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Fix Upate Update #60990

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Merged
luotao1 merged 2 commits into from
Jan 22, 2024
Merged

Fix Upate Update #60990

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7d81080
Fix
co63oc Jan 19, 2024
feef20f
ci
co63oc Jan 20, 2024
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20 changes: 10 additions & 10 deletions paddle/phi/kernels/funcs/lamb_functors.h
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Original file line number Diff line number Diff line change
Expand Up @@ -408,7 +408,7 @@ struct LambBetaPowUpdateFunctor<MT, /*NeedUpdateBetaPow=*/false> {
};

template <typename T, typename MT, bool IsMultiPrecision, bool UpdateBetaPow>
struct LambParamUpateFunctor
struct LambParamUpdateFunctor
: public LambBetaPowUpdateFunctor<MT, UpdateBetaPow> {
const MT* lr_;
const T* param_;
Expand All @@ -421,15 +421,15 @@ struct LambParamUpateFunctor

const bool* skip_update_;

LambParamUpateFunctor(const MT* lr,
const T* param,
const MT* master_param,
const MT* param_norm,
const MT* trust_ratio_div,
const MT* trust_ratio_div_norm,
T* param_out,
MT* master_param_out,
const bool* skip_update)
LambParamUpdateFunctor(const MT* lr,
const T* param,
const MT* master_param,
const MT* param_norm,
const MT* trust_ratio_div,
const MT* trust_ratio_div_norm,
T* param_out,
MT* master_param_out,
const bool* skip_update)
: lr_(lr),
param_(param),
master_param_(master_param),
Expand Down
4 changes: 2 additions & 2 deletions paddle/phi/kernels/impl/adagrad_kernel_impl.h
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Expand Up @@ -110,13 +110,13 @@ void AdagradSparseKernel(const Context& ctx,
PADDLE_ENFORCE_EQ(param_tensor,
param_out_tensor,
phi::errors::InvalidArgument(
"the input tensor not euqal with output tensor"));
"the input tensor not equal with output tensor"));

auto* moment_tensor = &moment_t;
PADDLE_ENFORCE_EQ(moment_tensor,
moment_out_tensor,
phi::errors::InvalidArgument(
"the input moment not eual with output moment"));
"the input moment not equal with output moment"));

SparseAdagradFunctor<Context, T> functor;
functor(
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/impl/bilinear_grad_kernel_impl.h
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Expand Up @@ -70,7 +70,7 @@ void BilinearGradKernel(const Context& ctx,

auto blas = funcs::GetBlas<Context, T>(ctx);

// Caculate the Output(X@Grad) and Output(Y@Grad).
// Calculate the Output(X@Grad) and Output(Y@Grad).
if (dx || dy || dweight) {
Eigen::DSizes<int, 2> bcast_for_x(1, y_dim);
Eigen::DSizes<int, 2> bcast_for_y(1, x_dim);
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/impl/dot_grad_kernel_impl.h
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Expand Up @@ -597,7 +597,7 @@ struct DotTripleGradFunction {
DenseTensor* out_tensor_d_ddy);
};

// TODO(wuweilong): enable this function when the unittests framewark for multi
// TODO(wuweilong): enable this function when the unittest framework for multi
// grad is ok (dtype: complex64 or complex128).
template <typename DeviceContext, typename T>
struct DotTripleGradFunction<DeviceContext, T, phi::funcs::EnableComplex<T>> {
Expand Down
4 changes: 2 additions & 2 deletions paddle/phi/kernels/impl/einsum_grad_impl.h
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Expand Up @@ -84,7 +84,7 @@ DenseTensor PerformTileAndReduction(const Context& dev_ctx,
for (size_t i = 0; i < ellipsis_dims.size(); ++i)
if (ellipsis_dims[i] == 1) to_reduce.push_back(i + new_offset);

VLOG(5) << "PermformTileAndReduction: reduce sum axis: "
VLOG(5) << "PerformTileAndReduction: reduce sum axis: "
<< paddle::string::join_strings(to_reduce, ",");
if (to_reduce.size() != 0) {
ret = Sum<T, Context>(dev_ctx,
Expand All @@ -98,7 +98,7 @@ DenseTensor PerformTileAndReduction(const Context& dev_ctx,
} else {
ret = after_tile;
}
VLOG(5) << "PermformTileAndReduction: recover shape: "
VLOG(5) << "PerformTileAndReduction: recover shape: "
<< paddle::string::join_strings(recover_shape, ",");
ret.Resize(common::make_ddim(recover_shape));
// undiagonalize by einsum equation. only contain undiagonal operations.
Expand Down
6 changes: 3 additions & 3 deletions paddle/phi/kernels/impl/einsum_impl.h
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Expand Up @@ -290,7 +290,7 @@ inline static void InferLabelPerm(const CharIterable& op,
int cur = 0;
for (int c : op) {
if (!label2perm->exist(
c)) // can appear repeatly. we just record the first position.
c)) // can appear repeatedly. we just record the first position.
(*label2perm)[c] = cur;
if (c == '.') {
cur += n_broadcast;
Expand Down Expand Up @@ -391,9 +391,9 @@ std::vector<T> GetShapeByType(const std::vector<char>& all_labels,
}

inline static std::vector<int> perm_moveto(int n, int from, int to) {
// a permution means moving `from` to `to`.
// a permutation means moving `from` to `to`.
/*
f => t permtation
f => t permutation
--------------------
0 1 2 3 4 5
5 => 2 : 0 2 5 2 3 4
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/impl/kron_grad_kernel_impl.h
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Expand Up @@ -200,7 +200,7 @@ struct KronGradOpFunctor {
p_shape_y = dim_y.Get();
#endif
// dout_x: dout * kron(ones(X), Y) re-aranged in shape (numel_x, numel_y)
// dout_y: dout * kron(X, ones(Y)) re-aranged in shaoe (numel_y, numel_x)
// dout_y: dout * kron(X, ones(Y)) re-aranged in shape (numel_y, numel_x)
DenseTensor dout_x;
T *p_dout_x = nullptr;
if (dx) {
Expand Down
42 changes: 21 additions & 21 deletions paddle/phi/kernels/impl/lamb_kernel_impl.h
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Expand Up @@ -282,27 +282,27 @@ void ComputeImpl(const Context& dev_ctx,
<< " , tn = " << tn[0];
}

