", "type": "str", "value": "" }, "collection_indexing_policy": { "display_name": "Collection Indexing Policy", "info": "Optional dictionary defining the indexing policy for the collection.", "type": "str", "value": "" }, "add_to_vector_store": { "display_name": "Add to ...
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(tranforms,on='tfidx').I realize this is inefficient, because there are 2,400x less transforms than clouds, and this greatly expands the total dataset. The only other option is putting the tranforms into a dictionary and looping on slices, which, as I have already mentioned, isquite slow...
Parameter name: key at System.ThrowHelper.ThrowArgumentNullException(ExceptionArgument argument) at System.Collections.Generic.Dictionary`2.FindEntry(TKey key) at System.Collections.Generic.Dictionary`2.TryGetValue(TKey key, TValue& value) at Python.Runtime.Runtime.InitializePlatformData() at Python....
(checkpoint_dir_path, 'step2/cp.ckpt') # Defining a dictionary with the hyperparameters hyperparameters = { "base_learning_rate": 0.0001, "BATCH_SIZE": 8, "beta1": 0.9, "beta2": 0.999, "epsilon": 1e-07 } IMG_SIZE=(283, 577) IMG_SHAPE = IMG_SIZE + (3,) _URL = 'https:/...