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I have gone through the example: opensearch-py-ml/examples/demo_deploy_cliptextmodel.html
Model is correctly registered in opensearch cluster but the final command of the example:
ml_client.deploy_model(model_id)
ends with an error Exception: Model deployment failed
Afrer trying to deploy the model using console directly on the cluster i.e.:
POST /_plugins/_ml/models/<model_id>/_deploy
and checking the corresponding task output:
GET /_plugins/_ml/tasks/<task_id>
I see that deployment fails with the following error returned by the task:
{
"model_id": "uDNmgZIBC9ZdJM8aMbns",
"task_type": "DEPLOY_MODEL",
"function_name": "TEXT_EMBEDDING",
"state": "FAILED",
"worker_node": [
"xbE0btjVQUGBAWrVqCmUoQ"
],
"create_time": 1728748205169,
"last_update_time": 1728748210632, "error": """{"xbE0btjVQUGBAWrVqCmUoQ":"\nUnknown builtin op: aten::scaled_dot_product_attention.\nHere are some suggestions: \n\taten::_scaled_dot_product_attention\n\nThe original call is:\n File "code/torch/transformers/models/clip/modeling_clip.py", line 190\n key_states = torch.transpose(torch.view(_54, [_49, -1, 8, 64]), 1, 2)\n value_states = torch.transpose(torch.view(_55, [_48, -1, 8, 64]), 1, 2)\n attn_output = torch.scaled_dot_product_attention(query_states, key_states, value_states, attn_mask, 0., False, scale=0.125)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE\n attn_output0 = torch.transpose(attn_output, 1, 2)\n input = torch.reshape(attn_output0, [_47, _51, _52])\n"}""",
"is_async": true
}
The text was updated successfully, but these errors were encountered:
The same error is raised when trying to deploy other transformer models e.g.:
model_name = "bert-base-uncased"
text_to_encode = "example search query"
model = BertModel.from_pretrained(model_name, torchscript=True, return_dict=False)
processor = BertTokenizer.from_pretrained(model_name)
I have gone through the example: opensearch-py-ml/examples/demo_deploy_cliptextmodel.html
Model is correctly registered in opensearch cluster but the final command of the example:
ml_client.deploy_model(model_id)
ends with an error Exception: Model deployment failed
Afrer trying to deploy the model using console directly on the cluster i.e.:
POST /_plugins/_ml/models/<model_id>/_deploy
and checking the corresponding task output:
GET /_plugins/_ml/tasks/<task_id>
I see that deployment fails with the following error returned by the task:
{
"model_id": "uDNmgZIBC9ZdJM8aMbns",
"task_type": "DEPLOY_MODEL",
"function_name": "TEXT_EMBEDDING",
"state": "FAILED",
"worker_node": [
"xbE0btjVQUGBAWrVqCmUoQ"
],
"create_time": 1728748205169,
"last_update_time": 1728748210632,
"error": """{"xbE0btjVQUGBAWrVqCmUoQ":"\nUnknown builtin op: aten::scaled_dot_product_attention.\nHere are some suggestions: \n\taten::_scaled_dot_product_attention\n\nThe original call is:\n File "code/torch/transformers/models/clip/modeling_clip.py", line 190\n key_states = torch.transpose(torch.view(_54, [_49, -1, 8, 64]), 1, 2)\n value_states = torch.transpose(torch.view(_55, [_48, -1, 8, 64]), 1, 2)\n attn_output = torch.scaled_dot_product_attention(query_states, key_states, value_states, attn_mask, 0., False, scale=0.125)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE\n attn_output0 = torch.transpose(attn_output, 1, 2)\n input = torch.reshape(attn_output0, [_47, _51, _52])\n"}""",
"is_async": true
}
The text was updated successfully, but these errors were encountered: