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【PIR API adaptor No.78、79、82】 Migrate api in fused_transformer.py into pir #58453

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Merged
0x45f merged 7 commits into from
Nov 3, 2023
Merged

【PIR API adaptor No.78、79、82】 Migrate api in fused_transformer.py into pir #58453

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29d7ffc
add FusedMultiHeadAttention
MarioLulab Oct 27, 2023
385d0ee
Merge branch 'develop' into luqi/pir_api_fused_transformer
MarioLulab Oct 31, 2023
d8f66cb
add fused_multi_head_attention
MarioLulab Oct 31, 2023
c70cffa
add fused_feedforward
MarioLulab Nov 1, 2023
ddb820f
fix fused_feedforward_op testcase
MarioLulab Nov 1, 2023
2c740bf
fix
MarioLulab Nov 2, 2023
4dada50
open test_error for fused_feedforward
MarioLulab Nov 2, 2023
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4 changes: 2 additions & 2 deletions paddle/fluid/pir/dialect/op_generator/ops_api_gen.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -84,6 +84,8 @@
'fusion_gru',
'fusion_seqconv_eltadd_relu',
'fusion_seqexpand_concat_fc',
'fused_attention',
'fused_feedforward',
]

NO_NEED_GEN_STATIC_ONLY_APIS = [
Expand All @@ -99,10 +101,8 @@
'c_reduce_sum',
'dpsgd',
'embedding_grad_sparse',
'fused_attention',
'fused_batch_norm_act_',
'fused_bn_add_activation_',
'fused_feedforward',
'fused_scale_bias_relu_conv_bnstats',
'memcpy',
'print',
Expand Down
331 changes: 214 additions & 117 deletions python/paddle/incubate/nn/functional/fused_transformer.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,12 +12,13 @@
# See the License for the specific language governing permissions and
# limitations under the License.

from paddle import _legacy_C_ops
import paddle
from paddle import _C_ops, _legacy_C_ops
from paddle.base import core
from paddle.base.data_feeder import check_dtype, check_variable_and_dtype
from paddle.base.framework import default_main_program
from paddle.base.layer_helper import LayerHelper
from paddle.framework import in_dynamic_mode
from paddle.framework import in_dynamic_mode, in_dynamic_or_pir_mode

__all__ = []

Expand Down Expand Up @@ -134,52 +135,95 @@ def fused_feedforward(
'downgrade_in_infer' if mode == 'downscale_in_infer' else mode
) # semantic transfer

if in_dynamic_mode():
if default_main_program().random_seed != 0:
seed = default_main_program().random_seed
out, _, _, _, _, _, _, _, _, _, _ = _legacy_C_ops.fused_feedforward(
x,
None,
None,
linear1_weight,
linear1_bias,
linear2_weight,
linear2_bias,
ln1_scale,
ln1_bias,
ln2_scale,
ln2_bias,
'pre_layer_norm',
pre_layer_norm,
'ln1_epsilon',
ln1_epsilon,
'ln2_epsilon',
ln2_epsilon,
'act_method',
activation,
'dropout1_rate',
dropout1_rate,
'dropout2_rate',
dropout2_rate,
"is_test",
not training,
"dropout1_fix_seed",
seed is not None,
"dropout2_fix_seed",
seed is not None,
"dropout1_seed",
seed if seed is not None else 0,
"dropout2_seed",
seed if seed is not None else 0,
'dropout1_implementation',
mode,
'dropout2_implementation',
mode,
'add_residual',
add_residual,
'ring_id',
ring_id,
)
if in_dynamic_or_pir_mode():
if paddle.static.default_main_program().random_seed != 0:
seed = paddle.static.default_main_program().random_seed

if in_dynamic_mode():
out, _, _, _, _, _, _, _, _, _, _ = _legacy_C_ops.fused_feedforward(
x,
None,
None,
linear1_weight,
linear1_bias,
linear2_weight,
linear2_bias,
ln1_scale,
ln1_bias,
ln2_scale,
ln2_bias,
'pre_layer_norm',
pre_layer_norm,
'ln1_epsilon',
ln1_epsilon,
'ln2_epsilon',
ln2_epsilon,
'act_method',
activation,
'dropout1_rate',
dropout1_rate,
'dropout2_rate',
dropout2_rate,
"is_test",
not training,
"dropout1_fix_seed",
seed is not None,
"dropout2_fix_seed",
seed is not None,
"dropout1_seed",
seed if seed is not None else 0,
"dropout2_seed",
seed if seed is not None else 0,
'dropout1_implementation',
mode,
'dropout2_implementation',
mode,
'add_residual',
add_residual,
'ring_id',
ring_id,
)
else:
dtype = x.dtype
check_variable_and_dtype(
x, 'x', ['float16', 'float32', 'float64'], 'fused_feedforward'
)
check_dtype(
dtype,
'dtype',
['float16', 'float32', 'float64'],
'fused_feedforward',
)

