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Ck tile/layernorm: implement naive reduce, opt performance (#1784)
* add no welford * enable output raw * raw of int8 * fix build * fix smoke test err * [ck_tile]layernorm: fix welford ok, set int8 and bf16 small N as default and others open by generate * [cktile]layernorm, fix err commit files and remove uselss * fix quant 8192 err & change norm_reduce class and file name --------- Co-authored-by: coderfeli <coderfeli@163.com> Co-authored-by: carlushuang <carlus.huang@amd.com>
This commit is contained in:
feli
@@ -58,6 +58,7 @@ template <typename XDataType_,
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bool kPadN_,
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bool kSaveMeanInvStd_,
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bool kFastFDiv_,
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bool kWelford_,
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bool kTwoPass_,
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ck_tile::index_t kFusedAdd_ = 0,
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ck_tile::index_t kFusedQuant_ = 0>
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@@ -120,6 +121,7 @@ struct layernorm2d_fwd_traits_
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static constexpr bool kPadN = kPadN_;
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static constexpr bool kSaveMeanInvStd = kSaveMeanInvStd_;
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static constexpr bool kFastFDiv = kFastFDiv_;
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static constexpr bool kWelford = kWelford_;
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static constexpr bool kTwoPass = kTwoPass_;
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static constexpr ck_tile::index_t kFusedAdd = kFusedAdd_;
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static constexpr ck_tile::index_t kFusedQuant = kFusedQuant_;
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@@ -137,6 +139,7 @@ template <typename XDataType_,
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bool kPadN_,
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bool kSaveMeanInvStd_,
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bool kFastFDiv_,
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bool kWelford_,
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bool kTwoPass_,
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int kFusedAdd_,
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int kFusedQuant_>
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@@ -152,6 +155,7 @@ using traits_ = layernorm2d_fwd_traits_<XDataType_,
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kPadN_,
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kSaveMeanInvStd_,
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kFastFDiv_,
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kWelford_,
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kTwoPass_,
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kFusedAdd_,
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kFusedQuant_>;
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@@ -184,6 +188,7 @@ float layernorm2d_fwd_(const S& s, A a)
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using PipelineTraits = ck_tile::Layernorm2dFwdTraits<Traits_::kPadN,
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Traits_::kSaveMeanInvStd,
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Traits_::kFastFDiv,
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Traits_::kWelford,
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Traits_::kTwoPass,
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static_cast<ck_tile::Layernorm2dFusedAddEnum>(Traits_::kFusedAdd),
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static_cast<ck_tile::Layernorm2dFusedQuantEnum>(Traits_::kFusedQuant)>;
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@@ -204,12 +209,13 @@ float layernorm2d_fwd_(const S& s, A a)
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using TwoPassPipeline = ck_tile::Layernorm2dFwdPipelineTwoPass<PipelineProblem>;
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using Pipeline = std::conditional_t<Traits_::kTwoPass, TwoPassPipeline, OnePassPipeline>;
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using Default2DEpilogueProblem = ck_tile::Default2DEpilogueProblem<ComputeDataType, YDataType, false, Traits_::kPadN, false>;
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using Default2DEpilogueProblem = ck_tile::Default2DEpilogueProblem<ComputeDataType, YDataType, false, Traits_::kPadN, true>;
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using Default2DEpilogue = ck_tile::Default2DEpilogue<Default2DEpilogueProblem>;
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static constexpr bool UseSmoothInputScale = Traits_::kFusedQuant == 1;
