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support mtp and cp open at the same time #725

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11f13d2
support mtp + cp
Apr 3, 2026
134f16c
Revert "support mtp + cp"
Apr 3, 2026
354266d
support mtp cp
Apr 3, 2026
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24 changes: 16 additions & 8 deletions src/paddlefleet/models/common/language_loss/language_loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -248,8 +248,20 @@ def forward(self, logits: Tensor | list, labels: Tensor) -> Tensor:
)
assert len(logits) == self.config.num_nextn_predict_layers + 1
labels_ori = labels
lm_labels = labels[:, : -self.config.num_nextn_predict_layers]
seq_length = lm_labels.shape[1]
if self.config.context_parallel_size > 1:
label_list = paddle.split(labels, self.config.num_nextn_predict_layers + 1)
lm_labels = label_list[0]
mtp_labels = label_list[1:]
seq_length = lm_labels.shape[1]
else:
lm_labels = labels[:, : -self.config.num_nextn_predict_layers]
mtp_labels = []
seq_length = lm_labels.shape[1]
for depth in range(self.config.num_nextn_predict_layers):
labels_cur_depth = labels_ori[
:, (depth + 1) : (depth + 1 + seq_length)
]
mtp_labels.append(labels_cur_depth)

mtp_loss = []
mtp_logits = logits[1:]
Expand All @@ -262,9 +274,7 @@ def forward(self, logits: Tensor | list, labels: Tensor) -> Tensor:

for depth in range(self.config.num_nextn_predict_layers):
logits_cur_depth = mtp_logits[depth]
labels_cur_depth = labels_ori[
:, (depth + 1) : (depth + 1 + seq_length)
]
labels_cur_depth = mtp_labels[depth]
loss_cur_depth = self._forward(
logits_cur_depth,
labels_cur_depth,
Expand Down Expand Up @@ -298,9 +308,7 @@ def padding(tensor, left=False, pad_len=1):
):
for depth in range(len(mtp_logits)):
prediction_scores_cur_depth = mtp_logits[depth]
labels_cur_depth = labels_ori[
:, (depth + 1) : (depth + 1 + seq_length)
]
labels_cur_depth = mtp_labels[depth]
lossmask = (
labels_cur_depth != self.ignored_index
).cast(paddle.float32)
Expand Down
42 changes: 28 additions & 14 deletions src/paddlefleet/models/gpt/gpt_embedding.py
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Original file line number Diff line number Diff line change
Expand Up @@ -142,13 +142,24 @@ def forward(
assert not self.multimodal_embedding, (
"MTP not support mm for now."
)
inputs_embeds_extra = decoder_input[
:, -self.config.num_nextn_predict_layers :, :
] # [B, S, H]
inputs_embeds = decoder_input[
:, : -self.config.num_nextn_predict_layers, :
]
inputs_embeds_ori = inputs_embeds
if self.config.context_parallel_size > 1:
# when mtp and cp are opened at the same time,
# shape of decoder_input is [(K + 1)*B, S, H]
# K is the number of num_nextn_predict_layers
tensor_list = paddle.split(decoder_input, self.config.num_nextn_predict_layers+1)
inputs_embeds = tensor_list[0] # [B, S, H]
inputs_embeds_extra = tensor_list[1:] # K * [B, S, H]
else:
# when just mtp is opened,
# shape of decoder_input is [B, S + K, H]
# K is the number of num_nextn_predict_layers
inputs_embeds_extra = decoder_input[
:, -self.config.num_nextn_predict_layers :, :
] # [B, k, H]
inputs_embeds = decoder_input[
:, : -self.config.num_nextn_predict_layers, :
] # [B, S, H]
inputs_embeds_ori = inputs_embeds
batch_size, seq_length, hidden_size = inputs_embeds.shape

if self.sequence_parallel:
Expand All @@ -163,13 +174,16 @@ def forward(
) # change to [S, B, H]
mtp_emb_res = [inputs_embeds]
for depth in range(self.config.num_nextn_predict_layers):
inputs_embeds_mtp = paddle.concat(
[
inputs_embeds_ori[:, (depth + 1) :, :],
inputs_embeds_extra[:, : (depth + 1), :],
],
axis=1,
)
if self.config.context_parallel_size > 1:
inputs_embeds_mtp = inputs_embeds_extra[depth]
else:
inputs_embeds_mtp = paddle.concat(
[
inputs_embeds_ori[:, (depth + 1) :, :],
inputs_embeds_extra[:, : (depth + 1), :],
],
axis=1,
)
if self.sequence_parallel:
inputs_embeds_mtp = inputs_embeds_mtp.reshape(
[-1, inputs_embeds_mtp.shape[-1]]
Expand Down
28 changes: 19 additions & 9 deletions src/paddlefleet/transformer/transformer_layer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -412,12 +412,17 @@ def forward(
# process position_ids
if "position_ids" in dict_args.keys():
position_ids = dict_args["position_ids"]
decoder_ids = position_ids[
:, : -self.config.num_nextn_predict_layers
]
mtp_ids = position_ids[
:, -self.config.num_nextn_predict_layers :
]
if self.config.context_parallel_size > 1:
tensor_list = paddle.split(position_ids, self.config.num_nextn_predict_layers + 1)
decoder_ids = tensor_list[0]
mtp_ids = tensor_list[1:]
else:
decoder_ids = position_ids[
:, : -self.config.num_nextn_predict_layers
]
mtp_ids = position_ids[
:, -self.config.num_nextn_predict_layers :
]
dict_args["position_ids"] = decoder_ids

# #process attn_mask_startend_row_indices
Expand Down Expand Up @@ -500,9 +505,14 @@ def forward(
rst["hidden_states"] = hidden_states_concat

if "position_ids" in dict_args.keys():
position_ids = paddle.concat(
[dict_args["position_ids"], mtp_ids], axis=1
)
if self.config.context_parallel_size > 1:
position_ids = paddle.concat(
[dict_args["position_ids"], *mtp_ids], axis=0
)
else:
position_ids = paddle.concat(
[dict_args["position_ids"], mtp_ids], axis=1
)
dict_args["position_ids"] = position_ids

if "attn_mask_startend_row_indices" in dict_args.keys():
Expand Down
11 changes: 9 additions & 2 deletions src/paddlefleet/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -267,15 +267,22 @@ def is_paddle_min_version(version, check_equality=True):
########################


def get_batch_on_this_cp_rank(inputs):
def get_batch_on_this_cp_rank(inputs, num_nextn_predict_layers=0):
if isinstance(inputs, paddle.Tensor):
return ContextParallelScatterOp.apply(inputs, axis=-1)
elif isinstance(inputs, dict):
res = {}
keys = ["input_ids", "position_ids", "labels"]
for k, tensor in inputs.items():
if k in keys:
res[k] = ContextParallelScatterOp.apply(tensor, axis=-1)
seq_len = tensor.shape[-1]
chunk_size = seq_len - num_nextn_predict_layers
res[k] = []
for i in range(num_nextn_predict_layers+1):
tensor_chunk = tensor[:, i : i+chunk_size]
res[k].append(ContextParallelScatterOp.apply(tensor_chunk, axis=-1))
# tensor shape = [(k+1)*b, s]
res[k] = paddle.concat(res[k])
else:
res[k] = tensor
elif isinstance(inputs, list):
Expand Down
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