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fixed validation error when using flash attention #2142

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fixed validation error when using flash attention #2142

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07d729a
fixed validation error when using flash attention
francesco-bertolotti Dec 11, 2025
628dbb6
propagated fix for pipeline parallelism
francesco-bertolotti Dec 12, 2025
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19 changes: 17 additions & 2 deletions torchtitan/components/validate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.

from typing import Generator
from typing import Generator, Any

import torch
import torch.nn as nn
Expand All @@ -18,6 +18,7 @@
from torchtitan.hf_datasets.text_datasets import build_text_validation_dataloader
from torchtitan.tools import utils
from torchtitan.tools.logging import logger
import torchtitan.protocols.train_spec as train_spec_module


class BaseValidator:
Expand Down Expand Up @@ -62,6 +63,7 @@ def __init__(
self.job_config = job_config
self.parallel_dims = parallel_dims
self.loss_fn = loss_fn
self.tokenizer = tokenizer
self.validation_dataloader = build_text_validation_dataloader(
job_config=job_config,
dp_world_size=dp_world_size,
Expand All @@ -76,12 +78,18 @@ def __init__(
self.pp_has_first_stage = pp_has_first_stage
self.pp_has_last_stage = pp_has_last_stage

self.train_spec = train_spec_module.get_train_spec(job_config.model.name)
model_args = self.train_spec.model_args[job_config.model.flavor]
model_args.update_from_config(job_config)
self.model_args = model_args

if self.job_config.validation.steps == -1:
logger.warning(
"Setting validation steps to -1 might cause hangs because of "
"unequal sample counts across ranks when dataset is exhausted."
)


@torch.no_grad()
def validate(
self,
Expand All @@ -105,6 +113,13 @@ def validate(
):
break

# prepare attention mask
extra_kwargs : dict[str, Any] = {"attention_masks" : model_parts[0].get_attention_masks(
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@wwwjn wwwjn Dec 12, 2025

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For readability, can you make this into a function similar as: https://github.com/pytorch/torchtitan/blob/refs/heads/main/torchtitan/train.py#L416C9-L416C33

input_batch=input_dict["input"],
tokenizer=self.tokenizer,
extra_inputs={k: v for k, v in input_dict.items() if k != "input"},
)} if getattr(self.model_args, "attn_type", "sdpa") in ["flex", "varlen"] else {}

self.metrics_processor.ntokens_since_last_log += labels.numel()
for k, v in input_dict.items():
input_dict[k] = v.to(device_type)
Expand Down Expand Up @@ -155,7 +170,7 @@ def validate(
with self.validation_context(optional_context_parallel_ctx):
assert len(model_parts) == 1
with self.maybe_enable_amp:
predictions = model_parts[0](inputs)
predictions = model_parts[0](inputs, **extra_kwargs)
loss = self.loss_fn(predictions, labels)

accumulated_losses.append(loss.detach())
Expand Down
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