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static constexpr bool UseRawStore = sizeof(YDataType) == 4;
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using DynamicQuantEpilogueProblem = ck_tile::DynamicQuantEpilogueProblem<ComputeDataType, XScaleDataType, YScaleDataType, YDataType, typename Traits_::Shape,
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ck_tile::DynamicQuantEpilogueTraits<false, Traits_::kPadN, UseSmoothInputScale, false, true/*max3*/>>;
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ck_tile::DynamicQuantEpilogueTraits<false, Traits_::kPadN, UseSmoothInputScale, UseRawStore, true/*max3*/>>;
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using DynamicQuantEpilogue = ck_tile::DynamicQuantEpilogue<DynamicQuantEpilogueProblem>;
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@@ -274,7 +280,7 @@ float layernorm2d_fwd(layernorm2d_fwd_traits t,
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#include "layernorm2d_fwd_api_common.hpp"
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// clang-format off
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// prec_i prec_o prec_sy rm rn tm tn vn pd mv rpcf 2p add sweep
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// prec_i prec_o prec_sy rm rn tm tn vn pd mv rpcf welford 2p add sweep
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{F_instance_def}
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// clang-format on
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@@ -362,6 +368,7 @@ float layernorm2d_fwd(layernorm2d_fwd_traits t,
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F_kPadN : bool
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F_kSaveMeanInvStd_ : bool
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F_kFastFDiv_ : bool
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F_kWelford_ : bool
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F_kTwoPass_ : bool
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F_kFusedAdd : int
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F_kFusedQuant : int
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@@ -369,7 +376,7 @@ float layernorm2d_fwd(layernorm2d_fwd_traits t,
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@property
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def trait_name(self) ->str:
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t_ = f'{DATA_TYPE_MAP[self.F_XDataType]}, {DATA_TYPE_MAP[self.F_YDataType]}, {DATA_TYPE_MAP[self.F_XScaleDataType]}, {DATA_TYPE_MAP[self.F_YScaleDataType]}, {self.F_Repeat_M:2}, {self.F_Repeat_N:2}, {self.F_ThreadPerBlock_M:2}, {self.F_ThreadPerBlock_N:4}'
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t_ += f', {self.F_Vector_N:2}, {BOOL_MAP(self.F_kPadN):5}, {BOOL_MAP(self.F_kSaveMeanInvStd_):5}, {BOOL_MAP(self.F_kFastFDiv_):5}'
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t_ += f', {self.F_Vector_N:2}, {BOOL_MAP(self.F_kPadN):5}, {BOOL_MAP(self.F_kSaveMeanInvStd_):5}, {BOOL_MAP(self.F_kFastFDiv_):5}, {BOOL_MAP(self.F_kWelford_):5}'
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t_ += f', {BOOL_MAP(self.F_kTwoPass_):5}, {self.F_kFusedAdd:4}, {self.F_kFusedQuant:4}'
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return t_
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@@ -422,11 +429,10 @@ float layernorm2d_fwd(layernorm2d_fwd_traits t,
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def name_common_header(self) -> str:
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return 'layernorm2d_fwd_api_common'
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@property
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def content_api(self) -> str:
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def content_api(self, args) -> str:
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# 1 sort based on dtype
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t_dtype_dict = dict()
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blobs = self.get_blobs()
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blobs = self.get_blobs(args)
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for blob in blobs:
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if blob.F_DataTypePair not in t_dtype_dict:
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t_dtype_dict[blob.F_DataTypePair] = {}
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@@ -462,8 +468,8 @@ float layernorm2d_fwd(layernorm2d_fwd_traits t,
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inner_str += self.API_INNER_CASE.format(F_if = get_if_str(idx_in_n, len_in_n, False),
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F_VEC_COND = _cond, F_instance_func=ins.call_name)
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#inner_str = inner_str + vec_str
