float momentum, float wd) | ||
: SgdW<T>(ctx, lr, momentum, wd) {} | ||
virtual ~SgdWCuda() {} | ||
virtual string name() { return "SgdWCuda"; } | ||
virtual vector<string> allowed_array_classes() { | ||
return SingletonManager::get<Cuda>()->array_classes(); | ||
} | ||
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protected: | ||
virtual void update_impl(const string &key, VariablePtr param); | ||
NBLA_DECL_WEIGHT_DECAY(); | ||
NBLA_DECL_CHECK_INF_GRAD(); | ||
NBLA_DECL_CHECK_NAN_GRAD(); | ||
NBLA_DECL_CHECK_INF_OR_NAN_GRAD(); | ||
NBLA_DECL_SCALE_GRAD(); | ||
}; | ||
} | ||
#endif |
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// Copyright (c) 2017 Sony Corporation. All Rights Reserved. | ||
// | ||
// Licensed under the Apache License, Version 2.0 (the "License"); | ||
// you may not use this file except in compliance with the License. | ||
// You may obtain a copy of the License at | ||
// | ||
// http://www.apache.org/licenses/LICENSE-2.0 | ||
// | ||
// Unless required by applicable law or agreed to in writing, software | ||
// distributed under the License is distributed on an "AS IS" BASIS, | ||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
// See the License for the specific language governing permissions and | ||
// limitations under the License. | ||
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#include <nbla/cuda/common.hpp> | ||
#include <nbla/cuda/solver/adamw.hpp> | ||
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#include "./mixed_precision_training.cuh" | ||
#include "./weight_decay.cuh" | ||
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namespace nbla { | ||
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template <typename T> | ||
__global__ void | ||
kernel_adamw_update(const int num, T *theta, T *m, T *v, const T *g, | ||
const float alpha_t, const float beta1, const float beta2, | ||
const float eps, const float wd, const T eta_t) { | ||
NBLA_CUDA_KERNEL_LOOP(s, num) { | ||
// Updating running mean and var. | ||
m[s] = beta1 * m[s] + (1 - beta1) * g[s]; | ||
v[s] = beta2 * v[s] + (1 - beta2) * g[s] * g[s]; | ||
// Update parameters. | ||
theta[s] = theta[s] - alpha_t * m[s] / (std::sqrt(v[s]) + eps) - | ||
eta_t * wd * theta[s]; | ||
} | ||
} | ||
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template <typename T> | ||
void AdamWCuda<T>::update_impl(const string &key, VariablePtr param) { | ||
cuda_set_device(std::stoi(this->ctx_.device_id)); | ||
Size_t size = param->size(); | ||
auto &state = this->states_.at(key); | ||
uint32_t &t = state.t; | ||
const T *g = param->get_grad_pointer<T>(this->ctx_); | ||
shared_ptr<Variable> mean_ = | ||
state.pstate["mean"]; // To prevent compile error. | ||
shared_ptr<Variable> var_ = state.pstate["var"]; // To prevent compile error. | ||
T *m = mean_->cast_data_and_get_pointer<T>(this->ctx_); | ||
T *v = var_->cast_data_and_get_pointer<T>(this->ctx_); | ||
T *theta = param->cast_data_and_get_pointer<T>(this->ctx_); | ||
t = std::min(t + 1, std::numeric_limits<uint32_t>::max() - 1); | ||
T eta_t = this->alpha_ / this->init_alpha_; | ||
const T bias_correction = std::sqrt(1 - std::pow(this->beta2_, t)) / | ||
(1 - std::pow(this->beta1_, t)); | ||
const T alpha_t = this->alpha_ * bias_correction; | ||
NBLA_CUDA_LAUNCH_KERNEL_SIMPLE(kernel_adamw_update, size, theta, m, v, g, | ||
alpha_t, this->beta1_, this->beta2_, | ||
this->eps_, this->wd_, eta_t); | ||
} | ||
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template <typename T> | ||