#define CALL_PADDLE_UPDATE_LAMB_PARAM_FUNC(__should_update_beta_pow) \
do { \
LambParamUpateFunctor<T, MT, IsMultiPrecision, __should_update_beta_pow> \
param_update_functor(lr.template data<MT>(), \
static_cast<const T*>(param_ptr), \
static_cast<const MT*>(master_param_ptr), \
p_norm_ptr, \
trust_ratio_div_ptr, \
trust_ratio_div_norm_ptr, \
static_cast<T*>(param_out_ptr), \
static_cast<MT*>(master_param_out_ptr), \
skip_update_flag); \
if (__should_update_beta_pow) { \
param_update_functor.SetBetaPows(beta1_pow_ptr, \
beta2_pow_ptr, \
beta1_pow_out_ptr, \
beta2_pow_out_ptr, \
beta1, \
beta2); \
} \
for_range(param_update_functor); \
#define CALL_PADDLE_UPDATE_LAMB_PARAM_FUNC(__should_update_beta_pow) \
do { \
LambParamUpdateFunctor<T, MT, IsMultiPrecision, __should_update_beta_pow> \
param_update_functor(lr.template data<MT>(), \
static_cast<const T*>(param_ptr), \
static_cast<const MT*>(master_param_ptr), \
p_norm_ptr, \
trust_ratio_div_ptr, \
trust_ratio_div_norm_ptr, \
static_cast<T*>(param_out_ptr), \
static_cast<MT*>(master_param_out_ptr), \
skip_update_flag); \
if (__should_update_beta_pow) { \
param_update_functor.SetBetaPows(beta1_pow_ptr, \
beta2_pow_ptr, \
beta1_pow_out_ptr, \
beta2_pow_out_ptr, \
beta1, \
beta2); \
} \
for_range(param_update_functor); \
} while (0)

if (should_update_beta_pow_later) {
Expand Down
4 changes: 2 additions & 2 deletions paddle/phi/kernels/impl/matmul_kernel_impl.h
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Original file line number Diff line number Diff line change
Expand Up @@ -1478,12 +1478,12 @@ void MatmulKernel(const Context& ctx,
common::product(x.dims()),
0,
phi::errors::InvalidArgument("The Input(X) dims size must not be equal "
"0, but reviced dims size is 0."));
"0, but received dims size is 0."));
PADDLE_ENFORCE_NE(
common::product(y.dims()),
0,
phi::errors::InvalidArgument("The Input(Y) dims size must not be equal "
"0, but reviced dims size is 0."));
"0, but received dims size is 0."));
const std::vector<std::int64_t> x_dims = common::vectorize(x.dims());
const std::vector<std::int64_t> y_dims = common::vectorize(y.dims());
MatmulJudgeDtypeKernel<Context, T>(
Expand Down
42 changes: 21 additions & 21 deletions paddle/phi/kernels/selected_rows/impl/lamb_kernel_impl.h
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Original file line number Diff line number Diff line change
Expand Up @@ -337,27 +337,27 @@ void ComputeRowImpl(const Context& dev_ctx,
<< " , tn = " << tn[0];
}

#define CALL_PADDLE_UPDATE_LAMB_PARAM_FUNC(__should_update_beta_pow) \
do { \
LambParamUpateFunctor<T, MT, IsMultiPrecision, __should_update_beta_pow> \
param_update_functor(lr.template data<MT>(), \
static_cast<const T*>(param_ptr), \
static_cast<const MT*>(master_param_ptr), \
p_norm_ptr, \
trust_ratio_div_ptr, \
trust_ratio_div_norm_ptr, \
static_cast<T*>(param_out_ptr), \
static_cast<MT*>(master_param_out_ptr), \
skip_update_flag); \
if (__should_update_beta_pow) { \
param_update_functor.SetBetaPows(beta1_pow_ptr, \
beta2_pow_ptr, \
beta1_pow_out_ptr, \
beta2_pow_out_ptr, \
beta1, \
beta2); \
} \
for_range(param_update_functor); \
#define CALL_PADDLE_UPDATE_LAMB_PARAM_FUNC(__should_update_beta_pow) \
do { \
LambParamUpdateFunctor<T, MT, IsMultiPrecision, __should_update_beta_pow> \
param_update_functor(lr.template data<MT>(), \
static_cast<const T*>(param_ptr), \
static_cast<const MT*>(master_param_ptr), \
p_norm_ptr, \
trust_ratio_div_ptr, \
trust_ratio_div_norm_ptr, \
static_cast<T*>(param_out_ptr), \
static_cast<MT*>(master_param_out_ptr), \
skip_update_flag); \
if (__should_update_beta_pow) { \
param_update_functor.SetBetaPows(beta1_pow_ptr, \
beta2_pow_ptr, \
beta1_pow_out_ptr, \
beta2_pow_out_ptr, \
beta1, \
beta2); \
} \
for_range(param_update_functor); \
} while (0)

if (should_update_beta_pow_later) {
Expand Down