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[PIR]Using inplace batch norm in PIR #59752

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[PIR]Using inplace batch norm in PIR #59752

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2 changes: 1 addition & 1 deletion paddle/fluid/pir/dialect/op_generator/ops_api_gen.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,6 +82,7 @@
'generate_sequence_xpu',
'layer_norm_act_xpu',
'memcpy',
'batch_norm_',
'multi_encoder_xpu',
'multihead_matmul',
'squeeze_excitation_block',
Expand All @@ -104,7 +105,6 @@
'add_n_',
'add_n_with_kernel',
'assign_value',
'batch_norm_',
'c_allgather',
'c_allreduce_max',
'c_allreduce_sum',
Expand Down
33 changes: 25 additions & 8 deletions python/paddle/nn/layer/norm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -42,6 +42,7 @@
_global_flags,
get_default_dtype,
in_dynamic_or_pir_mode,
in_pir_mode,
no_grad,
)
from .. import functional as F
Expand Down Expand Up @@ -1056,7 +1057,7 @@ def __init__(
self._trainable_statistics = trainable_statistics

def forward(self, input):
if in_dynamic_or_pir_mode():
if in_dynamic_mode():
batch_norm_out, t1, t2, t3, t4, _ = _C_ops.batch_norm(
input,
self._mean,
Expand All @@ -1072,13 +1073,29 @@ def forward(self, input):
)
if self._act is None:
return batch_norm_out
if in_dynamic_mode():
return dygraph_utils._append_activation_in_dygraph(
batch_norm_out, act=self._act, use_mkldnn=self._use_mkldnn
)
else:
act_op = getattr(_C_ops, self._act)
return act_op(batch_norm_out)

return dygraph_utils._append_activation_in_dygraph(
batch_norm_out, act=self._act, use_mkldnn=self._use_mkldnn
)
elif in_pir_mode():
batch_norm_out, t1, t2, t3, t4, _ = _C_ops.batch_norm_(
input,
self._mean,
self._variance,
self.weight,
self.bias,
not self.training,
self._momentum,
self._epsilon,
self._data_layout,
self._use_global_stats,
self._trainable_statistics,
)
if self._act is None:
return batch_norm_out

act_op = getattr(_C_ops, self._act)
return act_op(batch_norm_out)
else:
# create output
# mean and mean_out share the same memory
Expand Down