void AdamWCuda<T>::weight_decay_impl(const string &key, VariablePtr param, | ||
float decay_rate) { | ||
NBLA_CHECK(decay_rate == this->wd_, error_code::value, | ||
"Decay rate should remain the same."); | ||
weight_decay_cuda<T>(this->ctx_, param, decay_rate); | ||
} | ||
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NBLA_DEF_CHECK_INF_GRAD(AdamWCuda, check_inf_grad_cuda); | ||
NBLA_DEF_CHECK_NAN_GRAD(AdamWCuda, check_nan_grad_cuda); | ||
NBLA_DEF_CHECK_INF_OR_NAN_GRAD(AdamWCuda, check_inf_or_nan_grad_cuda); | ||
NBLA_DEF_SCALE_GRAD(AdamWCuda, scale_grad_impl_cuda); | ||
} |
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// Copyright (c) 2017 Sony Corporation. All Rights Reserved. | ||
// | ||
// Licensed under the Apache License, Version 2.0 (the "License"); | ||
// you may not use this file except in compliance with the License. | ||
// You may obtain a copy of the License at | ||
// | ||
// http://www.apache.org/licenses/LICENSE-2.0 | ||
// | ||
// Unless required by applicable law or agreed to in writing, software | ||
// distributed under the License is distributed on an "AS IS" BASIS, | ||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
// See the License for the specific language governing permissions and | ||
// limitations under the License. | ||
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#include <nbla/cuda/common.hpp> | ||
#include <nbla/cuda/solver/sgdw.hpp> | ||
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#include "./mixed_precision_training.cuh" | ||
#include "./weight_decay.cuh" | ||
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namespace nbla { | ||
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template <typename T> | ||
__global__ void kernel_update(const int num, T *data, const T *grad, T *v, | ||
const float lr, const float momentum, | ||
const float wd, T eta_t) { | ||
NBLA_CUDA_KERNEL_LOOP(idx, num) { | ||
v[idx] = momentum * v[idx] + lr * grad[idx] - (eta_t * wd * v[idx]); | ||
data[idx] -= v[idx]; | ||
} | ||
} | ||
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template <typename T> | ||
void SgdWCuda<T>::update_impl(const string &key, VariablePtr param) { | ||
cuda_set_device(std::stoi(this->ctx_.device_id)); | ||
Size_t size = param->size(); | ||
auto &state = this->states_.at(key); | ||
VariablePtr r_ = state.pstate["m"]; | ||
const T *grad = param->get_grad_pointer<T>(this->ctx_); | ||
T *v = r_->cast_data_and_get_pointer<T>(this->ctx_); | ||
T *data = param->cast_data_and_get_pointer<T>(this->ctx_); | ||
T eta_t = this->lr_ / this->init_lr_; | ||
NBLA_CUDA_LAUNCH_KERNEL_SIMPLE(kernel_update, size, data, grad, v, this->lr_, | ||
this->momentum_, this->wd_, eta_t); | ||
auto &t = state.t; | ||
t = std::min(t + 1, std::numeric_limits<uint32_t>::max() - 1); | ||
} | ||
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template <typename T> | ||
void SgdWCuda<T>::weight_decay_impl(const string &key, VariablePtr param, | ||
float decay_rate) { | ||
NBLA_CHECK(decay_rate == this->wd_, error_code::value, | ||
"Decay rate should remain the same."); | ||
weight_decay_cuda<T>(this->ctx_, param, decay_rate); | ||
} | ||
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NBLA_DEF_CHECK_INF_GRAD(SgdWCuda, check_inf_grad_cuda); | ||
NBLA_DEF_CHECK_NAN_GRAD(SgdWCuda, check_nan_grad_cuda); | ||
NBLA_DEF_CHECK_INF_OR_NAN_GRAD(SgdWCuda, check_inf_or_nan_grad_cuda); | ||
NBLA_DEF_SCALE_GRAD(SgdWCuda, scale_grad_impl_cuda); | ||
} |