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weiyixuanxxweiyixuanxx
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Merge branch 'PaddlePaddle:develop' into dev_mtp_mask
2 parents 34495c8 + 94a7d3d commit ee60bdb

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Lines changed: 1217 additions & 397 deletions

‎.github/workflows/check-bypass.yml‎

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on:
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workflow_call:
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inputs:
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workflow-name:
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required: true
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type: string
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secrets:
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github-token:
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required: true
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outputs:
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can-skip:
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description: "Whether the workflow can be skipped."
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value: ${{ jobs.check-bypass.outputs.can-skip }}
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jobs:
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check-bypass:
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name: Check bypass
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runs-on: ubuntu-latest
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permissions:
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contents: read
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env:
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CI_TEAM_MEMBERS: '["swgu98", "risemeup1" , "XieYunshen", "tianlef"]'
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outputs:
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can-skip: ${{ steps.check-bypass.outputs.can-skip }}
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steps:
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- id: check-bypass
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name: Check Bypass
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uses: PFCCLab/ci-bypass@v2
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with:
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github-token: ${{ secrets.GITHUB_TOKEN }}
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non-pull-request-event-strategy: 'never-skipped'
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type: 'composite'
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composite-rule: |
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{
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"any": [
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{
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"type": "labeled",
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"label": ["skip-ci: ${{ inputs.workflow-name }}", "skip-ci: all"],
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"username": ${{ env.CI_TEAM_MEMBERS }}
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},
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{
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"type": "commented",
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"comment-pattern": [".*/skip-ci ${{ inputs.workflow-name }}.*", ".*/skip-ci all.*"],
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"username": ${{ env.CI_TEAM_MEMBERS }}
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}
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]
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}

‎.github/workflows/cherry-pick.yml‎

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@@ -38,9 +38,8 @@ jobs:
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PR_BODY: ${{ github.event.pull_request.body }}
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PR_AUTHOR: ${{ github.event.pull_request.user.login }}
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MERGE_COMMIT_SHA: ${{ github.event.pull_request.merge_commit_sha }}
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BOT_USERNAME: ShigureNyako
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BOT_EMAIL: shigure_nyako@outlook.com
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REPO_NAME: ShigureNyako/PaddleFormers
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BOT_USERNAME: risemeup1111
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REPO_NAME: risemeup1111/PaddleFormers
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run: |
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# Function to post comment
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post_comment() {

‎.github/workflows/fleet-model-test.yml‎

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shell: bash
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jobs:
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check_skip:
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name: Check skip-fleet-models-ci label
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runs-on: ubuntu-latest
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outputs:
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skip: ${{ steps.check_skip.outputs.skip }}
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steps:
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- name: Check skip-fleet-models-ci label
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id: check_skip
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shell: bash
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run: |
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if [[ "${{ github.event_name }}" == "pull_request" ]]; then
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labels='${{ toJson(github.event.pull_request.labels.*.name) }}'
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echo "PR labels: $labels"
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if echo "$labels" | grep -q "skip-fleet-models-ci"; then
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echo "skip=true" >> "$GITHUB_OUTPUT"
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else
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echo "skip=false" >> "$GITHUB_OUTPUT"
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fi
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else
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echo "skip=false" >> "$GITHUB_OUTPUT"
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fi
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- name: Skip CI but mark success
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if: steps.check_skip.outputs.skip == 'true'
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run: |
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echo "skip-fleet-models-ci label found"
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echo "Downstream GPU jobs will be skipped"
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check-bypass:
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name: Check bypass
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if: ${{ inputs.can-skip != 'true' }}
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uses: ./.github/workflows/check-bypass.yml
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with:
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workflow-name: 'fleet-model-test'
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secrets:
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github-token: ${{ secrets.GITHUB_TOKEN }}
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check_documents_type:
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needs: check_skip
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if: ${{ needs.check_skip.outputs.skip == 'false' }}
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needs: check-bypass
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if: ${{ needs.check-bypass.outputs.can-skip == 'false' }}
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name: check documents type for pull request
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runs-on: ubuntu-latest
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env:
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echo "is_md_only: $(cat $GITHUB_OUTPUT | grep is_md_only || echo '未找到')"
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integration-test-H20-single-card:
106-
needs: [check_documents_type, check_skip]
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if: ${{ needs.check_documents_type.outputs.is_md_only == 'false' && needs.check_skip.outputs.skip == 'false' }}
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needs: [check_documents_type, check-bypass]
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if: ${{ needs.check_documents_type.outputs.is_md_only == 'false' && needs.check-bypass.outputs.can-skip == 'false' }}
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name: Integration test (H20, single card)
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runs-on:
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group: Fleet-H-single-card
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integration-test-H20-multi-card:
269-
needs: [check_documents_type, check_skip]
270-
if: ${{ needs.check_documents_type.outputs.is_md_only == 'false' && needs.check_skip.outputs.skip == 'false' }}
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needs: [check_documents_type, check-bypass]
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if: ${{ needs.check_documents_type.outputs.is_md_only == 'false' && needs.check-bypass.outputs.can-skip == 'false' }}
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name: Integration test (H20, multi-card)
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runs-on:
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group: Fleet-H-multi-card
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integration-test-a100:
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needs: [check_documents_type, check_skip]
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if: ${{ needs.check_documents_type.outputs.is_md_only == 'false' && needs.check_skip.outputs.skip == 'false' }}
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needs: [check_documents_type, check-bypass]
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if: ${{ needs.check_documents_type.outputs.is_md_only == 'false' && needs.check-bypass.outputs.can-skip == 'false' }}
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name: Integration test (A100)
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runs-on:
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group: Distribute