out, _, _, _, _, _, _, _, _, _, _ = _C_ops.fused_feedforward(
x,
None,
None,
linear1_weight,
linear1_bias,
linear2_weight,
linear2_bias,
ln1_scale,
ln1_bias,
ln2_scale,
ln2_bias,
pre_layer_norm,
ln1_epsilon,
ln2_epsilon,
activation,
dropout1_rate,
dropout2_rate,
mode,
mode,
not training,
seed is not None,
seed is not None,
seed if seed is not None else 0,
seed if seed is not None else 0,
add_residual,
ring_id,
)

return out

helper = LayerHelper("fused_feedforward")
Expand Down Expand Up @@ -624,9 +668,9 @@ def fused_multi_head_attention(
f"The rank of the x should be 3, but received {x.ndim}."
)

if in_dynamic_mode():
if default_main_program().random_seed != 0:
seed = default_main_program().random_seed
if in_dynamic_or_pir_mode():
if paddle.static.default_main_program().random_seed != 0:
seed = paddle.static.default_main_program().random_seed
# pre_ln_mean, pre_ln_variance, pre_ln_out, qkv_out, qkv_bias_out, transpose_out, qk_out,
# qktv_out, softmax_out, attn_dropout_mask_out, attn_dropout_out, attn_mask_out, fmha_out,
# linear_out, dropout_mask_out, ln_mean_out, ln_var_out, bias_dropout_residual_out, final_out
Expand Down Expand Up @@ -672,72 +716,125 @@ def fused_multi_head_attention(
"When enable transpose_qkv_wb, the 1st dim of qkv_bias and 2nd dim of "
"qkv_weight should be the same, i.e., embed_dim."
)
(
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
cache_kv_out,
final_out,
) = _legacy_C_ops.fused_attention(
x,
pre_ln_scale,
pre_ln_bias,
qkv_weight,
qkv_bias,
cache_kv,
attn_mask,
linear_weight,
linear_bias,
ln_scale,
ln_bias,
'num_heads',
num_heads,
'transpose_qkv_wb',
transpose_qkv_wb,
'pre_layer_norm',
pre_layer_norm,
'epsilon',
pre_ln_epsilon,
'dropout_rate',
dropout_rate,
'attn_dropout_rate',
attn_dropout_rate,
'ln_epsilon',
ln_epsilon,
'is_test',
not training,
'attn_dropout_fix_seed',
seed is not None,
'dropout_fix_seed',
seed is not None,
'attn_dropout_seed',
seed if seed is not None else 0,
'dropout_seed',
seed if seed is not None else 0,
'attn_dropout_implementation',
mode,
'dropout_implementation',
mode,
'add_residual',
add_residual,
'ring_id',
ring_id,
)
if in_dynamic_mode():
(
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
cache_kv_out,
final_out,
) = _legacy_C_ops.fused_attention(
x,
pre_ln_scale,
pre_ln_bias,
qkv_weight,
qkv_bias,
cache_kv,
attn_mask,
linear_weight,
linear_bias,
ln_scale,
ln_bias,
'num_heads',
num_heads,
'transpose_qkv_wb',
transpose_qkv_wb,
'pre_layer_norm',
pre_layer_norm,
'epsilon',
pre_ln_epsilon,
'dropout_rate',
dropout_rate,
'attn_dropout_rate',
attn_dropout_rate,
'ln_epsilon',
ln_epsilon,
'is_test',
not training,
'attn_dropout_fix_seed',
seed is not None,
'dropout_fix_seed',
seed is not None,
'attn_dropout_seed',
seed if seed is not None else 0,
'dropout_seed',
seed if seed is not None else 0,
'attn_dropout_implementation',
mode,
'dropout_implementation',
mode,
'add_residual',
add_residual,
'ring_id',
ring_id,
)
else:
(
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
_,
cache_kv_out,
final_out,
) = _C_ops.fused_attention(
x,
pre_ln_scale,
pre_ln_bias,
qkv_weight,
qkv_bias,
cache_kv,
attn_mask,
linear_weight,
linear_bias,
ln_scale,
ln_bias,
num_heads,
transpose_qkv_wb,
pre_layer_norm,
pre_ln_epsilon,
attn_dropout_rate,
not training,
seed is not None,
seed if seed is not None else 0,
mode,
dropout_rate,
seed is not None,
seed if seed is not None else 0,
mode,
ln_epsilon,
add_residual,
ring_id,
)

if cache_kv is not None:
return final_out, cache_kv_out
return final_out
Expand Down
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