Image Classification - TensorFlow #3808
Unanswered
Aashish-wj
asked this question in
Help
Replies: 0 comments
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
-
ClientError: An error occurred (ValidationException) when calling the CreateTrainingJob operation: RepositoryName shouldn't contain a scheme
I am uncertain as to the root cause of the issue at hand. I would greatly appreciate any insights that someone may be able to offer in this regard.
I followed the steps in this document
https://docs.aws.amazon.com/sagemaker/latest/dg/image-classification-tensorflow.html#IC-TF-sample-notebooks
My code :
from sagemaker import image_uris, model_uris, script_uris, hyperparameters
from sagemaker.estimator import Estimator
model_id, model_version = "tensorflow-ic-imagenet-mobilenet-v2-100-224-classification-4", "*"
training_instance_type = "ml.p3.2xlarge"
train_image_uri = image_uris.retrieve(model_id=model_id,
model_version=model_version,
image_scope="training",
instance_type=training_instance_type,
region=region,
framework=None)
train_source_uri = script_uris.retrieve(model_id=model_id, model_version=model_version, script_scope="training")
train_model_uri = model_uris.retrieve(model_id=model_id, model_version=model_version, model_scope="training")
hyperparameters = hyperparameters.retrieve_default(model_id=model_id, model_version=model_version)
training_dataset_s3_path = train_image_uri
s3_output_location = model_op
tf_ic_estimator = Estimator(
role=role_arn,
image_uri=train_image_uri,
source_dir=train_source_uri,
model_uri=train_model_uri,
entry_point="transfer_learning.py",
instance_count=1,
instance_type=training_instance_type,
max_run=360000,
hyperparameters=hyperparameters,
output_path=s3_output_location,
)
tf_ic_estimator.fit({"training": training_dataset_s3_path}, logs=True)
Beta Was this translation helpful? Give feedback.
All reactions