‎.github/workflows/remove-skip-lables.yml‎

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name: Remove Skip-CI Labels
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on:
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pull_request_target:
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types: [synchronize]
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permissions:
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pull-requests: write
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jobs:
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remove-skip-ci-labels:
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name: Remove skip-ci labels on new commits
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runs-on: ubuntu-latest
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steps:
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- name: Get PR labels
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id: get-labels
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uses: actions/github-script@v8
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with:
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github-token: ${{ secrets.GITHUB_TOKEN }}
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script: |
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const { data: labels } = await github.rest.issues.listLabelsOnIssue({
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owner: context.repo.owner,
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repo: context.repo.repo,
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issue_number: context.issue.number
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});
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const skipCiLabels = labels
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.filter(label => label.name.startsWith('skip-ci:'))
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.map(label => label.name);
30+
31+
console.log('Found skip-ci labels:', skipCiLabels);
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core.setOutput('skip-ci-labels', JSON.stringify(skipCiLabels));
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core.setOutput('has-skip-ci-labels', skipCiLabels.length > 0 ? 'true' : 'false');
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- name: Remove skip-ci labels
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if: steps.get-labels.outputs.has-skip-ci-labels == 'true'
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uses: actions/github-script@v8
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with:
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github-token: ${{ secrets.GITHUB_TOKEN }}
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script: |
41+
const skipCiLabels = JSON.parse('${{ steps.get-labels.outputs.skip-ci-labels }}');
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for (const label of skipCiLabels) {
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console.log(`Removing label: ${label}`);
45+
await github.rest.issues.removeLabel({
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owner: context.repo.owner,
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repo: context.repo.repo,
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issue_number: context.issue.number,
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name: label
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});
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}
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console.log(`Successfully removed ${skipCiLabels.length} skip-ci label(s)`);

‎examples/experiments/ernie_pretrain/ernie/src/callbacks/moe_correction_bias_adjust_callback.py‎

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self.use_sp = use_sp
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def on_optimizer_end(self, args, state, control, **kwargs):
35+
# Skip bias update when freeze_training is enabled
36+
if getattr(args, "freeze_training", False):
37+
logger.warning("freeze_training is enabled! MoE e_score_correction_bias will NOT be updated.")
38+
return
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3540
model = kwargs["model"]
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usages = {}

‎examples/experiments/ernie_pretrain/ernie/src/trainers/pretraining_trainer.py‎

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13001300
self._end_save_time = time.time()
13011301

13021302
def create_scheduler(self, num_training_steps):
1303+
# When freeze_training is enabled, use constant scheduler with lr=0
1304+
if getattr(self.args, "freeze_training", False):
1305+
logger.warning(
1306+
"WARNING: freeze_training is enabled! "
1307+
"Learning rate is set to 0 and model parameters will NOT be updated. "
1308+
"This mode is intended for debugging/profiling only, NOT for actual training."
1309+
)
1310+
from paddleformers.trainer.trainer_utils import get_constant_schedule
1311+
1312+
self.lr_scheduler = get_constant_schedule(learning_rate=0.0)
1313+
return self.lr_scheduler
1314+
13031315
if self.args.warmup_steps > 0:
13041316
warmup = self.args.warmup_steps
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else:

‎paddleformers/cli/train/ernie_pretrain/src/callbacks/moe_correction_bias_adjust_callback.py‎

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self.use_sp = use_sp
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3636
def on_optimizer_end(self, args, state, control, **kwargs):
37+
# Skip bias update when freeze_training is enabled
38+
if getattr(args, "freeze_training", False):
39+
logger.warning("freeze_training is enabled! MoE e_score_correction_bias will NOT be updated.")
40+
return
41+
3742
model = kwargs["model"]
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3944
usages = {}

‎paddleformers/cli/train/ernie_pretrain/src/trainers/pretraining_trainer.py‎

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13141314
self._end_save_time = time.time()
13151315

13161316
def create_scheduler(self, num_training_steps):
1317+
# When freeze_training is enabled, use constant scheduler with lr=0
1318+
if getattr(self.args, "freeze_training", False):
1319+
logger.warning(
1320+
"WARNING: freeze_training is enabled! "
1321+
"Learning rate is set to 0 and model parameters will NOT be updated. "
1322+
"This mode is intended for debugging/profiling only, NOT for actual training."
1323+
)
1324+
from paddleformers.trainer.trainer_utils import get_constant_schedule
1325+
1326+
self.lr_scheduler = get_constant_schedule(learning_rate=0.0)
1327+
return self.lr_scheduler
1328+
13171329
if self.args.warmup_steps > 0:
13181330
warmup = self.args.warmup_steps
13191331
else:

‎paddleformers/data/__init__.py‎

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"tolist",
4747
"DataCollatorForLanguageModeling",
4848
],
49-
"dist_dataloader": ["DummyDataset", "IterableDummyDataset", "DistDataLoader", "init_dataloader_comm_group"],
49+
"dist_dataloader": [
50+
"DummyDataset",
51+
"IterableDummyDataset",
52+
"DistDataLoader",
53+
"init_dataloader_comm_group",
54+
"StreamDistDataLoader",
55+
"init_stream_data_group",
56+
],
5057
"collate": ["Dict", "Pad", "Stack", "Tuple"],
5158
"vocab": ["Vocab"],
5259
"tokenizer": ["BaseTokenizer"],

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