How did Python find 5 in a dictionary containing 5.0? Python does this in constant time without having to scan through every item by using hash functions. When Python looks up a key foo in a dict, it first computes hash(foo) (which runs in constant-time). Since in Python it is requir...
[0, 1, 2]], dtype=uint8) >>> g = eng.mean(image) However, I received the following error: Traceback (most recent call last): File"<pyshell#19>", line1, in<module> g = eng.mean(image) File"C:\Python27\lib\site-packages\matlab\engine\matlabengine.py", line73, in__call__...
Here is the code. I do not understand what this code does. I read an image from opencv python, an it prints uint8. Do i have to specify the dtype parameter when calling get_symbol function? ''' def get_symbol(num_classes=1000, dtype='float32', **kwargs): ...
Tensor t is taken as an argument in flatten function and since reshape has to be done as the next part, -1 is passed as the second argument. The value should be based on the number of elements inside the tensor, and it equals the product of elements in the tensor. For example, if ...
Fixes AttributeError 'float' object has no attribute 'dtype' Pixel Classification Models Fixes issue where fit() retuns NaN values in the dice scores with data that has class values missing in the label files Fixes ValueError: Expected more than 1 value per channel when training when using ...
Imagine you're designing a new programming language and you decide to implement arrays in it; what does that mean they do? What will the properties and capabilities of those things be. If it depends on the type of language, how so? What makes an array an array? When is an array not ...
While some of the examples you see below may not be WTFs in the truest sense, but they'll reveal some of the interesting parts of Python that you might be unaware of. I find it a nice way to learn the internals of a programming language, and I believe that you'll find it ...
Foroutput1I have a feeling that it's a representation of the mask pixel-by-pixel of the original image with lower resolution than the input. I don't understand where the 32 channels come from. Does it mean that only 32 categories can be detected at the same time?
model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased") returns this warning message: Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertForSequenceClassification: ['cls...
python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)" b'v1.12.0-0-ga6d8ffa' 1.12.0 import tensorflow as tf import time # version 1 tic = time.time() elems = np.array(range(1,1000000), dtype=np.float64) output = tf.map_fn(lambda x: x**6 , elems, dtype=...