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fix code style
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@zhangting2020
zhangting2020 committed Jun 21, 2022
1 parent 9941a14 commit 2e3d220
Showing 1 changed file with 50 additions and 49 deletions.
99 changes: 50 additions & 49 deletions python/paddle/incubate/nn/functional/fused_transformer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -137,9 +137,9 @@ def fused_feedforward(x,
'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_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)
return out
Expand Down Expand Up @@ -176,48 +176,49 @@ def fused_feedforward(x,
if (seed is None or seed == 0) and helper.main_program.random_seed != 0:
seed = helper.main_program.random_seed

helper.append_op(type='fused_feedforward',
inputs={
'X': x,
'Linear1Weight': linear1_weight,
'Linear1Bias': linear1_bias,
'Linear2Weight': linear2_weight,
'Linear2Bias': linear2_bias,
'Ln1Scale': ln1_scale,
'Ln1Bias': ln1_bias,
'Ln2Scale': ln2_scale,
'Ln2Bias': ln2_bias,
},
outputs={
'Out': out,
'Dropout1Mask': dropout1_mask,
'Dropout2Mask': dropout2_mask,
'Ln1Mean': ln1_mean,
'Ln1Variance': ln1_variance,
'Ln2Mean': ln2_mean,
'Ln2Variance': ln2_variance,
'Linear1Out': linear1_out,
'Ln1Out': ln1_out,
'Dropout1Out': dropout1_out,
'Dropout2Out': dropout2_out,
},
attrs={
'dropout1_rate': dropout1_rate,
'dropout2_rate': dropout2_rate,
'act_method': activation,
'pre_layer_norm': pre_layer_norm,
'ln1_epsilon': ln1_epsilon,
'ln2_epsilon': ln2_epsilon,
'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,
})
helper.append_op(
type='fused_feedforward',
inputs={
'X': x,
'Linear1Weight': linear1_weight,
'Linear1Bias': linear1_bias,
'Linear2Weight': linear2_weight,
'Linear2Bias': linear2_bias,
'Ln1Scale': ln1_scale,
'Ln1Bias': ln1_bias,
'Ln2Scale': ln2_scale,
'Ln2Bias': ln2_bias,
},
outputs={
'Out': out,
'Dropout1Mask': dropout1_mask,
'Dropout2Mask': dropout2_mask,
'Ln1Mean': ln1_mean,
'Ln1Variance': ln1_variance,
'Ln2Mean': ln2_mean,
'Ln2Variance': ln2_variance,
'Linear1Out': linear1_out,
'Ln1Out': ln1_out,
'Dropout1Out': dropout1_out,
'Dropout2Out': dropout2_out,
},
attrs={
'dropout1_rate': dropout1_rate,
'dropout2_rate': dropout2_rate,
'act_method': activation,
'pre_layer_norm': pre_layer_norm,
'ln1_epsilon': ln1_epsilon,
'ln2_epsilon': ln2_epsilon,
'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,
})
return out


Expand Down Expand Up @@ -388,10 +389,10 @@ def fused_multi_head_attention(x,
'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,
'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 cache_kv is not None:
return final_out, cache_kv_out
Expand Down

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