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n_cnd = f'(a.n <= {n_})' if (i_n < len(blob_per_t) - 1) else ''
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n_str += self.API_PER_N_CASE.format(F_if = get_if_str(i_n, len(blob_per_t)), F_N_COND=n_cnd, F_inner_dispatch=inner_str)
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n_cnd = f'(a.n <= {n_})' if isinstance(n_, int) else ''
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n_str += self.API_PER_N_CASE.format(F_if = get_if_str(i_n, len(blob_per_t), not isinstance(n_, int)), F_N_COND=n_cnd, F_inner_dispatch=inner_str)
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prec_i, prec_o = dtype_.split(',')
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d_str += self.API_PER_DTYPE.format(F_if = get_if_str(i_d, len(t_dtype_dict), False), F_i_type=prec_i, F_o_type=prec_o, F_per_n_case=n_str)
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@@ -474,7 +480,7 @@ float layernorm2d_fwd(layernorm2d_fwd_traits t,
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def content_common_header(self) -> str:
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return self.API_COMMON_HEADER.format(F_traits_define=self.API_TRAITS_DEFINE)
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def get_blobs(self):
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def get_blobs(self, args):
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h_traits = layernorm_fwd_codegen.h_traits
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h_instance = layernorm_fwd_codegen.h_instance
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@@ -484,60 +490,61 @@ float layernorm2d_fwd(layernorm2d_fwd_traits t,
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scale_list = [('fp32,fp32')]
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dtype_list = [('fp16,fp16'), ('bf16,bf16'),
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('fp16,int8'), ('bf16,int8')] # NOTE: only fused-dynamic-quant use int8 out
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types_8bit = ('int8', 'fp8')
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types_16bit = ('int16', 'fp16', 'bf16')
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#fused_add_list = [0, 1, 2]
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#fused_sweep_list = [0, 1, 2] # NOTE: only single pass can use fused dynamic quant
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fused_add_list = [0, 1]
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fused_sweep_list = [0, 1] # NOTE: only single pass can use fused dynamic quant
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# rm rn tm tn vn pd mv fdiv 2p add sweep
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h_trait_dict = {'64' : [ h_traits('x', 'y', 'xs', 'ys', 1, 1, 8, 8, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 16, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 64, 1, True, False, True, False, 0, 0)],
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'128' : [ h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 16, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 64, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 4, 64, 1, True, False, True, False, 0, 0)],
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'256' : [ h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 64, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 4, 64, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 4, 64, 1, True, False, True, False, 0, 0)],
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'512' : [ h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 64, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 4, 64, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 4, 64, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 8, 4, 64, 1, True, False, True, False, 0, 0)],
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'768' : [ h_traits('x', 'y', 'xs', 'ys', 1, 3, 4, 64, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 6, 4, 64, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 12, 4, 64, 1, True, False, True, False, 0, 0)],
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'1024' :[ h_traits('x', 'y', 'xs', 'ys', 1, 1, 2, 128, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 2, 128, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 2, 128, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 1, True, False, True, False, 0, 0)],
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'1536' :[ h_traits('x', 'y', 'xs', 'ys', 1, 3, 4, 64, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 2, 128, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 256, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 6, 1, 256, 1, True, False, True, False, 0, 0)],
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'2048' :[ h_traits('x', 'y', 'xs', 'ys', 1, 1, 1, 256, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 1, 256, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 8, 1, 256, 1, True, False, True, False, 0, 0)],
