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Hi,
I am trying to first upload the model and code, and then run inference job.
For uploading the model from my local system, I am following this blog: https://docs.trainml.ai/blog/2021/06/28/local-model-integration/#using-the-sdk
I just want to upload the model first, but not to run a training job. In that case, what should I put the type field value?
Below is the code snippet I'm using for uploading the model. When I run below code, I'm getting an error which I pasted below the code. Is anything else not correct in the below code which is resulting in the error?
async def run_model_upload_job():
job = await trainml_client.jobs.create(
name="Personalization_video_model_trial_v1",
model=dict(source_type="local", source_uri="/home/tejaswini/Documents/Product_v1"),
type="model_load",
gpu_type="GTX 1060",
gpu_count=1,
disk_size=10
)
print(job)
await job.wait_for("waiting for model upload")
attach_task = asyncio.create_task(job.attach())
connect_task = asyncio.create_task(job.connect())
await asyncio.gather(attach_task, connect_task)
# Cleanup job
await job.disconnect()
await job.remove()
{'message': 'Invalid request body'}
Traceback (most recent call last):
File "load_model.py", line 66, in <module>
asyncio.run(run_model_upload_job())
File "/usr/lib/python3.8/asyncio/runners.py", line 44, in run
return loop.run_until_complete(main)
File "/usr/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete
return future.result()
File "load_model.py", line 17, in run_model_upload_job
job = await trainml_client.jobs.create(
File "/home/tejaswini/Documents/serverless_gpu_trial/trainml_ai/.venv/lib/python3.8/site-packages/trainml/jobs.py", line 115, in create
job = await self.create_json(payload)
File "/home/tejaswini/Documents/serverless_gpu_trial/trainml_ai/.venv/lib/python3.8/site-packages/trainml/jobs.py", line 121, in create_json
resp = await self.trainml._query("/job", "POST", None, payload)
File "/home/tejaswini/Documents/serverless_gpu_trial/trainml_ai/.venv/lib/python3.8/site-packages/trainml/trainml.py", line 129, in _query
raise ApiError(
trainml.exceptions.ApiError: ApiError(400, 'Invalid request body')
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