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'3072' :[ h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 128, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 256, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 6, 1, 256, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1,1024, 1, True, False, True, False, 0, 0)],
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'4096' :[ h_traits('x', 'y', 'xs', 'ys', 1, 2, 1, 256, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 1,1024, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1,1024, 1, True, False, True, False, 0, 0)],
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'6144' :[ h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 256, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 512, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1,1024, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 6, 1,1024, 1, True, False, True, False, 0, 0)],
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'8192' :[ h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 8, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 512, 4, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1,1024, 2, True, False, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 8, 1,1024, 1, True, False, True, False, 0, 0)],
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'big' :[ h_traits('x', 'y', 'xs', 'ys', 1, 2, 1, 256, 8, True, False, True, True, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 4, True, False, True, True, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 1,1024, 2, True, False, True, True, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1,1024, 1, True, False, True, True, 0, 0)]}
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# rm rn tm tn vn pd mv fdiv welford 2p add sweep
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h_trait_dict = {'64' : [ h_traits('x', 'y', 'xs', 'ys', 1, 1, 8, 8, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 16, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 64, 1, True, False, True, True, False, 0, 0)],
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'128' : [ h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 16, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 64, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 4, 64, 1, True, False, True, True, False, 0, 0)],
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'256' : [ h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 64, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 4, 64, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 4, 64, 1, True, False, True, True, False, 0, 0)],
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'512' : [ h_traits('x', 'y', 'xs', 'ys', 1, 1, 4, 64, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 4, 64, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 4, 64, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 8, 4, 64, 1, True, False, True, True, False, 0, 0)],
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'768' : [ h_traits('x', 'y', 'xs', 'ys', 1, 3, 4, 64, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 6, 4, 64, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 12, 4, 64, 1, True, False, True, True, False, 0, 0)],
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'1024' :[ h_traits('x', 'y', 'xs', 'ys', 1, 1, 2, 128, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 2, 128, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 2, 128, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 1, True, False, True, True, False, 0, 0)],
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'1536' :[ h_traits('x', 'y', 'xs', 'ys', 1, 3, 4, 64, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 2, 128, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 256, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 6, 1, 256, 1, True, False, True, True, False, 0, 0)],
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'2048' :[ h_traits('x', 'y', 'xs', 'ys', 1, 1, 1, 256, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 1, 256, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 8, 1, 256, 1, True, False, True, True, False, 0, 0)],
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'3072' :[ h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 128, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 256, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 6, 1, 256, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1,1024, 1, True, False, True, True, False, 0, 0)],
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'4096' :[ h_traits('x', 'y', 'xs', 'ys', 1, 2, 1, 256, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 2, 1,1024, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1,1024, 1, True, False, True, True, False, 0, 0)],
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'6144' :[ h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 256, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1, 512, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 3, 1,1024, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 6, 1,1024, 1, True, False, True, True, False, 0, 0)],
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'8192' :[ h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 8, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 512, 4, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 4, 1,1024, 2, True, False, True, True, False, 0, 0),
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h_traits('x', 'y', 'xs', 'ys', 1, 8, 1,1024, 1, True, False, True, True, False, 0, 0)],
|
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'big' :[ h_traits('x', 'y', 'xs', 'ys', 1, 2, 1, 256, 8, True, False, True, True, True, 0, 0),
|
||||
h_traits('x', 'y', 'xs', 'ys', 1, 4, 1, 256, 4, True, False, True, True, True, 0, 0),
|
||||
h_traits('x', 'y', 'xs', 'ys', 1, 2, 1,1024, 2, True, False, True, True, True, 0, 0),
|
||||
h_traits('x', 'y', 'xs', 'ys', 1, 4, 1,1024, 1, True, False, True, True, True, 0, 0)]}
|
||||
total_blob = list()
|
||||
for hs_key in h_trait_dict:
|
||||
hs = h_trait_dict[hs_key]
|
||||
@@ -558,16 +565,27 @@ float layernorm2d_fwd(layernorm2d_fwd_traits t,
|
||||
h_.F_YScaleDataType = scale_x
|
||||
h_.F_kFusedAdd = fused_add
|
||||
h_.F_kFusedQuant = fused_quant
|
||||
# disable welford update for 8bit and 16 bit smallN
|
||||
if not h_.F_kTwoPass_:
|
||||
#disable 16 bit when set args disable_16b_welford
|
||||
if args.disable_16b_welford and prec_i in types_16bit:
|
||||
h_.F_kWelford_ = False
|
||||
#disable 8bit by default
|
||||
elif prec_i in types_8bit or prec_o in types_8bit:
|
||||
h_.F_kWelford_ = False
|
||||
#disable 16bit small N
|
||||
elif prec_i in types_16bit and hs_key == '64':
|
||||
h_.F_kWelford_ = False
|
||||
current_hs.append(h_) # + "\n"
|
||||
#f.write(str(f.parent / GEN_DIR / (blobs.api_common_header_
|
||||
current_n_str = 'big' if hs_key == 'big' else current_n
|
||||
total_blob.append(h_instance(dtype, current_n_str, fused_add, fused_quant, current_hs))
|
||||
return total_blob
|
||||
|
||||
def list_blobs(self) -> None:
|
||||
def list_blobs(self, args) -> None:
|
||||
w_p = Path(self.working_path)
|
||||
list_p = w_p / 'layernorm2d_fwd_blobs.txt'
|
||||
blobs = self.get_blobs()
|
||||
blobs = self.get_blobs(args)
|
||||
with list_p.open('w') as list_f:
|
||||
# api related file
|
||||
list_f.write(str(w_p / (self.name_api + ".cpp")) + "\n")
|
||||
@@ -576,11 +594,12 @@ float layernorm2d_fwd(layernorm2d_fwd_traits t,
|
||||
for b in blobs:
|
||||
list_f.write(str(w_p / (b.name + ".cpp")) + "\n")
|
||||
|
||||
def gen_blobs(self) -> None:
|
||||
def gen_blobs(self, args) -> None:
|
||||
w_p = Path(self.working_path)
|
||||
(w_p / (self.name_api + ".cpp")).write_text(self.content_api)
|
||||
w_str = self.content_api(args)
|
||||
(w_p / (self.name_api + ".cpp")).write_text(w_str)
|
||||
(w_p / (self.name_common_header + ".hpp")).write_text(self.content_common_header)
|
||||
blobs = self.get_blobs()
|
||||
blobs = self.get_blobs(args)
|
||||
for b in blobs:
|
||||
(w_p / (b.name + ".cpp")).write_text(b.content)
|
||||
|
||||
@@ -588,14 +607,14 @@ def list_blobs(args):
|
||||
api_list = args.api.split(',')
|
||||
for api in api_list:
|
||||
if api == 'fwd':
|
||||
layernorm_fwd_codegen(args.working_path, args.filter).list_blobs()
|
||||
layernorm_fwd_codegen(args.working_path, args.filter).list_blobs(args)
|
||||
|
||||
|
||||
def gen_blobs(args):
|
||||
api_list = args.api.split(',')
|
||||
for api in api_list:
|
||||
if api == 'fwd':
|
||||
layernorm_fwd_codegen(args.working_path, args.filter).gen_blobs()
|
||||
layernorm_fwd_codegen(args.working_path, args.filter).gen_blobs(args)
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(
|
||||
@@ -663,6 +682,13 @@ if __name__ == "__main__":
|
||||
help="codegen receipt."
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--disable_16b_welford",
|
||||
default=False,
|
||||
required=False,
|
||||
help="enable/disable welford for 16bit datatype n > 64"
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
# print(f'{args.list_blobs}-{args.gen_blobs}')
|
||||
|
||||
@@ -27,7 +27,8 @@ $EXE -prec_i=$pr_i -fadd=$fadd $fquant -m=7 -n=2734
|
||||
$EXE -prec_i=$pr_i -fadd=$fadd $fquant -m=1 -n=3182
|
||||
$EXE -prec_i=$pr_i -fadd=$fadd $fquant -m=9 -n=4096
|
||||
$EXE -prec_i=$pr_i -fadd=$fadd $fquant -m=3 -n=8192
|
||||
#$EXE -prec_i=$pr_i -fadd=$fadd $fquant -m=1 -n=10547
|
||||
$EXE -prec_i=$pr_i -fadd=$fadd $fquant -m=3 -n=9120
|
||||
$EXE -prec_i=$pr_i -fadd=$fadd $fquant -m=1 -n=10547
|
||||
#$EXE -prec_i=$pr_i -fadd=$fadd $fquant -m=3 -n=17134
|
||||
done
|
||||
done
|
||||
|
||||
Reference in New Issue
Block a user